Evaporative Demand Drought Index Research Articles

Drought dynamics in California and Mississippi: A wavelet analysis of meteorological to agricultural drought transition

Understanding the transition from meteorological to agricultural drought is crucial for developing effective drought management strategies and early warning systems. This study provides a unique perspective by utilizing hybrid drought indices to explore the temporal and spatial complexities of drought propagation across two large watersheds—California and Mississippi—that feature distinct agro-climatic conditions and irrigation practices. We assess the links between meteorological drought, measured by the Standardized Precipitation Index (SPI), and agricultural drought using three indicators: Vegetation Drought Response Index (VegDRI), GRACE Root Zone Soil Moisture Percentile (SMI), and the Evaporative Demand Drought Index (EDDI). By comparing watersheds with different irrigation systems, we also consider the role of irrigation in modifying drought dynamics. Our analysis identified the 14-day SPI as particularly effective in capturing drought dynamics. Soil moisture showed the earliest response to rainfall anomalies, with a lag of 41 days in California and 59 days in Mississippi. Vegetation stress followed, with a lag of 137 days in California and 75 days in Mississippi, while atmospheric conditions lagged by 143 and 139 days, respectively. Irrigation was found to delay drought impacts by up to two months. This framework offers a finer temporal resolution and a more nuanced understanding of drought propagation, potentially informing more targeted drought mitigation strategies than traditional methods.

Spatiotemporal Variation Patterns of Drought in Liaoning Province, China, Based on Copula Theory

Liaoning Province, a crucial agricultural region in Northeast China, has endured frequent drought disasters in recent years, significantly affecting both agricultural production and the ecological environment. Conducting drought research is of paramount importance for formulating scientific drought monitoring and prevention strategies, ensuring agricultural production and ecological safety. This study developed a Comprehensive Joint Drought Index (CJDI) using the empirical Copula function to systematically analyze drought events in Liaoning Province from 1981 to 2020. Through the application of MK trend tests, Morlet wavelet analysis, and run theory, the spatiotemporal variation patterns and recurrence characteristics of drought in Liaoning Province were thoroughly investigated. The results show that, compared to the three classic drought indices, Standardized Precipitation Index (SPI), Evaporative Demand Drought Index (EDDI), and Standardized Precipitation Evapotranspiration Index (SPEI), CJDI has the highest accuracy in monitoring actual drought events. From 1981 to 2020, drought intensity in all regions of Liaoning Province (east, west, south, and north) exhibited an upward trend, with the western region experiencing the most significant increase, as evidenced by an MK test Z-value of −4.53. Drought events in Liaoning Province show clear seasonality, with the most significant periodic fluctuations in spring (main cycles of 5–20 years, longer cycles of 40–57 years), while the frequency and variability of drought events in autumn and winter are lower. Mild droughts frequently occur in Liaoning Province, with joint and co-occurrence recurrence periods ranging from 1.0 to 1.8 years. Moderate droughts have shorter joint recurrence periods in the eastern region (1.2–1.4 years) and longer in the western and southern regions (1.4–2.2 years), with the longest co-occurrence recurrence period in the southern region (3.0–4.0 years). Severe and extreme droughts are less frequent in Liaoning Province. This study provides a scientific foundation for drought monitoring and prevention in Liaoning Province and serves as a valuable reference for developing agricultural production strategies to adapt to climate change.

Is snow drought a messenger for the upcoming severe drought period? A case study in the Upper Mississippi River Basin

The exacerbation of floods and the extension of droughts, attributed to climate change and human-induced factors, are posing a substantial risk to communities by causing water scarcity. The significance of safeguarding water resources and managing them is increasingly gaining prominence. Snow is an efficient source of water for recharging groundwater compared to rainfall. This is attributed to its gradual melting process and capacity to infiltrate the soil, thereby providing sustenance to the groundwater. Thus, snow drought can be considered a major contributing factor to the issue of water scarcity. The objective of this study was to investigate the evolution of snow drought over the period since 1980, as well as its impact on agricultural drought across the Upper Mississippi River Basin (UMRB). An analysis is conducted for comparison between the spatial estimations of snow drought in the UMRB and two drought indicators, namely the evaporative demand drought index (EDDI) and water deficit amounts. The effects of the El Niño and La Niña phenomena on the UMRB as well as the results of the summer agricultural drought conditions were investigated since 2000. The results point to two important findings: 1) the snow-drought-affected zones show an increasing trend since 1980 and 2) severe snow droughts in the winter (from October to April) of a water year trigger severe agricultural droughts in the summer months of the same water year since 2000. It is seen that monitoring snow droughts is as essential as following rainfall regimes in the planning of water resources, agricultural production, and irrigation methods.

