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.

Soil water is a crucial factor for the growth of vegetation and sustainable development in water-limited areas. After large-scale vegetation restoration on the Chinese Loess Plateau, understanding the relationship between vegetation and deep soil moisture has become a crucial focus in current research. In this study, we selected artificial forest ( Pinus tabulaeformis, Robinia pseudoacacia, and Platycladus orientalis), apple orchard, secondary forest and farmland as the research objects, and native grassland as the control, using soil drilling techniques, we systematically monitored the soil water content of 0-10 m soil layer over two hydrological years, and explore the effects of different vegetation types on soil water deficiency. The results showed that: (1) The deep soil water various significantly among different vegetation types, which indicating the depth of the influence of vegetation on soil water has reached 10 m. (2) The mean deficit size values of P. tabulaeformis (0.14), R. pseudoacacia (0.17), P. orientalis (0.07), apple orchard (0.15) and secondary forest (0.10) and farmland (0.27) were positive in 0–1 m, indicating that surface soil water had accumulated during more than half of the sampling periods. In the 2–10 m soil layer, the mean deficit size was negative in all vegetation types except in farmland, leading to soil desiccation. The deficit size was found to fluctuate with soil depth. (3) Soil water deficit degree was affected by a combination of soil properties and vegetation growth. Altitude, soil bulk density and canopy density had a significant impact on soil water deficit. Our results indicate that the current afforestation model could lead to the deficiency of deep soil water. Therefore, in planning future vegetation allocation and management, it is imperative to make reasonable vegetation structure according to the available local soil and water resources.

Characterizing soil water content (SWC) dynamics is a prerequisite for conducting sustainable vegetation restoration on the Chinese Loess Plateau. However, quantifying the variations of the SWC in the deep soil layers remains a challenge because of the different driving factors and the complexity of surface processes. In this study, SWC in 0–10 m of artificial forestlands (AF), apple orchard (AO), native forestland (NF), farmland (maize; FL), and native grassland (NG) were monitored during 2019–2020. The deficit size (DS) and recovery index (RI) were used to explore the effects of vegetation types on SWC. The results showed that the SWCs of forestlands were significantly lower than the SWC of native grassland (12.32%) and tree species significantly affected the SWC. The monthly DS values in forestlands were negative, while those of FL were positive. The DS value in 0-10 m and predictive values below 10 m were negative of forestlands. Thus, tree planting may have consumed soil water at a depth of > 10 m. During the investigation period, soil water was restored in 0–1 m with the positive RI values. In addition, artificial forestlands showed good performance in deep soil water recovery. Canopy density was the controlling factor for soil water restoration. Our results demonstrated that the current afforestation mode used more soil water but was conducive to deep soil water conservation. Therefore, reasonable adjustments should be made according to the local soil and water resources for future vegetation selection and management.