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Dynamic Analysis Of Soil Erosion-Based Watershed Health

https://doi.org/10.24057/2071-9388-2018-58

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Abstract

Accelerated soil erosion is one of the most important detrimental factors affecting the quality of the watershed health. Due to different environmental pressures and drivers, the effort is needed for ecological health and resilience assessment in regards to erosion changeability. However, this important subject has not been adequately studied yet. Towards this, in the present research, an innovative approach was developed for conceptualizing the watershed health dynamics in viewpoint of soil erosion. A risk-based study was conducted to quantitatively characterize the spatiotemporal variability of erosion-based health in an industrialized watershed i.e., the Shazand Watershed using the conceptual reliability, resilience and vulnerability (RelResVul) framework for four node years of 1986, 1998, 2008 and 2014. To this end, the soil erosion was estimated at monthly scale in 24 sub-watersheds by applying the Revised Universal Soil Loss Equation (RUSLE). The RelResVul indicators were then computed according to the threshold defined for the study watershed. A geometric mean was used to combine the three risk indicators and the erosion-based watershed health index was ultimately calculated for each study sub-watershed. Additionally, the change detection analysis was conducted over the years of 1986 to 2014. According to the results of erosion-based the RelResVul indices, very healthy, healthy, moderately healthy, unhealthy and very un-healthy conditions in the Shazand Watershed were respectively distributed over some 67, 25, zero, zero and eight percent for 1986; 50, 13, eight, zero and 29 % for 1998; 71, eight, 83, zero, zero and eight percent for 2008 and finally 71, zero, 17, zero and 12 % for 2014. The results of change detection revealed an oscillating trend of erosion-based watershed health index during the whole study period (1986 -2014). So that, during periods of 1986-1998, 1986-2008 and 1986-2014, the watershed health decreased at tune of 23, 13 and six percent, respectively. Whilst, the watershed health improved during study periods of 1998-2008 (13 %), 2008-2014 (eight percent) and 1998-2014 (22 %). The results also identified ‘hot spots’ of the most important index of land degradation and ‘bright spots’ of land improvement in the Shazand Watershed.
The proposed approach would provide a sustainable framework supporting decision makers to comprehend health-related soil erosion targets according to the integrated watershed management plans.

About the Authors

Zeinab Hazbavi
Tarbiat Modares University
Iran, Islamic Republic of
Tehran, Iran


Seyed Hamidreza Sadeghi
Tarbiat Modares University
Iran, Islamic Republic of
Tehran, Iran


Mehdi Gholamalifard
Tarbiat Modares University
Iran, Islamic Republic of
Tehran, Iran


References

1. Ahn S.R., and Kim S.J. (2017). Assessment of watershed health, vulnerability and resilience for determining protection and restoration Priorities. Environmental Modelling and Software, 2017, pp. 1-19. http://doi.org/10.1016/j.envsoft.2017.03.014.

2. Alemaw B.F., Keaitse E.O., and Chaoka T.R. (2016). Management of water supply reservoirs under uncertainties in arid and urbanized environments. Journal of Water Resource and Protection, 08(11), pp. 990–1009. http://doi.org/10.4236/jwarp.2016.811080.

3. Asadi H., Honarmand M., Vazifedoust M., and Mousavi A. (2017). Assessment of changes in soil erosion risk using RUSLE in Navrood Watershed, Iran. Journal of Agricultural Science and Technology, 19, pp. 231-244. http://jast-old.modares.ac.ir/article_15958.html.

4. Chanda K., Maity R., Sharma A., and Mehrotra R. (2014). Spatiotemporal variation of long-term drought propensity through reliability-resilience-vulnerability based Drought Management Index. Water Resources Research, 50(10), 7662-7676. http://doi.org/10.1002/2014WR015703.

5. Chatrsimab Z., Ghavimi Panah M.H., Vafaeinejad A.R., Hazbavi Z., and Boloori S. (2019). Prioritizing of the sub-watersheds using the soil loss cost approach (A case study; SeljAnbar Watershed, Iran). ECOPERSIA, Accepted for publication.

