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Numerous recent studies have argued that moisture limitation is leading to growth declines and mortality of black spruce (Picea mariana) and white spruce (Picea glauca) in the North American boreal forest. A parallel line of research suggests that increasingly common severe wildfires are altering successional pathways and leading to long‐term replacement of spruce forests with those dominated by paper birch (Betula papyrifera, Betula neoalaskana) and trembling aspen (Populus tremuloides). When both conifers and deciduous trees establish after fire, this biome shift hypothesis implicitly assumes that deciduous species will outcompete the conifers, owing to their more rapid vertical growth and because they might be less sensitive to warm and dry conditions.We established a research site in a white spruce‐paper birch forest on an east‐facing slope in interior Alaska and tested the hypothesis that Alaska paper birch are better adapted to warm and dry conditions than white spruce. Over 6 years (2013–2018), we made hourly measurements of microclimate and xylem sap flux of both species. We also collected increment cores and conducted climate‐growth analyses for both species.During our 6‐year study, growing seasons with low volumetric soil water content (SWC) were those that followed shallow winter snowpacks and had limited summer rainfall, not necessarily those with warm air temperature. Both species were sensitive to moisture limitation. The tree‐ring data revealed significant positive effects of cumulative water year precipitation on radial growth, with a steeper slope for paper birch than for white spruce. Radial growth of both species was also positively related to mean water year air temperature. Sap flux density declined progressively for white spruce over the range of observed SWC and abruptly for paper birch when SWC fell below ~15%.Synthesis. Our results show that, while paper birch might be less sensitive to mild drought than white spruce, it may be more sensitive to severe drought, raising questions about the ability of paper birch to outcompete co‐occurring white spruce in a drier climate. [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]

Paciorek and Wehner raise important questions around our use of the Mann‐Kendall nonparametric trend test on smoothed data for analyzing long‐term hydrometeorological trends in Zhang et al. (2021, https://doi.org/10.1029/2020gl092293). We thank them for initiating this important conversation and their gracious cooperation in exploring the issues addressed in their comment. In this reply we confirm the inflation of significant p‐values by our choice to smooth, illustrate the relatively minor impacts on the main conclusions of our paper, and add our voices to those of Paciorek and Wehner in highlighting the lack of methodology for hypothesis testing across multiple stations that have spatial structure (i.e., testing for regionally consistent trends). Plain Language Summary: Our colleagues Drs. Paciorek and Wehner have raised concerns about our paper (Zhang et al., 2021, https://doi.org/10.1029/2020gl092293), which showed widespread increases in the duration of drought events over the last five decades in the western United States. They point out that our decision to smooth the data using a moving average inflated the number of weather stations at which the trends toward longer droughts were deemed significant by a statistical test. We agree with them on this point, and we have recomputed all our results using unsmoothed data to determine the impacts. We find that for most stations and regions, trend magnitudes remained largely unchanged, with many stations nearby one another often suggesting similar trends. Finally, we agree with Paciorek and Wehner that there is a lack of statistical methods to test such coherent regional patterns, and we caution that over‐reliance on p‐values limits the power of regional data to identify important climate trends. Key Points: We agree that smoothing to 5‐year moving windows introduced serial correlation into time series of annual statistics of daily rainfall data, inflating the number of weather stations individually showing significant trends (p < 0.05) with the Mann‐Kendall testRecomputation with unsmoothed values produced substantially the same dry intervals trend magnitude and direction at most stations individually and had only minimal impacts on dry interval trends computed for National Ecological Observatory Network domains using the Regional Kendall testNo perfect statistical approach leverages the capacity of coherent regional patterns among spatially correlated weather stations, and an over‐reliance on p‐values as a binary (significant vs. insignificant) determinant of trends limits the power of regional data [ABSTRACT FROM AUTHOR]

Although a growing body of literature studies drought impacts, papers providing a comprehensive review of drought's social and economic impacts are scarce. This paper fills this gap by exploring the consequences of drought on societies based on research findings in Australia—a large country used to experiencing severe droughts. To do this, we propose a framework to categorise drought impacts in three dimensions: individuals/households (including health), productive sectors and system (including economic and ecosystem) impacts. The framework then guides a systematic literature review and discussion of studies looking at diverse drought impacts and their related costs. By analysing and discussing the findings from this literature, we emphasise different policy considerations, empirical challenges and research needs to support robust analysis and estimates of the true cost of droughts. We conclude by proposing an expanded framework to identify drought impacts and a discussion of the implications of the review for policy development. [ABSTRACT FROM AUTHOR]

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]

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]

Drought, widely studied as an important driver of ecosystem dynamics, is predicted to increase in frequency and severity globally. To study drought, ecologists must define or at least operationalize what constitutes a drought. How this is accomplished in practice is unclear, particularly given that climatologists have long struggled to agree on definitions of drought, beyond general variants of "an abnormal deficiency of water." We conducted a literature review of ecological drought studies (564 papers) to assess how ecologists describe and study drought. We found that ecologists characterize drought in a wide variety of ways (reduced precipitation, low soil moisture, reduced streamflow, etc.), but relatively few publications (~32%) explicitly define what are, and are not, drought conditions. More troubling, a surprising number of papers (~30%) simply equated "dry conditions" with "drought" and provided little characterization of the drought conditions studied. For a subset of these, we calculated Standardized Precipitation Evapotranspiration Index values for the reported drought periods. We found that while almost 90% of the studies were conducted under conditions quantifiable as slightly to extremely drier than average, ~50% were within the range of normal climatic variability. We conclude that the current state of the ecological drought literature hinders synthesis and our ability to draw broad ecological inferences because drought is often declared but is not explicitly defined or well characterized. We suggest that future drought publications provide at least one of the following: (a) the climatic context of the drought period based on long‐term records; (b) standardized climatic index values; (c) published metrics from drought‐monitoring organizations; (d) a quantitative definition of what the authors consider to be drought conditions for their system. With more detailed and consistent quantification of drought conditions, comparisons among studies can be more rigorous, increasing our understanding of the ecological effects of drought. [ABSTRACT FROM AUTHOR]

In Senegal, agriculture is an important sector underpinning the socioeconomic fabric of the populace. Notably, the agricultural production in this region exhibits heightened sensitivity to climatic perturbations, particularly droughts and heat waves. This study aims to determine the resilience of different agronomic interventions for farmers practicing mixed farming that produce both crops (i.e., groundnut (Arachis hypogaea L.) and pearl millet (Pennisetum glaucum (L.) R. Br.)) and raise animals in the Groundnut Basin in Senegal, which holds historical and socioeconomic significance. To understand the current situation regarding demographics, economics, consumption behavior, and farm operations for smallholder farmers, data were comprehensively collected from government and nongovernment organizations (NGO) reports, scientific papers, organization databases, and surveys. Additionally, the Agricultural Production Systems sIMulator (APSIM) was used to understand how combinations of three planting dates, three plant densities, and six urea nitrogen (N) fertilizer rates affected the yield of pearl millet, which were used as the alternative scenarios to the baseline in the farm modeling and analyses. All the collected and generated data were used as inputs into the Farm Simulation Model (FARMSIM) to generate economic, nutritional, and risk data associated with mixed farming systems. The generated data were then used to determine the resilience of the alternative scenarios against the baseline. Initially, a multi‐objective optimization was employed to meet nutritional needs while maintaining a healthy diet at the lowest cost. Then, the scenarios that met the population's nutritional requirements were evaluated based on four economic indicators: net cash farm income (NCFI), ending cash reserves (EC), net present value (NPV), and internal rate of return (IRR). Lastly, those that passed the economic feasibility test were ranked based on risk criteria certainty equivalent (CE) and risk premium (RP). The analyses found N fertilizer rates of 0, 20, and 100 kg N ha−1 were generally economically not feasible. Additionally, medium (early‐July to late‐August) and late (late‐July to mid‐September) planting dates generally performed better than early (early‐June to late‐July) planting dates, while plant densities of 3.3 and 6.6 pL m−2 performed better than 1.1. The robust resilience approach introduced in this study is easily transferable to other regions. [ABSTRACT FROM AUTHOR]

