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Soil Conservation and Watershed Management Research Department, Ilam Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran. , shamsasgari@yahoo.com
Abstract:   (559 Views)

1- Introduction
The Ilam Basin, located in the southwest of Ilam Province, with Ilam City and Chavar City, in the north of this basin, is highly sensitive to gully erosion due to its climatic, topographic, and lithological characteristics. Gully erosion is active in this area, and sometimes the length of the gully reaches more than 200 meters. Considering that the study area is structurally located in the folded Zagres geological region with a specific morphology, topographic features or indicators resulting from the geological structure, along with other inherent factors such as lithology, vegetation cover, and climate, play an effective role in the occurrence of gully erosion. Also, due to the high sensitivity of the surface layers of the soil and in some parts of the surface and deep layers of the soil, runoff causes the creation of furrows and, in the later stages, ditches in the study area. Since the effect of ditch erosion on land degradation in the study area is several times greater than other types of water erosion, therefore, considering the aforementioned materials, the purpose of this study is to implement the maximum entropy model in order to determine the threshold of ditch erosion, the influencing factors and indicators, prepare a ditch erosion zoning map, and evaluate and validate the prediction maps of sensitivity to ditch erosion in order to increase the accuracy of prediction maps for ditch erosion.

2- Methodology
In this study, the capability of the maximum entropy model was used to zone the susceptibility of gully erosion. Using Google Earth images and field visits, 331 gully points were identified and recorded, and a gully distribution map was prepared. The spatial data of gully erosion distribution were divided into two random groups: training (70%) and experimental (30%). 23 factors affecting the occurrence of gully erosion (including slope curvature indices, profile curvature index, convergence index, curvature classification index, watershed area, watershed power index, watershed length-slope factor, topographic moisture index, elevation, slope gradient, slope direction, light and shade analysis index, drainage density map and distance from drainage network, lithology, soil type and depth characteristics, vegetation cover index (NDVI), land use and average precipitation, and Demarton climate layer) were used in the model analysis.

3- Results
     In this study, a method for identifying gullies was presented, and 331 gullies were recorded, and the gullies' boundaries and points were specified, and the gullies' distribution layer of the watershed was prepared for the first time in the Ilam watershed. The study of the Collinearity between the independent variables on gullies' erosion increased the accuracy of the model's prediction. The response curves to the sensitivity of gullies' erosion extracted from maximum entropy introduced the research method in terms of science, quantitative, mathematical and statistical regularity, and in the Ilam watershed, the relationship and effect of the indicators or independent variables with the dependent variable of gullies' erosion and gullies' erosion threshold were explained. The results of the classification of the gulley erosion susceptibility zoning map using the maximum entropy model showed that the percentage of the area of ​​the gulley erosion susceptibility classes of very high, high, medium, low and very low in the Ilam basin are 12.98, 24.05, 31.90, 11.58 and 19.49, respectively. Also, the percentage of gulley erosion occurrence in the very high, high, medium, low and very low sensitivity classes in the Ilam basin are 86.02, 12.16, 1.22, 0.30 and 0.30, respectively. In other words, the very high and high sensitivity classes have accounted for more than 37 percent in the Ilam basin in total. In general, based on the maximum entropy model, more than 80 percent of gulley erosion occurrences are in the two sensitivity classes of very high to high.
4- Discussion & Conclusions
The results of model validation from the ROC system performance characteristic curve and the area under the AUC graph obtained from the calibration points (30%) showed that the model had an acceptable percentage of the area under the curve, which indicates the high performance of this model in the region. The entropy model with 90.9% of the area under the graph has the best performance for gulley erosion sensitivity zoning, which is consistent with the research of Saeedian et al. (2023). The results of the response curve analysis of gulley erosion sensitivity thresholds and the Jackknife test diagram showed that topographic factors, watercourse density, lithology, land use, climate type, vegetation cover and precipitation have the greatest impact on gulley erosion. Research proposal: This model can be used in other regions for gulley erosion zoning, and the implementation proposal is to plan control and protection measures according to the influential factors introduced in this research in gulley erosion.
 