Hydrometeorological Drivers of the 2023 Louisiana Water Crisis

AbstractDuring summer and fall 2023, Louisiana experienced a historic local drought while dry conditions elsewhere in the central US withheld vital runoff from the Mississippi River, leading to below‐normal discharge into the Gulf of Mexico. Thus, by late October 2023, Louisiana was gripped by two super‐imposed water crises: a severe local drought and saltwater contamination in the Mississippi River channel. This study frames the development of the water emergency through the lens of flash drought using the Evaporative Demand Drought Index (EDDI). The EDDI shows south Louisiana experience a flash drought during June 2023, while the Mississippi River basin was subsequently characterized by large expanses of high‐percentile EDDI in August‐September 2023 shortly before the saltwater intrusion episode along the lower Mississippi River. Over the last 15 years, MRB‐wide EDDI percentile has oscillated between years‐long elevated and depressed states, accounting for 23.7% of the monthly discharge anomaly near New Orleans.

Flash drought monitoring using diurnal-provided evaporative demand drought index

Flash drought, as a relatively new concept, represents a rapidly evolving drought with sudden onset, short-term duration, and great destructiveness. With the warming of the planet in recent decades, the frequent occurrences of flash droughts have resulted in considerable losses to personnel and properties on a global scale. Nowadays, the emerging Evaporative Demand Drought Index (EDDI) has revealed its significant potential and adaptability in the early warning and quantification of flash droughts. In this study, an advanced method for improving the accuracy and temporal resolution of EDDI is proposed. The new set of EDDI estimates is calculated using diurnal-provided potential evapotranspiration values that have been calibrated with weather parameters and Global Navigation Satellite Systems (GNSS) atmospheric products. Then, the monitoring performances of flash droughts resulting from the diurnal-provided EDDIs are evaluated over the period 2010–2021 in Hong Kong. Results showed that the Probability Of Detection (POD) and False Alarm Rate (FAR) were 87.1 % and 16.7 %, respectively. By comparing with their counterparts obtained from the use of monthly EDDIs, it was found that the improvements made by the new method in the metrics of POD and FAR were 24.6 % and 11.2 %, respectively. In addition, with the use of diurnal-provided EDDI, the mean lead time for flash drought detection has been prolonged to 37.74 days, offering more time to prevent and mitigate the detrimental effects brought by flash drought events.

The effect of heterogeneous severe drought on all-cause and cardiovascular mortality in the Northern Rockies and Plains of the United States

Drought is a distinct and complicated climate hazard that regularly leads to severe economic impacts. Changes in the frequency and occurrence of drought due to anthropogenic climate change can lead to new and unanticipated outcomes. To better prepare for health outcomes, more research is needed to develop methodologies to understand potential consequences. This study suggests a new methodology for assessing the impact of monthly severe drought exposure on mortality in the Northern Rockies and Plains of the United States from 2000 to 2018. A two-stage model with the power prior approach was applied to integrate heterogeneous severe drought pattern and estimate overall risk ratios of all-cause and cardiovascular mortality related to multiple drought indices (the US Drought Monitor, 6- and 12-month Standardized Precipitation-Evapotranspiration Index, 6- and 12 month Evaporative Demand Drought Index). Under severe drought, the risk ratios of all-cause mortality are 1.050 (95 % Cr: 1.031 to 1.071, USDM), 1.041 (95 % Cr: 1.022 to 1.060, 6-SPEI), 1.009 (95 % Cr: 0.989 to 1.031, 12SPEI), 1.045 (95 % Cr: 1.022 to 1.067, 6-EDDI), and 1.035 (95 % Cr: 1.009 to 1.062, 12-EDDI); cardiovascular mortality are 1.057 (95 % Cr: 1.023 to 1.091, USDM), 1.028 (95 % Cr: 0.998 to 1.059, 6-SPEI), 1.005 (95 % Cr: 0.973 to 1.040, 12-SPEI), 1.042 (95 % Cr: 1.005 to 1.080, 6-EDDI), and 1.004 (95 % Cr: 0.959 to 1.049, 12-EDDI). Our results showed that (i) a model with properly accounted for heterogeneous exposure pattern had greater risk ratios if statistically significant; (ii) a mid-term (6-month) severe drought had higher risk ratios compared to longer-term (12-month) drought; and (iii) different severe droughts affect populations in a different way. These results expand the existing knowledge of drought relationship to increasing mortality in the United States. The findings from this study highlight the need for communities and policymakers to establish effective drought-prevention initiatives in this region.