We describe the bias adjustment and downscaling to a resolution of 1 × 1 km of daily temperature, precipitation and solar radiation of a multimodel ensemble of Coupled Model Intercomparison Project Phase 6 (CMIP6) GCMs with the local observational data set BhutanClim for Bhutan and an analysis of the results for 1996–2100. The GCMs were selected based on their ability to reproduce local temporal and spatial precipitation patterns, resulting in a total of 14 models for each shared socioeconomic pathway (SSP). The results are shown for five global warming levels (GWLs) 1.5, 2, 3, 4 and 5°C, providing insight into the projected impacts of climate change at different warming levels. The daily temperature and precipitation data are publicly available, which is of great benefit for climate impact studies, such as ecological, hydrological or infrastructure‐related studies. In this paper, we discuss showcase climate indicators. Peak‐over‐threshold climate indicators such as hot days above 30°C are relevant for human health. In the capital city of Thimphu, these are currently rare, at 4 days per year, but might increase to more than 80 for GWL5.0. Precipitation increases in the summer months, but slightly decreases in the drier winter months. Accordingly, the 3‐month SPEI drought index is projected to increase in summer, but strongly decreases in the winter months, mostly pronounced in February. The increasing severity of late‐winter and spring droughts might have a negative impact on vegetation, wildfires and water supply. [ABSTRACT FROM AUTHOR]

Understanding of past droughts has been mostly shaped by meteorological data, with relatively less known about the human aspects of droughts, their socio‐economic impacts, as well as choices people make in response to droughts in different environmental and socio‐political contexts. The lack of data that systematically record and categorize drought impacts is an important reason for this disparity. In this paper, we present an Irish drought impacts database (IDID) containing 6094 newspaper reports and 11,351 individual impact records for the island of Ireland, covering the period 1733–2019. Relevant articles were identified through systematic searching of the Irish Newspaper Archives, and recorded impacts were categorized using a modified version of the classification scheme employed by the European drought impact inventory (EDII). Drawing on the wealth and diversity of content provided by the newspapers, the IDID database provides information on the documented temporal and geographical extent of drought events, their socio‐economic and political contexts, their consequences, mitigation strategies employed and their change over time. The IDID also facilitates analysis of long‐term patterns in drought incidence, individual impact categories, as well as detailed insight into the impacts of individual drought events over nearly three centuries of Ireland's history. In addition, by allowing an examination of the coherence between meteorological records and identified impacts, it advances our understanding of the influences that contemporary economic, political, environmental and societal events had on the human experience, perception and impact of droughts. This new open‐access database, therefore, provides opportunities for improving understanding of drought vulnerability and is an important step in developing greater capacity to cope with and respond to future droughts on the island of Ireland. [ABSTRACT FROM AUTHOR]

Tree rings have been central to the understanding of variability of flow of the Colorado River. Spurred by steadily declining flows after the 1920s, early tree‐ring research drew attention to the importance of climate variability to water supply by identifying episodes in the past that were even drier. Application of modern statistical methods to tree‐ring data later yielded a reconstruction of annual flows at Lees Ferry back to the early 1500s that highlighted the unprecedented wetness of the base period for the 1922 Colorado River Compact. That reconstruction served as the framework for a collection of papers in a 1995 special issue of Water Resources Bulletin on coping with severe sustained drought on the Colorado River. This retrospective paper reviews historical aspects of the dendrohydrology of the Colorado River, and the updates since 1995. A constantly expanding tree‐ring network has been subjected to an array of new statistical approaches to reconstruction. Climate change and increasing demand for water have meanwhile driven increased interest in the processing and presentation of reconstructions for optimal use in water resources planning and management. While highlighting the robustness of main findings of earlier studies, recent research yields improved estimates of magnitudes of flow anomalies, extends annual flows to more than 1200 years, and underscores unmatched drought duration in the medieval period. [ABSTRACT FROM AUTHOR]

The water table depth (WTD) in peatlands determines the soil carbon decomposition rate and influences vegetation growth, hence the above‐ground carbon assimilation. Here, we used satellite‐observed Solar‐Induced chlorophyll Fluorescence (SIF) as a proxy of Gross Primary Production (GPP) to investigate water‐related vegetation stress over northern peatlands. A linear model with interaction effects was used to relate short‐ and long‐term anomalies in SIF with WTD anomalies and the absolute WTD. Most locations showed the occurrence of drought and waterlogging stress though regions with exclusively waterlogging or drought stress were also detected. As a spatial median, minimal water‐related vegetation stress was found for a WTD of −0.22 m (short‐term) and −0.20 m (long‐term) (±0.01 m, 95% confidence interval of statistical uncertainty). The stress response observed with SIF is supported by an analysis of in situ GPP data. Our findings provide insight into how changes in WTD of northern peatlands could affect GPP under climate change. Plain Language Summary: Water table depth is an important variable influencing the carbon cycle and vegetation growth in northern peatlands. In this paper, the impact of changing wetness conditions on vegetation growth over peatlands was studied through satellite measurements of solar‐induced fluorescence (SIF), which is a radiation signal emitted by vegetation during photosynthesis. Previous studies over ecosystems on mineral soil, that is, not over peatland, suggested a response of SIF to drought conditions. In our study, it was shown that peatland vegetation experiences moisture‐related growth stress under both very wet and very dry conditions, which might reduce the photosynthesis efficiency and the ability to capture and store CO2. Stress due to drought conditions was detected for peatlands in the south of the Western Siberian Lowlands and the Boreal Plains. Stress due to prolonged wet conditions occurred for example, in the north of the Western Siberian Lowlands and the north of the Hudson Bay Lowlands. Key Points: Spaceborne Solar‐Induced Fluorescence (SIF) data was used to analyze soil moisture‐related vegetation stress regimes in northern peatlandsFor most locations, waterlogging as well as drought stress regimes occurred and alternated depending on peatland water level dynamicsThe SIF‐based stress response observations are supported by in situ data of Gross Primary Production [ABSTRACT FROM AUTHOR]

There is a need to support applied, community‐relevant hydrologic research within changing climate, population, and socioeconomic conditions to better inform water policy and management. We hypothesized that providing a rural agricultural community in a semiarid valley with the necessary monitoring tool to meet local water management needs would increase adaptive capacity within the context of long‐term drought. Through a community science approach, researchers installed a telemetry monitoring system at participating acequia irrigation diversions that remotely sent water data to a web interface every 15 min. Two surveys distributed before and after web interface access targeted seven adaptive capacity indicators. After the first season of improved data accessibility, the following adaptive capacity indicators significantly increased: information diversity, cognitive social capital, leadership, and proactivity. Rather than focusing on the water savings aspect of real‐time monitoring, this paper summarizes a novel water resources study that assessed the social impact of real‐time irrigation water delivery monitoring on adaptive capacity. This study suggests that bridging the gap between community need and hydrologic research through community science, sociologic analysis, and stakeholder engagement provides significant benefits for communities facing water management challenges, further supporting problem‐driven water resources research. [ABSTRACT FROM AUTHOR]

Using recycled water to irrigate agricultural products can be an effective solution to water scarcity and security. However, a better understanding of how society values different sources of recycled water provides insights into potential demand‐side barriers to adoption of these solutions. This paper implements a framed field experiment conducted in the Southwest and Mid‐Atlantic regions of the United States that evaluates consumers' willingness‐to‐pay (WTP) for three sources of recycled irrigation water: "gray," "black," and "produced." Our analysis indicates that people consider certain sources of recycled water more acceptable for irrigating produce than others. Recycled gray water is preferred to recycled produced water, and both are preferred to recycled black water. We also explore how people respond to scientific information about the benefits and risks of using recycled irrigation water and found no evidence to support that this information changes people's behaviors. Plain Language Summary: We evaluate consumers' willingness to pay for produce irrigated with recycled water. We differentiate recycled water into "gray," "black," and "produced" categories following EPA guidelines. EPA defines gray water as household wastewater from washing, laundering, bathing and showering. Black water includes waste water that comes from toilets and urinals. Produced water comes from oil and gas drilling. We find that consumers are willing to pay more for produce irrigated with recycled gray water, followed by recycled produced water and that they prefer recycled black water the least. Key Points: Consumers' willingness to pay for foods irrigated with different types of recycled water is explored in framed field experimentsConsumers prefer foods irrigated by recycled gray water to recycled produced (industrial) water and both are preferred to recycled black waterScientific information about the benefits and risks of using recycled irrigation water did not change people's behavior [ABSTRACT FROM AUTHOR]

