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Flash droughts, characterized by rapid onset and development, present significant challenges to agriculture and climate mitigation strategies. Operational drought monitoring systems, based on precipitation, soil moisture deficits, or temperature anomalies, often fall short in timely detection of these events, underscoring the need for customized identification and monitoring indices that account for the rapidity of flash drought onset. Recognizing this need, this paper introduces a global flash drought inventory from 1990 to 2021 derived using the Soil Moisture Volatility Index (SMVI). Our work expands the application of the SMVI methodology, previously focused on the United States, to a global scale, providing a tool for understanding and predicting these rapidly developing phenomena. The dataset encompasses detailed event characteristics, including onset, duration, and severity, across diverse climate zones. By integrating atmospheric variables through their impact on soil moisture, the inventory offers a platform for analyzing the drivers and impacts of flash droughts, and serves as a large, consistent dataset for use in training and evaluating flash drought prediction models. [ABSTRACT FROM AUTHOR]

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Regional cities are having their unique water security challenges due to regional urban water contexts, regional socio-economic structure, and climate conditions. Regional urban community's perceptions of water usage are expected to be different from the communities in large metropolitan cities. The city of Townsville is the largest regional city in the northern tropical region of the state of Queensland in Australia, and it is known to have its unique dry tropic climate condition. The city faced a water crisis due to a prolonged drought in 2013–2018. As part of this research, at first, a literature review was conducted to understand what water demand management (WDM) tools worked well during urban water crisis in different parts of the world. This paper then investigates how residential water usage changed with the changes in drought measures in the city of Townsville in the last decade. A minimum per capita residential water requirement is established for the study region to benchmark the effects of tools implemented in the region. The paper investigates the WDM policies implemented in the city of Townsville including when the policies were applied and the impacts and efficacy of these policies before water crisis, during water crisis and after water crisis. The most effective WDM tools identified are water restrictions, public awareness raising and education programmes. The impacts of water restriction policies and the perceptions of local water professionals on their success elements are also studied. The results are compared and the reasons behind the findings are investigated. [ABSTRACT FROM AUTHOR]

This bibliographic article on Drought and Water Level examined the relationship between organizations, nations, institutions, authors, references, and publishers. It examined 742 papers from Web of Science at the Nanjing University of Information Science and Technology's. The total annual publication volume of articles was increased steadily from 2012 to 2021, with China and the United States ranking first and second in terms of publication volume and citations but in quality Switzerland and England were top-level. Institutional-partnership analyses indicated disparities in network density and connections, with the Chinese Academy of Sciences (2012) receiving the highest citations and degrees. The document co-citation analysis (DCA) network was created to improve understanding of the frequency and amplitude of bursts of various publications in separate clusters. The most cited work was J Hydrol (2012), with 302 citations. The analytical tool from CiteSpace collected high-frequency keywords and performed co-occurrence, grouping, and emerging word recognition. Gorges Dam is the most crowded cluster, followed by drought stress. The greatest burst duration and most significant phrase is reservoir (2019), followed by "water quality," which has a 5 year burst period. Estuaries perform important functions such as water purification and coastal. "Reservoir, water quality, restoration, phytoplankton, temperature, wetland, time series, diversity and carbon dioxide" are the most important terms, while "climate change, drought, water level, impact, growth, variability, response, dynamics, management and model" are the most frequently used keywords. In terms of citations, references, and academic influence, Zhang Q. (2012), the R Core team (2014), and Jappen E. (2015) were the top three contributors. Cook, ER (2013), and Allen, R.G. (2019) ranked first and second in terms of frequency, respectively. In this review work, significant information gaps were discovered in the areas of microbiological dynamics, environmental variables, fen peat incubation, lake water, drought risk reduction, biological ecology, lake acidification, salinity variations, and attribution. Future researchers should focus on these and similar topics, while Chinese and USA authors should concentrate on article quality rather than publishing numbers. [ABSTRACT FROM AUTHOR]

The future risk for droughts and water shortages calls for substantial efforts by authorities to adapt at local levels. Understanding their perception of drought hazards, risk and vulnerability can help to identify drivers of and barriers to drought risk planning and management in a changing climate at the local level. This paper presents a novel interdisciplinary drought case study in Sweden that integrates soft data from a nationwide survey among more than 100 local practitioners and hard data based on hydrological measurements to provide a holistic assessment of the links between drought severity and the perceived levels of drought severity, impacts, preparedness, and management for two consecutive drought events. The paper highlights challenges for drought risk planning and management in a changing climate at the local level and elaborates on how improved understanding of local practitioners to plan for climate change adaptation can be achieved. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper presents the composite drought indicator (CDI) that Jordanian, Lebanese, Moroccan, and Tunisian government agencies now produce monthly to support operational drought management decision making, and it describes their iterative co-development processes. The CDI is primarily intended to monitor agricultural and ecological drought on a seasonal time scale. It uses remote sensing and modelled data inputs, and it reflects anomalies in precipitation, vegetation, soil moisture, and evapotranspiration. Following quantitative and qualitative validation assessments, engagements with policymakers, and consideration of agencies' technical and institutional capabilities and constraints, we made changes to CDI input data, modelling procedures, and integration to tailor the system for each national context. We summarize validation results, drought modelling challenges and how we overcame them through CDI improvements, and we describe the monthly CDI production process and outputs. Finally, we synthesize procedural and technical aspects of CDI development and reflect on the constraints we faced as well as trade-offs made to optimize the CDI for operational monitoring to support policy decision-making—including aspects of salience, credibility, and legitimacy—within each national context. [ABSTRACT FROM AUTHOR]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Persistent droughts are known to induce stress on agricultural crops and forest ecosystems. Severe long-lasting droughts lead to food insecurity. With rising air temperatures and declining precipitation totals, there is often a presumption that droughts are becoming more severe. To understand the complexity of interrelated physical processes on various temporal scales, it is important to analyse trends and mutual relationships between drought-related climatic variables. In this paper, we analyse monthly time series of near-surface air temperature, precipitation totals, potential evapotranspiration, climatic water balance, and two meteorological drought indices: the standardised precipitation index (SPI) and the standardised precipitation-evapotranspiration index (SPEI), at a total of 71 locations located within the western Carpathian Mountains (Slovakia) and the adjacent northern part of the Pannonian Plain. The analysed data cover the time period 1981–2019. Quantile regression was used to determine the slopes of temporal trends in the investigated climate variables. The mutual relationships between precipitation and air temperature were analysed on a seasonal basis. Negative coupling (~ − 5.1%/°C) between precipitation and air temperature was observed in the spring season. Positive coupling between precipitation and air temperature was observed in the remaining part of the year. Spatio-temporal analyses of SPEI revealed intensification of meteorological drought in the spring season that continues into summer at most of the analysed locations. The negative temporal trends in the SPEI suggest that the severity of meteorological drought has increased over the investigated period. [ABSTRACT FROM AUTHOR]

