Integrated Watershed Management

Integrated Watershed Management

Evaluation of the Sensitivity of the Empirical Model of MPSIAC Parameters on Sediment Yield in the Basin

Document Type : Original Article

Authors
Mehdi Hayatzadeh 1
Vahid Moosavi 2
Esmaeil Soheili 3
1 Department of Watershed Management Engineering, Faculty of Agriculture and Natural Resources, Ardakan University, Ardakan, Iran.
2 Department of Watershed Management Engineering, Faculty of Natural Resources, Tarbiat Modares University, Tehran, Iran.
3 Department of Agricultural Engineering, Faculty of Basic Sciences, University of Darab, Shiraz university, Iran.
10.22034/iwm.2024.2016898.1117
Abstract
Extended Abstract
Introduction: The study of erosion and sedimentation is a crucial aspect and an integral part of watershed studies in a basin. The methods employed to prevent erosion and sedimentation play a significant role in basin management planning. However, due to the lack of accurate statistics on erosion and sediment amounts, it becomes necessary to utilize estimation models for assessing erosion and sedimentation. These models are often region-specific and may have a wide range of uncertainty in different areas. One notable benefit of modeling, regardless of its type, is its ability to analyze natural processes within the basin. On the other hand, understanding erosion and sedimentation processes in a region can be an effective step in managing, planning, and prioritizing available resources. In this research, the aim was to determine the sensitivity of the MPSIAC model to the relationships among its parameters. Additionally, the goal was to assess the model's sensitivity to changes in these parameters and their impact on sedimentation. By identifying the influential ground and atmospheric parameters, it becomes possible to prioritize their effect on water sedimentation in the region.
Materials and methods: Through the sensitivity analysis of the model, it is possible to identify the flexibility of the model to the changes of its various parameters. It is also possible to determine the relationships between model variables and prioritize the parameters affecting the model output. Sensitivity analysis can be used in the calibration stage, in such a way that results are accurate, and time and cost are saved. In this study, to analyze the sensitivity of the MPSIAC model, first, the nine parameters of the model were examined. Then, according to the arrangement of different parameters in the structure of this model, the parameters were numbered from X1 to X9. Then, the score range of each parameter was entered in its calculation table according to the modified model of PSIAC. In this step, the average of each parameter was calculated according to its upper and lower limits. To achieve this, the nine parameters of the model were standardized, and the sedimentation rate was estimated by varying each parameter within its lower and upper limits while keeping the other parameter(s) fixed at their averages. With each change, the sediment discharge was calculated.
Results and Discussion: In the analysis of the results, the slope of the curves of the standardized parameters relative to the dependent variable (specific sediment) is considered. So that, any part of the curve that has more slope changes means that the model is more sensitive to minor changes in that parameter in that interval. In this study, the results of this sensitivity analysis reveal that the slope factor and runoff volume have a considerable influence on sediment yield. For slopes up to approximately 15%, the slope parameter has a relatively smaller impact compared to other parameters. However, as the slope value increases, its effect becomes more pronounced, indicating that high slopes (greater than 15%) have the greatest impact on sedimentation. The runoff factor exhibits a sudden increase in sensitivity at higher flow rates.
Conclusion: In examining the effect of different parameters on the model performance, the parameters that had the largest slope of changes can be considered as the most effective parameters in sedimentation of the basin. In other words, the model demonstrates high sensitivity to slight changes in specific peak discharge values above 20 m³/s/km2. Therefore, implementing integrated (biomechanical) management measures to control slope steepness and reduce runoff volume can be an effective strategy for mitigating sedimentation. Therefore, based on the results, the role of land factors is very important, such as slope and then runoff, in the erodibility and sediment production in basins. Of course, it should be noted that climatic parameters directly and indirectly affect the amount of peak flood discharge and should not be neglected for their importance and influence in flooding and subsequently the erodibility of the watershed.
Keywords
Sensitivity Analysis
MPSIAC Model
Sediment Yield
Water Erosion

