Propagation of meteorological to hydrological drought for different climate regions in China

Evaluating multifaceted effects of watershed properties and human activities on drought propagation in the Wei River Basin with an integrated framework

Understanding the factors driving propagation from meteorological to hydrological drought is crucial for drought mitigation. In this study, an integrated framework based on the Soil and Water Assessment Tool model, standardised drought indices and Geographical Detector were used to investigate how and to what extent watershed properties and human activities affect the spatial heterogeneity of drought propagation in the Wei River Basin, a typical arid and semi-arid region in China. Results indicated that (1) spatially, the propagation times increased from southwest to northeast. Seasonally, the propagation was shorter and stronger in summer and autumn. (2) The aridity index significantly affected the spatial distribution of drought propagation time for the entire basin, especially in summer, while human activities primarily drove spatial distribution in the sub-basins. The explanatory power of any two independent factors was non-linearly enhanced after the interaction. (3) Watershed properties potentially impacted the anthropogenic driving factor of drought propagation. Strong anthropogenic effects on drought propagation often occurred in watersheds with moderate drought levels, steep slopes, low elevations, and small areas, and the key factors varied seasonally. These findings help elucidate the multifaceted effects of watershed properties and human activities on drought propagation. The proposed framework and the results of this study provide valuable guidance for formulating precise drought control strategies in the Wei River Basin and worldwide.

Evaluating the impacts of climate change and land-use change on future droughts in northeast Thailand

The impacts of climate change (CC) on droughts are well documented, but the effects of land-use change (LUC) are poorly understood. This study compares the projected individual and combined impacts of these stressors on future droughts (2021-2050), with respect to baseline (1981-2010) in one of the major tributaries of the Mekong River. LUC impacts on hydrological droughts are minimal compared to CC, with the latter expected to shorten the recurrence interval of a 20-year return period event to every 14 years. Both CC and LUC have significant impacts on agricultural droughts with heightened sensitivity. 'Once in a Decade' agricultural droughts will be 40% (35%) longer and 88% (87%) more severe under the CC (LUC) scenario. Under both stressors, the events occurring every 20 years will be twice as frequent. Results highlight the intensification of future droughts and the urgency for actions to mitigate/adapt to climate change and manage land use. Future policy shall holistically address agricultural water management, sustainable land use management, and crop management to cope with future droughts. We recommend developing resilient agricultural practices, enhanced water resource management strategies, and incorporating drought risk into land-use planning to mitigate the compounded impacts of CC and LUC.

Propagation thresholds and driving mechanism detection of karst meteorological- agricultural drought: A case study in Guizhou Province

It is significant to systematically quantify the propagation thresholds of meteorological drought to different levels of agricultural drought in karst areas, and revealit's the propagation driving mechanisms. This can guide early warning and fine management of agricultural drought. In this study,we selected Guizhou Province as an example. The standardized precipitation evapotranspiration index (SPEI) and standardized soil moisture index (SSI) were used to characterize meteorological and agricultural drought. The run theory was used to identify, merge and eliminate drought events. The maximum correlation coefficient was used to capture the propagation time of meteorological-agricultural drought. The regression models were used to quantify the propagation intensity threshold from meteorological drought to different levels of agricultural drought. Finally, the propagation threshold driving mechanism was explored using geographical detectors. The results show that: (1) in terms of temporal variations during the past 21 years, regional meteorological drought had a shorter duration and a higher intensity than agricultural drought, Particularly, 2011 was a year of severe drought, and agricultural drought was significantly alleviated after 2014. (2) In terms of spatial variations, the "long duration area" of meteorological drought duration showed an "S" shaped distribution in the northeast, and the "short duration area" showed a point-like distribution. The overall duration of agricultural drought showed a spatial distribution of northeast to "medium-high in the northeast and low in the southwest. (3) The drought propagation time showed an alternating distribution of "valley-peak-valley-peak" from southeast to northwest. In terms of propagation intensity thresholds, light drought showed an overall spatial distribution of high in the east and low in the west. Moderate, severe, and extreme droughts showed a spatial distribution of low in the center north of southern Guizhou) and high in the borders. (4) There was a strong spatial coupling relationship between karst development intensity, altitude and meteorological-agricultural drought propagation thresholds. The interaction of different factors exhibited a two-factor enhancement and nonlinear enhancement on the propagation threshold. This indicates that synergistic effects of different factors on the propagation threshold were larger than single-factor effects.

Spatiotemporal heterogeneity in meteorological and hydrological drought patterns and propagations influenced by climatic variability, LULC change, and human regulations

This study aims to quantify meteorological-hydrological drought propagations and examine the potential impacts by climatic variability, LULC change (LULC), and human regulations. An integrated observation-modeling framework quantifies drought propagation intervals and assesses mechanisms influencing hydrological droughts. Meteorological droughts are characterized using the Standardized Precipitation Evapotranspiration Index (SPEI), and hydrological droughts are assessed through the Standardized Streamflow Index (SSI) across diverse climatic zones. Cross-correlation analysis between SPEI and SSI time series identifies the lag time associated with the highest correlation as the drought propagation interval. Mechanisms are investigated via a coupled empirical-process modeling framework incorporating the Soil and Water Assessment Tool (SWAT). Discrepancies between simulated and observed SSI time series help quantify the extent of human regulation impacts on hydrological drought characteristics and propagation. The Yellow River Basin (YRB), divided into six subzones based on climate characteristics, is selected as the case study. Key findings include: (1) Meteorological droughts were extremely severe across most YRB during the 1990s, while the 2000s showed some mitigation primarily due to precipitation increases. (2) Hydrological droughts and propagation times from meteorology to hydrology demonstrated substantial spatiotemporal variability. In general, summer propagation times were shorter than other seasons. (3) Propagation times were shorter in arid regions with cropland or built-up land cover versus grassland and woodland, while the reverse held for humid regions. (4) Human regulations prolonged propagation times, likely due to reservoir regulations designed to overcome water deficits. While the YRB is the focus of this paper, the methodologies and findings are applicable to other regions worldwide to enhance drought forecasting and water resource management. In various hydrological and climatic contexts worldwide.

