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• GNSS-PWV time series are computed using 44 GNSS stations in Andalucía and ERA5 temperature and pressure data. • GNSS-PWV and ERA5-PWV are used to compute SPCI time series. • The SPCI generally shows high correlation with the SPEI, with better results for ERA5-SPCI than GNSS-SPCI. • The SPCI outperforms SPI for a limited geographical region and 24-month timescale. In this paper the Standardized Precipitation Conversion Index (SPCI), a PWV-based drought index, has been computed using GNSS and ERA5 PWV and its performance has been tested with respect to the Standardized Precipitation Evapotranspiration Index (SPEI) in Southern Spain. One of the climatic features of this area is the low correlation level between PWV and precipitation, in contrast with other areas in which SPCI has been previously tested. The GNSS-SPCI has been derived from validated ZTD time series estimated from local GNSS permanent stations' data. All the needed meteorological values were derived from ERA5, excepting precipitation values and SPEI-SPI values which were extracted from a national high-resolution dataset. The resulting SPCI time series have shown high correlation coefficients with respect to the SPEI. The use of longer SPCI time series allowed by ERA5 model has provided the most coherent results, suggesting that the ERA5-PWV data can be interesting to overcome problems caused by the short timespan of GNSS time series in SPCI computation. In general, high correlation coefficients have been obtained compared to global results from previous studies. This shows that, even for regions with low correlation levels between PWV and precipitation, the SPCI can have an interesting potential for drought monitoring. The SPCI was found to perform better on higher timescales (12 and 24 months). The performance of SPCI has also been compared that of the SPI: SPCI is able to outperform SPI for the 24-month timescale for a limited geographical region. This supports that the inclusion of PWV data in drought monitoring indices could be promising and is worth keeping to be investigated. [ABSTRACT FROM AUTHOR]

In shaping environmental policy, knowledge is power. Yet the opposite is also true. Control over the absence of knowledge facilitates certain policy outcomes being deflected, obscured, or magnified in a way that furthers political, personal, or institutional ends. Applying previous work on ignorance studies and agnotology to the development of Cambodian drought policy, the paper demonstrates how data gaps, restrictions on data sharing, and obstacles to data dissemination serve institutional interests and shape policy development. It proceeds in three parts, each reflecting one aspect of drought sensing in Cambodia and more broadly: hydrological, meteorological, and agricultural. First, how data on the Mekong River is shaped by regional geopolitics. Second, how national rainfall and flood data reflect the political geography of sub-national government administration. Third, how this multi-scalar landscape of political and institutional interests links data generation, data dissemination and adaptation policy, closing certain adaptation pathways, whilst opening others. • This paper examines data gaps, restrictions on data sharing, and restrictions on data dissemination. • This paper presents an agnotological perspective on the politics of data gaps and environmental policy generation. • It shows that drought policy development in Cambodia is influenced by control over environmental generation and circulation. [ABSTRACT FROM AUTHOR]

• The matrix representation of grey possibility function is provided. • The solution method of possibility function's turning points is given. • The "maximum criterion" decision paradox is solved. • A variable stage self-correcting grey clustering model is proposed. • The meteorological drought grade of 17 stations in china henan province is evaluated. The grey clustering model based on the possibility function is frequently used in system evaluation, but the setting of the possibility function is frequently subjective, which results in the weak credibility of the clustering results. In addition, the "maximum criterion" decision paradox of the model has fuzzy boundaries, making the clustering process impossible to program. Based on this, the possibility function is represented as a matrix in the paper, and the possibility function is calculated by an optimization model to guarantee the objectivity of the clustering results. A variable stage self-correcting grey clustering model is built by using the kernel weight transformation as the primary tool, "entropy subtraction" as the signal of the decision paradox, and "entropy non-subtraction" as the model's termination signal. The model's Matlab source code is provided to reduce the complexity of the model. The illustration and comparative analysis demonstrate the model's logic and efficacy. Using the model for the evaluation of the meteorological drought grade in Henan Province can offer a fresh perspective for meteorological departments to make choices and assessments. [ABSTRACT FROM AUTHOR]

Monthly rainfall data for Blue Nile Basin (BNB) were obtained from the Ethiopian Meteorological Authority (1950–2018). Long-term trends in the BNB annual and monthly rainfall are investigated in this study. The challenges of the paper were to explore the impact of climate change on the study area using sound practical methods. The paper used the widely used statistical methods to find precisely the significance of the impact of climate change rainfall variability and distribution both spatially and temporally in the BNB. The statistical significance of the trend in the study is calculated by the Mann-Kendall (MK) test. Data were analyzed using the coefficient of variation, anomaly index, and precipitation concentration index. The coefficient of variation is high in Kiremt rainfall which implies more inter-annual variability of Bega rainfall than Kiremt (Coefficient of Variation (CV): Bega˃ Belg˃ Kiremt season). Based on Precipitation Concentration Index (PCI) value, the number of moderate concentration years (89.9%) has been increasing through time and the study area has encountered successive years of drought. The results showed that the annual, Bega, Belg, and Kiremt precipitation over the whole of BNB is significantly decreasing except Bega season with a magnitude of 36.38, 3.8, 7.8, and 24.7 mm per decade respectively. The rainfall in the study area is characterized by a high CV. Moreover, prolonged droughts have become common which adversely affects the agricultural system. It was also found that very low values of rainfall anomalies that correspond to severe droughts were associated with El Niño Southern Oscillation (ENSO) events. [ABSTRACT FROM AUTHOR]