Accurate ensembles of precipitation data play an important role in precise and efficient drought monitoring systems at the regional level. This article proposes a weighted aggregation scheme – the Divergence and Interdependence-based Hybrid Weighting Scheme (DIHWS) – to ensemble precipitation data for accurate regional drought analysis. The derivation of weights is based on the interdependence among meteorological observatories and the divergence from the mean characteristics of regional data. Here, the interdependence among meteorological observatories is assessed using the Bayesian Network theory. At the same time, the divergence from the mean characteristics of regional data is based on the set of equations used for regional aggregation in (Ali et al., Water Resour Manage 36:4099–4114, 2022). Consequently, the paper introduces a new regional drought index – the Bayesian Network-based Adaptive Regional Drought Index (BNARDI). BNARDI is a standardized regional index and used estimated at multiple time scales. The application of DIHWS and BNARDI is based on five regions of varying observatories. We observed smaller MAE values associated with DIHWS than its Simple Model Average (SMA) and one other of its relevant compitator in all the regions. Therefore, we conclude that the proposed weighting scheme and drought index are more reliable for regional drought monitoring and forecasting. Additionally, the research includes various forecasting models to assess their appropriateness for forecasting the new regional index. The results of this research demonstrate that no single method is suitable for forecasting complex drought data, as generated by BNARDI. Therefore, we suggest using varying methods or a hybrid of various candidate forecasting models for forecasting BNARDI. [ABSTRACT FROM AUTHOR]

Drought stress remains one of the most detrimental environmental constraints that hampers plant growth and development resulting in reduced yield and leading to economic losses. Studies have highlighted the beneficial role of carbon-based nanomaterials (NMs) such as multiwalled carbon nanotubes (MWNTs), single-walled carbon nanotubes (SWNTs), graphene, fullerene, and metal-based nanoparticles (NPs) (Ag, Au, Cu, Fe2O3, TiO2, and ZnO) in plants under unfavorable conditions such as drought. NPs help plants cope with drought by improving plant growth indices and enhancing biomass. It improves water and nutrient uptake and utilization. It helps retain water by altering the cell walls and regulating stomatal closure. The photosynthetic parameters in NP-treated plants reportedly improved with the increase in pigment content and rate of photosynthesis. Due to NP exposure, the activation of enzymatic and nonenzymatic antioxidants has reportedly improved. These antioxidants play a significant role in the defense system against stress. Studies have reported the accumulation of osmolytes and secondary metabolites. Osmolytes scavenge reactive oxygen species, which can cause oxidative stress in plants. Secondary metabolites are involved in the water retention process, thus improving plant coping strategies with stress. The deleterious effects of drought stress are alleviated by reducing malondialdehyde resulting from lipid peroxidation. Reactive oxygen species accumulation is also controlled with NP treatment. Furthermore, NPs have been reported to regulate the expression of drought-responsive genes and the biosynthesis of phytohormones such as abscisic acid, auxin, gibberellin, and cytokinin, which help plants defend against drought stress. This study reviewed 72 journal articles from 192 Google Scholar, ScienceDirect, and PubMed papers. In this review, we have discussed the impact of NP treatment on morphological, physio-biochemical, and molecular responses in monocot and dicot plants under drought conditions with an emphasis on NP uptake, transportation, and localization. [ABSTRACT FROM AUTHOR]

Agricultural sectors worldwide are under direct threat from climate change conditions. In Iran, agricultural production has decreased due to droughts originating in an increase in annual maximum temperatures—with the corresponding increase in crop respiration and evapotranspiration—and a decrease in accumulated precipitation. Based on a static computable general equilibrium approach, this paper reports implication for the Iranian economy from the effects of climate change on agriculture––as modeled through three scenarios relying on assumptions about the magnitude of continued reduction in total agricultural production. Reductions of 6%, 12%, and 18% in total agricultural production reasonably cover the range of impacts that climate change is expected to impose on the Iranian agricultural sector––under the assumption that no behavioral adaptations or policy interventions are in place. Our simulations suggest that effects on the Iranian economy imply a reduction in GDP ranging between 3.7 and 6.3%. In addition, 5–17% of labor moves away from the agriculture sector––this labor relocation occurs due to declining agriculture incomes. Findings illustrate that climate change will reduce households' consumption and income in all economic sectors, particularly among rural households. We suggest that policies in Iran should focus on improving cultivation methods to save water resources and alleviate the expected effects of climate change. The current study's outcomes are helpful for policymakers, especially in countries with water scarcity. [ABSTRACT FROM AUTHOR]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Ecological environment is the essential material basis of human survival and connects regional economy with socially sustainable development. However, climate changes characterized by global climate warming have caused a series of ecological environmental problems in recent years. Few studies have discussed various climate factors affecting the ecological environment, and the spatial non-stationary effects of different climate factors on the ecological environment are still unclear. Dynamically monitoring ecological environment changes in fragile areas and identifying its climate-driving mechanism are essential for ecological protection and environmental repair. Taking Zoige Plateau as a case, this paper simulated the eco-environmental quality during 1987–2020 using remote sensing data, utilized Geodetector method to identify the contributions of various climate drivers to ecological environment quality, and then adopted the Geographically Weighted Regression model to explore the spatial non-stationary impacts of climate factors on ecological environment quality. The results showed that the ecological quality in the middle regions of the Zoige Plateau was slightly better than in the surrounding marginal areas. For the whole area of Zoige Plateau, the average ecological environment quality index was 54.92, 53.99, 56.17, 57.88, 63.44, 56.93, 59.43, and 59.76 in 1987, 1992, 1997, 2001, 2006, 2013, 2016 and 2020, respectively, which indicated that eco-environmental quality witnessed several fluctuations during the study period but showed a generally increasing trend. Among five climate factors, the temperature was the dominant climate factor affecting the ecological environment quality (q value: 0.11–0.19), sunshine duration (0.03–0.17), wind speed (0.03–0.11), and precipitation (0.03–0.08) were the main climate drivers, while the explanatory power of relative humidity to ecological environment quality was relatively small. Such various climate factors impacting the ecological environment quality demonstrated distinct spatial non-stationary and the range of driving impact varied with time. Temperature, sunshine duration, wind speed, and relative humidity promoted ecological environment quality in most regions (regression coefficients > 0), while precipitation mainly had a negative inhibitory impact (regression coefficients < 0). Meanwhile, the greater impacts of these five climate factors were concentrated in high-elevation regions of the south and west or the northern areas. The appropriate enhancement of climate warming and air humidity was beneficial to the improvement of the ecological environment, but the excessive precipitation would result in landslides and exhibit inhibition of vegetation growth. Therefore, selecting cold-tolerant herbs and shrubs, and strengthening climate monitoring and early warning systems (such as drought and excessive precipitation) are essential for ecological restoration. [ABSTRACT FROM AUTHOR]

The frequency of extreme weather events has increased in the latest years in Europe. The recent consecutive droughts caused severe damage in many sectors and underlined the demand for adaptation. There is a need for a better understanding of the response of ecosystems to climate change and the consequences for key ecosystem services, such as water supply and carbon sequestration, at a local and regional scale. This paper aims to support decision-making for climate adaptation in a low-mountainous region of central Germany. We analysed the temperature and precipitation trends and drought conditions. The response of two key services (surface water provision and carbon sequestration) to droughts is estimated using an ecosystem service model. The spatially averaged water yield, net ecosystem productivity (NEP), and soil moisture are assessed and compared for the five worst droughts with long-term averages to identify the vulnerable areas and ecosystems. The temperature increased on seasonal and annual scales, while precipitation decreased in some areas in summer and increased in winter and annually. The standardised precipitation-evapotranspiration index (SPEI) showed worsening drought conditions, especially after the late 1980s. Droughts caused a reduction of water yield by 54%, NEP by 18%, and upper zone soil moisture by 13%. The impacts varied spatially, with the central region being worst affected, while the southern part was relatively more resilient. Adaptation is urgently needed to reduce drought risks and enhance climate resilience. Adaptive measures can include amending crop rotations, introducing more drought-tolerant varieties, upgrading agriculture and food industry technology, increasing mixed forests, and reducing non-native tree species. [ABSTRACT FROM AUTHOR]

