Integrated Watershed Management

Integrated Watershed Management

Evaluating the effects of land use change on soil conservation with the InVEST model

Document Type : Original Article

Authors
1 Department of Watershed Management Science and Engineering, Kashan University, Kashan, Iran
2 Department of Watershed Management Science and Engineering, Gorgan University, Gorgan, Iran
3 Department of Watershed Management Science and Engineering, Malayer University, Malayer, Iran
Abstract
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.
Keywords
Subjects

Afifi M E. (2020). Modeling land use changes using Markov chain model and LCM model. Journal of Applied researches in Geographical Sciences, 20(56), 141-158. https://doi.org/10.29252/jgs.20.56.141
Al-Ahmadi, F.S., & A.S. Hames. (2009). Comparison of four classification methods to extract land use and land cover from raw satellite images for some remote arid areas. Kingdom of Saudi Arabia. Earth Science, 20, 167–191. https://doi.org/10.4197/Ear.20-1.9
Asadolahi, Z., & Norozi nazar, M. (2020). Quantification of the ecosystem service of erosion control under the influence of climate change in the Gorgan Rud watershed. Environmental research, 11(21), 3-16. https://doi.org/20.1001.1.20089597.1399.11.21.2.1 (In Persian)
Asadolahi, Z., Salmanmahiny, A., & Mirkarimi, H. (2015). Modeling the supply of sediment retention ecosystem service (Case study: eastern part of Gorgan-rud watershed). Environmental Erosion Research Journal, 5(3), 961-75. https://doi.org/20.1001.1.22517812.1394.5.3.6.6 (In Persian)
Bai, Y., Ochuodho, T. O., & Yang, J. (2019). Impact of land use and climate change on water-related ecosystem services in Kentucky, USA. Ecological Indicators, 102, 51-64. https://doi.org/10.1016/j.ecolind.2019.01.079
Barzali, M., Azimi, M., Abdolhoseini, M., & Lotfi, A., (2022). Evaluating rangeland ecosystem services from the perspective of sediment retention potential using the InVEST software package (Case study: Atrak watershed). Iranian Rangeland and Desert Research, 29(1), 133-144. https://doi.org/10.22092/ijrdr.2022.126019 (In Persian)
Bogdan, S. M., Pătru-Stupariu, I., & Zaharia, L. (2016). The assessment of regulatory ecosystem services: the case of the sediment retention service in a mountain landscape in the southern Romanian Carpathians. Procedia Environmental Sciences, 32, 12-27. https://doi.org/10.1016/j.proenv.2016.03.008
Borselli, L., Cassi, P., & Torri, D. (2008). Prolegomena to sediment and flow connectivity in the landscape: A GIS and field numerical assessment. Catena, 75, 268–277. https://doi.org/10.1016/j.catena.2008.07.006
Cavalli, M., Trevisani, S., Comiti, F., & Marchi, L. (2013). Geomorphometric assessment of spatial sediment connectivity in small Alpine catchments. Geomorphology, 188, 31–41. https://doi.org/10.1016/j.geomorph.2012.05.007
Daneshi, A., Najafinezhad, A., Panahi, M., & Zarandian, A. (2020). Predicting land use change effects on habitat quality of Narmada Dam Basin in Golestan Province. Journal of Degradation and Rehabilitation of Natural Land, 1(1), 120-130. (In Persian)
Deng, Z., Zhu, X., He, Q., & Tang, L. (2019). Land use/land cover classification using time series Landsat 8 images in a heavily urbanized area. Advances in Space Research, 63, 2144-2154. https://doi.org/10.1016/j.asr.2018.12.005
Deore, M.S.J. (2005). Prioritization of Micro-watershed of Upper Bhama Basin on the Basis of Soil Erosion Risk Remote Sensing and GIS Technology. Doctoral Dissertation, University of Pune Pune.
