Modelling of soil erosion susceptibility incorporating sediment connectivity and export at landscape scale using integrated machine learning, InVEST-SDR and Fragstats.

Evaluating the linkage between soil erosion and sediment connectivity for export assessment in different landscape patterns at catchment scale is valuable for optimization of soil and water conservation (SWC) practices. Present research attempts to identify the soil erosion susceptible (SES) sites in Kangsabati River Basin (KRB) using machine learning algorithm (decision trees, decision trees cross validation, CV, Extreme Gradient Boosting, XGB CV and bagging CV) taken thirty five variables, for investigating the linkage between erosion rates and sediment connectivity to assess the sediment export at sub-basin level employing connectivity index (IC) and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) sediment delivery ratio (SDR) model. Based on AUC of receiving operating curve in validation test, excellent capacity of extreme Gradient Boosting, XGB CV and bagging CV (0.

Multifunctional resilience of river health to human service demand in an alluvial quarried reach: a comparison amongst fuzzy logic, entropy, and AHP-based MCDM models.

Riverine ecosystem services to human beings are dynamically evaluated by harmonic relationships; however, over growing human service demands (HSDs) are leading to deteriorate the river health resilience. In this study, an assessment index system of river health involving pressure-state-response (PSR) based on twenty indicators of riparian, channel geomorphic, hydroecological, and social attributes was developed to detect the multifunctional reliability and resilience of river system integrity for HSDs at upper (US), middle (MS), and lower segments (LS) of Kangsabati River using fuzzy logic, analytical hierarchical process (AHP), and entropy weight-based multi-criteria decision matrix (MCDM) methods. Borda integrating MCDM results revealed that overall indicator performance is high health score in US (77), medium score in MS (69), but mostly unhealthy score in LS (34); thus, entropy-MCDM models give highest rank to US, medium rank to MS, and least rank to LS, while AHP and fuzzy MCDM models assigned as high priority rank to MS, medium rank to US, and least rank to LS, respectively.

Sub-basin prioritization for assessment of soil erosion susceptibility in Kangsabati, a plateau basin: A comparison between MCDM and SWAT models.

Kangsabati basin located in tropical plateau region faces multiple problems of soil erosion susceptibility (SES), soil fertility deterioration, and sedimentation in reservoirs. Hence, identification of SES zones in thirty-eight sub-basins (SB) for basin prioritization is necessary. The present research addressed the issue by using four multi-criteria decision-making (MCDM) models: VlseKriterijumska optimizacija I Kompromisno Resenje (VIKOR), technique for order preference by similarity to ideal solution (TOPSIS), simple additive weighing (SAW), compound factor (CF).

Sub-basin prioritization for assessment of soil erosion susceptibility in Kangsabati, a plateau basin: A comparison between MCDM and SWAT models.

Kangsabati basin located in tropical plateau region faces multiple problems of soil erosion susceptibility (SES), soil fertility deterioration, and sedimentation in reservoirs. Hence, identification of SES zones in thirty-eight sub-basins (SB) for basin prioritization is necessary. The present research addressed the issue by using four multi-criteria decision-making (MCDM) models: VlseKriterijumska optimizacija I Kompromisno Resenje (VIKOR), technique for order preference by similarity to ideal solution (TOPSIS), simple additive weighing (SAW), compound factor (CF).