https://iwm.ilam.ac.ir/ Integrated Watershed Management en daily 1 Sat, 22 Nov 2025 00:00:00 +0330 Sat, 22 Nov 2025 00:00:00 +0330 https://iwm.ilam.ac.ir/article_721897.html Extended Abstract Introduction: Watershed degradation is a critical environmental issue with significant impacts on water resources, local  livelihoods, and ecosystem sustainability. These impacts include reduced water quality and quantity, soil erosion, decreased agricultural productivity, and disrupted ecological balance. The Ilam Dam watershed, affected by land-use changes, overexploitation of natural resources, and unsustainable human activities, has faced numerous challenges in recent years. This study aims to identify and assess the roles of human and environmental factors in the degradation of the Ilam Dam watershed. Materials and methods: To achieve this, the study began with a comprehensive review of scientific literature to understand the factors contributing to watershed degradation. Additionally, consultations with local experts and residents were conducted to incorporate their insights and experiences. Field research, on-site visits, and analysis of previous studies and reports were also integral to identifying degradation factors. Two main categories of factors were identified: environmental and human-induced. Environmental factors included climate change, physiography, geology (rock type), and tectonics, with a total of 12 indicators. Human-induced factors encompassed high population growth and migration, infrastructure and settlement development, livestock farming, and agriculture, with 25 indicators. These indicators reflect the impacts of agricultural activities, infrastructure development, and land-use changes driven by population growth. The Analytical Hierarchy Process (AHP) and Expert Choice software were used to weigh and prioritize these factors. Expert judgments were collected through questionnaires distributed to 10 experts and university faculty members, providing accurate weights for each factor and indicator. These results formed the basis for developing strategies and management solutions to mitigate degradation and enhance the health of the Ilam Dam watershed. Results and Discussion: The analysis revealed that climate change, with a weight of 0.550, was the most influential environmental factor contributing to watershed degradation. Among its indicators, drought (weight: 0.708) was the most critical, significantly affecting precipitation and water resources. In the physiography sub-criterion, steep slopes (weight: 0.723) were identified as a primary factor, increasing soil erosion and surface runoff. In geology, erosion-prone formations (weight: 0.708) accelerated soil erosion and land vulnerability. In tectonics, fracture density (weight: 0.731) reduced land stability and exacerbated degradation. Among human-induced factors, agriculture (weight: 0.566) was the most influential. Encroachment on natural resources and land conversion (weight: 0.337) were significant under high population growth and migration. The expansion of residential areas (weight: 0.651) was a key indicator in infrastructure development. Input consumption in livestock farming (weight: 0.416) and excessive water extraction in agriculture (weight: 0.395) also significantly impacted the watershed's natural resources and environmental health. These findings provide essential guidelines for planning and managing natural resources in the Ilam Dam watershed. Conclusion: This study highlights climate change and agriculture as the most significant environmental and human factors, respectively, driving the degradation of the Ilam Dam watershed. These findings underscore the need for improved natural resource management and sustainable strategies to mitigate these impacts. Comprehensive management programs are recommended to address climate change effects, enhance agricultural practices, and prevent further degradation. This research serves as a valuable guide for policymakers and managers in protecting and managing the Ilam Dam watershed effectively. https://iwm.ilam.ac.ir/article_720674.html Extended Abstract Introduction: The excessive exploitation of natural resources, driven by the unsustainable practices of human societies to meet growing population needs, has become a critical global issue, threatening the health and sustainability of watersheds. To mitigate these risks, effective management measures are essential to build resilient communities capable of withstanding natural events and disasters. Accurate quantification of ecological changes and the identification of key indicators for watershed management are crucial for promoting resilience and ecological sustainability. In this context, viability—defined as the ability of a watershed system to return to its resilience threshold—is a vital concept for assessing the restoration of health and sustainability. However, analyzing and evaluating viability requires a comprehensive understanding of the complex relationships among various variables. Despite its importance, no prior research has specifically addressed the assessment of watershed viability. Materials and methods: This pioneering study aims to evaluate the viability of the Shazand Watershed in Markazi Province, Iran, based on its hydroclimatic characteristics. The study began by calculating selected hydroclimatic variables, followed by statistical analyses to identify and remove less relevant variables. Resilience and release thresholds were then determined for the remaining variables. The viability index was prioritized by comparing current conditions with these thresholds. Finally, the overall viability of the watershed was assessed by calculating the geometric mean of the hydroclimatic variables. Results and Discussion: The modeling and zoning results revealed that the hydroclimatic viability index of the Shazand Watershed is 0.58, indicating an intermediate state. Notably, the prioritization of sub-watersheds using the viability method differs significantly from conventional estimation methods. While examining current conditions alone provides limited insights, comparing the variability of variables in resilient and release states with current conditions offers a more robust assessment. For instance, instead of taking management measures in sub-watershed 7 with high priority in the current conditions state, it is necessary to pay attention to sub-watershed 21 with viability, hydrological, and hydroclimatic priorities of 1, 4, and 1, respectively. Other high-priority watersheds include sub-watersheds 9, 20, 24, 16, 1, 11, and 15. The aforementioned sub-watersheds, especially 9, 20, and 11, are currently in good condition, but they have very low viability (high variability). Sub-watersheds 22, 5, and 4 are also among the sub-watersheds with high viability (low variability). By focusing on priority sub-watersheds, hydroclimatic conditions can be significantly improved, enhancing the stabilization of these areas. Key variables influencing viability include normal characteristic discharge and erosion rates, with industrial expansion in the region identified as a major driver of variability, particularly in sub-watersheds 3, 6, and 7. Conclusion: This study demonstrates that identifying resilience and release thresholds for variables and comparing them with current conditions can help bring critical sub-watersheds closer to their resilience thresholds, preventing system collapse. Given the complexity of watershed systems and the multitude of factors influencing their performance, a comprehensive assessment of viability, incorporating all relevant variables, is essential for effective watershed management. The integration of modern technologies can further enhance our understanding of resources and environmental dynamics, ultimately improving comprehensive watershed management practices. https://iwm.ilam.ac.ir/article_718948.html Extended abstract  Introduction: The phenomenon of climate change, as one of the main drivers of the increase in greenhouse gases, has a significant impact on extreme events such as floods and droughts. Therefore, investigating the impact of climate change on these extreme phenomena is crucial for the planning and management of water resources in the future. Drought, along with its effects on natural resources, agricultural production, and economic and social development, is one of the fundamental challenges facing both Iran and the world. Since drought impacts various sectors of society—such as water resources, agriculture, and industry—it is essential to monitor and assess this phenomenon both now and, in the future, to plan effectively across different sectors. Considering that previous research relied on only one AOGCM model, primarily using the fourth or fifth reports, this study utilizes five CMIP6 climate models while incorporating the sixth assessment report. This research, therefore, discusses drought forecasting under climate change conditions using five climate models and two emission scenarios at the Qaen synoptic station. Materials and Methods: In this research, five large-scale models were used: ACCESS-ESM1-5, CNRM-CM6-1, HadGEM3-GC31-LL, MRI-ESM2-0, and MPI-ESM1-2-L-R. Two emission scenarios, SSP5-8.5 (pessimistic) and SSP2-4.5 (intermediate), along with the LARS-WG statistical downscaling method, were applied. First, the LARS-WG model was evaluated using the basic data. After calibrating and validating the model, temperature and precipitation parameters were produced for the future period. Then, the SPEI and SPI drought indices were calculated and analyzed for the base period (1990-2020) and the future period (2025-2055). Results and Discussion: The bR² values for the minimum and maximum temperatures were 0.99, and the RMSE values for these temperatures were 0.308 and 0.384, respectively, indicating the high accuracy of the model in downscaling temperature. For precipitation, the bR² value was 0.74, and the RMSE was 4.001, showing the model's good performance in downscaling precipitation data for the base period. The amount of precipitation increased or decreased depending on the emission scenario and the month. The simulated average temperature in both scenarios shows an increasing trend compared to the base period. Based on the 12-month SPI index, the number of dry and wet months increased relative to the base period. Additionally, the number of normal months in the future period decreased compared to the base period in both the SSP2-4.5 and SSP5-8.5 scenarios. According to the SPEI index in both scenarios, the number of dry months in the future period decreased compared to the base period, while the number of wet months showed only a slight increase.Conclusion: The LARS-WG model demonstrated good performance in downscaling precipitation and temperature for the future period. The results indicate an increasing trend in average downscaled temperature in both scenarios compared to the base period. Precipitation varied depending on the scenario and month. Findings revealed that the frequency of wet and dry periods on a short-term scale (6 months) was higher than on a longer time scale (12 months), suggesting that as the time scale increases, the frequency of wet and dry periods decreases, while their duration increases. Furthermore, in the future period (2025-2055), the frequency of droughts is expected to decrease, but with increased duration compared to the base period. The number of dry months in the future period will be significantly reduced, while the number of normal and wet months will increase slightly. The most severe drought, characterized by high continuity, is predicted to occur from 2045 to 2055. https://iwm.ilam.ac.ir/article_719958.html Extended AbstractIntroduction: Social capital plays a significant role as a key factor in enhancing effective governance and sustainable development in rural communities. Additionally, microcredit funds have been introduced as one of the strategies to emphasize social capital in rural sustainable development projects. ​Therefore, assessing the impact of development and progress initiatives in rural areas, with a focus on enhancing the social capital of microcredit fund members, is of great importance. Hence, the present study examines the role of social capital among members of rural microcredit funds in the target areas of the rural development and improvement plan in Bakharz County's rural systems, utilizing social network analysis. The primary aim of this study is to identify the impacts of social capital on social relationships, local participation, and changes in governance regimes across four villages in Bakharz County. Materials and methods: The present study is a survey-based research that involves the collection of field data.​ Social network analysis was employed to examine the relationships among the local community members of microcredit funds in four villages: Arzaneh, Qaleh Now Aliyah, Nasratabad, and Nobahar Gholaman in the Bakharz County. İt also evaluate their social capital before and after the implementation of the rural development and improvement plan in the county (2023 and 2024). Data were collected through structured network analysis questionnaires, and sampling was carried out using the Krejcie and Morgan (1970) table, resulting in a total sample size of 181 individuals. Subsequently, the UCINET6 network analysis software was used to calculate macro-level network metrics, including network density, network centralization, reciprocity, link transitivity, and average geodesic distance. To analyze the dynamics of the land governance regime before and after the implementation of the rural development and improvement plan, two metrics- density and centralization- were used, and the governance regimes were identified and analyzed.Results and Discussion: The results showed that increasing social capital leads to improved social relationships and resilience of local communities. The findings indicate age and gender diversity in the studied communities, where the presence of young populations can be considered an advantage for social and economic development. However, gender inequalities and the lack of women's participation in development activities can pose serious challenges for good land governance in these communities. The increase in the network density index and the decrease in the average geodesic distance in this study indicate improved social conditions and increased information flow speed in rural networks after the implementation of the Abadani project and the advancement of rural systems, which helps the entry of new knowledge and innovation. Additionally, the change in the governance regime from a centralized, uncoordinated state to a multi-center system showed better power distribution and increased cohesion in the community. Identifying key actors in social networks and strengthening their cooperation can also improve the social and economic performance of communities and lead to a more effective transition towards good governance. These findings emphasize that social capital is a fundamental factor in improving governance and reducing social inequalities. Conclusion: The findings demonstrate that increased social capital following the implementation of the rural development and improvement plan in Bakharz County's four studied villages has not only contributed to improved governance but could also serve as a suitable model for other rural areas. Therefore, it is recommended that developmental programs in rural regions focus more on strengthening social capital to achieve good and sustainable land governance. Furthermore, the transition from a centralized governance regime to a polycentric one—recognized as the most efficient form of governance—stands out as one of the significant achievements of implementing the rural development plan due to enhanced participatory culture and power distribution among rural communities facilitated by microcredit funds. Special attention to empowering women and youth can further improve the social and economic conditions within these communities. https://iwm.ilam.ac.ir/article_719959.html Extended Abstract Introduction: Natural resource management is considered the foundation of sustainable development. Therefore, in a country like Iran, located in the water-stressed and tense region of the Middle East, water resource management is of paramount importance. Knowledge of temporal changes in baseflow is crucial for effective water resources management. Identifying the most suitable and optimal method for hydrograph separation and baseflow estimation enables the accurate calculation of the baseflow index. Materials and methods: In this study, nine recession filter algorithms were used to estimate baseflow. These algorithms include Local Minimum, Sliding Interval, Fixed Interval, Eckhardt, Chapman, Chapman & Maxwell, Lyne & Hollick, Furey & Gupta, and Boughton. Using these algorithms, daily baseflow was calculated for the Kashkan watershed using daily discharge and rainfall data from 1999 to 2020. The Kakareza, Sarab Seid Ali, Cham Anjir, Afrineh, and Pol-e-Dokhtar stations were investigated to separate baseflow in the Kashkan watershed. The performance of the methods for separating baseflow in the hydrograph of the Kashkan watershed was assessed using the Nash-Sutcliffe efficiency (NSE) coefficient and the R² coefficient to select the most suitable filtering method. Results: Among the recession algorithms examined, the Furey & Gupta method estimated the lowest baseflow for all five sub-watersheds. In the Afrineh sub-watershed, the Lyne and Hollick, Fixed Interval, and Sliding Interval methods estimated baseflow as 36.41, 30.11, and 29.7 m3/s, respectively. These methods attributed 85%, 82%, and 81% of the total flow to groundwater contributions. In the Cham Anjir sub-watershed, the highest annual average baseflow values were obtained using the Lyne & Hollick, and Local Minimum methods, with values of 7.22, and 6.24 m3/s, respectively. The variation in mean baseflow among different methods in the Cham Anjir sub-watershed ranged from 17% to 94%. For the Kakareza sub-watershed, the highest annual average baseflow values were observed using the Lyne & Hollick, and Sliding Interval methods, with values of 9.70, and 9.72 m3/s, respectively. The variation in mean baseflow among different methods in the Kakareza sub-watershed ranged from 17% to 95%. Similarly, in  the Pol-e-Dokhtar sub-watershed, the highest values were obtained using the Lyne & Hollick, Fixed Interval, and Sliding Interval methods, with values of 36.10, 34.40, and 34.40 m3/s, respectively, and variations ranging from 17% to 99%. In the Sarab Seid Ali sub-watershed, the Lyne & Hollick, Fixed Interval, and Sliding Interval methods yielded the highest annual average baseflow values of 5.97, 5.95, and 5.94 m³/s, respectively, with variations ranging from 17% to 92%. Based on the findings and evaluation criteria, the Local Minimum, Lyne & Hollick, Sliding Interval, and Fixed Interval methods were identified as suitable for baseflow separation in the studied sub-watersheds. Discussion: Baseflow in the Kashkan watershed of Lorestan constitutes a significant portion of the flow. In the majority of the methods examined in this study, it was also shown that baseflow accounts for more than 50% of the streamflow throughout the year. In all studied sub-watersheds, the