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Drought has a paramount impact on global agriculture and food security. However, the study on future cropland areas that can incur drought is inadequate. This paper uses input parameters from 7 CMIP6 models for 7 future scenarios (SSP1‐1.9, SSP1‐2.6, SSP4‐3.4, SSP2‐4.5, SSP4‐6.0, SSP3‐7.0, and SSP5‐8.5) to measure South Asian cropland exposure to drought and its underlying factors. Some defined epochs such as 2021–2040 (near‐term), 2041–2060 (mid‐term), 2081–2100 (long‐term), and 1995–2014 (reference period) are designed to explore diverse outlooks of the change. The Standardized Precipitation Evapotranspiration Index and the Run theory methods are applied to detect drought. Results indicate an intensified cropland (under SSP4‐3.4, SSP3‐7.0, and SSP5‐8.5) in the Indo‐Gangetic Plain region of South Asia, where mostly the variation occurs among scenarios and periods. Notably, the future cropland exposed to drought will increase in the 2021–2040, and 2041–2060 periods, but it intends to decline during the 2081–2100. Relatively, the exposed cropland will upturn highest by 49.2% (SSP3‐7.0) in the mid‐term period and decrease by −8.2% (SSP5‐8.5) in the end future. Spatially, distributed cropland in the central, south‐west, and portion of the northeast of South Asia are subjective to be exposed largely, but it can drop greatly across the eastern part by the end future. Importantly, the climate change effect plays a grounding role in future exposure change over the region during the near to mid‐term periods, while the cropland change effect is predominant in the long‐term perspectives. However, these findings signify the urgency of policymaking focusing on drought mitigation to ensure food security. Plain Language Summary: Estimating drought‐induced cropland exposure is the pivotal aspect of agricultural risk assessment for drought impacts. The purposes of this study are to explore (a) how much of the cropland area would be exposed to drought under SSP scenarios; and (b) the degree to which climate change and cropland change effects contribute to changes in exposure. In this regard, we conducted a multi‐model and multi‐scenario‐based analysis to reveal variations in the cropland area exposed to drought in South Asia. Among the seven scenario combinations, the highest percentage of cropland exposed to drought was found at 49.2% (SSP3‐7.0) in the mid‐term epoch (2041–2060). The climate change effect seems to be the key contributor in the near‐term to mid‐term period, whereas it is the cropland change effect long‐term. To reduce drought risk, we recommend focusing on strong climate change mitigation policy development in the near‐ and mid‐term periods at a global scale and strict land‐use management policy interventions in the long‐term period at the regional level. Key Points: Larger cropland area will experience drought in the 2040–2060 period, while it will decline by the end of 21st centuryThe exposed cropland will increase by 49.2% under SSP3‐7.0 than that of historical timeThe climate change effect is the pivotal contributor in exposure changes over South Asia [ABSTRACT FROM AUTHOR]

The demand for woody biomass as a key raw material of the developing circular bioeconomy is expected to increase. This has led to the need of increased timber productivity and the search for new procurement methods, new assortments, and innovative supply chains. Timber is regarded as a climate-friendly resource, which can contribute to climate change mitigation through long-term carbon storage and through the substitution of fossil products and fossil fuels. Thus, it is of high importance to assess the amount of timber that can be harvested without compromising sustainability concerns. In this paper, we examined the amount of the wood stock accumulated in overmature stands in Hungary. We define overmature stands being those stands where the actual age of the stand is over its cutting age prescribed by the forest authority. According to our results, 11.5% of the standing volume in Hungary is overmature, and the wood stock of overmature stands has increased by more than 250% in the last 40 years. The importance of the overmature forests is enormous, as they represent an unused wood stock reserve, which could be available to meet the growing demand for timber. In our study, we also conducted a simple yield table-based projection on the maximum amount of timber available for harvest in the period 2020–2100 based on the data of the national forestry database and the cutting ages prescribed by the forest authority in the forest management plans. According to our results, even without new afforestation, more timber becomes available for harvest annually in the 2020–2100 period than the level of the average harvests of the last five historic years. In the 2020–2050 period, an additional 56% of timber is projected to become available for harvest as a maximum. This means a maximum additional potential of 4059 thousand m3, even without the harvesting of the stands, which were already overmature in the starting year of the projection. In the first part of the projection period, industrial wood available for harvest is forecasted to be above the average historic level of industrial wood production. However, in the second part of the projection period, the industrial wood yield shows a decreasing tendency and even drops below the 2017–2021 average. The decreasing availability of industrial roundwood in the second part of the projection period points out the importance of innovation in the wood industry. The inclusion of drought tolerant species, which are nowadays less used for industrial purposes seems inevitable in the production of high-quality wood products. [ABSTRACT FROM AUTHOR]

