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The increasing frequency of drought events has intensified the risk of water scarcity, posing significant challenges for urban domestic water supply. Reducing urban household water consumption is an important way to alleviate water stress during drought periods. However, due to various factors, it is difficult to determine a water-saving target that is within the residents' capacity. Here, taking Beijing, China as an example, we explored the socio-psychological factors behind urban household water use behaviors under drought conditions, and further quantified the compressible ratio of water quotas for flexible water use behaviors. Therefore, the present study was based on the theory of planned behavior (TPB) and extended TPB (ETPB) by adding drought risk perception as a variable to the theoretical framework. With the help of questionnaire method and structural equation modeling (SEM), the explanatory power of TPB and ETPB in predicting people's water saving intention and behavior was compared. Meanwhile, mathematical statistical analysis methods were employed to calculate the water quota for elastic water consumption behavior and the compressible proportion of urban residents' elastic water consumption under drought conditions. The results showed that drought risk perception has a significant positive correlation with subject norms and water reduction behavior under drought conditions. Furthermore, ETPB was more effective in analyzing water use intentions and behaviors. The predictive explanatory power of SEM for reducing water use increased from 44% to 50% after adding drought risk perception variable. In terms of quantification of elastic water use behavior, the average total water consumption in summer and winter were 71.3L/(p.d) and 52.9L/(p.d) under drought conditions, while it were 124.3 L/(p.d) and 108.9 L/(p.d) under normal conditions. And the compressible proportions of the total water quota for summer and winter elastic water use were 46.7% and 56.8%, respectively. The calculation results can provide a reference for the government to make emergency water supply decisions against drought., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to inflpuence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Terrestrial ecosystems, occupying 28.26% of Earth's surface, are extensively at risk from droughts, which is likely to propagate into human communities owing to loss of vital services. Ecosystem risk also tends to fluctuate within anthropogenically-forced nonstationary environments, raising considerable concerns about effectiveness of mitigation strategies. This study aims to assess dynamic ecosystem risk induced by droughts and identify risk hotspots. Bivariate nonstationary drought frequency was initially derived as a hazard component of risk. By coupling vegetation coverage and biomass quantity, a two-dimensional exposure indicator was developed. Trivariate likelihood of vegetation decline was calculated under arbitrary droughts to intuitively determine ecosystem vulnerability. Ultimately, time-variant drought frequency, exposure and vulnerability were multiplied to derive dynamic ecosystem risk, followed by hotspot and attribution analyses. Risk assessment implemented in the drought-prevalent Pearl River basin (PRB) of China during 1982-2017 showed that meteorological droughts in eastern and western margins, although less frequent, were prolonged and aggravated in contrast to prevalence of less persistent and severe droughts in the middle. In 86.12% of the PRB, ecosystem exposure maintains high levels (0.62). Relatively high vulnerability (>0.5) occurs in water-demanding agroecosystems, exhibiting a northwest-southeast-directed extension. A 0.1-degree risk atlas unveils that high and medium risks occupy 18.96% and 37.99% of the PRB, while risks are magnified in the north. The most pressing hotspots with high risk continuing to escalate reside in the East River and Hongliu River basins. Our results provide knowledge of composition, spatio-temporal variability and driving mechanism of drought-induced ecosystem risk, which will assist in risk-based mitigation prioritization., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Ecological security and ecosystem stability in Central Asia depend heavily on the local vegetation. Vegetation dynamics and the response and hysteresis relationships to climate factors and drought on multiple scales over long time series in the region still need to be further explored. Using the net primary productivity (NPP) values as the vegetation change index of interest, in this study, we analyzed vegetation dynamics in Central Asia from 1982 to 2020 and assessed the responses and time lags of vegetation to climate factors and drought. The results showed that NPP gradually decreased from north to south and from east to west. Vegetation was distributed along both sides of the mountains. The temperatures rose from northeast to southwest, while precipitation gradually increased from southwest to northeast. The proportion of dry and wet years was as follows: normal (56.41%) > slightly dry (28.2%) > slightly humid (15.39%). Precipitation and drought conditions were positively correlated with NPP during the growing season, while temperature was negatively correlated with NPP. Increased spring temperature, precipitation, and drought conditions positively affected vegetation, while sustained summer temperature resulted in suppressed vegetation growth. Autumn vegetation was positively affected by temperature and drought, and precipitation was negatively correlated with autumn vegetation. Increasing winter temperatures promoted vegetation growth. The time lag between NPP and temperature gradually increased from northeast to southwest, and the time lag between NPP and precipitation gradually increased from south to north. Spring temperatures had the greatest beneficial impact on forestlands; summer climatic factors and drought had little effect on shrublands; the autumn climate exhibited small differences in its influence of each plant type; and winter temperatures had the greatest positive effect on grasslands. No time lag effect was found between any of the four vegetation types and precipitation. A one-month lag was found between cultivated lands and temperature; a two-month lag was found between forestlands and temperature; and a one-month lag was found between forestlands and drought and between shrublands and drought. The results can provide a scientific foundation for the sustainable development and management of ecosystems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier Ltd.)

