To study the impact of land—use structure and landscape pattern on water quality at different spatial scales in the Dan River Basin (Qin Ling Mountains, China), water samples from 21 sites along the Dan River were collected in 2022 during the dry and wet seasons, and nine water quality indices were tested. Land—use composition and landscape pattern indices at riverine reach, riparian, and sub—basin were obtained, and correlation analysis and redundancy analysis (RDA) were used to determine the relationship with water quality. The results are as follows. (1) Water quality in the Dan River is better in the wet season than in the dry season; the main pollutants are total nitrogen (TN) and total phosphorus (TP). (2) The impact of land—use composition and landscape pattern on water quality has a scale effect; riverine reach can best explain the water quality. (3) Agricultural land and forest have the greatest impacts on water quality; agricultural land and construction land aggravate the deterioration of water quality, while forest, grassland, and water area have positive effects on water quality. The largest patch index (LPI) and contagion index (CONTAG) were positively correlated with pollutants, while Patch richness density (PRD), Patch shape (PD), Shannon’s diversity index (SHDI), and landscape shape index (LSI) were negatively correlated with pollutants, indicating that with an increase in the impact of human activities on landscapes, the degree of fragmentation decreases patch richness, landscape shape tends to be simplified, and water pollution is eventually aggravated. Land planners should focus on optimizing the land—use structure and landscape pattern to increase the diversity of the landscape. Therefore, strict environmental regulations must be established.

The Chinese Loess Plateau has undertaken a large-scale “Grain for Green” project since 1999. Understanding how reforestation affects soil moisture is crucial for ecological construction and the region’s revegetation. In this study, soil sensors were installed to monitor the soil moisture content (SMC) and soil desiccation intensity in a 0–200 cm soil profile online during the growing season, with farmland as a control and Robinia (R.) pseudoacacia L., Pinus (P.) tabulaeformis Carr., Populus (P.) alba L., and Ulmus (U.) pumila L. were selected. The results showed that the SMC increased with soil depth, and the soil moisture storage (SMS) in the 0–200 cm soil profile was ranked as R. pseudoacacia L. (424.3 mm) < farmland (479.8 mm) < U. pumila L. (569.8 mm) < P. alba L. (583.9 mm) < P. tabulaeformis Carr. (589.8 mm). Secondly, the percentages of inefficient water and gravimetric water in soil moisture were ranked as R. pseudoacacia L. (63%) > farmland (49%) > U. pumila L. (43%) > P. alba L. (17%) > P. tabulaeformis Carr. (11%). The soil desiccation intensity of artificial forests was heavy in June, light in April and July, and no desiccation in the other months. Moderate desiccation was discovered in the 0–40 cm soil layer and mild desiccation occurred in the 40–60 cm soil layer. Additionally, the representative soil layer for SMS in farmland for P. tabulaeformis Carr., U. pumila L., and R. pseudoacacia L. was the 90 cm soil layer, and the SMS representative soil layer for P. alba L. was the 70 cm soil layer. In brief, an SMS deficit occurred after the conversion of the farmland to R. pseudoacacia L., but there was an SMS surplus after the conversion of the farmland to P. alba L., U. pumila L., and P. tabulaeformis Carr. This suggests that the artificial forest species could be optimized by introducing P. tabulaeformis Carr. instead of R. pseudoacacia L., and the degradation of R. pseudoacacia L. could be suppressed by the application of a nitrogen fertilizer. Our research demonstrated that soil moisture depletion patterns were closely related to artificial forest species, and attention should be paid to the vegetation restoration and maintenance of afforestation achievements in water-constrained arid regions in the future.