The influences of human activity on regional climate over China have been widely reported and drawn great attention from both the scientific community and governments. This paper reviews the evidence of the anthropogenic influence on regional climate over China from the perspectives of surface air temperature (SAT), precipitation, droughts, and surface wind speed, based on studies published since 2018. The reviewed evidence indicates that human activities, including greenhouse gas and anthropogenic aerosol emissions, land use and cover change, urbanization, and anthropogenic heat release, have contributed to changes in the SAT trend and the likelihood of regional record-breaking extreme high/low temperature events over China. The anthropogenically forced SAT signal can be detected back to the 1870s in the southeastern Tibetan Plateau region. Although the anthropogenic signal of summer precipitation over China is detectable and anthropogenic forcing has contributed to an increased likelihood of regional record-breaking heavy/low precipitation events, the anthropogenic precipitation signal over China is relatively obscure. Moreover, human activities have also contributed to a decline in surface wind speed, weakening of monsoon precipitation, and an increase in the frequency of droughts and compound extreme climate/weather events over China in recent decades. This review can serve as a reference both for further understanding the causes of regional climate changes over China and for sound decision-making on regional climate mitigation and adaptation. Additionally, a few key or challenging scientific issues associated with the human influence on regional climate changes are discussed in the context of future research. [ABSTRACT FROM AUTHOR]

Afforestation is important for the EU forest management strategy. Afforestation of abandoned and marginal arable land is a favourable non-agricultural land use option for climate change mitigation. It may prevent threats of drought or erosion e.g. by affecting the water balance in soil via increased structural stability. The structural stability control in afforested soil is related to i.a. organic matter content, nutrient content, soil reaction, planted tree species prosperity, and amelioration. A four-year field small-plot experiment on afforestation was carried out with Chernozem covered with deciduous (oak), coniferous (pine) or mixed planting, amended with 3 doses (no-application, 0.5 kg.m-2, and 1.5 kg.m-2) of alginite. In 2013 and 2016, soil reaction pHH2O, mean weight diameter (MWD), organic matter content (LOI) and total organic carbon (TOC) were determined and related to the soil structural stability to evaluate the soil precondition to sustain drought twice per vegetation period (spring and autumn). Afforestation significantly improved MWD compared to the field soil between 2013 and 2016 from 1.63 ± 0.04 mm to 1.85 ± 0.05 mm. Tree planting significantly neutralized the soil pHH2O, mixed planting appeared to improve LOI and TOC. Four-year afforestation led also to higher structural stability, less alkaline pH and deciduous tree-related increase in LOI, which may indicate better soil sustainability to drought. [ABSTRACT FROM AUTHOR]

Today, city planners design urban futures by considering environmental degradation and climate mitigation. Here, we studied the greenhouse gas fluxes of urban lawns and meadows and linked the observations with plant functional types and soil properties. In eight lawns and eight meadows in the Helsinki metropolitan area, Finland, carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) fluxes were measured using manual chambers, and plant functional types were recorded. Four of these sites, i.e. an irrigated lawn, an old mesic meadow, a non-irrigated lawn and a young dry meadow, were more intensively studied in 2021–2022. The process-based ecosystem model JSBACH was utilized together with the momentary observations collected approximately every second week on CO2 exchange to quantify the annual carbon (C) balance of these sites. On the remaining sites, we studied the initial dynamics of conversion from lawns to meadows by transforming parts of lawns to meadows in late 2020 and conducting measurements from 2020 to 2022. The mean photosynthetic production (GPP) of the irrigated lawn and mesic meadow was the highest in this study, whereas the dry meadow had the lowest GPP. The studied lawns were stronger C sinks compared to the meadows. However, the net exchange values were uncertain as the soils were not in equilibrium with the vegetation at all sites, which is common for urban habitats, and modelling the heterotrophic emissions was therefore challenging. The conversion from a lawn to a meadow did not affect the fluxes of CH4 and N2O. Moreover, the mesic meadow was more resistant to drought events than the non-irrigated lawn. Lastly, the proportion of herbaceous flowering plants other than grasses was higher in meadows than in lawns. Even though social and economic aspects also steer urban development, these results can guide planning when considering environmentally friendlier green spaces and carbon smartness. [ABSTRACT FROM AUTHOR]

