Estimating the amount of Erosion and Sedimentation in Zimkan Watershed Basin in Kermanshah Province with an Emphasis on Influencing Variables

جغرافیا و مخاطرات محیطی

Article 10, Volume 14, Issue 1 - Serial Number 53, March 2025, Pages 210-226   

Document Type: Research Article

DOI: 10.22067/geoeh.2023.79388.1293

Authors

Shahram Roostaei^{* 1}; Asadolah Hejazi²; Hedyeh Shirzadi³

¹Professor in Geomorphology, Department of Physical Geography, Tabriz University, Tabriz Iran

²Associate Professor in Geomorphology, Department of Physical Geography, Tabriz University, Tabriz, Iran

³Ph.D in Geomorphology,Department of Physical Geography, Tabriz University, Tabriz, Iran

Abstract

Soil erosion is one of the most important problems that has affected human life in recent years. The type and intensity of soil erosion in a region depend on climatic conditions, altitude, soil, and land use. Meanwhile, the importance of land use is greater than other factors due to the effective role of humans in influencing it. In this research, to estimate the amount of erosion and sedimentation in the Zimkan watershed, we used two methods, MPSIAC and EPM, each of which evaluates nine factors (geology, soil, climate, water flow, elevation, vegetation, land use, landform, and river erosion) and four factors (erosion, land use, soil sensitivity, and the average slope of the basin), respectively. Then, ArcGIS software and Sentinel-2 satellite sensor images were used in the ENVI 5.3 environment to prepare the related layers. The results showed that the erosion values in the MPSIAC and EPM models were 5,142.9 and 6,401.2 tons per year, respectively, and the amounts of sediment were 2,461.25 and 3,624.72 tons per year, respectively. The erosion class and severity of the basin's erodibility, in terms of soil loss, are in critical condition. The highest intensity of erosion and sediment production was observed in the outlet sections of the basin. It is necessary to implement management and protection policies at the watershed level. It was also found that the results of the MPSIAC method are closer to the actual observations in the basin than those of the EPM method.
Extended Abstract
Introduction
The amount of erosion in a watershed can be determined if there are sufficient records of discharge and sediment data by applying statistical methods. However, in many basins across the country, there are no measurements of soil erosion and sediment production, which requires the use of experimental methods to estimate soil erosion. To estimate the amount of sediment and erosion in a region, there are many methods, including the modified global equation of soil erosion. This model is a suitable method for calculating soil losses because the results show no significant difference from those measured in the region.
Material and Methods
The Zimkan or Zamkan river basin is located in the north of Dalaho city and the west of Kermanshah province. The drainage pattern of this basin is rectangular with an area of 2,324 square kilometers and flows from the southeast to the northwest. This basin is bounded from the west by the Piran basin and from the north by the Posht Teng basin and the Lima river basin. The basin is located at the geographical coordinates of 46°4'30" to 46°11'8" east longitude and 34°35'44" to 34°22'56" north latitude. The research was conducted using two models for comparison, and the methodologies of these two models and their outputs are introduced below.
EPM Model
Introduced in 1988 by Gavrilovic at the international conference on river regimes for estimating the amount of erosion and sedimentation, this model was applied after 40 years of research on erosion plots in Yugoslavia. This model estimates reliable and acceptable results of the erosion rate with four main factors. The factors of this model are mentioned in the table, and after scoring and processing the data with the help of ARC/GIS software, they were calculated.
MPSIAC Model
The PSIAC method was presented in 1968 by the Water Management Committee in the United States for calculating the intensity of soil erosion and sediment production in arid and semi-arid areas. This method was modified in 1982. In Iran, this model was implemented for the first time in 1973 in the Dez Dam watershed, and it evaluates nine factors to calculate erosion and sediment production. Each of these factors has been examined from both quantitative and qualitative perspectives, with five qualitative grades and quantitative scores ranging from -10 to +25.
Results and Discussion
This research was conducted with the aim of estimating the erosion and sedimentation of the study area using EPM and MPSIAC models and comparing the results with actual measurements. To present the results, the final layers were classified and information was extracted from them. By preparing the required maps from the layers of the previous stage and analyzing the obtained information layers, appropriate outputs were prepared.
Conclusion
The difference between the calculated values of the annual sediment amounts by the MPSIAC method is small. This is in contrast to the EPM model, where this difference is large, demonstrating the accuracy of the MPSIAC model in estimating the amount of sediment.
Additionally, the low erosion class covers the largest area of the basin, accounting for about 58% of the total area, while the high and medium erosion classes cover nearly the same area. This nevertheless indicates that the study area is predominantly affected by erosion. Finally, the specific and annual sediment yields of the Zimkan catchment calculated by the EPM and MPSIAC models show that the sediment delivery ratio and specific erosion estimates in this basin differ significantly between the two models. Based on this, the EPM model produced higher estimates for both parameters. Therefore, it can be concluded that the MPSIAC model is more reliable, as its outputs are closer to reality.

