Qi Qingqing, Wang Zipeng, Zhang Zezhong, Yin Hang, Lai Hexin, Zhao Yiyang, Wang Fei, Feng Kai
School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China.
Yinshanbeilu Grassland Eco-Hydrology National Observation and Research Station, China Institute of Water Resources and Hydropower Research, Beijing, 100038, China.
Sci Rep. 2025 Jul 22;15(1):26621. doi: 10.1038/s41598-025-11513-w.
Traditional concepts of river health and methods for identifying ecological river disconnection are not applicable to seasonal rivers. Given the substantial negative impact of ecological river disconnection on river ecosystems and the importance of groundwater and soil moisture for the ecology of seasonal rivers in arid and semi-arid regions, developing a comprehensive index for accurately identifying ecological river disconnection in these rivers is crucial. This study introduces a new Standardized Seasonal River Disconnection Index (SSRDI), which is based on a Standardized Index (SCI) and a three-variable Copula function. The SSRDI integrates surface water, groundwater, and soil water information to reveal the true hydrological conditions of seasonal rivers and provides a comprehensive analysis of ecological river disconnection patterns in Tabu River from 2002 to 2020. The findings are as follows: (1) The Gaussian Copula is most suitable for constructing the SSRDI for Tabu River. Optimal distribution functions vary across regions, times, and datasets; therefore, using the best monthly distribution functions to compute SRI, SGDI, and SSMI provides a more scientifically robust mathematical and statistical basis. (2) The SSRDI, which combines surface water, groundwater, and soil water, is more consistent with the actual hydrological conditions of Tabu River compared to the three univariate indices. (3) From 2002 to 2020, the SSRDI for Tabu River shows a continuous declining trend, albeit at a slowing rate. The overall pattern exhibits a cyclical trend of worsening followed by improvement, with June being the month of most severe ecological river disconnection. (4) The seasonal component of the SSRDI from 2002 to 2020 displays cyclical changes, with a mutation in June 2004. The trend component shows a general decline, with two mutations observed in April 2005 and February 2007. This study provides valuable insights for identifying ecological river disconnection of seasonal rivers. The index can be applied to monitoring, forecasting, and mitigating ecological river disconnection in arid and semi-arid river systems, and can more accurately and comprehensively grasp the true health status of seasonal rivers, which is of great significance for the sustainable development of seasonal river ecological environment.
传统的河流健康概念以及识别生态河流断流的方法并不适用于季节性河流。鉴于生态河流断流对河流生态系统有重大负面影响，且地下水和土壤湿度对干旱和半干旱地区季节性河流的生态至关重要，因此制定一个能准确识别这些河流生态河流断流的综合指标至关重要。本研究引入了一种新的标准化季节性河流断流指数（SSRDI），该指数基于标准化指数（SCI）和三变量Copula函数。SSRDI整合了地表水、地下水和土壤水信息，以揭示季节性河流的真实水文状况，并对塔布河2002年至2020年的生态河流断流模式进行了综合分析。研究结果如下：（1）高斯Copula最适合构建塔布河的SSRDI。最优分布函数因地区、时间和数据集而异；因此，使用最佳月度分布函数来计算SRI、SGDI和SSMI能提供更科学可靠的数学和统计基础。（2）与三个单变量指数相比，结合了地表水、地下水和土壤水的SSRDI与塔布河的实际水文状况更一致。（3）2002年至2020年，塔布河的SSRDI呈持续下降趋势，尽管下降速度在放缓。总体模式呈现出先恶化后改善的周期性趋势，6月是生态河流断流最严重的月份。（4）2002年至2020年SSRDI的季节成分呈现周期性变化，2004年6月发生突变。趋势成分总体呈下降趋势，在2005年4月和2007年2月观察到两次突变。本研究为识别季节性河流的生态河流断流提供了有价值的见解。该指数可应用于干旱和半干旱河流系统中生态河流断流的监测、预测和缓解，能更准确、全面地掌握季节性河流的真实健康状况，对季节性河流生态环境的可持续发展具有重要意义。