The use of remote sensing for monitoring and managing droughts is examined in this review study. Drought has a significant impact on how water resources are managed and agricultural production is produced, and remote sensing is a vital technique for assessing and monitoring the severity of drought. A number of remote sensing data sources are discussed in the paper; including precipitation, groundwater and surface water storage, soil moisture, land surface temperature, evaporation, and agricultural indicators. With the use of these data sources, drought indices and indicators that measure the severity and spatiotemporal fluctuations of the drought may be developed. The novel approach of this review study emphasizes the benefits of using remote sensing to gain a full understanding of drought dynamics and to accurately capture fine-scale fluctuations in drought conditions. However, the study also highlights certain limitations, including issues related to data accessibility, data interpretation, and validation difficulties. It emphasizes the significance of using remote sensing to promote the developing policies and strategies to enhance drought resilience and adaptation. The importance of continuous research, technical development, and stakeholder cooperation in order to fully realize remote sensing's promise for tackling the complex problems associated with drought and promoting sustainable water resource management. [ABSTRACT FROM AUTHOR]

Climate change is a major concern, as it profoundly affects many facets of our lives. It has brought about several issues, including declining water supply, reduced agricultural yields, increased drought occurrences, and increased heat waves. Amidst these challenges, the influence of short-term drought events on plant growth and irrigation schedule emerges as a critical concern. However, despite these evident consequences, a nuanced understanding of the intricate relationship between the severity and duration of short-period drought/deficit events still needs to be explored. This paper analyses fortnightly water deficit periods over different regions of India, which would be more relevant to re-scheduling the irrigation events than monthly or longer duration in preventing crops from reaching the permanent wilting point. Hence, this work considers analyzing 15-day Standardized Precipitation Index (SPI) trends and drought characteristics using conventional methods and Innovative Trend Analysis (ITA) techniques. The analysis uses gridded rainfall data from the India Meteorological Department (IMD), which has a spatial resolution of 0.250-E and 0.250-N. The data spans the period from 1970 to 2021. The ITA and Mann Kendall (MK) displayed nearly identical areas of increasing and decreasing trends, but ITA effectively identified significant trends. While MK and Modified Mann Kendall (MMK) could only indicate significant trends for 12.94%, 9.57%, and 9.9% of grid points for SPI, drought severity, and duration, respectively, ITA was able to identify significant trends at 44.31%, 10.9%, and 10.1% on an annual scale. The ITA method effectively identified the significant trends and magnitudes of fortnightly SPI and drought characteristics. The Tropical monsoon (Am), Tropical savannah (Aw), Arid desert hot (BWh), Arid steppe hot (BSh), and Temperate dry winter warm summer (Cwb) climatic zones have shown a significant increase in annual drought severity. Similarly, a significant increase in monsoon drought severity is observed across several states, including Gujarat and Mizoram, impacting diverse geographic extents. The present study can help policymakers and water resource managers decide on water allocation, irrigation, and crop management practices. [ABSTRACT FROM AUTHOR]

The frequency of extreme events is increasing on a global scale due to various factors, accounting for natural disasters such as landslides, floods, and droughts. The Heilongjiang province, which is agriculturally important for China, has suffered from several extreme rainfall events in the past as a high-latitude plain region. Analysis of historical rainfall characteristics of the Heilongjiang region helps to understand and predict the behavior of extreme rainfall events and provides a reference for reducing agricultural economic losses. Precipitation data from 1974 to 2017 is selected to estimate whether rainfall series in Heilongjiang obey the Gumbel-Logistic Model. We compared the Gumbel-Logistic Model based on the data length of 5 years, 10 years, and 20 years with the original 44-year data to determine the appropriate data partition length and explore the reasons for errors. Combining the empirical frequency and KS test, this paper concludes that the proposed model is appropriate for the representation of the joint distribution of monthly extreme rainfall and annual rainfall. The proposed model improves the rainfall assessment of these two positively correlated variables in Heilongjiang. Univariate and bivariate return periods and correlation coefficients are derived as the basis for assessing the risk of extreme rainfall. The proposed model obtained from the 5-year data length has the largest error, while the distribution curve is progressively smoother as the data length increases. [ABSTRACT FROM AUTHOR]

Drought is a natural phenomenon that occurred in Central Europe in the past, but it is becoming a more serious problem due to the changes in its occurrence and intensity related to climate change. The main aim of this paper was to determine changes in air temperature and precipitation amounts in Slovakia from 1931 to 2020 and to identify changes in drought occurrence and intensity using the Standardised Precipitation and Evapotranspiration Index (SPEI). Cluster analysis was used to determine regions with similar drought occurrences. For each of the identified five clusters, drought characteristics were determined and compared between two reference periods 1961–1990 and 1991–2020. While a decrease in the number of months with SPEI-1 below − 1 was observed in autumn, spring and summer months showed a drying tendency. Overall, we can say that we observed a shift in drought occurrence from autumn and winter months to spring and summer months. This is an important finding for the agriculture or forestry because it affects work management and planning. The clearest tendency in drought events was observed in the western part of Slovakia covering areas with agriculturally intensive land use. Besides prolonging drought events, there was also a higher accumulated deficit for each event. The increase in drought intensity was not spatially consistent over the cluster area, mostly reaching a slight decline of about − 0.1 to − 0.3, which means slight intensification of drought periods in 1991–2020. [ABSTRACT FROM AUTHOR]

The impacts of climate change increasingly show themselves in many forms in our everyday lives such as heatwaves and droughts. Drought is one of the critical events today for increasing drought frequency. This study focuses on meteorological drought because it directly affects other drought types. Hence, this study focuses on how the future drought conditions will vary under climate change effects in the Mediterranean basin (Turkey). In doing so, this study utilizes precipitation data from three General Circulation Models (GCMs) and three Regional Circulation Models (RCMs). The GCMs are CNRM-CM6, GFDL-CM4, and MPI-ESM1, while the RCMs are (RCA4)-CNRM-CM5, (Reg CM4)-GFDL-ESM2M, and (RCA4)-MPI-ESM-MR. Mitigating biases of the climate models, this study utilizes four statistical downscaling methods (SD), linear scaling (LS), local intensity scaling (LOCI), power transformation (PT), and distribution mapping (DM). Here, the study has two purposes. The main aim of the paper here is to compare the performance of SD methods in improving the representation of observed climate variables in climate models. In addition, the study shows how different methods will affect the spatial drought distribution in the area under the SSP2 4.5 and SSP5 8.5 scenarios. Consequently, the study uses the standardized precipitation index (SPI) and Z-score index (ZSI) to quantify future drought conditions and reaches the following results. The study reveals that mild drought conditions are prevalent in the basin for future periods, and drought indices go down to − 0.55. The study also shows that different SD methods affect the results obtained by each climate model diversely. For example, while the LS method causes the most drought conditions on the results based on CNRM-CM5 and CNRM-CM6, the DM method has a similar impact on outcomes based on GFDL-CM4 and GFDL-ESM2M and causes the most drought conditions. [ABSTRACT FROM AUTHOR]