In recent years, remote sensing drought monitoring indices have been gradually developed and have been widely used for global or regional drought monitoring due to their strong drought-monitoring capabilities and easy implementation advantages. However, some defects of remote sensing drought indices stand to be improved due to certain errors in the inversion of surface characteristics by remote sensing datasets. The temperature-vegetation-precipitation drought index (TVPDI) was taken as the research object, and the leaf area index (LAI), the difference between the land surface temperature (LST) and monthly average temperature, and Global Precipitation Measurement (GPM) precipitation data were selected instead of the normalized difference vegetation index (NDVI), LST and tropical rainfall measuring mission (TRMM) data to improve TVPDI. The improved remote sensing drought index was named the improved temperature-vegetation-precipitation drought index (iTVPDI). The drought-monitoring accuracy of iTVPDI was verified by the gross primary productivity (GPP), soil moisture, and crop yield per unit. The drought-monitoring ability of iTVPDI was verified with traditional drought indices, including the standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI), Palmer drought severity index (PDSI), temperature-vegetation drought index (TVDI), drought severity index (DSI) and crop water stress index (CWSI). The drought-monitoring accuracy of iTVPDI was verified by selecting sample areas. iTVPDI was applied to monitor drought in mainland China over the 2001-2020 period and obtained four main results. First, the correlation analyses of iTVPDI and TVPDI with GPP, crop yield per unit area, and soil moisture showed that iTVPDI had a stronger monitoring ability in Northeast, North, and Southwest China; the R 2 value obtained with soil moisture was 0.62 (p < 0.05), and this value was higher than that of TVPDI. Then, the correlation analyses of iTVPDI and TVPDI with SPI, SPEI, PDSI, CWSI, DSI and TVDI showed that the correlation coefficients of iTVPDI and TVPDI with these six indicators were basically consistent, which indicated that the drought-monitoring capability of iTVPDI was consistent with that of TVPDI. In local areas such as the Qinghai-Tibet Plateau in China, the monitoring ability of iTVPDI was stronger than that of TVPDI. Third, through the sample area analysis, iTVPDI was found to moderate the NDVI-characterized vegetation factors in TVPDI in low-vegetation-cover areas affected by soil disturbances and in high-vegetation-cover areas affected by oversaturation. Finally, the results obtained from the application of iTVPDI in mainland China showed that during the warm-dry to warm-wet climate transition between 2001 and 2021, in 2010 and 2018, and in other special drought years, iTVPDI had the best response., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The study of the impact of high temperature and drought on the yield of major staple crops can provide important scientific support for the decision-making of agricultural sustainable development. Based on the temperature and precipitation data of the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA 5 for northern China, this paper calculates three indexes, the standard precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI) and the extreme degree-day (EDD), from 1979 to 2017. Monthly SPI and monthly SPEI were calculated at 1 - to - 12 month lags, and EDD was calculated per crop growth season. The yield of winter wheat, spring wheat and summer maize in each province of the study area from 1979 to 2017 was de-trended, and the relative fluctuation of the yield of the three crops was calculated. The change trends of SPI, SPEI and EDD were analysed using the Mann-Kendall test and Sen's slope. The single and interactive effects of high temperature and drought on crop yield were studied using multidimensional Copula function. The results show that: 1) Both high temperature and drought stress in northern China show an increasing trend. The drought trend in the study area detected based on SPEI was greater than the drought trend detected by SPI. The difference between SPEI and SPI in the winter wheat growing season was smaller than that in the spring wheat and maize growing seasons. 2) With the increase in EDD and the decrease of SPI/SPEI values, the probability of negative yield fluctuation gradually increased, and the probability of positive yield fluctuation gradually decreased. Under the same drought and high temperature conditions, the probability of yield fluctuation varies among different crops and different provinces. Drought has a greater impact on crop yield than high temperature. Both the single and interactive effects of drought and high temperature on yield are nonlinear. 3) Irrigation can effectively alleviate the impact of drought and high temperature on yield. In heavily irrigated provinces, the effects of both high temperature and drought on crop yield are not obvious., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Timely and accurate monitoring of the spatiotemporal changes in drought is very important for the reduction in the social losses caused by drought. The Optimized Meteorological Drought Index (OMDI), originally established in southwestern China, showed great potential for drought monitoring over large regions on a large scale. However, the applicability of the index requires further evaluation, especially when used throughout China, which has a different agricultural divisions, variable climatic conditions, complex terrain and diverse land cover. In addition, the OMDI model relies on training data to construct local parameters for the model. On a large scale, it is of great significance to use multisource remote sensing data sets to construct OMDI model parameters. In this paper, the constrained optimization method was used to establish weights