The interaction between forest and climate exhibits regional differences due to a variety of biophysical mechanisms. Observational and modeling studies have investigated the impacts of forested and non-forested areas on a single climate variable, but the influences of forest cover change on a combination of temperature and precipitation (e.g., drought) have not been explored, owing to the complex relationship between drought conditions and forests. In this study, we use historical forest and climate datasets to explore the relationship between forest cover fraction and drought from 1992–2018. A set of linear models and an analysis of variance approach are utilized to investigate the effect of forest cover change, precipitation and temperature on droughts across different timescales and climate zones. Our findings reveal that precipitation is the dominant factor (among the three factors) leading to drought in the equatorial, temperate and snow regions, while temperature controls drought in the arid region. The impact of forest cover changes on droughts varies under different precipitation and temperature quantiles. Precipitation modulates forest cover's impact on long-term drought in the arid region, while temperature modulates the impact of forest cover changes on both short- and long-term drought in the arid region as well as only on long-term drought in the temperate region. Forest cover can also modulate the impacts of precipitation and temperature on drought. High forest cover leads to a combined effect of precipitation and temperature on long-term drought in arid and snow regions, while precipitation is the only dominant factor in low forest cover conditions. In contrast, low forest cover triggers a strong combined effect of precipitation and temperature on drought in the temperate region. Our findings improve the understanding of the interaction between land cover change and the climate system and further assist decision-makers to modulate land management strategies in different regions in light of climate change mitigation and adaptation. [ABSTRACT FROM AUTHOR]

Ocean-onto-land droughts (OTLDs)—i.e., droughts originating over the oceans and migrating onto land—are a recently identified phenomenon with severe natural and human impacts. However, the influence of anthropogenic emissions on past and future changes in OTLDs and their underlying mechanisms remain unclear. Here, using precipitation-minus-evaporation deficits to identify global OTLDs, we find OTLDs have intensified due to anthropogenic climate change during the past 60 years. Under a future high-emissions scenario, the OTLDs would become more frequent (+39.68%), persistent (+54.25%), widespread (+448.92%), and severe (+612.78%) globally. Intensified OTLDs are associated with reduced moisture transport driven by subtropical anticyclones in the northern hemisphere and complex circulation patterns in the southern hemisphere. The reduction in moisture transport during OTLDs is mainly caused by the atmospheric thermodynamic responses to human-induced global warming. Our results underscore the importance of improving understanding of this type of drought and adopting climate mitigation measures. [ABSTRACT FROM AUTHOR]

Highlights • Few empirical studies investigate the role of forests in agricultural adaptation to climate change. • Whether the presence of forest cover near rice-producing villages can reduce the adverse effects of drought on rice yield is examined. • Natural forests and not planted forests near villages provide protection for rice against drought. • Forest cover enhances the availability of irrigation water in the form of protective role against drought. • Forest ecosystem-based adaptation (EBA) is relevant in coping with climate change and enhancing food security. Abstract Although the importance of forests in climate change mitigation has been widely recognized, there has been a lack of empirical research regarding the role of forests in agricultural adaptation to climate change. This paper uses a careful designed household survey in South China that considers an exogenous shock of drought, to determine whether the presence of natural and planted forests near rice-producing villages can reduce the adverse effects of drought on rice yield. After controlling for local climate and water infrastructure, we find robust evidence that natural forests and not planted forests have significant positive effects on rice yield, due to their influence on the availability of water for irrigation. Although drought hinders farmers' access to irrigation, which negatively affects rice yield, forests near villages provide protection for rice against drought. These findings support the adoption of forest ecosystem-based adaptation (EBA) to cope with climate change and enhance food security. [ABSTRACT FROM AUTHOR]

Highlights • Institutional research method; adaptive governance; policy instruments responding to climate change and drought. • Policy instruments that deliver co-benefits build livelihood capitals. • Redesign of policy instruments is best addressed with participation. Abstract Situate within new institutionalism literature, this paper builds a complex system model of institutional analysis for adaptive governance. This model combines Young's institutional environmental analysis method (2005), elements of subsequent environmental governance projects models, and ideas of multiple institutional levels and drivers. By applying the model, policy instruments are identified that build agricultural producer livelihoods improving their adaptive capacity to respond to climate change and drought. In relation to three case studies in Canada, Chile, and Argentina, policy instruments that deliver co benefits to improve agricultural producer technological, social, human, economic, and natural capital include crop insurance, income stabilization instruments, farm water infrastructure grants, environmental farm planning (improving soil management), drought predictions and alerts, and watershed management plans. Missing instruments included international instruments of mitigation and adaptation through disaster risk reduction, climate change mitigation instruments, and involvement of people in review and assessment of instruments in the context of climate change (iterative anticipatory governance). The model allows for instrument redesign through interdisciplinary interaction with the agricultural and policy community, reviewing climate change scenarios, identifying missing and weak instruments and dimensions of adaptive governance. [ABSTRACT FROM AUTHOR]

