Drought Hazard Research Articles

Drought risk assessment: The importance of vulnerability factors interdependencies in regional drought risk management

Recognizing the vulnerability factors is essential in assessing the drought risk of a region. Moreover, considering the interactions and interdependencies between the vulnerability factors will generate a more accurate and realistic analysis. The present study tries to depict the interdependencies between vulnerability factors and their covering effect on each other. Kashkan River basin in the west of Iran has hydrological, physical, social, and cultural diversity; hence, one of the main goals of the current research is to evaluate drought risk and detect its affecting factors in each rural district. Twelve vulnerability factors were selected and standardized based on regional risk management. To model interdependencies of vulnerability factors, the integration of the Fuzzy Analytic Network Process (FANP) and Decision-making Trial and Evaluation Laboratory (DEMATEL) method was compared with the Fuzzy Analytic Hierarchical Process (FAHP). The Drought Vulnerability Index (DVI), a weighted aggregation of factors, was multiplied by the Drought Hazard Index (DHI) to obtain a drought risk map. Based on the results, FANP-DEMATEL modifies the risk severity of 20 % of districts. Both methods introduce the western part of the basin with intense risk levels, indicating the irrefutable effect of the hazard index on drought risk maps. The scarcity of hydrological factors can cause profound risk changes in both methods. Furthermore, comparing weighting scenarios revealed that, in some cases, sophisticated weighting methods can be replaced by logical weighting strategies.

Spatio-temporal variation and dynamic risk assessment of drought and flood disaster (DFD) in China

It is important to understand the variations of Drought-Flood-Disaster (DFD) from the past to future for disaster management decision-making under the backdrop of global warming. This study explored the spatio-temporal variations of DFD risks in China from the past (2000–2020) to future (2020–2100) based on the natural and socio-economic datasets. The main findings include: (1) The spatial pattern of disaster vulnerability decreased from 2000 to 2100. The overall vulnerability distribution showed a spatial pattern of high east and low west, and its eastern distribution presented high north and low south. (2) The drought hazard danger degree showed a trend of decreasing first and then increasing with obvious spatial heterogeneity. The flood hazard danger degree had a decreasing spatial distribution from southeast to northwest, with an overall gradually increasing trend. (3) The DFD risks showed a spatial pattern of high east and low west, and were more closely related to disaster vulnerability. Overall, the flood and drought risks had good consistency at the highest level (VI), mainly distributed in the North China Plain, Northeast Plain, eastern Sichuan, and southern Guangdong. This level means that the most severe damage to life and property will occur in these regions. (4) The DFD showed the direction of “north(east)-south(west)”, and the main axis of the ellipse moved north eventually. The DFD hot spots were mainly distributed in North China and the middle and lower reaches of the Yangtze River. The DFD cold spots were mainly distributed in the southwest, Qinghai-Tibet region, and Gansu province.

Indigenous knowledge systems and drought preparedness in rural Umzingwane in Zimbabwe

Indigenous Knowledge Systems (IKS) are an essential survival tool for humans since time immemorial and have always been connected to the management of weather related hazards such as drought. However, the advancement in technology and dominant application of the western version of science in rural Africa continues to masks the significance of IKS resulting in the shrinkage of its use. Against this background, the article examines existing indigenous knowledge and the influence they have on the preparedness of vulnerable groups against drought shocks. Further, the study focuses on the perceptions of rural Umzingwane on the application of indigenous knowledge in predicting and responding to drought shocks in contemporary settings. In this context, the Drought Cycle Management Model anchored theoretical arguments on IKS and drought preparedness. The study gathered data using in-depth interviews purposively targeting spirit mediums, traditional leaders, Agriculture Technical and Extension Workers, District Development Coordinator to gain insights on IKS and its relevance in drought preparedness. The study found that IKS informs early detection of drought and response strategies in rural Umzingwane. In predicting drought hazards, communities rely on observing animal behaviour, fruiting of trees and growth of certain species in certain seasons. The study recommends documentation of IKS and the establishment of platforms to disseminate indigenous knowledge to strengthen capacities of the drought exposed to proactively deal with the hazard.

