Sediment Estimation Using Different Erosion Components

Document Type : Research Article

Authors

• H. Saeediyan
• Hamid Reza Moradi

Assistant Professor, Department of Soil Conservation and Watershed Management Research, Kerman Agricultural and Natural Resource Research Center, Agricultural Research, Education and Extension Organization, Kerman, Iran.

https://doi.org/10.22067/jsw.2021.69031.1029

Abstract

Introduction: Erosion and sediment production studies along with other natural resources studies in decision making and success and efficiency of watershed plans are of great importance. In order to plan and be aware of the destructive situation of the watershed, it is necessary to have erosion and sediment production from each watershed. The information about sediment load of basins can show the prospect of erosion. Sediment scatter from the soil surface by the impact of raindrops and shear force of runoff and is transported to downstream by spraying from raindrops and mainly by runoff. Also, the stress characteristics of soil particles are important in the process of effective transport. In recent decades, soil erosion has been intensified due to the human interference, inappropriate land management and land use. This is much more important in developing countries, because soil erosion is a serious risk to sustainable development in these countries. Soil erosion on farmland occurs due to the interaction between nature and human activities that have been being intensified in recent years. Estimation of sedimentation in watersheds, dealing with sediment accumulation risks in water structures and reservoirs of dams are the main objectives in water resources management that leads to sustainable development. One of the most erodibility of Iran is the Gachsaran formation. Gachsaran formation is about 1600 meters thick. A viewpoint of lithology is consisting of salt, anhydrite, colorful lime, and some shale. Gachsaran formation age is lower Miocene.
Materials and Methods: In this study, in order to determine sediment estimation by using different erosion components in different land uses of Gachsaran formation deposits, a part of Kuhe Gypsum watershed of Izeh city with an area of 1202 hectares was selected. In this study, the relationship between produced sediment and different erosion components such as runoff,soil permeability,runoff, and erosion threshold in different land uses of Gachsaran formation was determined by multivariate regression. Then, sampling of erosion different components was done at 6 points with 3 replicates and at rainfall different intensities of 0.75, 1 and 1.25 mm/min in three land uses of rangeland, residential area and agricultural using rain simulator. SPSS and EXCEL softwares were used for statistical analysis.
Results and Discussion: The results showed that sediment estimation using different erosion components presents acceptable results and can be used for other watersheds. The results also showed that in sediment estimation by erosion different components, runoff and erosion threshold had the most positive and negative effect and in eight cases played a role in modeling. Then, soil permeability has the average effect of positive and negative and has played a role in modeling in seven cases. In addition, runoff has not played a role in modeling in any of the three different land uses and intensities of precipitation.
Conclusion: Sediment estimation by erosion different components, the runoff and erosion threshold had the highest effect. Soil permeability had a moderate influence and runoff rate has not played a role in modeling in any of different land uses and precipitation intensities, it indicated the much more important role of runoff and erosion threshold and soil permeability in this modeling method in estimating sediment production. Finally, sediment estimation method by using erosion different components showed that it could be more applicable in sediment estimation in hard-to-reach watersheds in the future and be more effective in soil conservation and erosion reduction with appropriate and rational estimates in more appropriate implementation of watershed projects.

Keywords

• Erosion
• Gachsaran formation
• Land use
• Sediment estimation

20.1001.1.20084757.1400.35.3.5.4

Main Subjects

• Irrigation

References

1-       Ahmadi H. 2007. Applied geomorphology, 1 volume (water erosion), fifth edition, Tehran university publications, 714p. (In Persian with English Abstarct)

2-       Arab Khedri M. 1994. Revision of modified global equation of soil losses, Journal of Research and Construction, No. 25, Ministry of Jihad-e Sazandegi.

3-       Ares M.G., Varni M., and Chagas C. 2016: Suspended sediment concentration controlling factors: an analysis for the Argentine Pampas region. Hydrological Science Journal 61(12): 2237-2248.

4-       Fathizadeh H., Karimi H., and Tavakoli M. 2016. The Role of Sensitivity to Erosion of Geological Formations in Erosion and Sediment Yield (Case Study: Sub-Basins of Doiraj river in ilam province), Journal of Watershed Management, Volume 7, No. 13, Spring and Summer. (In Persian with English Abstarct)

5-       Hosseini S.S., and Ghorbani M. 2005. Economics of soil erosion. Ferdowsi University of Mashhad Press, 205 Pp. (In Persian with English Abstarct)

6-       Kamphorst A. 1987. A small rainfall simulator for the determination of soil erodibility, Netherlands Journal of Agricultural Science 35: 407-415.

