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Aim: As climate change increases the frequency and severity of droughts in many regions, conservation during drought is becoming a major challenge for ecologists. Droughts are multidimensional climate events whose impacts may be moderated by changes in temperature, water availability or food availability, or some combination of these. Simultaneously, other stressors such as extensive anthropogenic landscape modification may synergize with drought. Useful observational models for guiding conservation decision‐making during drought require multidimensional, dynamic representations to disentangle possible drought impacts, and consequently, they will require large, highly resolved data sets. In this paper, we develop a two‐stage predictive framework for assessing how drought impacts vary with species, habitats and climate pathways. Location: Central Valley, California, USA. Methods: We used a two‐stage counterfactual analysis combining predictive linear mixed models and N‐mixture models to characterize the multidimensional impacts of drought on 66 bird species. We analysed counts from the eBird participatory science data set between 2010 and 2019 and produced species‐ and habitat‐specific estimates of the impact of drought on relative abundance. Results: We found that while fewer than a quarter (16/66) of species experienced abundance declines during drought, nearly half of all species (27/66) changed their habitat associations during drought. Among species that shifted their habitat associations, the use of natural habitats declined during drought while use of developed habitat and perennial agricultural habitat increased. Main Conclusions: Our findings suggest that birds take advantage of agricultural and developed land with artificial irrigation and heat‐buffering microhabitat structure, such as in orchards or parks, to buffer drought impacts. A working lands approach that promotes biodiversity and mitigates stressors across a human‐induced water gradient will be critical for conserving birds during drought. [ABSTRACT FROM AUTHOR]

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

Drought poses a serious threat to agricultural production and food security in the context of global climate change. Few studies have explored the response mechanism and lag time of agricultural drought to meteorological drought from the perspective of cultivated land types. This paper analyzes the spatiotemporal evolution patterns and hysteresis relationship of meteorological and agricultural droughts in the middle and lower reaches of the Yangtze River in China. Here, the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index products and surface temperature products were selected to calculate the Temperature Vegetation Dryness Index (TVDI) from 2010 to 2015. Furthermore, we obtained the Standardized Precipitation Evapotranspiration Index (SPEI) and the Palmer Drought Severity Index (PDSI) for the same period. Based on these indices, we analyzed the correlation and the hysteresis relationship between agricultural and meteorological drought in rainfed and irrigated arable land. The results showed that, (1) compared with SPEI, the high spatial resolution PDSI data were deemed more suitable for the subsequent accurate and scientific analysis of the relationship between meteorological and agricultural droughts. (2) When meteorological drought occurs, irrigated arable land is the first to experience agricultural drought, and then alleviates when the drought is most severe in rainfed arable land, indicating that irrigated arable land is more sensitive to drought events when exposed to the same degree of drought risk. However, rainfed arable land is actually more susceptible to agricultural drought due to the intervention of irrigation measures. (3) According to the cross-wavelet transform analysis, agricultural droughts significantly lag behind meteorological droughts by about 33 days during the development process of drought events. (4) The spatial distribution of the correlation coefficient between the PDSI and TVDI shows that the area with negative correlations of rainfed croplands and the area with positive correlations of irrigated croplands account for 77.55% and 68.04% of cropland areas, respectively. This study clarifies and distinguishes the details of the meteorological-to-agricultural drought relationship in rainfed and irrigated arable land, noting that an accurate lag time can provide useful guidance for drought monitoring management and irrigation project planning in the middle and lower reaches of the Yangtze River. [ABSTRACT FROM AUTHOR]

