Soil water has become a major limiting factor in agriculture and forestry development on the Loess Plateau of China. In the past 20–30 years, large areas of apple orchards have been built in this region, which have resulted in excessive consumption of deep soil water and soil desiccation. To evaluate the effects of orchard development on deep soil water content (SWC), a meta-analysis of 162 sampling sites on the loess tableland from 44 peer-reviewed publications was conducted in this study. The results showed that the deep SWC in orchards depended on stand age, planting density and annual precipitation. In regions with 550–600 mm precipitation, the orchard with lower planting density showed no soil desiccation in young and early fruiting stages, while deep soil (>2 m) desiccation occurred in full fruiting and old orchards. The effect of planting density on deep SWC varied with stand age. There were significant differences in SWC among different planting densities in early fruiting orchards (p < 0.05), in which soil desiccation occurred in orchards with higher planting density. However, with the continuous consumption of soil water by apple trees, deep soil desiccation occurred in old orchards regardless of planting density. Further, affected by the spatial variation of annual precipitation, deep SWC in orchards significantly decreased with annual precipitation from 650 to 500 mm among the 44 study sites (p < 0.05). Our results suggest that the planting density should be reasonably regulated on the level of annual precipitation, and apple trees need to be pruned appropriately with a goal of moderate productivity, so as to achieve the sustainable use of regional water resources, food security and economic development.

Studies on the spatiotemporal dynamics in ecosystem carbon and water exchanges are essential in predicting the effects of climate change on regional carbon and energy budgets. Using the eddy covariance technique, carbon and water fluxes were observed in a typical winter wheat ecosystem (WWE) and an agroforest ecosystem (AFE) in the southern Loess Plateau from 2004 to 2010. The seasonal and inter-annual variability in gross primary productivity (GPP), net ecosystem exchange (NEE), evapotranspiration (ET), and water use efficiency (WUE) were examined and the main influencing factors were identified using the Pearson correlation. The results indicate that the seasonal GPP and NEE showed a bimodal distribution in WWE, while this was unimodal in AFE. The sinusoidal function did well in the characterization of seasonal ET dynamics for both ecosystems, with the determination coefficients being 0.85 and 0.94, respectively. In WWE and AFE, the annual mean GPP were 724.33 and 723.08 g C m⁻² a⁻¹, respectively, and the corresponding ET were 392.22 and 410.02 mm a⁻¹. However, the difference in NEE between the two ecosystems was obvious, NEE were −446.28 and −549.08 g C m⁻² a⁻¹, respectively, showing a stronger carbon sink in AFE. There were strong coupling relationships between the GPP and ET of both ecosystems; the overall slopes were 1.71 and 1.69, respectively. The seasonal trend of WUE was bimodal in WWE, with peak values of 3.94 and 3.65 g C kg⁻¹ H₂O, occurring in November and April, respectively. However, the monthly WUE in AFE had one single peak of 4.07 g C kg⁻¹ H₂O in January. Photosynthetically active radiation (PAR) and soil temperature (T_s) were most positively correlated with GPP, net radiation (R_n) and T_s were the major factors influencing ET, while vapor pressure deficit (VPD) and soil water content (SWC) were the major influencing factors for WUE. These results provide observational support for regional carbon neutrality simulations.

The generalized proportionality hypothesis (GPH) highlights the competitive relationships among hydrological components as precipitation (P) transforms into runoff (Q) and evapotranspiration (E), providing a novel perspective on E partitioning that differs from the traditional physical source-based approach. To achieve sequential partitioning of E into initial (E_i) and continuing (E_c) evapotranspiration under the GPH, a P-Q relationship-based E_i estimation method was proposed for the Model Parameter Estimation Experiment (MOPEX) catchments. On this basis, we analyzed the relationship between the GPH-based E components and the physical source-based ones separated by the Penman-Monteith-Mu algorithm. Additionally, we explored the differences between the calculated and inverse Budyko-WT model parameter (E_i/E) and discussed the implications for the Budyko framework. The results showed the following: (1) A significant linear P-Q relationship (p < 0.05) prevailed in the MOPEX catchments, providing a robust data foundation for E_i estimation. Across the MOPEX catchments, E_i and E_c contributed 73% and 27% of total E, respectively. (2) The combined proportion of evaporation from canopy interception and wet soil averaged about 25%, and it was much lower than that of E_i, indicating that it was difficult to establish a connection between E_i and the physical source-based E components. (3) The potential evapotranspiration (E_P) satisfying the Budyko-WT model was strictly constrained by the GPH, while the inappropriate E_P estimation method largely explained the discrepancy between the calculated and inverse E_i/E. This study deepens the knowledge of the sequential partitioning of E components, uncovers the discrepancies between different E partitioning frameworks, and provides new insights into the characterization of key variables in Budyko models.