Falahatkar, S., Hosseini, S.M., Salman Mahiny, A.R., & Ayoubi, S. (2016). Prediction of land use/cover change by using LCM model (Case study in Iran). Environmental Researches, 7(13), 163–174. (In Persian)
Fu, Q., Li, B., Hou, Y., Bi, X., & Zhang, X. (2017). Effects of land use and climate change on ecosystem services in central Asia’s arid regions: a case study in Altay Prefecture, China. Science of the Total Environment, 607, 633-646. https://doi.org/10.1016/j.scitotenv.2017.06.241
Haghdadi, M., Heshmati, GH. A., & Azimi, M.S. (2018). Assessment of water yield service on the basis of InVEST tool (Case study: Delichai watershed). Journal of Water and Soil Conservation, 25(4), 275-290. https://doi.org/10.22069/jwsc.2018.14361.2910
Jensen, J. (2005). Introductory digital image processing: A remote sensing perspective (3rd.ed). Upper Saddle River, NJ: Prentice Hall. 526 pp.
Kusi, K. K., Khattabi, A., & Mhammdi, N. (2023). Evaluating the impacts of land use and climate changes on water ecosystem services in the Souss watershed, Morocco. Arabian Journal of Geosciences, 16(2), 126. https://doi.org/10.1007/s12517-023-11206-6
Lang, Y., Song, W., & Zhang, Y. (2017). Responses of the water-yield ecosystem service to climate and land use change in Sancha River Basin, China. Physics and Chemistry of the Earth, 101, 102–111. https://doi.org/10.1016/j.pce.2017.06.003
Lopez-vicente, M., Poesen, J., Navas, A., & Gaspar, L. (2013). Predicting runoff and sediment connectivity and soil erosion by water for different land use scenarios in the Spanish Pre-Pyrenees. Catena, 102, 62–73. https://doi.org/10.1016/j.catena.2011.01.001
Mather, A. S., 1999. Land Use and Cover Change, Land Use Policy, 16, 143.
Mohammadyari, F. (2023). Evaluation the effects of land use changes on ecosystem services based on the InVEST model (Case study: Chaharmahal and Bakhtiari province). Town and Country Planning, 15 (2), 327-342. https://doi.org/10.22059/jtcp.2023.365685.670408 (In Persian).
Nikkami, D. and Mahdian, M. H. (2015). Rainfall erosivity mapping in Iran. Watershed Engineering and Management6(4), 364-376. https://doi.org/10.22092/ijwmse.2015.100819 (In Persian).
Ochoa, V., & Urbina-Cardona, N. (2017). Tools for spatially modeling ecosystem services: publication trends, conceptual reflections and future challenges. Ecosystem Services, 26, 155-169. https://doi.org/10.1016/j.ecoser.2017.06.011
Renard, K.G., Foster, G.R., Weesies, G.A., McCool, D.K., & Yoder, D.C. (1997). Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE). Washington, DC: United State Department of Agriculture.
Roose, E. (1996). Land Husbandry Components and Strategy. Rom. FAO.
Sahle, M., Saito,O., Fürst, C., & Yeshitela, K. (2019). Quantifying and mapping of water-related ecosystem services for enhancing the security of the food-water-energy nexus in tropical data–sparse catchment. Science of the Total Environment, 646, 573-586. https://doi.org/10.1016/j.scitotenv.2018.07.347
Shalaby, A., & Tateishi, R. (2007). Remote Sensing and GIS for mapping and monitoring land cover and land use changes in the Northwestern coastal zone of Egypt. Applied Geography, 27 (2007), 28-41. https://doi.org/10.1016/j.apgeog.2006.09.004
Sharp, R., H.T. Tallis, T. Ricketts, A.D. Guerry, S.A. Wood, R. Chaplin-Kramer, E. Nelson, D. Ennaanay, S. Wolny, N. Olwero, K. Vigerstol, D. Pennington, G. Mendoza, J. Aukema, J. Foster, J. Forrest, D. Cameron, K. Arkema, E. Lonsdorf, C. Kennedy, G. Verutes, C.K. Kim, G. Guannel, M. Papenfus, J. Toft, M. Marsik, J. Bernhardt, R. Grif- fin, K. Glowinski, N. Chaumont, A. Perelman, M. Lacayo, L. Mandle, P. Hamel and A.L. Vogl. (2018). InVEST User's Guide. The Natural Capital Project, Stanford, 307 pp.