Epigenetic and Hormonal Modulation in Plant-Plant Growth-Promoting Microorganism Symbiosis for Drought-Resilient Agriculture.

Plant growth-promoting microorganisms (PGPMs) have emerged as valuable allies for enhancing plant growth, health, and productivity across diverse environmental conditions. However, the complex molecular mechanisms governing plant-PGPM symbiosis under the climatic hazard of drought, which is critically challenging global food security, remain largely unknown. This comprehensive review explores the involved molecular interactions that underpin plant-PGPM partnerships during drought stress, thereby offering insights into hormonal regulation and epigenetic modulation. This review explores the challenges and prospects associated with optimizing and deploying PGPMs to promote sustainable agriculture in the face of drought stress. In summary, it offers strategic recommendations to propel research efforts and facilitate the practical implementation of PGPMs, thereby enhancing their efficacy in mitigating drought-detrimental effects in agricultural soils.

Social vulnerability and climate risk assessment for agricultural communities in the United States

Floods and droughts significantly affect agricultural activities and pose a threat to food security by subsequently reducing agricultural production. The impact of flood events is distributed disproportionately among agricultural communities based on their socio-economic fabric. Understanding climate-related hazards is critical for planning mitigation measures to secure vulnerable communities. This study introduces a holistic approach for evaluating the combined risks associated with drought and flood hazards for agricultural communities in the United States. It accomplishes this by merging social vulnerability indicators with data on drought and flood exposure, enabling the identification of the most susceptible agricultural communities. The research seeks to offer valuable insights into the vulnerability of agricultural communities across the United States. It fills a vital research gap by conducting a comprehensive nationwide assessment of social vulnerability, considering expected annual losses related to both flood and drought hazards, and amalgamating social vulnerability with these expected annual losses. The analyses were conducted by adapting datasets and methodologies that are developed by federal institutions such as FEMA, USACE, and USDA. The study identified the 30 most socially vulnerable counties and assessed their exposure to drought and flooding, finding that Mendocino, Sonoma, Humboldt, El Dorado, Fresno, and Kern counties in California had the highest drought exposure and expected annual losses, with Humboldt (CA) and Montgomery (TX) having the highest combined risk. The study estimated over $1 billion in crop damage, with California experiencing the greatest losses, primarily affecting a diverse range of crops, while the Midwest was primarily impacted in terms of major crop types. The findings of this study can serve as supportive information for policymakers to better understand climate risks in agricultural communities and identify where risk mitigation activities should be allocated.

Integrated assessment of flood and drought hazards for current and future climate in a tributary of the Mekong river basin

Abstract Projecting floods and droughts characteristics under climate change is important to formulate an integrative management plan and enhance resiliency of society. However, studies that provide the integration of floods-drought hazards are scarce within literature. This study assessed flood and drought hazards separately and together for future climate in the Mun River basin, a tributary of the Mekong river. A non-modelling and multi-variate approach was used to assess flood and drought hazard respectively. Climate model ensemble suggests that the area under ‘high’ and ‘very high’ drought hazard level will increase from 27% and 4% during baseline period (1981–2010) to 43% and 37%, respectively, during near-future period (2021–2050). Similarly, an increase in ‘high’ and ‘very high’ flood hazard from 11% and 22% during baseline period to 16% and 24% during near-future period is projected. When both hazards are considered together, the total hazard is projected to increase by 155% in the near-future period. 76% of the catchment during the near future period will have combined hazard level from ‘medium’ to ‘very high’ compared to the 30% during the baseline period. The research presents a grim outlook on for the basin, with the area at risk from both hydro-meteorological hazards.