Subjects

Avarand, R., Torabi Poodeh, H. & Farzaei, A. (2006). Analysis of sensitivity of HEC-1 model to input parameters, 7th International Seminar on River Engineering. (In Persian)
Barker, D. W., Sawyer, J. E., Al-Kaisi, M. M. & Lundvall, J. P. (2006). Assessment of the amino sugar-nitrogen test on Iowa soils: II. Field correlation and calibration. Agronomy journal, 98(5), 1352. https://doi.org/10.2134/agronj2006.0034.
Borooshke, E., & Sokouti, R. (2018). Comparative efficacy of some empirical models to sediment yield in small catchments. J. Agri. Forest, 64 (2), 163-173. https://doi.org/10.17707/AgricultForest.64.2.12
Bahremand, A., De Smedt, F., Corluy, J., Liu, Y. B., Poórová, J., Velcická, L. & Kuniková, E. (2007). WetSpa model application for assessing reforestation impacts on floods by in Margecany–Hornad watershed, Slovakia. Water Resour. Manag, 21, 1373–1391. https://doi.org/10.1007/s11269-006-9089-0.
Chi, M. Ho., Roger, A. Cropp and Roger D. Braddock. (2005). On the Sensitivity Analysis of Two Hydrologic Models. Congress on Modelling and Simulation (CMS).
Daneshafraz, R., Rahmati, M. & Akbari Moghanji, Q. (2017). Soil erosion and sediment mapping in Aidoghmoush watershed using MPSIAC model and GIS and RS technologies. J. Environ. Resour. Re, 5(1), 35-49. https://doi.org/10.22069/ijerr.2017.9991.1119.
Dastorani, M. T. & Hayatzadeh, M. (2010). Reviews the Most Important Factors in the Maximum Flood Discharge by Sensitivity Analysis Empirical. Arid Biom Scientific and Research Journal. 1(1), 1-12. https://doi.org/20.1001.1.2008790.1389.1.1.1.5
Ebrahimi, N. (2019). Estimation of erosion and sediment production with MPSIAC model (Case Study: Banrahman Basin, Ilam Province), Proc. 14th Int. Conf. Watershed Management Science and Engineering of Iran with the focus on watershed management and comprehensive soil and water management, Urmiah, Iran (In Persian).
Ghaderi, M., Dastorani, M.T. & Saber, K. (2015). Sensitivity analysis of two flow velocity formulae and evaluation of important factors effecting of flow velocity. Watershed Management Researches (Pajouhesh-Va-Sazandegi), 28(107), 73-83. https://doi.org/10.22092/WMEJ.2015.107087.
Hasanlo, M. (2003). Determining the intensity of soil erosion and sedimentation in the Taham Chay watershed using the PSIAC model and GIS. Geomatic conference.
Jamali, A. (2001). Investigating the sensitivity of a number of experimental hydrological methods for estimating the peak flood discharge with respect to the watershed level in some watersheds of Iran. Master thesis of Tarbiat Modares University. (In Persian)
Johnson, C.W. & Gebhardt, K.A. (1982). Predicting sediment yields from saga brush rangeland, Proceedings of the workshop on estimating erosion and sediment yield on rangeland, Tucson, Arizona. US department of agriculture, Agricultural Reviews and manuals, Western series, 26, 145-156.
Foglia, L., Hill, M. C., Mehl, S. W. & Burlando, P. (2009). Sensitivity analysis, calibration, and testing of a distributed hydrological model using error‐based weighting and one objective function. Water Resources Research, 45(6). https://doi.org/10.1029/2008WR007255.
Khaledian, H. & Nikkami, D. (2017). Optimization of land use to reduce the potential of erosion and sediment using linear programming model (Case study: Chehel-Gazi basin of Sanandaj). Journal of Water and Soil Science. 21 (1), 95-111. https://doi.org/10.18869/acadpub.jstnar.21.1.95