Atmospheric Flash Drought in the Caribbean

Abstract Despite the intensifying interest in flash drought both within the United States and globally, moist tropical landscapes have largely escaped the attention of the flash drought community. Because these ecozones are acclimatized to receiving regular, near-daily precipitation, they are especially vulnerable to rapid-drying events. This is particularly true within the Caribbean Sea basin where numerous small islands lack the surface and groundwater resources to cope with swiftly developing drought conditions. This study fills the tropical flash drought gap by examining the pervasiveness of flash drought across the pan-Caribbean region using a recently proposed criterion based on the evaporative demand drought index (EDDI). The EDDI identifies 46 instances of widespread flash drought “outbreaks” in which significant fractions of the pan-Caribbean encounter rapid drying over 15 days and then maintain this condition for another 15 days. Moreover, a self-organizing maps (SOM) classification reveals a tendency for flash drought to assume recurring typologies concentrated in one of the Central American, South American, or Greater Antilles coastlines, although a simultaneous, Caribbean-wide drought is never observed within the 40-yr (1981–2020) period examined. Furthermore, three of the six flash drought typologies identified by the SOM initiate most often during Phase 2 of the Madden–Julian oscillation. Collectively, these findings motivate the need to more critically examine the transferability of flash drought definitions into the global tropics, particularly for small water-vulnerable islands where even island-wide flash droughts may only occupy a few pixels in most reanalysis datasets. Significance Statement The purpose of this study is to understand if flash drought occurs in tropical environments, specifically the Caribbean. Flash droughts represent a quickly evolving drought, which have particularly acute impacts on agriculture and often catch stakeholders by surprise as conditions evolve rapidly from wet to dry conditions. Our results indicate that flash droughts occur with regular periodicity in the Caribbean. Expansive flash droughts tend to occur in coherent subregional clusters. Future studies will further investigate the drivers of these flash droughts to create early warning systems for flash drought.

Spatiotemporal variability of vegetation response to meteorological drought on the Korean Peninsula

Abstract To assess vegetation drought, it is important to understand the relationship between climate and vegetation and to accurately measure the response of vegetation activity to meteorological drought. In this study, we used the vegetation health index (VHI) to investigate the propagation time and time-lag of vegetation response to different meteorological drought indices, including the standardized precipitation index (SPI), evaporative demand drought index (EDDI), standardized precipitation–evapotranspiration index (SPEI), and copula-based joint drought index (CJDI). Using correlation analyses of meteorological drought indices with different time-scales and time-lags and VHIs with different weights, we determined which meteorological drought indices and their corresponding time-scales and time-lags best represent the effects of meteorological drought on vegetation activity on the Korean Peninsula. We also evaluated the relative roles of normalized difference vegetation index (NDVI) and land surface temperature (LST) in quantifying vegetation response to meteorological drought. The meteorological drought index for monitoring vegetation response to meteorological drought on the Korean Peninsula was best applied using EDDI in January–May and SPEI in June–December. Vegetation health was dominated by LST in January–September, with a higher impact of NDVI in November–December. We expect these results to provide useful information for vegetation drought monitoring.