The impacts of hot, dry, and compound hot‐dry extremes are significant for societies, economies, and ecosystems worldwide. Such events therefore need to be assessed in the light of anthropogenic climate change so that suitable adaptation measures can be implemented by governments and stakeholders. Here we show a comprehensive analysis of hot, dry, and compound hot‐dry extremes over global land regions using 25 Coupled Model Intercomparison Project Phase 6 models and four future emissions scenarios from 1950 to 2100. Hot, dry, and compound hot‐dry extremes are projected to increase over large parts of the globe by the end of the 21st century. Hot and compound hot‐dry extremes show the most widespread increases and dry extreme changes are sensitive to the index used. Many regional changes depend on the strength of greenhouse‐gas forcing, which highlights the potential to limit the changes with strong mitigation efforts. Plain Language Summary: Heatwaves, drought and their joint occurrences can negatively impact populations, economies, and natural systems worldwide. It is therefore of paramount importance that governments and stakeholders assess the risk from such events and adapt accordingly. In this study we use 25 climate models and four emission scenarios from 1950 to 2100 to assess how hot, dry, and compound hot‐dry extremes are expected to change in the future when compared to current climate conditions. We find that such extremes are projected to increase by the end of the 21st century over large parts of global land areas under the highest‐emission, no‐policy, climate change scenario. Hot and compound hot‐dry extremes show the most widespread increases, whereas dry extreme changes are sensitive and more regionally limited depending on the method by which they are computed. Most of the regional changes in hot, dry, and compound hot‐dry extremes can be reduced with strong climate change mitigation efforts to limit future green‐house gas emissions. Key Points: Hot extremes are projected to increase in frequency and intensity over almost all land areas by the end of the 21st centuryDrought changes depend on measure but increase robustly over central and northern South America, the Mediterranean, and southern AfricaCompound hot and dry extremes are sensitive to the drought measure but projected to increase in most regions globally [ABSTRACT FROM AUTHOR]

Protecting and enhancing forest carbon sinks is considered a natural solution for mitigating climate change. However, the increasing frequency, intensity, and duration of droughts due to climate change can threaten the stability and growth of existing forest carbon sinks. Extreme droughts weaken plant hydraulic systems, can lead to tree mortality events, and may reduce forest diversity, making forests more vulnerable to subsequent forest disturbances, such as forest fires or pest infestations. Although early warning metrics (EWMs) derived using satellite remote sensing data are now being tested for predicting post-drought plant physiological stress and mortality, applications of unmanned aerial vehicles (UAVs) are yet to be explored extensively. Herein, we provide twenty-four prospective approaches classified into five categories: (i) physiological complexities, (ii) site-specific and confounding (abiotic) factors, (iii) interactions with biotic agents, (iv) forest carbon monitoring and optimization, and (v) technological and infrastructural developments, for adoption, future operationalization, and upscaling of UAV-based frameworks for EWM applications. These UAV considerations are paramount as they hold the potential to bridge the gap between field inventory and satellite remote sensing for assessing forest characteristics and their responses to drought conditions, identifying and prioritizing conservation needs of vulnerable and/or high-carbon-efficient tree species for efficient allocation of resources, and optimizing forest carbon management with climate change adaptation and mitigation practices in a timely and cost-effective manner. [ABSTRACT FROM AUTHOR]

Large‐scale bioenergy plays a key role in climate change mitigation scenarios, but its efficacy is uncertain. This study aims to quantify that uncertainty by contrasting the results of three different types of models under the same mitigation scenario (RCP2.6‐SSP2), consistent with a 2°C temperature target. This analysis focuses on a single bioenergy feedstock, Miscanthus × giganteus, and contrasts projections for its yields and environmental effects from an integrated assessment model (IMAGE), a land surface and dynamic global vegetation model tailored to Miscanthus bioenergy (JULES) and a bioenergy crop model (MiscanFor). Under the present climate, JULES, IMAGE and MiscanFor capture the observed magnitude and variability in Miscanthus yields across Europe; yet in the tropics JULES and IMAGE predict high yields, whereas MiscanFor predicts widespread drought‐related diebacks. 2040–2049 projections show there is a rapid scale up of over 200 Mha bioenergy cropping area in the tropics. Resulting biomass yield ranges from 12 (MiscanFor) to 39 (JULES) Gt dry matter over that decade. Change in soil carbon ranges from +0.7 Pg C (MiscanFor) to −2.8 Pg C (JULES), depending on preceding land cover and soil carbon.2090–99 projections show large‐scale biomass energy with carbon capture and storage (BECCS) is projected in Europe. The models agree that <2°C global warming will increase yields in the higher latitudes, but drought stress in the Mediterranean region could produce low yields (MiscanFor), and significant losses of soil carbon (JULES and IMAGE). These results highlight the uncertainty in rapidly scaling‐up biomass energy supply, especially in dry tropical climates and in regions where future climate change could result in drier conditions. This has important policy implications—because prominently used scenarios to limit warming to 'well below 2°C' (including the one explored here) depend upon its effectiveness. [ABSTRACT FROM AUTHOR]