Hydrometeorological droughts are complex hazards expressed through the relative deviation in water availability relative to long‐term average conditions. The development and propagation of drought is governed by hydrological processes at different spatial scales including precipitation, evapotranspiration, overland flow, soil moisture, groundwater storage and discharge. Detailed investigation is thus required to evaluate associated linkages among various types of hydrometeorological drought to understand the likely impacts of climate change on drought characteristics (magnitude, frequency, duration and propagation). This study explores the impact of climate change on hydrometeorological drought for 10 Irish catchments, using standardized drought indices representing different components of the hydrological system. We employ 12 Global Climate Models from the Coupled Model Inter‐comparison Project phase 6 (CMIP6), forced with SSP370 and bias corrected to catchment conditions to force a conceptual hydrological model to generate hydrological projections for each catchment. The results indicate substantial drying during summer with associated increases in summer drought magnitude and frequency. However, simulations show a wide range of change, especially for hydrological drought (discharge and baseflow). Only modest changes in the magnitude and frequency of hydrological drought events were found, with increases in winter and spring precipitation offsetting summer dryness. Similarly, the probability of meteorological drought propagating to hydrological events (Standardized Streamflow Index/Standardized Baseflow Index), shows modest increases under the climate change projections considered. Findings highlight that drought, especially during summer are a critical climate change risk for adaptation. Plain Language Summary: Climate change aggravates the impact of hydrometeorological droughts on water availability and distribution in Ireland. Rainfall, evaporation, overland flow, soil moisture, groundwater storage, and the size and strength of discharges are the main factors that cause drought extent and duration. Therefore, for the sustainable development of ecosystems and water resources in a country, it is a requirement to evaluate associated linkages among various types of hydrometeorological drought to understand the likely impacts of climate change on drought characteristics (magnitude) and propagation. This paper explores the impact of climate change on hydrometeorological drought for 10 Irish catchments. The findings indicate significant summer drying, as well as increases in the magnitude and frequency of summer droughts. The probability of meteorological drought propagating to hydrological events, shows modest increases under the climate change projections considered. Drought, particularly during the summer, is a critical climate change risk for adaptation, according to the findings. Key Points: Changes in hydrometeorological drought characteristics under changing climate conditions were estimated; and the results indicate substantial drying during summer with associated increases in summer drought magnitude and frequencyIncreases in winter and spring precipitation result in a decrease in the frequency and magnitude of drought events outside summer and are critical for maintaining baseflow during summer. This also raises the risk of extreme droughts for a dry winter/springThe probability of drought propagation from meteorological to hydrological events increases for the 2050s but decreases for the end of century, highlighting the importance of increases in winter and spring precipitation to drought risk [ABSTRACT FROM AUTHOR]

Water conservation in California has been a major subject of concern for agencies in their efforts to satisfy their residential demand while coping with frequent shortfalls, especially in periods of drought. During the 2012–2016 severe drought in California, the state enacted a conservation mandate that imposed specific conservation targets of 4% up to 36% for water utilities. While the utilities met those targets in 2015, water use, on average, has slowly crept up or rebounded subsequently, although not to pre‐drought levels. Understanding the manner and degree to which water use rebounds can be critically important for water utilities in their planning and investment decisions. Using a unique panel dataset on single‐family residential water use by nearly 20,000 customers of a Northern California water agency from 2013 to 2019, this paper explores the magnitude and character of the rebound effect that occurred after the cessation of a statewide conservation mandate that was imposed on water use in response a severe drought enveloping California from 2014 through 2016. Our results suggest the presence of a significant rebound in water use—of approximately 9% on average—after the conservation mandate ended. Yet, and novel to our research, we find significant heterogeneity in the rebound effects across seasons and water users, with a greater rebound in the warm season months relative to other months and among lower water use households relative to higher water use households. Our results also suggest a significant shift in water use to earlier periods of the day once the mandate was lifted. Understanding the magnitude and variation in rebound effects both temporally and across different types of water users can be useful to water agencies in their efforts to make informed decisions surrounding investments, management, and messaging in response to drought, conservation, and water scarcity. Plain Language Summary: Given the prominence of demand‐side management in the water utilities toolbox for addressing increasing water shortages driven by drought and climate change, understanding how water use changes during a drought along with how and to what extent it increases, or "rebounds," afterward can be useful if not necessary in making informed policy decisions and cost‐effective investments. This research develops a unique data set consisting of household‐level daily and hourly water use by nearly 19,500 residential accounts from a California water utility from 2013 through 2019. It explores how water use changed during and post‐drought relative to pre‐drought levels. During this period, California entered a significant drought. Its governor requested a voluntary cutback, imposed a conservation mandate, and implemented a self‐certification requirement lasting until the drought eased. We find that residential water use decreased by 26% during the conservation mandate relative to pre‐drought levels but rebounded by approximately 9% post‐mandate. The "rebound" effect varied across the season (greatest in summer months) and water user type (lower‐end water users showed a larger percentage rebound than higher‐end water users). Our results suggest that due to the mandate, the peak hour water consumption shifted to the earlier hours of the day. Key Points: Our results suggest that the 2015 California water mandate resulted in temporary and permanent reductions in water useRebound effects are more prevalent in the warm season than in other months and for lower‐end water users than high‐end water usersOur results also show that, due to the mandate, the peak hour water consumption shifted to the earlier hours of the day [ABSTRACT FROM AUTHOR]

Tree diversity and species identity are known to play an important role in modulating forest productivity and its capacity to buffer the effects of climatic events. The FunDivEurope exploratory platform allowed us to analyse this modulating effect in a medium‐term time span, after an abrupt rise to a new stable level of the average summer temperature of ca 2°C, in Mediterranean forests in central Italy. This paper aims to answer the following questions: 1) did increasing temperature and drought events affect the growth of thermophilous deciduous forests? 2) Was this effect buffered in mixed stands compared to monocultures? 3) Did co‐occurring tree species with different ecological characteristics, from more mesophilous to more xerophilous, have different responses? In 2012 and 2017, wood cores were collected from 659 trees in 36 plots representative of thermophilous deciduous forests. The selected tree species were Castanea sativa, Ostrya carpinifolia, Quercus cerris, Quercus ilex and Quercus petraea. In the sampling plots, they were present in pure stands and mixtures from two to four species. After measuring annual rings on cores, chronologies of basal area increment were built, and inventory data were used to estimate tree growth. Results showed a strong reduction of growth, lasting at least 18 years, after the temperature rise. Tree diversity significantly reduced the growth drop after the sudden and stable rise in summer average temperature. Tree mixture effect on growth stability appeared to be dependent on the tree species present in the mixture. Temperature rise and associated drought events, even without changes in rainfall, are one of the main challenges that European forests will face in the current scenarios of climate change. Tree diversity can buffer the effects of climate change over periods of at least 15 years and should be considered in forest management plans. [ABSTRACT FROM AUTHOR]

Intermittent and ephemeral streams in dryland environments support diverse assemblages of aquatic and terrestrial life. Understanding when and where water flows provide insights into the availability of water, its response to external controlling factors, and potential sensitivity to climate change and a host of human activities. Knowledge regarding the timing of drying/wetting cycles can also be useful to map critical habitats for species and ecosystems that rely on these temporary water sources. However, identifying the locations and monitoring the timing of streamflow and channel sediment moisture remains a challenging endeavor. In this paper, we analyzed daily conductivity from 37 sensors distributed along 10 streams across an arid mountain front in Arizona (United States) to assess spatiotemporal patterns in flow permanence, defined as the timing and extent of water in streams. Conductivity sensors provide information on surface flow and sediment moisture, supporting a stream classification based on seasonal flow dynamics. Our results provide insight into flow responses to seasonal rainfall, highlighting stream reaches very reactive to rainfall versus those demonstrating more stable streamflow. The strength of stream responses to precipitation are explored in the context of surficial geology. In summary, conductivity data can be used to map potential stream habitat for water‐dependent species in both space and time, while also providing the basis upon which sensitivity to ongoing climate change can be evaluated. [ABSTRACT FROM AUTHOR]

This paper analyses extreme meteorological droughts in the territory of the Pannonian Basin in central and southeastern Europe. Droughts are treated from an agricultural perspective as periods of consecutive days with very little or no rainfall at all. By using data from the historical period 1981–2010, time intervals longer than 20 days with less than 3 mm per day during the growing season April–September are examined to determine theoretical and empirical distributions of their number and durations. Related discrete stochastic process of extremes is analysed by the Zelenhasic–Todorovic (ZT) method, successfully applied in hydrology and meteorology (e.g., peak flows, low flows, meteorological droughts, etc.). The method is applied to 52 locations across Pannonia Basin. At each location, the Poisson distribution is determined for the number of droughts, exponential distribution for the duration of droughts, and double exponential distribution for the duration of the (annually) longest droughts. To validate the quality of modelling and the results obtained, standard statistical goodness of fit tests are used. Historical data from the period 1981–2010 indicate that the central and northern part of Hungary and the entire territory of Vojvodina Province in the north of Serbia experienced the longest droughts, on average 55–60 days. In statistical terms, across Pannonia Basin once in 100 years drought may occur with an average duration of 56 days. Theoretically longest 100‐year droughts could be expected in the northern part of Hungary (up to 70 days), the eastern part of Romania (up to 68 days), and Serbia (up to 69 days). The 2‐year droughts are on the average duration of 3 weeks. Generated maps of the longest droughts in the basin may help to reduce agricultural risks due to global warming and other negative impacts of climate change. [ABSTRACT FROM AUTHOR]

