Vegetation exerts profound influences on evapotranspiration (ET) partitioning. Many studies have demonstrated the positive impact of vegetation cover on the ratio of transpiration (T) to ET. Whether it is universally true with regard to different vegetation types and different sites is understudied. In this study, five sites in Northern China with different vegetation types were selected for comparison study.ET partitioning is conducted using an approach based on the concept of the underlying water use efficiency with eddy covariance measurements. The results show various patterns of vegetation’s effects over ET partitioning and, when compared with existing studies, also reveal a new relationship between the T/ET ratio and Normalized Difference Vegetation Index (NDVI) at some of the sites. At the alpine meadow site, the T/ET ratio gradually increase when NDVI is low and rapidly increase as NDVI go beyond a certain value, whereas at the arid shrub site, the T/ET ratio rapidly increase when NDVI is low and plateaus at a certain value when NDVI reaches a relatively high value. In deciduous forest, the T/ET ratio becomes unresponsive to NDVI beyond a threshold value. This study also reveals that irrigation schemes play a major role in determining the correlation between the T/ET ratio and NDVI because the T/ET ratio becomes well correlated with NDVI in case of flood irrigation and irrelevant to NDVI in the case of mulch drip irrigation. Furthermore, this study helps us to understand ET partitioning under different sites and different human activities such as irrigation. These findings can help policymakers to better understand the connection between vegetation and climate change or human activities and provide significant information for water management policy.

A high-resolution and near real-time drought monitoring dataset has not been made readily available in drought-prone China, except for the low-resolution global product. Here we developed a set of near real-time meteorological drought data at a 0.25° spatial resolution over China, by seamlessly merging the satellite-based near real-time (RT) precipitation (3B42RTv7) into the high-quality gauge-based retrospective product (CN05.1) using the quantile-mapping (QM) bias-adjustment method. Comparing the standard precipitation index (SPI) from the satellite-gauge merged product (SGMP) with that from the retrospective ground product CN05.1 (OBS) shows that the SGMP reproduces well the observed spatial distribution of SPI and the pattern of meteorological drought across China, at both the 6-month and 12-month time scales. In contrast, the UN-SGMP generated by merging the unadjusted raw satellite precipitation into the gauging data shows systematical overestimation of the SPI, leaving less meteorological droughts to be identified. Furthermore, the SGMP is found to be able to capture the inter-annual variation of percentage area in meteorological droughts. These validation results suggest that the newly developed drought dataset is reliable for monitoring meteorological drought dynamics in near real-time. This dataset will be routinely updated as the satellite RT precipitation is made available, thus facilitating near real-time drought diagnosis in China.

Existing gauging networks are sparse and not readily available in real-time over the transboundary Lancang–Mekong River (LMR) basin, making it difficult to accurately identify drought. In this study, we aimed to build an operational real-time Lancang–Mekong drought monitor (LMDM), through combining satellite real-time data and the Variable Infiltration Capacity (VIC) hydrological model at a 0.25° spatial resolution. Toward this, three VIC runs were conducted: (1) a 60-year (1951–2010) historical simulation driven by Princeton’s global meteorological forcing (PGF) for yielding ‘normal’ conditions (PGF-VIC), wherein the VIC was calibrated with 20-year observed streamflow at six hydrological stations; (2) a short-period (2011–2014) simulation to bridge the gap between the historical and the real-time modeling; (3) the real-time (2015–present) simulation driven by bias-corrected satellite data, wherein the real-time soil moisture (SM) estimate was expressed as percentile (relative to the ‘normal’) for drought monitoring. Results show that VIC can successfully reproduce the observed hydrographs, with the Nash–Sutcliffe efficiency exceeding 0.70 and the relative bias mostly within 15%. Assessment on the performance of LMDM shows that the real-time SM estimates bear good spatial similarity to the reference, with the correlation coefficient beyond 0.80 across >70% of the domain. In terms of drought monitoring, the LMDM can reasonably reproduce the two recorded droughts, implying extreme droughts covering the Lower LMR during 2004/05 and widespread severe 2009/10 drought across the upper domain. The percentage drought area implied by the LMDM and the reference is close, corresponding to 66% and 60%, 43% and 40%, and 44% and 36% for each typical drought month. Since January 2015, the LMDM was running in an operational mode, from which the 2016 unprecedented drought was successfully identified in Mekong Delta. This study highlights the LMDM’s capability for reliable real-time drought monitoring, which can serve as a valuable drought early warning prototype for other data-poor regions.