Global drought risk in cities: present and future urban hotspots

Hydrological droughts pose a persistent threat for cities and are increasingly studied. However, this is rarely within a large-scale context, complicating comparisons between cities and potentially hampering the most efficient allocation of resources in terms of drought risk adaptation and mitigation. Here, we investigate global urban hydrological drought risk for 264 urban agglomerations across all continents for both the present time and future projections. To derive risk profiles for each agglomeration, we include components of: drought hazard (drought volume focusing on surface water deficits), exposure (urban population), vulnerability (multivariate vulnerability index), and cost (replacement of freshwater expenses). These components are dynamic in time, except for vulnerability. Most agglomerations are projected to experience an increase in drought hazard, exposure, and cost by 2050, with the most notable current and future hotspot being northern South Asia (India & Pakistan). Also, the number of agglomerations with high risk increases, whereas the number with lower risk decreases, indicating that high urban drought risk is increasing in scale over time. Our results enable a better targeting of those agglomerations that need most urgent attention in terms of drought risk solutions. It can also be used to identify agglomerations with similar drought risk profiles that could be studied in conjunction and may benefit from cooperative drought risk management strategies.

Meteorological and Hydrological Drought Risks under Future Climate and Land-Use-Change Scenarios in the Yellow River Basin

The primary innovation of this study lies in the development of an integrated modeling framework that combines downscaled climate projections, land-use-change simulations, and copula-based risk analysis. This framework allows for the assessment of localized sub-seasonal and seasonal drought hazards under future scenarios. The BCC-CSM1-1 climate model projections from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset are utilized to represent the future climate for 2025–2060 under RCP 4.5 and 8.5 scenarios. The CA-Markov model is employed to predict future land-use-change distributions. The climate–land use–drought modeling nexus enables the generation of refined spatio-temporal projections of meteorological and hydrological drought risks in the Yellow River Basin (YRB) in the future period of 2025–2060. The results highlight the increased vulnerability of the upper YRB to sub-seasonal meteorological droughts, as well as the heightened sub-seasonal hydrological drought risks in the Loess Plateau. Furthermore, downstream areas experience escalated seasonal hydrological drought exposure due to urbanization. By providing actionable insights into localized future drought patterns, this integrated assessment approach advances preparedness and climate adaptation strategies. The findings of the study enhance our understanding of potential changes in this integral system under the combined pressures of global climate change and land use shifts.

Drought Sensitivity of Spring Wheat Cultivars Shapes Rhizosphere Microbial Community Patterns in Response to Drought.

Drought is the most important natural disaster affecting crop growth and development. Crop rhizosphere microorganisms can affect crop growth and development, enhance the effective utilization of nutrients, and resist adversity and hazards. In this paper, six spring wheat varieties were used as research material in the dry farming area of the western foot of the Greater Khingan Mountains, and two kinds of water control treatments were carried out: dry shed rain prevention (DT) and regulated water replenishment (CK). Phenotypic traits, including physiological and biochemical indices, drought resistance gene expression, soil enzyme activity, soil nutrient content, and the responses of potential functional bacteria and fungi under drought stress, were systematically analyzed. The results showed that compared with the control (CK), the leaf wilting, drooping, and yellowing of six spring wheat varieties were enhanced under drought (DT) treatment. The plant height, fresh weight (FW), dry weight (DW), net photosynthetic rate (Pn) and stomatal conductance (Gs), soil total nitrogen (TN), microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), microbial biomass phosphorus (MBP), organic carbon (SOC), and soil alkaline phosphatase (S-ALP) contents were significantly decreased, among which, FW, Gs and MBC decreased by more than 7.84%, 17.43% and 11.31%, respectively. By contrast, the soil total phosphorus (TP), total potassium (TK), and soil catalase (S-CAT) contents were significantly increased (p < 0.05). TaWdreb2 and TaBADHb genes were highly expressed in T.D40, T.L36, and T.L33 and were expressed at low levels in T.N2, T.B12, and T.F5. Among them, the relative expression of the TaWdreb2 gene in T.L36 was significantly increased by 2.683 times compared with CK. Soil TN and TP are the most sensitive to drought stress and can be used as the characteristic values of drought stress. Based on this, a drought-tolerant variety (T.L36) and a drought-sensitive variety (T.B12) were selected to further analyze the changes in rhizosphere microorganisms. Drought treatment and cultivar differences significantly affected the composition of the rhizosphere microbial community. Drought caused a decrease in the complexity of the rhizosphere microbial network, and the structure of bacteria was more complex than that of fungi. The Shannon index and network modular number of bacteria in these varieties (T.L36) increased, with rich small-world network properties. Actinobacteria, Chloroflexi, Firmicutes, Basidiomycota, and Ascomycota were the dominant bacteria under drought treatment. The beneficial bacteria Bacillus, Penicillium, and Blastococcus were enriched in the rhizosphere of T.L36. Brevibacillus and Glycomyce were enriched in the rhizosphere of T.B12. In general, drought can inhibit the growth and development of spring wheat, and spring wheat can resist drought hazards by regulating the expression of drought-related genes, regulating physiological metabolites, and enriching beneficial microorganisms.