The recent bushfires (2019–2020) in New South Wales (NSW) Australia were catastrophic by claiming human and animal lives, affecting ecosystems, destroying infrastructure, and more. Recent studies have investigated relationships between hydroclimatic signals and past bushfires, and very recently, a few commentary papers claimed drought and fuel moisture content as the probable causes for the widespread 2019–2020 bushfires. Therefore, in this study, a novel work of encompassing a wide range of factors attributing to the recent bushfires is presented. Empirical evidence‐based statistical methods are used to identify the hydroclimatic variables and geomorphic characteristics contributing to the 2019–2020 bushfires. The results highlight that ongoing drought, surface soil moisture (SSM), wind speed (WS10), relative humidity (RH), heat waves (HW), dead and live fuel moisture, and certain land cover types create favorable conditions for fire ignition and aid in fire propagation in different regions of the NSW state. The findings suggest that accounting for the above‐identified variables in bushfire prediction and monitoring system are crucial in avoiding such catastrophes in the future. The overarching application of this study is developing robust and more versatile fire protection planning and management. Plain Language Summary: Since the 2019–2020 Australian bushfires were catastrophic in terms of burnt area and severity, a detailed analysis of the primary causes is crucial. In this paper, several probable causes are tested statistically to establish their relationship with the burnt area. The results indicate that the ongoing drought, surface soil moisture, wind speed, relative humidity, heat waves, dead and live fuel moisture, and land cover with certain vegetation (particularly native eucalyptus and grazing land) are the primary causes of the widespread bushfire. These results are extremely critical in updating the current bushfire planning and management. Key Points: Empirical evidence‐based statistical approach is employed to assess the causes of the 2019–2020 bushfire in the NSW state of AustraliaDrought, soil moisture, wind speed, relative humidity, heat waves, fuel moisture, and certain land cover types drive bushfiresSlope did not contribute in bushfire occurrence and propagation [ABSTRACT FROM AUTHOR]

Salt accumulations in aquifers significantly affect and transform the conjunctive use of surface water and groundwater supporting irrigated agriculture. Salt accumulates in aquifers under many semi‐arid irrigated lands where pumping has lowered water levels enough to prevent drainage of saline groundwater from the basin. This paper provides new insights into optimal conjunctive management of groundwater pumping, recharge, surface water, and cropping patterns with groundwater salinity and hydrologic variability in an irrigated semi‐arid region, such as California's western San Joaquin Valley, reducing agricultural crop yields and revenues. A two‐stage stochastic quadratic model explores this problem to prescribe economically optimal crop mix and conjunctive water operation policies over a 10‐year period with probabilistic annual surface water availability, considering groundwater salinity's harm to crop yields. At low groundwater salinity, agricultural conjunctive use usually pumps most groundwater in drier years, supplied by additional recharge in wetter years. In contrast, at higher groundwater salinity, optimal conjunctive use pumps less in drier years while pumping more in wetter years, when more surface water allows more dilution of saltier groundwater. Reduced pumping in drier years substantially reduces a region's ability to support higher‐value perennial crops and reduces or eliminates lower‐value annual crops in dry years. Artificial recharge with fresh surface water in wetter years can have economic value from slowing groundwater salination which allows more groundwater use in drier years. Key Points: A two‐stage stochastic quadratic model estimates the economic impact of groundwater salinity on agriculture, especially with perennial cropsEconomically optimized groundwater management fundamentally changes with groundwater salinationArtificial recharge for aquifers with severe salt accumulation can reduce both loss of agricultural production and groundwater salinity [ABSTRACT FROM AUTHOR]

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

This paper focuses on the interdecadal variation in drought in Northeast China (NEC) in recent decades. Two dry and wet periods have occurred in the past 61 years (1950–2010). The mechanism underlying the interdecadal variation in drought in NEC is further analyzed; the results indicate that the direct cause is the interdecadal change of the Okhotsk High (OH). A strong (weak) OH is conducive (detrimental) to the convergence of cold air transported by northeast cold vortex and water vapor from the east of NEC, eventually leading to an increase (decrease) in precipitation. Furthermore, we seek to understand why OH displays such an interdecadal variation. The interdecadal increases and decreases in sea ice in the Barents Sea and the Kara Sea explain most of the interdecadal change of the OH. When more sea ice is present in this area, more energy is transferred eastward from the sea ice area to Northeast Asia, weakening the OH; in contrast, less sea ice strengthens the OH. Sensitivity simulations by Community Atmosphere Model, version 4 (CAM4) using sea ice forcing in the Barents Sea and the Kara Sea yield similar results to the observed data, further confirming our conclusion. The results of this paper provide a new understanding of the interdecadal variation in drought in NEC, and it may help to improve our ability to predict drought and provide early warning in the future. Key Points: The drought over Northeast China has significant interdecadal variability during the past decadesThe Okhotsk High acts as the direct factor causing interdecadal changes in NEC drought by affecting atmospheric circulationThe interdecadal increases and decreases in sea ice in the Barents Sea and the Kara Sea can modulate the Okhotsk High changes [ABSTRACT FROM AUTHOR]

Annual vegetation aboveground net primary productivity (ANPP) exhibits a non‐linear dependence on annual precipitation. A common pattern of non‐linearity, called asymmetry, arises when productivity responses in wet years are larger than declines in dry years. To date, ANPP asymmetry has been attributed primarily to vegetation water stress, an internal ecosystem response to precipitation and soil water availability. However, when quantified via the asymmetry index (AI) estimated from productivity measurements, the asymmetry can be a sampling artefact that arises from a positively skewed annual precipitation distribution. In this paper, we aimed to separate the sampling effect (from external precipitation variability) from the non‐linear response of the system (the internal ecosystem dynamics). We constructed a probabilistic model that integrates the precipitation distribution with the precipitation‐productivity response curve (PPT‐ANPP curve), derived using empirical formulae and a process‐based soil water balance model. The model was used to derive the probability density function of AI and to attribute its shape to the PPT distribution and the PPT‐ANPP response curve. The models were compared to data from 47 grasslands. Results demonstrated that positively skewed precipitation produces a positive AI as a statistical artefact. The non‐linear ecosystem PPT‐ANPP dependence can further enhance or dampen this statistical artefact. In all sites, the precipitation skew highly affected the probability of correctly identifying asymmetry using AI. Observed negative asymmetry arises from a larger soil water holding capacity and positive asymmetry from plant water stress. More robust statistical indicators of non‐linear ecological responses to climate variability are needed to improve ecosystem forecasts. [ABSTRACT FROM AUTHOR]

Although the environmental and economic impacts of drought have been widely studied, few large‐scale studies have examined the broader social impacts of drought. To fill this knowledge gap, the Australian Institute of Family Studies undertook the Regional and Rural Families Survey in 2007, when a significant part of Australia was experiencing a severe drought. This paper analyses that survey to measure the extent to which drought affects a range of economic, health and social outcomes. Drought is found to have a substantial negative economic and health impact on farmers and others employed in the agricultural sector. There is some evidence that groups that are not employed in agriculture are adversely affected, with a widespread loss of services in drought‐affected areas and some marginal labour market groups (e.g. carers) experiencing poor employment outcomes in a drought‐affected local economy. Policymakers need to take these impacts into account in designing effective responses to future droughts. [ABSTRACT FROM AUTHOR]

Summary: This paper focuses on and summarizes the animal welfare impacts of kangaroo (Macropus and Osphranter spp.) management and the need for a multidisciplinary approach to a complex problem for the best animal welfare outcomes. A concern for the welfare of kangaroos was the main motivator for preparation of the National Statement which underpins this special edition. Importantly, given that the primary concern of veterinarians is the health and welfare of all animals, the Australian Veterinary Association welfare and ethics special interest group (AVAWE) and the conservation biology special interest group (AVCB) have endorsed the National Statement. [ABSTRACT FROM AUTHOR]

Drought has become more common and severe in many parts of the world due to climate change. The effect of water stress on insect oviposition preference that is key determinant for their fitness has received less attention.Here, we examined how water stress may affect oviposition selection of Ostrinia furnacalis for maize plants in the greenhouse, and tested difference in volatile compounds emitted from treated maize, and electronantennogram and bioassay responses of O. furnacalis to the volatile profiles in maize plants.Ostrinia furnacalis were more prone to lay eggs on the well‐watered maize. Most plant volatile compounds differed significantly among the three water treatments, including increased emissions of β‐caryophyllene, (E)‐2‐hexenal, and linalool, and decreased emission of (Z)‐3‐hexen‐1‐ol when subjected to increasing intensity of drought.Varied volatile profiles of maize may drive oviposition decision of O. furnacalis, because O. furnacalis showed a clear oviposition preference for (Z)‐3‐hexen‐1‐ol, while not for β‐caryophyllene, (E)‐2‐hexenal, and linalool, at the concentration of 1000 ppm.This study advances understanding of drought effects on plant–insect interactions through volatile profiles. Our finding calls for attention to oviposition selection for insect pest management in agricultural settings, especially in regions under changing precipitation patterns. [ABSTRACT FROM AUTHOR]