Sharp, R., Tallis, H.T., Ricketts, T., Guerry, A.D., Wood, S.A., Chaplin-Kramer, R., Nelson, E., Ennaanay, D., Wolny, S., Olwero, N., Vigerstol, K., Pennington, D., Mendoza, G., Aukema, J., Foster, J., Forrest, J., Cameron, D., Arkema, K., Lonsdorf, E., Kennedy, C., Verutes, G., Kim, C.K., Guannel, G., Papenfus, M., Toft, J., Marsik, M., Bernhardt, J., Grif- fin, R., Glowinski, K., Chaumont, N., Perelman, A., Lacayo, M., Mandle, L., Hamel, P. and Vogl, A.L. (2014). InVEST User's Guide. The Natural Capital Project, Stanford.
Singh, P., & Khanduri, K. ( 2011). Land use and land cover change detection through Remote Sensing & GIS technology: case study of pathankot and dhar kalan tehsils, Punjabl. International Journal of Geomatics and Geosciences, 4, 839-846.
Sougnez, N., Wesemael, B., & Vanacker, V. (2011). Low erosion rates measured for steep sparsely vegetated catchments in southeast Spain. Catena, 84, 1–11. https://doi.org/10.1016/j.catena.2010.08.010
Vigerstol, K. L., & J. E. Aukema., (2011). A comparison of tools for modeling freshwater ecosystem services. Journal of Environmental Management, 92(10), 2403-2409. https://doi.org/10.1016/j.jenvman.2011.06.040
Vigiak, O., Borselli, L., Newham, L.T.H., Mcinnes, J., & Roberts, A.M. (2012). Comparison of conceptual landscape metrics to define hillslope-scale sediment delivery ratio. Geomorphology, 138, 74–88. https://doi.org/10.1016/j.geomorph.2011.08.026
Vogl, A., Tallis, H., Douglass, J., Sharp, R., Wolny, S., Veiga, F., Benitez, S., León, J., Game, E., Petry, P., Guimerães, J., Lozano, J.S. (2016). Resource Investment Optimization System (RIOS), Introduction and Theoretical Documentation. United Nations, Stanford (CA).
Wang, S., Hu, M., Wang, Y., & Xia, B. (2022). Dynamics of ecosystem services in response to urbanization across temporal and spatial scales in a mega metropolitan area. Sustainable Cities and Society, 77, 103561. https://doi.org/10.1016/j.scs.2021.103561
Xie, Z., Li, X., Chi, Y., Jiang, D., Zhang, Y., Ma, Y., & Chen, S. (2021). Ecosystem service value decreasesmore rapidly under the dual pressures of land use change and ecological vulnerability: A case study inZhujiajian Island. Ocean & Coastal Management, 201, 105493. https://doi.org/10.1016/j.ocecoaman.2020.105493
Zabihi, M., Moradi, H., Khaledi Darvishan, A., & Gholamalifard, M. (2021). Application of InVEST ecosystem services model to prioritize sub-watersheds of Talar in term of soil erosion, sediment retention and yield. Environment and Water Engineering, 7(2), 293-303. https://doi.org/10.22034/jewe.2020.257980. 1470
Zarandian, A., Mohammadyari, F., Mirsanjari, M. M., & Visockiene, J. S. (2023). Scenario modeling to predict changes in land use/cover using Land Change Modeler and InVEST model: a case study of Karaj Metropolis, Iran. Environmental monitoring and assessment, 195(2), 273. https://doi.org/10.1007/s10661-022-10740-2
Zhang, X., F. Zhang, Y. Qi, L. Deng, X. Wang & S. Yang. (2019). New research methods for vegetation information extraction based on visible light remote sensing images from an unmanned aerial vehicle (UAV). International Journal of Applied Earth Observation and Geoinformation, 78, 215–226.  https://doi.org/10.1016/j.jag.2019.01.001 
Volume 6, Issue 1 - Serial Number 19
Spring 2026
Pages 147-163

  • Receive Date 02 July 2025
  • Revise Date 25 August 2025
  • Accept Date 10 September 2025