Drought risk assessment considering ecosystem resilience: A case study in the Huang-Huai-Hai Plain, China

Drought caused by global warming has a profound impact on the stability of terrestrial ecosystems and agricultural production. As one of the key indicators to measure the response of ecosystems to climate change, the spatial difference of ecosystem resilience will also affect the accuracy of regional drought risk assessment. In this study, the 12-month standardized precipitation evapotranspiration index (SPEI-12) was used to identify drought characteristics and combined with meteorological elements to characterize drought hazard. Drought vulnerability was characterized using crop and environmental sensitivity, disaster prevention, and mitigation capacity. Specifically, ecosystem resilience was also considered in assessing vulnerability. And drought exposure was investigated by considering crop sown area and population density. Based on this, a drought risk assessment framework was constructed using the random forest algorithm and applied to the Huang-Huai-Hai (HHH) Plain, China. The results showed that: (1) approximately 66.34 % of the HHH Plain had a drought hazard level above moderate; among them, southern Hebei, northern Anhui, northern Henan, and scattered small areas in Shandong were extreme high hazard areas. (2) The northeast Anhui, central and southern Shandong, and northeast Jiangsu were extreme high drought vulnerability areas, accounting for 10.34% of the total area. (3) The drought risk in the HHH Plain was low in the south and north, and high in the center. Among these, the drought risk in the border regions of Shandong and Anhui, the northeast part of Jiangsu, as well as central Henan were extreme high, accounting for 11.23%. (4) The drought risk assessment framework constructed by considering ecosystem resilience was more suitable for HHH Plain. This study result could provide scientific reference for managing water resources and preventing drought.

Spatiotemporal characteristics and obstacle factors identification of agricultural drought disaster risk: A case study across Anhui Province, China

Identifying the spatiotemporal characteristics and obstacle factors of the agricultural drought disaster risk is essential to reduce grain losses and ensure food security. However, due to the high uncertainty in drought disaster risk system, there are few effective risk evaluation and diagnosis methods. In this study, the uncertain information contained in sample data was mined and utilized, and a calculation method of the dynamic difference degree coefficients for the five-element connection number was proposed. Then, a quantitative risk evaluation and diagnosis model was established. Furthermore, the spatiotemporal characteristics and key obstacle factors of the agricultural drought disaster risk across Anhui Province, China from 2008 to 2017 were identified. The results indicated that the risk grades of the connection number values of North Anhui, Central Anhui, and South Anhui in 2008 were 0.359 (high risk), 0.072 (medium risk), and 0.097 (medium risk), respectively, and those in 2017 were 0.103 (medium risk), 0.196 (medium risk), and 0.368 (low risk), respectively. Thus, there were salient spatiotemporal characteristics in which the risk decreased from north to south and tended to decrease over time. In addition, the long-term high risk in North Anhui was due to the severe drought hazard, low forest cover, high exposure to drought, and low drought resistance capacity. The worse risk status in Central Anhui was caused by the small precipitation and water resources amount, low relative humidity, and large agricultural population. The factors inhibiting risk reduction in South Anhui were the large paddy field areas, low reservoir regulation and storage, and fewer water-saving irrigation areas. In summary, this method is effective and exhibits high sensitivity to risk change, and it can be applied to other grain production areas. The results can provide a scientific basis for formulating the targeted measures of agricultural drought disaster risk control in Anhui Province.

