Abstract
The slope length gradient (LS) factor expresses the effect of topography, i.e., combining effects of slope length (L) and slope steepness (S) on rate of soil erosion. The longer the slope length, greater is the amount of cumulative runoff and similarly steeper the slope of the land the higher is the velocities of the runoff that contributes erosion. The LS factor is the most important parameter for estimation of soil loss and soil management using Universal Soil Loss Equation (USLE) and Revised Universal Soil Loss Equation (RUSLE). A precise inventory and assessment of vulnerable areas includes the formulation of correct soil management for property development. Juri is a peri-urban watershed situated in Tripura, India, having high undulating topography, which leads to increase soil erosion and land slide problem. Therefore, it has become essential to quantify the LS factor to understand the characteristics of the topographic factor, which will help the researchers for estimation of soil erosion and preparation of management plan. The present study focused to evaluate the LS factor for the sub-watershed areas of Juri River of Tripura. Two methods namely (1) suggested by Moore and Burch (1986) and (2) proposed by Wischmeier and Smith (1978) were used to calculate the LS factor. Both the methods use Digital Elevation Model (DEM) in spatial domain to estimate the LS factor. The LS factor of the study area ranges from 0 to 982.71 by method-1 and 0.66 to 285.58 by method-2. The study indicates that, the method-2 is more apposite than method-1 because it gives LS factor value, which distributed uniformly in spatial domain; whereas method-1 resulted highest LS factor value along the flow direction and it had almost same value of LS factor in the remaining areas. This study will help for prediction of soil erosion and preparation of management plan by reducing the slope length of the study area. This findings and the methodology employed can be widely used in similar mountainous to hilly watersheds around the world for calculation of soil loss.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Bizuwerk A, Taddese G, Getahun Y (2008) Application of GIS for modeling soil loss rate in a wash basin Ethiopia. International Livestock Research Institute
Das S, Sarkar R, Bora PK (2018) Comparative study of estimation of soil erodibility factor for the lower Transact of Ranikhola watershed of east Sikkim. J Plant Develop Sci 10:317–322
Das S, Bora PK, Katre P (2019) Determining and mapping of soil erodibility index for Nongpoh Watershed. Indian J Hill Farming 32:27–33
Das S, Deb P, Bora PK, Katre P (2021) Comparison of RUSLE and MMF soil loss models and evaluation of catchment scale best management practices for a mountainous watershed in India. Sustainability 13:232
Deb P, Kiem AS (2020) Evaluation of rainfall-runoff model performance under non-stationary hydroclimatic conditions. Hydrol Sci J 65:1667–1684
Deb P, Moradkhani H, Abbaszadeh P, Kiem AS, Engström J, Keellings D, Sharma A (2020) Causes of the widespread Australian bushfire season. Earths Future 8:20-e2020EF001671
Food and Agriculture Organization of the United Nations (2015) Status of the World’s Soil Resources. Technical Summary FAO
Gafur A, Jensen JR, Borggaard OK, Petersen L (2003) Runoff and losses of soil and nutrients from small watersheds under shifting cultivation (Jhum) in the Chittagong Hill tracts of Bangladesh. J Hydrol 274(1):30–46
Haregeweyn N, Poesen J, Nyssen J, de Wit J, Haile M, Govers G, Deckers S (2006) Reservoirs in Tigray (Northern Ethiopia): characteristics and sediment deposition problems. Land Degrad Dev 17(2):211–230
Haregeweyn N, Poesen J, Deckers J, Nyssen J, Haile M, Govers G, Verstraeten G, Moeyersons J (2008) Sediment-bound nutrient export from micro-dam catchments in Northern Ethiopia. Land Degrad Dev 19(2):136–152
Kinnell PIA (2000) AGNPS-UM: applying the USLE-M within the agricultural non-point source pollution model. Environ Modell Softw 15(3):331–341
Lee S (2014) Geological application of geographic information system. Korea Inst Geosci Min Resour 9:109–118
Lu S, Liu B, Hu Y, Fu S, Cao Q, Shi Y, Huang T (2019) Soil erosion topographic factor (LS): accuracy calculated from different data sources. CATENA 1:104334
McCool DK, Brown LC, Foster GR, Meyer MCK, LD, (1989) Revised slope length factor for the universal soil loss equation. Trans ASAE 30(5):1387–1396
Merritt WS, Jakeman LRA (2003) A review of erosion and sediment transport models. Environ Modell Softw 18(8):761–799
Montanarella L (2015) Agricultural policy: govern our soils. Nature 528:32–33
Moore ID, Burch GJ (1986) Physical basis of the length slope factor in the universal soil loss equation. Soil Sci Soc Am 50:1294–1298
Nearing MA, Lane LJ, Lopes VL (1994) Modeling soil erosion. In: Lal R (ed) Soil erosion research methods. Soil and Water Conservation Society and St. Lucie press, pp 127–156
Olaniya M, Bora PK, Das S, Chanu PH (2020) Soil erodibility indices under different land uses in Ri-Bhoi district of Meghalaya (India). Sci Rep 10:14986
Perrin C, Michel C, Andréassian V (2001) Does a large number of parameters enhance model performance? Comparative assessment of common catchment model structures on 429 catchments. J Hydrol 242:275–301
Pimentel D (2006) Soil erosion: a food and environmental threat. Environ Dev Sustain 8(1):11–137
Prasannakumar V, Vijith H, Abinod S, 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. Geosci Front 3(2):209–215
Qin W, Guo Q, Cao W, Yin Z, Yan Q, Shan Z, Zheng F (2018) A new RUSLE slope length factor and its application to soil erosion assessment in a Loess Plateau watershed. Soil Tillage Res 182:10–24
Renard KG, Foster GR, Weesies GA, McCool DK, Yoder DC (1997) Predicting soil erosion by water: a guide to conservation planning with the revised universal soil loss equation (RUSLE). United States Department of Agriculture
Silalahi FES, Pamela AY, Hidayat F (2019) Landslide susceptibility assessment using frequency ratio model in Bogor, West Java. Indonesia Geosci Lett 6:10
Srivastava A, Deb P, Kumari N (2020) Multi-model approach to assess the dynamics of hydrologic components in a tropical ecosystem. Water Resour Manag 34:327–341
Stocking MA (2003) Tropical soils and food security: the next 50 years. Science 302:1356–1359
Vargas FZ (1993) An Approach to Slope Length and Features calculating Using DEM and GIS. POSTER SESSIONS 236 at FAO/UNESCO, INEGI
Wainwright J, Mulligan M (2013) Environmental modeling: finding simplicity in complexity. wiley-Blackwell Publishing Ltd.
Wischmeier WH, Smith DD (1978) Predicting rainfall erosion losses: a guide to conservation planting United States Department of Agriculture. Agriculture Handbook: N0. 537. United States Department of Agriculture
Wu L, He Y, Ma X (2020) Can soil conservation practices reshape the relationship between sediment yield and slope gradient? Ecol Eng 142:105630
Yadav S, Babel MS, Shrestha S, Deb P (2019) Land use impact on the water quality of large tropical river: Mun River Basin. Thailand Environ Monit Assess 191:614
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Das, S., Bora, P.K. & Das, R. Estimation of slope length gradient (LS) factor for the sub-watershed areas of Juri River in Tripura. Model. Earth Syst. Environ. 8, 1171–1177 (2022). https://doi.org/10.1007/s40808-021-01153-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40808-021-01153-0