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Received: 2025/04/23

References
1. Alencar, P.H.L., Simplício, A.A.F., de Araújo, J.C., (2022). Entropy-based Model for Gully Erosion - A combination of probabilistic and deterministic components, Science of The Total Environment, 836(155629), 0048-9697, https://doi.org/10.1016/j.scitotenv.2022.155629 [DOI:10.1016/j.scitotenv.2022.155629.]
2. Arabameri, A. , rezaei, K. , yamani, M. and shirani, K. (2019). Optimization of gully erosion susceptibility using data-driven statistical combined methods (case study: Toroud-Najar Abad basin). Researches in Earth Sciences, 10(1): 18-38. https://doi.org/ 10.52547/esrj.10.1.18. (In Persian). https://doi.org/10.52547/esrj.10.1.18 [DOI:10.52547/esrj.10.1.18. (In Persian).]
3. Azareh.A, Rahmati.O, Rafiei-Sardooi.E, Joel B. Sankey, Lee.S, Shahabi.H, Bin Ahmad.B, (2019), Modelling gully-erosion susceptibility in a semi-arid region, Iran: Investigation of applicability of certainty factor and maximum entropy models, Science of the total Environment, 655(10):684-696. https://doi.org/10.1016/j.scitotenv.2018.11.235 [DOI:10.1016/j.scitotenv.2018.11.235. (In Persian).]
4. Bernini, Alice, Alberto Bosino, Greg A. Botha, and Michael Maerker. 2021. "Evaluation of Gully Erosion Susceptibility Using a Maximum Entropy Model in the Upper Mkhomazi River Basin in South Africa" ISPRS International Journal of Geo-Information 10(11): 715-729. https://doi.org/10.3390/ijgi10110729 [DOI:10.3390/ijgi10110729.]
5. Conforti, Massimo, and Fabio Ietto. 2024. "Testing the Reliability of Maximum Entropy Method for Mapping Gully Erosion Susceptibility in a Stream Catchment of Calabria Region (South Italy)" Applied Sciences 14(1): 240-261. https://doi.org/10.3390/app14010240 [DOI:10.3390/app14010240.]
6. Ejtemaei B, Moghtaderi G. 2025. Zoning and Analysis of Temporal and Spatial Changes in Gully Erosion and Its Impact on the Villages of the Mond Watershed during the Years 2000 to 2024. E.E.R. 15 (1):105-119. https://doi.org/ 10.61186/jeer.15.1.105. (In Persian). https://doi.org/10.61186/jeer.15.1.105 [DOI:10.61186/jeer.15.1.105. (In Persian).]
7. Khazaei M, Shirani K, Saleh I. 2024. Susceptibility modeling and determining the contribution of factors affecting gully erosion. E.E.R., 14 (3):123-141. https://doi.org/ 10.61186/jeer.14.3.123.(In Persian). https://doi.org/10.61186/jeer.14.3.123 [DOI:10.61186/jeer.14.3.123.(In Persian).]
8. Kou M., Jiao J., Yin Q., Wang N., Wang Z., Li Y., Yu W., Wei Y., Yan F., Cao B. 2016. Successional trajectory over 10 years of vegetation restoration of abandoned slope croplands in the hill‐gully region of the Loess Plateau. Land Degradation & Development, 27(4): 919-932. https://doi.org/ 10.1002/ldr.2356 [DOI:10.1002/ldr.2356]
9. Madadi, A., Asghari Saraskanroud, S., Negahban, S., Marhamat, M. (2022). 'Evaluation of Gully Erosion Sensitivity using Maximum Entropy Model in Shoor River Watershed (Mohr Township), Journal of Geographyand Environmental Hazards,11(3): 123-145.https://doi.org/ 10.22067/geoeh.2022.76707.1228. (In Persian). [DOI:10.22067/geoeh.2022.76707.1228. (In Persian).]
10. mohamdkhan, S., pirani, P., riahi, S. and geravand, F. (2020). Evaluation of entropy model efficiency in erosion zoning of kand watershed with geomorphologic approach. Geographical Planning of Space, 9(34), 85-98. https://doi.org/ 10.30488/gps.2019.100315. (In Persian). [DOI:10.30488/gps.2019.100315. (In Persian).]