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

Summary: Despite the importance of understanding plant growth, the mechanisms underlying how plant and fruit growth declines during drought remain poorly understood. Specifically, it remains unresolved whether carbon or water factors are responsible for limiting growth as drought progresses. We examine questions regarding the relative importance of water and carbon to fruit growth depending on the water deficit level and the fruit growth stage by measuring fruit diameter, leaf photosynthesis, and a proxy of cell turgor in olive (Olea europaea). Flow cytometry was also applied to determine the fruit cell division stage. We found that photosynthesis and turgor were related to fruit growth; specifically, the relative importance of photosynthesis was higher during periods of more intense cell division, while turgor had higher relative importance in periods where cell division comes close to ceasing and fruit growth is dependent mainly on cell expansion. This pattern was found regardless of the water deficit level, although turgor and growth ceased at more similar values of leaf water potential than photosynthesis. Cell division occurred even when fruit growth seemed to stop under water deficit conditions, which likely helped fruits to grow disproportionately when trees were hydrated again, compensating for periods with low turgor. As a result, the final fruit size was not severely penalized. We conclude that carbon and water processes are able to explain fruit growth, with importance placed on the combination of cell division and expansion. However, the major limitation to growth is turgor, which adds evidence to the sink limitation hypothesis. Significance Statement: The mechanism by which whole plants/organs reduce their growth during drought is still relatively little studied, the reduction of photosynthesis or turgor being the two major limitations considered. This paper aims at adding some evidence to the current debate on growth limitation thanks to a synchronous estimation of growth, turgor, and photosynthesis in olive trees (Olea europaea) exposed or not to water deficit using sensors and modeling with implications on process‐based models of forest and agriculture productivity. [ABSTRACT FROM AUTHOR]

Drought and water scarcity pose a risk to the economy, particularly sectors where water is a crucial input to the production process. This paper describes integrated simulations of water shortages from a dynamic national water resource systems model with a static economic input‐output (I‐O) model to assess total drought risk to the economy. To quantify the economic risks of drought and water scarcity, the analysis: (a) integrates a large ensemble of simulated meteorological droughts, propagated through a national hydrological model and water resource systems model to simulate water availability from reservoirs and groundwater; (b) assesses implications of restrictions on water availability for multiple water user categories, representing natural and human contributions to water scarcity; (c) investigates how water shortages propagate into economy‐wide direct and indirect impacts. The study focuses on England and Wales where the water supply system is considered under strain, with growing recognition of the economic risk of prolonged and widespread shortages. The direct Expected Annual Loss (EAL) to water users, averaged over an ensemble equivalent to 2800 years of synthetic daily weather, is estimated to be £11.7 million in the 2011 base‐year. Accounting for indirect economic losses results in a total EAL of £30.2 million in 2011. The most severe event simulated results in a total loss of £1.4 billion in 2011, equivalent to 0.11% of GVA. The analysis provides a framework to assess what the economically efficient level of system reliability should be, and for deciding upon appropriate water management regulations and strategic investments. Key Points: Simulated water availability from a national water resource system model are integrated with a macroeconomic model to assess drought riskThe use of a large ensemble of synthetic drought simulations supports the risk‐based analysis of direct and indirect economic lossesThe method supports national economic assessment of the implications of climate change and different water management strategies [ABSTRACT FROM AUTHOR]

Amazon tropical forests and the semiarid Northeast Brazil (NEB) region have registered very severe droughts during the last two decades, with a frequency that may have exceeded natural climate variability. Severe droughts impact the physiological response of Amazon forests, decreasing the availability to absorb atmospheric CO2, as well as biodiversity and increasing risk of fires. Droughts on this region also affect population by isolating them due to anomalous low river levels. Impacts of droughts over NEB region are related to water and energy security and subsistence agriculture. Most drought episodes over Amazonia and NEB are associated with El Niño (EN) events, anomalous warming over the Tropical North Atlantic (TNA), and even an overlapping among them. However, not all the dry episodes showed a large‐scale pattern linked to a canonical EN event or warm TNA episodes. For instance, dry episodes linked to EN events present distinct spatial patterns of precipitation anomalies depending on EN type (Central‐Pacific vs. Eastern‐Pacific EN), and NEB region experienced a severe drought in 2012 that is not attributed to EN or warm TNA events. Even in the case of the strong EN in 2015/16, some regional impacts have not been explained by EN contribution. This paper discusses the effects of CP and EP EN events, and the role of warm TNA events on tropical Walker and Hadley circulation leading to drought over Amazonia and NEB regions. [ABSTRACT FROM AUTHOR]

The Demnitzer Millcreek catchment (DMC), is a 66 km2 long‐term experimental catchment located 50 km SE of Berlin. Monitoring over the past 30 years has focused on hydrological and biogeochemical changes associated with de‐intensification of farming and riparian restoration in the low‐lying landscape dominated by rain‐fed farming and forestry. However, the hydrological function of the catchment, which is closely linked to nutrient fluxes and highly sensitive to climatic variability, is still poorly understood. In the last 3 years, a prolonged drought period with below‐average rainfall and above‐average temperatures has resulted in marked hydrological change. This caused low soil moisture storage in the growing season, agricultural yield losses, reduced groundwater recharge, and intermittent streamflows in parts of an increasingly disconnected channel network. This paper focuses on a two‐year long isotope study that sought to understand how different parts of the catchment affect ecohydrological partitioning, hydrological connectivity and streamflow generation during drought conditions. The work has shown the critical importance of groundwater storage in sustaining flows, basic in‐stream ecosystem services and the dominant influence of vegetation on groundwater recharge. Recharge was much lower and occurred during a shorter window of time in winter under forests compared to grasslands. Conversely, groundwater recharge was locally enhanced by the restoration of riparian wetlands and storage‐dependent water losses from the stream to the subsurface. The isotopic variability displayed complex emerging spatio‐temporal patterns of stream connectivity and flow duration during droughts that may have implications for in‐stream solute transport and future ecohydrological interactions between landscapes and riverscapes. Given climate projections for drier and warmer summers, reduced and increasingly intermittent streamflows are very likely not just in the study region, but in similar lowland areas across Europe. An integrated land and water management strategy will be essential to sustaining catchment ecosystem services in such catchment systems in future. [ABSTRACT FROM AUTHOR]

Water scarcity has emerged as a potential risk for mining operations. High capital spending for desalination and water conflicts leading to asset stranding have recently occurred. Investors in mining companies are interested in the exposure to such risks across portfolios of mining assets (whether the practical at-site consequences are foregone production, higher OPEX and CAPEX and ensuing lost revenues, or asset-stranding). In this paper, an index of the potential financial exposure of a portfolio is developed and its application is illustrated. Since the likely loss at each mine is hard to estimate a priori, one needs a proxy for potential loss. The index considers drought duration, severity and frequency (defined by a return-level in years) at each mining asset, and provides a measure of financial exposure through weighing of production or Net Asset Value. Changes in human needs are not considered, but are relevant, and could be incorporated if global data on mine and other water use were available at the appropriate resolution. Potential for contemporaneous drought incidence across sites in a portfolio is considered specifically. Through an appropriate choice of drought thresholds, an analyst can customize a scenario to assess potential losses in production value or profits, or whether conflicts could emerge that would lead to stranded assets or capital expenditure to secure alternate water supplies. Global climate data sets that allow a customized development of such an index are identified, and selected mining company portfolios are scored as to the risk associated with one publicly available drought index. [ABSTRACT FROM AUTHOR]