For an effective reservoir operation during drought, the variations of both water supply and water demand which depend on hydrological and meteorological conditions need to be dealt with. This paper aimed to consider these variations in the Aharchay basin (Iran) by coupling a hedging rule (HR)-based reservoir operation model (HRROM) with a climate-based irrigation scheduling model (CBISM) at the farm level. Through the HRROM, optimal long-term decisions for Sattarkhan reservoir were made by considering the probable streamflow scenarios in the system. Given the variable agricultural demands (VAD) in the CBISM, the irrigation water was optimally allocated to the crops using several evapotranspiration (ET) scenarios. The CBISM employs three sub-models including linear programming (LP), nonlinear programming (NLP), and particle swarm optimization (PSO) to maximize the total income of the Aharchay agricultural network as a function of the climate factors and the supplied water. To this end, the daily weather and discharge data from 1990 to 2015 were used in this study. The standardized precipitation-evapotranspiration index (SPEI) and the streamflow drought index (SDI) were used to detect the meteorological and hydrological droughts, respectively. The SPEI was calculated based on the high-resolution-gridded datasets of the Climatic Research Unit (CRU). The findings demonstrated that the HRROM-CBISM generally managed to increase the time-based (αt) and volume-based (αv) reliability indices by 20% and 44%, respectively, compared with the conventional standard operation policy (SOP). For more investigations, the three major droughts of 2000–2002, 2004–2006, and 2008–2014 were separately analyzed. The average values of αt, αv, and vulnerability (V) for SOP were 0.33, 0.51, and 0.48, respectively. With the HRROM-CBISM, these values were about 0.5, 0.55, and 0.45, respectively. Among these indices, αt had the highest variations, while αv had the lowest variations in both the SOP and HRROM-CBISM approaches. The average water shortage for the mentioned droughts was significantly decreased from 89 (SOP) to 75 MCM (HRROM-CBISM). [ABSTRACT FROM AUTHOR]

The Western United States is experiencing historic drought, increasing pressure on water management systems. Agricultural production that relies on surface water flows is therefore imperiled, requiring new innovations and partnerships in order to adapt and survive. In Arizona, some agriculture continues to rely on historic, low-tech irrigation infrastructure such as hand-dug open ditches that divert river water to flood fields. These ditch systems are managed through both formal ditch companies and informal associations. To address changing water availability and needs, ditch users regularly "tinker" with water infrastructure, experimenting and making changes beyond the original infrastructure plans. Such changes are informed and driven by local social relationships and realities of the physical infrastructure. These dynamics are critical to understanding the adaptive capacity and flexibility of the water system; however, they are challenging to recognize and record. In this paper, we apply the emerging conceptualization of sociotechnical tinkering to examine the adaptive management of irrigation ditches in the Verde Valley of Arizona. We find evidence that water users frequently tinker with their water delivery and monitoring infrastructure to respond to and anticipate changes in water availability. Viewed through the lens of sociotechnical tinkering, these interactions are understood as the material manifestations of situated practice and actor agency within a water management system. This case study contributes to literature on adaptive environmental management and the hydrosocial cycle. [ABSTRACT FROM AUTHOR]

Due to global climate change, droughts are likely to become more frequent and more severe in many regions such as in South Africa. In Limpopo, observed high climate variability and projected future climate change will likely increase future maize production risks. This paper evaluates drought patterns in Limpopo at two representative sites. We studied how drought patterns are projected to change under future climatic conditions as an important step in identifying adaptation measures (e.g., breeding maize ideotypes resilient to future conditions). Thirty-year time horizons were analyzed, considering three emission scenarios and five global climate models. We applied the WOFOST crop model to simulate maize crop growth and yield formation over South Africa's summer season. We considered three different crop emergence dates. Drought indices indicated that mainly in the scenario SSP5-8.5 (2051–2080), Univen and Syferkuil will experience worsened drought conditions (DC) in the future. Maize yield tends to decline and future changes in the emergence date seem to impact yield significantly. A possible alternative is to delay sowing date to November or December to reduce the potential yield losses. The grain filling period tends to decrease in the future, and a decrease in the duration of the growth cycle is very likely. Combinations of changed sowing time with more drought tolerant maize cultivars having a longer post-anthesis phase will likely reduce the potential negative impact of climate change on maize. [ABSTRACT FROM AUTHOR]

There are several standardized meteorological, hydrological, agricultural, and environmental indices for drought classification into a set of dry categories all of which are derived from the basic concept of standardized precipitation index (SPI). Almost all these indices are based on crisp (bivalent) logic where boundary limits between neighboring categories are numbers without transboundary inclusiveness. The SPI procedure depends on the standard normal (Gaussian) probability distribution function (PDF) with zero mean and standard deviation equal to one. This paper proposed fuzzification of the SPI limits among categories for the inclusion of more than one category with different membership degrees. This method is referred to as the fuzzy SPI (FSPI) procedure, which provides drought tracing possibility and categorization. At the end for a numerical value, one can defuzzify the fuzzy result through defuzzification methods. FSPI provides preliminary warning system in terms of two or more fuzzy rule propositions and categories. Thus, one can know the logical alternatives of the drought behavior of a given hydro-meteorology variable. The application of the FSPI is presented for New Jersey State wise and Istanbul annual precipitation records. [ABSTRACT FROM AUTHOR]

The present paper examines the significance of remittances by the male outmigrants on socio-economic development of the receipient households in a frequently drought affected Bankura district in the Rarh region of West Bengal State of India with particular emphasis on the varied impacts with respect to differential access to landholding or lack of it. As many as 185 out of a total of 756 households were randomly selected for collection of data with the help of a structured household schedule. Logistic regression model has been fitted to analyse the relation between the size of migrant remittances and important socio-economic determinants. The study revealed that the size of the remittance depends on nature and types of work undertaken by the migrants at the destination. Only a small proportion of the recipient migrant households utilized the remittances received by them for a single purpose though the majority used it for a multiple of purposes. Majority of the migrant households utilized the remittances for food consumption as well as to repay the loans taken by them before adopting migration as a strategy to improve their living. Outmigration for a short or longer period appears to be a successful strategy for these households to withstand chronic poverty suffered by the most marginalised segment while the somewhat better-off sections manages to further improve their living conditions with the help of remittances received. [ABSTRACT FROM AUTHOR]

A critical understanding of the water crisis of Lake Urmia is the driver in this paper for a basin-wide investigation of its Meteorological (Met) droughts and Groundwater (GW) droughts. The challenge is to formulate a data-driven modelling strategy capable of discerning anthropogenic impacts and resilience patterns through using 21-years of monthly data records. The strategy includes: (i) transforming recorded timeseries into Met/GW indices; (ii) extracting their drought duration and severity; and (iii) deriving return periods of the maximum drought event through the copula method. The novelty of our strategy emerges from deriving return periods for Met and GW droughts and discerning anthropogenic impacts on GW droughts. The results comprise return periods for Met/GW droughts and their basin-wide spatial distributions, which are delineated into four zones. The information content of the results is statistically significant; and our interpretations hint at the basin resilience is already undermined, as evidenced by (i) subsidence problems and (ii) altering aquifers' interconnectivity with watercourses. These underpin the need for a planning system yet to emerge for mitigating impacts and rectifying their undue damages. The results discern that aquifer depletions stem from mismanagement but not from Met droughts. Already, migration from the basin area is detectable. [ABSTRACT FROM AUTHOR]

