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• Introduce an evaluation approach for the Ecological Service Value of Water (ESV-W). • Improve the assessment of Ecosystem Services Value (ESV) by introducing the Agricultural Price Index (API) into the Equivalence Factor (EF). • Improve the Water Allocation and Simulation Model (WAS) to simulate and quantify the 'natural-artificial' soil water cycle. • Analysis of the ESV and ESV-W in the Yangtze River Basin from 2005 to 2020. This paper introduces an evaluation approach for the Ecological Service Value of Water (ESV-W) by coupling the assessment of Ecosystem Services Value (ESV) with the Water Allocation and Simulation Model (WAS). The proposed method is applied to evaluate ESV and ESV-W in the Yangtze River Basin from 2005 to 2020. Firstly, an improved Equivalence Factor (EF) method is employed to estimate ESV by considering different land use types and service categories. Then, the enhanced WAS model is used to quantify and identify the role of the 'natural-artificial' soil water cycle in supporting the ecological service functions. Finally, by integrating the ESV evaluation system with the WAS model, the evaluation method for ESV-W is established. The results indicated that from 2005 to 2020, the total ESV increased from 4.0 to 5.6 trillion US Dollars, with forests being the primary contributor among land use types (about 52%), and regulating services are dominating among service categories (about 70%). The spatial distribution of the ESV showed a decreasing trend from southeast to northwest in the Yangtze River Basin, while the ESV-W exhibited high values concentrated along the main stream of the upper reaches of the Yangtze River and lower in the middle. The ESV-W of the 'natural' soil water cycle still dominates (over 96%), but the ESV-W of the 'artificial' soil water cycle has been rapidly increasing in recent years. In 2020, the ESV-W per unit water of precipitation, irrigation, and ecological water were 4.0 Dollars/ m 3 , 0.7 Dollars/ m 3 , and 32.4 Dollars/ m 3 , respectively. This study aims to provide references for the protection of water ecosystems and the sustainable utilization of water resources. It also serves as a reference for improving the evaluation system of ESV. [ABSTRACT FROM AUTHOR]

[Display omitted] • Water recession pattern were classified as optimal, early, or late water recession. • Phenological mismatch is the days between geese arrival and timing of optimal NDVI. • Unusually early or late water level recession leads to a greater mismatch. • Greater mismatch negatively affected Lesser White-fronted Goose abundance. • Greater mismatch resulted in a clumped Lesser White-fronted Goose distribution. Phenological mismatches between migratory birds and food availability driven by global warming have been found to influence the fitness and population dynamics of several herbivorous goose species in Arctic breeding sites. However, the effect of phenological mismatches at wintering sites have been inadequately studied. We used long-term data to explore the consequences of water regime changes on phenological mismatch (i.e., days between arrival of geese and timing of the optimal Normalized Difference Vegetation Index [NDVI opt ]) and detect the relative role of the mismatch as a driver of annual variations in abundance and distribution of the Lesser White-fronted Goose Anser erythropus (a vulnerable species on the IUCN Red List) in East Dongting Lake, which is the one of this species' largest wintering sites worldwide. The NDVI of the Carex meadow (i.e., the dominant vegetation in East Dongting Lake wetland and also the major food resource for the geese) was used as the phenology metric. Results showed that the water recession pattern greatly influenced food conditions when geese arrived at the site. Early water recession led to significantly higher NDVI, whereas late water recession led to significantly lower NDVI than did the optimal water recession. However, the suitable habitat area was significantly larger under the optimal water recession pattern. Both early and late water level recessions caused greater mismatches and resulted in lower geese abundance and a more concentrated distribution. NDVI was positively correlated with aboveground biomass and negatively correlated with N% of Carex spp. High biomass and low N% related to high NDVI caused by early water recession may indicate unfavorable food conditions at the time that geese arrive and reduced sustainable food availability in mid-winter, while a low NDVI and limited habitat area caused by late water recession may indicate an insufficient food supply. In conclusion, non-optimal water recession led to a greater phenological mismatch and resulted in limited habitat quality (e.g., lower leaf N%) under early water recession but limited habitat quantity (e.g., smaller habitat area and lower aboveground biomass) under late water recession, and ultimately threatened the Lesser White-fronted Goose. Our results contributed to explaining the decline of the Lesser White-fronted Goose population in this wintering site. [ABSTRACT FROM AUTHOR]