Across recent years, there has been a growing prevalence of extreme weather events throughout the United States, posing significant challenges to the reliable and resilient operation of power systems. Specifically, summer droughts threaten to severely reduce available generation capacity to meet regional electricity demand, potentially leading to power outages. This underscores the importance of accurate resource adequacy (RA) assessment to ensure the reliable operation of the nation's energy infrastructure. Accurately evaluating the usable capacity of regional generation fleets is a challenging undertaking due to the intricate interactions between power systems and hydro-climatic systems. This paper proposes a systematic and analytical framework to evaluate the impacts of extreme summer drought events on the available capacity of various generating technologies, incorporating both meteorological and hydrologic factors. The framework provides detailed plant-level capacity derating models for hydroelectric, thermoelectric, and renewable power plants, facilitating evaluations with high temporal and spatial resolution. The application of the proposed impact assessment framework to the 2025 generation fleet of the real-world power system within the PJM and SERC regions of the United States yields insightful results. By analyzing the daily usable capacity of 6,055 at-risk generators across the study region, it shows that the summer capacity deration is most significant for hydroelectric and once-through thermal power plants, followed by recirculating thermal power plants and combustion turbines. In the event of the recurrence of the 2007 southeastern summer drought event in the near future, the generation fleet could experience a substantial reduction in available capacity, estimated at approximately 8.5 GW, compared to typical summer conditions. The sensitivity analysis reveals that the usable capacity of the generation fleet would suffer an even more significant decrease under conditions of increasingly severe summer droughts. The proposed approach and the findings of this study provide valuable methodologies and insights, empowering stakeholders to bolster the resilience of power systems against the potentially devastating effects of future extreme drought events. [Display omitted] • A systematic summer droughts generating capacity assessment framework is developed. • Capacity derating models for various generation technologies are presented. • The impacts of summer droughts on generating fleet in PJM and SERC are studied. • Impact of extreme summer drought on usable capacity of generators is significant. [ABSTRACT FROM AUTHOR]

Summary: Drought is intensifying globally with climate change, creating an urgency to understand ecosystem response to drought both during and after these events end to limit loss of ecosystem functioning. The literature is replete with studies of how ecosystems respond during drought, yet there are far fewer studies focused on ecosystem dynamics after drought ends. Furthermore, while the terms used to describe drought can be variable and inconsistent, so can those that describe ecosystem responses following drought. With this review, we sought to evaluate and create clear definitions of the terms that ecologists use to describe post‐drought responses. We found that legacy effects, resilience and recovery were used most commonly with respect to post‐drought ecosystem responses, but the definitions used to describe these terms were variable. Based on our review of the literature, we propose a framework for generalizing ecosystem responses after drought ends, which we refer to as 'the post‐drought period'. We suggest that future papers need to clearly describe characteristics of the imposed drought, and we encourage authors to use the term post‐drought period as a general term that encompasses responses after drought ends and use other terms as more specific descriptors of responses during the post‐drought period. [ABSTRACT FROM AUTHOR]

Forest tree species are likely to be affected by drought due to global climate change. Drought and nitrogen (N) affect plant growth. Therefore, we should understand the mechanisms underlying the N availability and species response to drought for plant development. This paper had two objectives. First, it determined the effects of N addition on water potential, gas exchange parameters, soluble sugar and photosynthetic pigment content, leaf N concentration, and growth parameters under drought stress and well-watered conditions. Second, it searched the drought response of Quercus ithaburensis Decne. subsp. macrolepis (Kotschy) Hedge & Yaltırık seedlings under N conditions with drought stress. In a greenhouse, one-year-old seedlings were exposed to two drought stress and nitrogen addition and three drought cycles. Drought stress significantly reduced stem water potential, relative water content, net photosynthetic rate, stomatal conductance, transpiration rate, leaf area, root collar diameter, seedling height, shoot and root dry weight. On the other hand, it increased water use efficiency and soluble sugar content. N addition is effective on soluble sugar content and photosynthetic pigment content, and promoted leaf N concentrations. Nitrogen addition under well-watered conditions stimulated the growth of Q. ithaburensis seedlings. Drought stress changed the physiological response of Q. ithaburensis seedlings (decreased water potential, net photosynthetic rate, stomatal conductance, and transpiration rate) in the short term, although nitrogen addition under drought stress has not changed the decreasing trend overall. [ABSTRACT FROM AUTHOR]

Frequent drought disasters have significant impacts on socio-economic and ecosystems, and it is crucial to explore the propagation characteristics of drought for disaster prevention and mitigation. In this paper, based on 0.25° × 0.25° grid-point Meteorological hydrological and large-scale climate factor data, the start-to-start, peak-to-peak, and end-to-end drought propagation times, and the periods and rates of drought development and recovery were estimated for 11 regions in the Luanhe River Basin under stationary and non-stationary conditions. The Generalized Additive Model for Location, Scale and Shape (GAMLSS) framework was used to construct stationary and non-stationary models to capture the stationary and non-stationary drought characteristics respectively, and then the drought development and recovery patterns, and drought propagation times were assessed. The results showed that under the influence of climate factors, severe drought events occurred in most study areas, the duration of meteorological drought was prolonged by 0.1–0.6 months, and the peak intensity was increased by about 0.05. The severity of hydrological drought increased by 0.2–0.8, and the peak intensity decreased by 0.1–0.2. The rate of development and recovery of hydrological drought was accelerated by 0.1–0.2 per month. The propagation time of start-to-start was shortened by 0.2 months, and the propagation time of end-to-end was extended by 1–2 months. These mean that water resource control authorities need to propose responses to droughts more quickly. • The non-stationary drought indices considering climatic factors were constructed. • The drought propagation time was calculated from start to start, peak to peak, and end to end. • Quantification of the effects of climate change on drought propagation [ABSTRACT FROM AUTHOR]