Keywords

Zimkan Watershed Basin; Soil Erosion Modeling; EPM(Erosion Potential Method); MPSIAC(Modified PSIAC); Sediment Yield Estimation; GIS-Based Assessment

References

Asghari Saraskanrood, S., Mozaffari, H., & Esfandiari, F. (2022). Modeling the Erosion and Sedimentation Rate of Sojasrood River before and after Construction of Golaber Dam with Machine Learning Algorithms. Environmental Erosion Research Journal, 12(2) ,172-204. [In Persian]  https://dor.isc.ac/dor/20.1001.1.22517812.1401.12.2.12.9

Esmali Ouri, A., & Abdollahi, K. (2010). Watershed management and soil conservation. Ardabil: Mohaghegh Ardabili Publications. [In Persian]

Gavrilovic, Z. (1988). Use of an Empirical Method(Erosion Potential Method) for Calculating Sediment Production and Transportation in Unstudied or Torrential Streams. In International Conference on River Regime. Hydraulics Research Limited, Wallingford, Oxon UK. 411-422.

Ghazawi, R., Wali, A. A., Maghami, Y., Abdi, Z., & Sharafi, S. (2012). Comparison of EPM, MPSIAC and PSIAC models in estimating erosion and sedimentation using GIS. Geography and development, 10(27), 117-126. [In Persian] http://dx.doi.org/10.22111/GDIJ.2012.488

Grauso, S., Fattoruso, G., Crocetti, C., & Montanari, A. (2007). A spatially distributed analysis of erosion susceptibility and sediment yield in a river basin by means of geomorphic parameters and regression relationships. Hydrology and Earth System Sciences Discussions, 4(2), 627-654. http://dx.doi.org/10.5194/hessd-4-627-2007

Guzmán, G., Barrón, V., & Gómez, J. A. (2010). Evaluation of magnetic iron oxides as sediment tracers in water erosion experiments. Catena, 82(2), 126-133. https://doi.org/10.1016/j.catena.2010.05.011

Hashemi, S. A. A., & Arab Khedri, M. (2008). Evaluation of EPM Model by Sediment Measurement in Reservoirs of Small Dams. Journal of Crop Production and Processing, 11(42), 345-355. [In Persian]  http://dorl.net/dor/20.1001.1.22518517.1386.11.42.28.7

Hejazi, A., Ahmadi, A., & Shahabi, H. (2018). Estimates of erosion amount and sediment production in the Kangir watershed in Ilam Province using E.P.M model. Journal of Natural Environmental Hazards, 7(16), 1-22. [In Persian] https://journals.usb.ac.ir/article_3628.html

Kassas, M. (1984). The global biosphere: Conservation for survival. World Futures: Journal of General Evolution, 19(3-4), 209-222. https://doi.org/10.1080/02604027.1984.9971981

Mezbani, M., Rezaei Moghadam, M. H., & Hejazi, A. (2021). Assessment of soil erosion risk in land uses using Revised Universal Soil Loss Equation (Case Study: Sikan Basin). Journal of Geography and Environmental Hazards, 10(1), 41-63. [In Persian]  https://doi.org/10.22067/geoeh.2021.67238.0