Drought is a complex natural hazard that affects various regions of the world, causing significant economic and environmental losses. Accurate and timely monitoring and forecasting of drought conditions are essential for mitigating their impacts and enhancing resilience. Satellite-based drought indices have the advantage of providing spatially continuous and consistent information on drought severity and extent. A new drought product was developed from the thermal infrared observations of the Fengyun (FY) series of satellites. We proposed a data fusion algorithm to combine multiple FY satellites, including FY-2F, FY-2G, and FY-4A, to create a long time series of a land surface temperature (LST) data set without systematic bias. An FY drought index (FYDI) is then derived by coupling the long-term LST data set with the surface–atmospheric energy exchange model at 4 km spatial resolution over China from 2013 to present. The performance and reliability of the new FYDI product are evaluated in this study by comparing it with the Meteorological-drought Composite Index (MCI), one of the authoritative drought monitoring indices used in the Chinese meteorological services. The main objectives of this paper are: (1) to evaluate the performance of the FYDI in capturing the spatiotemporal patterns of drought events over China; (2) to quantitively analyze the consistency between the FYDI and MCI products; and (3) to explore the advantages and limitations of the FYDI for drought monitoring and assessment. The preliminary results show that the FYDI product has good agreement with the MCI, indicating that the FYDI can effectively identify the occurrence, duration, severity, and frequency of drought events over China. These two products have a strong correlation in terms of drought detection, with a correlation coefficient of approximately 0.7. The FYDI was found to be particularly effective in the regions where ground observation is scarce, with the capability of reflecting the spatial heterogeneity and variability of drought patterns more clearly. Overall, the FYDI can be a useful measure for operational drought monitoring and early warning, complementing the existing ground-based MCI drought indices.

The Beijing-Tianjin-Hebei (Jingjinji) region is the most densely populated region in China and suffers from severe water resource shortage, with considerable water-related issues emerging under a changing context such as construction of water diversion projects (WDP), regional synergistic development, and climate change. To this end, this paper develops a framework to examine the water resource security for 200 counties in the Jingjinji region under these changes. Thus, county-level water resource security is assessed in terms of the long-term annual mean and selected typical years (i.e., dry, normal, and wet years), with and without the WDP, and under the current and projected future (i.e., regional synergistic development and climate change). The outcomes of such scenarios are assessed based on two water-crowding indicators, two use-to-availability indicators, and one composite indicator. Results indicate first that the water resources are distributed unevenly, relatively more abundant in the northeastern counties and extremely limited in the other counties. The water resources are very limited at the regional level, with the water availability per capita and per unit gross domestic product (GDP) being only 279/290 m³ and 46/18 m³ in the current and projected future scenarios, respectively, even when considering the WDP. Second, the population carrying capacity is currently the dominant influence, while economic development will be the controlling factor in the future for most middle and southern counties. This suggests that significant improvement in water-saving technologies, vigorous replacement of industries from high to low water consumption, as well as water from other supplies for large-scale applications are greatly needed. Third, the research identifies those counties most at risk to water scarcity and shows that most of them can be greatly relieved after supplementation by the planned WDP. Finally, more attention should be paid to the southern counties because their water resources are not only limited but also much more sensitive and vulnerable to climate change. This work should benefit water resource management and allocation decisions in the Jingjinji region, and the proposed assessment framework can be applied to other similar problems.

Existing studies on the vulnerability assessment of ecological drought often focus on analyzing vegetation phenotypic characteristics, overlooking the impact of drought on ecosystem services. This study proposes an ecosystem vulnerability assessment method under ecological drought stress from the perspective of ecosystem service value (ESV), considering the characteristics and interactions of hazard-causing factors and hazard-bearing bodies. The spatiotemporal evolution of ecological drought, the spatial characteristics of ecosystem vulnerability, and the vulnerability characteristics of different ecosystem types in the North China region from 1991 to 2021 were evaluated. The results showed that: (1) ecological drought exhibited a trend of intensification followed by alleviation, with the most severe droughts occurring between 2002 and 2011, affecting up to 64.3% of the region; (2) ESV was mainly influenced by vegetation cover and precipitation gradients, displaying a spatial pattern of high values in the southeast and low values in the northwest, with total ESV averaging CNY 18.23 trillion; (3) grasslands exhibited higher sensitivity to drought compared to forests, and the sensitivity was higher in summer and autumn than in winter and spring. This method assessed the vulnerability of ecological drought from the perspective of ecosystem services, providing a new approach for a more comprehensive understanding of the impact of drought on ecosystem service functions.