A Novel Non-Parametric Data Envelopment Analysis (DEA) Approach in Sub-basin Prioritization for Watershed Management in the Kumari River Basin, India

Abstract

Abstract In a country like India where economy of the area is predominantly based on agriculture, a maximum proportion of people are dependent upon cultivation and therefore the soil health plays as engine to the enhancement of the agricultural productivity. Continuous soil erosion leads to the loss of top soil that has been responsible for systematic degradation of the soil and natural environment with time. In this context, watersheds, as a scale of natural boundaries, can be applied to implement a comprehensive soil management plan for the systematic conservation of the soil resource. In this situation, watershed management has emerged as a new approach that is based on the interrelationships between landuse, soil, and water and the process of planning and management of land, soil, water resources as well as the biotic resources. It is well accepted that the measurement of actual soil loss is not possible, so different proxies and prediction-based models of erosion susceptibility have been widely used for assessing the soil loss. Sub-basin prioritization with respect to erosion susceptibility, therefore, has become increasingly popular in the last few decades as this helps in optimal distribution of resources for management. In a country like India, where the availability of resources is limited, optimal distribution of resources becomes a challenge. Erosion is a complex problem wherein a large number of factors play an important role in influencing this process. Therefore, Multi-Criteria Decision Making (MCDM) techniques are now becoming more popular in this aspect. However, there are a myriad parametric and non-parametric MCDM models have been used to measure sub-basin soil erosion susceptibility. In terms of the non-parametric techniques, the most common are composite ranks. But the linear programming algorithm-based Data Envelopment Analysis (DEA) technique takes into account one possible optimal solution based on a number of solutions. Although the DEA technique is extremely popular in the domain of business management, this approach has never been used in the domain of resource and hazard management. So, this study is a novel approach in this field where the DEA technique has been introduced for sub-basin prioritization. The approach that has been included for this study is one of profit maximization i.e., the maximum efficiency of the sub-watersheds in terms of erosion susceptibility. So, the basins which are characterized by higher DEA scores are experiencing greater risk of erosion (and hence require prioritization). In the Kumari Basin, the sub watershed wise erosion susceptibility does not show any spatial pattern. The most erosion susceptible sub-watersheds which require the greatest priority for the right bank watersheds as compare to the left bank tributary include DMDR041R013, DMDR041R002, DMDR041R009, DMDR041R016 and DMDR041R014.