6. Dabral P.P., Baithuri N., and Pandey A. (2008). Soil erosion assessment in a hilly catchment of North Eastern India using USLE, GIS and remote sensing. Water Resources Management, 22(12), pp. 1783-1798. https://doi.org/10.1007/s11269-008-9253-9.

7. Darabi H., Shahedi K., Solaimani K., and Miryaghoubzadeh M. (2014). Prioritization of subwatersheds based on flooding conditions using hydrological model, multivariate analysis and remote sensing technique. Water Environmental Journal, 28, pp. 382-392. https://doi.org/10.1111/wej.12047.

8. Davudirad A.A., Sadeghi S.H.R., and Sadoddin A. (2016). The impact of development plans on hydrological changes in the Shazand Watershed, Iran. Land Degradation and Development, 27, pp. 1236-1244. https://doi.org/10.1002/ldr.2523.

9. Emadodin I., Narita D., and Rudolf Bork H. (2012). Soil degradation and agricultural sustainability: an overview from Iran. Environment, Development and Sustainability, 14(5), pp. 611-625. http://doi.org/10.1007/s10668-012-9351-y.

10. Fayas S.M., Abeysingha N.S., Nirmanee G.K.S., Samaratunga D., and Mallawatantri A. (2019). Soil loss estimation using RUSLE model to prioritize erosion control in KELANI river basin in Sri Lanka. International Soil and Water Conservation Research, 7(2), pp. 130–137. http://doi.org/10.1016/j.iswcr.2019.01.003.

11. Ganasri B.P., and Ramesh H. (2015). Assessment of soil erosion by RUSLE model using remote sensing and GIS - A case study of Nethravathi Basin. Geoscience Frontiers, 7(6), pp. 1-9. http://doi.org/10.1016/j.gsf.2015.10.007.

12. Golosov V.N., Zhang X., Qiang T., Zhou P., and He X. (2014) Quantitative assessment of sediment redistribution in the Sichuan Hilly Basin and the central Russian Upland during the past 60 years. Geography, Environment, Sustainability, 2014, 7(3), pp. 39-64. https://doi. org/10.24057/2071-9388-2014-7-3-35-39.

13. Golrang B.M., Lai F.S., Rostami M., Kamurudin M.N., Abd Kudus K., Sadeghi S.H.R., and Mashayekhi M. (2013). The relationship between level of watershed project successful and level of people participation. World of Sciences Journal, 3, pp. 1-9.

14. Hashimoto T., Loucks D. P., and Stedinger J. (1982). Reliability, resilience and vulnerability criteria for water resource system performance evaluation. Water Resources Research, 18(1), pp. 14-20. https://doi.org/10.1029/WR018i001p00014.

15. Hazbavi Z. (2018). Importance of geology and geomorphology. Agriculture & Forestry, 64(4), pp. 277–287. http://doi.org/10.17707/AgricultForest.64.4.27.

16. Hazbavi Z., Jantiene B., Nunes J.P., Keesstra S.D., and Sadeghi S.H.R. (2018a). Changeability of reliability, resilience and vulnerability indicators with respect to drought patterns. Ecological Indicators, 87, pp. 196-208.

17. Hazbavi Z., Keesstra S.D., Nunes J.P., Jantiene B., Gholamalifard M., and Sadeghi S.H.R. (2018b). Health comparative comprehensive assessment of watersheds with different climates. Ecological Indicators, 93, pp. 781–790. http://doi.org/10.1016/j.ecolind.2018.05.078.

18. Hazbavi Z., and Sadeghi S.H.R. (2017). Watershed health characterization using reliabilityresilience-vulnerability conceptual framework based on hydrological responses. Land Degradation and Development, 28, pp. 1528–1537. http://doi.org/10.1002/ldr.2680.

19. Hazbavi Z., Sadeghi S.H.R., and Gholamalifard M. (2018c). Land cover based watershed health assessment. AGROFOR International Journal, 3(3), pp. 47–55. 10.7251/AGRENG1803047H.