• Vegetation response to drought can be inferred from correlating VAI and SPEI. • The strongest accumulation period for vegetation response is 6–8 months. • Trees and irrigated cropland are the least sensitive to drought. • Shrubland and rainfed cropland show the most sensitivity to drought. • The cumulative climate has a higher impact on vegetation than lag effects. Drought caused by climate change has significantly increased vegetation vulnerability in Afghanistan during the last decades. This paper investigates vegetation response to drought at multiple scales across the country based on historical data from 1980 to 2020. It explores the multiscale relationships between drought as indicated by the grid-based standardised precipitation evapotranspiration index (SPEI) and vegetation condition as represented by the satellite-derived vegetation anomaly index (VAI). It also examines the links of dominant land cover with drought and their implications for agriculture. We assess the spatiotemporal correlations by integrating TerraClimate grids with timeseries data sourced from NOAA AVHRR (National Oceanic and Atmospheric Administration Advanced Very High-Resolution Radiometer), MODIS (Moderate Resolution Imaging Spectroradiometer) images and ESA CCI (European Space Agency Climate Change Initiative) land cover maps. We evaluated the effect of cumulative drought on predominant land covers. Our results show years 2000–2001 and 2017–2018 as the driest in the last four decades, and vegetation substantially correlated to drought with spatial and temporal variations across Afghanistan. The most sensitive vegetation response months are June to July and the most significant cumulative drought impacts on vegetation are 6 to 8 months. The predominant land covers more prone to negative effects under severe drought are (in order) shrubland, rainfed cropland, grassland, trees, and irrigated cropland. These findings suggest the sensitivity of vegetation to drought that future national scale drought management should be focused on. This study also demonstrates the usefulness of open-access data to researchers and planners in data-poor countries. [ABSTRACT FROM AUTHOR]

Due to climate change, the frequency and intensity of droughts are expected to increase. To improve resilience to droughts, proactive drought management is essential. Economic assessments are typically included to decide on the drought risk-reducing investments to make. The choice of both methods and scope of economic assessments influences the outcome, and thus the investment choice. This paper aims to identify how comprehensively economic assessments are applied in practice. Through a systematic literature review, 14 actual economic assessments are identified and their methods are evaluated based on seven criteria for economic assessments as derived from the United Nations Framework Convention on Climate Change (UNFCCC). The results show that in practice, economic assessments rarely address all criteria. Applying a limited number of criteria reduces the scope and narrows the approach, possibly leading to the underestimation of drought risk reduction approaches' related benefits. Applying the seven criteria in practice will improve the results of economic assessments of drought risk reduction measures, allowing for optimal investment selection. Based on the different criteria, a Framework for Economic Assessments of Drought Risk-Reducing Applications (FEADRRA) is proposed. Applying the criteria of the framework can support decision-makers in drought risk management and in carrying out the most fitting drought interventions. • Criteria of the economics of climate change rarely translate into practice. • Limited criteria included can underestimate risk-reducing measures' attractiveness. • A framework for the economic assessment of drought mitigation measures is proposed. [ABSTRACT FROM AUTHOR]

• Based on the principles of SPEI, we develop a GDAI. • The relationship between GDAI and AI is closer. • The correlation between GDAI and SPEI is also better. Climate change has increased the risk of drought in both arid and non-arid regions of the globe. Therefore, in order to monitor and evaluate global drought and aridity, based on the principle of standardized precipitation evapotranspiration index (SPEI), this paper selected precipitation and potential evapotranspiration data and used a frequency calculation method to develop a multi-scale global drought aridity index (GDAI) that concurrently considers spatial and temporal variation characteristics: the spatiotemporal standardized precipitation evapotranspiration index. The index was compared with the aridity index (AI) and SPEI. The results showed that the correlation coefficients between GDAI and AI were greater than 0.8 in most areas, and the relationship was closer and could reveal the global aridity and wetness zoning. In addition, the correlation between GDAI and SPEI was also better, which could capture the temporal change characteristics of drought. Moreover, this study also compared the grades of GDAI and SPEI with the actual drought grades in Yunnan from September 2009 to August 2010, and found that GDAI was better than SPEI, and GDAI was the most accurately evaluated at the 3 month time scale, with an accuracy rate of 86.11%. Therefore, this index is more helpful for the assessment and monitoring of global drought and aridity. [ABSTRACT FROM AUTHOR]

