Spatial optimization of watershed best management practices based on slope position units
Spatial optimization of watershed best management practices based on slope position units
复制标题
基于坡位单元的流域最佳管理实践空间优化
DOI：
10.2489/jswc.73.5.504
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发表时间：
2018
影响因子：
3.9
通讯作者：
Wu Hui
中科院分区：
文献类型：
--
作者：
Qin Cheng-Zhi;Gao Huiran;Zhu Liang-Jun;Zhu A-Xing;Liu Junzhi;Wu Hui
最佳管理措施的空间优化是选择和分配最佳管理措施的有效途径，可用于水土保持和减少非点源污染等流域管理。BMP配置的常用空间单元(或BMP配置单元)包括子盆地、水文响应单元(HRU)、农场和田地。通常，从山坡尺度的自然地理角度(例如山坡的地貌和水文条件)来看，这些空间单元并不是同质的功能单元，因此不能有效地反映从上游到下游的山坡过程中边界条件和空间位置之间的空间关系。这使得高效、合理地构建流域BMP的空间优化变得困难。提出了一种基于坡位单元的空间BMP优化方法，坡位单元是具有自然地理特征的同质空间单元。该方法将坡位单元作为BMP配置单元，通过遗传算法(即NSGA-II)在BMP场景初始化和优化过程中显式考虑BMP与坡面位置的关系。采用基于物理的分布式流域模型来评价环境效益(即土壤侵蚀减少率)，并开发了一种简单的估算方法来计算BMP情景的净成本。以福建省东南部典型红壤区中国的一个小流域为例进行了研究，该红壤区是土壤侵蚀严重的地区。使用三种类型的坡位(即山脊、后坡和山谷)的简单系统来描绘BMP构型单元。该方法考虑了中国红壤地区实际使用的4种BMP方案(封育措施、乔灌草混交林、低质量森林改良和果园改良)，以达到最大化土壤侵蚀减少率和最小化BMP方案的净成本的多重优化目标。与在BMP配置单元上随机选择和分配BMP的标准随机优化方法进行了比较。实验结果表明，与随机方法相比，该方法能更有效地提出实用的BMP场景。
Spatial optimization of best management practices (BMPs) is an effective way to select and allocate BMPs for watershed management such as soil and water conservation and nonpoint source pollution reduction. The commonly used spatial units for BMP configuration (or BMP configuration units) include subbasins, hydrologic response units (HRUs), farms, and fields. Normally, these spatial units are not homogeneous functional units from the perspective of physical geography at the hillslope scale (in terms of geomorphic and hydrologic conditions of the hillslope, for example), and thus cannot effectively represent the spatial relationships between BMPs and spatial locations with respect to hillslope processes from upstream to downstream. This makes it difficult to efficiently and rationally construct spatial optimizations for watershed BMPs. This paper proposes a spatial BMP optimization approach based on slope position units, which are homogeneous spatial units with physical geographic features. In the proposed approach, slope position units are used as BMP configuration units by which the relationships between BMPs and slope positions along a hillslope can be explicitly considered during BMP scenario initialization and optimization via genetic algorithm (i.e., NSGA-II). A distributed and physically based watershed model was used to evaluate the environmental effectiveness (i.e., the reduction rate of soil erosion), and a simple estimation method was developed to calculate the net cost of BMP scenarios. A case study was conducted in a small hilly watershed in the typical red-soil region of the Fujian Province in southeastern China, which suffers severely from soil erosion. A simple system of three types of slope positions (i.e., ridge, backslope, and valley) was used to delineate BMP configuration units. Four BMPs that are used in actual Chinese red-soil regions (closing measures, arbor-bush-herb mixed plantation, low-quality forest improvement, and orchard improvement) were considered in the proposed approach to achieve the multiple optimization objectives, which included maximizing the reduction ratio of soil erosion and minimizing the net cost of the BMP scenario. The proposed approach was compared with the standard random optimization approach, which selects and allocates BMPs randomly on BMP configuration units. The results show that the proposed approach is more effective and efficient for proposing practical and effective BMP scenarios than the random approach.