The spatial variation of hydrological conditions and their impact on wetland vegetation in connected floodplain wetlands: Dongting Lake Basin

Wetland vegetation plays a crucial role in wetland conservation policy formulation and global climate change research. This study analyzed remotely sensed images of West Dongting Lake (DTL) Wetland from 1994 to 2020. This wetland is one of the most important wetlands in the world. At the pixel scale, we applied the histogram comparison approach, the range variability analysis (RVA) method, and the structural equation model (SEM) to quantify spatial changes in the hydrological conditions of wetland lakes and the ecological effects of environmental factors (precipitation, temperature, nutrients, water coverage) on vegetation. We propose a climate (C) - hydrological status (S) - vegetation response (R) (CSR) framework to elucidate the propagation relationships between climate, hydrology, and wetland vegetation conditions. The study found that the hydrological degradation promotes the succession of vegetation into the lake, and the distribution is concentrated in the northern Yangtze River inflow area. And the extent of hydrological changes in the West DTL region reached 34.5% during the flood period. In addition, the post-dam period showed a high degree of hydro-ecological failure, accounting for 65% of the total. Within the wetland area, there was a significant negative correlation between water coverage nutrient levels and bare vegetation within the lake area. Nutrient levels were also significantly negatively correlated with wetland vegetation conditions. Rainfall and temperature influence wetland vegetation by affecting the condition of the water body. This research provides valuable insights into managing wetland water resources and ecological restoration under the influence of climate change and human activities and provides a basis for decision-making.

The negative-positive feedback transition thresholds of meteorological drought in response to agricultural drought and their dynamics

There are complex bidirectional feedback relationships among different types of droughts (e.g., meteorological and agricultural droughts). As agricultural drought intensifies, meteorological drought response to agricultural drought may be changed from negative to positive feedback. Nevertheless, the negative-positive feedback transition thresholds of meteorological drought in response to agricultural drought and their dynamics have remained unsolved. Herein, we proposed a new quantitative method to characterize the mutual feedback between meteorological drought and agricultural drought based on the vine copula function for the first time in this study. The negative-positive feedback transition threshold and the sensitivity of the feedback were quantified under certain drought conditions. In order to investigate the feedback relationship dynamics under a changing environment, the total study period was evenly divided into two stages: stage 1 (1982-1999) and stage 2 (2000-2018). Finally, the random forest method was used to explore the dominant factors on the transition threshold. Results indicate that: (1) the negative-positive feedback transition thresholds in August is generally lower than June and July in mainland China, the basin with large threshold is the Southwest River Basin; (2) the sensitivity of meteorological drought in response to agricultural drought was higher in positive feedback than in negative feedback; (3) the transition thresholds of stage 2 was mostly reduced, while the feedback sensitivity of positive feedback was mostly increased; and (4) compared with the single factor, the land-meteorological coupling strength (the correlation between precipitation and soil moisture) dominants the negative-positive feedback transition threshold. This study sheds new insights into droughts feedback.

Insights from CMIP6 SSP scenarios for future characteristics of propagation from meteorological drought to hydrological drought in the Pearl River Basin

Drought is a common and widely distributed natural hazard. Analyzing and predicting drought characteristics and propagation are important for the early warning, prevention, and mitigation of drought disasters. This study used the precipitation and runoff outputs from General Circulation Models (GCMs) of Coupled Model Intercomparison Project Phase 6 (CMIP6) to evaluate the meteorological drought (MD) and hydrological drought (HD) characteristics in the Pearl River Basin (PRB) under two Shared Socioeconomic Pathways (SSPs) (i.e., SSP2-4.5 and SSP5-8.5). The propagation characteristics of external propagation (response between different type of drought) and internal propagation (drought development and recovery stages of a single type of drought) were also comprehensively investigated based on CMIP6. The results revealed that: 1) the percentage of grids within the dry range of MD and HD will decrease from the historical period to the future period under the two scenarios. The PRB is projected to exhibit wetter patterns; 2) Higher emission scenarios (SSP5-8.5) are more likely to weaken dryness conditions; 3) regarding the external propagation, the drought response time from MD to HD would be 2 months, and there would be no significant change under two scenarios; and 4) regarding the internal propagation, during three study periods (1971-2010, 2021-2060 and 2061-2100), the MD (HD) average recovery time changed from 3.90 (3.36) to 3.75 (3.41) and then to 3.95 (3.43) months under the SSP2-4.5 scenario, and changed from 3.93 (3.46) to 3 (3.51) and then to 3.7 (3.25) months under the SSP5-8.5 scenario. These results aid in understanding future drought characteristics and drought propagation under climate change.

