Explore the vast range of titles available.

Climate variability poses a significant threat to smallholder farmers in the Gwayi catchment, Zimbabwe. This study investigated the spatiotemporal dynamics of agrometeorological droughts from 1990 to 2020 using the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Vegetation Condition Index (VCI), and Vegetation Health Index (VHI). The triangulation of these indices provided a comprehensive understanding of drought dynamics. Severe to extreme drought events were identified in 1995, 1998, 2005, 2016, 2018, and 2020, while moderate droughts were consistently detected across all indices. Favourable conditions were observed in 2000 and 2006. A strong positive correlation (r = 0.88) between VHI and VCI suggests their similar effectiveness in reflecting vegetation health. In contrast, moderate correlations between VHI and SPI (r = 0.30), VHI and SPEI (r = 0.39), VCI and SPI (r = 0.28), and VCI and SPEI (r = 0.40) indicate that these indices capture complementary information, reflecting not only precipitation deficits but also the impacts of temperature, soil moisture, and land cover changes. The SPI and SPEI displayed a strong positive correlation (r = 0.78), aligning in their sensitivity to precipitation and evapotranspiration. Spatial analysis revealed a pronounced north-south drought gradient, with the southwestern region being particularly vulnerable, underscoring the need for targeted interventions.

Early detection of agricultural drought can alert farmers and authorities, enhancing the resilience of the food sector. A framework is proposed for developing a novel regional agricultural drought index (RegCDI) by combining remotely sensed vegetation health, soil moisture and crop water stress via a transparent Shannon’s entropy weighting method. The framework consists of the selection of suitable datasets based on their regional performance, the aggregation of selected drought indicators, the validation of the combined index against crop yield, and the testing of predictive capabilities. The creation and performance of RegCDI are demonstrated for the drought prone Indian state of Odisha. MODIS surface reflectance is selected for crop water stress and GLDAS-2 for assessing soil moisture deficits and vegetation health. Three selected indicators (SMCI, TCI, and SIWSI-1) are combined into RegCDI for Odisha. The performance of RegCDI is evaluated (a) against other popular drought indices and (b) by comparing with seasonal crop yields. RegCDI is used to identify drought hotspots based on drought severity, duration, and propensity over the study area. A reforecast evaluation of RegCDI (up to three months ahead) showed that the indicators based on soil moisture deficit and crop water stress could predict drought conditions up to two months ahead with no less than 80% accuracy. This demonstrated the potential of the RegCDI framework and its component indicators for early warning of drought in Odisha.

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.

The impacts of climate change are globally evident and cause significant damage to ecosystems and human activities. These impacts intensify social and economic inequality in Southern Africa (SA), where agriculture is vital for livelihoods and economic development. This study aimed to assess long-term trends in climate elements and parameters relevant to drought regimes in SA to identify drought hotspots and relate them to socioeconomic indicators. The methods include the Theil–Sen slope estimator and the Mann–Kendall statistical significance test. The study analysed ERA5 data for the 1971–2020 to compute the Standardised Precipitation Index (SPI) and Standardised Precipitation Evapotranspiration Index (SPEI) drought indices and descriptors. Results of the trend analysis reveal (i) the existence in almost the entire SA of statistically significant trends of increasing temperature and potential evapotranspiration and decreasing precipitation; (ii) increasing drought risk hotspots in the SPI and SPEI across all timescales, in the north central rainforest region, south and southeast of SA, while decreasing in the northwest coast, central west region, and in the northeast more recently; and (iii) hotspots in the drought descriptors within the same regions, but of a smaller size. Our findings pinpoint drought hotspots in regions with moderate-to-high population density and agricultural systems that involve species vital for food security and of considerable socioeconomic and commercial importance, emphasising the significance of our results for managers and decision-makers.

Global warming likely will intensify drought in groundwater and river flow (hydrological drought) in many regions across the globe. This chapter starts with an overview of hydrological drought assessments over time. It shows that the hydroclimatological community moved from single model to multi‐model ensembles to account for the uncertainty in model simulations. The likely most‐affected regions (hotspots) ‐ e.g. the Mediterranean ‐ are described based on studies using different emission scenarios, model ensembles and characteristics to portray hydrological drought (frequency, duration, severity). The impact of humans (reservoirs, water use), either alleviating or enhancing the drought, can have a substantial impact, which urges scientists to include this influence more comprehensively in future drought studies. Several approaches have been used to explore uncertainty in the assessment of future drought, either based on model outcome or on comparisons with observations. Uncertainty assessments are hard to compare and should be brought together in integrated conceptual frameworks.

Drought-related risk is among the major global challenges of our time. It negatively impacts food security and ecosystem health. It is becoming a persistent problem in many parts of sub-Saharan Africa and specifically in Ethiopia. Information on its intensity and spatiotemporal distribution is critical to contextualize interventions and build agroecosystem and community resilience. This study aims at analyzing spatiotemporal characteristics of meteorological drought over eight Agroecological Zones (AEZs) of the Awash Basin, Ethiopia. Annual gridded temperature and precipitation dataset obtained from the National Meteorological Agency of Ethiopia for the period 1983–2016, covering 1655 grid points, were used. The study applied the Standard Precipitation and Evapotranspiration Index (SPEI) and Standard Precipitation Index (SPI) methods to characterize the meteorological droughts. The study applied Arc GIS 10.5 to map the drought hotspots. From the result, the value of SPEI and SPI methods was divergent in characterizing the magnitude and spatial occurrence of drought episodes. SPEI has more advantages in detecting dry months and a small advantage in detecting dry seasons compared to the SPI. Temporally, wet and dry years dominated the 1990s and 2010s, respectively. Drought dominated 1980s and normal years dominated the 2000s. The spatial context of drought hotspot showed that AEZs in the upper and lower parts of the Awash Basin were hit by severe to extreme drought while the escarpments and middle parts of the basin experienced mild to moderate drought. This contrasts with the common perception that the hot to warm arid lowlands AEZs are the only hotspot areas to drought. Moreover, previously none frequent drought AEZs, such as tepid to cool humid mid-highlands were identified as drought hotspots in the basin. This information could help policymakers to target AEZs and implement context-specific and informed drought risk management decisions and adaptation measures.

