Researchers from Tianjin Normal University (TNU), in collaboration with Tianjin University, the Chinese Research Academy of Environmental Sciences, and Beijing Normal University, have developed a novel Water Cycle Intensity (WCI) evaluation model based on landscape indices. This groundbreaking research, which analyzes the evolution and status of the water cycle in the Haihe River Basin, has been published in Ecological Indicators, an internationally renowned academic journal in the field of ecological and environmental sciences.

In recent years, landscape patterns and water cycle processes have changed significantly as a result of intensive interference from human activities. While the intensification of the global water cycle has been well elaborated from the perspective of climate change, and some scholars have linked landscape spatial patterns with hydrological processes for ecological or water quality assessments, the use of landscape indices to characterize the evolution of the water cycle remains relatively unexplored.

This study addresses this gap by examining the evolution of the water cycle from the perspective of landscape patterns. The authors established a WCI evaluation model based on landscape indices and analyzed the trends and status of the water cycle in the Haihe River Basin. The proposed method can be effectively applied to evaluating and predicting water cycle status in ungauged basins or future landcover scenarios, particularly in regions facing water scarcity or ecological fragility. This approach aids in the formulation of more rational water resource development and management strategies, ensuring the sustainable use of water resources.

The research reveals the relationship between the evolution of the water cycle and changes in landscape patterns in the Haihe River Basin, providing a new methodology for studying water cycle evolution. It also offers critical scientific insights and practical guidance for regional planning, water resource management, and climate change adaptation. Traditional water cycle studies have primarily relied on climate change perspectives, but this research breaks new ground by using landscape pattern changes to characterize water cycle evolution, offering a more comprehensive analytical framework. The findings underscore the importance of optimizing landscape patterns to enhance regional resilience to climate change, particularly in rapidly urbanizing areas where overexploitation could lead to water resource depletion and ecological degradation. As global climate change intensifies, the evolution of water cycle is expected to become more complex. Therefore, future water resource management strategies must place greater emphasis on landscape optimization to improve adaptability to climate change.

For more details, please refer to the original article: https://www.sciencedirect.com/science/article/pii/S1470160X24001389