Comprehensive drought risk assessment using structural equation modeling and objective weighting methods

Study regionGyeongsang province in Korea Study focusDrought is a complex phenomenon influencing the natural, physical, and social sectors depending on the occurrence probability, regional characteristics, and the water supply and demand. To reduce the damage resulting from drought, it is necessary to assess the drought risk that can identify the impacts, causes, and vulnerability of drought. Previous drought risk assessment has usually been conducted by combining drought hazard and vulnerability, but such assessment is of limited value because the regional response capacity for drought is not considered. Moreover, it contains high uncertainty because indicators and weighting factors are determined by subjective methods. In this study, the comprehensive drought risk was assessed including the drought response capacity and with consideration of the regional water supply system. To remove the uncertainty in the drought risk assessment, this study employed partial least squares – structural equation modeling (PLS-SEM) to select effective indicators including the regional drought response capacity, and also applied objective weighting methods such as entropy, principal component analysis (PCA), Gaussian mixture model (GMM), and Bayesian networks to determine optimal weighting factors. New hydrological insights into the region under studyAs a result of application to Gyeongsang province in Korea, PLS-SEM selected 10 indicators for drought risk assessment. Using the selected indicators and the objective weighting methods, this study determined that the drought hazard, vulnerability, response capacity, and risk were highest in GS26 (Ulleung), GS27 (Changwon), GS16 (Cheongsong), and GS28 (Jinju), respectively. The districts with large actual drought damage had high drought risk, indicating that the results of this study were reasonable and useful in the identification of the major impacts and risk of regional drought and may facilitate the decision-making process for selecting drought countermeasures to reduce drought risk.

Evaluation of the revision of spatial planning for flood due to land and climate changes in Soppeng Regency

The follow-up to reviewing the Regional Spatial Planning in Soppeng Regency indicated that the spatial planning could have been better, so an improvement process was carried out. Changes in spatial use and disaster vulnerability are factors in the need to rearrange spatial patterns. The exposure of environmental conditions in Soppeng to hydrometeorological disasters is inseparable from the condition of the area, which is located downstream of several watersheds originating from the surrounding area. Therefore, this study aims to evaluate the revision of the Soppeng spatial pattern for flood events due to land and climate change. This research was conducted based on the ecological boundary conditions of the watershed that affected, where the method used was based on several stages, namely: Land use change analysis using LanduseSim software to project land cover changes, Analysis of climate change using Sibias software to project rainfall and temperature conditions according to the projected period for regional planning, Analysis of flood discharge and drought hazard is processed using the SWAT and Hec-Ras models. Based on the research, it was obtained that the occurrence of floods in the study area occurred in several places with a percentage of 24% of the total area, respectively. After analyzing a revision of the existing spatial pattern, several directions for cultivation areas have a high level of disaster vulnerability. The directions for the affected areas include agricultural and other development areas, such as residential areas. So based on the results of this study, consideration is needed for areas with high flood vulnerability because disaster-related considerations need to be considered in changes to the spatial layout of the Soppeng area.