Response of the runoff process to meteorological drought: Baseflow index as an important indicator

Runoff and baseflow are two hydrological elements most closely involved in water-resource management. Defining the response of runoff/baseflow to meteorological drought (MD) is helpful for designing precise drought resisting measures. Thus, Pearson correlation coefficients and mutual information scores between runoff/baseflow and MD in five sub-basins of the Weihe River Basin (WRB) were estimated on a weekly scale, and the best response times of runoff/baseflow to MD on annual and calendar months were determined according to the maximum degree of response. Furthermore, the spatial and seasonal differences in response characteristics in the WRB were discussed and the baseflow index (BFI) was introduced to further explain the propagation process of MD to runoff/baseflow. The results showed that (1) in addition to the response time, the transition sequences of MD propagating to runoff and baseflow varied across basins due to the specific basin properties; (2) Response time of runoff to MD was related to BFI value and showed significant seasonality and hydrological periodicity. In summer and autumn (wet season), the response was faster and stronger, whereas the opposite occurred in winter and spring (normal/dry season); (3) BFI values indicated the main path of drought propagation, explaining the variation in response time between basins and seasons; hence, it can be used to simply and effectively determine the propagation speed of MD to runoff. This study clarified the response characteristics of the runoff process to MD and enhanced our understanding of the drought propagation process, which is crucial for mitigating and managing drought-related hazards.

Cascading effects of drought in Xilin Gol temperate grassland, China

In the context of global climate change, the cascading risk of compound natural hazards is becoming increasingly prominent. Taking Xilin Gol grassland as study area, we used the Mann-Kendall trend method, the maximum Pearson correlation coefficient method, and Partial least squares structural equations modeling to detect the characteristics of spatiotemporal pattern changes of the three types of droughts. The propagation characteristics and the cascade effects among the three types of droughts was also identified. The standardized precipitation evapotranspiration index, standardized evapotranspiration drought index, and soil moisture index were selected as indicators of meteorological drought, ecohydrological drought, and soil drought, respectively. The results show that the warm and dry trend in Xilin Gol grassland was obvious in the past 30 years. The seasonal propagation of different drought was prominent, with stronger spread relationships in summer. Persistent meteorological drought was more likely to trigger the other two types of droughts. The intensity and range both increased during the propagation from meteorological drought to ecohydrological drought. The cascade effect was differed in different time scales. The multi-year persistent climatic drought has an overwhelming cascade effect on soil drought and ecohydrological drought. For seasonal or annual drought, vegetation cover change has an amplifying or mitigating impact on the cascade effect, where soil moisture, evapotranspiration (ET), and their relationship all play important roles. In eastern areas with better vegetation cover, the reduction of vegetation in the early stage aggravated the cascading effect of meteorological drought to ecohydrological drought through reducing ET. In the northwestern sparsely vegetated areas, ET was mainly influenced by meteorological factors, and the cascade effect of meteorological factors to ecohydrological drought was more obvious than that of soil drought.

Study on the driving mechanism of lagged effects based on different time scales in a karst drainage basin in South China

Compared to earthquakes and volcanoes, drought is one of the most damaging natural disasters and is mainly affected by rainfall losses, especially by the runoff regulation ability of the underlying watershed surface. Based on monthly rainfall runoff data recorded from 1980 to 2020, in this study, the distributed lag regression model is used to simulate the rainfall-runoff process in the karst distribution region of South China, and a time series of watershed lagged-flow volumes is calculated. The watershed lagged effect is analyzed by four distribution models, and the joint probability between the lagged intensity and frequency is simulated by the copula function family. The results show that (1) the watershed lagged effects simulated by the normal, log-normal, P-III and log-logistic distribution models in the karst drainage basin are particularly significant, with small mean square errors (MSEs) and significant time-scale characteristics. (2) Affected by spatiotemporal distribution differences in rainfall and the impacts of different basin media and structures, the lag response of runoff to rainfall differs significantly among different time scales. Especially at the 1-, 3- and 12-month scales, the coefficient of variation (C_v) of the watershed lagged intensity is greater than 1, while it is less than 1 at the 6- and 9-month scales. (3) The lagged frequencies simulated by the log-normal, P-III and log-logistic distribution models are relatively high (with medium, medium-high and high frequencies, respectively), while that simulated by the normal distribution is relatively low (medium-low and low frequencies). (4) There is a significant negative correlation (R < - 0.8, Sig. < 0.01) between the watershed lagged intensity and frequency. For the joint probability simulation, the fitting effect of the gumbel Copula is the best, followed by the Clayton and Frank-1 copulas, and while that of the Frank-2 copula is relatively weak. Consequently, the propagation mechanism from meteorological drought to agricultural or hydrological drought and the conversion mechanism between agricultural and hydrological drought are effectively revealed in this study, thereby providing a scientific basis for the rational utilization of water resources and drought resistance and disaster relief in karst areas.

Quantification of the meteorological and hydrological droughts links over various regions of Iran using gridded datasets

Drought is a gradual phenomenon that occurs slowly and directly impacts human life and agricultural products. Due to its significant damage, comprehensive studies must be conducted on drought events. This research employs precipitation and temperature from a satellite-based gridded dataset (i.e., NASA-POWER) and runoff from an observation-based gridded dataset (i.e., GRUN) to calculate hydrological and meteorological gical droughts in Iran during 1981-2014 based on the Standardised Precipitation-Evapotranspiration Index (SPEI) and Hydrological Drought Index (SSI) indices, respectively. In addition, the relationship between the meteorological and hydrological droughts is assessed over various regions of Iran. Afterward, this study employed the Long Short-Term Memory (LSTM) method to predict the hydrological drought based on the meteorological drought over the northwest region of Iran. Results show that hydrological droughts are less dependent on precipitation in the northern regions and the coastal strip of the Caspian Sea. These regions also have a poor correlation between meteorological and hydrological droughts. The correlation between hydrological and meteorological drought in this region is 0.44, the lowest value among the studied regions. Also, on the margins of the Persian Gulf and southwestern Iran, meteorological droughts affect hydrological droughts for 4 months. Besides, except the central plateau, most regions experienced meteorological and hydrological droughts in the spring. The correlation between droughts in the center of the Iranian plateau, which has a hot climate, is less than 0.2. The correlation between these two droughts in the spring is stronger than in other seasons (CC = 0.6). Also, this season is more prone to drought than other seasons. In general, hydrological droughts occurred one to two months after the meteorological drought in most regions of Iran. LSTM model for northwest Iran showed that the predicted values had a high correlation with the observed values, and their RMSE was less than 1 in this region. CC, RMSE, NSE, and R-square of the LSTM model are 0.7, 0.55, 0.44, and 0.6, respectively. Overall, these results can be used to manage water resources and allocate water downstream to deal with hydrological droughts.