Lyne and Holick algorithm showed suitable values for the NSE coefficient and R². Therefore, this algorithm can be considered an appropriate method for estimating baseflow in the Kashkan watershed. Considering the hydrological characteristics of the watershed, this method can better simulate the natural fluctuations of baseflow.Conclusion: The results of this study can inform baseflow contribution estimates and help in selecting appropriate methods for flow separation in the hydrological modeling of rivers with varying discharge ranges in the Kashkan watershed. The present research focused on differentiating water sources in the Kashkan watershed using digital filtering methods. Future studies are recommended to explore other approaches, such as chemical methods and tracers, for water source differentiation in the Kashkan watershed, and to compare the accuracy of these methods with digital filtering techniques. https://iwm.ilam.ac.ir/article_721593.html Extended AbstractIntroduction: Groundwater resources in border areas have often been overlooked by managers and policymakers due to challenges such as wide geographical spread, and the high costs associated with their study. However, it is crucial to inform decision-makers about the potential of these resources to address water scarcity issues. In the border areas of Razavi Khorasan Province, many farmers and ranchers lack access to sufficient water for agriculture and livestock. Constructing underground dams in these regions can help store significant portions of subsurface water flow in alluvial reservoirs, making it available for use when needed. This study aims to identify and prioritize suitable sites for subsurface water harvesting using underground dams in the border areas of Kalat and Sarakhs in Khorasan Razavi Province. Materials and methods: In this study, Boolean logic was used to eliminate areas unsuitable for underground dam construction. Five criteria—slope, geology, land use, distance from villages, and distance from roads—were employed to locate potential sites. The Fuzzy-AHP method was then used to weight these factors and identify susceptible areas. To prioritize the proposed sites, the Data Envelopment Analysis (DEA) method was applied. DEA, a linear programming-based technique, categorizes suggested points into effective and ineffective categories based on inputs such as dam construction costs, watershed area, precipitation, water demand, and water supply costs. The output considered was the estimated volume of harvested water. Results and Discussion: The results indicate that 58.6% of the study area is unsuitable for underground dam construction, demonstrating the effectiveness of Boolean logic in reducing the workload of site selection. The Fuzzy-AHP analysis revealed that geology and slope are the most influential factors, with weights of 0.395 and 0.268, respectively, while land use and distance from roads have the least impact, with weights of 0.07 and 0.097, respectively. Slopes of 0–3% were found to be most suitable due to minimal water flow velocity, which facilitates the creation of effective reservoirs. Pasture land use was identified as ideal for dam construction. Approximately 6.8% of the area has very high potential, and 11.7% has high potential for underground dam construction. Using DEA, seven priority sites were identified for further investigation. Conclusion: The study concludes that: (1). Farmers and ranchers in the border areas of Khorasan Razavi Province, located on alluvial plains near dry rivers, lack access to sufficient water resources. Constructing underground dams can store significant groundwater flows in alluvial reservoirs, providing a reliable water source for agriculture and livestock. (2). Building underground dams in border areas can create employment opportunities, increase the working population, and enhance regional security. This, in turn, will boost the income and satisfaction of local residents. (3). Eliminating unsuitable areas for dam construction simplifies analysis, reduces fieldwork, and lowers costs. (4). The use of DEA for prioritizing dam construction sites represents a novel approach, offering a new perspective on site selection techniques. https://iwm.ilam.ac.ir/article_722905.html Extended abstractIntroduction: The Zagros forests, one of the largest and most significant vegetation zones in Iran, play a vital role in sustaining natural resources and environmental stability. These forests provide critical ecosystem services, including groundwater recharge, soil erosion reduction, climate regulation, biodiversity conservation, and socio-economic benefits. Among the dominant species, Quercus brantii (Persian oak) holds a crucial position, widely distributed across the Zagros forests. However, this species has become highly vulnerable and is at risk of extinction due to threats such as overexploitation, habitat destruction, and climate change. This study aims to model the distribution of Quercus brantii using the maximum entropy (MaxEnt) method, evaluate the influence of various environmental factors on its distribution, and produce an optimal distribution map for the species in Holilan County, Ilam Province. The findings will support targeted conservation strategies and sustainable management of Zagros forests. Materials and Methods: To model the distribution of Quercus brantii in the forests of Holilan County, Ilam Province, the MaxEnt method was employed. For model development, 75%  of the data (89 pints) were randomly selected as training data, and the remaining 25% (30 points) were used as test data for independent model evaluation. The maximum number of background points was set to 10,000 with 15 repetitions. Nineteen climatic variables, three physiographic variables (elevation, slope, aspect), and snow cover data were utilized. Initially, the desired environmental layers were prepared using ArcGIS software, and then the MaxEnt model was used to assess the species’ current and future (2050-2070) distribution. Model performance was evaluated using the Receiver Operating Characteristic (ROC) curve and the Area Under the Curve (AUC) metric. Results and Discussion: The evaluation of the modeling accuracy based on the ROC curve showed that the model's accuracy was at an excellent level (AUC = 0.947). The model identified annual temperature, mean monthly temperature, isothermality, annual precipitation, and elevation as the most influential variables, collectively explaining 58% of the distribution variance. Suitable habitats for Quercus brantii covered 7,067 hectares (excellent potential) and 10,779 hectares (good potential), while 54,750 hectares showed low-to-moderate suitability. The species primarily occurred at elevations between 1,000–2,339 meters, with higher prevalence on southern, eastern, and southeastern slopes. Presence peaked at slopes up to 25%, beyond which habitat suitability declined. Conclusion: The overall findings of this study highlight the significant role of variables such as annual mean temperature, mean monthly temperature, isothermality, annual precipitation, and elevation in modeling the distribution of Quercus brantii. The species is predominantly distributed in southern aspects and at elevations ranging from 1,000 to 2,339 meters above sea level. This research provides valuable insights into the ecological tolerance range of Quercus brantii in relation to environmental variables, which can serve as a scientific basis for management decisions. The information obtained is not only effective for prioritizing protected areas and implementing conservation and restoration measures but also enhances the success rate of plantation and rehabilitation projects, aiding in the preservation and development of this species in vulnerable regions. https://iwm.ilam.ac.ir/article_722906.html Extended AbstractIntroduction: Rangelands are one of the most vital bases for the continuation of life and sustainable development and the most basic production factor in traditional livestock systems. The expansion of production activities and population growth on the one hand, and the collapse of the traditional comprehensive rangeland management system on the other, have created an unfavorable situation in the rangelands. Today, with population growth and need for food, the necessity of sustainable use of rangelands is of great importance in the process of sustainable development. Undoubtedly, this necessity demands that its use in development programs be continuously. Since management is one of the most important factors in the productivity of rangelands and most of the country's rangelands are exploited by nomads, these areas require proper management with the aim of preserving, revitalizing, developing, and optimal exploitation. Therefore, designing a model of sustainable management of nomadic rangelands in Kermanshah Province is essential. Therefore, this research seeks to answer the question, what are the components and dimensions of the sustainable management model of rangelands under grazing by nomads in Kermanshah Province? Materials and methods: The present qualitative study is applied research in terms of its purpose, which was conducted using the grounded theory method. The statistical population of the study was specialists and experts in the field of animal husbandry, environmental protection, rangelands, and nomads of Kermanshah province, of whom 13 were interviewed using purposive sampling, and theoretical saturation was achieved. Data analysis was performed in the form of conventional content analysis using MAXQDA software. The results were coded in three stages: open, axial, and selective coding. In the open coding stage, 29 key concepts were identified. At the end of the coding stages, a sustainable management model for nomadic rangelands was extracted using the paradigm model. Results and Discussion: Based on the research findings, in the paradigm model, the education and research system, scientific and technical management of rangelands and forests, the executive system and the development of nomadic capacities were identified as the components of the central category. Economic, governmental, individual and cultural factors were identified as causal conditions; factors related to the rangelands and factors related to the users as contextual conditions; and natural and human factors as intervening conditions. Also, based on the results, fundamental factors and innovation were identified as strategies, and employment creation, promotion of management performance and improvement of production were the outcomes of implementing the sustainable management model of nomadic rangelands. Conclusion: This study presents a paradigmatic model demonstrating how sustainable nomadic rangeland management is shaped by livelihood conditions, contextual factors, and policy interventions. If implemented with consideration for nomadic lifestyles and ecological conditions, the model can enhance pasture sustainability and productivity. The findings are valuable for the General Office of Nomad Affairs, Natural Resources Organization, Veterinary Organization, and Nomad Cooperative Union in policymaking and rangeland management. https://iwm.ilam.ac.ir/article_719879.html Extended Abstract Introduction: Rangelands, as renewable natural resources, play a vital role in environmental preservation and in meeting the needs of both livestock and vegetation. These resources not only provide forage for livestock but also protect soil and water. However, unplanned land-use changes and degradation of vegetation cover in Iran, especially over the past four decades, have led to a decline in the quality of these resources. Factors such as population growth, urbanization, and overgrazing by livestock have contributed to rangeland degradation. In this context, remote sensing (RS) and geographic information systems (GIS) are efficient tools for monitoring these changes. These technologies enable precise monitoring of environmental changes and the identification of factors such as soil salinity and erosion without the need for costly traditional methods. The use of satellite data provides valuable insights for assessing vegetation cover changes, drought impacts, and other environmental threats. Therefore, these tools play a significant role in natural resource management and rangeland conservation.Materials and Methods: This study focuses on the Jiransu winter rangeland in the Maneh and Samalqan district, covering an area of 2,168 hectares. Located in northwestern Iran, the region has a cold and dry climate with an annual rainfall of 223 mm. To analyze vegetation cover changes, Landsat time-series images (TM and OLI) and Google Earth images were used. Satellite images with a spatial resolution of 30 meters were collected from different years (1997, 2002, 2008, 2013, 2018, and 2023) from the US Geological Survey (USGS) archive. After data preprocessing to ensure quality and correct geometric and radiometric errors, the images were processed using various techniques such as histogram adjustment and color composite for information enhancement. NDVI and MSAVI vegetation indices were employed for vegetation analysis. Subsequently, vegetation cover changes were analyzed using image differencing and threshold classification methods.Results and Discussion: The results revealed that during the analyzed time periods, the lowest vegetation index values were observed in 2008, coinciding with a severe drought in Iran. This reduction in vegetation cover highlights its strong dependence on rainfall and climatic conditions. Land-use changes showed similar trends, particularly during the 1997–2008 period, where approximately 226 hectares of poor rangeland were lost, representing 10% of the total rangeland area. In the subsequent period (2008–2013), approximately 323 hectares of poor rangeland decreased, with declining classes covering more than 14% of the area. These findings indicate that RS methods, particularly those using vegetation indices, are efficient and accurate tools for monitoring vegetation changes and assessing rangeland conditions. Overall, the study emphasizes that satellite images and vegetation indices like NDVI and MSAVI offer significant accuracy in detecting ecological changes and trends, especially in dry and semi-arid regions, compared to traditional methods. Conclusion: This study emphasizes the importance of NDVI and MSAVI indices in monitoring vegetation cover changes and demonstrates that these indices can effectively track degradation trends and environmental changes. These indices, particularly in dry and semi-arid regions impacted by climate change and drought, play a key role in modeling vegetation decline and rangeland productivity. Furthermore, the results suggest that using these indices, due to their ability to correct for bare soil effects and their effectiveness in assessing vegetation changes, provides valuable tools for rangeland monitoring and management. These tools can aid in identifying degraded areas and, by providing timely and accurate data, help predict and manage rangeland degradation. Therefore, integrating these indices into comprehensive natural resource management programs and utilizing them in detailed environmental assessments can play a crucial role in enhancing conservation efforts for natural resources. Additionally, their application can have a profound impact on the restoration and improvement of ecosystem health, leading to long-term environmental sustainability. https://iwm.ilam.ac.ir/article_723444.html Extended Abstract Introduction: Achieving sustainable development requires transforming society-nature interactions into synergistic relationships. Effective governance of natural resources, particularly rangelands, requires collaboration and consensus among stakeholders to ensure the adaptability and sustainability of these ecosystems. Social capital, particularly trust and social participation, plays a crucial role in the successful participatory management of common-pool resources. In this context, social network analysis emerges as a valuable tool for identifying relationships and interactions among actors, facilitating the flow of information, and enhancing the effectiveness of management initiatives. This study analyzes social capital in rangeland governance across three customary jurisdictions in Tafresh County, focusing on social network structures and key actors. Materials and methods: This study investigates the social relationships among rangeland users in three customary rangeland management units—Ahmadabad, Fark, and Nobahar—located in Tafresh County. Data were collected via full-network social network analysis (SNA). A Likert-scale questionnaire assessed trust and participation ties among 33 rangeland users. Data analysis was performed using UCINET software, applying key network metrics such as degree centrality, betweenness centrality, closeness centrality, and structural holes to identify key actors and analyze their relationships. The findings highlight influential actors within each rangeland management unit and their role in facilitating information flow, enhancing participation, and improving rangeland governance. This study provides a deeper understanding of the social structure of rangeland users and its implications for sustainable rangeland management. Results and Discussion: SNA revealed significant differences in social network structures across Ahmadabad, Fark, and Nobehar, particularly in participation, trust, and key actors' roles. The findings identified the central actors in each rangeland unit’s social network and their influence on cooperation and information exchange. In Ahmadabad, the actor BH-AG, with the highest in-degree centrality, was recognized as a key player in receiving information and facilitating collective decision-making. Meanwhile, the actor HS-SD, with high out-degree centrality, demonstrated strong social influence and effective communication within the network. These results suggest that empowering these actors could enhance the adaptability of rangeland management and facilitate collective decision-making. Fark’s homogeneous network metrics suggest limited innovation in relationship-building. In Nobahar, the actor ZY-KH emerged as the most influential player, while the participation and trust metrics reflected a complex and diverse network structure. Conclusion: In Fark, there exists a strong foundation of trust and relationships among stakeholders that facilitates effective collaboration and participation. This network represents the most successful instance of collaborative governance, characterized by high levels of participation and transparency in decision-making; however, there is a pressing need for innovation. In Nobahar, the trust and willingness to participate among stakeholders are also robust, fostering a sense of responsibility through established processes. Nonetheless, empowerment programs must enhance natural resource management. In contrast, Ahmadabad faces challenges related to the relationships and trust among stakeholders, which negatively impacts cooperation. Enhancing transparency and empowering stakeholders through educational initiatives and workshops is crucial. Fark exemplifies successful collaborative governance; Nobahar shows promise, while Ahmadabad lags in social participation and trust. Strengthening these social