(1) Background: Water security is at the front and center of climate change, human security, and sustainable development in regions and communities with competing water usage contexts, climate change effects, and cross-border water-sharing agreements, resulting in conflicts arising. Shared water agreements are affected by geopolitics, segregation, water availability, and access rights. Climate change can worsen water problems by changing precipitation trends or causing droughts. (2) Methods: Document and content analysis and primary and secondary data assessment were used to develop spatio-temporal patterns. In establishing a water security narrative for the region, the selection of SDG 6 (water) and SDG 13 (climate action) targets and indicators was also evaluated. UN-Water's 2013 water security conceptual framework was used to examine water and climate security concerns and give a set of principles to assess gaps and fulfill needs toward a 'water security future' for communities and states in the region. Also, hydro-political perspectives in the region or state were evaluated using discourse analysis and guiding notes from emerging scholarship to support suggestions and prospective solutions toward mitigating water insecurity and risks from climate change and disasters, including resource (water) related conflicts. (3) Results: Hydro-hegemony keeps the water sector in one state under massive stress, and the lack of consensus-building for the regional water agenda continues to breed conflicts between communities and states. (4) Conclusions: We reiterate that the escalating water and climate crises will deepen, and at the national and local scale for OPT, the restrictions and geopolitical tensions about shared waters can render coping and adaptation mechanisms for people and stakeholders challenging. [ABSTRACT FROM AUTHOR]

Drought is a global issue with profound implications worldwide on biodiversity, equal safety, poverty eradication, sustainable development, and social-economic stability due to the significant role that water resources play in the growth of the world economy. Burundi is one of the highly vulnerable countries to the effects of climate change-related events because of its low adaptive capacity and high dependence on rainfed agriculture for livelihood. This research aimed to identify drought incidents and their characteristics in terms of duration, severity, and intensity and analysis of their trends in Burundi using the Standardized Precipitation Evapotranspiration Index (SPEI). Monthly precipitation and temperature data of seven meteorological stations across Burundi (1981–2020) were obtained from Burundi Geographical Institute (IGEBU). The SPEI index of -2, -6 and -24 month timescales were generated to understand drought characteristics and the Mann–Kendall (MK) test combined with Sen's slope estimator were utilized to analyze the drought trend based on the calculated SPEI values. The overall analysis of the computed SPEI time series demonstrated that drought is more frequent and severe in Burundi, especially in the northern and eastern parts. The results showed that the most prolonged and severe drought occurred during the 1990–2010 decades, and 1993, 1994, 1995, 1999, 2000, 2001, 2004, 2005, 2006, 2009, and 2016 were extremely dry years. Proactive drought mitigation activities, climate change mitigation and water resources management policy are highly recommended in order to reduce drought risk and its effect on both population and the natural environment. [ABSTRACT FROM AUTHOR]

Accurate and reliable drought monitoring is of primary importance for drought mitigation and reduction of social-ecological vulnerability. The aim of the paper was to propose a multiscale composited drought index (CDI) which could be widely used for drought monitoring and early warning in China. In the study, the upper Huaihe River basin above the Xixian gauge station, which has been hit by severe droughts frequently in recent decades, was selected as the case study site. The newly built short-term/long-term CDI comprehensively considered three natural forms of drought (meteorological, hydrological, and agricultural) by selection of different variables that are related to each drought type. The short-term/long-term CDI was developed using the Principle Component Analysis of related drought components. The thresholds of the short-term/long-term CDI were determined according to frequency statistics of different drought indices. Finally, the feasibility of the two CDI was investigated against the self-calibrating Palmer drought severity index, the standardized precipitation evapotranspiration index, and the historical drought records. The results revealed that the short-term/long-term CDI could capture the onset, severity, and persistence of drought events very well with the former being better at identifying the dynamic evolution of drought condition and the latter better at judging the changing trend of drought over a long time period. [ABSTRACT FROM AUTHOR]