Miguel, P., Samuel-Rosa, A., Dalmolin, R. S. D., PEDRON, F., Bueno, J. M. M., & Balbinot, A. (2011). The USLE model for estimating soil erosion in complex topography areas. Anais XV Simpósio Brasileiro de Sensoriamento Remoto-SBSR, 85, 9227-9230. http://marte.sid.inpe.br/col/dpi.inpe.br/marte/2011/07.07.14.41/doc/p1441.pdf

Moghimi, E., & Mahmoodi, F. (2005). The research method of Naural Geography. Tehran: Ghomes. [In Persian] 

Morgan, R. P. C., & Nearing, M. A. (2011). The future role of information technology in erosion modeling. Hand Book of Erosion Modeling.

Nayyeri, H., Salari, M., & Chardawli, Z. (2021). Prioritization of Linear Erosion Using Morphometric and Geomorphological Indicators Case Study: Gheshlagh Watershed, Sanandaj West of Iran. Hydrogeomorphology, 8(28), 191-214. [In Persian]  https://doi.org/10.22034/hyd.2021.47623.1601

Nwaogu, C., Okeke, O. J., Assuah Adu, S., Babine, E., & Pechanec, V. (2017). Land use—Land cover change and soil-gully erosion relationships: A study of Nanka, South-Eastern Nigeria using geoinformatics. In Proceedings of GIS Ostrava. Cham: Springer International Publishing, 305-319.

Prasannakumar, V., Vijith, H., Abinod, S., & Geetha, N. J. G. F. (2012). Estimation of soil erosion risk within a small mountainous sub-watershed in Kerala, India, using Revised Universal Soil Loss Equation (RUSLE) and geo-information technology. Geoscience frontiers, 3(2), 209-215. https://doi.org/10.1016/j.gsf.2011.11.003

Rahman, M. R., Shi, Z. H., & Chongfa, C. (2009). Soil erosion hazard evaluation—an integrated use of remote sensing, GIS and statistical approaches with biophysical parameters towards management strategies. Ecological Modelling, 220(13-14), 1724-1734. http://dx.doi.org/10.1016/j.ecolmodel.2009.04.004

Rasouli, A. A. (2007). An analytic approach to GIS technology. Tabriz: University of Tabriz. [In Persian]

Rastgoo, S., Ghahraman, B., Sanei Nejad, H., Davary, K., & Khodashenasi, S. R. (2006). Estimation of Erosion and Sedimentation of Tang-e-Kenesht Basin with Empirical Models of MPSIAC and EPM Using GIS. Journal of Water and Soil Science, 10(1), 91-105. [In Persian] http://dorl.net/dor/20.1001.1.24763594.1385.10.1.7.2

Refahi, H. (2016). Water erosion and its control. Tehran: University of Tehran. [In Persian]

Sadeghi, S. H., Mostafazadeh, R., & Sadoddin, A. (2015). Response of Sedimentgraphs and Sediment Rating Loops to Land Use Type and Spatial Pattern. Watershed Engineering and Management, 7(1), 15-26. [In Persian] https://doi.org/10.22092/ijwmse.2015.100900

Sadogh, S. H., Hosseinzadeh, M. M., & Azadi, F. (2015). Determining the Erosion in Kahman Drainage Basin Using EPM, BLM and Fargas Models. Hydrogeomorphology, 2(2), 137-154. [In Persian] https://dor.isc.ac/dor/20.1001.1.23833254.1394.2.2.8.7

Shirzadi, H. (2009). Landslide potential on the new road from Sanandaj to Marivan using the AHP model. Master's thesis, University of Tehran. [In Persian]

Talebi Khiavi, H., Zabihi, M., & Mostafazadeh, R. (2017). Effects of Land-use Management Scenarios on Soil Erosion Rate using GIS and USLE Model in Yamchi Dam Watershed, Ardabil. Journal of Water and Soil Science, 21(2), 221-234. [In Persian] http://dx.doi.org/10.18869/acadpub.jstnar.21.2.221