Separating productive green water from non-productive green water could determine the potential for improving green water use through water-to-vapor conversion and the optimization of green water resource management. This study selected three typical planted forests of Robinia pseudoacacia, Platycladus orientalis, and Pinus tabulaeformis in the Nanxiaohegou sub-basin, a typical small sub-basin located in the gully region of the Loess Plateau. A combination of field monitoring, hydrological models, and statistical tests was used to obtain the crop coefficient and to differentiate productive green water from non-productive green water, based on the hydrological, climatic, and ecological processes in the basin. The results demonstrated that the complementary relationship areal evapotranspiration (CRAE) model was the most effective complementary relationship-based model for the simulation. Based on the calibrated parameters, it could be used for the simulation of green water flux of different vegetation types in the studied region. In the Nanxiaohegou sub-basin, the amounts of productive green water, non-productive green water, and total green water flux of R. pseudoacacia were the highest among all three types of vegetation, followed by those of P. orientalis and P. tabulaeformis forests during the growing seasons between 2015 and 2017.

Due to the differences in the green water (GW) budget patterns of different vegetation, improper vegetation restoration may not only fail to improve the ecological environment but also cause irreversible damage to ecologically vulnerable areas, especially when vegetation restoration continues to be implemented in the future, and the pressure on water scarcity increases further. However, there is a lack of standardized research on the differences in the patterns of recharge, consumption, and efficient use of GW in typical vegetation. This makes the research results vary and cannot provide direct support for water management decision-making. Therefore, in this study, 30-year-old woodlands (R. pseudoacacia and P. orientalis) and two typical grasslands (I. cylindrican and M. sativa) that are similar to each other except for species were selected in a headwater catchment in the rain-fed agricultural area. A new GW concept and assessment framework was constructed to study the GW of long-term revegetation using a combination of field experiments and model simulations during the 2019–2020 growing season. The study findings comprise the following: (1) High-efficiency green water (GW_H), low-efficiency green water (GW_L), ineffective green water (GW_I), and available green water storage (GW_A) in the four sample plots during the study period were defined, separated, and compared. (2) An analysis of GW_A variations under different water scenarios. (3) The establishment of GW_H and GW_L thresholds. (4) Strategies to reduce GW_I and optimize GW potential while maintaining soil erosion prevention measures. (5) Suggestions for vegetation restoration species based on diverse factors. This research enhances comprehension of the impact of vegetation restoration on green water dynamics in ecologically vulnerable areas such as the rain-fed agricultural zone of the Loess Plateau.

Improving the Van Bavel-Hillel model for soil evaporation in grasslands by introducing vegetation coverage resistance

Water–energy–food (WEF) is fundamental for human survival, with land use profoundly impacting their supply-demand relationships. Integrating land into the WEF nexus is crucial for sustainable development. This study used a pressure–state–response model to establish its water–energy–food–land (WEFL) evaluation indicator system. The entropy method and coupling coordination degree (CCD) were applied to assess the WEFL nexus of Shanxi Province during 2000−2023. The obstacle degree model and Geodetector were utilized to identify internal constraints and external drivers, while the ARIMA model was employed to predict future CCD trends. The results show that (1) the comprehensive evaluation index and CCD increased over time, but overall coordination remained limited (average CCD = 0.575). Most regions were at bare to primary coordination levels, indicating persistent subsystem constraints. The spatial pattern evolved from “high in north and south, low in central region” to “high in north and west, low in south and east.” (2) Energy and land subsystems were the main sources of constraints, while the obstacle degrees of the water and food subsystems increased. External drivers shifted from being dominated by government scale and economic growth to being led by technological innovation and urbanization, with growing interaction between anthropogenic and natural factors. (3) The ARIMA model predicted further CCD improvement to intermediate coordination by 2030, although regional disparities persisted. These results provided a scientific basis for resource management and sustainable development in Shanxi Province.

The 24 solar terms (STs) comprise a traditional Chinese seasonal calendar that has long guided agricultural practices, but their agronomic relevance under observed historical climate change remains uncertain. We assessed 24 STs’ applicability in Shanxi Province using climate records from 23 meteorological stations during 1960–2019. Climate trends were analyzed at the ST scale, and the Decision Support System for Agrotechnology Transfer (DSSAT) CERES-Maize model, calibrated for Denghai 679, was applied to simulate maize phenology and yield for evaluating phenological shifts and sowing-date effects. Results showed that (1) warming was concentrated during Yushui–Qingming and Xiaoxue–Dahan, with sunshine declines across Mangzhong–Xiaoshu and Bailu–Hanlu. Precipitation trends were weak and spatially variable. (2) The calibrated CERES-Maize model reliably reproduced regional yields and phenology. Simulated V3 growth stage, anthesis, and maturity dates advanced by 1.53, 1.88, and 3.11 days per decade, respectively. V3 was associated with early-spring hydrothermal and radiation conditions, while anthesis and maturity were closely associated with summer heat during the STs Xiazhi, Xiaoshu, and Dashu. (3) Model-derived optimal ST/hou sowing windows were Guyu–H2–H3, Xiaoman–H1–H2, and Xiaoman–H2–H3 for Northern, Central, and Southern Shanxi, respectively. Optimized sowing shifted V3 towards Xiaoman–Mangzhong, delayed anthesis from early Xiaoshu to late Dashu–Liqiu, and postponed maturity towards Qiufen, all referring to STs. These findings provide a scientific basis for continued use of the 24 STs in guiding agricultural practices for maize.