Ministry of Education Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Hohai University, Nanjing 210098, China; Yangtze Institute for Conservation and Development, Hohai University, Nanjing 210098, China.
Ministry of Education Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Hohai University, Nanjing 210098, China; Yangtze Institute for Conservation and Development, Hohai University, Nanjing 210098, China.
Sci Total Environ. 2024 Nov 20;952:176021. doi: 10.1016/j.scitotenv.2024.176021. Epub 2024 Sep 3.
Rivers are undergoing significant changes under the pressures of natural processes and human activities. However, characterizing and understanding these changes over the long term and from a spatial perspective have proven challenging. This paper presents a novel framework featuring twelve indicators that combine geometric and spatial structures for evaluating changes in river network patterns. Through global principal component analysis, these indicators were integrated into a comprehensive river network pattern index (RNP). Employing Pearson correlation analysis, geographically weighted regression, geographic detector models, and the Shapley Value, the study quantitatively analyzed various stressors' impacts and relative contributions on river network changes from the 1960s to 2015s. The results showed a clear trend of degradation over time, particularly with frequency and density declining by 57 % and 48 %, respectively. The changes across subbasins varied temporally and spatially, with the 1980s emerging as a significant temporal hotspot and six spatial hotspots identified among twenty subbasins. The analysis showed that agriculture was significantly negatively associated with RNP, while the relationship between urbanization and RNP was inverted N-shaped. To address the negative effects of human activities, a shift from uniform management approaches is crucial. In agricultural areas, adopting more intensive farming practices could help mitigate negative impacts on RNP. For highly urbanized regions, city planning should consider the interactions between urbanization and other factors affecting RNP. Overall, incorporating an understanding of RNP's spatial-temporal dynamics and driving factors into spatial planning is critical for creating effective and sustainable management strategies for human-river interactions.
河流在自然过程和人类活动的压力下正在发生重大变化。然而，从长期和空间角度来描述和理解这些变化一直具有挑战性。本文提出了一个新的框架，该框架具有 12 个指标，这些指标结合了几何和空间结构，用于评估河流网络模式的变化。通过全局主成分分析，将这些指标整合到一个综合的河流网络模式指数（RNP）中。利用 Pearson 相关分析、地理加权回归、地理探测器模型和 Shapley 值，从 1960 年代到 2010 年代，定量分析了各种胁迫因素对河流网络变化的影响及其相对贡献。结果表明，随着时间的推移，退化趋势明显，尤其是频率和密度分别下降了 57%和 48%。子流域之间的变化在时间和空间上存在差异，20 个子流域中有 6 个空间热点和 1980 年代出现了一个重要的时间热点。分析表明，农业与 RNP 呈显著负相关，而城市化与 RNP 的关系呈倒 N 型。为了应对人类活动的负面影响，必须从统一的管理方法转变。在农业区，采用更集约的耕作方式可能有助于减轻对 RNP 的负面影响。对于高度城市化的地区，城市规划应考虑城市化与影响 RNP 的其他因素之间的相互作用。总体而言，将 RNP 的时空动态和驱动因素的理解纳入空间规划对于制定有效的和可持续的人类与河流相互作用管理策略至关重要。