Intensification of the Earth's hydrological cycle amplifies the interannual variability of precipitation, which will significantly impact the terrestrial carbon (C) cycle. However, it is still unknown whether previously observed relationship between soil respiration (Rs) and precipitation remains applicable under extreme precipitation change. By analyzing the observations from a much larger dataset of field experiments (248 published papers including 151 grassland studies and 97 forest studies) across a wider range of precipitation manipulation than previous studies, we found that the relationship of Rs response with precipitation change was highly nonlinear or asymmetric, and differed significantly between grasslands and forests, between moderate and extreme precipitation changes. Response of Rs to precipitation change was negatively asymmetric (concave‐down) in grasslands, and double‐asymmetric in forests with a positive asymmetry (concave‐up) under moderate precipitation changes and a negative asymmetry (concave‐down) under extreme precipitation changes. In grasslands, the negative asymmetry in Rs response was attributed to the higher sensitivities of soil moisture, microbial and root activities to decreased precipitation (DPPT) than to increased precipitation (IPPT). In forests, the positive asymmetry was predominantly driven by the significant increase in microbial respiration under moderate IPPT, while the negative asymmetry was caused by the reductions in root biomass and respiration under extreme DPPT. The different asymmetric responses of Rs between grasslands and forests will greatly improve our ability to forecast the C cycle consequences of increased precipitation variability. Specifically, the negative asymmetry of Rs response under extreme precipitation change suggests that the soil C efflux will decrease across grasslands and forests under future precipitation regime with more wet and dry extremes. [ABSTRACT FROM AUTHOR]

Long‐term droughts, closely linked to oceanic climate variability, are a great threat to the global economy, as well as food and water security. Skillful predictions will provide enormous benefit to the human societies. By taking advantages of the newly available decadal hindcasts and target experiments from the Coupled Model Intercomparison Project phase 6 (CMIP6), this paper evaluates potential predictability and decadal prediction skill of droughts over major river basins across the globe. The results show that the CMIP6 drought prediction is skillful within 3–6 years, and the skill score is 11% higher than CMIP5 over 47% river basins. Prediction skill is enhanced by 15% (16%) over 47% (49%) basins, forced by the actual sea surface temperature over tropical eastern Pacific (North Atlantic). Our findings imply the possibility of drought adaptation based on skillful decadal prediction with sufficient lead time. Plain Language Summary: A reliable drought prediction is helpful to reduce adverse impact and economic loss by increasing the preparedness. Although operational seasonal drought prediction has been applied over the world, decadal prediction is still a grand challenge due to limited knowledge about the predictability and mechanism of long‐term drought. Here we apply the decadal hindcasts from CMIP6 to evaluate the probabilistic decadal prediction skill of drought and analyze the impacts of sea surface temperature on the prediction through CMIP6 pacemaker experiments. Our results show the skillful prediction can be found over half of the major river basins at 1–4 years lead. In addition, incorporating the actual sea surface temperature in tropical eastern Pacific or North Atlantic can efficiently enhance the drought prediction skill over 48% basins as well. This study suggests that it is possible to provide useful long‐term drought information for water and agricultural management through using coupled models, but the skill can be improved further by optimization of initialization and ensemble methods. Key Points: Probabilistic predictions of basin‐scale droughts by dynamical models are skillful within 3–6 years across the globeThere is an 11% improvement from CMIP6 models compared to CMIP5 over 47% of the largest 177 global river basinsSSTs in the tropical eastern Pacific and the North Atlantic have critical importance for the success over about 48% basins [ABSTRACT FROM AUTHOR]

Reliable information on the likelihood of drought is of crucial importance in agricultural planning and humanitarian decision‐making. Acting based upon probabilistic forecasts of drought, rather than responding to prevailing drought conditions, has the potential to save lives, livelihoods and resources, but is accompanied by the risk of acting in vain. The suitability of a novel forecasting tool is assessed in the present paper in terms of its ability to provide skilful information of the likelihood of drought impacts on crops and pasture within a timeframe that allows for anticipatory action. The Tropical Applications of Meteorology using SATellite data—AgriculturaL Early waRning sysTem (TAMSAT‐ALERT) tool provides forecasts of seasonal mean soil moisture and the water requirement satisfaction index (WRSI). TAMSAT‐ALERT metrics were found to be strongly correlated with pasture availability and maize yield in Kenya and provided skilful forecasts early in key seasons, allowing sufficient time for preparatory actions. Incorporating TAMSAT‐ALERT forecasts in a layered approach, with actions triggered by spatiotemporally varying triggers and fundamentally informed by humanitarian actors, will provide reliable information on the likelihood of drought, ultimately mitigating food insecurity.Anticipatory drought‐risk management is gaining considerable attention owing to its potential to improve food security. The suitability of Tropical Applications of Meteorology using SATellite data—AgriculturaL Early waRning sysTem (TAMSAT‐ALERT) soil moisture and water requirement satisfaction index (WRSI) forecasts are assessed in terms of their ability to provide skilful information on the likelihood of drought impacts within a timeframe that allows for anticipatory action. Triggers based on TAMSAT‐ALERT forecasts and developed in collaboration with humanitarian actors present promise for use in anticipatory drought‐risk management. [ABSTRACT FROM AUTHOR]

Evidence suggests that catchment state variables such as groundwater can exhibit multiyear trends. This means that their state may reflect not only recent climatic conditions but also climatic conditions in past years or even decades. Here we demonstrate that five commonly used conceptual "bucket" rainfall‐runoff models are unable to replicate multiyear trends exhibited by natural systems during the "Millennium Drought" in south‐east Australia. This causes an inability to extrapolate to different climatic conditions, leading to poor performance in split sample tests. Simulations are examined from five models applied in 38 catchments, then compared with groundwater data from 19 bores and Gravity Recovery and Climate Experiment data for two geographic regions. Whereas the groundwater and Gravity Recovery and Climate Experiment data decrease from high to low values gradually over the duration of the 13‐year drought, the model storages go from high to low values in a typical seasonal cycle. This is particularly the case in the drier, flatter catchments. Once the drought begins, there is little room for decline in the simulated storage, because the model "buckets" are already "emptying" on a seasonal basis. Since the effects of sustained dry conditions cannot accumulate within these models, we argue that they should not be used for runoff projections in a drying climate. Further research is required to (a) improve conceptual rainfall‐runoff models, (b) better understand circumstances in which multiyear trends in state variables occur, and (c) investigate links between these multiyear trends and changes in rainfall‐runoff relationships in the context of a changing climate. Key Points: Environmental state variables such as groundwater display multiyear trends in response to sustained climate anomaliesWe show that five commonly used conceptual "bucket" rainfall runoff models are unable to replicate such trendsBecause of this, the models fail to extrapolate realistically to different climatic conditions, compromising runoff projections Plain Language Summary: It is common in science to use a mental picture or metaphor that simplifies a complex phenomenon. A common metaphor used for a water supply catchment is that of a leaky bucket. When it rains, the bucket fills up; when it does not rain for a while, the bucket empties due to evaporation and water used by trees; and leaking water is like river flow. Computer models based on variants of this metaphor are common and can provide predictions of how much streamflow might occur under future scenarios. This paper explores limitations of the bucket metaphor and associated models. Recently, during a 13‐year drought in Australia, river catchments gradually started to dry up. With each passing year, the depth to groundwater increased gradually as the water used by trees was not replenished by rainfall. We compare this long, slow behavior to that of five commonly used "bucket" models. The models do not show the long, slow drying up—they only show the seasonal ups and downs, and their predictions of streamflow over the drought are poor. This is surprising, and it means we should choose our models carefully and seek out models that can simulate this behavior and its impact on streamflow. [ABSTRACT FROM AUTHOR]

Recent severe drought events have occurred over the Ogallala Aquifer region (OAR) during the period 2011–2015, creating significant impacts on water resources and their use in regional environmental and economic systems. The changes in terrestrial water storage (TWS), as indicated by the Gravity Recovery and Climate Experiment (GRACE), reveals a detailed picture of the temporal and spatial evolution of drought events. The observations by GRACE indicate the worst drought conditions occurred in September 2012, with an average TWS deficit of ~8 cm in the northern OAR and ~11 cm in the southern OAR, consistent with precipitation data from the Global Precipitation Climatology Project. Comparing changes in TWS with precipitation shows the TWS changes can be predominantly attributable to variations in precipitation. Power spectrum and squared wavelet coherence analysis indicate a significant correlation between TWS change and the El Nino‐Southern Oscillation, and the influence of equatorial Pacific sea surface temperatures on TWS change is much stronger in the southern OAR than the northern OAR. The results of this study illustrate the value of GRACE in not just the diagnosis of significant drought events, but also in possibly improving the predictive power of remote signals that are impacted by nonregional climatic events (El Nino), ultimately leading to improved water resource management applications on a regional scale. Editor's note: This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series. Research Impact Statement: The value of GRACE is not just in the diagnosis of drought events but also in the improvement of the predictive power of remote signals, then improving water resource management on a regional scale. [ABSTRACT FROM AUTHOR]