Global analysis of the correlation and propagation among meteorological, agricultural, surface water, and groundwater droughts

Groundwater drought monitoring relies on ground observation data, which cannot be used to reflect large-scale droughts in groundwater resources. The Gravity Recovery and Climate Experiment Satellite (GRACE) improved the situation and provided a new solution for groundwater drought research. However, the propagation relationship among global different drought types has not been fully explored. We employed CRU precipitation data, MERR2 reanalysis soil moisture data, GLDAS and GRACE data to calculate SPI (Standardized precipitation index), SSI (Standardized soil moisture index), SRI (Standardized runoff index), and GDI (Groundwater drought index), characterizing meteorological, agricultural, surface water and groundwater droughts, respectively. The Pearson correlation coefficient was adopted to study the propagation time of these four types of droughts. The results showed that the average propagation times for the different drought types are meteorological drought to surface water drought (3.5 months), meteorological drought to agricultural drought (5.7 months), agricultural drought to groundwater drought (12.97 months), surface water drought to groundwater drought (13.78 months), and meteorological drought to groundwater drought (14.47 months) from longest to shortest. (2) Climate conditions had a significant impact on the propagation time of different drought types. Low temperatures in cold climates resulted in the longest drought propagation time, while dry summer climates in temperate climates reduced drought propagation time. There were weaker propagation relationships in arid climates. In tropical climates, precipitation may not be the main driving factor for drought propagation. (3) Different land cover types show significant differences in the propagation of groundwater droughts, with forests having a longer propagation time from meteorological drought to agricultural drought or surface water drought than grassland and cropland, and forests having the shortest propagation time when meteorological drought, agricultural drought, and surface water drought is propagated to groundwater drought. Woody plants have deeper root systems than herbaceous plants and can draw up deeper groundwater. Forests have greater water storage capacity and weaker groundwater recharge than grasslands and croplands, resulting in forests being more resistant to agricultural and surface water droughts and less resistant to groundwater droughts during meteorological droughts. This study can help to clarify the propagation laws among different drought types and understand the internal mechanisms that affect the development of drought during the water cycle.

Drought impacts on hydrology and water quality under climate change

The Intergovernmental Panel on Climate Change (IPCC) has predicted that droughts are projected to affect global hydrology and water quality in varying ways, resulting in a considerable challenge to water availability for society, environment, and ecosystems. This study employed the Soil and Water Assessment Tool to evaluate how drought affects hydrology and water quality in the Miyun Reservoir watershed, coupled with bias-corrected climate projections in the Representative Concentration Pathway 8.5 scenario, accommodating the intercoupling effects of precipitation shifts and rising temperatures. The standardized precipitation index (SPI), standardized runoff index (SRI), and standardized soil moisture index (SSWI) were used to characterize meteorological, hydrological, and agricultural droughts that occur in the different phases in the hydrological cycle. Climate change had the most significant impact on agricultural drought. SSWI were projected to considerably increase in intensity, frequency, and duration in most subbasins by up to 15 %, 55 %, and 45 %, respectively, and showed a strong correlation with meteorological and hydrological droughts (correlation coefficients r = 0.54, 0.57, and 0.60 with SPI for the baseline, near future and far future periods, and 0.91, 0.87, and 0.89 with SRI for the three periods, respectively). Hydrological components, sediment export, and nutrient loss were highly correlated with changes in drought indexes, with r ranging between -0.68 and 0.34 in the near future period and -0.62 and 0.53 in the far future period. Drought conditions of surface runoff and soil water dominated the changes in sediment export, and hydrological drought was the major cause for reduced nutrient loads. In addition to drought impacts, the synergistic effects of increasing precipitation and rising temperature led to a certain degree of increase in sediment and nutrient exports. The results of this study emphasize the need to enhance the resilience of watershed systems to the predicted increases in the intensity, frequency, and duration of droughts.

Response of vegetation dynamic change to multi-scale drought stress in the high-latitude Nenjiang River basin in China

Vegetation is an integral part of terrestrial ecosystem and plays an important role in responding to climate change, with its dynamic characteristics reflecting the ecological environmental quality. Recently, the continually increasing frequency and intensity of droughts has greatly changed how vegetation growth and development respond to drought. In this study, using normalized difference vegetation index and standardized precipitation evapotranspiration index (SPEI), we studied the response characteristics of vegetation dynamics to multi-scale drought stress (SPEI-1, SPEI-3, and SPEI-12) in the Nenjiang River basin (NRB) via Pearson correlation analysis, along with further exploration of the vegetation stability under drought. The results showed that the same period effect of drought on vegetation growth in NRB mainly occurs during the early and middle stages of vegetation growth. Furthermore, the proportion of significant positive correlation between them is 15.3%–43.3%, mainly in the central and southern parts of the basin. The lagged period effect of drought on vegetation growth mainly occurred during autumn in the southeast and middle of the basin, with a significant positive correlation of 20.8%. Under drought stress, the forest vegetation stability in NRB was the highest, with the resilience of wetland and grassland vegetation being the best and worst, respectively. Our study results will not only deepen our understanding of the dynamic vegetation changes in the high-latitude semi-arid basin under global climate change, but also provide a scientific basis for the management and water resources allocation of “agriculture-wetland-forest” complex ecosystem in the future.