In this paper, the standardized precipitation evapotranspiration index (SPEI) at the monthly scale was derived based on the ground observations to obtain different drought and wet events at the surface of the Loess Plateau in summer from 2000 to 2017. Using the National Centers for Environmental Prediction (NECP) Final Analysis (FNL) data for the same period, backward simulations with the FLEXPART model were performed to obtain the water vapor transport characteristics and potential evaporative sources corresponding to different dry and wet events. Finally, the contribution of water vapor sources to precipitation on the Loess Plateau was obtained. The results show that the primary sources of water vapor on the Loess Plateau during dry and wet summer events are concentrated in the Loess Plateau and the Yunnan-Kweichow Plateau regions and sporadically distributed in the Altay region of Xinjiang, as well as at the junction of China, Kazakhstan and Mongolia. The evaporation extent and intensity in northern Xinjiang and Mongolia increase when the surface experiences wet-normal-dry events. The local internal circulation on the Loess Plateau contributes to 31.3% and 36.8% of the water vapor in drought and wet events, respectively. Influenced by the westerly wind belt and southwest monsoon, the precipitation contributions of the Yunnan-Kweichow Plateau are 11.2% and 13.1%, respectively, and those of Mongolia are 14.6% and 11.9%, respectively. The water vapor contributions from the Arabian Sea and Bay of Bengal in the south are insignificant. The results aid in understanding the mechanisms of drought and wet events on the Loess Plateau. [ABSTRACT FROM AUTHOR]

Climate change may cause adverse impact on agricultural production that could jeopardize food availability and security. In this paper, we investigate how changes in mean values and variability of weather variables may affect rice yield using panel data for 30 districts of Tamil Nadu State from 1971 to 2018. We estimate a fixed-effects regression model with panel-corrected standard errors. Results show that rainfall and temperature have a statistically significant impact on rice yield. Furthermore, weather variability, measured as standard deviations of temperature and rainfall, has a negative effect on rice yields. We use the Coupled Model Inter-comparison Project-5 outputs and dynamically downscaled the weather outputs using the regional climate model. The results of the climate model showed that the rise in temperature and disruptions in rainfall patterns including both excessive and deficient rainfall events in Tamil Nadu will continue in the future under different climate scenarios. Projected changes in the weather variables are likely to decrease rice yield in Tamil Nadu from 0.7 to 6.3% under the low emission scenario and 4.1 to 20.1% in the high emission scenario during 2022–2050 (relative to 1971–2018). These projections have implications for the planning and targeting of climate adaptation technologies such as drought-tolerant and flood-tolerant varieties to lessen the adverse impact of weather variability due to climate change in the future. [ABSTRACT FROM AUTHOR]

Drought is a natural disaster that causes much damage to the communities. Recently, water demand has been increasing sharply due to the population growth and the development process. By approaching the amount of water demand to the natural supplies, any decrease in the water supply may lead to a considerable negative socio-economic consequence. In this condition, the sense of drought prevails over the physical drought. Therefore, usual drought indices can not be used for characterizing and monitoring the drought in a basin. In this paper, multivariate standardized drought feeling index (MSDFI) is introduced which represents two dimensions of water management: (1) water supply in terms of precipitation and (2) water demand in terms of population. The MSDFI is calculated and its variation over time is compared to the standardized precipitation index (SPI). According to the results, MSDFI values in the early years were usually higher than SPI values and vice versa in the last years. This situation is highly correlated with the population trend in the basin. Thereafter, intensity of drought index (IDI) was defined as the difference between MSDFI and SPI to show the role of water demand in the drought feeling. Results show that IDI has an increasing trend in the populated areas, generally downstream of the basin, where population growth is high. In contrast, in the sparsely populated areas generally upstream of the basin where population growth is low and even negative due to migration, the IDI does not show any significant sense of drought. [ABSTRACT FROM AUTHOR]

The present study aims to investigate Iran's agrometeorological drought history and its properties using Multivariate Standardized Drought Index (MSDI). For this purpose, precipitation and soil moisture recorded at 99 synoptic stations in Iran during 1985 to 2018 were selected. Based on MSDI time series, drought properties including duration and severity were calculated and trend analysis was carried on using Trend Free Prewhitening Mann Kendall test. Also, the standard normal homogeneity test was applied to investigate chronological drought change-point detection. From agrometeorological perspective, results showed that longer and more severe droughts are more dominant in southern, southeastern, northeastern, and some western regions of the country. Trend analysis revealed that most study stations have rising frequency and significant drying trend especially in winter at central plateau and western regions. Also, we recognized two main periods 1991–2000 and 2006–2010 that many stations experienced change-point in their MSDI time series, mainly because of climatic and anthropogenic causes. Drought properties assessment shows 6 stations with serious upward trend in drought duration and severity in northeast and western regions. Sens's Slope statistics in these stations was calculated around 1.5 degree per event for drought severity and 1 month per event for drought duration. It is also observed that the 75th quantile of drought severity for most parts of the country is between 13 and 18 and the 75th quantile for drought duration varies between 8 and 24 months in different regions. The probability analysis revealed that most stations have a ratio around 2–5 times increase in drought occurrence probability after change point, leading to longer and more severe droughts in these stations. The paper indicates a serious situation related to agrometeorological drought occurrence, persistence, and severity in Iran because of many climatic and anthropogenic factors over the last 30 years. [ABSTRACT FROM AUTHOR]

The present paper investigates the time-series properties of average rainfall and temperature readings of countries in Southeast Asia (Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand, Timor-Leste, and Vietnam) using monthly data, spanning from 1901 to 2016. Specifically, we analyze the time trend, persistence, and seasonality properties of the series using I(d) fractional integration framework, an approach that is found to be robust in dealing with climatological series. Antipersistence is observed in the rainfall series of Cambodia, Laos, Myanmar, and Vietnam while long memory is found in the rainfall series of the remaining countries. Thus, those countries with antipersistent rainfall are prone to erratic rainfall distribution which could lead to flooding or drought. Long memory is observed in the distribution of rainfall across all countries with increasing trend found in some cases. Both climatic variables display evidence supporting seasonality with stronger seasonality observed in Cambodia, Laos, Myanmar, Thailand, and Vietnam. Findings in the present paper are of policy relevance to climate monitoring agencies and the government. [ABSTRACT FROM AUTHOR]

The flood protection embankments of Hungary and Europe face numerous challenges. Some dike bases were constructed more than 200 years ago; since then, they have been elevated and extended. Because of these iterative adaptations, the dikes bear many construction errors, which can trigger failures and slides. Due to climate change, droughts and low-water periods of the rivers in central Europe are becoming more frequent. As a result of these effects, the water balance of the dikes can alter and desiccate in the long term. The most staggering fissures appeared on dikes built from clays susceptible to volume change. The General Directorate of Water Management ordered a comprehensive survey of dike pavement cracks in Hungary. This was one of the most extensive surveys of such kind. Hungary has some 4400 km of primary flood protection embankments, out of which 1250 km is paved. There are multiple reasons why the pavement of an embankment can crack. The main features of crack patterns related to clays with shrink-swell potential are identified. The results of international studies and the present survey are synthesised. The main objective of this paper is to draw a correlation between drought (aridity) zones, plasticity index of the soil samples, and crack thickness. [ABSTRACT FROM AUTHOR]

While California has ideal weather for many activities, beaches, and mountains, the water shortage in the state has caused challenges for its growing population. The state has implemented some water saving measures but must do more to meet its needs as its population continues to increase. This paper explores what has been done and what might be done to seek more sources of water. Existing literature tends to examine individual options, instead of performing a broader comparison. This study uses comparative analysis to evaluate multiple approaches to mitigating the effects of drought in California, comparing cost information, technical maturity, and less easily quantified advantages and disadvantages. The study found that conservation, wastewater recycling, water transfer, and similar options have been used successfully in California in the past and should continue to be used. Because all those approaches except wastewater recycling are reaching their limits, the most feasible method to mitigate future droughts in California is increased use of wastewater recycling. However, it faces some emotional and political obstacles to its widespread use. [ABSTRACT FROM AUTHOR]