Due to the adverse impacts of severe droughts on various aspects of human life and ecosystem services (ESs), the spatio-temporal assessment of the resilience of ESs under droughts is essential. In this paper, we propose a new methodology for assessing ESs-based resilience, taking into account the seven resilience principles: a) redundancy and diversity, b) managing connectivity, c) managing slow variables and their feedback, d) complex adaptive system (CAS) thinking, e) experimentation and learning, f) broadening participation, and g) polycentric governance. These principles enable us to consider the main social, political, hydrological, economic, and environmental aspects concerning resilience which have been overlooked in previous studies. The methodology is evaluated by applying it to Zarrinehroud River Basin (ZRB) in north-western Iran. A set of qualitative and quantitative criteria and their sub-criteria are proposed for quantifying the ES-based resilience and generating time series of resilience against severe droughts in several sub-basins in the study area. To evaluate the criteria and sub-criteria, the required data are derived from calibrated SWAT and MODSIM models as well as experts' judjments. The time series of ES-based resilience under 128 Water and Environmental Resources Management (WERM) scenarios (for enhancing agricultural practices, altering and modernizing irrigation methods, improving irrigation network and drainage facilities) and Climate Change (CC) scenarios (RCP 4.5, RCP6.0, and RCP 8.5) are derived for each sub-basin based on short-term (2020–2049) and long-term (2020–2098) periods. The low resilience values (0.53–0.6) of all sub-basins under the base management scenario (the status quo scenario (SC 0)) illustrate the need for implementing some projects to enhance the ESs in the study area. The results show that the WERM scenario SC 12346 can improve the values of the resilience criterion in sub-basins up to 0.85 and reduce the vulnerability of the study area to droughts. By evaluating all management scenarios, scenario SC 12346 is reported as the best scenario, since it can significantly increase the resilience of all sub-basins against extreme droughts with an acceptable cost of 636 million US dollars compared to other scenarios. Under this WERM scenario, the resilience values of sub-basins increase up to 40%. This scenario suggests implementing a set of projects such as improving irrigation networks and drainage facilities. [Display omitted] • A new methodology is proposed to assess basin-wide spatio-temporal resilience. • 128 scenarios are evaluated using a novel two-point evidential reasoning approach. • The best management scenario enhances the resilience value from 0.53 up to 0.85. • The selected scenario suggests improving irrigation networks and drainage facilities. • The seven resilience principles decrease the width of uncertainty band by 0.44%. [ABSTRACT FROM AUTHOR]

• The relationship between the groundwater depth and grassland ecology was analysed; • Groundwater depth affected the composition and diversity of vegetation species; • A reasonable groundwater depth can buffer the impact of climate change on the vegetation to maintain grassland ecological stability; • The control of grassland degradation should include the potential exploitation of groundwater. Grassland degradation in the semiarid area of China is often attributed to overgrazing and expansion of irrigated agriculture without the consideration of groundwater. However, falling groundwater levels in the region have caused many problems for grassland ecology. In this paper,the typical sandy grassland- the Tongliao part of Horqin grassland was selected as the study area to study the spatial distribution of normalized difference vegetation index (NDVI) and the relationship between the NDVI and groundwater depth (GD) of each grassland pixel was studied. The temporal variation of the NDVI and its correlations with precipitation were investigated. The relationship between GD and vegetation species diversity in grassland was analyzed based on the vegetation survey. The results of the relation between GD and NDVI and vegetation species showed that GD can buffer the impact of increase in drought events on the vegetation because GD affected the composition and diversity of vegetation species. As the GD increases, the mean NDVI showed a trend of increasing first and then decreasing, and basically remained unchanged when the GD was greater than 3.5 m. The species diversity of grassland decreased with increasing GD and was not related to GD when GD was greater than 3.5 ∼ 4 m. Falling groundwater levels will cause great changes in the structure of grassland; specifically, azonal vegetation will gradually die and 3.5 m may be the critical GD needed to maintain the incomplete extinction of grassland azonal vegetation in the aeolian sandy soil. Correlation analysis proved that the correlation between NDVI and precipitation was significantly enhanced when GD increased sharply from 3 m to 6 m after 1999. This research indicates that the control of grassland degradation should pay attention to controlling the groundwater exploitation to recover a reasonable groundwater level, which was found to be necessary in the support of diverse and climate resilient of vegetation. [ABSTRACT FROM AUTHOR]