The purpose of this study is to analyze the spatiotemporal variations in drought in Serbia over recent decades using the standardized precipitation evapotranspiration index (SPEI). The analysis is performed for time series of 1-, 3-, 6-, and 12-month SPEI indices (SPEI-01, SPEI-03, SPEI-06 and SPEI-12, respectively) calculated using the E -OBS gridded dataset with a horizontal resolution of 0.1° for the period of 1950–2022. In general, it was found that negative SPEI trends prevailed in Serbia for all months and all analyzed SPEI timescales, indicating a more frequent appearance of droughts in recent decades. Moreover, for a large majority of month-timescale combinations, the area with a negative trend was larger than the area with a positive trend. For several reasons, we focused on the SPEI for August. First, the SPEI for this month shows one of the most pronounced negative trends, which is rather consistent over different timescales and consistent in terms of the area over which the trend was found to be significant. Statistically significant negative trends of SPEI-03, −06 and − 12 for August were found over 11, 17 and 38% of the country area, respectively. To better understand the trends and changes in the SPEI for August, focusing on extreme and severe drought events, an innovative trend analysis (ITA) was applied. It was found that the occurrence of both extreme and severe SPEI drought categories has doubled over the last thirty years in comparison with the previous thirty-year period. Additionally, more frequent transitions from neutral and wet categories to dry categories were observed through an application of the Markov chain. Second, the special focus on SPEI-03, −06 and − 12 for August was motivated by the fact that we found a significant correlation between these index values and the annual maize production in Serbia, indicating that the SPEI for August can be useful for the assessment of drought impact on agriculture. To better understand interannual variability and long-term trends, this paper also explores the relations between the SPEI over Serbia and large-scale circulation patterns, together with general global and continental warming trends. Our findings indicate that drought changes over recent decades may be driven by the interplay of long-term warming and large-scale circulation patterns. In the context of climate change, especially climate projections, Serbia is situated in a region for which climate projections of mean precipitation change demonstrate weak signals and often with conflicting signs of change within multimodel ensembles. From this point of view, our results can be seen as a contribution to a better understanding of changes in extremes, in our case droughts, that can be hidden by inconclusive changes in the mean values. Finally, due to the similar situation in terms of precipitation and drought trends and changes, our results may be relevant for a wider region, and not only for Serbia. • For Serbia negative trends in SPEI index, for different months and timescales, are dominant. • Occurrence of extreme drought categories has doubled over the last decades. • Transitions from neutral and wet categories to dry categories are more frequent. • These changes are driven by long-term warming and large-scale circulation patterns. [ABSTRACT FROM AUTHOR]

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

This paper presents an analysis of trends in drought variables at 29 stations across the Euphrates-Tigris Basin over the period 1965–2022. Drought variables were calculated using the Standardized Precipitation Index (SPI) for 1-, 3-, 6- and 12-month scales. The drought values have been decomposed for these time scales through application of Discrete Wavelet Transform (DWT). The components are defined as short, medium and long periodicities. DWT-based trend analysis was computed using Mann-Kendall (MK) and Innovative Trend Analysis (ITA) methods. As the time scale and the periodicity of drought increase, a strong increase in drought occurs. It was revealed that drought increased significantly at all time scales in almost all stations, especially in the long periodicity, according to both MK and ITA. The droughts and the serious increasing trend of droughts in this basin constitute a significant threat to water resources. • Drought in the largest basin of Turkey, the Euphrates-Tigris Basin, was scrutinized through an assessment of the Standard Precipitation Index (SPI). • Short, medium, and long periodicities acquired by decomposing Standardized Precipitation Index (SPI) time series have been introduced. • The trends of SPI time series and short, medium and long periodicity series were analysed by MK and ITA tests. • The most severe droughts began after 2020 throughout the basin and the drought intensified significantly during the long periodicity. [ABSTRACT FROM AUTHOR]

The Mediterranean region is a unique area characterized by a large spectrum of atmospheric phenomena, some of which have a high impact on many aspects of human activities, safety and wellbeing. The area is long considered as a hot spot of such atmospheric phenomena deserving multidisciplinary scientific attention. The scientific research that has been carried out on these high impact atmospheric processes that occur in the Mediterranean area is indeed widespread and the available international literature is very extensive. The paper touches initially the temperature and precipitation regimes, followed by a discussion of floods and droughts. The exciting cyclogenetic patterns of explosive cyclones and medicanes are presented in separate sections. The lightning activity and the presence of dust and other pollutants are also presented herein. The atmospheric chemistry of the region which is increasingly becoming of utmost importance for the area under study is distinctly discussed. Attempts to modify the weather (the precipitation, in particular) are outlined too. The effects of climatic change on various atmospheric processes are considered throughout this paper, in addition to a dedicated section on temperature and precipitation. [ABSTRACT FROM AUTHOR]

