A review: model estimations on effectiveness of best management practices for agricultural non-point source pollution control

Abstract

With the development of point source pollution control, Agricultural Non鄄point Source Pollution (AGNPS) issues have become increasingly prominent worldwide. Non鄄point source pollution is difficult to control because it comes from the everyday activities of many different people, such as fertilizing a lawn, using a pesticide, or constructing a road or building. Recently, the agricultural non鄄point source pollution control has become a hotspot in the water research. As a common tool used to reduce non鄄point source pollution, Best management practices (BMPs) have been widely adopted to improve water quality problems associated with agricultural nonpoint source pollution, however, there have been few realistic efforts to assess their effectiveness in reducing AGNPS pollution. The effectiveness of BMPs must be evaluated at various spatial and temporal scales before adoption. Models are more comprehensive that can reflect choice of mitigation at a widely range of scales and then to achieve the best cost鄄effectiveness selection and placement of BMPs for non鄄point source

Distribution characteristics of non-point source pollution of TP and identification of key source areas in Nanyi Lake (China) Basin: based on InVEST model and source list method

“…The non-point source pollution model is an effective tool for the description, evaluation, predictionand, and early warning of the non-point source pollution (Sun et al, 2017;Geng et al, 2014). The development process of non-point source pollution model mainly goes through four stages from simple to complex, namely the empirical model, 2 mechanism model, functional model, and improved model combined with 3S technology (Zhang et al, 2016).…”