Flash drought evaluation using evaporative stress and evaporative demand drought indices: a case study from Awash River Basin (ARB), Ethiopia

Drought is one of the most devastating phenomena that affect the livelihood of most communities in Ethiopia as they have low adaptive capacity. Recent advancements in remote sensing and drought investigations have made it possible to identify a new type of flash drought that has rapid intensification with a short duration (i.e., less than 1 month unlike conventional droughts). This study intends to identify flash drought in the Awash River Basin (ARB) based on Moderate Resolution Imaging Spectroradiometer (MODIS) data of actual evapotranspiration and potential evapotranspiration using Evaporative Demand Drought Index (EDDI) and Evaporative Stress Index (ESI) indices. The flash drought result exhibited that agricultural lands, grasslands, vegetation areas, and irrigational croplands along the river were vulnerable to flash drought in the ARB. Using ESI, the area of ARB that experienced flash drought in 2002, 2008, 2009, 2012, and 2015 were 23%, 40%, 20%, 40%, and 24%, respectively. These intense flash drought areas can be used as drought monitoring sites. The flash drought extent of EDDI is more compared to ESI because of ESI’s dependency on vegetation coverages and soil moisture. The lowland downstream part of the ARB is highly prone to flash drought, particularly in the major rainy season (MRS) and the last two months of the minor rainy season (mRS). EDDI can discern the onset of flash drought better compared to ESI, but both can be used as a drought early warning mechanisms to minimize agricultural losses and drought-associated risks in the basin.

The Spread of Multiple Droughts in Different Seasons and Its Dynamic Changes

Investigating the propagation and influencing mechanism that transitions a meteorological drought to a hydrological drought in a changing environment is crucial for understanding the formation process and mechanism of hydrological drought. Furthermore, it is essential to establish an effective hydrological drought warning system based on meteorological drought. To assess the dynamic changes in the spread of meteorological drought to hydrological drought during various seasons, this study employs the Standardized Precipitation Index (SPI), Standardized Runoff Index (SRI), and Normalized Vegetation Index (NDVI) to represent meteorological, hydrological, and vegetation droughts, respectively, in the Ganjiang River Basin (GRB) from 2002 to 2020. Considering that meteorological drought can be caused not only by insufficient precipitation but also by excessive evaporation, an additional index, namely the Evaporative Demand Drought Index (EDDI), is constructed to quantify meteorological drought resulting from evaporation factors. The article analyzes the characteristics of the spatiotemporal evolution of meteorological, hydrological, and vegetation drought. The Spearman rank correlation coefficient is employed to calculate the propagation time of different seasons from meteorological drought to hydrological/vegetation drought and from hydrological drought to vegetation drought. Furthermore, we examine the propagation relationship among meteorological, hydrological, and vegetation drought in the time-frequency domain through cross-wavelet analysis and explore the key factors and physical mechanisms that influence the propagation of drought in various seasons. The result shows: The propagation time from meteorological to hydrological drought (SPI-SRI) is shortest in spring, extended during summer and autumn, and longest in winter. The meteorological drought arising from excessive evapotranspiration in autumn has the most substantial impact on hydrological drought. Vegetation drought and meteorological/hydrological drought exhibit significant intermittent resonance periods in 0~6 months and significant stable resonance periods in 7~15 months.

The Association between Drought Exposure and Respiratory-Related Mortality in the United States from 2000 to 2018.

Climate change has brought increasing attention to the assessment of health risks associated with climate and extreme events. Drought is a complex climate phenomenon that has been increasing in frequency and severity both locally and globally due to climate change. However, the health risks of drought are often overlooked, especially in places such as the United States, as the pathways to health impacts are complex and indirect. This study aims to conduct a comprehensive assessment of the effects of monthly drought exposure on respiratory mortality for NOAA climate regions in the United States from 2000 to 2018. A two-stage model was applied to estimate the location-specific and overall effects of respiratory risk associated with two different drought indices over two timescales (the US Drought Monitor and the 6-month and 12-month Evaporative Demand Drought Index). During moderate and severe drought exposure, respiratory mortality risk ratio in the general population increased up to 6.0% (95% Cr: 4.8 to 7.2) in the Northeast, 9.0% (95% Cr: 4.9 to 13.3) in the Northern Rockies and Plains, 5.2% (95% Cr: 3.9 to 6.5) in the Ohio Valley, 3.5% (95% Cr: 1.9 to 5.0) in the Southeast, and 15.9% (95% Cr: 10.8 to 20.4) in the Upper Midwest. Our results showed that age, ethnicity, sex (both male and female), and urbanicity (both metro and non-metro) resulted in more affected population subgroups in certain climate regions. The magnitude and direction of respiratory risk ratio differed across NOAA climate regions. These results demonstrate a need for policymakers and communities to develop more effective strategies to mitigate the effects of drought across regions.