11. Panagos, P., Standardi, G., Borrelli, P., Lugato, E., Montanarella, L., & Bosello, F., 2018. Cost of agricultural productivity loss due to soil erosion in the European :union:: From direct cost evaluation approachesto the use of macroeconomic models. L. Degrad.29(21):471-484. https://doi.org/10.1002/ldr.2879 [DOI:10.1002/ldr.2879.]
12. Pandey, V.K., Pourghasemi, H.R., & Sharma, M.C., 2018. Landslide susceptibility mapping using maximum entropy and support vector machine models along the Highway Corridor, Garhwal Himalaya. Geocarto International, 35(2):1-38. https://doi.org/10.1080/10106049.2018.1510038 [DOI:10.1080/ 10106049. 2018. 1510038.]
13. Poesen, J., Nachtergaele, J., Verstraeten, G. and Valentin, C 2003. Gully erosion and environmental change: importance and research needs, Catena, 50(2-4):91-133. https://doi.org/10.1016/S0341-8162(02)00143-1 [DOI:10.1016/S0341-8162(02)00143-1.]
14. Roy J, Saha S. 2019. GIS-based gully erosion susceptibility evaluation using frequency ratio, cosine amplitude and logistic regression ensembled with Fuzzy logic in Hinglo River Basin, India, Remote Sensing Applications, Society and Environment,64(452):125-148 https://doi.org/10.1016/j.rsase.2019.100247 [DOI:10.1016/j.rsase.2019.100247.]
15. Saeediyan, H., shirani, K., salajegheh, A., ahmadi, R. (2023). 'Investigating the performance of the entropy maximum model in determining the importance of effective environmental factors in creating gully erosion in semi-arid areas', Journal of New Approaches in Water Engineering and Environment, 2(1): 129-144. https://doi.org/ 10.22034/nawee.2023.407297.1047. (In Persian). [DOI:10.22034/nawee.2023.407297.1047. (In Persian).]
16. Shirani, K., Zakerinejad, R. 2020. Gully erosion mapping and susceptibility assessment using statistical and probabilistic methods. Journal of Water and Soil Sciences, 25 (2):151-174. https://doi.org/10.47176/jwss.25.2.147215 [DOI:10.47176/jwss.25.2.147215. (In Persian).]
17. Tadesual A, Setargie M, Ebabu K, Nzioki B, Meshesha TM. 2023. Random Forest-based gully erosion susceptibility assessment across different agro-ecologies of the Upper Blue Nile Bbasin, Ethiopia. Geomorphology,431(14):241-263. https://doi.org/10.1016/j.geomorph.2023.108671 [DOI:10.1016/j.geomorph.2023.108671.]
18. Teimurian, T., Nazari Samani, A. , Feiznia, S. , Ahmadaali, K. and Soleimanpour, S. M. (2022). Determining the Spatial Distribution of Gully Erosion Probability Using the MaxEnt Model. Watershed Management Research, 35(2), 2-15 [DOI:10.22092/wmrj.2021.354647.1415. (In Persian).]
19. Yousefi Mobarhan E, Shirani K. (2023). Assessment of Maximum Entropy (ME) to identify Effective Factors on Gully Erosion and Determination of Sensitive Areas in Alaa Semnan Watershed. J Watershed Manage Res, 14(28), 37-54. https://doi.org/ 10.61186/jwmr.14.28.37. (In Persian). https://doi.org/10.61186/jwmr.14.28.37 [DOI:10.61186/jwmr.14.28.37. (In Persian).]
20. Zakerinejad R, Alvandi P. 2023. Spatial prediction of gully erosion using TanDEM-X data and Maximum Entropy Model (A case study: Khasoyeh Watershed, in Southeast of Fars Province). Environmental Erosion Research Journal,3(1):96-113. [DOI:20.1001.1.22517812.1402.13.1.4.6. (In Persian).]

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