dimensions across all jurisdictions has the potential to significantly enhance natural resource management and collaborative governance. https://iwm.ilam.ac.ir/article_724391.html Extended AbstractIntroduction: A watershed system regulates both the quantity and quality of water within the hydrological cycle. Challenges have arisen in managing this cycle, largely due to insufficient understanding of its complexity and inadequate planning regarding the interconnections between water resource management and community development. Effective watershed management requires comprehensive and accurate information on various technical and managerial approaches. Simulating hydrological processes within a watershed is considered a promising approach for achieving optimal management. This study aims to develop and evaluate a new rainfall-runoff model for the Meymeh Watershed as a mountainous watershed located in a semi-arid region of Ilam Province, Iran.Materials and methods:  This study was conducted using the new SWAT+ model. SWAT+ is a powerful tool for achieving watershed management objectives, offering a flexible spatial representation of basin processes and responses. It integrates a large number of parameters, utilizes the free QGIS software, and features a robust graphical interface.The data required for this research include meteorological records from the watershed and its surrounding areas, historical flow data of the Meymeh River, a Digital Elevation Model (DEM), and geological and soil maps. Meteorological data were collected from two synoptic stations near the watershed and 20 rain gauges located within and around the watershed, sourced from governmental organizations. Historical and observed daily flow data from a hydrometric station at the watershed outlet were also obtained from existing databases.Daily meteorological and hydrological data from 2010 to 2020 were used to simulate streamflow in the study area. Considering that using multiple statistical indicators can lead to mixed interpretations of model performance, in this study were employed the coefficient of determination (R²), Nash–Sutcliffe Efficiency (NSE), Mean Absolute Error (MAE), and Mean Bias Error (MBE) to evaluate the accuracy and reliability of the model.Results and Discussion: Based on the results, NS, R2 coefficients, MAE and MBE were obtained -0.38 , 0.39, 11.1 and 8.4 respectively, using non-optimized coefficients using in the initial run of the model. According to the value of the objective functions in the first run, it was found that the SWAT+ model has insufficient accuracy for the watershed runoff simulation, so the calibration operation is necessary to improve its accuracy. For calibration, ten coefficients and parameters that are effective in producing watershed runoff were determined. These parameters were entered into the model along with the allowed range of their changes (Theoretically) and were real and optimized during 2000 iterations. Following this process, the R2, Nash-Sutcliffe coefficients, MAE and MBE for the calibration period (2010-2018) were obtained 0.72, 0.70, 2.97 and 0.58 respectively, and for the validation period (2019-2020), 0.78, 0.77, 7.6 and 0.38 respectively. In order to evaluate the ability of the model in simulating base and peak flows and also checking their temporal consistency with the observed data, scatter plots and time series of observed and simulated daily flow values were drawn for the calibration and validation periods. A detailed review of the drawn graphs showed that this model has correctly identified the time of the peak flows. Also, the daily fluctuations of the river flow are correctly modeled. From a graphical point of view, the comparison of the time series plots during the validation period shows that the SWAT+ model estimated the peak and base flows close to the actual values.Conclusion: The results of this study showed that SWAT+ has a good ability to simulate of daily runoff in The Meymeh river watershed. It can also  be applied to simulate runoff under different  https://iwm.ilam.ac.ir/article_724408.html Extended Abstract Introduction: The SWOT model easily assesses the strengths, weaknesses, opportunities, and threats in a watershed and provides solutions that are consistent with the realities and capabilities of the watershed. This model is one of the group decision-making models designed to determine long-term or short-term strategies and to make major decisions and various issues and topics. To this end, this study identified and prioritized strategies for management in the Tanghebostanak watershed, located in the northwest of Fars Province, using the integrated SWOT-QSPM model. Materials and methods: Field surveys were conducted to identify strengths, weaknesses, opportunities, and threats (SWOT). Through multiple meetings and brainstorming sessions with 24 subject-matter experts, both internal and external factors were identified, and a SWOT matrix was constructed. Management strategies were then developed based on these factors. The relative importance of each factor was assessed using the AHP. Internal and external factor scores were determined using a five-point Likert scale questionnaire, completed by two groups: experts and local watershed residents. The questionnaire's validity was confirmed by a panel of experts after finalizing the SWOT matrix. Responses were categorized using ordinal variables aligned with the Likert scale. The statistical population included 24 experts and 35 informed local residents. The reliability of the questionnaire was assessed using Cronbach’s alpha. Weighted scores were calculated, the strategic position of the watershed was determined, and the overall attractiveness of each strategy was evaluated to prioritize management strategies. Results and Discussion: A total of 14 internal factors (7 strengths and 7 weaknesses) and 10 external factors (5 opportunities and 5 threats) were identified, resulting in 12 strategies: 3 aggressive (SO), 3 conservative (WO), 3 competitive (ST), and 3 defensive (WT). Among these, "suitable soil" (S2) with a weighted score of 1.2 was identified as the most significant strength, while "soil erosion caused by human activities" (W2), scoring 1.044, was the most significant weakness. The most notable opportunity was "the willingness of surrounding counties to develop nature tourism" (O3), with a score of 1.35. Conversely, "complex and time-consuming administrative procedures for land transfer" (T5), with a score of 0.944, emerged as the most critical threat. The total weighted scores were as follows: strengths (3.383), weaknesses (3.317), opportunities (3.66), and threats (3.225). Internal and external factor scores were 0.066 and 0.435, respectively. These results highlight the dominance of strengths over weaknesses and opportunities over threats, indicating the need for a balanced approach incorporating all four strategic types. The results of the QSPM in prioritizing strategies indicate that strategies SO3 (beekeeping development), ST3 (improvement of agricultural production insurance services), and WT2 (long-term transfer of national lands for the development of tourism, medicinal plants, and beekeeping), with overall attractiveness of 20.296, 18.515, and 18.238, respectively, are the best strategies for managing the Tanghebostanak watershed in Fars province. Conclusion: Supporting new economic activities in the watershed is essential. This support should include raising public awareness, providing financial assistance, insuring emerging services, securing land, and simplifying bureaucratic processes. Since rangelands dominate the watershed’s landscape, their restoration—particularly through proper grazing management—can significantly reduce soil erosion and landslides. Participatory watershed management is crucial for coordinated efforts among relevant institutions, mitigating fragmented governance. It is strongly recommended that policies prioritize the long-term lease of national lands, legal reforms, and facilitation measures to promote tourism, medicinal plant cultivation, and beekeeping. Additionally, protecting rangelands and preventing land-use change should be high on the agenda. Educating residents about the importance of watershed management, building their capacity for implementation and stewardship, and fostering collaboration with local cooperatives are among the key strategies for sustainable development in the Tanghebostanak watershed. https://iwm.ilam.ac.ir/article_724554.html Extended Abstract Introduction: Although numerous studies have investigated the relationships between soil moisture and various environmental and climatic variables, the spatial relationship between soil moisture and these variables has not yet been fully identified. This is primarily because traditional statistical methods present parameter values as averages across the study area, thereby ignoring spatial variations in the relationships between soil moisture and independent variables. To overcome this limitation, it is necessary to use an appropriate spatial analysis approach. In this context, spatial statistical methods such as Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) can be employed to model spatial relationships between different variables. The Halilrud Basin is a key agricultural region in Kerman Province, Iran, with the local economy heavily dependent on crop production. Soil moisture is a critical factor affecting agricultural drought. Therefore, this study aimed to estimate soil moisture in the Halilrud watershed using field observations and laboratory analyses, and to evaluate its spatial relationship with remotely sensed indices—specifically the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST)—using OLS and GWR models. Material and Methods: Soil moisture measurements were taken in the plains of the Halilrud watershed using a TDR device at a depth of 30 cm across 72 sampling points in May 2019. To prepare NDVI and LST maps, Landsat 8 (OLI) and MODIS (MOD11A1) satellite images from May 2019 were acquired and preprocessed. The NDVI and LST indices were then extracted. To assess the spatial relationship between soil moisture and each independent variable (NDVI, LST) as well as their combination, both GWR and OLS regression models were applied. Results and Discussion: The results showed that the GWR model outperformed the OLS model based on evaluation criteria. The GWR model yielded R² values of 0.28 for LST, 0.44 for NDVI, and 0.58 when both variables were combined, indicating improved model performance. Additionally, the GWR model demonstrated higher efficiency across all scenarios due to lower AICc values and higher local and adjusted R² values. While the OLS model indicated a general correlation between soil moisture and the independent variables, the GWR model revealed that this relationship varies spatially. In particular, the northern regions of the watershed exhibited a stronger correlation between soil moisture and the independent variables. This spatial variability illustrates the advantage of the GWR model, which accounts for local variations in the relationships, unlike the OLS model that assumes a uniform relationship across the study area. Conclusion: The maps generated in this study can be used to identify areas with significant increases or decreases in soil moisture, which is valuable for decision-making, watershed management, and irrigation planning in the agricultural sector. The methodology and objectives applied here can be extended to other watersheds, offering practical and research value. For future studies, it is recommended to include additional independent variables—such as topographic features and other satellite-derived indices—to identify the most influential factors affecting soil moisture. https://iwm.ilam.ac.ir/article_724821.html Extended Abstract Introduction: Effective management of critical resources such as water, energy, and food is essential due to their strong interdependence—changes in one sector often impact the others. Rapid population growth, economic development, and escalating climate change are intensifying challenges in resource management worldwide. The Water-Energy-Food (WEF) nexus framework has emerged as a comprehensive approach to address these complexities by integrating environmental, social, economic, and political dimensions. This framework is especially relevant for arid and semi-arid regions like Iran, where water scarcity exerts considerable pressure on local governance systems. Qeshm Island, the largest island in the Persian Gulf, exemplifies the difficulties of managing the WEF nexus under such constraints. Fragmented policymaking and weak coordination across water, energy, and food sectors on the island highlight the urgent need for integrated management strategies and stronger inter-sectoral cooperation. This study aims to analyze and evaluate the governance structure of the WEF nexus on Qeshm Island using Social Network Analysis (SNA). The goal is to provide a comprehensive understanding of institutional interactions and identify opportunities for enhancing sustainable resource management in the region. Materials and Methods: This research adopts a descriptive-survey design with an applied focus on examining the governance network of the WEF nexus on Qeshm Island through SNA. The study investigates inter-organizational relationships across the water, energy, and food sectors by collecting primary data via 123 questionnaires distributed equally among sector experts and officials. Additionally, document reviews and field visits complemented data collection efforts. Network data were analyzed using UCINET6 software, focusing on key metrics such as network density, reciprocity, transitivity, centralization, average geodesic distance, and core-periphery structure. This approach allows for an in-depth assessment of the governance network, revealing institutional dynamics and pinpointing areas requiring policy and management improvements. The findings provide a foundational basis for developing integrated and effective governance frameworks for the island’s critical resources. Results and Discussion: Analysis reveals significant governance challenges within Qeshm Island’s WEF nexus. The overall low network density indicates limited collaboration and underutilization of institutional capacity. Among the sectors, the energy network showed the highest density, suggesting better coordination, whereas the food network exhibited the lowest density, highlighting critical weaknesses in collaboration. Reciprocity scores were moderate, demonstrating some mutual communication among stakeholders; however, weak transitivity—particularly in the food sector—suggests a lack of sustained tripartite interactions necessary for cohesive governance. Centralization measures revealed that governance is highly concentrated around a few key organizations, with the food network showing the greatest centralization, potentially restricting the system’s adaptability. The high average geodesic distance points to slow information and resource flows, especially within the food network, further impeding effective governance. Core-periphery analysis identified two central institutions—the Qeshm Free Trade Zone Organization and the Governor’s Office—as dominant nodes facilitating inter-sectoral linkages. These results collectively indicate that despite some institutional interactions, the governance structure remains fragmented and inefficient. Conclusion: This study highlights the institutional strengths and weaknesses within the water, energy, and food governance networks on Qeshm Island through rigorous network analysis. While there is some collaboration, significant opportunities exist to improve coordination and cohesion among stakeholders. Enhancing inter-sectoral communication, broadening stakeholder participation, and adopting integrated governance approaches are crucial to increasing the sustainability and resilience of resource systems on the island. The prominent role of the Qeshm Free Trade Zone Organization underscores the potential of leveraging key institutions to strengthen weaker sectors, notably the food network. Moreover, considering informal relationships and the influence of macro-level policies—both national and international—will be essential for a more comprehensive understanding of governance challenges and opportunities. Future research should also explore the role of non-state actors in this nexus. Ultimately, reforming governance structures and fostering stronger institutional cooperation is vital for the sustainable management of water, energy, and food resources in Qeshm Island, and these findings offer actionable insights for policymakers aiming to address complex resource challenges in similar contexts. https://iwm.ilam.ac.ir/article_725255.html Extended Abstract  Introduction: : By 2050, the global population is projected to reach approximately 9.2 billion. This growth, coupled with global and environmental changes, will significantly impact people's lives. To address these challenges, it is essential to adopt approaches that demonstrate how these changes exert their influence and to propose adaptive solutions. Sustainability and sustainable development play a crucial role in the conservation and restoration of natural resources; however, anthropogenic pressures and improper management pose serious threats to these resources. Sustainable management necessitates the identification of all stakeholders and their active participation in decision-making processes to establish a systemic and comprehensive perspective for the optimal protection and utilization of natural resources. Accordingly, the analysis and identification of the natural resource governance system approach in Khash County, located in Sistan and Baluchestan Province, is considered a vital issue in the natural resource management and sustainable development of this region. Effective natural resource governance implies creating an efficient management system wherein all stakeholders, including the government, local communities, and the private sector, actively participate in the decision-making process. This approach not only contributes to improving the condition of natural resources but also lays the groundwork for strengthening civil society and enhancing transparency and accountability in resource management. Therefore, the identification and analysis of good governance indicators are of particular importance. This research was conducted to identify the modes of natural resource governance in Khash County. Materials and methods: To investigate natural resource governance modes, 11 formal institutional stakeholders were selected from four villages: Eslamabad Poshtkuh, Esmailabad Garanjin, Butegan, and Bilariy Poshtkuh. Data were collected via a questionnaire comprising ten factors introduced by Poul Westel in 2001, with each factor measured by three indicators. Data analysis was performed using SPSS software. Subsequently, in the next phase, the desired strategy was analyzed and formulated using the QSPM Matrix. The study population for this phase consisted of 45 experts and managers from the Natural Resources and Agriculture-Jihad departments of the county, from whom 17 individuals were purposively selected. Result and Discussion: The results indicate a significant difference among the governance indicators. Among the 10 sub-functions, legitimacy, policy framing, knowledge generation, and resource mobilization were ranked first to third, respectively. In the sub-functions of rulemaking, knowledge generation, resource mobilization, and comprehensiveness, the hierarchical governance mode showed a significant difference compared to the other two investigated governance modes.  