Comparative Analysis of Drought Indices in Hydrological Monitoring in Ceará’s Semi-Arid Basins, Brazil

The purpose of this work is to evaluate the applicability of five drought indices (Surface Water Supply Index—SWSI, Reclamation Drought Index—RDI, Streamflow Drought Index—SDI, Standardized Precipitation Index—SPI, and Evaporative Demand Drought Index—EDDI) as tools for monitoring, in identifying the duration, intensity, and frequency of hydrological droughts in the basins of the Banabuiú, Castanhão, and Orós reservoirs, located in the state of Ceará, Brazil. The analysis focused on determining the performance of the indexes for capturing the droughts characteristics from 2002 to 2020. Thus, the comparison of the values of the indexes with the Target Levels of the reservoir’s operation were used, as well as the analysis of six decision criteria: robustness, tractability, transparency, sophistication, extensibility, and dimensionality, to compare the behavior of drought indices. The results of the evaluation criteria showed that the SPI was superior to the other indices, being able to significantly represent the drought episodes, capturing a greater number of events. Thus, SPI received the highest total weighted score (118), followed by SWSI (97), EDDI (95), SDI (95), and RDI (88). In this context, it was found that the SPI and SWSI are the most suitable indices to monitor drought in the region and that the use of longer time scales can be recommended to manage hydrological droughts, in order to improve planning and management of water resources.

Drought characterization and severity analysis using GRACE-TWS and MODIS datasets: a case study from the Awash River Basin (ARB), Ethiopia

Abstract Drought is the utmost highly devastating phenomenon in Ethiopia because of societies that are reliant on rainfall-dependent agriculture; thus, it is crucial to characterize drought at the basin scale using new developments in remote sensing products and recently proposed drought indices. This study aimed to quantify drought in the Awash River Basin (ARB) using drought indices of the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Evaporative Demand Drought Index (EDDI), Evaporative Stress Index (ESI), and Water Storage Deficit Index (WSDI). The Mann–Kendall test analysis of annual and seasonal terrestrial water storage (TWS) showed a significant increase from 2002 to 2017 that is beneficial for developmental activities in the ARB. GRACE showed a record high extreme drought that persisted for 15 months was noticed from 2005/01 to 2006/03 with a total water storage deficit of −411.8 mm with a peak shortage of −46.24 mm in 2005/03, representing severe terrestrial water shortage in the ARB. This GRACE-TWS-based quantified extreme water shortage in 2005/30 can be used as a threshold for adaptation. Overall, this study provides a reliable outcome that will be vital for the establishment of climate change adaptation pathways in the future for viable water resources management to minimize the disastrous impacts of drought in the AR.

Developing a Combined Drought Index to Monitor Agricultural Drought in Sri Lanka

Developing an agricultural drought monitoring index through integrating multiple input variables into a single index is vital to facilitate the decision-making process. This study aims to develop an agricultural drought index (agCDI) to monitor and characterize the spatial and temporal patterns of drought in Sri Lanka. Long-term (1982 to 2020) remote sensing and model-based agroclimatic input parameters—normalized difference vegetation index (NDVI), land surface temperature (LST), 3-month precipitation z-score (stdPCP), and evaporative demand drought index (EDDI)—were used to develop agCDI. The principal component analysis (PCA) approach was employed to qualitatively determine the grid-based percentage contribution of each input parameter. The agCDI was apparently evaluated using an independent dataset, including the crop yield for the major crop growing districts and observed streamflow-based surface runoff index (SRI) for the two main crop growing seasons locally, called Yala (April to September) and Maha (October to March), using 20-years of data (from 2000 to 2020). The results illustrate the good performance of agCDI, in terms of predominantly capturing and characterizing the historic drought conditions in the main agricultural producing districts both during the Yala and Maha seasons. There is a relatively higher chance of the occurrence of moderate to extreme droughts in the Yala season, compared to the Maha season. The result further depicts that relatively good correlation coefficient values (> 0.6) were obtained when agCDI was evaluated using a rice crop yield in the selected districts. Although the agCDI correlated well with SRI in some of the stations (>0.6), its performance was somehow underestimated in some of the stations, perhaps due to the time lag of the streamflow response to drought. In general, agCDI showed its good performance in capturing the spatial and temporal patterns of the historic drought and, hence, the model can be used to develop agricultural drought monitoring and an early warning system to mitigate the adverse impacts of drought in Sri Lanka.

