Groundwater is important for maintaining ecosystem balance. However, the ecological value of groundwater is always undervalued, while its value as water resources is emphasized. Thus, this paper divided the systematic valuation of groundwater-dependent ecosystems (GDEs) into three categories, and its services into four categories based on the utilization. In addition, a service valuation system was developed, with ten indicators and nine assessment models for the GDEs. We then used this model to value the GDEs services of Handan city in 2015 as a case study, with seven relevant indicators. The results show that the total value of Handan’s GDEs is 9.10 billion Renminbi (RMB, Chinese unit of currency), including a direct use value of 3.53 billion, and an indirect use value of RMB 5.57 billion. These results highlight the significant indirect use value of GDEs. Consequently, groundwater resources should be rationally exploited to maximize both direct and indirect service values on the basis of a comprehensive understanding of the inherent value of the resource.

Due to global warming, global and regional extreme precipitation events occur frequently, causing severe drought and flood disasters. This has a significant impact on productivity and human life. Therefore, it is of great significance to study the characteristics of extreme precipitation and its spatiotemporal variation. In this study, we investigate the dominant variation patterns of extreme precipitation (EP), which is characterized by indices, and also analyze its potential causes in the Shandong province of China during 1961–2015 using the daily precipitation data from 123 metrological stations. The results show that there has been a dry trend in the Shandong Province in the past 55 years, that is, with the decrease in precipitation, most of the extreme precipitation index has basically showed a downward trend to varying degrees. In particular, the increase in the number of consecutive dry days (CDD) and the decrease in the number of consecutive wet days (CWD) can better explain the drought in this region. After the 1980s, the extreme precipitation index basically showed an upward trend to varying degrees, indicating that extreme precipitation events have shown an increasing trend in recent years. The spatial distribution of each extreme precipitation index generally increased from north to south. The mutation of each extreme precipitation index occurred in the 1970s and 1990s, and there was a main period of 0.9–2.2 years. In terms of influencing factors, the NINO3 area can be used as the critical sea area for the response of extreme precipitation to SSTAs in the Shandong Province. The research results are helpful to understand the temporal and spatial variations of extreme precipitation and have very important reference value for the prediction of and response to climate change and extreme events in the future.

Watershed water cycles undergo profound changes under changing environments. Analyses of runoff evolution characteristics are fundamental to our understanding of the evolution of water cycles under changing environments. In this study, linear regression, moving average, Mann–Kendall, Pettitt, accumulative anomaly, STARS, wavelet analysis, and CEEMDAN methods were used to analyze the trends, mutations, and periodic and intrinsic dynamic patterns of runoff evolution using long-term historical data. The intra-annual distribution of runoff in the Dawen River Basin was uneven, with an overall decreasing trend and mutations in 1975–1976. The main periods of runoff were 1.9 and 2.2 years, and the strongest oscillations in the study period occurred in 1978–1983. The runoff decomposition high-frequency term (intra-annual fluctuation term) had a stronger fluctuation frequency, with a period of 0.51–0.55 years, while the low-frequency term (interannual fluctuation term) had a period of 1.55–2.26 years. The trend term for the runoff decomposition tended to decrease throughout the monitoring period and gradually stabilized at the end of the monitoring period, while the period gradually decreased from upstream to downstream. In summary, we used multiple methods to analyze the evolutionary characteristics of runoff, which are of great relevance to the adaptive management of water resources under changing environments.

Surface runoff change is significantly influenced by both human activities and climate change. Decoupling their respective contributions to runoff change represents a critical frontier in hydrological research and a pressing challenge for water resource management. This study focuses on the Dawen River Basin, a strategic area for ecological conservation and high-quality development in the lower Yellow River region. By integrating three methodological approaches—empirical models (Precipitation–Runoff Double Mass Curve), conceptual models (elasticity coefficient methods), and hydrological models (Soil and Water Assessment Tool, SWAT)—we systematically quantify the impacts of climate change and human activities on runoff change. A correlation analysis was first applied to screen independent runoff drivers and basin characteristic factors, followed by a random forest algorithm to rank their relative importance. This process informed the establishment of a comprehensive framework for runoff attribution analysis. Results demonstrate that hydrological modeling (SWAT) is the most appropriate method for the Dawen River Basin, revealing human activities as the dominant driver of runoff changes, accounting for 70% to 82%. These findings provide critical insights for guiding sustainable water resource planning and management in anthropogenically stressed basins under a changing environment.