In the other sub-functions of rulemaking, monitoring and evaluation, legitimacy, and leadership, the market-based governance mode exhibited a significant difference compared to the other two modes. Furthermore, only in the sub-function of conflict resolution did the network governance mode attain the first priority. The QSPM matrix results demonstrate that among the proposed strategies, strengthening stakeholder participation through the establishment of participatory and network frameworks in decision-making processes holds the highest attractiveness. Conclusion: The research findings indicate that the dominant governance method in the studied villages relies more on hierarchical and market-based structures, which can lead to inefficiency in natural resource management. Therefore, to improve the current situation, it is recommended that the governance system incorporate the positive elements of both (and implicitly, all three, including network) approaches to establish a more effective natural resource governance framework. https://iwm.ilam.ac.ir/article_725314.html Extended Abstract Introduction: Wind erosion is a critical environmental issue and a major barrier to development in arid and semi-arid regions. This destructive process causes considerable ecological damage by stripping away topsoil, reducing land productivity, and increasing dust and sandstorm occurrences. Vegetation cover, soil stability, and surface roughness are among the key factors influencing wind erosion. The Sistan region, characterized by flat topography and long-term drought, experiences severe wind erosion due to the degradation of vegetation cover. This leads to frequent dust storms, further disrupting the ecosystem. To combat these effects, the construction of contour furrows for rainwater harvesting has proven effective. These furrows increase soil surface roughness and enhance water retention, creating favorable conditions for vegetation establishment and ecological restoration. Materials and Methods: This study was conducted in a flat area with approximately 0.5% slope and sparse vegetation, located west of Lake Hamun. Furrows measuring 40 cm in depth and 50 cm in width were constructed along horizontal lines, each 90 meters long. Seeding was conducted inside the furrows. The experimental design included three variables: precipitation storage location (inside the furrows, between the furrows, and a control area without furrows), sampling season (beginning and end of the rainy season), and year (first and second year). Each treatment was replicated four times. Vegetation characteristics, including plant height, canopy cover, bare soil percentage, and plant vitality, were assessed using 90-meter transects and quadrat sampling. Soil samples from each treatment zone were analyzed for their hydrological classification based on the SCS (Soil Conservation Service) method. Data were statistically analyzed using ANOVA in SPSS software to evaluate treatment effects. Results and Discussion: Statistical analysis revealed that the location of precipitation storage and sampling season significantly affected plant height and canopy cover (P<0.05). Vegetation indicators improved markedly within the furrows during the second year, especially after rainfall. Plant vitality assessment showed that 54% of plants in the furrows had high vitality (first degree), 40% moderate (second degree), and only 6% low vitality (third degree). In contrast, in the control area, 73% of plants exhibited low vitality and 27% moderate vitality, with no high-vitality plants observed. Soil infiltration capacity also improved significantly in the furrowed areas. While infiltration rates in the control zone ranged from 0.3 to 1 mm/hour, they increased to between 1.3 and 3.8 mm/hour in furrowed zones. This improvement enhances water availability in the root zone, increasing soil moisture and thereby creating a suitable environment for plant growth and stabilization of the soil surface. Conclusion: This study demonstrates that contour furrows are an effective technique for vegetation restoration and soil conservation in wind-eroded, arid environments such as the western area of Lake Hamun. By improving infiltration and increasing soil moisture, furrow construction facilitates vegetation establishment and resilience. Given the region’s limited precipitation, high evaporation rates, and compact soil layers, furrows represent a practical and low-cost solution for managing water resources and combating desertification. Their application can greatly enhance the effectiveness and sustainability of restoration efforts in degraded arid lands. https://iwm.ilam.ac.ir/article_725315.html Extended Abstract Introduction: Flooding is one of the most common and destructive natural hazards worldwide, with numerous economic, social, and environmental consequences. In fact, one-third of the costs associated with natural disasters are related to floods. Floods occur when river flow exceeds its carrying capacity, which can result from factors such as intense or prolonged rainfall, frozen ground during precipitation, sudden snowmelt, deforestation, river blockage, and dam failure. In Iran, poor economic conditions and the inability of livestock owners to provide sufficient forage have led to overgrazing, which exacerbates soil erosion and increases flood risk. Rainfall is a key factor in flood occurrence, exhibiting significant spatial and temporal variations influenced by elevation, slope, soil characteristics, land use, and geology. The concept of the Hydrological Response Unit (HRU) is a widely used approach in hydrological modeling. Therefore, defining and measuring key hydrological response indicators at the watershed scale is essential for effective water and soil resource management and for reducing flood risk. Materials and Methods: This study analyzes hydrological data from the Balikhlouchay watershed. The research process includes the collection, processing, and analysis of river flow data. Five hydrometric stations with a common 20-year statistical period (2003–2023) were selected. Key hydrological response indicators, including base flow index, peak discharge, runoff depth, drainage density, and recession coefficient, were calculated. Base flow was extracted using the one-parameter digital filter method, and its index was calculated as the ratio of base flow to total streamflow. The recession coefficient was obtained from an exponential recession model. Spatial variations of the indicators were analyzed using GIS-based interpolation techniques. In addition, the Mann–Kendall test was applied using Pro UCL software to detect temporal trends in river flow changes. Results and Discussion: Analysis of Hydrological Response Indicators in the Balikhlouchay Watershed revealed that geological conditions, topography, and physical characteristics of the basin have a significant impact on flood behavior and river flow stability. In particular, the high values of the base flow index at the Nir station indicate the influence of permeable geological structures and effective aquifer recharge. In contrast, the high drainage density at the Pol-e Almas station reflects the basin’s rapid response to rainfall and the occurrence of flash floods. These results are consistent with findings from similar studies in other Iranian watersheds and confirm the critical role of geological conditions and hydro-geomorphological structures in shaping the flood hydrograph pattern. Conclusion: The analysis of hydrological response indicators in the Balikhlouchay watershed highlights the significant influence of geological, topographic, and land surface characteristics on flood behavior and flow regime. The spatial distribution of base flow index, drainage density, and runoff depth across the watershed indicates notable variability, driven by differences in permeability, land cover, and geomorphological structure. For instance, higher base flow index values in the Nir station emphasize the importance of permeable geological layers and sustained groundwater contributions, whereas areas with high drainage density, such as the Pol-e Almas station, demonstrate rapid hydrological response and increased susceptibility to flash flooding. These variations reflect the complex hydrological functioning of the watershed and underscore the need for location-specific flood management strategies. The use of GIS-based spatial analysis and the Mann–Kendall trend test provided valuable insights into the temporal dynamics of key hydrological indicators. The observed trends in river flow suggest that changes in land use, soil conditions, and climate variability may be contributing to increasing flood risks in certain sub-regions. https://iwm.ilam.ac.ir/article_725319.html Extended Abstract Introduction: Floods are among the natural and human-induced disasters that have consistently caused various forms of human casualties, financial losses, and environmental damage in the watersheds of the country. Accordingly, managing this phenomenon and addressing different aspects of resilience against it are of particular importance. Resilience has diverse dimensions, and this research focuses on its socio-cultural and economic aspects. The process of socio-cultural resilience connects a network of adaptive capacities to post-disruption recovery. Economic resilience has two dynamic and static dimensions: dynamic economic resilience refers to the speed at which an institution or system recovers from a severe shock and returns to its desired state, while static economic resilience is defined as the ability of an institution or system to maintain its functionality when experiencing a severe shock. In this study, we measured the socio-cultural and economic resilience of local communities against floods in various hydrological and non-hydrological units of the Sange Sefid region in Ilam Province and classified their flood resilience potential. This understanding will play a significant role in future planning aimed at enhancing the socio-cultural and economic resilience potential of rural environments. Materials and Methods: In this research, first, the socio-cultural and economic resilience in the Sange Sefid watershed in Ilam Province and Chardavol County was assessed. To evaluate resilience in different sub-watersheds, the indicators for each component were determined based on a literature review, library studies, expert interviews, and field visits. Then, a survey of watershed residents was conducted to measure the intensity or magnitude of the considered indicators as resilience measurement items using a five-point Likert scale questionnaire, after assessing the validity and reliability of the questionnaire. The questionnaire's validity was confirmed by experts. Additionally, Cronbach's alpha method was used to calculate the reliability or trustworthiness of the measurement tool. Furthermore, the sampling unit was rural households, and Cochran's formula, based on the rural household population in each sub-watershed, was used to calculate the sample size. The questionnaire results were then entered into SPSS software, and one-way analysis of variance (ANOVA) was used to examine and analyze the data. Subsequently, the Tukey test was employed to prioritize sub-watersheds and compare means in terms of socio-cultural and economic resilience. Results and Discussion: Eleven socio-cultural indicators and nine economic indicators were used to measure the socio-cultural and economic resilience of local communities against floods in different hydrological and non-hydrological units. The results showed that Cronbach's alpha values for socio-cultural and economic resilience questionnaires were 0.832 and 0.815, respectively, indicating good reliability. The ANOVA results assessing socio-cultural and economic resilience against floods showed a significant difference between the units. Accordingly, flood resilience grouping of different hydrological and non-hydrological units was performed based on the Tukey test. The prioritization of socio-cultural resilience potential against floods, based on groups' calculated mean values in order from high to low, was: S-int2, S-int3, S8-int, S11, S-int5, S8-2, S-int4, S10, S12, S1, S-int1, and S9. The prioritization of economic resilience potential against floods in order from high to low was: S-int3, S-int2, S-int5, S10, S1, S-int1, S-int4, S8-int, S11, S12, S8-2, and S9. From the local community's perspective, units S-int2 (score 30.88) and S9 (score 47.07) had the minimum and maximum socio-cultural flood resilience, respectively, while units S-int3 (score 11.40) and S9 (score 35.13) had the minimum and maximum economic flood resilience, respectively. Conclusion: Overall, the results indicate the presence of units with different potentials for socio-cultural and economic resilience against floods in the study area. The grouping of socio-cultural and economic flood resilience potential showed classification into two groups with minimum and maximum resilience potential and three intermediate groups for socio-cultural resilience. For economic resilience, units were grouped into four distinct categories and one intermediate category. Accordingly, strategic planning to enhance the socio-cultural and economic resilience potential of rural environments—especially through applying problem-structuring methods and considering the flood resilience measurement indicators identified in this study—is strongly recommended. https://iwm.ilam.ac.ir/article_725926.html Extended Abstract Introduction:  Land subsidence is one of the most destructive yet hidden environmental hazards caused by various factors. In recent years, this phenomenon has become increasingly noticeable across the country. Land subsidence can result from natural processes such as tectonic and volcanic activities. However, human activities—particularly excessive groundwater extraction and the imposition of heavy loads on the earth’s surface—have recently been identified as its primary causes Moreover, climate change, reduced precipitation, and rising temperatures have decreased renewable water resources, thereby increasing reliance on groundwater and exacerbating land subsidence. Materials and Methods: This study investigate and analyzes ground surface changes within the Marvdasht aquifer using advanced radar interferometry techniques. Initially, the Differential Interferometric Synthetic Aperture Radar (DInSAR) methodology, utilizing Sentinel-1A satellite imagery, was employed to extract the land subsidence rate from 2015–2022. Subsequently, cumulative subsidence across the entire aquifer was calculated for the study period. Additionally, average groundwater level changes during the overlapping period with interferometric data were computed to analyze the correlation between groundwater decline and land subsidence. Results and Discussion: The results from the Marvdasht aquifer between 2015 and 2022 revealed an alarming trend of land subsidence. The highest annual subsidence rate was recorded between 2015 and 2016, reaching 24.1 cm per year, indicating the severity of the phenomenon during that period. The overall trend of subsidence over the seven years shows that, except for  2019–2020 (which experienced sharp increases in subsidence rates), the remaining years exhibited a decreasing trend. The lowest annual subsidence rate was observed in 2018–2019 at 16.3 cm.A comparison of groundwater level changes with subsidence rates during 2016–2017 and 2019–2020 indicates a significant and direct relationship. Specifically,  noticeable drops in groundwater levels coincided with  substantial rises in subsidence rates. The coefficient of determination between groundwater level changes and land subsidence was 0.26 across the entire aquifer and 0.50 in subsiding areas, indicating a relatively strong and statistically significant correlation between the two variables. This suggests a meaningful relationship between land subsidence and groundwater fluctuations in the Marvdasht aquifer. Additionally, This finding confirms the detrimental impact of excessive groundwater extraction on the intensification of land subsidence. Spatial analysis shows that the highest rates of subsidence occurs in the central and southern parts of the aquifer, areas known for a high density of groundwater extraction wells. Conversely, in urban areas of Marvdasht, where construction restrictions and extraction regulations limit the number of wells, subsidence is negligible. This findings highlight the critical importance of proper water resource management and strict monitoring of extraction activities in controlling and preventing land subsidence. Conclusion: Land subsidence, as one of the serious environmental hazards in the Marvdasht aquifer, was investigated over the period from 2015 to 2022. The results indicate a significant relationship between groundwater level decline and the rate of land subsidence. The highest annual subsidence rate occurred during 2015–2016, reaching approximately 24.1 cm, while the lowest was recorded in 2018–2019 at 16/3 cm per year. In subsiding areas, the relationship between groundwater level changes and vertical ground displacement—considering a time lag of about two years—yielded a coefficient of determination (R²) of 0.50, statistically significant at the 5% level. Spatial analysis further revealed that the highest subsidence occurred in regions with a high density of groundwater extraction wells (central and southern parts of the aquifer), while minimal subsidence was observed in areas with low well density (northeastern and southeastern regions). This underscores the substantial role of excessive groundwater withdrawal in driving land subsidence in the region. Ultimately, this study emphasizes the urgent need for sustainable groundwater management. Recommended strategies include controlling over-extraction through the installation of smart water meters, implementing artificial recharge programs, improving irrigation efficiency, developing land subsidence risk zoning plans, and enhancing public awareness and education for groundwater users. These measures can significantly contribute to reducing subsidence rates and mitigating associated risks. https://iwm.ilam.ac.ir/article_726325.html Extended Abstract Introduction: Wetlands are among the most ecologically significant yet vulnerable ecosystems, playing a pivotal role in biodiversity conservation, water regulation, and climate stabilization. However, these ecosystems are increasingly threatened by both anthropogenic pressures and climate change, leading to widespread degradation. According to global assessments, more than 50% of wetlands have been lost since the early 20th century. This alarming trend underscores the urgent need for effective monitoring and management strategies, particularly in semi-arid regions where wetlands are critical for maintaining environmental balance. The Salehiyeh Wetland, located in Alborz Province, Iran, has experienced substantial environmental