Spatial optimization of watershed best management practice scenarios based on boundary-adaptive configuration units
Spatial optimization of watershed best management practice scenarios based on boundary-adaptive configuration units
复制标题
基于边界自适应配置单元的流域最佳管理实践场景空间优化
DOI：
10.1177/0309133320939002
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发表时间：
2020-07
期刊：
影响因子：
--
通讯作者：
Zhu A-Xing
中科院分区：
文献类型：
--
作者：
Zhu Liang-Jun;Qin Cheng-Zhi;Zhu A-Xing
基于流域建模的流域最佳管理实践情景空间优化是一种有效的流域管理决策支持工具。在这种优化过程中，用于配置BMP的现有BMP配置单元类型（或BMP配置单元，如子流域、水文响应单元、农场）在BMP情景优化之前通过空间离散化创建后保持固定边界。这种“边界固定”方法不允许调整BMP配置单元的空间特征。因此，它有可能错过通过调整单元边界可以获得的最佳BMP场景，并且可能产生不太有效的空间优化。在本文中，我们提出了一种基于边界自适应配置单元的BMP场景空间优化方法。本文提出的优化方法采用坡位（沿山坡的基本地貌单元，与物理山坡过程具有内在联系）作为BMP配置单元，并在优化过程中利用坡位的空间梯度定量信息（即模糊坡位）动态调整其边界。通过对福建尤乌镇流域的实例研究表明，与边界固定单元相比，所提出的优化方法能够显著扩大搜索空间，获得最优BMP情景，且具有更好的成本效益和更高的优化效率。本文提出的优化方法为BMP场景的空间优化提供了一个新的框架，在该框架中，其他流域模型、智能优化算法和可用于边界调整的BMP配置单元可以以边界自适应的方式应用于BMP场景的优化。该研究还举例说明了将与物理山坡过程和bmp相关的斜坡位置单位的定性、模糊和经验地理知识转化为定量、明确和自动化的地理空间算法的潜力，从而以更有地理意义的方式有效地解决环境管理问题。
Spatial optimization of watershed best management practice (BMP) scenarios based on watershed modeling is an effective decision support tool for watershed management. During such optimization, existing types of BMP configuration units for configuring BMPs (or BMP configuration units, e.g. subbasins, hydrologic response units, farms) remain fixed boundaries once they have been created through spatial discretization prior to BMP scenario optimization. This sort of “boundary-fixed” method does not allow for adjustments to the spatial characteristics of BMP configuration units. Hence, it runs the risk of missing superior BMP scenarios that could have been obtained by adjusting unit boundaries and may produce less effective spatial optimization. In this article, we propose a new approach to the spatial optimization of BMP scenarios based on boundary-adaptive configuration units. The proposed optimization approach adopts slope positions (basic landform units along hillslopes inherently related to physical hillslope processes) as BMP configuration units and dynamically adjusts their boundaries by using quantitative information about their spatial gradation (i.e. fuzzy slope positions) during the optimization. A case study conducted in the Youwuzhen watershed in Fujian, China, showed that the proposed optimization approach can significantly enlarge the search space and obtain optimal BMP scenarios with better cost-effectiveness and higher optimization efficiency than with boundary-fixed units. The proposed optimization approach provides a new alternative framework for spatial optimization of BMP scenarios, in which other watershed models, intelligent optimization algorithms, and BMP configuration units available for boundary adjustment can be applied to BMP scenario optimization in a boundary-adaptive manner. This study also exemplifies the potential for transforming qualitative, vague, and empirical geographical knowledge about slope position units related to physical hillslope processes and BMPs into quantitative, explicit, and automated geospatial algorithms for effectively resolving environmental management problems in a more geographically meaningful way.
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影响因子：
4.9
作者：
Liangjun Zhu;Junzhi Liu;Cheng-Zhi Qin;A-Xing Zhu
通讯作者：
A-Xing Zhu
影响因子：
2.3
作者：
Jing Yao;Xiaoxiang Zhang;Alan T. Murray
通讯作者：
Jing Yao;Xiaoxiang Zhang;Alan T. Murray
基于坡位单元的流域最佳管理实践空间优化
影响因子：
3.9
作者：
Qin Cheng-Zhi;Gao Huiran;Zhu Liang-Jun;Zhu A-Xing;Liu Junzhi;Wu Hui
通讯作者：
Wu Hui
影响因子：
5.4
作者：
H. G. Rodriguez;J. Popp;C. Maringanti;I. Chaubey
通讯作者：
H. G. Rodriguez;J. Popp;C. Maringanti;I. Chaubey
影响因子：
3.8
作者：
Jiali Qiu;Zhenyao Shen;Maoyi Huang;Xuesong Zhang
通讯作者：
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