Gajbhiye S, Mishra SK, Pandey A (2015) Simplified sediment yield index model incorporating parameter CN. Gajbhiye S, Mishra SK, Pandey A (2014) Relationship between SCS-CN and sediment yield. Gajbhiye S, Mishra SK, Pandey A (2013c) Prioritizing erosion-prone area through morphometric analysis: an RS and GIS perspective. Gajbhiye S, Mishra SK, Pandey A (2013b) Estimation of design runoff curve numbers for Narmada watersheds (India). Gajbhiye S, Mishra SK, Pandey A (2013a) Effect of seasonal/monthly variation on runoff curve number for selected watersheds of Narmada basin. Environ Earth Sci 59(1):223вЂ“231ДЇlaxman (1971) Sediment yield predictive equation, soil conservation service, Technical Service Centre AdvisoryвЂ“POI Washington D.C.U.S.D.A. J Soils Sediments 9:613вЂ“626Дiodato N, Grauso S (2009) An improved correlation model for sediment delivery ratio assessment. Model Earth Syst Environ 2:123Дelmas M, Olivier C, Jean-Marie M, Manuel G (2009) A method for developing a large-scale sediment yield index for European river basins. Дatta S (2016) Soil erosion, sediment yield and sedimentation of reservoir: a review. Hydrol Sci J 29(2):203вЂ“218ДahmardehGhaleno MR, Meshram SG, Alvandi E (2020) Pragmatic approach for prioritization of flood and sedimentation hazard potential of watersheds. Hydrol Eart Syst Sci 6:255вЂ“265Д¬aroni E, Singh VP, Ubertini L (1984) Rainfall-runoff-sediment yield relation by stochastic modelling. Д«rath A, Castellarin A, Montanari A (2002) Assessing the effect of land-use changes on annual average gross erosion. The prediction of SYI is important when adopting a suitable soil conservation measure in the watershed for minimizing soil erosion.ДЄISLUS (1977) Priority delineation, Matatilla RVP, U.P Report No.Agri.484.ДЄISLUS (1991) Methodology of Priority Delineation Survey, All India Soil and Land Use Survey Technical Bulletin 9, Department of Agriculture and Cooperation, New Delhi, IndiaД«rahim B, Meshram SG, Abdallah D, Larbi B, Drisss S, Khalid M, Khedher KM (2020) Mapping of soil sensitivity to water erosion by RUSLE Model: case of the inaouene watershed (Northeast Morocco). The resulting higher Nash efficiency values support the versatility of the derived relationship and invoke assessment of SYI from the watershed stream length value. It is observed that the simplified AISLUS model (logarithm form) incorporating parameter SL had a satisfactory efficiency as 76.35% (Shakkar watershed), 66.05% (Mohgaon watershed), 93.36% (Bamhani watershed), and 83.83% (Manot watershed) by Nash efficiency scale. Therefore, the logarithm simplified AISLUS model was chosen as the best regression model for this study. The logarithmic simplified AISLUS model incorporating parameter SL resulted with the coefficient of R 2 as 0.76 (Shakkar watershed), 0.93 (Bamhani watershed), 0.84 (Manot watershed) and 0.66 (Mohgaon watershed). The three models (A model, CN model and simplified All India Soil and Land Use Survey (AISLUS) model including parameter SL) performed differently, with the coefficient of R 2 equal to 0.01, 0.02 and 0.71 (Shakkar watershed), 0.11, 0.23 and 0.91 (Bamhani watershed), 0.06, 0.001 and 0.80 (Manot watershed) and 0.40, 0.05 and 0.66 (Mohgaon watershed), respectively. Area (A), Curve Number (CN) and stream length (SL) were utilized as input for model development. In the present study an attempt has been made to develop a relationship between watershed stream length and Sediment Yield Index (SYI) and test it on Narmada watersheds, Madhya Pradesh, India. Sediment-Runoff process is highly variable and nonlinear in nature.

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