Abstract

Different spatial configurations (or scenarios) of multiple best management practices (BMPs) at the watershed scale may have significantly different environmental effectiveness, economic efficiency, and practicality for integrated watershed management. Several types of spatial configuration units, which have resulted from the spatial discretization of a watershed at different levels and used to allocate BMPs spatially to form an individual BMP scenario, have been proposed for BMP scenarios optimization, such as the hydrologic response unit (HRU) etc. However, a comparison among the main types of spatial configuration units for BMP scenarios optimization based on the same one watershed model for an area is still lacking. This paper investigated and compared the effects of four main types of spatial configuration units for BMP scenarios optimization, i.e., HRUs, spatially explicit HRUs, hydrologically connected fields, and slope position units (i.e., landform positions at hillslope scale). The BMP scenarios optimization was conducted based on a fully distributed watershed modeling framework named the Spatially Explicit Integrated Modeling System (SEIMS) and an intelligent optimization algorithm (i.e., NSGA-II, short for Non-dominated Sorting Genetic Algorithm II). Different kinds of expert knowledge were considered during the BMP scenarios optimization, including without any knowledge used, using knowledge on suitable landuse types/slope positions of individual BMPs, knowledge of upstream–downstream relationships, and knowledge on the spatial relationships between BMPs and spatial positions along the hillslope. The results showed that the more expert knowledge considered, the better the comprehensive cost-effectiveness and practicality of the optimized BMP scenarios, and the better the optimizing efficiency. Thus, the spatial configuration units that support the representation of expert knowledge on the spatial relationships between BMPs and spatial positions (i.e., hydrologically connected fields and slope position units) are considered to be the most effective spatial configuration units for BMP scenarios optimization, especially when slope position units are adopted together with knowledge on the spatial relationships between BMPs and slope positions along a hillslope.

Highlights

  • Different best managementpractices practices(or(orbeneficial beneficialmanagement managementpractices, practices,best management practices (BMPs)BMPsforforshort) short)Different best management scenarios at the watershed scale may have scenarios at the watershed scale may have significantly significantly different environmental effectiveness, economic efficiency, and practicality [1,2,3,4,5,6].They different environmental effectiveness, economic efficiency, and practicality [1,2,3,4,5,6]

  • Using the strategies that adopt BMP. Configuration knowledge, those non-effective configuration knowledge, those non-effective configurations generated by the random configuration strategy (Section 2.5) can be avoided for all configurations generated by the random configuration strategy (Section 2.5) can be avoided for all BMP configuration units

  • This paper presents a comparison among the four main types of BMP configuration units (i.e., hydrologic response unit (HRU), spatially explicit HRUs, hydrologically connected fields, and slope position units) for watershed BMP scenarios optimization based on the same one distributed watershed model

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Summary

Introduction

BMPs) at the watershed scale may have scenarios (i.e., spatial configurations of multiple BMPs) at the watershed scale may have significantly significantly different environmental effectiveness, economic efficiency, and practicality [1,2,3,4,5,6]. They different environmental effectiveness, economic efficiency, and practicality [1,2,3,4,5,6]. Economic efficiency of watershed BMP scenarios and propose optimal ones.optimal.

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