changes over recent decades, largely attributed to human interventions such as the construction of drainage systems. This study aims to investigate land use/land cover (LULC) changes in the Salehiyeh Wetland between 1988 and 2021 (1367–1400 in the Iranian calendar) by employing satellite remote sensing data, NDWI and NDVI indices, and the Random Forest (RF) machine learning algorithm. Materials and Methods: This research utilized Landsat 5 TM and Landsat 8 OLI/TIRS imagery to analyze temporal variations in land cover within the wetland and its surrounding areas. The satellite data underwent standard preprocessing, including geometric and radiometric corrections, to ensure optimal data quality. To quantify water bodies and vegetation cover, the Normalized Difference Water Index (NDWI) and the Normalized Difference Vegetation Index (NDVI) were computed. These indices were employed to distinguish between water surfaces and vegetation, providing critical insights into the wetland’s hydrological and ecological dynamics. For land cover classification, the Random Forest (RF) algorithm was applied, a robust and widely-used machine learning technique known for its high classification accuracy and ability to handle large, multidimensional datasets. The classification results were evaluated using traditional accuracy assessment metrics, including Overall Accuracy (OA) and Kappa Coefficient (Kappa), which are standard indicators for the reliability of remote sensing-based classifications. Results and Discussion: The analysis of NDWI revealed that the highest water extent in the study area occurred in 1988, with a peak NDWI value of 0.64, indicating a substantial water coverage. However, over the 42-year period, a marked decline in aquatic areas was observed. Specifically, the extent of water bodies decreased from 2.64% of the total land area in 1988 to 0.05% in 2021, signifying a dramatic reduction in wetland habitats. In terms of land cover dynamics, rangelands predominated the landscape in 1988, 1998, and 2008, occupying over 49% of the study area. However, this trend reversed significantly by 2021, as large portions of rangeland were converted into agricultural lands. By 2021, agricultural areas expanded to cover 2,817.84 km², accounting for over 45% of the total area, marking a clear transition towards more intensive land use. Urbanization and the expansion of built-up areas also showed a significant upward trend. From 1988 to 2021, urban and residential areas increased from 46.25 km² to 770.21 km², reflecting growing human encroachment on natural ecosystems. This expansion further exacerbates the pressures on the wetland, as urban sprawl often leads to the drainage of surrounding water bodies. The performance of the RF classifier was exemplary, with overall classification accuracy exceeding 93%, and the Kappa coefficient exceeding 0.90, confirming the high reliability of the model for accurately detecting long-term LULC changes in the region. Conclusion: This study provides compelling evidence of the profound environmental transformations occurring in the Salehiyeh Wetland over the past four decades. The construction of drainage systems, agricultural intensification, and urban sprawl have all contributed to the drastic reduction of natural water bodies and rangelands. The integration of satellite remote sensing data with advanced machine learning techniques, such as the Random Forest algorithm, offers a highly effective framework for monitoring LULC changes over time. The high accuracy of the results highlights the potential of these methodologies for large-scale environmental monitoring and decision-making. Given the ecological importance of wetlands, it is imperative that policymakers adopt comprehensive conservation and restoration strategies to mitigate further degradation. A balanced approach that integrates urban development, agricultural needs, and ecological preservation is crucial for ensuring the long-term sustainability of wetland ecosystems. Continuous remote sensing monitoring should be prioritized to support evidence-based decision-making and adaptive management in the face of ongoing environmental challenges. https://iwm.ilam.ac.ir/article_726574.html Extended Abstract Introduction: Dust storms are among the most significant climatic hazards in the arid and semi-arid regions of Iran, accompanied by consequences such as reduced visibility, severe air pollution, threats to public health, decreased agricultural productivity, and damage to urban and rural infrastructure. In recent years, particularly in the western regions of the country, an increasing trend has been observed in the intensity, frequency, and spatial extent of this phenomenon. This alarming trend results from a combination of natural factors, such as recurring droughts, declining soil moisture, and strong winds, as well as human-induced drivers, including unbalanced land use changes, excessive exploitation of water resources, and unsustainable land management practices. Given the widespread impacts of this phenomenon on the environment and the livelihoods of local populations, accurately predicting the number of dusty days within specific time periods is of great importance as a critical tool for damage mitigation and informed operational and managerial decision-making. Achieving this goal requires the use of advanced data-driven methods and artificial intelligence algorithms that can be effective in identifying complex, nonlinear, and non-deterministic patterns. Materials and methods: In this study, a nonparametric predictive model based on the K-Nearest Neighbors (KNN) algorithm was developed. The Particle Swarm Optimization (PSO) metaheuristic algorithm was employed as a catalyst to optimize the model structure and enhance its prediction accuracy. The input data included the Frequency of Dust Storm Days (FDSD) index from 26 synoptic stations located in 11 provinces across western Iran, covering the long-term period from 1981 to 2020. To construct the predictive model, lagged values of the FDSD index over the four previous time steps were used as input variables to accurately capture the temporal patterns of this phenomenon. Initially, the base KNN model was implemented by adjusting the k parameter. Subsequently, the PSO algorithm was applied to optimize key model parameters, including the number of influential neighbors and the weighting of input variables. The models’ performance was evaluated using four statistical indicators: the correlation coefficient (r), root mean square error (RMSE), mean absolute error (MAE), and Nash–Sutcliffe efficiency (NS) coefficient, to assess the model’s accuracy and stability in predicting the FDSD index. Results and Discussion: The results show that the KNN-PSO model outperformed the standalone KNN model. The application of the PSO algorithm allowed for automatic and optimal determination of key KNN parameters, such as the optimal number of neighbors (k) and weighting of input variables. For instance, at Abadan station, the correlation coefficient (R) of the KNN-PSO model increased to 0.997, while the RMSE decreased to 0.113. In contrast, the KNN model values were 0.654 and 0.437, respectively, indicating a significant improvement in prediction accuracy using the hybrid model. Comparison between observed and predicted values confirmed the improved model performance with an increased frequency of dust storm days. Among the stations studied, Abadan, which recorded the highest FDSD values, showed the highest agreement between the observed and predicted data. Overall, high-dust stations, such as Abadan, Ahvaz, Masjed Soleyman, Bostan, Sarpol-e Zahab, and Bandar Mahshahr, exhibited strong correlations between actual and predicted values. In scatter plots, these predictions closely followed the 1:1 line (f(x) = x), indicating the high efficiency of the KNN-PSO model. Furthermore, results revealed that using lagged FDSD indices from previous seasons did not enhance model performance, and simpler models utilizing only one-step lag yielded more accurate predictions. Conclusion: Overall, the results demonstrate that the hybrid KNN-PSO model can significantly enhance the accuracy of predicting the frequency of dust storm days, particularly at stations with high occurrence rates, such as Abadan. By leveraging the capability of the PSO algorithm to automatically and optimally determine the sensitive parameters of the KNN model, this approach improves predictive performance compared to the base model. The findings indicate that integrating metaheuristic optimization algorithms such as PSO with simple data-driven models such as KNN not only increases prediction accuracy and efficiency in climatically challenging regions but also enhances the stability and generalizability under varying climatic and spatial conditions. Therefore, the use of such hybrid approaches can be considered an effective strategy for improved monitoring and management of climate-related hazards, including dust storms, in arid and semiarid regions. https://iwm.ilam.ac.ir/article_728128.html Extended Abstract Introduction: In recent decades, concerns about climate change and unprecedented greenhouse gas emissions have highlighted the importance of carbon sequestration as a key tool for mitigating the negative effects of this phenomenon. Ecosystems, especially forests, capture atmospheric carbon through photosynthesis and store it in their tissues and soil. This process helps reduce atmospheric carbon levels and mitigate greenhouse gas emissions. However, the potential of ecosystems for carbon sequestration varies and is directly influenced by their functional diversity. Different species in more diverse forest ecosystems, perform different roles, such as nitrogen fixation, enhancing soil organic matter, and protecting the soil. Therefore, such ecosystems likely have a greater capacity to capture and conserve carbon. Understanding ecosystem services requires an understanding of functional diversity, which governs ecosystem processes through various components. Different plant species have different performance traits, resulting in varying abilities to absorb, store, and emit carbon. Thus, the relationship between functional diversity and carbon storage is important. This study aimed to evaluate the functional diversity and carbon storage of the Quercus brantii Lindl. forest in Dehdez city, Khuzestan Province.   Materials and methods: To study the correlation between different components of functional diversity and carbon storage, 16 plots were selected in a representative Quercus brantii forest in Dehdez, Khuzestan Province. The following parameters were measured to calculate community-weighted mean (CWM), functional divergence (FDvar), and functional dispersion (FDis) as indices of functional diversity: six plant traits (leaf nitrogen content, leaf phosphorus content, specific leaf area, plant height, wood specific gravity, and leaf dry matter content), total ecosystem carbon (TEC), aboveground biomass carbon (AGBC), aboveground litter carbon (ALC), and soil organic carbon (SOC). Principal component analysis (PCA) was used to identify the most important independent variables, which were then used in stepwise multiple linear regression analysis to determine which components best explain the variability in carbon storage.   Results and Discussion: The mean organic carbon amounts in TEC, AGBC, ALC, and SOC were 89.5, 11, 3, and 74.4 tons per hectare, respectively. The first PCA axis, explaining 41.9% of the variance, was characterized by the CWM of height, while the second axis, explaining 34.3% of the variance, was characterized by the CWM of specific leaf area. Results showed that litter carbon was predicted by functional divergence, while soil carbon was predicted by community-weighted mean. Both were related to the specific leaf area index, which had a negative association. In the study area, the community-weighted mean of leaf nitrogen and specific leaf area, as well as the functional divergence related to specific leaf area, were identified as the most important factors for predicting carbon storage. The final model for biomass indicated that an increase in nitrogen content leads to an increase in carbon storage. Overall, significant effects of functional diversity on some plant traits such as leaf nitrogen content and specific leaf area were observed. Conclusion: This study found that indices based on a single trait, such as community-weighted mean (CWM) and functional divergence (FDvar), were more important for estimating carbon storage than the functional dispersion (FDis) index, which considers multiple traits. Additionally, the most important plant traits for carbon estimation were specific leaf area and leaf nitrogen content. https://iwm.ilam.ac.ir/article_728129.html Extended Abstract Introduction: Severe rainfall reduction, rising temperatures, and excessive exploitation of surface and groundwater resources—especially in arid regions of Iran—have turned water scarcity into one of the country’s major challenges. Among available water sources, karst aquifers play a crucial role in meeting water demands due to their unique geological characteristics. These aquifers, with their fractures, joints, and secondary porosity, offer high storage and transmission capacities. Moreover, the limestone composition of these formations often ensures suitable water quality for drinking and agricultural uses. Approximately 11% of Iran’s surface area—particularly in the Zagros highlands—is composed of karstic formations. This underscores the necessity of proper evaluation, and sustainable exploitation of karst water resources. The Semirom region in southern Isfahan Province is considered a promising area for developing karstic water sources but has faced declining water tables and drinking water resources in recent years. The present study investigates the potential of groundwater resources in the Garmook area of Semirom County and identifies suitable locations for drilling wells and exploiting karst aquifers. Materials and Methods: In this study, the geological structure of the region was first examined using existing geological maps, satellite imagery, and field surveys. The study area mainly includes zones developed in the Asmari and Shahbazan formations. Due to their hydraulic connectivity, these two formations were analyzed as a single hydrogeological unit. Data on precipitation, air temperature, topographic slope, vegetation cover, and soil characteristics were used to assess infiltration potential. The water balance method was then used to estimate inputs and outputs for each karstic zone. Inputs included effective precipitation, subsurface recharge from adjacent areas, and surface flows, while outputs comprised spring discharge, abstraction from wells, qanats, evapotranspiration from the epikarst zone, and subsurface discharge to adjacent plains. To delineate the recharge basins of the springs, empirical relationships were applied, considering mean annual precipitation, spring discharge, and infiltration rates. Additionally, water samples were collected from the identified sources, and the quality was assessed using laboratory results and plotted on Wilcox and Scholler diagrams. Results and Discussion: Geological investigations of the region revealed that the widespread presence of carbonate formations—particularly the Asmari Formation—in the Garmook area has created favorable conditions for karst development and the formation of high-capacity aquifers. The presence of active faults, such as the Narmeh Fault and its subsidiary branches, not only increases fracturing and jointing in the rock mass but also facilitates the infiltration of rainwater into the limestone bodies, thereby enhancing the recharge of karst aquifers. In this region, multiple water sources—including Khansar Spring, Khan-Ali Spring, Jaq-Jaq Spring, Semirom Waterfall, and several extraction wells within the Garmook area—have been identified, with a total discharge estimated at over 435 liters per second. This corresponds to approximately 13.7 million cubic meters per year, indicating the high yield potential of the area. In particular, the electrical conductivity of the regional waters is less than 450 µS/cm, further confirming their suitability for potable and irrigation use. On the other hand, results showed that in certain parts of the region (such as west of Narmeh), the infiltration rate decreases to about 30% due to the presence of thick soil cover and dense vegetation. However, in other parts—where karst development is more pronounced and open fractures and joints are prevalent—the infiltration rate can reach up to 50%. Water balance studies also indicated that part of the groundwater exits the area through transverse and longitudinal faults, flowing toward adjacent plains or distant springs such as Sandegan. Conclusion: Based on the conducted analyses, the Garmook area possesses adequate capacity to supply drinking and irrigation water in the short and medium term. Considering the geological context, the positive groundwater balance, and acceptable water quality, four locations were proposed for drilling new wells. These points are situated in areas with high recharge probability, good permeability, and suitable discharge rates. Additionally, to better understand the aquifer’s hydrodynamic behavior, the installation of piezometers and implementation of water-level monitoring programs are recommended. Given the significant influence of regional faults on groundwater flow directions, further studies—including dye and isotope tracing—are essential for determining the precise flow paths to improve groundwater resource management. The findings of this study can serve as a foundation for water resource management in southern Isfahan Province and other similar regions. https://iwm.ilam.ac.ir/article_728282.html Extended Abstract Introduction: Due to existing limitations in sharing spatial data, numerous studies conducted within various organizations suffer from high costs and are not suitable for dissemination or reuse. Furthermore, incompatibility among data generated by different organizations, or even between departments within a single organization, poses a significant challenge to cross-sector decision-making. This inconsistency stems from differences in data standards, foundational principles, and production processes. Additionally, due to security concerns, organizations tend to produce redundant data repeatedly, leading to resource wastage and reduced efficiency. This study aims to design and implement an integrated spatial data infrastructure (SDI) for sustainable natural resource management in Ilam Province. A conceptual model was developed, and a systematic approach was adopted to propose a framework for integrating spatial data across the Department of Natural Resources. Materials and Methods: To achieve the research objectives, the department's organizational structure was analyzed in terms of its chart and the information layers required. This was followed by a needs assessment and the design of conceptual, logical, and physical models. The selected open-source software environment was used to deploy the SDI  on a server. For data processing, open-source PostgreSQL and PostGIS databases were employed, while ENVI and ArcGIS were used for satellite imagery analysis. To disseminate the generated maps