Precipitation Deficit Research Articles

Drought intensity–duration–frequency curves based on deficit in precipitation and streamflow for water resources management

Abstract. Drought estimates in terms of physically measurable variables such as precipitation deficit or streamflow deficit are key knowledge for an effective water management. How these deficits vary with the drought event severity indicated by commonly used standardized indices is often unclear. Drought severity calculated from the drought index does not necessarily correspond to the same amount of deficit in precipitation or streamflow at different regions, and it is different for each month in the same region. We investigate drought to remove this disadvantage of the index-based drought intensity–duration–frequency (IDF) curves and develop IDF curves in terms of the associated deficit. In order to study the variation of deficits, we use the link between precipitation and streamflow and the associated indices, the Standardized Precipitation Index (SPI) and the Standardized Streamflow Index (SSI). More specifically, the analysis relies on frequency analysis combined with the total probability theorem applied to the critical drought severity. The critical drought has varying durations, and it is extracted from dry periods. IDF curves in terms of precipitation and streamflow deficits for the most severe drought of each drought duration in each year are then subject to comparison of statistical characteristics of droughts for different return periods. Precipitation and streamflow data from two catchments, the Seyhan River (Türkiye) and the Kocher River (Germany), provide examples for two climatically and hydrologically different cases. A comparison of the two cases allows a similar method to be tested in different hydrological conditions. We found that precipitation and streamflow deficits vary systematically, reflecting seasonality and the magnitude of precipitation and streamflow characteristics of the catchments. Deficits change from one month to another at a given station. Higher precipitation deficits were observed in winter months compared to summer months. Additionally, we assessed observed past major droughts experienced in both catchments on the IDF curves, which show that the major droughts have return periods at the order of 100 years at short durations. This coincides with the observation in the catchments and shows the applicability of the IDF curves. The IDF curves can be considered a tool for using in a range of specific activities of agriculture, ecology, industry, energy and water supply, etc. This is particularly important to end users and decision-makers to act against the drought quickly and precisely in a more physically understandable manner.

Managed phreatic zone recharge for irrigation and wastewater treatment

Managed phreatic zone recharge with marginal water, using (existing) drainage systems, raises the water table and increases water availability for crops. This is a newly developed method of freshwater conservation and marginal water treatment and disposal, but risks crop and environmental contamination. The fate of contaminants of emerging concern (CECs) within the irrigated water is addressed. We introduce numerical and analytical models, inspired loosely by a field site where treated domestic wastewater is used for subsurface irrigation. The treated wastewater would otherwise have been discharged into rivers, thereby spreading downstream. Model results show that minimal amounts of CECs are transported to deeper aquifers. Crops are not contaminated, except during dry years where small amounts of mobile CECs rise to the root zone, but then only directly above each irrigation drain. Under an annual precipitation surplus, less-mobile solutes are thus unlikely to ever enter the root zone. The primary mechanism of solute transport is lateral advection within the phreatic aquifer. Despite spatio-temporal heterogeneity in water flux magnitudes and directions, contaminant retardation does not significantly alter mass balance outcomes, only how fast it gets there. Therefore, persistent CECs pose the greatest risks, though overall environmental and crop contamination risks appear low. To maximize complementarity with subsurface irrigation systems, future advances in water treatment technologies should focus on removing persistent CECs. However, the system may be unsuitable for climates with annual precipitation shortages, as CECs may accumulate in the root zone and crops.

Exploring the contribution of environmental factors to evapotranspiration dynamics in the Three-River-Source region, China