The Arid Area of Northwest China (AANC) has the most resource-based water scarcity in China. It also has engineering-, structural-, and management-based water scarcity, all of which seriously restricts the AANC's socioeconomic development. This paper uses the Water Poverty Index's (WPI) characterization of socioeconomic drought to analyze WPI change trends and spatiotemporal patterns in the AANC from 2001 to 2020. Further, the paper comprehensively analyzes the relative water scarcity degree across different zones, using the Structural Equation Model (SEM) to identify the main factors affecting the WPI and the contribution rate of each factor. The results show that the average value of the WPI in the AANC from 2001 to 2020 was 45.6, indicating severe drought. However, from 2016 onward, the degree of socioeconomic drought eased and then transitioned to moderate drought. Significant differences in the spatial distribution of the WPI occur in the AANC, with the WPI in the Hexi Corridor (47.17) being higher than the regional average (45.32), the WPI in northern Xinjiang (45.74) being the same as the regional average, and the WPI in southern Xinjiang (43.05) being lower. There are different types of water scarcity problems across the region, with Alashan, Kezhou and Zhangye experiencing water scarcity that is resource-, engineering-, and management-based, respectively. Numerous factors affect the socioeconomic drought in the AANC. Potential water resources are the main factor, with a contribution rate of 36.58%. Water supply facilities, utilization capacity, use efficiency, and the environment have a relatively small impact on the WPI, with contribution rates of 18.29%, 15.36%, 15.52%, and 14.25%, respectively. This study can provide a reference framework for the construction of a regional socioeconomic index system for drought evaluation. It can also provide scientific and technological support for regional water resources management and industrial structure planning. [ABSTRACT FROM AUTHOR]

In recent years, large parts of arid and semi-arid areas in the world are dealing with water restrictions. In these areas, wetlands provide habitats for migratory birds and have a critical role in socio-ecological systems. Generally, in these areas, changing water-use patterns because of land-use change and water limitation because of climate change have led to the loss of wide areas of wetlands. Wetland restoration is suggested to restore the functions and values of wetlands that have been destroyed or affected by stresses. In this paper, a new application of wetland restoration prioritizing is introduced; restoration prioritizing to reduce the negative effects of drought. In this method, areas with the highest priority for restoration will be determined in a wetland destroyed because of water limitations. Multicriteria-spatial decision support system (MC-SDSS) was used to plan a scheme for Hamun wetlands restoration prioritizing in order to reduce the negative effects of drought and to restore the wetlands. This prioritization-determined areas that are valuable for Long-term water conservation, reduce the negative effects of dust storms and conserve water bird’s habitats. This method was used in a wetland that is the only water resource in the middle of a wide arid plain. Because of water limitation, it is not possible to restore the hole wetland; therefore, different parts of this wetland were prioritized for restoration. Based on the results, it is possible to produce a model to determine which priority can be restored in each amount of water volume. In this way, it becomes clear for decision-makers to select areas for restoration in different volumes of water. The result of this study shows that since MC-SDSS decreases conflicts between alternatives in a decision-making process and uses their spatial situation, it is a preferred method to balance among conflicting goals. Furthermore, because spatial data are the most important parts of MC-SDSS, this paper shows the ability of remote sensing to be used in MC-SDSS method. It seems that in the future; remote sensing will have the most important role in MC-SDSS. [ABSTRACT FROM AUTHOR]

This paper presents the results of the research on the overall distribution of selenium (Se) in various aquatic compartments (water, sediment, plankton and macrophytes) at six selected sites of the Croatian part of the Drava and Danube rivers, the connected floodplain lake and the melioration channel system carried out in two sampling periods (flooding in June and the drought period in September). In addition, the physicochemical water properties, plankton composition and biomass were analysed. Our study revealed low mean Se contents in sediments and water, indicating Se deficiency in the studied freshwater systems. The physicochemical environment, including Se distribution, was primarily influenced by hydrology rather than site-specific biogeochemical and morphological characteristics. The flooding period was characterised by higher Se content in water and higher transparency, nitrate and total nitrogen concentrations than drought conditions. At the river sites, sediment Se content was the highest during the flood period, while at all other sites, higher concentrations were found during the drought, reaching the maximum in the lake. Although Se concentrations were below the threshold for aquatic ecotoxicity, they increased in the following order: water (0.021–0.187 μg Se L−1) < sediments (0.005–0.352 mg Se kg−1) < macrophytes (0.010–0.413 mg Se kg−1) < plankton (0.044–0.518 mg Se kg−1) indicating its possible biomagnification at the bottom of the food chain. Species known for high Se accumulation potential dominated the biomass of the main plankton groups and the composition of the macrophyte community, which may provide a more sensitive and accurate steady-state compartment monitor for Se assessment in freshwater biotopes. [Display omitted] • Low Se content in sediments and water indicates Se deficiency in the studied area. • Se concentration increased in the order: water < sediments < macrophytes < plankton. • Hydrology influences the Se distribution in aquatic compartments. • Se potentially accumulates at the bottom of the food web. [ABSTRACT FROM AUTHOR]

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

Climate change led an increase in the frequency of severe droughts, the effects of which are exacerbated by a lack of water storage. Despite increasing research on global-scale total water storage (TWS) change and drought prediction, basin-scale long-term hydrological drought, TWS change, and El Nino–Southern Oscillation (ENSO) influence in East Africa (EA) remain unexplored. In this paper, we used multiple approaches, of ensemble machine learning (ML) and weighted averaging, to conduct a basin-scale exploratory analysis of future hydrological drought and TWS change for the period 2025–2099. Climate change will affect future hydrological conditions in the basins, with maximum severity values of −90.3, −726.6, and −2567.7 Gt in the Tana, Turkana, and Victoria basins, respectively, under RCP6.0. Similarly, we found maximum severities of −187.5 and −277.7 Gt in the Abaya-Chamo and Tanganyika basins, respectively, under RCP 2.6. The most severe El Nino drought and exceptional La Nina conditions in the basins were found under both RCP scenarios. To ensure future water security in EA, sustainable water resource management strategies that can mitigate the impacts of extreme climate events in the future are urgently needed. [ABSTRACT FROM AUTHOR]