POTENSI RAINWATER HARVESTING DALAM MENGURANGI RISIKO KEKERINGAN DI KABUPATEN KARAWANG

&lt;p class="Abstract"&gt;&lt;em&gt;&lt;span lang="EN-US"&gt;Drought occurs quite often in Indonesia, closely related to water availability for community needs. One of the districts in West Java Province experiencing drought problems is Karawang district, where the RWH (Rainwater Harvesting) concept will be applied. This study aimed to analyze the risk of drought-related to applying the potential RWH in reducing drought risk. This study only focuses on meteorological drought, determined by SPI (Standardized Precipitation Index). Identification of potential areas for the application of RWH is carried out using the Weighted Method Overlay approach in the Geographic Information System (GIS), which was modified by adding a parameter of potential drought hazard. The potential reliability of RWH, as seen from Volumetric Reliability (VR) for supplying the average water requirement of MCK (Bath Washing Toilet) per year, indicates that most of the Karawang district area is potential for applying RWH. The results of adding the potential drought hazard parameters on applying the RWH concept show the decreasing area of very potential and potential category areas into 5,38%, the increase of drought resistance capacity is 17.5%, and the risk-reducing to 8.3%. Those results are due to the changes in the area of drought in the risk analysis. The assumptions of 60 rainy days on the average rainy day in a year and all households making RWH storage systems were used in the analysis. The results of this study can be used as a first step to see the potential of RWH in Karawang Regency both in terms of area and reliability.&lt;/span&gt;&lt;/em&gt;&lt;/p&gt;

Long-chain propagation pathways from meteorological to hydrological, agricultural and groundwater drought and their dynamics in China

Drought propagation is a complex process involving various components of water cycle. Clarifying the propagation pathways and mechanisms among multiple types of droughts is essential. However, the current drought propagation analysis mainly focuses on the relationship between two types of droughts, which highlights the urgence in studying the propagation among multiple types of droughts. To this end, this study will first develop a dynamic threshold framework to identify the propagation pathways among meteorological, hydrological, agricultural and groundwater droughts, and further investigate the risk probability, trigger threshold and their controlling factors in the long-chain drought propagation. The propagation pathways among multi-type droughts were identified as meteorological-hydrological-agricultural-groundwater drought. In the long-chain drought propagation, the spatial heterogeneity of risk probability and trigger threshold in China is significant. Among them, the risk probability triggering the next stage decreases progressively in south China, and the drought propagation is blocked. A significant upward trend exhibited in the trigger thresholds in east China, indicating that drought resistance is weakening. Temperature, aridity index and soil evaporation flux are the main drivers affecting the dynamics of trigger thresholds. This study contributes to the completeness and systematization of the propagation process of drought in the water cycle. It not only offers new insights into the process of drought propagation, but also provides scientific guidance for establishing drought early warning systems and reducing drought hazards.

Drought: Profile Assessment, Impact Analysis and Coping Strategies to Combat Drought in Naogaon District of Bangladesh

This article tends to analyse the drought scenario of the Naogaon district in Bangladesh through groundwater potential zone modelling. The study’s findings illustrate that the maximum area covers a moderately potential groundwater zone. The study data also portrays various threats, including food insecurity and economic, social and environmental risks that were noticed as a consequence of the severe drought. The findings from the data indicate that the Porsha and Sapahar upazillas (sub-districts) of Naogaon district are more vulnerable zones in terms of drought. It is noteworthy that the people have been using indigenous knowledge to combat drought hazards. Local people are using crop calendars, agronomic management, water harvesting practices for less water-consuming crops and changes in occupation to manage the risks of drought in the study region.