according to OGC standards, GeoServer was utilized. Results and Discussion: Findings indicate that establishing such an infrastructure can enhance interdepartmental coordination, accelerate organizational workflows, reduce operational costs, and support sustainable natural resource management through centralized information. The fully operational implementation within the Department of Natural Resources and Watershed Management represents a significant advancement in spatial data management. Unlike many theoretical studies in this field, the system developed in this research actively provides services to real users, distinguishing it from purely conceptual work. Its primary advantage lies in the integrated data approach and the practical delivery of services. Implementation of this infrastructure has reduced decision-making time. For example, in monitoring and controlling violations, the system decreased the time required to detect land encroachment by up to 60%, thanks to the simultaneous display of ownership and land-use layers and the capability for online measurement of violations. In disaster management, the system identified a 70-hectare wildfire in Ilam County and automatically calculated the affected areas, reducing response times by up to 50%. A unique aspect of this research is its adaptation of advanced technologies to local and country-specific conditions. The system is not only theoretically sound but also addresses operational challenges such as infrastructural limitations, organizational resistance, and user-specific needs. The development of a mobile service with offline data upload capabilities and field mapping tools has addressed the needs of experts in remote areas, reducing reliance on specialized hardware by 75%. Despite these successes, the study encountered several limitations. The practical and indigenous nature of the project makes direct comparison with theoretical studies or systems implemented in other countries difficult. Challenges such as inter-organizational discrepancies, resistance to change, and hardware constraints were valuable learning experiences, often overlooked in experimental and theoretical research. Conclusion: This research confirms that, despite various limitations, establishing a unified spatial data system is not only feasible within the country but can also significantly improve natural resources management processes. The practical experiences gained through this project can serve as a valuable guide for other organizations seeking to implement similar systems. https://iwm.ilam.ac.ir/article_729081.html Extended Abstract Introduction: Ecosystem services, the direct and indirect benefits provided by natural systems, play an essential role in maintaining ecological balance, environmental sustainability, and effective natural resource management. Among these services, sediment retention is considered a crucial regulating function. It helps reduce soil loss, sustain agricultural productivity, protect water quality, extend the operational lifespan of reservoirs, and mitigate flood risks. However, land use change, driven by human activities such as urbanization, agricultural expansion, industrial development, and deforestation, has increasingly disrupted this service. In recent decades, factors like population growth, climate variability, and increasing demand for land and water have caused significant transformations in land cover, particularly in mountainous and erosion-prone watersheds. These changes have altered sediment production and transport processes, often resulting in increased erosion and downstream sedimentation. To assess and address these impacts, spatially explicit and process-based models have become essential tools. One such tool is the InVEST model, which allows for spatially distributed estimation of ecosystem services under different land use scenarios. This study aims to evaluate the effects of land use change on sediment retention in the Bazoft watershed, located in the upstream area of the Karun-4 Dam in southwestern Iran, using the sediment delivery ratio (SDR) module of the InVEST model. The results can offer useful insights into sediment dynamics and inform integrated watershed management and sustainable land use strategies. Materials and Methods: The study was conducted in the Bazoft watershed, which is located in the upper part of the Northern Karun Basin and drains into the Karun-4 Dam. The area is mountainous, with steep slopes averaging around 45%, a cold and semi-humid climate, and annual precipitation of about 766 mm. The average annual discharge is approximately 57.8 m³/s. The natural land cover consists mainly of forests and rangelands, while cultivated and residential areas represent the dominant human-induced land uses. In this study, land use and land cover (LULC) maps were generated for the years 2001 and 2021 using Landsat satellite imagery (ETM+ and OLI sensors, respectively), classified using the Maximum Likelihood algorithm in ENVI and ArcGIS software. Future land use for the year 2041 was simulated using the Scenario Generator tool, incorporating land suitability analysis and expert knowledge. The InVEST SDR model was used to estimate soil loss, sediment export, and sediment retention capacity based on inputs including LULC maps, a 30-meter resolution DEM, rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), vegetation cover factor (C), and support practice factor (P). Additional ecological inputs such as NDVI and hydrological connectivity parameters were included. Results and Discussion: The results of this study indicated that human land uses such as rainfed agriculture, irrigated agriculture, and residential areas have shown an increasing trend, while natural covers like dense forests and dense rangelands have declined. The greatest increases during the 2001–2021 period were observed in rainfed agriculture (25.9%) and residential areas (63.07%). These trends are projected to continue, with increases of 21.7% and 20.91% respectively for the 2021–2041 period. The most significant decreases were related to dense forests and dense rangelands, by −7.53% and −9.07%, respectively, in the 2001–2021 period. According to the results of the SDR (Sediment Delivery Ratio) model in the InVEST software, the potential soil loss, sediment export, and sediment deposition are expected to increase by 0.56%, 1.01%, and 0.16%, respectively, compared to the current conditions of the watershed due to land use changes. These findings suggest that the continued expansion of human land uses could lead to a long-term decline in the ecosystem’s capacity to control erosion and sedimentation. The results are consistent with similar studies and highlight the importance of sustainable land use management. Conclusion: This study demonstrates that land use changes significantly reduce the sediment retention service in the Bazoft watershed. Continued expansion of agriculture at the expense of natural vegetation exacerbates soil erosion and sediment delivery, undermining watershed sustainability. The findings reinforce the necessity of conserving forests and rangelands, and support the use of scenario-based tools like InVEST for guiding land use planning and environmental policy in fragile mountainous ecosystems. https://iwm.ilam.ac.ir/article_729082.html Extended Abstract Introduction: Forests and rangelands are considered among the richest sources of ecosystem services. With population growth and the intensification of natural resource exploitation, the demand for these services has increased dramatically. Understanding these services and the extent of human dependence on them highlights the need for the development of systematic frameworks for their economic valuation. Among these ecosystems, the Zagros rangelands stand out as one of the most critical ecological systems in Iran, currently facing escalating threats. Although these rangelands play an irreplaceable role in regulating water and soil cycles, conserving biodiversity, and supporting the livelihoods of local communities, increasing pressures from overexploitation and unsustainable management have placed their survival at serious risk. The objective of this study was to conduct an economic valuation of the most important ecosystem services provided by the rangelands in the Kolashak watershed. Materials and Methods: In this study, the Kolashak watershed, encompassing an area of 9,110.2 hectares and located in Gilan-e Gharb County, Kermanshah Province, was investigated. First, all essential base maps, including topography, vegetation cover, land use, and soil maps, were prepared and processed within a GIS environment. Subsequently, the most important ecosystem services were assessed, comprising regulatory services (functions: carbon sequestration and oxygen production)****, supporting services (functions: soil formation and nutrient conservation)****, and provisioning services (function: forage production). The economic valuation of these services was conducted using the replacement cost method. Finally, the total economic value of ecosystem services in rangeland land use was estimated. Results and Discussion: The economic value of each hectare of rangeland in the study area was estimated at 784,247 Thousand Rials per hectare per year. Among the assessed services, oxygen production (503,795 Thousand Rials) and carbon sequestration (248,976 Thousand Rials) contributed the most to this economic value. The average carbon sequestration in the rangelands was estimated at 24.96 tons per hectare; 87% of which (21.74 tons) is stored in the soil, highlighting the role of rangeland soils as key carbon sinks. Regarding oxygen production, calculations based on photosynthesis equations indicated that each hectare of rangeland annually produces an average of 3.7 tons of oxygen (equivalent to 11,077.8 tons across the entire watershed), sufficient to meet the annual oxygen needs of 12 individuals. These findings suggest that rangelands with greater vegetative cover and larger areas have a higher capacity for carbon sequestration and oxygen production. Furthermore, the economic value of forage production was calculated at 29,540 Thousand Rials per hectare. The rangelands of the Kolashak watershed also play a vital role in soil conservation and erosion prevention. With an average erosion rate of 13.85 tons per hectare, these rangelands perform better than the region’s agricultural lands (17.43 tons per hectare). The rangelands prevent the annual loss of approximately 3,580 kg of soil per hectare, equating to an economic value of 1,815 Thousand Rials per hectare for nutrient retention. Additionally, the economic value of soil formation was estimated at 121,633 Thousand Rials per hectare. Although this value appears lower than that of other functions, it reflects the long time required for soil formation and the replacement cost-based valuation method. Overall, these results underscore the substantial ecological and economic importance of rangelands in maintaining biogeochemical cycles and moderating climate change. Conclusion: Valuing environmental resources such as rangelands has two important applications. First, it is used in cost-benefit analysis to attract economic support for rangeland protection and to determine the amount of damage caused by rangeland degradation. Second, the estimated economic values can be used in generating the gross income of a sector of the economy. The findings highlight the significant economic value of ecosystem services provided by the rangelands in the Kolashak watershed. This valuable ecosystem is under increasing threat from factors such as overgrazing, land-use change, water erosion, and shifts in precipitation patterns. These threats emphasize the urgent need for sustainable management. The results of this study can serve as a scientific foundation for management decisions and conservation planning, particularly in balancing livestock numbers with rangeland carrying capacity and improving grazing practices. Such measures can help simultaneously address the livelihood needs of local communities while ensuring the long-term health and functionality of rangeland ecosystems. https://iwm.ilam.ac.ir/article_729267.html Extended Abstract Introduction: Evaluating the water resources adequacy in watersheds to meet local community needs is critically important—particularly in arid and semi-arid regions where water scarcity and environmental stress are significant. In the context of ongoing climate change and unsustainable water management practices, a comprehensive and multidimensional evaluation of water adequacy—encompassing quantitative, qualitative, institutional, and social dimensions—is essential. In Iran, as a country with a large proportion of arid and semi-arid regions, the necessity of addressing this issue is increasingly apparent. Accordingly, a systematic review of indicators and models for assessing water adequacy, accompanied by critical analysis and identification of research gaps, can provide a reliable foundation for developing evaluation frameworks that are suited to national conditions. Previous studies—largely based on approaches involving quantitative indicators, qualitative measures, institutional-social metrics, and simulation or decision-making models—have made significant contributions. However, they also exhibit several limitations, including a narrow focus on one or two dimensions (e.g., solely quantitative or qualitative), lack of context-specific indicators for dry regions with variable precipitation and limited resources, insufficient attention to social components such as local community resilience, distributive justice, and indigenous knowledge, and the absence of integrated conceptual frameworks that combine indicators with modeling tools and the actual needs of watershed inhabitants. Only a limited number of studies have succeeded in integrating productivity indicators, simulation models, and institutional measures to offer a comprehensive picture of water adequacy. Moreover, most existing research has not adequately addressed the specific needs of watershed communities in arid regions in terms of livelihoods, resilience, and participation. This review article comprehensively analyzes the most critical indicators, models, and challenges related to the evaluation of water resource adequacy in watershed areas, with a particular emphasis on the applicability and adaptability of these approaches to watersheds in arid and semi-arid environments. Materials and methods: This critical analytical review study was conducted through a comprehensive search of international databases (Scopus, ScienceDirect), academic search engines (Google Scholar), and nationally credible databases (SID, Magiran), with source selection based on scientific credibility and thematic relevance. Through an analytical framework, the identified indices and models were categorized into six distinct groups: (1) quantitative indicators, (2) qualitative indicators, (3) institutional-social indicators, (4) productivity and indirect consumption measures, (5) risk and resilience metrics, and (6) simulation and decision-making models for water adequacy assessment. Each category was examined to identify its advantages, implementation challenges, and limitations, with particular emphasis on arid and semi-arid regions. The final synthesis focused on analyzing studies employing integrated approaches. Results and Discussion: The review of 130 selected scientific studies reveals that, foremost, quantitative indicators are among the primary tools used to assess water resource adequacy in watersheds. At more advanced levels of analysis, qualitative indicators—particularly in studies concerned with environmental aspects—have received increasing attention. Additionally, indicators of indirect water use, such as water footprint, virtual water, and economic–physical productivity, have enabled recent studies to explore the water–livelihood nexus at both micro and macro scales. Institutional and resilience-related indicators—such as stakeholder participation, institutional flexibility, and the adaptive capacity of local systems—have opened new perspectives for understanding socio-structural sustainability in the context of water adequacy evaluations. Given the complexity introduced by limitations such as the lack of reliable data, institutional fragmentation, and environmental challenges, integrating various indicators and models—while considering the specific characteristics of arid and semi-arid regions, including those in Iran—is essential for delivering more accurate and practical assessments of water adequacy. Moreover, greater emphasis on institutional-social dimensions, as well as on risk and resilience, contributes to a deeper and more comprehensive understanding of the issue, and lays the foundation for the development of sustainable water resource management policies and strategies. Conclusion: To enhance the effectiveness of evaluations, there is a need for up-to-date field data, coherent conceptual frameworks tailored to the specific region under study, and cross-sectoral collaboration. Future research must develop dynamic indicators and integrated, empirically-grounded models that address the evolving needs of watershed communities in arid and semi-arid regions and to support the achievement of sustainable water security. This study can provide valuable insights for water resource managers and policymakers to improve decision-making and promote sustainable resource management. https://iwm.ilam.ac.ir/article_729319.html Extended Abstract Introduction: The main goal of this study was to analyze and forecast the health condition of watersheds within third-order catchment basins across Iran, based on the variability of dynamic factors and their quantitative influence on future watershed health. The research takes a forward-looking approach, aiming to evaluate the state of watershed health for the years 2033, 2043, and 2053. The introduction highlights the importance of conserving and maintaining water and environmental resources for sustainable development, especially in a country facing diverse climates and significant human and environmental pressures. Watersheds play a vital role in water supply, flood control, and biodiversity conservation, making it crucial to understand the factors affecting their health. Materials and Methods: In the study, key indicators and criteria influencing the health of priority watersheds in the country were collected and analyzed. These indicators were divided into two groups: static and dynamic. Initially, 173 indicators related to environmental, climatic, and human factors were selected as pressure indices, 331 indicators of similar factors were chosen as state indices, and 13 human and ecological factors were designated as response indices. After standardizing the averages of these indicators, the health status of watersheds for each targeted year was estimated by combining and weighting these indicators. To analyze the effects of independent variables on watershed health, multiple regression methods were used. These variables included maximum and minimum temperature parameters, land use, and vegetation cover levels. Results and Discussion: The results showed that in 2033, watersheds in the northern regions —especially in Gilan and Mazandaran—are expected to remain in good to very