High-quality ecological environments are vital for sustainable agro-pastoral development. This study evaluated the spatiotemporal dynamics of ecological environment quality (EEQ) in Zalait Banner from 2000 to 2022 using the Remote Sensing Ecological Index (RSEI) and explore the correlation between various factors and EEQ via Geodetector. Results show a fluctuating upward RSEI trend over 22 years. EEQ hit a low in 2004, with “poor” areas peaking at 30.77%, followed by a significant recovery between 2009 and 2013. Spatially, the region exhibits a “high in the west/northeast, low in the central-south/southeast” pattern. Notably, the central-south region, despite early recovery, has shown continuous deterioration since 2009, requiring urgent remediation. Geodetector analysis revealed that land surface temperature (LST) is the dominant single factor (q = 0.87) influencing EEQ, followed by land use/cover (LULC) and air temperature. Interaction analysis indicates that the synergy between RSEI’s four components (NDVI, WET, NDBSI, and LST) provides the highest explanatory power, while socioeconomic factors (GDP, population) and topography show weaker effects. These findings could provide a scientific basis for local ecological management, with future research planned for the Qinghai–Tibet Plateau.

As an important grain-producing region of China, Anhui Province suffered its most severe drought in 70 years in 1978, particularly in summer. During the drought, the west–northward shifted western Pacific subtropical high (WPSH) induced local high temperatures, while a weakened monsoon suppressed south-to-north moisture transport into the region. These two factors jointly triggered the extreme drought. This study aims to quantitatively examine the respective contributions of water vapor and air temperature anomalies to the drought. Based on the tight relationship between precipitation and relative humidity as well as the definition expression of relative humidity, two measures are constructed to separate moisture and temperature effects, with three supplementary indicators for assessing their relative importance. The results show that water vapor anomalies dominate this drought, contributing approximately 73% of the total effect, while temperature anomalies account for 27%. At the condensation levels, the contribution of less-than-normal water vapor to the drought is roughly 4.6 times that of warmer-than-normal temperature. Distinguishing the dominance of moisture and air temperature in the drought and quantifying their respective contribution fractions provides physical support for drought classification and prediction.

The day-to-day monitoring of drought is required by decision-makers. Treating flood/drought as an instantaneous state, we have developed a physical model to describe the time change in the state, and proposed the derived WAP (Weighted Average of Precipitation) index, which uses precipitation only and monitors meteorological drought. Evaporation is implicitly included in the model as one of the dissipation components. In the present study, we modify the model to express evaporation explicitly, making the “flood extent” forced by both precipitation and evaporation. The derived WAPE index serves as a water-balance-based drought indicator that reflects the day-to-day variation in moisture conditions, with particular emphasis on soil drying processes. Compared with WAP, WAPE captures further changes in drought extent during dry periods, corresponding to soil moisture evolution. The WAPE reasonably describes two real physical processes: (1) during dry spells with strong evaporation, drought tends to be aggravated; and (2) when local drought is severe and evaporation weakens, drought may be locally mitigated due to the restoring force from horizontal and vertical soil moisture gradients. The daily-resolution and physically based nature of the WAPE index also suggests its potential applicability to the identification and dynamic monitoring of flash droughts under climate warming.