The Fen River Basin (FRB), an ecologically fragile region in China, exemplifies the intricate interplay between vegetation dynamics and both climatic and human-driven factors. This study leverages a 40-year (1982–2022) dataset, utilizing the kernel-based normalized difference vegetation index (kNDVI) alongside key climatic variables—rainfall (PRE), temperature (TMP), and solar radiation (SRAD)—to investigate vegetation variations and their drivers in the FRB, particularly in relation to the Grain for Green Program (GGP). Our analysis highlights significant greening across the FRB, with the kNDVI slope increasing by 0.0028 yr⁻¹ and green-covered areas expanding by 92.8% over the study period. The GGP facilitated the greening process, resulting in a notable increase in the kNDVI slope from 0.0005 yr⁻¹ to 0.0052 yr⁻¹ and a marked expansion in the area of significant greening from 24.6% to 95.8%. Regional climate shifts, characterized by increased warming, heightened humidity, and a slight rise in SRAD, have further driven vegetation growth, contributing 75%, 58.7%, and 23.6% to vegetation dynamics, respectively. Notably, the GGP has amplified vegetation’s sensitivity to climatic variables, with areas significantly impacted by multiple climate factors expanding from 4.8% to 37.5%. Specially, PRE is the primary climatic influence, impacting 71.3% of the pertinent regions, followed by TMP (60.1%) and SRAD (30%). The integrated effects of climatic and anthropogenic factors, accounting for 47.8% and 52.2% of kNDVI variations, respectively, collectively influence 96% of the region’s vegetation dynamics. These findings underscore the critical role of climate change and human interventions in shaping vegetation patterns and provide a robust foundation for refining ecological conservation strategies, particularly in the context of global warming and land-use policies.

Water resources are scarce in the Northeastern Loess Plateau, and water cellar water (WCW) is a vital water resource available in the vast rural areas of the region. The quality of WCW was assessed by principal component analysis (PCA) and Nemerow’s pollution index (NPI) for different rainfall catchment areas, depths, and storage times. Eleven indicators were measured, including pH, electrical conductivity (EC), F⁻, Cl⁻, NO₃⁻, SO₄²⁻, Na⁺, NH₄⁺, Ca²⁺, Mg²⁺, and K⁺. The results show that the tap water quality in the rural areas of the Northeastern Loess Plateau is above the second level and meets the drinking water standard (DWS), which is similar to the tap water quality in the region. The main component score of water quality from tile roof + cement ground (I) is 0.32, and the Nemero index is 0.41; the principal component score of water quality from cement ground (I) is 0.45, and the Nemero index is 0.29; the principal component score of water quality from trampled land (I) is 0.59, and the Nemero index is 0.44; the principal component score of water quality from tile roof + trampled land (II) is 1.87, and the Nemero index is 1.10. The rainwater harvesting catchment area of tile roof + cement ground (I) ensured the highest water quality, followed by cement ground (I), trampled ground (I), and tile roof + trampled ground (II). The water quality of the catchment area for artificially collected rainwater (roof tile surface, cement ground, etc.) was better than that of the original soil (trampled ground). The highest water quality was found at a storage time of 1 year (I), followed by 2.5 years (I), and 2 months (II). A depth of 4 m (I) contributed to the highest water quality, followed by 2 m (II), 3 m (II), and 1 m (II). Water quality improved with the increasing depth of WCW. The rainfall and WCW in the area were weakly alkaline, and the groundwater was contaminated with NO₃⁻. PCA’s water quality assessment results were similar to the NPI method, indicating that both methods can be used in combination for unconventional water quality assessment.

Quantifying the spatial variation in soil organic carbon (SOC) accumulation and its determining factors is vital for improving soil fertility and quality. The Fenhe River Basin is a major grain-producing area in Shanxi province in northern China, whereas the spatial heterogeneity of SOC accumulation is poorly known. Therefore, this study investigated SOC accumulation and its driving factors in arable soils across three representative counties (JL, FY, and XF) in the upper, middle, and lower reaches of the Fenhe River, respectively, which differ in climatic conditions and soil characteristics. SOC was determined using the potassium dichromate oxidation method. Results showed that both SOC content and stock were significantly lower in JL County (27–32% and 27–29% lower, respectively) compared to FY and XF. Within each county, the coefficient of variation was the highest in JL County (37.01%), indicating the highest spatial heterogeneity. Kriging interpolation indicated apparent spatial variation in SOC accumulation across the three counties. In JL, SOC was relatively higher in the northwest and southeast, while in FY, higher values occurred in the east. In XF, SOC generally decreased from north to south. The Spearman rank correlation and Random Forest analysis showed that SOC content and stock were significantly influenced by pH and cation exchange capacity (CEC), and pH had negative influences in JL County. Notably, in XF, available phosphorus and potassium, CEC, and clay proportion had positive influences on the SOC content and stock, while sand proportion had a negative relationship. These findings highlight the divergent, spatially heterogeneous nature of SOC accumulation across the Fenhe River Basin, driven by different factors. This study emphasizes the importance of specific soil management strategies in different locations to enhance carbon sequestration at the basin scale.