Drought propagation under global warming: Characteristics, approaches, processes, and controlling factors

Drought is a costly natural hazard with far-reaching impacts on agriculture, ecosystem, water supply, and socio-economy. While propagating through the water cycle, drought evolves into different types and affects the natural system and human society. Despite much progress made in recent decades, a synthesis of the characteristics, approaches, processes, and controlling factors of drought propagation is still lacking. We bridge this gap by reviewing the recent progress of drought propagation and discussing challenges and future directions. We first introduce drought propagation characteristics (e.g., response time scale, lag time), followed by different approaches, including statistical analysis and hydrological modeling. The recent progress in the propagation from meteorological drought to different types of drought (agricultural drought, hydrological drought, and ecological drought) is then synthesized, including the basic process, commonly used indicators, data sources, and main findings of drought propagation characteristics. Different controlling factors of drought propagations, including climate (e.g., aridity, seasonality, and anomalies of meteorological variables), catchment properties (e.g., slope, elevation, land cover, aquifer, baseflow), and human activities (e.g., reservoir operation and water diversion, irrigation, and groundwater abstraction), are then summarized. Challenges in drought propagation include the discrepancy in drought indicators (and approaches) and difficulty in characterizing the full propagation process and isolating influencing factors. Future analysis of drought propagation should shift from single indicators to multiple indicators, from individual drivers to combined drivers, from uni-directional analysis to feedbacks, from hazards to impacts, and from stationary to nonstationary assumptions. This review is expected to be useful for drought prediction and management across different regions under global warming.

Understanding interactive processes: a review of CO2 flux, evapotranspiration, and energy partitioning under stressful conditions in dry forest and agricultural environments

Arid and semiarid environments are characterized by low water availability (e.g., in soil and atmosphere), high air temperature, and irregularity in the spatio-temporal distribution of rainfall. In addition to the economic and environmental consequences, drought also causes physiological damage to crops and compromises their survival in ecosystems. The removal of vegetation is responsible for altering the energy exchange of heat and water in natural ecosystems and agricultural areas. The fluxes of CO₂ are also changed, and environments with characteristics of sinks, which can be sources of CO₂ after anthropic disturbances. These changes can be measured through methods such as sap flow, eddy covariance, remote sensing, and energy balance. Despite the relevance of each method mentioned above, there are limitations in their applications that must be respected. Thus, this review aims to quantify the processes and changes of energy fluxes, CO₂, and their interactions with the surfaces of terrestrial ecosystems in dry environments. Studies report that the use of methods that integrate data from climate monitoring towers and remote sensing products helps to improve the accuracy of the determination of energy fluxes on a global scale, also helping to reduce the dissimilarity of results obtained individually. Through the collection of works in the literature, it is reported that several areas of the Brazilian Caatinga biome, which is a Seasonally Dry Tropical Forest have been suffering from changes in land use and land cover. Similar fluxes of sensible heat in areas with cacti and Caatinga can be observed in studies. On the other hand, one of the variables influenced mainly by air temperature is net radiation. In dry forest areas, woody species can store large amounts of carbon in their biomass above and belowground. The use of cacti can modify the local carbon budget when using tree crops together. Therefore, the study highlights the complexity and severity of land degradation and changes in CO₂, water, and energy fluxes in dry environments with areas of forest, grassland, and cacti. Vegetation energy balance is also a critical factor, as these simulations are helpful for use in forecasting weather or climate change. We also highlight the need for more studies that address environmental conservation techniques and cactus in the conservation of degraded areas.

Estimating the Applicability of NDVI and SIF to Gross Primary Productivity and Grain-Yield Monitoring in China

Vegetation, a key intermediary linking water, the atmosphere, and the ground, performs extremely important functions in nature and for our existence. Although satellite-based remote-sensing technologies have become important for monitoring vegetation dynamics, selecting the correct remote-sensing vegetation indicator has become paramount for such investigations. This study investigated the consistencies between a photosynthetic activity index (the solar-induced chlorophyll fluorescence (SIF) indicator) and the traditional vegetation index (the Normalized Difference Vegetation Index (NDVI)) among different land-cover types and in different seasons and explored the applicability of NDVI and SIF in different cases by comparing their performances in gross primary production (GPP) and grain-yield-monitoring applications. The vegetation cover and photosynthesis showed decreasing trends, which were mainly concentrated in northern Xinjiang and part of the Qinghai–Tibet Plateau; a decreasing trend was also identified in a small part of Northeast China. The correlations between NDVI and SIF were strong for all land-cover types except evergreen needleleaf forests and evergreen broadleaf forests. Compared with NDVI, SIF had some advantages when monitoring the GPP and grain yields among different land-cover types. For example, SIF could capture the effects of drought on GPP and grain yields better than NDVI. To summarize, as the temporal extent of the available SIF data is extended, SIF will certainly perform increasingly wide applications in agricultural-management research that is closely related to GPP and grain-yield monitoring.