Evapotranspiration (ET) exerts substantial effects on terrestrial ecosystem carbon and water cycles. A deep understanding of the spatial and temporal variability in ET and its dominant controls has crucial implications for future ecological management, especially for the ecologically-fragile Three-River-Source region (TRSR) in China. The study examined the performance of three ET products including Global Land Evaporation Amsterdam Model (GLEAM), Famine Early Warning Systems Network Land Data Assimilation System (FLDAS) and Global Land Surface Satellite (GLASS) based on eddy covariance-based flux observations. On this basis, ET dynamics in the TRSR from 1982 to 2018 were analyzed at two time scales using the GLASS ET product. Spatially, the pattern in ET showed a gradual upward trend from northwest to southeast. Meanwhile, ET in the majority of regions significantly enhanced, with multiannual mean ET and summer ET (June to August) increasing by 0.609 mm/yr and 0.765 mm/yr, respectively. Especially, ET in summer dominated the interannual dynamics of ET in the TRSR. The individual contributions of five environmental factors including Leaf Area Index (LAI), solar radiation (Rs), air temperature (Ta), precipitation (PRE) and vapour pressure deficit (VPD), to the variability in ET were isolated using ridge regression. Significant differences appeared when explaining ET over different time scales. Rs (33.05 %) and LAI (25.29 %) were the dominant control variables in shaping the interannual ET, with VPD contributing the least by 7.19 %. However, the long-term dynamics in summer ET were mainly controlled by LAI (35.73 %) and PRE (31.19 %), and Ta exerted the least effect by 5.73 %. All analyses will strengthen our understanding of the relationships between climate, vegetation and ET in the TRSR area, China.

Water and Irrigation Requirements of Glycine max (L.) Merr. in 1981–2020 in Central Poland, Central Europe

Soya, one of the most economically important crops, is sensitive to periodic water deficits, which, because of climate change, are becoming more and more common in central Europe. The goal of this study was to estimate the water requirements of soybean from 1981 to 2020 in four provinces of central Poland and the rainfall deficits affecting soybean cultivation; the study also evaluates rainfall water use efficiency for soybean cultivated in production fields to investigate the future necessity of supplemental irrigation. Calculations were based on the values of monthly air temperature and the sum of precipitation. Soybean water requirements were calculated using the method of crop coefficients and reference evapotranspiration was estimated using the Blaney–Criddle approach. Crop water requirements were defined as potential evapotranspiration. Precipitation deficits for soybean were estimated using the Ostromęcki method. Water use efficiency was calculated based on rainfall totals and soybean yield in the rainfed fields. It was found that, on average in the central Poland provinces, from 1981 to 2020, the water requirements of soybean in the growing season amounted to 384 mm, and the highest water requirements occurred in June and July. In the studied forty-year period, a significant upward trend in soybean water requirements in central Poland was observed, both from 1 May to 31 August and from 1 June to 31 August. Rainfall deficits in soybean cultivation in central Poland were found from May to August and amounted to 123 mm in normal years (N50%). The rainfall water use efficiency from April to August for soybean cultivated in central Poland on average amounted to 6.6 kg ha−1 mm−1 and varied in individual years and regions. The results of the study indicate the need to develop supplemental irrigation systems for soybean crops cultivated in central Poland and other areas of the world with similar climate conditions to optimize yield and the sustainable use of water resources.

A watershed-scale evapotranspiration model considering forest type, stand parameters, and climate factors

We developed a model to estimate evapotranspiration (ET) for temperate coniferous and broadleaf forests that considers stand structure (density and height) and meteorological data (precipitation, air temperature, solar radiation, and vapor pressure deficit) as input. We used globally available data from 65 publications, as well as 37 datasets from sources such as FLUXNET, that were collected mainly from temperate climates. The wet canopy evaporation (Ewet) submodel consisted of a nonlinear function to determine the ratio of interception loss to precipitation from stand density for coniferous forests or stand height for broadleaf forests. The parameters of the Ewet submodel were determined separately for rainfall and snowfall. The dry canopy evaporation (Edry) submodel consisted of a simplified Penman–Monteith equation, including a nonlinear function to determine the reference surface conductance from stand height. We tested the prediction ability of the model using data from three locations covered by evergreen coniferous (ET, 13–83 mm/month) and deciduous coniferous forests (24–104 mm/month) in central Japan, and a deciduous broadleaf forest (1–59 mm/month) in northern Wisconsin, USA, for a mixture of rain and snow. Our model reproduced seasonal ET patterns, with mean absolute errors of 10 ± 5, 12 ± 7, and 6 ± 9 mm/month for the evergreen coniferous, deciduous coniferous, and deciduous broadleaf forests, respectively. The model is applicable to ET estimation over watershed-scale areas with heterogeneous biotic (forest condition) and abiotic (meteorological) factors in landscapes with complex topography.