7-       Khajehei A., Bereshkeh A., Sokooti R., and Arab Khedri M. 2002. Investigating application of MUSLE Empirical Model for Estimating Sediment From Single Storms and Annual Sediment in Shahrchay River Watershed, Proceedings of the National Conference on Land Management- Soil Erosion and Sustainable Development, Arak, Ministry of Agriculture Jihad Publications, pp. 447-436.

8-       Merdun H., Cinar O., Meral R., and Apan M. 2006. Comparison of artificial neural network and regression pedotransfer function for prediction of soil water retention and saturated hydraulic conductivity, Soil and Tillage Research 90: 108-116.

9-       Morady H.R., and Saidian H. 2010. Comparing the Most Important Factors in the Erosion and Sediment Production in Different Land Uses, Journal of Environmental Science and Engineering 4(11): 1-11.

10-   Murat A., and Cigizoglu H.K. 2007. Suspended sediment load simulation by two artificial neural network methods using hydrometeorological data, Environ. Model.Soft.22:2-13.

11-   Musgrave G.W. 1947. The Quantitative evaluation of factors in water erosion, a first Approximation, Journal of Soil and Water Conservation 2(3): 133-138.

12-   Noor H., Mirnia S.Kh., Fazli S., Raisi M.B., and Vafakhah M. 2010. Application of MUSLE for the prediction of phosphorus losses.Water Science and Technology 62(4): 809-815.

13-   Pasific Southwest Inter-Agency Committee. 1968. Factors Affecting Sediment Yield and Measures for the Reduction of Erosion and Sediment Yield, 13 pp.

14-   Rendard K.C., Foster G., Yoder D., Et Maccol D. 1994. RUSLE Revised: Status, Questions, Answers and the Future. Journal of Soil Water Conservation 49: 213-220.

15-   Renfro G.W. 1975. Use of Erosion Equations and Sediment Delivery Rations for Predicting Sediment Yield. In Present and Prospective Technology for Predicting Sediment Yields and Sources. Agric. Res. Serv., ARS-S-40, 33-45.US Dept. Agric.,Washington, D.C.

16-   Restrepo Juan D., Lopez Sergio A., and Restrepo Juan C. 2009, The Effects of Geomorphic Controls on Sediment Yield in the Andean Rivers of Colommbia, Latin American Journal of Sedimontology and Basin Analusis 16(2): 79-92.

17-   Roman David C.,Vogel Richard M., and Schwarz Gregory E. 2010, Multivariate Models ofWatershed Suspended Sediment Loads for the Eastern United States. Urban Water Resources Research Council -7^th Urban Watershed Management Symposium 3133-3144.

18-   Shahkarami A. 2002. Investigation of sediment estimation methods of P.S.I.A.C MPS. I.A.C and EPM in Nozhian Watershed, Proceedings of the National Conference on Land Management- Soil Erosion and Sustainable Development, Arak, Ministry of Agriculture Jihad Publications 562-572.

19-   Soni S. 2017. Assessment of morphometric characteristics of Chakrar watershed in Madhya Pradesh India using geospatial technique.Applied Water Science 7(5): 2089-2102.

20-   Vafakhah M., and Saeediyan H. 2014. Modeling of observed runoff and sediment with estimative runoff and sediment with using neural network and multi regression in aghajari marls, Journal of Range and Watershed Management 67(3): 487-499.

21-   Walling D.E. 1988. Erosion and sediment yield research-some recent perspectives. Journal of Hydrology 100: 113-141.

22-   Williams J.R. 1975. Sediment Yield Prediction with Universal Soil Loss Equation Using Runoff Energgy Factors, In Present and Prospective Technology for Predicting Sediment Yields and Sources. Agric. Res. Serv., US Dept. Agric.,Washington, D.C., ARS-S-40, 244-252.

23-   Wischmeier W.H., and Smith D.D. 1978. Predicting Rainfall Erosion Losses- A Guied to Conservation Planning. Agric. Handbook No.537, US Dept. of Agric., Washington, D.C.

24-   Zhang H.Y., Shi Z.H., Fang N.F., and Guo M.H. 2015. Linking watershed geomorphic characteristics to sediment yield: Evidence from the Loess Plateau of China.Geomorphology 234: 19-27.

25-   Zhen H., Jiangwen L., Yanhai Li., Xiaojie Gu., Xiaoyan Ch., and Chaofu W. 2021. Eroded sediment in a partially saturated sandy loam soil using scouring experiments, CATENA 201: 105234.

26-   Zhen W, Yi Zeng., Cai L., Hua Y., Shuxia Y., Ling W., and Zhihua Shi. 2021. Telecoupling cropland soil erosion with distant drivers within China, Journal of Environmental Management 288(15): 112395.