A Drought Index: The Standardized Precipitation Evapotranspiration Irrigation Index

Drought has had an increasingly serious impact on humans with global climate change. The drought index is an important indicator used to understand and assess different types of droughts. At present, many drought indexes do not sufficiently consider human activity factors. This study presents a modified drought index and the standardized precipitation evapotranspiration irrigation index (SPEII), considering the human activity of irrigation that is based on the theory of the standardized precipitation evapotranspiration index (SPEI). This study aims to compare the modified drought index (SPEII) and ·SPEI and self-calibrating Palmer drought severity index (scPDSI) in the major crop-producing areas and use SPEII to evaluate the possible future drought characteristics based on CMIP5 Model. The Pearson correlation coefficient was used to assess the relevance between drought indexes (SPEII, SPEI, and scPDSI) and vegetation dynamics. The normalized difference vegetation index (NDVI) was used to represent the vegetation dynamics change. The results showed that SPEII had better performance than the SPEI and scPDSI in monitoring cropland vegetation drought, especially in cropland areas with high irrigation. The winter wheat growth period of the SPEII had better performance than that of summer maize in croplands with higher irrigation levels on the North China Plain (NCP) and Loess Plateau (LP). In general, future drought on the NCP and LP showed small changes compared with the base period (2001–2007). The drought intensity of the winter wheat growth period showed an increasing and steady trend in 2020–2080 under the representative concentration pathway (RCP) 4.5 scenario on the NCP and LP; additionally, the severe drought frequency in the central LP showed an increasing trend between 2020 and 2059. Therefore, the SPEII can be more suitable for analyzing and evaluating drought conditions in a large area of irrigated cropland and to assess the impacts of climate change on vegetation.

Response of vegetation ecosystems to flash drought with solar-induced chlorophyll fluorescence over the Hai River Basin, China during 2001-2019

With global climate change, frequent flash droughts have critically impacted vegetation productivity. Based on the new definition on flash drought onset and duration, the temporal and spatial evolution patterns of the flash drought over the Hai River Basin (HRB) was analysed. Among the events, the flash drought in 2019 lasted for 40 days, from the day of the year (DOY) 120 to DOY160, which was the strongest and mainly concentrated in the south-eastern part of the basin. Solar-induced chlorophyll fluorescence (SIF) and vegetation indices were used to explore the responses of different vegetation types to this flash drought. Compared to forest and grassland, the SIF and SIFyield (SIF normalized by the absorbed photosynthetically active radiation (APAR)) values of cropland were more sensitive to water losses and replenishment. By analysing different radiation conditions which would affect SIF and photosynthesis, low radiation was found altering the linear relationship between fluorescence and photosynthesis. The flash drought event caused gross primary productivity (GPP) losses in 40% of the basin and the maximum loss reached 0.16 kg C m^-2, indicating that the impact of this flash drought on vegetation productivity was quite serious. The results obtained in this work can be used to understand the mechanisms with which the vegetation photosynthetic capacity responds to flash droughts and to evaluate the impact of flash droughts on terrestrial ecosystems.

Integrated scheduling-assessing system for drought mitigation in the river-connected lake

Lakes are important inland surface water resources and have great influence on the ecological environment as well as the surrounding residential life. However, global lake water resources showed a depleting tendency over the past decades because of the climate change and human activities. To mitigate the drought of lakes linked to a regulated main river, this study proposes an integrated scheduling-assessing system (ISAS) based on the machine learning methodology for a large river-lake system controlled by upstream reservoirs. Closely calibrated to observational data, the ISAS was applied to the middle Yangtze River to mitigate the Poyang Lake drought. The results show that the drought situation in the downstream lake could be improved through the reservoir optimal operation. For the Poyang Lake case, the lowest lake level is not obviously improved, while the starting data of the drought could be delayed by 12, 11, and 17 days, comparing to the conventional scheme in typical dry, normal, and wet years, respectively. Moreover, the duration of the drought could be 20, 19, and 21 days less. It is illustrated that accelerating the reservoir filling speed and decelerating the emptying speed is beneficial to alleviate the drought situation of downstream river-connected lakes.

Drought Assessment on Vegetation in the Loess Plateau Using a Phenology-Based Vegetation Condition Index

Frequent droughts induced by climate warming have caused increasing impacts on the vegetation of the Loess Plateau (LP). However, the effects of drought on vegetation are highly dependent on when the drought occurs and how long it lasts during the growing season. Unfortunately, most of the existing drought indices ignore the differences in the drought effects on different vegetation growth stages. In this study, we first established a phenology-based vegetation condition index, namely weighted vegetation condition index (WVCI), which accounts for the differences in vegetation sensitivity to drought by assigning specific weights to different phenological stages of vegetation. Then, we used the WVCI to reveal the temporal and spatial variations in vegetative drought from 2001 to 2019 over the LP from the aspects of drought frequency, trend and relative deviation. The results showed that (1) the LP experienced frequent droughts during the study period, but mainly mild and moderate droughts. The drought frequencies decreased from southeast to northwest, and extreme droughts rarely occurred in mountainous areas and plains. (2) The droughts in most areas of the LP tended to ease, and only a few areas in the Hetao Plain, Ningxia Plain and Fenwei Plain showed an increasing trend of drought. (3) After 2012, the departure percentage of WVCI in most areas of the LP was positive, indicating above-average vegetation conditions. (4) Compared with the well-established vegetation condition index, the WVCI proved to have the ability to monitor and assess vegetative drought on an annual scale in the LP. As a result, our research could help develop and implement drought-resistance and disaster-prevention measures on the LP.

Extreme Hydro-Climate Events: Past, Present, and Future

In recent years, extreme hydro-climate events (such as floods and droughts) have occurred more frequently, leading to significant threats to lives and damage of property [...]