Flash Drought Mechanism and Characteristics in South Korea

A flash drought is a drought that occurs rapidly within a short period of time, owing to changes in weather and environmental factors that occur rapidly due to extreme weather caused by climate change. Drought damage occurs within a relatively short period of time, and extreme vegetation stress can damage crops due to reduced water supply. Thus, different monitoring methods are required for different drought types. In this study, ESI (Evaporative Stress Index) and EDDI (Evaporative Demand Drought Index) were calculated to evaluate the short-term drought and determine the mechanism that causes flash droughts. The ESI and EDDI both indicates faster responses to the 2017 spring drought event than the SPI (Standardized Precipitation Index), confirming their sensitive drought assessment abilities. A flash drought detection standard was established based on the drought category used in USDM (United States Drought Monitor), and seven flash drought events were detected in South Korea over 5 years (2014-2018). A correlation analysis indicates that, among the hydrometeorological factors, the correlation coefficients between soil moisture/maximum temperature and flash drought occurrence exhibited strong positive (negative) correlations (0.9 and -0.9, respectively). The carbon change pattern obtained using GPP (Gross Primary Productivity) differed, exhibiting a -60% average GPP reduction rate compared to three other regions (JB, CN, and CB) where flash droughts occurred in 2018. We focus our discussion on opportunities to extend flash drought detection and mechanism determination using two drought indices that must be addressed to improve flash drought monitoring in South Korea.

Drought and all-cause mortality in Nebraska from 1980 to 2014: Time-series analyses by age, sex, race, urbanicity and drought severity

BackgroundClimate change will increase drought duration and severity in many regions around the world, including the Central Plains of North America. However, studies on drought-related health impacts are still sparse. This study aims to explore the potential associations between drought and all-cause mortality in Nebraska from 1980 to 2014. MethodsThe Evaporative Demand Drought Index (EDDI) were used to define short-, medium- and long-term drought exposures, respectively. We used a Bayesian zero-inflated censored negative binomial (ZICNB) regression model to estimate the overall association between drought and annual mortality first in the total population and second in stratified sub-populations based on age, race, sex, and the urbanicity class of the counties. ResultsThe main findings indicate that there is a slightly negative association between all-cause mortality and all types of droughts in the total population, though the effect is statistically null. The joint-stratified analysis renders significant results for a few sub-groups. White population aged 25–34 and 45–64 in metro counties and 45–54 in non-metro counties were the population more at risk in Nebraska. No positive associations were observed in any race besides white. Black males aged 20–24 and white females older than 85 showed protective effect against drought mainly in metro counties.We also found that more sub-populations had higher rates of mortality with longer-term droughts compared to shorter-term droughts (12-month vs 1- or 6-month timescales), in both metro and non-metro counties, collectively. ConclusionOur results suggest that mortality in middle aged white population in Nebraska shows a greater association with drought. Moreover, women aged 45–54 were more affected than men in non-metro counties. With a projected increase in the frequency and severity of drought due to climate change, understanding these relationships between drought and human health will better inform drought mitigation planning to reduce potential impacts.

Spatiotemporal assessment of potential drivers of salt marsh dieback in the North Inlet-Winyah Bay estuary, South Carolina (1990–2019)