for the MODIS-derived Vegetation Conditional Index (VCI), TRMM-derived Precipitation Condition Index (PCI), and GLDAS-derived Soil Moisture Condition Index (SMCI) and calculate the OMDI based on the Standard Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI) and weather stations. The accuracy of the OMDI model was evaluated by using the correlation coefficient. Moreover, the spatiotemporal changes in drought were also analyzed through trend analysis, Mann-Kendall (MK) statistics and the Hurst index on the monthly and annual scales. The results showed that (1) the highest positive correlation between the OMDI and the SPI was SPI-1, which was higher than that for any other month interval, such as 3 months, 6 months, 9 months and 12 months of the SPI. The results indicated that the OMDI was suitable to monitor meteorological drought. (2) In the nine agricultural subareas in China, the degree of drought in the Yangtze River (DYR) area had the most severe evolution and change frequency. This region was very sensitive to drought in the past two decades. (3) The area with OMDI variation coefficient less than 0.1 accounted for 94%, indicating that the degree of drought fluctuates little; The linear tendency rate is 0.0004, and the area greater than 0 reaches 66.44%, indicating that the drought is developing in a lightning trend. (4) The Hurst index value is mostly higher than 0.5 (the area ratio is 56.31%), and the area of "Positive-Consistent" and "Negative- Opposite" accounted for 54.02%, indicating that more than half of China's area drought changes will show a trend of mitigation in the future., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

This paper explored the drought propagation phenomenon based on meteorological, hydrological, and agricultural aspects in the Yangtze River basin (YRB), China. To evaluate meteorological, hydrological, and agricultural droughts, this paper used three drought indices, standardized precipitation evapotranspiration index (SPEI), standardized runoff index (SRI), and standardized soil moisture index (SSMI), respectively. The community land model (CLM) in the YRB to generate the monthly evapotranspiration, soil moisture, runoff data, which are required for the estimation of drought index, were applied. Different mean durations (6-and 12-month) were used for drought estimation, and propagations of meteorological to hydrological and meteorological and agricultural droughts were investigated for different durations as SPEI6-SRI6, SPEI6-SSMI6, SPEI12-SRI12, SPEI12-SSMI12. The average drought propagation between 1950 and 2010 presented the highest autocorrelation and correlation with one-month lags in four combinations of drought indices in SPEI6-SRI6, SPEI6-SSMI6, SPEI12-SRI12, and SPEI12-SSMI12. Additionally, this paper estimated the optimal lags of SPEI-SRI and SPEI-SSMI drought propagations using mean 6-and 12-month lag times for six representative drought periods. Therefore, the propagation phenomenon of meteorological to hydrological and to agricultural droughts were confirmed in the YRB. • SPEI, SRI, and SSMI indices have been applied to the Yangtze River basin (YRB). • Propagation analysis of SPEI-SRI and SPEI-SSMI have extended to 1951–2010. • Mean 12-month duration shows clearer drought propagation than mean 6-month duration. • SPEI-SSMI presents 1–7 months propagation time. • SPEI-SRI presents 1–2 months propagation time. [ABSTRACT FROM AUTHOR]

Understanding the impact of climate change on terrestrial wet and dry changes and the relationship between the two is of great significance to the sustainable development of terrestrial ecosystems. The farming-pastoral ecotone of northern China (FPENC) is an area that is sensitive to climate change, suffering from perennial drought and a clear aridification trend. Unlike previous single-factor, single-timescale studies, we identified aridification in the region based on a dataset established by remote sensing and ground-based monitoring stations from a combination of two perspectives: climate and soil. The results show that, in terms of climate, the period from 2000 to 2019 was the driest in the region during the last 120 years , and the summer drought was the most severe and shifted from a summer to spring drought; in terms of soil, the soil aridification trend in the region was severe, with 16.1% of the areas becoming significantly drier (P < 0.1) among the years and 41.6% in spring, respectively. Similar to climate change, soils exhibited recessive aridification due to the counterbalancing effect of the dry and wet seasons within the year. Then the coupling relationship between climate change and soil aridification was established in time and space. Moreover, the spatiotemporal response patterns of both were obtained. The results showed that the frequency of soil drought under meteorological drought conditions showed an increasing trend and that the sensitivity of soil drought occurrence increased. Among them, the effect of precipitation on relative soil moisture (RSM) was immediate, and the effect of prolonged warming on RSM is greater. The area of soil aridification that was caused by climatic aridification in spring accounted for 13.7% of the entire area. The regional aridification research mode proposed in this paper can provide ideas for subsequent studies. [Display omitted] • A comprehensive judgment mode of the regional aridification combining climate elements, soil moisture was established. • Over the last 20 years, the central part of the FPENC showed overall warming and wetting of the climate. • Over the last 20 years, the trend of the soil aridification in the central part of the FPENC remained severe. • The counterbalancing effect of the dry and wet seasons leads to recessive aridification. • The sensitivity of the occurrences of soil drought to the climate drought anomalies continuously became stronger. [ABSTRACT FROM AUTHOR]