This paper introduces a new framework to evaluate the resilience of lakes under climatic and anthropogenic droughts. The proposed hierarchical structure of criteria for assessing lake's resilience has four levels. The first level includes several indices such as long-term resilience, reliability, and implementation cost. In the second to fourth levels, four main resilience-based criteria (i.e. robustness, resourcefulness, redundancy, and rapidity) and some qualitative and quantitative sub-criteria are defined considering the factors affecting the ecological condition of lakes. To quantify the time series of the sub-criteria, a coupled SWAT-MODSIM-based simulation model has been applied. Also, the values of criteria and sub-criteria have been aggregated using the Evidential Reasoning (ER) approach. After estimating the annual resilience time series, three resilience indices, namely the recovery time (Tr), loss of resilience (LOR), and final resilience (Res f), have been calculated. The normalized values of these indices and reliability criteria have been aggregated to evaluate the overall performance of lake restoration scenarios. To show the applicability of the proposed methodology, the Zarrinehrud river basin and Lake Urmia have been selected as the case study. As one of the largest hypersaline lakes globally, Lake Urmia suffers from drastic changes in its water body and a high level of salinization. Also, the Zarrinehrud river basin, located in the southeastern of Urmia Lake, is the most significant sub-basin of the lake and is responsible for supplying 41% of the total annual inflow of the lake. The restoration scenarios of Lake Urmia have been assessed from 2019 to 2049. Eventually, the most effective scenario, which has an average overall performance of 0.72, the implementation cost of 17.1 million dollars, and the uncertainty band of 0.05, has been selected. • A new methodology is proposed for evaluating resilience of lakes under drought. • Some new criteria are proposed for assessing the lake's ecological condition. • The evidential reasoning approach is utilized for combining resilience sub-criteria. • Three new resilience indices have been proposed for evaluating management scenarios. • The methodology has been applied to Lake Urmia and Zarrinehrud river basin in Iran. [ABSTRACT FROM AUTHOR]

Strategic decision-making on long-term drought risk management can be supported by integrated assessment models to explore uncertain future conditions and potential policy actions. Such models have to meet many – sometimes conflicting – requirements posed by policy-makers, model developers, and stakeholders. This paper discusses the case of the National Water Model (NWM) that is applied for national policy-making on drought risk management in the Netherlands. The case demonstrates that the chosen assembled model set-up (in which several existing models are combined) is cost-effective and increases stakeholder acceptance, but also leads to high model complexity and computation time. To be effective for policy-making, integrated assessment models need to produce relevant model outcomes that are accepted by stakeholders, within acceptable time and cost limits. For this, the model set-up must support simulations at different aggregation levels (allowing both detailed analysis and exploratory analysis of many scenario/strategy combinations) while maintaining internal consistency. • Decision-making for drought risk management requires Integrated Assessment Models. • Integrated Assessment Models must meet many – sometimes conflicting – requirements. • There is a clear trade-off between model complexity and timeliness. • Effective models are those that allow simulations at different aggregation levels. [ABSTRACT FROM AUTHOR]