This paper offers a snapshot of the 2015 El Niño drought among Min people in Papua New Guinea's West Sepik and Western Provinces. Local assessments of food, water, and health show variation between locations, but with an overall tendency for the drought's effects to spread from lower to higher elevations as the drought progresses. This zone is in the hinterland of the Ok Tedi Mine, and the drought's regional impact was intensified by Ok Tedi's abrupt closure when low water in the Fly River stopped shipments of concentrate and cut off fuel and food supplies. The decision to close the mine was accompanied by the mandatory 'repatriation' of workers and their families to 'home' communities in the drought-stricken hinterland. This, combined with deteriorating regional links, has eroded the capacity of Min communities to weather the drought, suggesting that we must look beyond the garden when calculating El Niño's costs. [ABSTRACT FROM AUTHOR]

Aim: Shifting climates are reshaping ecosystems globally and are projected to intensify over the coming century. Understanding how biodiversity will respond to these shifts is crucial for developing effective climate adaptation measures. We generate predictive models built from long‐term data to hindcast historic fluctuations in small mammal abundances as they have responded to shifting rainfall and fire conditions. This data set serves as the basis for predicting historical variations (hindcasting) in small mammal abundances, allowing us to examine their responses to decadal changes in fire and rainfall conditions within our study landscape. Location: Australia (Victoria). Taxa: Small mammals (Mammalia). Time Period: 1970–2022. Methods: Small mammal abundance was surveyed at 36 long‐term trapping sites and modelled against coinciding fire history, vegetation productivity and rainfall using generalized additive mixed models. Six species were then used in predictive modelling against these variables for the decades preceding our monitoring programme (1970–2007). Results: All species abundances increased with higher rainfall. Time since fire was also an important variable in all but one species model, with species displaying varying responses to time since fire. Hindcasting predictions for small mammal abundances varied with some species showing marked declines over time. Clear trends emerged, indicating more volatile population fluctuations in response to intensified fire and rainfall extremes in the 21st century. This suggests that periods of higher rainfall and less frequent fire events in the decades preceding our monitoring period supported higher and more stable small mammal abundances. Conclusions: Native species show distinct sensitivity to the combined effects of drought and fire, which has occurred in recent times. Intensification of these drivers has caused increased volatility in small mammal abundances with low abundance extremes occurring more frequently. [ABSTRACT FROM AUTHOR]

Drought can cause significant disruption to forest ecosystems and may have long‐term impacts on the structure and function of ecosystems after the end of drought. This is the key to quantifying the ability of ecosystem to respond to disturbance events by comprehensively analyzing the impact of drought on vegetation, the lagged effect, and ecosystem resilience to drought. This article takes broad‐leaved forests and coniferous forests in multiple temperature zones of China as the object of study, using distributed lagged nonlinear model (DLNM) to construct a systematic method. Our results show that the main sensitive lagged time for coniferous forests and broad‐leaved forests is the first 3 months in various temperature zones, with the strongest lagged effect in the month when the drought incidents occur. Coping capacity represents ecosystems to remain stable during droughts, and we quantified the indicator by the ratio of the resistance (the difference between NDVI value before the drought and during the drought) to recovery (the difference between NDVI value after the drought and during the drought). When dealing with intensive drought events, the coping capacity of subtropical broad‐leaved forests (−0.67) and tropical broad‐leaved forests (−0.88) exhibit the strongest coping capacity (value tends to −1). Overall, vegetation growth in subtropical and tropical regions is less affected by drought compared to temperate and cold temperate zones. The research results help us understand the comprehensive impact of drought on vegetation and the strategies for different vegetation to cope with drought. [ABSTRACT FROM AUTHOR]

Scenarios have emerged as valuable tools in managing complex human‐natural systems, but the traditional approach of limiting focus on a small number of predetermined scenarios can inadvertently miss consequential dynamics, extremes, and diverse stakeholder impacts. Exploratory modeling approaches have been developed to address these issues by exploring a wide range of possible futures and identifying those that yield consequential vulnerabilities. However, vulnerabilities are typically identified based on aggregate robustness measures that do not take full advantage of the richness of the underlying dynamics in the large ensembles of model simulations and can make it hard to identify key dynamics and/or storylines that can guide planning or further analyses. This study introduces the FRamework for Narrative Storylines and Impact Classification (FRNSIC; pronounced "forensic"): a scenario discovery framework that addresses these challenges by organizing and investigating consequential scenarios using hierarchical classification of diverse outcomes across actors, sectors, and scales, while also aiding in the selection of scenario storylines, based on system dynamics that drive consequential outcomes. We present an application of this framework to the Upper Colorado River Basin, focusing on decadal droughts and their water scarcity implications for the basin's diverse users and its obligations to downstream states through Lake Powell. We show how FRNSIC can explore alternative sets of impact metrics and drought dynamics and use them to identify drought scenario storylines, that can be used to inform future adaptation planning. Plain Language Summary: Scenario analysis is a useful tool for assessing the impacts of future conditions or alternative strategies. Focusing on a small number of predetermined scenarios can, however, limit our understanding of key uncertainties, and fail to represent diverse stakeholder impacts. Approaches such as exploratory modeling have been developed to address these issues by exploring a wide range of possible futures and system perspectives. These approaches often involve large simulation experiments with their own interpretability challenges. So, on one hand, we recognize the need to utilize large ensembles of hypothesized changes, but on the other hand, each additional dimension considered makes it more difficult to convey actionable insights. We introduce the FRamework for Narrative Storylines and Impact Classification (FRNSIC; pronounced "forensic"), a scenario discovery framework that helps users identify scenario storylines that capture key system dynamics and as well as important outcomes. We demonstrate its application to the Upper Colorado River Basin, focusing on decadal droughts and their water scarcity implications for the basin's diverse users and its obligations to downstream states through Lake Powell. We explore alternative impact metrics and dynamics, identifying scenario storylines with significant impacts, which can be used in future planning efforts to adapt to these stressed conditions. Key Points: Introduce framework for discovery of scenario storylines describing diverse stakeholder impacts and consequential dynamicsDemonstrate the framework in the Upper Colorado River Basin with hundreds of stakeholders and complex human‐natural system interactionsThe framework improves understanding and selection of drought scenario storylines through their effects on user‐ and basin‐scale impacts [ABSTRACT FROM AUTHOR]

The C4 Poaceae are a diverse group in terms of both evolutionary lineage and biochemistry. There is a distinct pattern in the distribution of C4 grass groups with aridity; however, the mechanistic basis for this distribution is not well understood. Additionally, few studies have investigated the functional strategies of co‐occurring C4 grass species for dealing with aridity in their natural environments. We explored the coordination of leaf‐level gas exchange, water use, and morphology among five co‐occurring semiarid C4 grasses belonging to divergent clades, biochemical subtypes, and size classes at three sites along a natural aridity gradient. More specifically, we measured predawn and midday water potential, stomatal conductance, water use efficiency, and photosynthesis. Leaf tissue was also collected for the analysis of stable isotopes of carbon and oxygen as well as for measurement of specific leaf area (SLA) and leaf width. Species differences in responsiveness of stomata to changes in vapor pressure deficit (VPD) were also assessed. It was expected that NAD‐me species would maintain higher rates of photosynthesis, higher water use efficiency, and have more responsive stomata than other co‐occurring species based on observed biogeographic patterns and past greenhouse studies. We found that Aristidoideae and Chloridoideae NAD‐me‐type grasses had greater stomatal sensitivity to VPD, consistent with a more isohydric strategy. However, midgrasses had both greater apparent water access and water use efficiency, regardless of subtype or lineage. PCK‐type species had less responsive stomata and maintained lower levels of photosynthesis with increasing aridity. There were strong interspecific differences in δ13C, leaf width, and SLA; however, these were not significantly correlated with water use efficiency. C4 grasses in our study did not fit discretely into functional groups as defined by lineage, biochemistry, or size class. Interspecific differences, evolutionary legacy, and biochemical pathway are likely to interact to determine water use and photosynthetic strategies of these plants. Control of water loss via highly responsive stomata may form the basis for dominance of certain C4 grass groups in arid environments. These findings build on our understanding of contrasting strategies of C4 grasses for dealing with aridity in their natural environments. [ABSTRACT FROM AUTHOR]

Identifying areas expected to remain buffered from climate change and maintain biodiversity and ecological function (i.e., climate refugia) is important for climate adaptation planning. As structurally diverse transitional zones between terrestrial and aquatic environments, riparian areas are often biological hotspots and provide critical corridors for species movement, particularly in arid and semi‐arid regions. In our study region in the western and central USA, identifying riparian areas that could serve as climate refugia is a priority for wildlife managers. We mapped areas with connected riparian habitats that, based on landscape diversity and projected changes in summer temperatures and landscape runoff, are expected to serve as climate refugia. To incorporate uncertainty and balance the need for near‐ and long‐term planning, we mapped potential refugia for 2 future time periods (2040–2069, 2070–2099) based on 2 climate models that represented divergent but plausible climate outcomes. The approach we developed is not constrained by physiology or behavior of target species and can be used to identify areas expected to fare comparatively well under a wide range of future climate scenarios. Our approach can also be used to identify areas where restoration could increase riparian connectedness and climate resilience. [ABSTRACT FROM AUTHOR]

