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Compared to the growing number of utility-scale solar farms (USFs) sitting in hilly regions, knowledge of the hydrological behaviors in responding to the installation of USFs in these environments remains limited. We present herein a novel model (the Solar-Farm model) to understand the hydrological behaviors following the construction of a USF in the Loess Hilly Region of China, by combining it with an index of hydrological connectivity (HC). Scenarios were designed to estimate the effects of climate and terrain in controlling the effects of the USF on soil erosion, by altering the mean annual precipitation amount, the frequency of precipitation events, and the relief amplitude. Our results show that land use changes (e.g., vegetation removal) incurred a considerable increase in the accumulative soil erosion (22.45%-66.48%) during the installation period. During the 40-year deployment period, photovoltaic panels (PVs) incurred an average of 0.138 m deeper erosion in the USF compared with the background rate without PVs. A wetter climate induced the highest increase (88.25%) in erosion. However, the relief amplitude and precipitation frequency are also confirmed as important controlling factors for soil erosion (increased by 85.42% and 58%, respectively). The HC was increased during both the construction (0.005-0.12) and operation periods (0.149-0.314). Correlation analysis presented that the landscapes with higher HC were more likely to be exposed to the risks of soil erosion. USFs could increase soil erosion by increasing runoff and local HC, and higher background HC in turn could further aggravate the effects of USFs on soil erosion.

<p>Groundwater-dependent ecosystems (GDEs) exist all over the world, especially in water-limited regions. To achieve better water management, it is necessary to map and identify GDEs. Central Asia (CA) is one of the most arid regions in the mid-latitudes and one of the major regions with shallow groundwater tables. However, the role of groundwater in the impacts of climate change and regional anthropogenic activities on environmental risks, especially regional desertification, is inadequately understood due to the limited available research on GDEs. In the present study, a remote sensing-based method was used for mapping GDEs in regional CA, and three means—overlay analysis, correlation analysis, and the water balance method—were adopted to validate the accuracy of the mapping outcomes. Our results indicated that: 1) GDEs were concentrated around large lakes and in central Kazakhstan (between 46°N and 50°N latitudes), and areas "Very Likely" and "Likely" to be GDEs accounted for 36.89%, and 28.85% of the total natural vegetation areas, respectively; 2) at the watershed scale, the Sarysu Basin had the largest proportion (94.02% of the area) of potential GDEs while the Ysyk-Kol Basin had the lowest proportion (17.84%); 3) all the three validation methods indicated a good performance for our GDE mapping results. We concluded that the remote sensing-based GDE identification method can be considered a potential approach for mapping GDEs regionally. Better recognition of relationships among groundwater availability, ecosystem health and groundwater management policies should be developed by conducting further studies, to protect GDEs and to prevent regional land degradation. </p>