The prediction of future drought is an effective mitigation tool for assessing adverse consequences of drought events on vital water resources, agriculture, ecosystems and hydrology. Data-driven model predictions using machine learning algorithms are promising tenets for these purposes as they require less developmental time, minimal inputs and are relatively less complex than the dynamic or physical model. This paper authenticates a computationally simple, fast and efficient non-linear algorithm known as extreme learning machine (ELM) for the prediction of Effective Drought Index (EDI) in eastern Australia using input data trained from 1957–2008 and the monthly EDI predicted over the period 2009–2011. The predictive variables for the ELM model were the rainfall and mean, minimum and maximum air temperatures, supplemented by the large-scale climate mode indices of interest as regression covariates, namely the Southern Oscillation Index, Pacific Decadal Oscillation, Southern Annular Mode and the Indian Ocean Dipole moment. To demonstrate the effectiveness of the proposed data-driven model a performance comparison in terms of the prediction capabilities and learning speeds was conducted between the proposed ELM algorithm and the conventional artificial neural network (ANN) algorithm trained with Levenberg–Marquardt back propagation. The prediction metrics certified an excellent performance of the ELM over the ANN model for the overall test sites, thus yielding Mean Absolute Errors, Root-Mean Square Errors, Coefficients of Determination and Willmott's Indices of Agreement of 0.277, 0.008, 0.892 and 0.93 (for ELM) and 0.602, 0.172, 0.578 and 0.92 (for ANN) models. Moreover, the ELM model was executed with learning speed 32 times faster and training speed 6.1 times faster than the ANN model. An improvement in the prediction capability of the drought duration and severity by the ELM model was achieved. Based on these results we aver that out of the two machine learning algorithms tested, the ELM was the more expeditious tool for prediction of drought and its related properties. [ABSTRACT FROM AUTHOR]

With a changing climate, drought has become a common natural disaster. In our study, population exposure to drought over the Pearl River Basin (PRB) under climate change is investigated. Drought frequency is evaluated through the Standardized Precipitation Evapotranspiration Index (SPEI). The data needed for SPEI calculation are obtained based on the ensemble of multiple global climate model (GCM) outputs. Population exposure to drought for the future is assessed by combining drought frequency under two emission scenarios (RCP4.5 and RCP8.5) with three downscaled population scenarios (SSP1, SSP2, and SSP3). Moreover, the main contribution (and their interactions) of GCM, RCP, and SSP to the sources of uncertainty on population exposure projections is explored through multilevel factorial analysis. Results indicate that the temperature and precipitation would continually increase for the future, and the increase in drought frequency is more substantial during the 2080s than in the 2050s. Meanwhile, population exposure to drought accounts for 21.60% of the total population in 1976–2005 over the PRB area. During the 2050s, it would decrease to 11.98–12.28% under RCP4.5 and 14.15–14.40% under RCP8.5, respectively. By the 2080s, population exposure would slightly reduce under RCP4.5 and increase to 28.86–29.44% under RCP8.5. GCM is the primary uncertainty source of drought exposure in the 2050s, with contribution rates of 72.41%, 57.47%, 51.10%, and 78.71% to the four responses. In comparison, by the 2080s, RCP is the primary contributing factor, with contribution rates of 53.91%, 44.92%, 64.20%, and 48.00%, respectively. Plain Language Summary: Climate change has an extensive impact on future drought conditions in the Pearl River Basin. Therefore, the projection of population exposure to drought is essential for making informed decisions toward climate change mitigation and adaptation. This study aims at exploring the changes in population exposure to droughts (e.g., moderate, severe, and extreme) under multiple emission‐population scenarios and quantifying the main contribution (and their interactions) of global climate model (GCM), RCP, and SSP to the sources of uncertainty on population exposure. The temperature and precipitation would continually increase for the future, and the increase in drought frequency is more substantial during the 2080s than in the 2050s. As a result, future population exposure to moderate, severe, and extreme drought would decrease in the 2050s, under two RCPs. While during the 2080s, there is a slight decrease under RCP4.5 and an apparent increase under RCP8.5. GCM is the primary uncertainty source of drought exposure in the 2050s to the four responses. In comparison, by the 2080s, RCP is the major contributing factor. Key Points: Population exposure to drought for the future is projected through the combination of multiple emission‐population scenariosPopulation exposure to drought would increase apparently in the 2080s under RCP8.5Global climate model (GCM) and RCP are the primary uncertainty sources of drought exposure in the 2050s and 2080s, respectively [ABSTRACT FROM AUTHOR]