Khoda Rahimi, R. (2005). Investigating the effectiveness of EPM and MPSIAC experimental methods in estimating erosion and sedimentation in Kharestan watershed, Fars. Master's thesis, Mazandaran University.
Kousari, M. R., Saremi Naeini, M. A., Tazeh, M. & Frozeh, M. R. (2010). Sensitivity analysis of some equations for estimatingof time of concentration in watersheds. Journal of Arid Biome, 1(1), 57-67. https://doi.org/20.1001.1.2008790.1389.1.1.6.0. (In Persian).
Kamali Maskooni, E., Adelpour, A. A. & Pirnia, A. (2016). Evaluation of the effect of slope gradient on threshold of erosion (gully) in flood spreading projects. Watershed Management Research Journal, 29(4), 20-29. https://doi.org/10.22092/WMEJ.2017.115315. (In Persian).
Maghsoudi, M., Shadfar, p. & Abbasi, M. (2012). Landslide sensitivity zoning to gully erosion in Zavaryan basin of Qom province. Quantitative Geomorphology Researches, 1(2), 35-52. https://doi.org/20.1001.1.22519424.1391.1.2.3.7. (In Persian).
Memariyan, H., & Dehghan, H. (2019). Sensitivity and uncertainty analysis of sediment rating equation coefficients using the Monte-Carlo simulation (Case study: Zoshk-Abardeh watershed, Shandiz). Jwmseir; 13 (44), 90-102. https://doi.org/20.1001.1.20089554.1398.13.44.11.3.
Motamedirad, M., Zangane Asadi, M. A. & Ajam, H. (2023). Investigating the rate of soil erosion and sediment production using the RUSLE model and the modified method PSIAC (case study: kal basin of Ismail, Shahrood city, Semnan province). Quantitative Geomorphological Research, 11(4), 147-165. (In Persian). https://doi.org/10.22034/GMPJ.2022.360813.1374.
Nikpour, N., Fotohi, S., Negaresh, H. & Sistani, M. (2017). Morphometric of gully erosion (ditch) and factors affecting the development of the basin plains on southern west Ilam Cham Fazel. Spatial analysis of environmental hazards, 4 (1), 97-112. (In Persian).
Nourani, V. & Mohsenzadeh, S. (2017). Monthly Sediment Load Estimation of Aji Chay Basin Stations Using MPSIAC Model and Cascade Exponential Sub-cales. Hydrogeomorphology, 4(11), 83-103. https://doi.org/20.1001.1.23833254.1396.4.11.5.6
Refahi, H. (2003). Water erosion and its Control.Tehran University Press. (In Persian).
Shojaei, S. H., Nora, M. & Habibi, S. (2017). Estimation of sedimentation and erosion using MPSIAC and FSM experimental models and direct measurement method (Case study: Gabrik watershed, southeast of Iran). J. Environ. Erosion Res, 8(4), 82-100. https://doi.org/20.1001.1.22517812.1397.8.4.5.8. (In Persian).
Talebi, A., Poormohammadi, S. & Rahimian, M. (2010). Investigation of Effective Factors on Reference Evapotranspiration using Sensitivity Analysis of FAO-Penman-Monteith Equation (Case-study: Yazd, Tabas and Marvast stations). Physical Geography Research Quarterly, 42(73), 97-109. (In Persian).
Zhang, R., Liu, X., Heathman, GC. Yao, X., Hu, X. & Zhang, G. (2013). Assessment of soil erosion sensitivity and analysis of sensitivity factors in the Tongbai–Dabie mountainous area of China. CATENA, 101, 92-98. https://doi.org/10.1016/j.catena.2012.10.008.
Zabihi Silabi, M. & Khaledi Darvishan, A. (2021). Qualitative Evaluation of IntErO, EPM, MPSIAC and RUSLE Models in Order to Select the Optimal Models for Different Conditions for Description of Detailed-Executive Watershed Management Services. Extension and Development of Watershed Management, 9(32), 52-66.

  • Receive Date 03 December 2023
  • Revise Date 24 January 2024
  • Accept Date 06 February 2024