The summer monsoon–affected area is a suitable area for agricultural production in China. Against the background of climate warming, the activity of the summer monsoon is changing significantly. The drought and flood disasters in this region are becoming more and more frequent and have a greater and more serious impact on agricultural production. Therefore, based on observational data from meteorological stations and yield loss data in agriculture caused by drought and flood disasters in summer monsoon–affected areas, this paper studied the characteristics of the hazard of disaster-causing factors, the risk of losses to agriculture caused by droughts and floods, and their correlation. Moreover, it compared and analyzed the variability of drought and flood hazard and risk to agriculture before and after a temperature rise. The results showed that the precipitation in summer monsoon–affected areas is obviously affected by monsoon activities, and there is an overall though non-significant positive correlation between annual average standardized precipitation evapotranspiration index (SPEI) and the summer monsoon activity index (MI). The drought disaster comprehensive loss rate (DCLR) was generally higher than the flood disaster comprehensive loss rate (FCLR). This shows that the impact of drought on agriculture production is significantly greater than that of floods in this area. The high hazard and risk areas for drought were mainly distributed along the edge of the summer monsoon area and in its vicinity, whereas the high hazard and risk areas for flooding were mainly distributed in the lower reach of the Yangtze, Songhua, and Liaohe Rivers. Among them, Liaoning, Jilin and Heilongjiang are high-risk superposition areas of drought and flood disasters. The hazards of drought and flood dominate the risk of disaster loss. Climate warming has significantly expanded the high-hazard and high-risk ranges in China for drought and flood disasters and has also changed their spatial distribution patterns. The high-hazard area for drought has shifted to the monsoon edge area, the high-risk area for drought has moved northward, and both the high-hazard and the high-risk areas for floods have clearly moved southward. The impact of climate warming on drought was more significant than on floods. This study provides important scientific guidance for formulating drought and flood disaster prevention planning and agricultural production development patterns in China. [ABSTRACT FROM AUTHOR]

This paper presents a composite approach for drought characterization and monitoring using in situ and remote sensing-based drought indicators. The study was carried out on one of the most drought-prone areas of India, i.e., the Marathwada region of Maharashtra. Meteorological, hydrological, and agricultural drought indices, namely standardized precipitation index (SPI), streamflow drought index (SDI), and vegetation condition index (VCI), respectively, were integrated to develop the composite drought index (CDI) using principal component analysis (PCA). SPI and SDI were computed using in situ precipitation and streamflow data, respectively, for 35 years (1980–2014), whereas VCI was computed using MODIS satellite data (500-m resolution) for 15 years (2000–2014) at 1-, 3-, and 5-month time scales. The time scales of drought indices were evaluated using historical drought years and foodgrain production of the region. The drought areas observed by SPI, SDI, and VCI at different time scales were correlated with foodgrain production during the kharif crop growing season for 15 years (2000–2014). The maximum correlation of foodgrain production was observed with 3-month SPI (r = − 0.72), 5-month SDI (r = − 0.40), and 5-month VCI (r = − 0.81) for meteorological, hydrological, and agricultural drought, respectively. Three-month SPI, 5-month SDI, and 5-month VCI were selected from each drought category to develop CDI. These drought indices were combined using weights derived through the PCA technique. The maximum weight was obtained for 3-month SPI (45.4%) followed by 5-month VCI (42.8%) and 5-month SDI (11.8%). The developed CDI products showed a strong relationship (r = − 0.85) with foodgrain production. The drought years observed by CDI were also closest to drought years declared by the State Government. The time series trend of the drought-affected area observed by CDI, 3-month SPI, and 5-month VCI resembled the drought patterns very closely, especially during the drought years. The spatio-temporal analysis of individual drought indices and CDI with foodgrain production deviation showed that CDI was better for capturing drought conditions than individual indicators. The study suggested that an individual or single indicator is not sufficient to capture the actual drought severity and its magnitudes; therefore, using a composite approach could be a good choice for effective drought assessment and monitoring in the region. [ABSTRACT FROM AUTHOR]

Drought is a natural, global and recurring phenomenon caused by climatic anomalies and inevitable meteorological changes. Lake Urmia in northwestern Iran has been drying up in recent years mainly because of its management and operations. On the other hand, with decreasing rainfall, the process of the lake drying up has intensified and affected different aspects of people's lives, especially farmers. In this paper, regional drought was studied in the Urmia Lake Basin from an agricultural perspective in the period of 2001 to 2021 using different vegetation indices such as the Enhanced Vegetation Index (EVI), the Vegetation Condition Index (VCI), the Temperature Condition Index (TCI) and the Temperature Vegetation Dryness Index (TVDI) as well as by applying the temperature product and vegetation cover product of the MODIS sensor of the Terra satellite. The efficiency of the methods was evaluated. The results of the linear correlation between drought indices and cumulative precipitation values during 1 month, 2 months, 3 months, 5 months and 7 months before the acquisition of the image showed that the correlation of indices, especially of the TVDINDVI index with the cumulative rainfall of 4 months, showed that the precipitation is more frequent than with other time scales due to the delayed response of vegetation to rainfall. From 2001 to 2020, it was observed that the severity of annual drought decreased according to TVDI values. The area with heavy drought decreased from 4.45 to 1.8% and medium drought decreased from 43.49 to 33%. Also, the correlation coefficient between other vegetation indices and temperature vegetation drought indices (TVDINDVI) showed that TCI and TVDI values were negatively (r = −0.73) correlated. Generally, by observing the calculated TVDI maps, it was seen that this basin has not encountered heavy drought so far. The results showed that the Urmia Lake Basin experienced long-term light and medium drought conditions. On the other hand, by calculating the NDWI index, changes in the area of Lake Urmia were monitored and it was found that the lake surface started to decrease beginning in 2005 and reached its lowest level in 2015, which corresponds to the other droughts that occurred. Finally, by conducting a trend analysis of TVDI, it was observed that there is no specific trend in the drought time series so it can be seen that drought may be one of the causes of a sharp decline in the lake's water level, but not the only factor. [ABSTRACT FROM AUTHOR]

This paper aims to improve the methodology and results accuracy of MEDALUS model for assessing land degradation sensitivity through the application of different data detail levels and by introducing the application of Ellenberg indices in metrics related to vegetation drought sensitivity assessment. For that purpose, the MEDALUS model was applied at 2 levels of detail. Level I (municipality level) implied the use of available large-scale databases and level II (watershed) contains more detailed information about vegetation used in the calculation of the VQI and MQI factors (Fig. S6). The comparison was made using data based on CORINE Land Cover (2012) and forest inventory data, complemented with object-based classification. Results showed that data based on forest inventory data with the application of Ellenberg's indices and object-based classification have one class more, critical (C1 and C2) and that the percentage distribution of classes is different in both quantitative (area size of class sensitivity) and qualitative (aggregation and dispersion of sensitivity classes). The use of data from Forest Management Plans and the application of Ellenberg's indices affect the quality of the results and find its application in the model, especially if these results are used for monitoring and land area management on fine scales. Remote sensed data images (Sentinel-2B) were introduced into the methodology as a very important environmental monitoring tool and model results validation. [ABSTRACT FROM AUTHOR]