In 2015, El Niño contributed to severe droughts in equatorial Asia (EA). The severe droughts enhanced fire activity in the dry season (June–November), leading to massive fire emissions of CO2 and aerosols. Based on large event attribution ensembles of the MIROC5 atmospheric global climate model, we suggest that historical anthropogenic warming increased the chances of meteorological droughts exceeding the 2015 observations in the EA area. We also investigate changes in drought in future climate simulations, in which prescribed sea surface temperature data have the same spatial patterns as the 2015 El Niño with long-term warming trends. Large probability increases of stronger droughts than the 2015 event are projected when events like the 2015 El Niño occur in the 1.5 and 2.0 ∘ C warmed climate ensembles according to the Paris Agreement goals. Further drying is projected in the 3.0 ∘ C ensemble according to the current mitigation policies of nations. We use observation-based empirical functions to estimate burned area, fire CO2 emissions and fine (<2.5 µ m) particulate matter (PM 2.5) emissions from these simulations of precipitation. There are no significant increases in the chances of burned area and CO2 and PM 2.5 emissions exceeding the 2015 observations due to past anthropogenic climate change. In contrast, even if the 1.5 and 2.0 ∘ C goals are achieved, there are significant increases in the burned area and CO2 and PM 2.5 emissions. If global warming reaches 3.0 ∘ C, as is expected from the current mitigation policies of nations, the chances of burned areas and CO2 and PM 2.5 emissions exceeding the 2015 observed values become approximately 100 %, at least in the single model ensembles. We also compare changes in fire CO2 emissions due to climate change and the land-use CO2 emission scenarios of five shared socioeconomic pathways, where the effects of climate change on fire are not considered. There are two main implications. First, in a national policy context, future EA climate policy will need to consider these climate change effects regarding both mitigation and adaptation aspects. Second is the consideration of fire increases changing global CO2 emissions and mitigation strategies, which suggests that future climate change mitigation studies should consider these factors. [ABSTRACT FROM AUTHOR]

Background and Aims Bioenergy crops are central to climate mitigation strategies that utilize biogenic carbon, such as BECCS (bioenergy with carbon capture and storage), alongside the use of biomass for heat, power, liquid fuels and, in the future, biorefining to chemicals. Several promising lignocellulosic crops are emerging that have no food role – fast-growing trees and grasses – but are well suited as bioenergy feedstocks, including Populus , Salix , Arundo , Miscanthus , Panicum and Sorghum. Scope These promising crops remain largely undomesticated and, until recently, have had limited germplasm resources. In order to avoid competition with food crops for land and nature conservation, it is likely that future bioenergy crops will be grown on marginal land that is not needed for food production and is of poor quality and subject to drought stress. Thus, here we define an ideotype for drought tolerance that will enable biomass production to be maintained in the face of moderate drought stress. This includes traits that can readily be measured in wide populations of several hundred unique genotypes for genome-wide association studies, alongside traits that are informative but can only easily be assessed in limited numbers or training populations that may be more suitable for genomic selection. Phenotyping, not genotyping, is now the major bottleneck for progress, since in all lignocellulosic crops studied extensive use has been made of next-generation sequencing such that several thousand markers are now available and populations are emerging that will enable rapid progress for drought-tolerance breeding. The emergence of novel technologies for targeted genotyping by sequencing are particularly welcome. Genome editing has already been demonstrated for Populus and offers significant potential for rapid deployment of drought-tolerant crops through manipulation of ABA receptors, as demonstrated in Arabidopsis , with other gene targets yet to be tested. Conclusions Bioenergy is predicted to be the fastest-developing renewable energy over the coming decade and significant investment over the past decade has been made in developing genomic resources and in collecting wild germplasm from within the natural ranges of several tree and grass crops. Harnessing these resources for climate-resilient crops for the future remains a challenge but one that is likely to be successful. [ABSTRACT FROM AUTHOR]

Drought monitoring is important for characterizing the timing, extent, and severity of drought for effective mitigation and water management. Presented here is a novel satellite-based drought severity index (DSI) for regional monitoring derived using time-variable terrestrial water storage changes from the Gravity Recovery and Climate Experiment (GRACE). The GRACE-DSI enables drought feature comparison across regions and periods, it is unaffected by uncertainties associated with soil water balance models and meteorological forcing data, and it incorporates water storage changes from human impacts including groundwater withdrawals that modify land surface processes and impact water management. Here, the underlying algorithm is described, and the GRACE-DSI performance in the continental United States during 2002-14 is evaluated. It is found that the GRACE-DSI captures documented regional drought events and shows favorable spatial and temporal agreement with the monthly Palmer Drought Severity Index (PDSI) and the U.S. Drought Monitor (USDM). The GRACE-DSI also correlates well with a satellite-based normalized difference vegetation index (NDVI), indicating sensitivity to plant-available water supply changes affecting vegetation growth. Because the GRACE-DSI captures changes in total terrestrial water storage, it complements more traditional drought monitoring tools such as the PDSI by providing information about deeper water storage changes that affect soil moisture recharge and drought recovery. The GRACE-DSI shows potential for globally consistent and effective drought monitoring, particularly where sparse ground observations (especially precipitation) limit the use of traditional drought monitoring methods. [ABSTRACT FROM AUTHOR]