Previous studies in the Gulf of Mexico and Atlantic states have suggested that a suite of possibly abiotic and biotic attributes is responsible for salt marsh dieback, e.g., drought, soil waterlogging, soil chemistry, top-down consumers control, etc. However, there are no conclusive answers in current literature explaining what led to marsh dieback in past decades, especially from the spatiotemporal perspective. Exploring all Landsat-retrieved marsh dieback events in 1990–2019, this research investigates the spatiotemporal relationships between the dieback series and the associated environmental variables in an intertidal marsh in South Carolina (SC). Based on our previous study, a series of marsh dieback events in the past 30 years were identified and dieback pixels in the estuary were extracted. Among these were the most severe marsh dieback events (1991, 1999, 2000, 2002, 2004, and 2013). Daily Evaporative Demand Drought Index (EDDI), daily precipitation data from Parameter Elevation Regressions on Independent Slopes Model (PRISM), and station-based water quality observations (dissolved oxygen, specific conductivity, salinity, turbidity, pH, and temperature) in the estuary were retrieved. Integrated with the proof-by-exhaustion method, statistical analysis showed marsh dieback were highly related to moisture imbalance in a period of 90 days before the dieback events. Respectively, pH for Clambank and Debidue Creek, salinity and turbidity for Thousand Acre were found to be the key water quality variables influencing marsh dieback besides drought. This study cogitates the environmental influence on coastal marsh dieback from a spatiotemporal perspective using a long-term satellite time series analysis. The findings could provide insights into marsh ecological resilience and facilitate coastal ecosystem management.

Assessing the Joint Impact of Climatic Variables on Meteorological Drought Using Machine Learning

With the intensification of climate change, the coupling effect between climate variables plays an important role in meteorological drought identification. However, little is known about the contribution of climate variables to drought development. This study constructed four scenarios using the random forest model during 1981–2016 in the Luanhe River Basin (LRB) and quantitatively revealed the contribution of climate variables (precipitation; temperature; wind speed; solar radiation; relative humidity; and evaporative demand) to drought indices and drought characteristics, that is, the Standard Precipitation Evapotranspiration Index (SPEI), Standard Precipitation Index (SPI), and Evaporative Demand Drought Index (EDDI). The result showed that the R2 of the model is above 0.88, and the performance of the model is good. The coupling between climate variables can not only amplify drought characteristics but also lead to the SPEI, SPI, and EDDI showing different drought states when identifying drought. With the decrease in timescale, the drought intensity of the three drought indices became stronger and the drought duration shortened, but the drought frequency increased. For short-term drought (1 mon), four scenarios displayed that the SPEI and SPI can identify more drought events. On the contrary, compared with the SPEI and SPI, the EDDI can identify long and serious drought events. This is mainly due to the coupling of evaporative demand, solar radiation, and wind speed. Evaporation demand also contributed to the SPEI, but the contribution (6–13%) was much less than the EDDI (45–85%). For SPEI-1, SPEI-3, and SPEI-6, the effect of temperature cannot be ignored. These results are helpful to understand and describe drought events for drought risk management under the condition of global warming.

Toward a Robust, Impact‐Based, Predictive Drought Metric

AbstractThis work presents a new approach to defining drought by establishing an empirical relationship between historical droughts (and wet spells) documented in impact reports, and a broad range of observed climate features using Random Forest (RF) models. The new drought indicator quantifies the conditional probability of drought, considering multiple drought‐related climate features and their interactive effects, and can be used for forecasting with up to 3‐month lead time. The approach was tested out‐of‐sample across several random selections of training and testing datasets, and demonstrated better predictive capabilities than commonly used drought indicators (e.g., Standardised Precipitation Index and Evaporative Demand Drought Index) in a range of performance metrics. Furthermore, it showed comparable performance to the (expert elicitation‐based) US Drought Monitor (USDM), the current state‐of‐the‐art record of historical drought in the USA. As well as providing an alternative historical drought indicator to USDM, the RF approach offers additional advantages by being automated, by providing drought information at the grid‐scale, and by having forecasting capacity. While traditional drought metrics define drought as extreme anomalies in drought‐related variables, the approach presented here reveals the full suite of circumstances that lead to impactful droughts. We highlight several combinations of climate features—such as precipitation, potential evapotranspiration, soil moisture and change in water storage—that led to drought events not detected by commonly used drought metrics. The new RF drought indicator combines meteorological, hydrological, agricultural, and socioeconomic drought, providing drought information for all impacted sectors. As a proof‐of‐concept, the RF drought indicator was trained on Texan climate data and droughts.

Evaporative demand drought index forecasting in Busan-Ulsan-Gyeongnam region using machine learning methods

Evaporative demand drought index forecasting in Busan-Ulsan-Gyeongnam region using machine learning methods