A strong high-temperature event in late-spring 2023 in Yunnan province, Southwest China: Characteristics and possible causes

In April–May 2023, Yunnan province of Southwest China experienced a strong high-temperature event with relatively large return period and small occurrence probability, causing adverse impacts on the regional development. The possible causes for the 2023 high-temperature event are mainly involved with an upper-level high-pressure system induced by a Rossby wave train and the precipitation shortage associated with a lower-level anticyclonic circulation over the Bay of Bengal. On the one hand, the atmospheric Rossby wave train is attributed to the decreased snow depth in the North America. On the other hand, the lower-level anticyclone over the Bay of Bengal may be caused by the warming SSTs in the tropical western Indian ocean and in the tropical eastern Pacific via the excited Matsuno-Gill response and the atmospheric signals of Southern Oscillation, respectively. The mechanisms are validated by the pacemaker experiments run with CESM1 climate model. These three factors that cause the 2023 high-temperature event are highly correlated to the surface temperature anomalies in Yunnan. Hence, a physical-based multiple regression model with the leave-five-out cross validation can be constructed to perform a skilful seasonal prediction.

Increased risk of flash droughts with raised concurrent hot and dry extremes under global warming

Flash droughts pose large threats to crop yields and ecosystem services due to their sudden onset and rapid intensification, arousing wide public concern in a warming climate. Their long-term characteristics of change, underlying mechanisms, and especially potential impacts on agriculture, forests, and populations at a global scale, however, remain largely unknown. We used in situ observations, two observation-based global reanalysis data sets, and 22 Earth system models to determine that flash droughts are shifting toward more frequent, accelerated-onset, and longer duration. These changes increased the exposure of agricultural areas, forested areas, and populations to flash droughts by 20.3%, 17.1%, and 30.0%, respectively, during 2001–2020 compared to 1981–2000, with a disproportionate increase in integrated risks across the Amazon Basin and eastern and southern Asia. The increase in concurrent hot and dry climatic conditions driven by warming has been mostly responsible for enabling and intensifying flash droughts over large regions. State-of-the-art Coupled Model Intercomparison Project Phase 6 (CMIP6) models, however, failed to identify the acceleration of the onset time of flash droughts and widely underestimated the occurrence of flash droughts that are driven only by precipitation deficits or by heat waves, probably because they misrepresent the dependence between precipitation and temperature and underestimate the sensitivity of soil moisture to temperature and precipitation at short timescales (e.g., 5 days). These syntheses comprehensively advance our understanding of the characteristics and impacts of flash droughts but also highlight that the CMIP6 models need to be validated to represent the correct covariability between climatic variables at short timescales to provide more reliable projections of flash droughts.

Persistent Meteorological Drought in the Yangtze River Basin during Summer–Autumn 2022: Relay Effects of Different Atmospheric Internal Variabilities

During the summer–autumn (July–October, Jul–Oct) period of 2022, the Yangtze River Basin (YRB) of China experienced an extreme meteorological drought, with Jul–Oct containing the lowest precipitation in the YRB since 1979. The possible causes of this drought were analyzed in the present study. Surprisingly, unlike many previous drought events, we found that this event was not characterized by a consistent atmospheric circulation anomaly regime throughout the entire drought period. Instead, two distinct circulation patterns were responsible for the precipitation deficit in two different stages, i.e., July–August (Jul–Aug) and September–October (Sep–Oct). In Jul–Aug, the YRB precipitation deficit primarily resulted from an intensified and northward-shifted East Asian subtropical jet, which allowed for an extremely northwestward shift of western Pacific subtropical highs, leading to an anomalous descending motion. Such circulation patterns in Jul–Aug originated from the dispersion of Rossby waves upstream from central Asia and Europe. Meanwhile, in Sep–Oct, the YRB drought was primarily attributed to a low-level cyclonic anomaly over the western North Pacific, which was closely associated with frequent tropical cyclones traveling across this region. Observational analysis and a model ensemble hindcast suggest that atmospheric internal variabilities dominated the drought process, while the SSTA, particularly the La Niña event, played a limited role. Therefore, this long-lasting extreme YRB meteorological drought was largely driven by the relay effects of different atmospheric internal variabilities in Jul–Aug and Sep–Oct, respectively, which shows limited model predictability and poses a great challenge for operational climate predictions.