Global climate change may result in severe regional consequences affecting agricultural production potential. One of the essential climatic impacts is associated with drought conditions. Therefore, projected future changes of several drought indices are analyzed for the future period 2071-2100 (compared to 1961-1990, as a reference period) using three different global emission scenarios (A2, A1B, and B2). The monthly time series of the indices have been calculated from the simulation outputs of the regional climate model PRECIS (Providing REgional Climates for Impacts Studies) for Central/Eastern Europe with 25 km horizontal resolution accomplished by the Department of Meteorology, Eotvos Lorand University. According to the results significant drying is projected in the region, especially in summer. [ABSTRACT FROM AUTHOR]

Drought research is an important aspect of drought disaster mitigation and adaptation. For this purpose, we used the Standardized Precipitation Evapotranspiration Index (SPEI) to investigate the spatial-temporal pattern of drought and its impact on crop production. Using monthly precipitation (Precip) and temperature (Temp) data from 1986–2015 for 39 weather stations, the drought index was obtained for the time scale of 3, 6, and 12 months. The Mann–Kendall test was used to determine trends and rates of change. Precip and Temp anomalies were investigated using the regression analysis and compared with the drought index. The link between drought with large-scale atmospheric circulation anomalies using the Pearson correlation coefficient (R) was explored. Results showed a non-uniform spatial pattern of dryness and wetness which varied across Myanmar agro-ecological zones and under different time scales. Generally, results showed an increasing trend for the SPEI in the three-time scales, signifying a high tendency of decreased drought from 1986–2015. The fluctuations in dryness/wetness might linked to reduction crop production between 1986–1999 and 2005, 2008, 2010, 2013 cropping years. Results show relationship between main crops production and climate (teleconnection) factors. However, the low correlation values (i.e., <0.49) indicate the extent of the relationship within the natural variability. However, readers are urged to interpret this result cautiously as reductions in crop production may also be affected by other factors. We have demonstrated droughts evolution and trends using weather stations, thus providing useful information to aid policymakers in developing spatially relevant climate change adaptation and mitigation management plans for Myanmar. [ABSTRACT FROM AUTHOR]

The important aspect of changing hydro-climatic extremes is addressed in studies examining projected changes to flood-generating mechanisms associated with snowmelt across Canada, and historical and projected changes to severe Canadian Prairie droughts. The earth has vast amounts of surface and sub-surface freshwater in the form of lakes, reservoirs, rivers, wetlands, soil water, groundwater, as well as water stored in snowpacks, glaciers, and permafrost. Hydro-climatic extremes such as floods and droughts have significant impacts on freshwater availability and are projected to increase in frequency as the result of climate change. Summary of This Special Issue This special issue includes two invited critical reviews related to hydro-climatic processes associated with freshwater availability. [Extracted from the article]

The uncertainty of drought forecasting based on past meteorological data is increasing because of climate change. However, agricultural droughts, associated with food resources and determined by soil moisture, must be predicted several months ahead for timely resource allocation. Accordingly, we designed a severe drought area prediction (SDAP) model for short-term drought without meteorological data. The predictions of our proposed SDAP model indicate a forecast of serious drought areas assuming non-rainfall, not a probability prediction of drought occurrence. Furthermore, this prediction provides more practical information to help with rapid water allocation during a real drought. The model structure using remote sensing data consists of two parts. First, the drought function f(x) from the training area by random forest (RF) learned the changes in the pattern of soil moisture index (SMI) from the past drought and the training performance was found to be root mean square error (RMSE) = 0.052, mean absolute error (MAE) = 0.039, R2 = 0.91. Second, derived f(x) predicted the SMI of the study area, which is 20 times larger than the training area, of the same season of another year as RMSE = 0.382, MAE = 0.375, R2 = 0.58. We also obtained the variable importance stemming from RF and discussed its meaning along with the advantages and limitations of the model, training areas selection, and prediction coverage. [ABSTRACT FROM AUTHOR]