Many regions globally are grappling with the challenge of recurrent extreme weather events. Whereas attempts are being undertaken to understand their characteristics as a first step to guide targeted mitigation measures, these are focused on dryness and not wetness, which is also a challenge in sub‐humid areas. This study investigates dryness and wetness characteristics using the standardized precipitation evaporation index (SPEI) at timescales of 3, 6, 12 and 24 months for a period of 1901–2018 across Uganda's drainage basins. Trends in the dryness and wetness evolutions were conducted using the Mann‐Kendall (MK) statistic to establish the effects of global warming on the study area. A step change analysis reveals 1961 as a change point year from cool to warm periods. Results also reveal that warming mainly occurred in the recent period (1962–2018), with a temperature rise of over 2οC being recorded in 2009. Severe dryness events occurred in the recent period as opposed to wetness events that dominated the earlier period (1901–1961). Dryness and wetness varied among drainage basins, with the Aswa basin being more susceptible to severe dryness while the Lake Kyoga basin to severe wetness. Lira and Kitgum were identified as drought hotspots at timescales of 3, 6 and 12 months. SPEI was able to reveal 60% of historical dryness events and 75% of wetness events on record, making it an adequate tool for monitoring humid events as opposed to droughts in sub‐humid climates. It is hoped that this evidence can guide targeted mitigation measures towards climatic shocks within the region. Step change analysis revealed 1961 as the year of significant change at p < 0.01 and already warming of above 2°C is already being experienced in Uganda. The northern region is the most susceptible to severe dryness in the recent period, while severe wetness was mostly experienced in the 1901–1961 period across the entire study area.

Droughts are complex natural phenomena with multifaceted impacts, and a thorough drought impact assessment should entail a suite of adequate modelling tools and also include observational data, thus hindering the feasibility of such studies at large scales. In this work we present a methodology that tackles this obstacle by narrowing down the study area to a smaller subset of potential drought hot-spots (i.e., areas where drought conditions are expected to be exacerbated, based on future climate projections). We achieve this by exploring a novel interpretation of a well-established meteorological drought index that we link to the hydrological drought status of a catchment by calibrating its use on the basis of streamflow observational data. We exemplify this methodology over 25 sub-catchments pertaining to the Adige catchment. At the regional level, our findings highlight how the response to meteorological drought in Alpine catchments is complex and influenced by both the hydrological properties of each catchment and the presence of water storage infrastructures. The proposed methodology provides an interpretation of the hydrologic behavior of the analyzed sub-catchments in line with other studies, suggesting that it can serve as a reliable tool for identifying potential drought hot-spots in large river basins.

Across Africa, drought seldom occurs alone. Rainfall deficits often coincide with heat, rapid soil moisture loss and reduced streamflow, producing compound events whose impacts exceed those of any single driver. This review synthesises station observations, satellite and reanalysis products, and climate model simulations to clarify where such events are most common, how they form, how they affect societies and ecosystems, and how risks are changing. A practical tiered definition tailored to African conditions is outlined and applied to identify five recurrent hotspots: the Sahel, the Greater Horn of Africa, southern Africa, the margins of the Congo Basin and the Guinea Coast. The review sets out a physically consistent sequence that links basin-scale sea surface temperature anomalies to shifts in monsoon circulation, and then to land processes that amplify and prolong heat and dryness through reduced evapotranspiration and soil-moisture memory. Documented impacts include lower crop and pasture productivity, pressure on rivers, reservoirs and groundwater, stress on hydropower and wider consequences for food and energy security. Compound drought frequency across these hotspots has risen by 18–55% since 1980, with the probability of the most severe events roughly doubling at 1.5 °C of global warming and tripling at 3 °C. The review highlights near-term priorities, including compound-aware monitoring, sub-seasonal-to-seasonal early warning and conjunctive water management.

Understanding the genetic bases of economically important traits is fundamentally important in enhancing genetic gains in durum wheat. In this study, a durum panel of 208 lines (comprised of elite materials and exotics from the International Maize and Wheat Improvement Center gene bank) were subjected to genome wide association study (GWAS) using 6,211 DArTseq single nucleotide polymorphisms (SNPs). The panel was phenotyped under yield potential (YP), drought stress (DT), and heat stress (HT) conditions for 2 years. Mean yield of the panel was reduced by 72% (to 1.64 t/ha) under HT and by 60% (to 2.33 t/ha) under DT, compared to YP (5.79 t/ha). Whereas, the mean yield of the panel under HT was 30% less than under DT. GWAS identified the largest number of significant marker-trait associations on chromosomes 2A and 2B with -values 10 to 10 and the markers from the whole study explained 7-25% variation in the traits. Common markers were identified for stress tolerance indices: stress susceptibility index, stress tolerance, and stress tolerance index estimated for the traits under DT (82 cM on 2B) and HT (68 and 83 cM on 3B; 25 cM on 7A). GWAS of irrigated (YP and HT combined), stressed (DT and HT combined), combined analysis of three environments (YP + DT + HT), and its comparison with trait and stress indices identified QTL hotspots on chromosomes 2A (54-70 cM) and 2B (75-82 cM). This study enhances our knowledge about the molecular markers associated with grain yield and its components under different stress conditions. It identifies several marker-trait associations for further exploration and validation for marker-assisted breeding.