In this paper, future drought characteristics (frequency, duration and intensity) over China are analysed by using four climate models from CMIP6 under the seven SSP-RCP (shared socioeconomic pathway-representative concentration pathway) scenarios (SSP119, SSP126, SSP434, SSP245, SSP460, SSP370, and SSP585) for three defined periods of 2021–2040 (near-term), 2041–2060 (mid-term) and 2081–2100 (long-term). The corresponding four climate models output from CMIP5 are also used to conduct a comparison analysis between CMIP5 and CMIP6 to address the improvements added to CMIP6 in terms of drought identification. The drought characteristics are identified by applying the standardized precipitation-evapotranspiration index (SPEI) at a 12-month timescale and run theory. The results show that CMIP6 has a robust capability to capture historical (1986–2005) drought characteristics. For the future period of 2021–2040, the decrease in precipitation and increase in potential evapotranspiration will lead to continuous dry conditions in the upper and middle Yangtze River basin and eastern Pearl River basin. Relative to the reference period, drought events will be more frequent and severe with longer durations in the Northwest River basins and middle Yangtze River basin. Furthermore, higher emissions signify a greater increase in drought frequency and intensity in the long-term period. Except for the SSP585 scenario, the lower emission scenario corresponds to the higher drought duration soon and in the mid-21st century (2021–2060). This finding is regarded as a "strange phenomenon", which cannot be detected by the previous CMIP5-based emission scenarios (RCP2.6, RCP4.5 and the unlikely pathway RCP8.5). Therefore, additional "possible future"-based scenarios (SSP119, SSP126, SSP434, SSP245, SSP460, and SSP370) should be included in extreme climate studies, especially for the near future and mid-21st century. Notably, compared with CMIP5, the reduced biases in drought characteristics are more likely associated with improvements in the representation of physical processes in climate models from CMIP6. The results of this study could provide a basis for the development of drought adaptation measures over China. • Latest CMIP6 climate models and seven SSP-RCP scenarios are used to analyze the possible changes in droughts over China. • More robust projections will be presented by CMIP6 than CMIP5, due to the better representations in physical processes. • The higher emission signifies shorter drought duration, lower precipitation and PET in mid-21st century over China. [ABSTRACT FROM AUTHOR]

Drought is a complex natural hazard. It occurs due to a prolonged period of deficient in rainfall amount in a certain region. Unlike other natural hazards, drought hazard has a recurrent occurrence. Therefore, comprehensive drought monitoring is essential for regional climate control and water management authorities. In this paper, we have proposed a new drought indicator: the Seasonally Combinative Regional Drought Indicator (SCRDI). The SCRDI integrates Bayesian networking theory with Standardized Precipitation Temperature Index (SPTI) at varying gauge stations in various month/seasons. Application of SCRDI is based on five gauging stations of Northern Area of Pakistan. We have found that the proposed indicator accounts the effect of climate variation within a specified territory, accurately characterizes drought by capturing seasonal dependencies in geospatial variation scenario, and reduces the large/complex data for future drought monitoring. In summary, the proposed indicator can be used for comprehensive characterization and assessment of drought at a certain region. • Comprehensive drought monitoring. • Save time and resources in the forecasting of future drought. • Systematic way to combine SDI by using a Bayesian network approach. • Easy in the calculation, save time and resources. [ABSTRACT FROM AUTHOR]

Climate variability and recurrent droughts have caused remarkable strain on water resources in most regions across the globe, with the arid and semi-arid areas being the hardest hit. The impacts have been notable on surface water resources, which are already under threat from massive abstractions due to increased demand, as well as poor conservation and unsustainable land management practices. Drought and climate variability, as well as their associated impacts on water resources, have gained increased attention in recent decades as nations seek to enhance mitigation and adaptation mechanisms. Although the use of satellite technologies has, of late, gained prominence in generating timely and spatially explicit information on drought and climate variability impacts across different regions, they are somewhat hampered by difficulties in detecting drought evolution due to its complex nature, varying scales, the magnitude of its occurrence, and inherent data gaps. Currently, a number of studies have been conducted to monitor and assess the impacts of climate variability and droughts on water resources in sub-Saharan Africa using different remotely sensed and in-situ datasets. This study therefore provides a detailed overview of the progress made in tracking droughts using remote sensing, including its relevance in monitoring climate variability and hydrological drought impacts on surface water resources in sub-Saharan Africa. The paper further discusses traditional and remote sensing methods of monitoring climate variability, hydrological drought, and water resources, tracking their application and key challenges, with a particular emphasis on sub-Saharan Africa. Additionally, characteristics and limitations of various remote sensors, as well as drought and surface water indices, namely, the Standardized Precipitation Index (SPI), Palmer Drought Severity Index (PDSI), Normalized Difference Vegetation (NDVI), Vegetation Condition Index (VCI), and Water Requirement Satisfaction Index (WRSI), Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), Land Surface Water Index (LSWI+5), Modified Normalized Difference Water Index (MNDWI+5), Automated Water Extraction Index (shadow) (AWEIsh), and Automated Water Extraction Index (non-shadow) (AWEInsh), and their relevance in climate variability and drought monitoring are discussed. Additionally, key scientific research strides and knowledge gaps for further investigations are highlighted. While progress has been made in advancing the application of remote sensing in water resources, this review indicates the need for further studies on assessing drought and climate variability impacts on water resources, especially in the context of climate change and increased water demand. The results from this study suggests that Landsat-8 and Sentinel-2 satellite data are likely to be best suited to monitor climate variability, hydrological drought, and surface water bodies, due to their availability at relatively low cost, impressive spectral, spatial, and temporal characteristics. The most effective drought and water indices are SPI, PDSI, NDVI, VCI, NDWI, MNDWI, MNDWI+5, AWEIsh, and AWEInsh. Overall, the findings of this study emphasize the increasing role and potential of remote sensing in generating spatially explicit information on drought and climate variability impacts on surface water resources. However, there is a need for future studies to consider spatial data integration techniques, radar data, precipitation, cloud computing, and machine learning or artificial intelligence (AI) techniques to improve on understanding climate and drought impacts on water resources across various scales. [ABSTRACT FROM AUTHOR]