Evaluation of the impacts of human activities on propagation from meteorological drought to hydrological drought in the Weihe River Basin, China

Understanding the relationship among different types of drought is crucial for drought mitigation and early warnings. Much attention has been recently focused on the propagation from meteorological drought (MD) to hydrological drought (HD); however, the influences of human activities on drought propagation have rarely been explored. The novelty of the study was to propose an effective framework to quantify the impacts of human activities on MD-HD propagation. We adopted the framework to comprehensively evaluate the anthropic impacts on hydrological drought variations and time, thresholds, and probabilities of MD-HD propagation in the Weihe River Basin (WRB) during different periods. The results showed that human activities did significantly disturb HD variations and MD-HD propagation characteristics. Specifically, human activities increased the frequency and extremes of HD and weakened its correlation with MD. The MD-HD propagation characteristics showed spatiotemporal differences across three subbasins because of the different levels of human activities. The thresholds of MD triggering different levels of HD generally became larger with change rates from 1% to 143% and 3% to more than 189% during two periods, respectively. Meanwhile, we also found that the thresholds became distinctly smaller, which could only be observed in spring and winter. Moreover, the relationship between natural and human-induced probabilities of HD occurrence showed three patterns with the increase of MD severity. The quantitative results of this study can provide guide information on adaptation strategies to promote drought preparedness in the WRB. The proposed framework can be also applied in other regions to improve the understanding of hydrological drought mechanisms.

Assessing the responses of vegetation to meteorological drought and its influencing factors with partial wavelet coherence analysis

The increase in drought frequency in recent years is considered as an important factor affecting vegetation diversity. Understanding the responses of vegetation dynamics to drought is helpful to reveal the behavioral mechanisms of terrestrial ecosystems and propose effective drought control measures. In this study, long time series of Normalized Difference Vegetation Index (NDVI) and Solar-induced chlorophyll fluorescence (SIF) were used to analyze the vegetation dynamics in the Pearl River Basin (PRB). The relationship between vegetation and meteorological drought was evaluated, and the corresponding differences among different vegetation types were revealed. Based on an improved partial wavelet coherence (PWC) analysis, the influences of teleconnection factors (i.e., large-scale climate patterns and solar activity) on the response relationship between meteorological drought and vegetation were quantitatively analyzed to determine the roles of factors. The results indicate that (a) vegetation in the PRB showed an increasing trend from 2001 to 2019, and the SIF increased more than that of NDVI; (b) the vegetation response time (VRT) based on NDVI (VRTN) was typically 4-6 months, while the VRT based on SIF (VRTS) was typically 2-4 months. The VRT was shortest in the woody savannas and longest in the evergreen broadleaf forests. (c) The relationship between the SIF and meteorological drought was more significant than that between the NDVI and meteorological drought. (d) There was a significant positive correlation between meteorological drought and vegetation in the period of 8-20 years. The El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and sunspots were important driving factors affecting the response relationship between drought and vegetation. Specifically, the PDO had the greatest impacts among these factors.

Meteorological and Hydrological Drought Risk Assessment Using Multi-Dimensional Copulas in the Wadi Ouahrane Basin in Algeria

A persistent precipitation deficiency (meteorological drought) could spread to surface water bodies and produce a hydrological drought. Meteorological and hydrological droughts are thus closely related, even though they are separated by a time lag. For this reason, it is paramount for water resource planning and for drought risk analysis to study the connection between these two types of drought. With this aim, in this study, both meteorological and hydrological drought were analyzed in the Wadi Ouahrane Basin (Northwest Algeria). In particular, data from six rainfall stations and one hydrometric station for the period 1972–2018 were used to evaluate the Standardized Precipitation Index (SPI) and the Standardized Runoff Index (SRI) at multiple timescales (1, 2, 3, 4, …, 12 months). By means of a copula function, the conditional return period for both types of drought was evaluated. Results evidenced that runoff is characterized by high level of temporal correlation in comparison to rainfall. Moreover, the composite index JDHMI (Joint Deficit Hydro-meteorological Index) was evaluated. This index is able to reflect the simultaneous hydrological and meteorological behavior at different timescales of 1–12 months well and can present the probability of a common hydrological and meteorological deficit situation more accurately and realistically compared to precipitation or runoff-based indicators. It was found that, over the analyzed basin, the average severity of combined hydro-meteorological drought (JDHMI) was 10.19, with a duration of 9 months and a magnitude of 0.93.

Fusion-based framework for meteorological drought modeling using remotely sensed datasets under climate change scenarios: Resilience, vulnerability, and frequency analysis

Severe drought events in recent decades and their catastrophic effects have called for drought prediction and monitoring needed for developing drought readiness plans and mitigation measures. This study used a fusion-based framework for meteorological drought modeling for the historical (1983-2016) and future (2020-2050) periods using remotely sensed datasets versus ground-based observations and climate change scenarios. To this aim, high-resolution remotely sensed precipitation datasets, including PERSIANN-CDR and CHIRPS (multi-source products), ERA5 (reanalysis datasets), and GPCC (gauge-interpolated datasets), were employed to estimate non-parametric SPI (nSPI) as a meteorological drought index against local observations. For more accurate drought evaluation, all stations were classified into different clusters using the K-means clustering algorithm based on ground-based nSPI. Then, four Individual Artificial Intelligence (IAI) models, including Adaptive Neuro-Fuzzy Inference System (ANFIS), Group Method of Data Handling (GMDH), Multi-Layer Perceptron (MLP), and General Regression Neural Network (GRNN), were developed for drought modeling within each cluster. Finally, two advanced fusion-based methods, including Multi-Model Super Ensemble (MMSE) as a linear weighted model and a nonlinear model called machine learning Random Forest (RF), combined results by IAI models using different remotely sensed datasets. The proposed framework was implemented to simulate each remotely sensed precipitation data for the future based on CORDEX regional climate models (RCMs) under RCP4.5 and RCP8.5 scenarios for drought projection. The efficiency of IAI and fusion models was evaluated using statistical error metrics, including the coefficient of determination (R²), Mean Absolute Error (MAE), Mean Square Error (MSE), and Root Mean Square Error (RMSE). The proposed methodology was employed in the Gavkhooni basin of Iran, and results showed that the RF model with the lowest estimation error (RMSE of 0.391 and R² of 0.810) had performed well compared to all other models. Finally, the resilience, vulnerability, and frequency of probability metrics indicated that the 12-month time scale of drought affected the basin more severely than other time scales.