[Display omitted] • Spring drought factors include snow cover, precipitation, temperature, and soil moisture. • Established a variance analysis projection pursuit model (ANOVA PPM) • ANOVA PPM achieves a balance between overall dispersion and local aggregation. Due to the influence of snow cover and soil freeze–thaw processes in the early spring, the characteristics of spring drought in cold regions are different from those in other regions. This paper takes Qiqihar, a cold and semiarid grain production area in Northeast China, as the study area. Based on factors such as snow cover in the early spring period and precipitation, temperature, evapotranspiration, and soil moisture during the spring sowing period, a projection pursuit model with analysis of variance (ANOVA PPM) was used to analyze the spatiotemporal variation characteristics of regional spring drought. For the ANOVA PPM, based on the grouping of the projection points, local aggregation is measured by the mean square within groups, and overall dispersion is measured by the mean square between groups, thus achieving comparability and balance between overall dispersion and local aggregation. The spatial analysis of spring drought showed that, from a spatial perspective, there were significant spatial differences in spring drought in different subregions, and spring drought was closely related to latitude, with significant differences occurring at different latitudes. The northern region is relatively light, while the central and southern regions are more severe. From a temporal perspective, there are significant differences in spring droughts between different decades (1980 s, 1990 s, 2000 s and 2010 s). Overall, spring drought first intensifies and then decreases. [ABSTRACT FROM AUTHOR]

Single drought index such as Precipitation Condition Index (PCI), Temperature Condition Index (TCI), Evapotranspiration Condition Index (ETCI) and so on, has a limited capability to indicate drought state. It has been proved that the composite drought index proposed by integrating multiple single drought indices can indicate and predict drought state more efficiently and accurately. This paper presents the Precipitation Temperature Evapotranspiration Drought Index (PTEDI) combining the PCI, TCI and ETCI. The three-dimensional Euclidean PCI-TCI-ETCI space is built, and the PTEDI is defined as the magnitude of the vector in the PCI-TCI-ETCI space. To verify the rationality and effectiveness of the PTEDI as a desired drought index in the Huang-Huai-Hai Plain, it is compared with the PCI, TCI, ETCI and PCACDI (Principal Component Analysis Combined Drought Index), and is evaluated with the Drought Affected/Disaster Area (DAA/DDA) and Net Primary Productivity (NPP). The results indicate that the PTEDI outperforms the PCI, TCI, ETCI and PCACDI, and is highly correlated with the Standardized Precipitation Index (SPI-1) (R = 0.61), Soil Moisture Condition Index (SMCI) (R= 0.56), and NPP (R = 0.56). The time series of the PTEDI and four indices (SPI-1, SMCI, Crop Water Stress Index (CWSI) and Temperature Vegetation Drought Index (TVDI)) exhibits good spatial consistency. The PTEDI has a negative correlation with the DAA/DDA (R < −0.6). Furthermore, to illustrate the applicability of the PTEDI, the drought spatiotemporal variation is analyzed by taking it as a drought index. At the monthly scale, moderate drought occurs most frequently in March and July. At the annual scale, the PTEDI fluctuates between 0.34 and 0.60 without obvious periodicity, and the study area is mainly characterized by mild drought. Moreover, the drought evolution is analyzed by using the timing analysis methods. In conclusion, the PTEDI can be applied to monitor drought effectively. [Display omitted] • The Precipitation Temperature Evapotranspiration Drought Index (PTEDI) was proposed. • The PTEDI outperformed multiple drought indices and reflected the drought state well. • Spatiotemproal evolution of drought in Huang-Huai-Hai Plain was shown with PTEDI. • The PTEDI is an effective composite drought index based on remote sensing. [ABSTRACT FROM AUTHOR]

The year 2015 was characterized by a very low precipitation totals and long rainless periods all over the Czech Republic as well as other central European countries. This fact has attracted the attention of both the public as well as professional society whose focus was recently put more on floods which are hydrologic extremes with more sound impacts. In this paper, the summer period 2015 is in the focus for the catchment of Blanice River (Central Bohemia Region, South Bohemia Region). It was analyzed from both the meteorological and hydrological point of view. Total area of the catchment is 534 km 2 and is located 50 km southeast of Prague. For the assessment of drought, the data from one hydrological gauging as well as from a number of meteorological stations were used. The time series used for this study are more than 50 years long. Drought indices used for this study and presented in this paper were Standardized Precipitation Index ( SPI ), Streamflow Drought Index ( SDI ) and deficit volumes ( DV ). The analyses of precipitation data carried out for given purpose were supported by GIS application in order to get real precipitation data based on available station data. Drought indexes were calculated on the basis of data for entire period, however the emphasis was put on the data from year 2015. The results of all performed analyses show the significance of the drought event which occurred in summer 2015 with respect to both meteorological and hydrological indices. However, the significance of meteorological drought seems to be higher with respect to the results of analyses carried out. The results also show, that there were even more severe drought episodes in past within the analyzed period. [ABSTRACT FROM AUTHOR]

The paper presents a methodological framework based on the proactive planning approach for combating droughts and the associated water shortages. Three interrelated procedures tailored for each affected system are proposed: (a) the drought severity assessment; (b) the system vulnerability appraisal; and (c) the evaluation of drought risk. This scheme is assisted by the DPSIR methodology for the detailed estimation of drought risk of each affected system. The proposed methodological framework is put into practice through the preparedness and contingency plans against droughts. Further in this paper several technocratic and institutional aspects of these plans are discussed and brief guidelines for devising them are presented. Finally, the involvement of stakeholders and the public is examined in a decentralised decision system for the effective implementation of these plans in real world drought episodes. [ABSTRACT FROM AUTHOR]