20. Hazbavi Z., Sadeghi S.H.R., Gholamalifard M., Davudirad A.A. (2019). Watershed health assessment using pressure–state–response (PSR) framework. Land Degradation and Development, https://doi.org/10.1002/ldr.3420.

21. Hoque Y.M., Hantush M.M., and Govindaraju R.S. (2014a). On the scaling behavior of reliability-resilience-vulnerability indices in agricultural watersheds. Ecological Indicators, 40, pp. 136-146. https://doi.org/10.1016/j. ecolind.2014.01.017.

22. Hoque Y.M., Raj C., Hantush M.M., Chaubey I., and Govindaraju R.S. (2014b). How do landuse and climate change affect watershed health? a scenario-based analysis. Water Quality, Exposure and Health. 6, pp. 19-33. http://doi.org/10.1007/s12403-013-0102-6.

23. Hoque Y.M., Tripathi S., Hantush M.M., and Govindaraju R. S. (2012). Watershed reliability, resilience and vulnerability analysis under uncertainty using water quality data. Journal of Environmental Management, 109, pp. 101–112. http://doi.org/10.1016/j.jenvman.2012.05.010.

24. Hoque Y.M., Tripathi S., Hantush M.M., and Govindaraju R. S. (2016). Aggregate Measures of Watershed Health from Reconstructed Water Quality Data with Uncertainty. Journal of Environment Quality, 45(2), 709. http://doi.org/10.2134/jeq2015.10.0508.

25. Hosseini S., and Ghorbani M. (2005). Economics of soil erosion. Ferdowsi University of Mashhad Press. 128 p (in Persian).

26. Jain S.K., Kumar S., and Varghese J. (2001). Estimation of soil erosion for a Himalayan Watershed using GIS technique. Water Resources Management, 15(1), pp. 41-54. https://doi.org/10.1023/A:1012246029263.

27. Lakkad A.P., Nayak, D., Patel, G., and Shrivastava, P.K. (2017). Micro-watersheds prioritization for effective soil conservation planning of sub-watershed. Research in Environment and Life Sciences, 10(3), pp. 275-279.

28. Li H., Chen X., Lim K.J., Cai X., and Sagong M. (2010). Assessment of soil erosion and sediment yield in Liao Watershed, Jiangxi Province, China, using USLE, GIS and RS. Journal of Earth Science, 21, 941-953. https://doi.org/10.1007/s12583-010-0147-4.

29. Lin C.Y. (1997). A study on the width and placement of vegetated buffer strips in a mudstone-distributed watershed. Journal of Chinese Soil and Water Conservation, 29(3), pp. 250-266 (in Chinese with English abstract).

30. López-Vicente M., Navas A., and Machín J. (2007). Identifying erosive periods by using RUSLE factors in mountain fields of the Central Spanish Pyrenees. Hydrology Earth System Sciences Discussion, 4(4), pp. 2111–2142. http://dx.doi.org/10.5194/hessd-4-2111-2007.

31. Loucks O.L. (1997). Emergence of research on agro-ecosystems. Annual Review of Ecology and Systematics, 8, 1730192. https://doi.org/10.1146/ annurev.es.08.110177.001133.

32. Lu J. (2011). Soil erosion changes based on GIS/RS and USLE in Poyang Lake Basin. Transactions of CSAE, 27, pp. 337-345. https://doi.org/10.3969/j.issn.1002-6819.2011.02.057.

33. Maity R., Sharma A., Kumar D.N., Asce M., and Chanda K. (2013). Characterizing drought using the reliability-resilience-vulnerability concept. Journal of Hydrologic Engineering, pp. 859-869. http://doi.org/10.1061/(ASCE)HE.1943-5584.0000639.

34. Millward A.A., and Mersey J.E. (1999) Adapting the RUSLE to model soil erosion potential in a mountainous tropical watershed. Catena, 38, pp. 109-129. https://doi.org/10.1016/S0341-8162(99)00067-3.

35. Mohammadi S., Karimzadeh H., and Alizadeh M. (2018). Spatial estimation of soil erosion in Iran using RUSLE model. EcoHydrology, 5(2), pp. 551-569 (in Persian).