In this study, we present a machine‐learning model capable of predicting food insecurity in the Horn of Africa, which is one of the most vulnerable regions worldwide. The region has frequently been affected by severe droughts and food crises over the last several decades, which will likely increase in future. Therefore, exploring novel methods of increasing early warning capabilities is of vital importance to reducing food‐insecurity risk. We present a XGBoost machine‐learning model to predict food‐security crises up to 12 months in advance. We used >20 data sets and the FEWS IPC current‐situation estimates to train the machine‐learning model. Food‐security dynamics were captured effectively by the model up to 3 months in advance (R2 > 0.6). Specifically, we predicted 20% of crisis onsets in pastoral regions (n = 96) and 20%–50% of crisis onsets in agro‐pastoral regions (n = 22) with a 3‐month lead time. We also compared our 8‐month model predictions to the 8‐month food‐security outlooks produced by FEWS NET. Over a relatively short test period (2019–2022), results suggest the performance of our predictions is similar to FEWS NET for agro‐pastoral and pastoral regions. However, our model is clearly less skilled in predicting food security for crop‐farming regions than FEWS NET. With the well‐established FEWS NET outlooks as a basis, this study highlights the potential for integrating machine‐learning methods into operational systems like FEWS NET. Plain Language Summary: In the face of increasing droughts and food crises, this study explored the use of machine learning to provide predictions of food crises in the Horn of Africa, up to 12 months in advance. We used an algorithm called "XGBoost," which we fed with over 20 data sets of potential food security drivers. After training the model, we found that food security dynamics were accurately predicted up to 3 months in advance, especially in pastoral and agro‐pastoral regions. The model accurately predicted 20% of crisis onsets in pastoral areas and 20%–50% in agro‐pastoral regions with a 3‐month lead time. In agro‐pastoral and pastoral regions, our machine learning algorithm showed a similar performance to the established early warning system from FEWS NET. The machine‐learning model did not show good performance in crop‐farming areas. Nonetheless, this study underscores the potential of integrating machine‐learning methods into existing operational systems like FEWS NET. By doing so, it paves the way for improved early warning capabilities, crucial in mitigating the looming threat of food insecurity in the Horn of Africa. Key Points: A machine‐learning model is presented to predict food‐security crises in the Horn of AfricaThe model demonstrates high overall performance, and performs similarly to FEWS NET outlooks in the (agro‐) pastoral regionsThis study can be utilized to integrate machine learning into existing early warning systems, thereby creating hybrid solutions for the future [ABSTRACT FROM AUTHOR]

Martin's laboratory studies plant-environment interactions at the whole-plant, cellular and molecular levels focusing on the mechanisms by which plants respond to changes in their environment including drought, elevated carbon dioxide and ozone stress. Agricultural sustainability, drought, elevated carbon dioxide (CO2), environmental stress, food security, ozone stress, plant stress, plant-environment interactions Keywords: agricultural sustainability; drought; elevated carbon dioxide (CO2); environmental stress; food security; ozone stress; plant stress; plant-environment interactions EN agricultural sustainability drought elevated carbon dioxide (CO2) environmental stress food security ozone stress plant stress plant-environment interactions 29 31 3 06/05/21 20210701 NES 210701 What inspired your interest in plant science?. [Extracted from the article]

Water availability to meet consumptive use demands over the next century in the Lower Basin of the Colorado River in the southwestern United States is considered under alternative climate and policy scenarios. Modeling reservoir storage and annual releases under scenario alternatives demonstrates that policy can only modestly mitigate losses from potential long run streamflow reductions. The major reservoirs Lake Powell and Lake Mead are treated as composite storage, and Upper Basin depletions are held constant over 97 annual periods beginning with calendar year 2020. Averaged over six climate change scenarios with mean inflow reductions of 22% (reaching 45% by end of century) estimated mean releases fall by 16% to 23% from year 2020 levels depending on decision scenario. Mean releases under the existing Law of the River are 6.1% below the benchmark decision scenario which uses a perfect forecast of future flows. This is largely the result of evaporation losses because reservoir storage across climate scenarios is about double that of the benchmark. In contrast, a decision scenario based on next year and future mean flow expectations shows a release reduction of only 2.6% below the benchmark, and a 2.8% decrease in standard deviation. Across the three decision scenarios, future reservoir storage is well below capacity in almost all years, and under the three higher impact climate scenarios mean storage across the century is only 35% to 40% of capacity. [ABSTRACT FROM AUTHOR]

Plants have evolved a multitude of adaptations to survive extreme conditions. Succulent plants have the capacity to tolerate periodically dry environments, due to their ability to retain water in a specialized tissue, termed hydrenchyma. Cell wall polysaccharides are important components of water storage in hydrenchyma cells. However, the role of the cell wall and its polysaccharide composition in relation to drought resistance of succulent plants are unknown. We investigate the drought response of leaf‐succulent Aloe (Asphodelaceae) species using a combination of histological microscopy, quantification of water content, and comprehensive microarray polymer profiling. We observed a previously unreported mode of polysaccharide and cell wall structural dynamics triggered by water shortage. Microscopical analysis of the hydrenchyma cell walls revealed highly regular folding patterns indicative of predetermined cell wall mechanics in the remobilization of stored water and the possible role of homogalacturonan in this process. The in situ distribution of mannans in distinct intracellular compartments during drought, for storage, and apparent upregulation of pectins, imparting flexibility to the cell wall, facilitate elaborate cell wall folding during drought stress. We conclude that cell wall polysaccharide composition plays an important role in water storage and drought response in Aloe. This paper highlights the significance of structured cell wall folding in the drought‐stressed hydrenchyma tissue of Aloe helenae and Aloe vera. Dynamic changes in cell wall polysaccharide composition, especially mannan polymers, reveal a potential mechanism for plant leaf succulence. [ABSTRACT FROM AUTHOR]

Gibberellins (GAs) is one kind of important endogenous hormone in plants that regulates vegetative and reproductive growth of plants. GA2ox is a class of oxidase that plays a regulatory role in the third stage of GAs synthesis. In this paper, we cloned the GhGA2ox1 gene from an upland cotton (Gossypium hirsutum L. var. CCRI49). The results showed that the CDS of GhGA2ox1 is 996 bp, which encode 331 amino acids, which has high homology with GhGA2ox2 and NtGA2ox1. The quantitative real‐time PCR showed that under the conditions of salt and drought stress, the expression of GhGA2ox1 had a higher upregulation in root, stem, and leaf of transgenic plant, compared with non‐transgenic plant. Cotton plant that overexpressed the GhGA2ox1 gene showed higher drought and salt tolerance than non‐transgenic cotton plant, and these results were supported by data of higher free proline, chlorophyll, and relative water content in transgenic plant compared with control plant. The expression level of antiretroviral genes, including GhEREB2, GhDREB1, GhWRKY5, and GhP5CS, was upregulated to varying degrees in transgenic plant. The above results indicate that overexpressed GhGA2ox1 gene can increases the tolerance to respond to drought and salt stress in upland cotton. [ABSTRACT FROM AUTHOR]

The paper estimates the impacts of risk-reducing government programs on the use of conservation tillage (no-till and other conservation tillage) practices in agriculture. Conservation tillage can be used to reduce production risk from weather shocks. However, subsidized crop insurance and disaster payments also reduce risk through financial assistance. The paper examines the extent to which risk-reducing tillage practices and government programs are substitutes for each other. The economic model shows that a decline in average weather conditions increases the use of conservation tillage. The economic model also shows that the impact of weather risk and risk aversion on risk-reducing practices like conservation tillage are ambiguous. The effect depends on the degree that losses are offset by government payments. The paper uses county-level tillage practice data from the Conservation Tillage Information Center for the three-state region of Iowa, Nebraska, and South Dakota. Results are estimated using instrumental variables and spatial panel data techniques. Instruments for the program participation and payment data include political variables and weather data. The empirical analysis shows that recent disaster and indemnity payments are associated with an increase in the use of no-till and a decrease in the use of other conservation till. Results also show that producers in counties with recent drought and food events are more likely to use other conservation tillage. The results imply that there may be unintended impacts of changes to agricultural policies like disaster payments and crop insurance on the use of on-farm conservation practices. [ABSTRACT FROM AUTHOR]