Shifting climate patterns are causing extreme drought and flooding across the globe. This combined with the world's burgeoning population and insatiable thirst for water requires water service providers to think differently about the limited resources they manage. In Australia, the severe drought at the beginning of the century caused dams to fall to record levels. In response, many state governments invested heavily in rain-independent supplies such as desalination to augment and diversify traditional sources. However, extreme rainfall soon followed the drought, filled reservoirs and caused flooding in many locations leaving billions of dollars worth of damage and new water infrastructure standing idle. This is the case in Sydney, where the new desalination plant is still not used and the potential for major flooding has raised concerns over the safety of the large population downstream of the dam. This paper explores the growing need to understand the relationship between drought, flooding and infrastructure optimisation. The paper focuses on Sydney to illustrate the application of a system dynamics model. The new model explores options for raising the dam wall, offering airspace to assist flood protection, in contrast to options to lower the dam full supply level and utilise idle desalination capacity to fill the water security gap created. The illustrative results, using publicly available data, find that by lowering the dam water levels and operating desalination, significant flood protection can be achieved at a similar cost to raising the dam wall. The paper demonstrates the importance of optimising existing and new water resources for multiple purposes and how system dynamics modelling can assist water service providers in these complex investigations. [ABSTRACT FROM AUTHOR]

The drought indices are common tools for monitoring and risk assessment of the drought. Based on copula function, this paper proposes a bivariate combined drought index (BCDI bcf) that can comprehensively characterize the meteorological characteristics (precipitation) and hydrological characteristics (runoff). Besides, the cross-wavelet transform (XWT) is introduced to research the relationship of drought, and identifies the lag in the propagation process. Take Huayuankou station as an example, results indicated: (1) The BCDI bcf combines the merit of the standardized precipitation index (SPI) in capturing the onset of drought and that of the standardized runoff index (SRI) in capturing the end of drought, which contains information on both SPI and SRI, can characterize two types droughts of hydrology and meteorology simultaneously. (2) The characteristics of hydrology and meteorology have significantly periodic, the most obvious on the scale of 2-4a. (3) There is the significant positive statistical correlation between precipitation and runoff, and hydrological droughts are lagging behind meteorological droughts by 1–2 months at Huayuankou station. The BCDI bcf can identify drought more comprehensively and provide strong support for drought detection and prevention. [ABSTRACT FROM AUTHOR]

Water systems worldwide are experiencing climate change-induced shifts in drought properties like frequency, intensity, and duration, affecting water security and reliability. To develop and test effective drought preparedness plans, researchers often use synthetic weather generators to create hydrological scenarios that explore drought variability beyond historical records. Existing weather generators typically allow users to adjust streamflow statistics like percentiles or temporal correlation but do not directly control drought properties of frequency, intensity, and duration. To fill this gap, we propose FIND (Frequency, INtensity, and Duration) synthetic weather generator. FIND incorporates a standardized drought index to directly and independently control drought frequency, intensity, and duration in generated streamflow time series while preserving observed hydrological variability. Use cases for FIND include (i) water systems analysis applications that seek to train and test drought strategies under historical and plausible future drought conditions, and (ii) bottom-up vulnerability studies relating system vulnerability outcomes to specific changes in drought properties of frequency, intensity, and duration. We demonstrate FIND's versatility through three experiments: replicating historically observed drought properties, generating streamflow scenarios for multiple sites preserving correlation between their drought conditions, and generating a set of scenarios with direct and independent changes in drought properties. FIND source code is openly available for applications beyond the scope of this paper. • FIND generates synthetic weather timeseries with desired drought properties. • FIND supports weather generation for multiple correlated site. • With FIND, modelers can pinpoint changes in drought properties that threaten water systems. [ABSTRACT FROM AUTHOR]

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

This paper proposes a framework based on the integration of bottom-up and top-down approaches to assess and quantify the effect of local climate change on carbon and water fluxes in a protected Mediterranean mixed forest. The forest, with an extent of 50 ha, is in a coastal zone and is in decline because of severe summer drought stress. Since 2018, it has been involved in the LIFE PRIMED ecological restoration project. The bottom-up approach used gas exchange measurements and the MOCA model (MOdelling for Carbon Assessment) to quantify photosynthesis and transpiration of the main species in the forest (P. latifolia , P. lentiscus , Q. cerris , and F. angustifolia sub. oxycarpa). The top-down approach used the satellite models C-fix and NDVI-CWS, to quantify and spatialise gross primary production (GPP), net primary production (NPP), and evapotranspiration (ETA) at the forest stand scale. The up-scaling process from leaf to forest stand was made possible by calibrating two key parameters: light use efficiency (ε) and vegetation transpiration coefficient (Kc veg). The results indicate a decline in GPP , NPP , and ETA during the study period (2018–2022) due to the summer drought conditions caused by rising temperatures (16.60 °C in 2018 vs. 16.98 °C in 2022), increased vapor pressure deficit, reduced soil water content, and rainfall (1328 mm in 2018 vs. 468 mm in 2022). In 2018, the annual GPP was 1186.83 ± 351.40 gC/m2y, which decreased to 1128.67 ± 331.21 gC/m2y in 2022. During the dry summer period, GPP ranged from 401.76 ± 119.54 gC/m2y in 2018 to 347.39 ± 101.62 gC/m2y in 2022. Annual ETA rates varied between 1184.86 ± 351.86 mmH₂O/m2y (2018) and 1304.92 ± 384.07 mmH₂O/m2y (2022). The summer ETA rates were significantly influenced by drought conditions, decreasing from 638.73 ± 190.67 mmH₂O/m2y in 2018 to 390.35 ± 108.83 mmH₂O/m2y in 2022. Based on the observed trend in other Mediterranean areas, species-specific responsiveness to local climate change suggests that P. latifolia and P. lentiscus , which are better adapted to water-limited environments, could gradually replace Q. cerris and F. angustifolia subs. o xycarpa. This study provides useful quantitative indications for the management and restoration goals of the area and suggests a methodology that can be applicable in several management practices, particularly for small heterogeneous and fragmented forested areas such as the Mediterranean ones. • High temperature and reduced rainfall influence forest carbon and water fluxes. • Soil Water Availability negatively affects GPP, NPP and ETA trends. • Leaf and stand scale data are analysed through bottom-up and top-down approaches. • Specific light use efficiency (ε) and crop transpiration coefficient (K veg) are used to calibrate satellite-based models. [ABSTRACT FROM AUTHOR]