With global climate change and the rapid urbanization, urban flood and drought disasters are frequent and urban water supply systems are facing a sea of serious challenges. It is crucial to assess the resilience of urban water supply systems and develop corresponding disaster mitigation and improvement strategies. Urban water supply systems include many subsystems, but existing researches generally focus on a single subsystem. Therefore, this paper proposes a correlation analysis method and a factor analysis method for the resilience evaluation index system of urban water supply systems by combining each subsystem and applying grey system theory. The method can reflect the four dimensions of the water supply process (water source, water plant, supply and distribution network and users) and the five dimensions of the urban management system (society, natural environment, economy, physics and organization). Taking Qingdao as an example, a multi-level integrated evaluation model based on a cloud model is applied to simulate and analyze the resilience of Qingdao's water supply system. As a result, decision support is provided for planning and building resilience systems for urban water systems in the short and long term, based on four main factors. [ABSTRACT FROM AUTHOR]

Drought has become a dominant climate risk both around the world and in Europe, adding to the already challenging task of farming and governing the agricultural sector under climate change. Drought risk management is extremely complex. Apart from irrigation, most drought risk management options have more than one goal and may potentially have negative trade-offs with other risk management objectives. Moreover, government regulations and market mechanisms influence farmers' decision-making. However, previous studies, both in developed and in developing countries, have predominantly focused on attitudinal and structural influencing factors on farmers' risk management behavior. In this paper, we comprehensively investigate farmers' decision spaces with respect to drought risk management. We address two applied research questions: (1) What are farmers' preferred drought risk management measures? (2) From a farmer's perspective, what are the dominant factors influencing drought risk management decisions? We find that farmers primarily think of production-based rather than financial measures with respect to drought risk management. At the same time, natural and technical constraints and enabling factors dominate their mental decision space, followed by public and private institutional aspects. This research provides a basis for the design of integrated and holistic drought risk management policy and the drought risk governance needed for sustainable use of land and water resources such as needed to address systemic risks and achieve the Sustainable Development Goals. Moreover, we introduce a novel approach using mental models extracted from interviews to explore cognitive representations of farmers' decision spaces. This approach has the potential to complement mainstream research using standardized surveys and behavioral models to analyze drivers of risk management. [ABSTRACT FROM AUTHOR]

Climate change is one of the multiple challenges facing all categories of farmers globally. However, African farmers are the most sensitive in respect of climate variability and change. Climate change impacted negatively on crop production and the livelihoods of the local farmers. In black township South Africa, agricultural activities are highly dominated by small-scale farmers, whose farming system is highly vulnerable to changes in climate. This paper presents the analysis of how small-scale farmers employed adaptation strategies in response to climate change and determinants of small-scale households' choices of coping and adaptation approach to climate variability and change in Vhembe District, South Africa. Multi nominal logit model was used on a surveyed of 224 local farmers. Farmers' socio-economic attributes, was used in response to climate changes and further, households have adaptation strategies both on-farm and off-farm approach. Such approaches were; drought-tolerant seeds, shorter cycle crops, diversification of crops, changing planting dates, small-scale irrigation, migrating to urban areas and involvement in petty business. The results of the findings reveals that the significant drivers affecting choice of adaptation approach include climate information, gender, farm size, education level, farmer experience, decreasing rainfall and increases in temperature as farmers' determinant choices of adaptation to climate change. While, on the other hand, off-farm resources, headed households and age had no significant impact on the choice of coping and adaptation approach to climate change. Therefore, policy makers in the local municipality should play a significant role by enhancing adaptation strategies appropriate for particular climatic shock on the study area. [ABSTRACT FROM AUTHOR]

In the last two decades, recurring drought becomes a challenge for Iran's economy, which is located in a drought-prone area, and it has been expected that drought will become more severe and frequent in the future. In this paper, a computable general equilibrium model was applied to give a full scope of drought economic impacts on Iran's economy. In order to model the effects of droughts as a shock to the economy, water entered into the production function as one of the primary factors. Since drought can lead to health problems, the health sector was separated from the service sector to study the effects of drought events on the health sector. The numerical simulations reveal that drought can lead to lower GDP levels up to 7%. Thus, it can have negative impacts on economic growth. Moreover, other factors such as household savings and income can decrease up to 43% and 12% in drought periods, respectively. These adverse effects will lead to a decline in welfare as a socio-economic consequence of drought. Furthermore, demand for health products will rise around 47%; this can refer to some kinds of diseases followed by droughts. Policies and applicable legislation should be introduced to improve water supply usage and develop efficient methods to save water resources, especially in the agriculture sector, which consumes the most significant part of water. [ABSTRACT FROM AUTHOR]

The complexity and randomness of drought events make its description difficult. Although previous studies have analyzed the characteristics of drought events in different regions, there are few studies to explore the influence of the selection of time intervals on the extraction of drought events. To make up for the deficiency of traditional drought event characteristic analysis, we compared and analyzed the drought event characteristics extracted at different time intervals (1, 5, 10, and all years). Additionally, a new drought event percentage area index was constructed based on the non-divided time method. The Mann–Kendall and Theil-Sen analysis methods were used to investigate its variation trend from 1960 to 2018. The results show that the shorter the time interval, the more significant the change in drought severity, but the more likely it is to separate a drought event, causing accuracy errors. Furthermore, the extraction of drought events with a short time interval tends to underestimate the time change of extreme drought and overestimate the time change of mild drought. Moreover, the non-divided method can more accurately extract the features of drought events. The drought event percentage index can effectively quantify the drought situation in different regions by introducing the spatial dimension's description. The global drought event percentage index rose slightly from 1960 to 2018, with a slope of 0.026% per year. Finally, the drought event characteristic analysis methods adopted in this paper are flexible, effective, and simple, providing possible scientific references for other types of drought research. [ABSTRACT FROM AUTHOR]

In this paper, we investigate space time patterns of meteorological drought events in the Greater Alpine Region (GAR) of Europe. A long-term gridded dataset of monthly precipitation sums spanning the last 210 years is used to assess abnormally dry states using a shortfall below a monthly precipitation percentile threshold. These anomalies are calculated for 1, 3, 6, and 12 monthly moving averages. Contiguous areas of grid points below the threshold are indicating drought areas which are analyzed with respect to their drought severity. The severity is quantified by taking the average deviation from the threshold and the size of the drought area into account. The results indicate that the most severe dry anomalies in the GAR occurred in the 1860s, the 1850s, and the 1940s. However, no significant trends of dry anomaly severity are found over the last 210 years. A spatial clustering analysis of the detected drought areas shows distinct spatial patterns, with the Main Alpine Crest as a frequent divide between dryer areas in the north and wetter areas in the south, or vice versa. The patterns are highly significant and similar for all averaging time scales. The clusters are more clearly defined in winter than in summer. Droughts in the north are most frequent in the second half of the nineteenth century, while in the south and east, they are most frequent in the late twentieth century. [ABSTRACT FROM AUTHOR]

Understanding the causes of rainfall anomalies in the West African Sahel to effectively predict drought events remains a challenge. The physical mechanisms that influence precipitation in this region are complex, uncertain, and imprecise in nature. Fuzzy logic techniques are renowned to be highly efficient in modeling such dynamics. This paper attempts to forecast meteorological drought in Western Niger using fuzzy rule-based modeling techniques. The 3-month scale standardized precipitation index (SPI-3) of four rainfall stations was used as predictand. Monthly data of southern oscillation index (SOI), South Atlantic sea surface temperature (SST), relative humidity (RH), and Atlantic sea level pressure (SLP), sourced from the National Oceanic and Atmosphere Administration (NOAA), were used as predictors. Fuzzy rules and membership functions were generated using fuzzy c-means clustering approach, expert decision, and literature review. For a minimum lead time of 1 month, the model has a coefficient of determination R2 between 0.80 and 0.88, mean square error (MSE) below 0.17, and Nash-Sutcliffe efficiency (NSE) ranging between 0.79 and 0.87. The empirical frequency distributions of the predicted and the observed drought classes are equal at the 99% of confidence level based on two-sample t test. Results also revealed the discrepancy in the influence of SOI and SLP on drought occurrence at the four stations while the effect of SST and RH are space independent, being both significantly correlated (at α < 0.05 level) to the SPI-3. Moreover, the implemented fuzzy model compared to decision tree-based forecast model shows better forecast skills. [ABSTRACT FROM AUTHOR]