Unanticipated environmental shocks impact the livelihoods of many resource users around the world. These shocks are likely to be more unpredictable as the effects of climate change continue to mount. Yet how households adapt to these changing climatic conditions especially in the context of rapidly changing market conditions in most areas of the world, is poorly understood. These interactions have wide implications for both smallholder livelihoods and sustainable use of natural resources. In this paper, we examine the relationship between environmental shocks and stocking rates in livestock herds in the Inner Mongolian grasslands of northern China. We uniquely examine three types of shocks and how households adapt livestock production strategies in response to each. Separately and in aggregate, we look at three common shocks in Inner Mongolia: droughts, snowstorms, and locust outbreaks. We use a difference-in-differences approach to estimate changes in stocking rates among households that experience shocks versus those that do not with a panel dataset from 2009 to 2014 of 597 households. While we find no clear impact from locusts, our results suggest droughts and snowstorms have opposite effects: droughts are associated with increases in herd sizes, but snowstorms result in decreased herds. We suggest these differences are due to interactions between shocks, emerging options to borrow on credit, and livestock markets. Household adaptation to climate change will be strategic and take advantage of both available resources as well as market conditions. • Climate change is causing stronger and more unpredictable environmental shocks. • We use a difference-in-differences model to estimate the impact of shocks on stocking rate. • Drought relates to bigger herds; snowstorms relate to smaller herds. • Households adapt to shocks taking advantage of both available resources and market conditions. • Shaping well-functioning market may reduce opportunistic resource exploitation. [ABSTRACT FROM AUTHOR]

Hydro-meteorological hazards (HMHs) have had a strong impact on human societies and ecosystems. Their impact is projected to be exacerbated by future climate scenarios. HMHs cataloguing is an effective tool to evaluate their associated risks and plan appropriate remediation strategies. However, factors linked to HMHs origin and triggers remain uncertain, which pose a challenge for their cataloguing. Focusing on key HMHs (floods, storm surges, landslides, droughts, and heatwaves), the goal of this review paper is to analyse and present a classification scheme, key features, and elements for designing nature-based solutions (NBS) and mitigating the adverse impacts of HMHs in Europe. For this purpose, we systematically examined the literature on NBS classification and assessed the gaps that hinder the widespread uptake of NBS. Furthermore, we critically evaluated the existing literature to give a better understanding of the HMHs drivers and their interrelationship (causing multi-hazards). Further conceptualisation of classification scheme and categories of NBS shows that relatively few studies have been carried out on utilising the broader concepts of NBS in tackling HMHs and that the classification and effectiveness of each NBS are dependent on the location, architecture, typology, green species and environmental conditions, as well as interrelated non-linear systems. NBS are often more cost-effective than hard engineering approaches used within the existing systems, especially when taking into consideration their potential co-benefits. We also evaluated the sources of available data for HMHs and NBS, highlighted gaps in data, and presented strategies to overcome the current shortcomings for the development of the NBS for HMHs. We highlighted specific gaps and barriers that need to be filled since the uptake and upscaling studies of NBS in HMHs reduction is rare. The fundamental concepts and the key technical features of past studies reviewed here could help practitioners to design and implement NBS in a real-world situation. Image 1 [ABSTRACT FROM AUTHOR]