Title: | Effects of different spatial configuration units for the spatial optimization of watershed best management practice scenarios |
Authors: | Zhu, L., C.-Z. Qin, A.-X. Zhu, J. Liu and H. Wu |
Year: | 2019 |
Journal: | Water |
Volume (Issue): | 11(2) |
Pages: | |
Article ID: | 262 |
DOI: | 10.3390/w11020262 |
URL (non-DOI journals): | |
Model: | SWAT |
Broad Application Category: | pollutant only |
Primary Application Category: | BMP assessment (genetic algorithm or similar optimization approach) |
Secondary Application Category: | sediment loss and transport |
Watershed Description: | 5.39 km^2 Youwuzhen drainage area, located in a severely eroded red-soil region in southeast China. |
Calibration Summary: | |
Validation Summary: | |
General Comments: | |
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. |
Language: | English |
Keywords: | spatial configuration units; best management practices (BMPs); spatial optimization; hydrologic response units (HRUs); hydrologically connected fields; slope positions; watershed process simulation |