36. Mokhtari Sh., Babazadeh H., Sedghi H., and Kaveh F. (2011). Long term simulation of Shazand Plain Aquifer under changing resources and applications. International Journal of Research in Agricultural Sciences and Research, 2, pp. 1-10. http://ijasr.srbiau.ac.ir/article_5533.html.

37. Prasannakumar V., Vijith H., Abinod S., and Geetha N. (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), pp. 209-215. http://doi.org/10.1016/j.gsf.2011.11.003.

38. Renard K., Foster G., Weesies G., McCool D., and Yoder D. (1997). Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE). US Government Printing Office, Washington, DC. Handbook No. 703, 404 p.

39. Roose E. (1977) Erosion et ruissellement en Afrique de louest-vingt annees de mesures en petites parcelles experimentales. Pour faire face a`ce proble`me pre´occupant, I’ORSTOM et les Instituts Travaux et Documents de I’ORSTOM No. 78, 108 p.

40. Pietroń J., Chalov S., Chalova A., Alekseenko A., and Jarsjö J. (2017). Extreme spatial variability in riverine sediment load inputs due to soil loss in surface mining areas of the Lake Baikal basin. Catena, 152, pp. 82–93. http://dx.doi.org/10.1016/j.catena.2017.01.008.

41. Sadeghi S.H.R., and Hazbavi Z. (2017a). Necessity of watershed health assessment in integrated soil and water resources management. In: Proceedings of 2nd IAHS Panta Rhei International Conference on Water System Knowledge Innovation and Its Practices in Developing Countries, Iran, Gorgan, November 20-22, 2017, pp. 22-23.

42. Sadeghi S.H.R., and Hazbavi Z. (2017b). Spatiotemporal variation of watershed health propensity through reliability-resilience-vulnerability based drought index (case study: Shazand Watershed in Iran). Science of The Total Environment. http://doi.org/10.1016/j.scitotenv.2017.02.098.

43. Sadeghi S.H.R., Davudirad A.A., Sadoddin A., and Paimozd Sh. (2018). Trend of Changes in Land Degradation Index in Shazand Watershed-Markazi Province. Watershed Engineering and Management, 9(4), pp. 383-397. http://doi.org/10.22092/IJWMSE.2017.113459.

44. Sadeghi S.H.R., Hazbavi Z., and Cerdà A. (2017). Watershed health assessment to monitor land degradation. Geophysical Research Abstracts, EGU General Assembly 2017, Vol. 19, EGU2017-28. http://adsabs.harvard.edu/abs/2017EGUGA..19...28H.

45. Sadeghi S.H.R., Hazbavi Z., and Gholamalifard M. (2019). Interactive impacts of climatic, hydrologic and anthropogenic activities on watershed health. Science of the Total Environment, 648, pp. 880-893. http://doi.org/10.1016/j.scitotenv.2018.08.004.

46. Sadeghi S.H.R., Hazbavi Z., and Younesi H. (2014). Sustainable watershed management through applying appropriate level of soil amendments. In Sustainable Watershed Management - Proceedings of the 2nd International Conference on Sustainable Watershed Management, SUWAMA 2014.

47. Sadeghi S.H.R., and Tavangar S. (2015). Development of stational models for estimation of rainfall erosivity factor in different timescales. Natural Hazards, 77(1), 429–443. http://doi.org/10.1007/s11069-015-1608-y.

48. Salvati L., Smiraglia D., Bajocco S., Ceccarelli T., Zitti M., and Perini L. (2014). Map of LongTerm Changes in Land Sensitivity to Degradation of Italy. Journal of Maps, 10(1), pp. 65-72. http://doi.org/10.1080/17445647.2013.842506.

49. Shepherd K.D., Shepherd G., and Walsh M.G. (2015). Land health surveillance and response: A framework for evidence-informed land management. Agricultural Systems, 132, pp. 93-106. http://doi.org/10.1016/j.agsy.2014.09.002.