The Sahel is prone to climate stressors such as droughts, winds and floods. This study employs a systematic review approach to track the frequency with which these stressors are reported in the scientific peer reviewed literature, examining publishing trends to identify which stressors are most reported, documenting the spatial distribution of these stressors from a country and regional perspective, and assessing the role played by climatic and non-climatic drivers in causing the stressors. A total of (n = 388) reports of stressors were documented in (n = 164) peer reviewed articles. From a country perspective, Southern Niger records the highest number of reports on all three stressors (15.97%), followed by Ethiopia (11.85%) and Senegal (10.56%). Regionally, West African Sahel recorded the highest number of reports on all stressors (49.97%) followed by East African Sahel (29.89%) and Central African Sahel (12.11%) respectively. Droughts are observed to be the most frequently reported stressor (n = 219), followed by floods (n = 123) and winds (n = 46). The decade 1975-1985 recorded the highest reports of stressors (n = 207), while the decade 1997-2007 recorded (n = 80) and the decade 1986-1996 recorded (n = 52). While climatic drivers are dominant (52%), there is however an increasing attribution of the drivers of the stressors to non-climatic drivers (47%). The main weakness of this study is that it uses peer reviewed papers dwelling on climate stressors as a proxy for climate stressors in the Sahel and a lot more studies could be hiding in non-peer reviewed studies, underscoring that this work provides a general and baseline overview of the climate stressors in the region. [ABSTRACT FROM AUTHOR]

The sustainability of large dams has been questioned on several grounds. One aspect that has been less explored is that the development of dams and reservoirs often enables agricultural expansion and urban growth, which in turn increase water consumption. As such, dam development influences, while being influenced by, the spatial and temporal distribution of both supply and demand of water resources. In this paper, we explore the interplay between large dams, patterns of population growth and agricultural expansion in the United States over the past two centuries. Based on a large-scale analysis of spatial and temporal trends, we identify three distinct phases, in which different processes dominated the interplay. Then, we focus on agricultural water use in the Southwest region (Arizona, California and Nevada) and explore chicken-and-egg dynamics where water supply partly meets and partly fuels water demand. Lastly, we show that the legacy of dams in the United States consists of a lock-in condition characterized by high levels of water consumption, especially in the Southwest, which leads to severe water crises and groundwater overexploitation when droughts occur. [ABSTRACT FROM AUTHOR]

This paper used original survey data in Shandong province of China to depict local farmers' perceptions of combined climatic and market risks, and their adaptive behaviors. Two Logit models were developed to capture the empirical relationship between farmers' risk perception of the combined risks and adaptive behaviors. Results show that farmer's risk perception of climate change and market significantly affected their adoption behavior of adaptive measures, including perception of rainfall decrease, gale decrease, drought increase, and price fall of agricultural products. Moreover farmers' adaptive behaviors are more sensitive to their perceptions of extreme climatic events. Addition of demographic factors can improve the explanatory capacity of the Logit model. As illustrated by the models, male and better educated farmers have greater willingness to take actions for averting risks, while household heads with bigger farm are more reluctant. A majority of respondents chose to construct farm structure for irrigation and water conservation to avert climatic risks. Insurance, which is regarded as an effective tool to help farmers mitigate risks and avoid losses, has not been sufficiently accepted by farmers in rural areas in Shandong province. This underscores the need of effective communication of knowledge to enhance farmers' coping capacity and to encourage their active response to risk. [ABSTRACT FROM AUTHOR]

Terrestrial vegetation growth activity plays pivotal roles on regional development, which has attracted wide attention especially in water resources shortage areas. The paper investigated the spatiotemporal change characteristics of vegetation growth activity using satellite-based Vegetation Health Indices (VHIs) including smoothed Normalized Difference Vegetation Index (SMN), smoothed Brightness Temperature (SMT), Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and VHI, based on 7-day composite temporal resolution and 16 km spatial resolution gridded data, and also estimated the drought conditions for the period of 1982–2016 in Jing-Jin-Ji region of China. The Niño 3.4 was used as a substitution of El Niño Southern Oscillation (ENSO) to reveal vegetation sensitivity to ENSO using correlation and wavelet analysis. Results indicated that monthly SMN has increased throughout the year especially during growing season, starts at approximate April and ends at about October. The correlation analysis between SMN and SMT, SMN and precipitation indicated that the vegetation growth was affected by joint effects of temperature and precipitation. The VCI during growing season was positive trends dominated and vice versa for TCI. The relationships between VHIs and drought make it possible to identify and quantify drought intensity, duration and affected area using different ranges of VHIs. Generally, the intensity and affected area of drought had mainly decreased, but the trends varied for different drought intensities, regions and time periods. Large-scale global climate anomalies such as Niño 3.4 exerted obvious impacts on the VHIs. The Niño 3.4 was mainly negatively correlated to VCI and positively correlated to TCI, and the spatial distributions of areas with positive (negative) correlation coefficients were mainly opposite. The linear relationships between Niño 3.4 and VHIs were in accordance with results of nonlinear relationships revealed using wavelet analysis. The results are of great importance to assess the vegetation growth activity, to monitor and quantify drought using satellite-based VHIs in Jing-Jin-Ji region. [ABSTRACT FROM AUTHOR]

Reliable knowledge of the near-future climate change signal of extremes is important for adaptation and mitigation strategies. Especially compound extremes, like heat and drought occurring simultaneously, may have a greater impact on society than their univariate counterparts and have recently become an active field of study. In this paper, we use a 12-member ensemble of high-resolution (7 km) regional climate simulations with the regional climate model COSMO-CLM over central Europe to analyze the climate change signal and its uncertainty for compound heat and drought extremes in summer by two different measures: one describing absolute (i.e., number of exceedances of absolute thresholds like hot days), the other relative (i.e., number of exceedances of time series intrinsic thresholds) compound extreme events. Changes are assessed between a reference period (1971–2000) and a projection period (2021–2050). Our findings show an increase in the number of absolute compound events for the whole investigation area. The change signal of relative extremes is more region-dependent, but there is a strong signal change in the southern and eastern parts of Germany and the neighboring countries. Especially the Czech Republic shows strong change in absolute and relative extreme events. [ABSTRACT FROM AUTHOR]

Various meteorological studies require probabilistic modeling such as the flood, drought, and wet and dry spell occurrences. The most commonly employed approaches are based on the binomial probability distribution function (pdf), which is valid for homogeneous temporal and spatial probabilities. However, in practice, heterogeneous probabilities are very common, and in this case, the classical binomial pdf cannot be employed. This paper presents a rigorous probabilistic methodology for heterogeneous probabilities by considerations from the random field concept. The general form of the binomial pdf is derived and it is shown that for homogeneous probabilities it yields the classical binomial pdf exactly. The necessary analytical formulations are derived with the assumption that the meteorological occurrences at a set of sites or time periods (day, month, and year) are independent from each other. The probability statements derived in this paper are helpful in predicting the regional and temporal probable potential future meteorological occurrences. The application of the proposed methodology is presented for annual precipitation occurrences at six meteorology stations around Istanbul, Turkey. [ABSTRACT FROM AUTHOR]