Crop response pattern to several drought timescales and its possible determinants: A global-scale analysis during the last decades

Crop response characteristics to different timescales of precipitation deficit may represent crop system resilience to drought characteristics. In this study, we assess the crop yield response of major crops to meteorological drought estimated by a standardized precipitation index with multiple timescales (1-12 months) during 1981-2016 all over the globe. We estimate that about one- to two-thirds of global harvested areas of maize, rice, soybean, and wheat, were significantly affected by various drought timescales. Soybean and wheat might respond to more prolonged droughts, while rice and maize responded to short-medium drought time scales. Using multiple machine learning models, we reveal that set of determinants could explain most variations of crop response to drought timescale with average accuracies between 45.7% - 56.0% (across models and crop types). Moreover, this study suggests that crops in warmer and higher water availability (precipitation minus potential evapotranspiration) might respond significantly to more short-term drought. The other factors (i.e., socioeconomic, fertilizer, soil, topography, production, irrigation) shows a complex and weaker effect on defining crop vulnerability to the various drought characteristics. This study attempts to fill the gaps in understanding global crop resistance to different drought characteristics. The future challenge in understanding the multifaceted effect of physical and socioeconomic factors on global crop vulnerability to drought may remain and should be addressed in further studies.

Last glacial hydroclimate variability in the Yucatán Peninsula not just driven by ITCZ shifts

We reconstructed hydroclimate variability in the Yucatán Peninsula (YP) based on stalagmite oxygen and carbon isotope records from a well-studied cave system located in the northeastern YP, a region strongly influenced by Caribbean climate dynamics. The new stalagmite isotopic records span the time interval between 43 and 26.6 ka BP, extending a previously published record from the same cave system covering the interval between 26.5 and 23.2 ka BP. Stalagmite stable isotope records show dominant decadal and multidecadal variability, and weaker variability on millennial timescales. These records suggest significant precipitation declines in the broader Caribbean region during Heinrich events 4 and 3 of ice-rafted discharge into the North Atlantic, in agreement with the antiphase pattern of precipitation variability across the equator suggested by previous studies. On millennial timescales, the stalagmite isotope records do not show the distinctive saw-tooth pattern of climate variability observed in Greenland during Dansgaard–Oeschger (DO) events, but a pattern similar to North Atlantic sea surface temperature (SST) variability. We propose that shifts in the mean position of the Intertropical Convergence Zone (ITCZ), per se, are not the dominant driver of last glacial hydroclimate variability in the YP on millennial timescales but instead that North Atlantic SSTs played a dominant role. Our results support a negative climate feedback mechanism whereby large low latitude precipitation deficits resulting from AMOC slowdown would lead to elevated salinity in the Caribbean and ultimately help reactivate AMOC and Caribbean precipitation. However, because of the unique drivers of future climate in the region, predicted twenty-first century YP precipitation reductions are unlikely to be modulated by this negative feedback mechanism.

The Meteorological Conditions of Precipitation Deficits in the Cultivation of Winter Wheat in Central and Eastern Poland

The Meteorological Conditions of Precipitation Deficits in the Cultivation of Winter Wheat in Central and Eastern Poland

Propagation in the Drought Cascade: Observational Analysis Over the Continental US

AbstractPersistent deficits in meteorological, hydrological and ecological variables define different types of drought that are often linked together in a cascade. The drought cascade is an emergent phenomenon in the climatic system. A quantitative evaluation of the drought cascade based on observations is both a rigorous test of how different components of numerical Earth System models interact with one‐another and a useful tool for practitioners concerned with drought impacts on water resource and ecosystem services. In this study the drought cascade is characterized over the continental US using remote sensing data and in situ observations. Remote sensing fields of coincident vegetation photosynthesis and above‐ground biomass anomalies are introduced into the cascade to assess the role of the terrestrial biosphere within the cascade. The propagation of the diverse drought types, in terms of amplitude‐dampening and phase‐delays, are quantified. It is shown that woody and herbaceous vegetation have contrasting responses to prolonged soil moisture deficit that is traceable to access and storage of water as well as the dual effects of water‐ and light‐limitation. The observations also show that prolonged precipitation deficit in itself is not adequate to trigger the intense soil moisture and vegetation stress responses and that excessive atmospheric evaporative demand needs to be coincident with the precipitation anomalies.