Spatially Consistent Drought Hazard Modeling Approach Applied to West Africa

A critical stage in drought risk assessment is the measurement of drought hazard, the probability of occurrence of a potentially damaging event. The standard approach to assess drought hazard is based on the standardized precipitation index (SPI) and a drought intensity classification established according to a fixed set of SPI values. We show that this method does not allow for the assessment of region-specific hazards, and we propose an alternative method based on the extreme value theory. We model precipitation using an extreme value mixture model, with a normal distribution for the bulk, and a generalized Pareto distribution for the upper and lower tails. The model estimation allows us to identify the threshold value below which precipitation can be qualified as extreme. The quantile function is used to measure the intensity of each category of droughts and calculate the drought hazard index (DHI). By construction, the DHI value varies according to the specific characteristics of the left tail of the precipitation distribution. To test the relevance of our approach, we estimate the DHI over a gridded set of rainfall data covering West Africa, a large and climatically heterogeneous region. The results show that our mixture model fits the data better than the model used for SPI calculation. In particular, our model performs better to identify extreme precipitation in the left tail of the distribution. The DHI map highlights clusters of high drought hazard located in the central part of the region under study.

Improvements and Evaluation of the Agro-Hydrologic VegET Model for Large-Area Water Budget Analysis and Drought Monitoring

We enhanced the agro-hydrologic VegET model to include snow accumulation and melt processes and the separation of runoff into surface runoff and deep drainage. Driven by global weather datasets and parameterized by land surface phenology (LSP), the enhanced VegET model was implemented in the cloud to simulate daily soil moisture (SM), actual evapotranspiration (ETa), and runoff (R) for the conterminous United States (CONUS) and the Greater Horn of Africa (GHA). Evaluation of the VegET model with independent data showed satisfactory performance, capturing the temporal variability of SM (Pearson correlation r: 0.22–0.97), snowpack (r: 0.86–0.88), ETa (r: 0.41–0.97), and spatial variability of R (r: 0.81–0.90). Absolute magnitudes showed some biases, indicating the need of calibrating the model for water budget analysis. The seasonal Landscape Water Requirement Satisfaction Index (L-WRSI) for CONUS and GHA showed realistic depictions of drought hazard extent and severity, indicating the usefulness of the L-WRSI for the convergence of an evidence toolkit used by the Famine Early Warning System Network to monitor potential food insecurity conditions in different parts of the world. Using projected weather datasets and landcover-based LSP, the VegET model can be used not only for global monitoring of drought conditions, but also for evaluating scenarios on the effect of a changing climate and land cover on agriculture and water resources.

Evaluating Hydrological Drought Risk in Lithuania

Hydrological drought poses a major global challenge, exacerbated by climate change and increasing water demand, leading to water scarcity, environmental degradation, and socioeconomic impacts. Thereby, there is a need for comprehensive methods to assess and predict hydrological droughts. The methodology part was based on the calculation of hydrological drought risk components—hazard and vulnerability—according to the equal weight scale of each variable. The spatial distribution of point values was performed by the inverse distance weighting interpolation method. To calculate indices, the spatial layer overlapping of variables was performed using the Raster Calculator tool. Statistical tools were used to estimate drought risk in river catchments. As a result, three main maps were prepared: The hydrological drought hazard index, the hydrological drought vulnerability index, and the hydrological drought risk. These maps highlight regional variations in drought hazards, vulnerability, and risk. Hazard and risk index values are higher in the northern part of Lithuania and lower in the south. The central region exhibits the highest percentage of areas at high and very high risk; the western region shows less risk due to a maritime climate; and the Southeastern region demonstrates the lowest susceptibility to hydrological drought due to physical-geographical factors.

Historical rainfall data in northern Italy predict larger meteorological drought hazard than climate projections

Abstract. Simulations of daily rainfall for the region of Bologna produced by 13 climate models for the period 1850–2100 are compared with the historical series of daily rainfall observed in Bologna for the period 1850–2014 and analysed to assess meteorological drought changes up to 2100. In particular, we focus on monthly and annual rainfall data, seasonality, and drought events to derive information on the future development of critical events for water resource availability. The results show that historical data analysis under the assumption of stationarity provides more precautionary predictions for long-term meteorological droughts with respect to climate model simulations, thereby outlining that information integration is key to obtaining technical indications.