This paper explores the role that incremental water charging (temporary levies on water use) can play in reducing the environmental costs that arise during drought events. The paper combines a multi-attribute Revealed Preference Model calibrated at a local level (Agricultural District) and a regionally-calibrated Computable General Equilibrium model to estimate the impacts of incremental water charging on water use, water withdrawals and market income. The methodology is applied to the particular case of Italy's Emilia Romagna Region. Results provide a basis for the assessment of tradeoffs in water conservation. [ABSTRACT FROM AUTHOR]

• The environmental policy impact climate (EPIC) model is capable of simulating crop productivity for hundreds of years under a variety of climate scenarios, environmental conditions, and management systems and is often used to study the impact of climate change on agriculture. • The application of EPIC crop growth model can be divided into three categories: the improvement of crop growth model accuracy, the applied research on the effects of climate change, and the mitigation of agricultural drought risk. • Four aspects of research hot spots in the future: applications of extreme climate change, application of agricultural drought risk assessment and early warning, application of an agricultural catastrophe management system, application of drought relief operations. Climate change is breaking global food supplies. The Environmental Policy Impact Climate (EPIC) model is capable of simulating crop productivity for hundreds of years under a variety of climate scenarios, environmental conditions, and management systems and is often used to study the impact of climate change on agriculture. Combined with systematic evaluation and meta-analysis, this paper reviews the application of EPIC crop growth model. Those research can be divided into three categories: the improvement of crop growth model accuracy, the applied research on the effects of climate change, and the mitigation of agricultural drought risk. In addition, the paper puts forward four aspects of research hot spots in the future: applications of extreme climate change, application of agricultural drought risk assessment and early warning, application of an agricultural catastrophe management system, application of drought relief operations. Research shows the accuracy of the model is greatly improved by determining the genetic parameters of crops, modifying the parameters according to the weather, land use and technical conditions, and establishing the local and even global model parameter database; the uncertainty of model parameters, input data and model structure is analyzed to improve the stability of the model. In the process of discussing the influence mechanism and sensitivity analysis of climate change on crop growth, the analysis of various meteorological factors is concentrated from multi-factor analysis to temperature and precipitation. With the development of computing technology, the emergence of GIS technology and GCMs technology makes it possible to predict the impact of different meteorological factors on crop growth under future climate change. In some studies, EPIC crop growth model has been performed to reduce the risk of agricultural drought. [ABSTRACT FROM AUTHOR]

Drought exerts a significant impact on the sustainable development of social economy. For sustainable water use and rapid drought response, it is very meaningful to explore the correlation between meteorological drought and hydrological drought. This paper investigates the features of drought evolution based on cross wavelet transform (XWT) and mutual entropy. The meteorological drought was measured by the standardized precipitation index (SPI), while the hydrological drought was evaluated by the standardized runoff index (SRI). The research data were collected from hydrological stations and meteorological stations in the Yellow River basin of Henan Province, China. The main conclusions are as follows: (1) Both meteorological drought and hydrological drought had obvious periodicity, especially on the scale of 2–4a. (2) The evolution of meteorological drought varied greatly from place to place; through the study period, Henan province did not suffer any extreme drought, though the drought situation in the western region has an aggravating trend. (3) Hydrological drought has a strong positive correlation with meteorological drought, and generally lagged behind meteorological drought by 1–2 months in the study area. The research results lay a good basis for drought response in the Yellow River basin. [ABSTRACT FROM AUTHOR]

The distribution focuses of water resources, socio-economic development and environmental maintenance are usually mismatched, leading a gap between regional resources and the environment, as well as the disharmony of development. Water resource spatial equilibrium (WRSE) is an important yardstick for guiding regional water resource planning and sustainable utilization. However, research on the spatiotemporal heterogeneity and driving factors of WRSE is extremely lacking, and few existing studies have considered drought and flood disasters as the important reflection of WRSE. Therefore, this paper proposes a systematic integrated model for WRSE including regional evaluation, spatiotemporal heterogeneity and geodetector analysis functions, and constructs the evaluation index system considering droughts and floods. First, the performance of WRSE is quantified using the general deprivation index (GDI) innovatively. Then, combined with the Moran's I , the spatial patterns and regional differences of WRSE are analyzed. Last, the geographical detector models are employed to perform driving analysis of WRSE. The effectiveness of the model is verified in China. Results show that (1) from 2009 to 2021, the national average of WRSEI exhibits a declining trend from 0.879 in 2009 to 0.789 in 2021. (2) The areas with high WRSEI values are mainly distributed in the western provinces, whereas the eastern region has a higher percentage of imbalanced provinces. (3) Water resources per capita, added value of tertiary industry, urbanization rate and GDP per capita are key driving factors of China' WRSE. The study provides a novel insight for WRSE improvement and is greatly helpful for developing differentiated management measures to optimize resource allocation. • A systematically integrated model for water resource spatial equilibrium (WRSE) was established. • First applying the general deprivation index method to analyze WRSE. • The evaluation index system was enriched by adding drought and flood factors. • Differentiated measures can improve the equity of water resources development and utilization process. [ABSTRACT FROM AUTHOR]