Water or mirage? Nightmare over dams and hydropower across Iran

ABSTRACT This study examines the influence of human activities and climate variability on 86 dams and hydropower across Iran. The term ‘mirage water’ is introduced to estimate the impact of these factors on inflow. Data analysis shows that out of 1729 m3s−1 of mirage water, 705 m3s−1 are contributed by anthropogenic activities and 1024 m3s−1 by precipitation deficits. This indicates that some parts of Iran’s strategic investments in water resources management over the past 60 years have failed. The study underscores the necessity for enhanced management practices and infrastructure investments to ensure sustainable water resources in arid and semi-arid regions.

Increasing vapor pressure deficit accelerates land drying

Increase Vapor Pressure Deficit (VPD) imposes higher atmospheric demand on land evaporation in the warming climate. However, it remains uncertain that how the increasing evaporative stress may enhance the global pattern of land drying. Here, we have used self-calibrating Palmer Drought Severity Index (scPDSI) based on outputs from 20 CMIP6 models to study the contribution of VPD, precipitation and other climatic factors to scPDSI changes globally. Global land drying and wetting are found to be regionally dependent, with statistically significant enhancement of drying and wetting under SSP2-4.5, SSP3-7.0 and SSP5-8.5 pathways (2015–2100) compared to the historical period (1961–2014). Increasing precipitation is the main reason of land wetting, while the land drying is initially associated with precipitation deficit, it is partly dominated by the increasing VPD over 20 ∼ 27% of the global land, where the estimated VPD contribution is nearly 6 times of that of precipitation under high forcing pathways. Elevated CO2 concentration is suggested to partly mitigate land drying by altering vegetation physiology; however, this mitigation is quantified to be limited. Our findings highlight the key role of VPD in accelerating global pattern of land drying and its increasing dominance in the warming climate.

Current and future risk of unprecedented hydrological droughts in Great Britain

The UK has experienced recurring hydrological droughts in the past and their frequency and severity are predicted to increase with climate change. However, quantifying the risks of extreme droughts is challenging given the short observational record, the multivariate nature of droughts and large internal variability of the climate system. We use EC-Earth time-slice large ensembles, which consist of 2000 years of data each for present-day, 2°C and 3°C conditions relative to pre-industrial, to drive hydrological models of river catchments in Great Britain (GB) to obtain a large set of plausible droughts. Since future warming is certain, the uncertainty in drought is mainly associated with uncertainty in precipitation. Estimates of unprecedented extremes show that the chance of a summer month in a given year drier than the observed driest summer (1995) is projected to increase with future warming (from 9% in the present-day (PD) to 18% in a 3°C warmer world (3C) for southeast England). For winter, the chance of a dry winter month drier than the observed driest winter (1991–92) slightly decreases (from 10% - PD to 8% − 3C for southeast England) but the chance of the driest winter does not change significantly with future warming. We add value to these probabilistic estimates by sampling for physical climate storylines of drought sequences characterised by dry spring-summers, autumn-winters and consecutive dry winters. Dry spring-summers are estimated to become drier with future warming primarily driven by reduced precipitation in summer. Dry autumn-winters may become wetter mainly driven by the general trend of more precipitation in winter although drought conditions triggered by moderate autumn–winter precipitation deficits may worsen given the higher likelihood of being followed by a dry summer. Similarly, drought impacts of consecutive dry winters, a particular risk for slow-responding catchments in the English Lowlands, may worsen with future warming as the intervening summer is projected to become hotter and drier. These storylines can be used to stress-test hydrological systems and inform decision-making.

How Unusual Is the 2022 European Compound Drought and Heatwave Event?

AbstractThe 2022 Compound Drought and Heatwave (CDHW) caused widespread crop damage, water shortages, and wildfires across Europe. Our study analyzed this event’s severity and return period (RP) and compared it with past mega CDHWs in Europe. The hardest‐hit areas were Iberian Peninsula, France, and Italy, where temperatures exceeded 2.5°C above normal, and severe droughts persisted from May to August. Using a Bayesian approach, we estimated the RP for the 2022 CDHW event, which was unprecedented in Northern Italy, Iberian Peninsula, and western parts of France, with RPs of 354, 420, and 280 years, respectively. The reduced soil moisture due to precipitation deficits and high temperatures contributed to the persistence and severity of drought, creating a positive feedback loop where dry soils led to even drier conditions. In light of our findings, it is evident that global warming poses increased risks of severe CDHW events, which are likely to increase.