good condition (about 60 to 70% of areas), owing to extensive forests and sufficient rainfall. Conversely, in the southern regions such as Hormozgan and Sistan and Baluchestan, conditions were assessed as weaker (around 40 to 50% in moderate to poor categories). By 2043, this trend continued in the north and northwest, mainly because of persistent dense vegetation cover and adequate rainfall. However, in eastern and southeastern areas, decreasing rainfall and human pressures resulted in an increase in unhealthy areas to roughly 50 to 60%. By 2053, regional differences became more prominent; in the north, especially in Gilan and Mazandaran, abundant rainfall and dense cultivation helped sustain relatively healthy conditions (about 40 to 50%). In contrast, in eastern and northeastern regions, reduced rainfall and increased human activities led to a decline in watershed health, with healthy areas falling to approximately 30 to 40%. Analysis indicates that temperature fluctuations, particularly changes in minimum temperatures, play a highly sensitive and significant role in altering watershed health. The impact of these fluctuations in each of the three years exceeds 47.66% on the health index. These findings emphasize the importance of managing climate change, land use modifications, and vegetation cover for the sustainability and health of watersheds in the country. The effects of dynamic variables related to land use and vegetation cover are steadily increasing, and by 2053, their influence on the health index is expected to surpass 33.5%. Conclusion: This study highlights that future planning should focus on controlling and managing temperature fluctuations, human pressures, and land use changes, as these factors directly and significantly affect the health and sustainability of water resources and ecosystems. Management actions and policy decisions in climate management, including adherence to or modification of land use patterns and preservation of vegetation cover, can play a crucial role in improving and maintaining watershed health. These results highlight the need for ongoing monitoring, strategic planning, and the sustainable use of natural resources in the future. https://iwm.ilam.ac.ir/article_729322.html Extended Abstract Introduction:Soil loss and sediment yield are among the main challenges in watershed management, especially in mountainous areas, which, in addition to reducing soil fertility and ecosystem functioning, also threaten water quality and the sustainability of hydrological services. In this context, watershed hydrological services, such as sediment retention, are of high importance because they control soil erosion and reduce downstream sediment transport, thereby improving water quality. The topographic, climatic, and human conditions of mountainous regions in northern Iran, especially the Hyrcanian forests, make these areas particularly susceptible to soil degradation, increasing the need for monitoring ecosystem services and analyzing the spatiotemporal dynamics of sediment retention to assess changes in ecosystem functioning and the effectiveness of management measures. In this regard, the InVEST model, with a simple structure, limited input requirements, and high interpretability, is an effective tool for analyzing these services at the watershed scale. This model, using sediment delivery ratio equations and spatial data, allows examination of the spatiotemporal changes in soil erosion, sediment yield, and sediment retention. Given the need for comprehensive studies in Iran, especially in the Hyrcanian forests, the present study aims to investigate the spatiotemporal changes of soil loss, sediment retention, and sediment yield over a 25-year period in the Talar mountainous watershed. Additionally, sensitivity analysis of model input factors was conducted to identify the most influential variables affecting sediment delivery ratio results. Materials and methods: The study area is the Talar watershed (Mazandaran Province), spanning over 1,700 km² on the northern slopes of the Alborz mountain range, with an elevation range from 216 to 3,983 meters. The SDR model from the InVEST toolkit was applied to estimate annual soil loss, sediment retention, and sediment yield. Average soil loss was calculated using the InVEST soil erosion equation based on key factors including rainfall erosivity, soil erodibility, vegetation cover, land management, and topography across three study periods. Additional parameters such as the sediment connectivity index, K factor, and maximum sediment delivery ratio were defined based on regional characteristics and expert knowledge. A sensitivity analysis of the model input factors was also conducted to identify the most influential variables affecting the sediment delivery ratio outcomes. Results and Discussion: According to the results, over the 25-year study period, soil loss decreased from 896,535 to 758,981 ton, sediment retention from 1.297 to 0.757 million  ton, and sediment yield from 113,643 to 57,426  ton. The main cause of this reduction was a 28.8 % decrease in rainfall erosivity during the study period. The analysis showed that pasture land had the highest sediment retention capacity (415,978  ton), whereas orchards had the lowest (3,676 t). Meanwhile, the highest sediment yield occurred in rainfed agriculture and pasture, while forests and orchards had the lowest amounts. Sensitivity analysis indicated that rainfall erosivity, with a relative sensitivity coefficient of 0.99, was the most important factor affecting soil loss, sediment retention, and sediment yield, explaining more than 47 % of model output variations. The K parameter also influenced sediment retention and yield, though it had no direct effect on soil loss. Overall, the InVEST model is more sensitive to natural parameters such as rainfall than to management variables, highlighting the necessity of integrating climatic data with human interventions in management. Conclusion: The findings indicate that the InVEST model, with high spatiotemporal analysis capability, is a suitable tool for assessing watershed hydrological services, especially in mountainous regions. The observed reduction in soil loss, sediment retention, and sediment yield over the study period was mainly due to decreased rainfall erosivity and climatic changes. Dense vegetation cover, such as forests and pastures, played a key role in sediment retention and soil erosion reduction, while human land uses such as agriculture contributed more to sediment yield. Sensitivity analysis emphasized the importance of natural factors, particularly rainfall, in watershed management. The findings can be applied to identify critical areas for conservation, prioritize sensitive land uses, design monitoring systems, and develop future management scenarios. It is recommended that future studies utilize long-term data, complementary models, and scenario-based analyses under climate change to enhance the accuracy of assessments and the applicability of results in ecosystem management decisions. https://iwm.ilam.ac.ir/article_730082.html Extended Abstract Introduction: Integrated watershed management is a cornerstone of sustainable development, encompassing policies and actions aimed at conserving water and soil resources, preventing environmental degradation, and enhancing the quality of life for local communities. As natural units, watersheds play a critical role in maintaining ecological balance, preserving biodiversity, and supplying freshwater. Effective management requires a holistic approach—considering water, soil, vegetation, wildlife, and human activities—while integrating economic, social, and environmental dimensions to create synergies. One widely used tool in this context is the DPSIR framework, which analyzes cause-and-effect relationships among system components. However, in its conventional form, DPSIR often merges driving forces and pressures, making it difficult to isolate the specific impact of each pressure on particular states. This limitation typically leads to generalized strategies. To address this issue, this study applies the nested DPSIR framework (Atkins et al., 2011) to develop targeted management strategies for the Goorsefid Watershed in Tehran Province, with active participation from local stakeholders.  Materials and Methods: The nested DPSIR process involved eight key steps: (1) constructing individual DPSIR cycles, (2) compiling a DPSIR table, (3) designing a conceptual map, (4) developing a decision matrix, (5) prioritizing pressures, (6) scoring responses based on pressure significance, (7) evaluating responses against watershed health and sustainability criteria, and (8) ranking responses. In this study, the environmental, economic, and social states of the watershed were assessed both quantitatively and qualitatively through literature review, field surveys, and stakeholder interviews. The remaining components were analyzed following the nested DPSIR methodology. Data were collected via questionnaires administered to 60 local residents and 25 experts and were validated by 12 specialists. Reliability and internal consistency were tested using Cronbach’s alpha, and a five-point Likert scale was used to assess the weight and importance of the DPSIR components.  Results and Discussion: Five key drivers were identified, leading to 18 major pressures. These pressures caused changes in 17 states and ultimately affected 23 ecosystem services. To address these challenges, 27 management strategies were proposed. The five highest-priority pressures—based on stakeholder feedback and their recurrence across multiple states—were: (1) land-use change and vegetation degradation, (2) lack of a coherent water-use system in agriculture and livestock, (3) overexploitation of surface and groundwater resources, (4) drought, and (5) issuance of grazing permits to non-local, non-pastoralist individuals. The proposed responses were categorized as follows: 11 physical, 6 political, 1 managerial, 5 economic, 1 socio-cultural, and 3 ecological. The nested DPSIR framework effectively illustrated the complex interactions between human and natural factors in a simplified and more accessible manner. As a methodological innovation, this study introduced a coding system for nested DPSIR components to reduce redundancy, maintain structural consistency, and improve visual understanding of interrelationships.  Conclusion: Applying the nested DPSIR framework—through mapping individual cycles, constructing interaction matrices, developing conceptual diagrams, conducting quantitative analysis, and prioritizing components—enabled the identification of causal relationships across all system elements. This approach provided a comprehensive understanding of watershed dynamics, supported precise goal-setting, facilitated issue prioritization, and ultimately guided the selection of the most effective management strategies. Therefore, it can be concluded that applying this framework not only enhances the decision-making process but also fosters active participation of local communities and promotes the integration of scientific knowledge with traditional experience. This approach may serve as a model for sustainable management of other watersheds across the country. https://iwm.ilam.ac.ir/article_731363.html Extended AbstractIntroduction: Various factors contribute to public non-participation in watershed management projects. Understanding these inhibiting factors is a fundamental step toward fostering effective public involvement and achieving comprehensive watershed management goals. In this context, prioritizing the indicators and sub-indices that affect non-participation is essential for the cycle of participatory management and proper basin stewardship. Identifying and ranking these factors provides a pathway for implementing measures to remove obstacles to beneficiary participation, thereby encouraging maximum involvement from local residents in planning processes. This study, conducted from 2018 to 2021 in the Kaki watershed of Dashti, Bushehr province, aims to identify, classify, and prioritize these factors based on the perspectives of both watershed residents and experts.Materials and methods: The research site is located in the Kaki watershed, part of the Kaki district of Dashti city in Bushehr province, southern Iran. After identifying and classifying the specific factors, measurement tools were prepared in the form of pairwise comparison and Likert-scale questionnaires; the validity of these questionnaires was confirmed by a panel of experts. Following the completion of the Analytical Hierarchy Process (AHP) questionnaires by 34 experts, the Fuzzy Analytical Hierarchy Process (FAHP) was used to prioritize the indicators. To prioritize the indicators and sub-indices affecting the lack of sustainable public participation from the perspective of the basin residents, a Likert-scale questionnaire was used. After confirming its validity and reliability, the survey was administered. The sampling unit was a rural household, and Cochran's formula was used to determine the sample size. Based on the total number of households in the villages (814 households), 261 questionnaires were completed by the heads of households.Results and Discussion: The results of the hierarchical analysis from the experts' perspective showed that the sub-index of "lack of education for basin residents regarding the relevant projects and goals" had the highest relative priority with a mean rank of 4.98, while the sub-index of "delayed effectiveness of watershed management projects" had the lowest relative priority with a mean rank of 0.64. From the perspective of local communities, the sub-index of "ethnic and local differences" had the highest relative priority with a mean rank of 8.77, whereas the sub-index of "non-use of local promoter groups" had the lowest with a mean rank of 4.32.Conclusion: In the Kaki watershed, the weights obtained from the Fuzzy AHP for expert opinions indicate that design-implementation, economic, social, and finally educational-promotional indicators, in that order, played the greatest role in the lack of public participation. The results of the Friedman test from the local communities' perspective differed slightly, ranking the indicators as social, economic, educational-promotional, and finally design-implementation. Based on these findings, it is recommended to prioritize training courses and classes aimed at increasing the knowledge of local communities about watershed management projects. Furthermore, since local trustees (e.g., elders, educated individuals, members of the Islamic Council, and village teachers) are highly trusted, these groups, along with non-governmental organizations (NGOs), could act as local promoters. They can advocate for project goals and help foster public participation. Additionally, creating conditions for the active involvement of watershed residents in various stages—such as decision-making, design, implementation, maintenance, and repair—is crucial. This could include developing new participatory frameworks for comprehensive watershed management. Providing employment opportunities for local residents in project implementation, for instance through contracts with village councils or by mandating the employment of local labor in contractor agreements, is also recommended. https://iwm.ilam.ac.ir/article_731617.html Extended Abstract Introduction: Urban water resilience has emerged as a critical concept within urban science and resource management, particularly in metropolises like Tehran. The city faces a confluence of challenges, including rapid population growth, unbalanced physical development, the escalating impacts of climate change, and intensifying pressure on its limited water resources. These trends have profoundly impacted the sustainability and functionality of socio-hydrological systems—defined by the complex, feedback-driven interactions between human society and water systems. Consequently, urban water resilience has become a fundamental metric for evaluating a city's capacity to manage water crises. Within this context, the principles of diversity and redundancy are recognized as key components in maintaining the stability and continuous performance of urban water systems. By effectively strengthening these factors through urban policy, cities can reduce vulnerabilities and enhance their flexibility in confronting water crises and environmental changes. This study aims to conduct a comparative analysis of the role of diversity and redundancy in enhancing the resilience of the socio-hydrological system across three distinct urban districts of Tehran: Districts 4, 10, and 22. Materials and methods: This research employed a comparative analytical approach, selecting three Tehran districts (4, 10, and 22) as case studies due to their significant differences in demographic and infrastructural characteristics. The conceptual framework was organized around five key dimensions of resilience: social, economic, organizational, infrastructural, and human capital. Data were collected using a structured questionnaire distributed to urban water managers and experts via a snowball sampling method. The questionnaire's validity was confirmed through expert review, and its reliability was demonstrated by a Cronbach's alpha coefficient of 0.89, indicating high internal consistency. For data analysis, the non-parametric Kruskal-Wallis test was utilized to compare the mean ranks across the different districts and dimensions, as the data distribution was non-normal. Results and Discussion: The analysis revealed nuanced findings regarding diversity and redundancy. At the overall level of diversity, no significant difference was observed between the three districts (p=0.577). However, a detailed examination of sub-dimensions showed that District 22 held a significant superiority in social capital diversity (p=0.003). This indicates a high capacity for strengthening social participation and leveraging dynamic informal civic relationships, underscoring the importance of social networks in enhancing resilience in newer districts, even with less-developed physical infrastructure. In contrast, the redundancy dimension showed a notable advantage for the more established Districts 4 and 10, particularly in the economic, organizational, and infrastructural domains, with an overall significant difference (p=0.019). This superiority was statistically significant in the sub-dimensions of economic (p=0.014), institutional (p=0.013), and infrastructural (p=0.033) capital. These findings suggest that historical context and existing infrastructure bolster structural and economic resilience in older districts, whereas newer districts may derive dynamic resilience from robust social capital and informal networks. The study also identified cross-cutting challenges, including a lack of precise organizational data, a disconnect between national policies and local implementation, and structural-demographic constraints, which hinder resilience-building in all districts. Addressing these weaknesses requires holistic, region-specific strategies, improved inter-institutional communication, and the mobilization of local social capacities. Conclusion: The findings demonstrate that urban water resilience is a multidimensional phenomenon that cannot be achieved through