• 1. The lag degree of hydrological drought is studied by changing the time scale. • 2. Multi-scale standardized indicators can explore the strongest correlation. • 3. According to the synchronization, relevance, correlation to calculate the results. • 4.The scale time with the strongest correlation is the propagation time. To study the propagation law of meteorological droughts to hydrological droughts under variable time scales, and to reveal the synchronisation gap and lag time of hydrological droughts compared to meteorological droughts, and the lag degree of hydrological drought is quantitatively studied. In this paper, the Yellow River Water Supply Area in Henan is taken as the research area, and the propagation time of meteorological drought to hydrological drought under variable time scale is mainly studied. The calculation of drought propagation time is set as two states: interval scale and continuous scale. The Standardized Precipitation Index (SPI) sequence and Standardized Runoff Index (SRI) sequence (1)with interval and continuous scales were obtained by multi-scale standardization of precipitation and runoff, which were used to characterize meteorological drought and hydrological drought respectively. The Mann-Kendall (M−K) test method was used to analyze the evolution of SPI sequence and SRI sequence at monthly scale, and to study the lag time of hydrological drought in four seasons compared with meteorological drought. Combining the Grey Correlation Method and Pearson correlation coefficient methods, the time interval for the propagation of meteorological droughts to hydrological droughts was determined based on the strongest correlation of different combinations of sequences. Finally, the propagation time series is divided into sliding windows to analyse the M−K dynamic trend of propagation time from a seasonal scale perspective. It provides a strong basis for the study of drought propagation based on multi-scale. [ABSTRACT FROM AUTHOR]

• An ecosystem process model-based NEP was predicted under varying climate scenarios. • Alpine grasslands were projected to play an important part in carbon sink contributions in Qinghai Province in the 21st century. • An earlier peak and faster decreasing NEP projected for a warmer climate scenario (RCP 8.5). • A more stable carbon sink was projected under a less warm, stable precipitation scenario (RCP 4.5). The alpine grasslands of the Qinghai-Tibetan Plateau play an important role in multiple ecosystem functions, all of which are key in regulating regional climate influences and providing pristine headwaters for millions of people downstream from this basin. Alpine grasslands act as a carbon sink, storing carbon dioxide and keeping heat-trapping greenhouse gases out of the atmosphere, but it is not clear how this will change in a warming climate in the future. In this paper, the net ecosystem productivity (NEP) of alpine grasslands in Qinghai province, on the Qinghai-Tibetan Plateau, was predicted for the period from 2010 to 2099. Trends and stability were analyzed under two climate scenarios, Representative Concentration Pathway 4.5 (RCP4.5) and 8.5 (RCP8.5) representing the lower and higher emission scenarios for greenhouse gases. The results suggest that grasslands will continue to contribute as a carbon sink, with a positive NEP through this century. Almost the same magnitude (38 Tg C a-1, 1 T g = 1012 g) of contribution was projected under both scenarios. Grasslands are projected to be the major contributor to NEP in Qinghai province, with more than 89% of NEP in the future. The carbon sink function will increase over more than 69% of the grasslands and peak around 2069 (RCP4.5) or 2066 (RCP8.5). Then the carbon sink function will begin to decrease and it will decrease more quickly and become more variable under the RCP8.5 than the RCP4.5. The impacts of temperature and precipitation changes were analyzed and NEP was found to be more sensitive to temperature than precipitation change. The trend of increasing contribution to NEP is driven by a warming climate, while the stability of NEP is mainly influenced by the precipitation, which results in an upward trend before the peak and a decline due to stresses from limits in available water in a continued warming climate. [ABSTRACT FROM AUTHOR]

[Display omitted] • The proposed MSDI can capture the occurrence of drought. • There was a tendency of aridity with a mutation point of 1983. • The drought severity was the heaviest in the DXJB, with an average MSDI of –0.75. • The most severe drought event occurred from September 1988 to October 1990. • ENSO had the largest influence on the drought variation in the XJB. The reasonable and appropriate drought indicator is a crucial instrument for drought investigation and assessment, which can objectively compare the severity, duration, and frequency of drought events, so as to achieve the purpose of accurately monitoring and evaluating drought. However, a univariate drought index is often difficult to precisely describe the complex drought situation, and it is urgent to establish a multivariate comprehensive drought index to identify and reveal the drought characteristics. Based on Copula models, combined with meteorological factors precipitation and hydrological factors runoff, this paper constructed a Multivariate Standardized Drought Index (MSDI), which can characterize meteorological drought and hydrological drought simultaneously and evaluate the spatial–temporal evolution characteristics of drought over the Xijiang River Basin (XJB) in South China. The results indicated that: (1) the proposed MSDI can capture the occurrence of drought as sensitively as the Standardized Precipitation Index (SPI), and can represent the termination of drought as effectively as the Standardized Runoff Index (SRI), which can comprehensively depict the drought situation in the XJB, China; (2) since the 1980 s, there was a tendency of aridity with a mutation point of 1983 in the downstream of Xijiang River (DXJB), and the worst comprehensive drought occurred in 1989; (3) among the tributaries, the comprehensive drought severity was the heaviest in the DXJB, with an average MSDI value of –0.75; (4) based on the run theory and Copula model, the most serious drought event occurred from September 1988 to October 1990, with a drought severity of 33.36, a drought duration of 27 months, and a drought return period exceeding 50 years; and (5) the drought evolution was significantly influenced by abnormal atmospheric circulation factors, while ENSO had the largest influence on the drought variation in the XJB, followed by sunspot. [ABSTRACT FROM AUTHOR]