50. Smiraglia D., Ceccarelli T., Bajocco S., Salvati L., and Perini L. (2016). Linking trajectories of land change, land degradation processes and ecosystem services. Environmental Research, 147, pp. 590-600. http://doi.org/10.1016/j.envres.2015.11.030.

51. Sood A., and Ritter W.F. (2011). Developing a framework to measure watershed sustainability by using hydrological/water quality model. Journal of Water Resource and Protection, 3(11), pp. 788-804. http://doi.org/10.4236/jwarp.2011.311089.

52. Spalevic V., Al-Turki A.M., Barovic G., Silva M.L.N., Djurovic N., Souza W.S., Batista P.V.G., and Curovic M. (2016): Modeling of soil erosion by IntErO model: The case study of the Novsicki Potok Watershed of the Prokletije high mountains of Montenegro. Geophysical Research Abstracts. Vol. 18, EGU2016-13864, 2016. EGU General Assembly 2016.

53. Teh S.H. (2011). Soil erosion modeling using RUSLE and GIS on Cameron Highlands, Malaysia for hydropower development. A 30 ECTS Credit Units MSc Thesis. The School for Renewable Energy Science in affiliation with University of Iceland and University of Akureyri, 71 p.

54. USDA (1978). Predicting rainfall erosion losses. A Guide to Conservation Planning, Washington DC. Agricultural Handbook 537.

55. Van der Knijff, J.M., Jones, R.J.A., Montanarella, L., 2000. Soil Erosion Risk Assessment in Europe. European Commission Directorate General. Joint Research Centre (JCR), Space Applications Institute, European Soil Bureau.

56. van Noordwijk M. (2017). Integrated natural resource management as pathway to poverty reduction: Innovating practices, institutions and policies. Agricultural Systems, (October), 1-12. http://doi.org/10.1016/j.agsy.2017.10.008.

57. Vijith H., Suma M., Rekha V.B., Shiju C., and Rejith P.G. (2012). An assessment of soil erosion probability and erosion rate in a tropical mountainous watershed using remote sensing and GIS. Arabian Journal of Geosciences, 5(4), pp. 797-805. http://doi.org/10.1007/s12517-010-0265-4.

58. Wiegand A.N., Walker C., Duncan P.F., Roiko A., and Tindale N. (2013). A systematic approach for modelling quantitative lake ecosystem data to facilitate proactive urban lake management. Environmental Systems Research, 2, 12. https://doi.org/10.1186/2193-2697-2-3.

59. Wischmeier W.H., and Smith D.D. (1965). Predicting rainfall-erosion losses from cropland east of the Rocky Mountains: Guide for selection of practices for soil and water conservation. Agricultural Research Service, US Department of Agriculture in cooperation with Purdue Agricultural Experiment Station. 1965.

60. Wischmeier W.H., and Smith D.D. (1978). Predicting rainfall erosion. Losses: a guide to conservation planning. Agriculture Handbook, US Department of Agriculture, Washington, DC. 537, 58 p.

61. Yu J.X., Zheng B.F., Liu Y.F., and Liu C.L. (2011). Evaluation of soil loss and transportation load of adsorption N and P in Poyang Lake watershed. Acta Ecologic Sinica, 14, pp. 3980-3989.

62. Yuan L.F., Yang G.S., Zhang Q.F., and Li H.P. (2016). Soil erosion assessment of the Poyang Lake Basin, China: using USLE, GIS and remote sensing. Journal of Remote Sensing and GIS, 5(3). http://doi.org/10.4172/2469-4134.1000168.

63. Zhao Y.Z., Zou X.Y., Cheng H., Jia H.K., Wu Q., Wang G.Y., Zhang C.L., and Gao S.Y. (2006). Assessing the ecological security of the Tibetan plateau: Methodology and a case study for Lhaze County. Journal of Environmental Management, 80, pp. 120-131. https://doi.org/10.1016/j.jenvman.2005.08.019.


For citation:


Hazbavi Z., Sadeghi S.H., Gholamalifard M. Dynamic Analysis Of Soil Erosion-Based Watershed Health. GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY. 2019;12(3):43-59. https://doi.org/10.24057/2071-9388-2018-58

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