Yield shortfall of cereals in Ukraine caused by the change in air temperature and precipitation amount

Yield shortfall of cereals in Ukraine caused by the change in air temperature and precipitation amount

Drought Prediction: A Comprehensive Review of Different Drought Prediction Models and Adopted Technologies

Precipitation deficit conditions and temperature anomalies are responsible for the occurrence of various types of natural disasters that cause tremendous loss of human life and economy of the country. Out of all natural disasters, drought is one of the most recurring and complex phenomenons. Prediction of the onset of drought poses significant challenges to societies worldwide. Drought occurrences occur across the world due to a variety of hydro-meteorological causes and anomalies in sea surface temperature. This article aims to provide a comprehensive overview of the fundamental concepts and characteristics of drought, its complex nature, and the various factors that influence drought, drought indicators, and advanced drought prediction models. An extensive survey is presented in the different drought prediction models employed in the literature, ranging from statistical approaches to machine learning and deep learning models. It has been found that advanced techniques like machine learning and deep learning models outperform traditional models by improving drought prediction accuracy. This review article critically examines the advancements in technology that have facilitated improved drought prediction, identifies the key challenges and opportunities in the field of drought prediction, and identifies the key trends and topics that are likely to give new directions to the future of drought prediction research. It explores the integration of remote sensing data, meteorological observations, hydrological modeling, and climate indices for enhanced accuracy. Under the frequently changing climate conditions, this comprehensive review provides a valuable resource for researchers, practitioners, and policymakers engaged in drought prediction and management and fosters a deeper understanding of their capabilities and limitations. This article paves the way for more accurate and effective drought prediction strategies, contributing to improved resilience and sustainable development in drought-prone regions.

Drivers of Dry Day Sensitivity to Increased CO2

AbstractPersistent precipitation deficits are among the most impactful consequences of global warming. Here we focus on changes in the annual number of dry days (NDD) and in the annual maximum length of dry spells due to a quadrupling of atmospheric CO2. We use atmosphere‐only simulations to decompose the projected changes into additive contributions. A fast adjustment leads to a global increase in NDD despite notable regional exceptions (e.g., South Asia and Sahel). The effect of the uniform component of the surface ocean warming is model‐dependent but shapes the regional distribution of the NDD response in each model. Finally, the ocean warming pattern also contributes to large uncertainties, likely through contrasting changes in large‐scale circulation. Our results thus highlight the complexity of the NDD response, with policy‐relevant practical implications for mitigation and adaptation strategies.

Heuristic data-inspired scheme to characterize meteorological and groundwater droughts in a semi-arid karstic region under a warming climate

Study regionThe Edwards Aquifer Region is located in south-central Texas United States.Study focusThe paper focuses on the development and implementation of a data-inspired heuristic drought identification scheme to (i) quantify the intensity, duration, and frequency of precipitation deficit- and high temperature-driven meteorological droughts (PMet- and TMet-droughts), and (ii) link their propagation to groundwater droughts (GW-droughts) using baseline hydroclimatic measures and prevailing drought conditions derived from historical climate data and regional mitigation strategies.New hydrological insights for the regionBased on the intensity, duration, and timing of PMet- and TMet-droughts in the semi-arid karstic region, we identified three distinct GW-droughts, including persistence-driven, preconditions-driven, and intensity-driven droughts. The analysis revealed that successive heavy precipitation events are needed to end GW-droughts. The scheme also identified TMet-droughts with the longest dry spells, TMet- and PMet-droughts with the highest intensity, and GW-drought with the second-highest intensity on record all occurred over the past 15 years. These findings provide evidence for a warming climate, intensified meteorological droughts, and increasing stress on the aquifer. Among the artificial intelligence models used, Extremely Randomized Trees (ERT) regressor predicted time series of intensity & duration of GW-droughts from hydroclimatic features with high accuracy. The ERT classifier revealed that the duration of PMet droughts and the intensity of TMet droughts are the topmost decisive features in predicting GW-drought intensity in the region.