technical and infrastructural solutions alone. A comprehensive approach must also strengthen human interactions, institutional cooperation, and the strategic application of local social capacities. The analytical framework developed in this research provides a valuable, context-sensitive basis for evaluating, planning, and enhancing urban water resilience in other metropolises. Achieving sustainable urban water resilience is contingent upon participatory governance, transparent management mechanisms, meaningful stakeholder engagement, and a dedicated focus on the unique local capacities of each district. Therefore, it is recommended that urban policymakers, in their pursuit of enhanced water resilience, simultaneously address human, economic, and institutional aspects alongside the expansion of technical and financial infrastructures. Ultimately, resilience in the face of future water challenges demands a comprehensive, interdisciplinary, and continuous approach that integrates the participation of all stakeholders with the application of technological and managerial innovations. https://iwm.ilam.ac.ir/article_731727.html Extended AbstractIntroduction: Hydrological ecosystem services (HES), such as water yield and sediment retention, are fundamental to ecological balance and sustainable resource management. However, these critical functions are increasingly disrupted by rapid land use and landscape changes driven by human activities. These dynamics are effectively captured by landscape metrics, which quantify the spatial configuration, composition, and structure of land cover patches. This study aims to model and predict key HES in the Talar watershed, Mazandaran Province, Iran, and to quantitatively examine their relationships with landscape metrics and the processes of landscape change.Materials and methods: The research employed a multi-step methodological framework. First, land use/land cover (LULC) maps for 1989, 2000, and 2014 were generated using the Support Vector Machine (SVM) classifier. A projected LULC map for 2030 was then created using a Markov chain integrated with the Land Change Modeler (LCM). A suite of landscape metrics—including Number of Patches (NP), Patch Density (PD), Largest Patch Index (LPI), and others—was calculated using FRAGSTATS software. Concurrently, specific landscape change processes (e.g., deformation, shift, creation) were quantified for each LULC class using TerrSet. The InVEST model was applied to simulate and project the HES of water yield and sediment retention for all study years, including the 2030 scenario based on current change trends. Finally, the relationships between the landscape metrics, change processes, and ecosystem service delivery were analyzed using Pearson correlation coefficients in SPSS.Results and Discussion: The Land Change Modeler demonstrated excellent performance in predicting LULC changes (Klocation = 0.969, Kno = 0.964). Projections for 2014–2030 indicate significant shifts: a decline in forest (–14.86 km²) and rangeland (–19.85 km²) areas, contrasted with an expansion of rainfed agriculture (+21.01 km²) and residential areas (+13.60 km²). Pearson correlation analysis revealed that most spatial pattern indices, except for patch density and edge density, had significant correlations with both water yield and sediment retention. The Perimeter-Area Ratio (SHAPE_AM or a similar PA metric) exhibited the strongest correlation (0.699 for water yield; 0.782 for sediment retention). An inverse relationship was found between the Largest Patch Index (LPI) and these services, suggesting that the dominance of large, consolidated patches can negatively impact hydrological functions. Furthermore, the Landscape Shape Index (LSI) for forest and rangeland patches decreased over the 25-year period, a trend associated with reduced water yield and sediment retention. Analysis of change processes showed that the expansion of rainfed agriculture increased water yield but decreased sediment retention, while the decline in forest cover negatively impacted both services, highlighting the adverse consequences of deforestation.Conclusion: The findings indicate that ongoing land use changes and landscape fragmentation are likely to degrade hydrological ecosystem services and reduce the ecological resilience of the Talar watershed. This study confirms the significant influence of landscape structure on water yield and sediment retention, with metrics like the Perimeter-Area Ratio serving as strong indicators. The negative correlation with the Largest Patch Index and the detrimental impact of forest loss underscore the need for integrated land use planning and targeted conservation strategies in northern Iran. The combined methodology of spatial modeling, landscape metric analysis, and change process assessment provides a robust and practical framework for evaluating and predicting ecosystem services at the watershed scale, offering valuable insights for sustainable environmental management. https://iwm.ilam.ac.ir/article_732638.html Extended Abstract Introduction: Climate change stands as one of the most critical environmental challenges of the 21st century, with profound implications for natural resources and the agricultural sector. It disrupts established climate patterns, directly threatening water sustainability, soil fertility, and the ecological cycles that underpin agricultural production. Globally, rising temperatures, shifting precipitation regimes, prolonged droughts, and the increased frequency of extreme weather events like floods and heatwaves jeopardize agricultural yields. According to the Intergovernmental Panel on Climate Change (IPCC), global temperatures have already increased by approximately 1.1°C since pre-industrial times and could exceed 4°C by the century's end if current trends continue. Such changes are projected to reduce yields of staple crops such as wheat, rice, and maize by 10 to 25 percent in some regions by 2050, with disproportionate impacts on developing nations reliant on subsistence farming. Iran, with its predominantly arid and semi-arid climate, is highly vulnerable. The country faces reduced precipitation, rising temperatures, recurrent droughts, and the depletion of surface and groundwater resources. These climatic stressors endanger agricultural productivity, rural livelihoods, and national food security, presenting multidimensional environmental, economic, and social challenges. This study employs a systematic bibliometric analysis to map and evaluate the international scientific literature on Iranian farmers' adaptation to climate change, addressing key quantitative, qualitative, conceptual, and geographic research questions. Materials and methods:  This research utilizes a systematic bibliometric analysis to map and evaluate the international scientific literature concerning Iranian farmers' adaptation to climate change. The focus on internationally indexed sources ensures methodological rigor and global scientific representation. A two-stage systematic search was conducted to identify relevant publications. First, a general search combining terms for adaptation, climate change, and Iran yielded 384 documents, including research articles, reviews, conference proceedings, and books. Second, a refined search incorporating agriculture and farmer-specific terms narrowed the corpus to 140 publications. The bibliographic data from these publications were imported into VOSviewer software for quantitative analysis. Techniques such as co-authorship and keyword co-occurrence analysis were applied to uncover collaboration networks, identify prolific authors and countries, and trace thematic trends and conceptual evolution. This quantitative bibliometric approach provides a data-driven overview of the research landscape, revealing knowledge gaps, methodological tendencies, and priority topics within this critical domain. Results and Discussion:  The findings indicate that scientific production on Iranian farmers' climate adaptation has followed a steadily increasing trend, with international collaborations enhancing both methodological quality and policy relevance. Thematically, most studies have focused on individual and socio-economic factors, vulnerability assessments, and behavioral models, although a significant portion (25%) lacked a clear theoretical framework. Geographically, research has been concentrated in agriculturally intensive and climate-vulnerable provinces such as Khuzestan, Fars, and Azerbaijan. The analysis identified a wide range of adaptive behaviors among farmers, including adjustments to planting dates, the adoption of drought-resistant seeds, improved water management practices (e.g., drip irrigation, rainwater harvesting), the use of innovative technologies like precision agriculture, engagement with economic mechanisms such as crop insurance, participation in educational interventions via extension services, and responses influenced by psychosocial factors like risk perception and self-efficacy. Conclusion: This bibliometric analysis provides a comprehensive, data-driven overview of international research on Iranian farmers' adaptation to climate change, illuminating publication trends, key contributors, collaborative networks, dominant themes, and geographic focus areas. The findings highlight the multifaceted nature of adaptation, underscoring the necessity of integrating social, economic, and environmental factors while also pointing to a need for more robust theoretical frameworks to guide future empirical work. The study reveals significant regional research disparities, advocating for targeted investigations in understudied provinces. Furthermore, the results emphasize the critical role of international cooperation in elevating research quality and policy relevance. These insights can inform strategic planning for climate adaptation policies tailored to Iran's diverse agro-ecological contexts, ultimately supporting resilient agricultural development in the face of ongoing climatic shifts. https://iwm.ilam.ac.ir/article_734243.html Extended Abstract  Introduction: In recent decades, the increased intensity and frequency of flood events due to climate change, urbanization, and land degradation have become a major challenge in water resource management. The occurrence of flash floods in mountainous areas of the country, including the Taleghan watershed, results in consequences such as soil erosion, damage to infrastructure and threats to water resources. Therefore, accurate prediction of flood discharge and hydrological behavior of watersheds is essential for timely decision-making in early warning systems and risk management. The present study aimed to evaluate and compare the performance of three models, XBeach, DBN, and LightGBM, in predicting the maximum monthly flood discharge in the Taleghan watershed.  Materials and methods: The data used included time series of monthly discharge from hydrometric stations in the region over several consecutive years. To evaluate the effect of temporal memory, four different seasonal combinations were designed, including lags of one to four seasons (each season consisting of three months) in the discharge modeling. After preprocessing, standardization and separation into training and test sets, the data were analyzed within the framework of the three models using the R programming software. The physical model XBeach was analyzed as a process-based baseline, while the DBN model was implemented using the structure of dynamic Bayesian networks and probabilistic hidden layers to represent temporal dependencies of the data. The LightGBM model was designed as a gradient boosting tree, with optimization of learning parameters and non-surface growth of trees. The performance of the models was evaluated using the statistical indices NSE, RMSE, MAE and the correlation coefficient (R).  ­­­­­­­­­­­­­­­­­­­­­­­­Results and Discussion: The results showed that the LightGBM model had a significantly better performance than the other two models in all stations and in all temporal combinations. With NSE values ranging from 0.908 to 0.931 and correlation coefficient between 0.896 and 0.918, this model showed the highest degree of agreement with the observed data. Also, the RMSE error values for the LightGBM model at the studied stations ranged from 0.079 to 0.131, indicating the high accuracy of the model in predicting the maximum monthly discharge. The DBN model provided good performance with NSE values between 0.864 and 0.896 and correlation coefficient 0.816 to 0.832, while the XBeach numerical model with NSE values of 0.834 to 0.862 and correlation of 0.807 to 0.823 had lower accuracy than the two data-driven models. Despite the relative superiority of the DBN model over XBeach, the performance difference between the two models was not statistically significant in most temporal combinations. Given the complexity of the network structure and the higher computational cost of DBN, the use of the XBeach model is suggested as a more practical option in the second rank. In addition, the ability of the LightGBM model to reproduce seasonal fluctuations and strong flow trends was more significant than other models. The DBN model also performed better compared to XBeach, but the statistical difference resulting from the evaluation criteria between the two models was not significant in most combinations. Considering the complexity of the network structure, high computation time, and cost of adjusting DBN parameters, the use of the XBeach numerical model is recommended as a more economically and practically efficient option. In contrast, the ability of LightGBM to combine nonlinear features of input data and learn complex patterns made this model the most accurate and stable option for flow prediction.  Conclusion: Correlation analyses between observational and predicted data showed that the points resulting from the LightGBM model had the highest density along the one-to-one correlation line and showed the least dispersion, while the XBeach and DBN models had more deviation from the correlation line. These findings are consistent with recent studies that have reported the effectiveness of gradient boosting algorithms in flow and flood prediction. Overall, the findings of this study suggest that the use of lightweight and fast data-driven models such as LightGBM can play an important role in the development of flood forecasting systems in mountainous basins such as Taleghan. High accuracy, fast update capability, low computational requirements, and the possibility of integrating with remote sensing data make this model a suitable option for use in early warning systems and intelligent water resource management. The main innovation of this research is to provide a quantitative and systematic comparison between lightweight data-driven models, deep learning, and physical process models for predicting the maximum monthly discharge, as well as analyzing the sensitivity of their performance to the input temporal memory length, which leads to the presentation of an operational decision-making framework based on accuracy and computational cost. https://iwm.ilam.ac.ir/article_734255.html Extended Abstract Introduction: Iran’s unique spatial-geographical context renders it highly vulnerable to natural hazards, including floods and droughts. The aim of the present study is to investigate the factors affecting the adaptation of Iranian agricultural communities to natural hazards with an emphasis on floods and droughts (single-hazard studies) and studies on the combination of these hazards (combined studies) occurring in different regions of Iran. Materials and methods: The method of this research is systematic analysis, which is a type of qualitative research method based on secondary sources and is used to examine phenomena and identify categories based on research literature. In previous studies, the concepts of "adaptation" and "adaptation capacity" have often been examined in a well-known analytical framework (concept analysis), but in this study, first the theoretical foundations related to adaptation and its capacity were studied based on a review of relevant sources and literature, and then, using conceptual methodology and systematic analysis, related research conducted in the country in the form of articles, dissertations, and theses included in the databases of Scientific Information Database (SID), Iranian Research Institute for Information Science and Technology (IranDoc), Iran's Publications Database (Magiran), Civilica and Google Scholar were analyzed using Nvivo12 software and in three stages: creating information categories (open coding), selecting one of these categories and placing it in a relationship model (axial coding), and then inferring a classification using the internal relationships of these categories (coding). “Selective” was conducted and factors affecting the adaptation of Iranian agricultural communities to natural hazards were identified. Results and Discussion: The first studies conducted in the field of adaptation in Iran were mostly articles in 1989 in the "Iranian Journal of Agricultural Science" and mostly master's thesis in 2000 at Al-Zahra University, but adaptation studies in the field of natural hazards, especially in rural areas and agricultural communities, have a short life; so that the results obtained from these studies in Iran began in the early 1990s. Based on the inclusion and exclusion criteria, after scientific filtering, 80929 scientific documents, 51 articles and thesis were included in the review process. The highest frequency was related to the "Google Scholar" database and the lowest frequency was related to the "Magiran" database. The highest and lowest number of studies conducted were in 2011 and 2024 (7 studies in each year) and in 2015 (one study), respectively. The most of the studies data were analyzed using statistical tests. ArcGIS software was used to georeference the data and spatially display the data for zoning in the study areas. In the analysis stage and also the interpretation of the output of the documents, three stages were performed: open coding, axial coding, and selective coding in the NVivo12 software environment. The data analysis process in the open coding stage ultimately led to the extraction of 72 concepts, 31 subcategories, and 7 main categories, which include the factors of "educational-extension", "knowledge", "institutional", "technical-infrastructure", "economic", "social", and "agricultural". Conclusion: The results indicate that statistical tests have the highest frequency and the use of analytical techniques has the lowest frequency in the field of study methods of the statistical sample of the research. Also, the most studies conducted in the field of adaptation are in the field of drought and the least studies conducted in the field of flood studies, and social factors (with a frequency of 20.5%) have the highest and educational-promotional factors (with a frequency of 4.3%) have the lowest impact on the adaptation of rural communities in Iran to natural hazards. This indicates that relevant local, provincial and national institutions can increase the level of adaptation of rural communities to natural hazards by developing infrastructure and social capital such as participation, trust, interaction, etc., and make them resilient to such hazards.