Spatial optimization of watershed best management practices based on slope position units

Abstract

Information System (LREIS), the Institute of Geographic Sciences and Natural Resources Research (IGSNRR), the Chinese Academy of Sciences; the University of Chinese Academy of Sciences (UCAS) in Beijing, China; and the Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application in Nanjing, China. Hui-Ran Gao is a graduate student at the LREIS, the IGSNRR, the Chinese Academy of Sciences; and the UCAS in Beijing, China. Liang-Jun Zhu (corresponding author) is a doctoral student at the LREIS, the IGSNRR, the Chinese Academy of Sciences; and the UCAS in Beijing, China. AXing Zhu is a professor at the Key Laboratory of Virtual Geographic Environment (VGE),

Effects of Different Spatial Configuration Units for the Spatial Optimization of Watershed Best Management Practice Scenarios

“…Different best management practices (or beneficial management practices, BMPs for short) scenarios (i.e., spatial configurations of multiple BMPs) at the watershed scale may have significantly different environmental effectiveness, economic efficiency, and practicality [1][2][3][4][5][6]. They are valuable for decision-making of integrated watershed management to assess the environmental effectiveness and economic efficiency of watershed BMP scenarios and then propose optimal ones.…”

“…They are valuable for decision-making of integrated watershed management to assess the environmental effectiveness and economic efficiency of watershed BMP scenarios and then propose optimal ones. Currently, a popular approach to achieving this target is based on watershed modeling [7][8][9] coupled with intelligent optimization algorithms [2,4,5,[10][11][12][13], so-called BMP scenarios optimization. To conduct the BMP scenarios optimization, each individual BMP scenario is created by automatically selecting and allocating BMPs on spatial configuration units (also called BMP configuration units hereafter), which have resulted from the spatial discretization of a watershed at one among different levels (such as subbasins, and hydrologic response units; Figure 1).…”

“…However, using subbasins as BMP configuration Currently, spatial configuration units used in BMP scenarios optimization mainly include five types with different levels, i.e., subbasins [14][15][16][17], hydrologic response units (HRUs) [12,18,19], farms [10,11], hydrologically connected fields [5], and slope position units (i.e., landform positions at hillslope scale, such as ridge, backslope, etc.) [2].…”

“…Meanwhile, using subbasins as BMP configuration units can decrease the search space of spatial optimization more than that of the adoption of other more detailed spatial configuration units, and thus can achieve a better optimizing efficiency [15]. However, using subbasins as BMP configuration units is not available for configuring multiple spatially explicit BMPs within one subbasin while BMPs often have different effects on different spatial positions of a hillslope [2,21,22].…”

“…Similar to subbasins, HRUs are also inappropriate to serve as BMP configuration units for spatially explicit BMPs. Furthermore, the impact of BMPs of an upslope HRU on a downslope HRU cannot be represented [24], although this impact is important for incorporating the expert knowledge of spatial relationships between BMPs and spatial positions [2,5].…”