Apple tree productivity is influenced by the quantity of water and nutrients that are supplied during planting. To enhance resource utilization efficiency and optimize yields, a suitable strategy for supplying water and nitrogen must be established. A field experiment was conducted using a randomized block group design on five-year-old apple trees in Ningxia, with two irrigation lower limit levels (55%FC (W1) and 75%FC (W2)) and four N application levels (0 (N1), 120 (N2), 240 (N3), and 360 (N4) kg·ha⁻¹). Our findings showed that leaf N content increased with a higher irrigation lower limit, but the difference was not statistically significant. However, the leaf N content significantly increased with increasing N application. The growth pattern of new shoots followed logistic curve characteristics, with the maximum new shoot growth rate and time of new shoot growth being delayed under high water and high nitrogen treatments. Apple yield and yield components (weight per fruit and number of fruits per plant) were enhanced under N application compared to no N application. The maximum apple yields were 19,405.3 kg·ha⁻¹ (2022) and 29,607 kg·ha⁻¹ (2023) at the N3 level. A parabolic relationship was observed between apple yield and N application level, with the optimal range of N application being 230–260 kg⸱ha⁻¹. Apple quality indicators were not significantly affected by the irrigation lower limit but were significantly influenced by N application levels. The lower limit of irrigation did not have a significant impact on the quality indicators of the apples. Water and N utilization efficiencies improved with the W2 treatment at the same N application level. A negative relationship was observed between the amount of nitrogen applied and the biased productivity of nitrogen fertilizer. The utilization of nitrogen fertilizer was 127.6 kg·kg⁻¹ (2022) and 200.3 kg·kg⁻¹ (2023) in the W2N2 treatment. The apple yield was sustained, the quality of the fruit improved, and a substantial increase in water productivity was achieved with the W2N3 treatment. The findings of this study can be used as a reference for accurate field irrigation.

Soil covering is a soil management technique used to address issues such as high alkalinity, nutrient deficiency, and a low soil and water-holding capacity in saline–alkali lands. Coal gangue, a solid waste generated from coal mining, contains nutrients and trace elements comparable to those in soil, making it a promising covering material. This study investigates the effects and mechanisms of coal gangue coverage on the physicochemical properties of soil, enzyme activity, and the growth of ryegrass. The experimental treatments comprised (1) three coal gangue particle sizes (0–0.5 cm, 0.5–1 cm, and 1–2 cm) and (2) three coverage thicknesses (4 cm, 8 cm, and 12 cm). The results show that with particle sizes of 0–1 cm and cover thicknesses of 8–12 cm, the saturated water content of the soil increased by 11.1% to 17.23%, the content of organic matter rose by 4.99 to 13.64 mg/kg, the total nitrogen increased by 0.07 to 0.12 mg/kg, and the urease activity increased by 0.56 to 0.64 μg/(d·g). Our analyses indicated that an improvement in soil porosity, a reduction in pH, and an increase in urease, organic matter, and total nitrogen collectively promoted ryegrass growth, with similar impacts. Among the treatments, coverage with 12 cm of coal gangue with a size of 0.5–1 cm produced the best results, increasing the ryegrass height by 16.24 cm, primarily due to a high level of soil porosity and elevated urease activity. In conclusion, coal gangue coverage significantly improves the properties of soil, enhances enzyme activity, and promotes ryegrass growth.

The effects of climate change and of land use/cover change (LUCC) on streamflow as demonstrated by hydrological models are pressing issues on the frontiers of global environmental change research. The Nandu River Basin (NRB) as the largest of three river basins on the tropical Hainan Island, China, is subjected to an analysis of streamflow response to climate and to land-use change. It is based on the Soil and Water Assessment Tool (SWAT) coupled with climate change signals extracted from the global climate model data in the Coupled Model Intercomparison Project Phase 6 (CMIP6) and with land-use change scenarios modeled by Cellular Automata (CA)—Markov. The results are summarized as follows: (1) Climate change contributed more to streamflow change than land-use change in the NRB, with contributions of 97.57% and 2.43%, respectively. Precipitation and temperature were the most important climate variables, contributing 92.66% and 4.91% to streamflow change. (2) In the tropical island basin from 1990 to 2015, LUCC regulated the hydrological processes in the NRB and affected hydrological processes by increasing evapotranspiration and decreasing surface runoff and subsurface flow, which resulted in decreasing streamflow. (3) Under the climate change and land-use change scenarios of the near-term period (2021–2040), the annual streamflow decreased as during the reference period (1995–2014); particularly, it decreased most (−6.16%) on the SSP126 path. These results present a case study for understanding the hydrological cycle of tropical island basins and to provide a theoretical basis for water resources management and regional sustainable development of tropical islands.

(1) Background: Crop yields in China’s arid and semi-arid regions are limited by water shortages. Exploring the interactions and resource utilization among agroforestry species is key to maintaining diversified agricultural production. (2) Objective: An apple–watermelon agroforestry system and watermelon sole-cropping system were compared to quantify how resource availability (light, water) and watermelon performance (leaf photosynthetic rate, growth, and yield) change with irrigation strategies. (3) Methods: A three-year apple and watermelon field experiment was conducted in a young apple orchard in the arid area of central Ningxia to test the effect of light competition and irrigation systems on light environment, leaf photosynthetic rate, plant growth, and yield in watermelon. The experiment encompassed two planting patterns: (i) apple–watermelon agroforestry (AF) and watermelon sole-cropping (SC) and (ii) three irrigation quotas (W1: 105 mm, W2: 210 mm, and W3: 315 mm). (4) Results: The results show that the agroforestry planting pattern extended the growth period of watermelon and increased the leaf area index. Mean daily shade intensity increased by 16.02% from 2020 to 2022. The land equivalent ratio (LER) was >1 in 2021 and 2022. The SWC, leaf photosynthetic rate, LAI, and yield of watermelon in an agroforestry planting pattern were lower than when in a sole-cropping planting pattern. However, under the W1 irrigation strategy, the total soluble solids of the agroforestry planting pattern were 2.27% higher than those of the sole-cropping pattern, and the yield of the agroforestry planting pattern was 2.59% higher than that of the sole-cropping pattern. Under the W3 irrigation strategy, the average watermelon weight in the agroforestry planting pattern was 2.85% higher than that of the sole-cropping pattern. A path analysis showed that the agroforestry planting pattern can increase the yield by increasing soil water content, which is different from the sole-cropping pattern. (5) Conclusions: The results confirm that the apple–watermelon agroforestry planting pattern reduced watermelon yields. However, the LER of the agroforestry system was greater than 1.0. It is reasonable to plant watermelons in young apple forests.