Identification of priority areas for water ecosystem services by a techno-economic, social and climate change modeling framework.

Water scarcity and quality deterioration often occur in economically developing regions, particularly during crises related to climate change or increasing human activities. The assignment of priority areas is considered a suitable strategy for stakeholders to mitigate water crises and cope with water stress. However, most studies focused on protecting water bodies in priority areas and did not consider the hydrological/hydrochemical/hydroecological interaction between aquatic and terrestrial ecosystems. We divided a watershed into manageable areas to select priority areas for multiple water-related ecosystem services (WES-priority areas), considering the aquatic-terrestrial interactions to predict the effects of climate change and human activities. The proposed novelty framework couples the soil and water assessment tool and maximum entropy models with a systematic conservation planning tool. It uses the gross domestic product as the economic cost to assess dynamic changes and social-environmental driving forces. A case study is conducted in the Xiangjiang River basin, a modified watershed of the main tributary of the Yangtze River, China. Results revealed that most of the WES-priority areas were located in the southern and southeastern regions of the upper reaches in all climatic scenarios. The conservation efficiency of the WES-priority areas decreased from 1.264 to 0.867 in 50 years, indicating that the level of protection declined as climate change accelerated. The precipitation was positively correlated with the WES-priority area selection in all climate scenarios. The temperature was only negatively correlated with the WES-priority areas when it exceeded 20 °C, and this effect became more pronounced as the temperature increased. The topographic factors had the most crucial impacts on the upstream priority areas selection. The water flow regulation service played a leading role in identifying WES-priority areas in the middle reaches because the priority areas' distribution here was closely related to the water yield, and its proportion decreased with the acceleration of global warming. The number of WES-priority areas was relatively low in the lower reaches. It was positively associated with the gross domestic product and the amount of built-up land. The proposed framework for WES-priority areas identification enables a sound trade-off between environmental protection and economic development.

Detecting changes in water level caused by climate, land cover and dam construction in interconnected river-lake systems.

There is a growing recognition of the broader environmental significance of exploring the relative importance of climate change and anthropogenic impacts on hydrologic fluctuations in river-lake systems. In the case of Dongting Lake, the typical river-lake system, we collected the water level from 1990 to 2019, spanning before and after the operation of the Three Gorges Dam (TGD) in 2003. This study was conducted to detect water level fluctuations in Dongting Lake and to quantify the relative influence of climate, land cover and dam construction on water levels. We defined the impact of the dam construction as the three inlets inflow of Yangtze River (In-YR), and four waters inflow of Hunan (In-HN). The Mann-Kendall (M-K) test revealed the trends and change points of water level fluctuations. Structural Equation Model (SEM) was used to detect the direct and indirect effects of these factors on water level and quantify their relative importance. The MIKE21 hydrodynamic model reflected the spatial-temporal variability of water levels under the action of key driver. The results showed that the water level appeared a downward trend during 1990-2019 and the change point appeared in 2003; During 1990-2002, the significant factors were: precipitation (V = 0.469, P = 0.013), evaporation (V = -0.424, P = 0.029), non-agricultural cover (V = -0.334, P = 0.025), and agricultural cover (V = 0.235, P = 0.033); During 2003-2019, the significant factors were: In-YR (V = 0.436, P = 0.007), In-HN (V = 0.431, P = 0.012), and precipitation (V = 0.349, P = 0.045); The In-YR was the key factor affecting the changes of the water level during 1990-2019; Under the influence of In-YR, the most obvious fluctuation of water level was in the flood adjustment period (Jun-Aug) and the impoundment period (Sep-Nov) when the average declined by about 0.50 and 0.67 m, respectively. Our findings provide a new insight into how to better maintain the stability of river-water system water resources under the influence of multiple factors.