Study on the Spatial and Temporal Characteristics of Mesoscale Drought in China under Future Climate Change Scenarios

In this study, precipitation, and temperature data from HadGEM2-ES under Representative Concentration Pathways (RCPs) 4.5 and 8.5 were used to evaluate drought in China in the 21st century. The K-means clustering algorithm was used to analyze the regional characteristics of the dry hazard index (DHI) in China, and the impact of climate change on the variation trend and periodicity of regional drought in China was explored. The results show that the temperature and potential evapotranspiration (PET) of all clusters have an increasing trend under the two RCPs, and the precipitation of most clusters shows a significantly increasing trend. The drought index calculated by the standardized precipitation-evapotranspiration index (SPEI) is higher than those calculated by the standardized precipitation index (SPI) and standardized effective precipitation evapotranspiration index (SP*ETI). The variation trends of drought intensity and frequency in China are not significant in the 21st century; however, the local variation trends are significant. The droughts in most parts of the Xinjiang Province, northern Tibet and western Qinghai Province show significantly increasing trends. According to the DHI analyses and the variations in the drought area ratio, with increases in greenhouse gas concentrations, the droughts in central and western China will become more severe, and drought will spread to the eastern areas of China. In the case that both precipitation and temperature may increase in the future, the increase in evapotranspiration caused by temperature rise will greatly affect drought dynamics. The main drought periodicity in China in the 21st century is 1~3.6 years. Drought is affected by climate change but not significantly.

Long-Term Projection of Water Cycle Changes over China Using RegCM

The global water cycle is becoming more intense in a warming climate, leading to extreme rainstorms and floods. In addition, the delicate balance of precipitation, evapotranspiration, and runoff affects the variations in soil moisture, which is of vital importance to agriculture. A systematic examination of climate change impacts on these variables may help provide scientific foundations for the design of relevant adaptation and mitigation measures. In this study, long-term variations in the water cycle over China are explored using the Regional Climate Model system (RegCM) developed by the International Centre for Theoretical Physics. Model performance is validated through comparing the simulation results with remote sensing data and gridded observations. The results show that RegCM can reasonably capture the spatial and seasonal variations in three dominant variables for the water cycle (i.e., precipitation, evapotranspiration, and runoff). Long-term projections of these three variables are developed by driving RegCM with boundary conditions of the Geophysical Fluid Dynamics Laboratory Earth System Model under the Representative Concentration Pathways (RCPs). The results show that increased annual average precipitation and evapotranspiration can be found in most parts of the domain, while a smaller part of the domain is projected with increased runoff. Statistically significant increasing trends (at a significant level of 0.05) can be detected for annual precipitation and evapotranspiration, which are 0.02 and 0.01 mm/day per decade, respectively, under RCP4.5 and are both 0.03 mm/day per decade under RCP8.5. There is no significant trend in future annual runoff anomalies. The variations in the three variables mainly occur in the wet season, in which precipitation and evapotranspiration increase and runoff decreases. The projected changes in precipitation minus evapotranspiration are larger than those in runoff, implying a possible decrease in soil moisture.

Propagation from Meteorological to Hydrological Drought and Its Influencing Factors in the Huaihe River Basin

Understanding the propagation from meteorological to hydrological drought is crucial for hydrological drought monitoring and forecasting. In this study, daily precipitation and streamflow data of 16 sub-catchments in the Huaihe River Basin from 1980 to 2014 are used to establish a framework to quantitatively reveal the propagation relationship between meteorological and hydrological drought and explore the impact of climate, catchment properties, and human activities on drought propagation. The propagation from meteorological to hydrological drought is divided into three types. Type-1 propagation indicates that one or several meteorological droughts trigger a hydrological drought. The occurrence probability of Type-1 calculated by the conditional probability on SPI and SRI series varies from 0.25 to 0.48 among all catchments. Features of Type-1 propagation can be concluded as lengthening of duration, amplification of severity, lag of onset time, and reduction of speed. Type-2 propagation indicates that a meteorological drought occurs but no hydrological drought occurs, which accounts for 63–77% of the total meteorological drought events in all catchments. Type-3 indicates that a hydrological drought occurs without a proceeding meteorological drought, which is caused mostly by human activities. The occurrence probability of Type-3 ranges from 0.31 to 0.58. Climate factors have significant effects on hydrological drought duration, while catchment properties represented by topographic index and base flow index significantly relate to hydrological drought severity, propagation time, and occurrence probability of Type-1 propagation. The ratio of crop land reflecting irrigation on hydrological drought is far less than that of topographic index, denoting that the impact of irrigation on hydrological drought is less than that of catchment properties. Reservoirs have significant effects on alleviating the duration and severity of extreme hydrological droughts, but little effects on the average duration and severity of hydrological droughts.