In this paper, a new Groundwater Quantity-Quality-based Drought Index (GQQI) is developed based on multivariate Copula analysis of groundwater quantity and quality indicators. For evaluating the developed index, its temporal and spatial distribution is studied and compared to those of some other indices, such as Standardized Salinity Index (SSI), Standardized Groundwater Index (SGI), and Standardized Water level Index (SWI). The proposed index is applied for the temporal and spatial evaluation of the quantity and quality of groundwater in theLake Urmia basin, having 1084 piezometric and 935 groundwater quality monitoring wells. For a more comprehensive analysis of drought, 24 marginal and 26 joint probability distribution functions are driven. Based on the results, the developed GQQI is correlated with drought indices of SSI, SGI, and SWI by 88%, 86%, and 61%, respectively. Moreover, the values of the developed drought index indicates the occurrence of more severe droughts, compared to those detected by other drought indices. This can be resulted from considering the combined effects of groundwater quantity and quality using the proposed index. In addition, the multivariate GQQI can spatially and temporally represent the drought severity over the basin, and identify severe and extreme drought conditions better than other univariate drought indices. [ABSTRACT FROM AUTHOR]

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

This paper examines how resilience capacity mediates or moderates the relationship between weather shocks and household food security based on two waves of farm household survey and satellite-based weather data in northern Ghana and applying econometric models. Results show that resilience capacity moderate or mediates the negative effects of heat stress and drought on food security. However, the mediating role of resilience capacity in the shock-food security nexus is more stable and stronger than its moderating role. A standard deviation (SD) increase in heat stress reduces household food consumption by 0.71 SD, but resilience capacity effectively moderates this effect by approximately 0.61 SD. For drought, household food consumption is reduced by 0.67 SD, but resilience capacity effectively dampens this negative effect by approximately 0.60 SD. The mediation results, on the other hand, indicate that 537% of the total effect of heat stress on household calorie consumption is explained by the indirect effect through resilience capacity. Similarly, resilience capacity mediates about 74% of the total effect of heat stress on household food consumption. These results suggest that strategies that help improve resilience capacity, such as the adoption of sustainable intensification practices, are critical in enhancing food security in northern Ghana. • Weather shocks, proxied by heat stress and drought, are found to reduce food security. • Heat stress cause stronger adverse effects on food security than drought does. • Resilience capacity mediates substantial shares of the total effects of heat stress and drought. • The shock-dampening effect of resilience capacity is stable for heat stress than for drought. [ABSTRACT FROM AUTHOR]

Abstract: This paper provides an evidence-based contribution to understanding processes of climate change adaptation in water governance systems in the Netherlands, Australia and South Africa. It builds upon the work of Ostrom on institutional design principles for local common pool resources systems. We argue that for dealing with complexities and uncertainties related to climate change impacts (e.g. increased frequency and intensity of floods or droughts) additional or adjusted institutional design propositions are necessary that facilitate learning processes. This is especially the case for dealing with complex, cross-boundary and large-scale resource systems, such as river basins and delta areas in the Netherlands and South Africa or groundwater systems in Western Australia. In this paper we provide empirical support for a set of eight refined and extended institutional design propositions for the governance of adaptation to climate change in the water sector. Together they capture structural, agency and learning dimensions of the adaptation challenge and they provide a strong initial framework to explore key institutional issues in the governance of adaptation to climate change. These institutional design propositions support a “management as learning” approach to dealing with complexity and uncertainty. They do not specify blueprints, but encourage adaptation tuned to the specific features of local geography, ecology, economies and cultures. [Copyright &y& Elsevier]

Graphical abstract Highlights • This study introduced a modified total storage deficit index to monitor drought in basins with high water consumption. • This study assessed the potential of GRACE observation for developing a drought monitoring system. • Two drought events were found in 2008–09 and 2010–11 over Markazi basin in Iran. • This study analyzed the relationship between climatic teleconnection signals and the extreme events over the study area. Abstract Although total storage deficit index (TSDI) is a well-known GRACE-based drought index, it is not efficient for the basins with high consumption because water harvesting in these areas affect GRACE signal. To overcome this limitation, the modified total storage deficit index (MTSDI) is introduced in this paper. To develop MTSDI, residuals of the signal were used instead of total signal. The proposed approach was applied to monitor drought in the Markazi Basin, Iran, during 2002–2016. Based on the obtained results, TSDI detected a moderate drought event in 2012 and a long-term severe drought from 2013 to 2016, which is not compatible with the recorded results of standardized precipitation index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI). Meanwhile MTSDI identified two drought events in 2008–09 and 2010–11 that coincided with droughts detected using SPI and SPEI. Results revealed that MTSDI is highly correlated with SPI and SPEI at a 12 month-scale, showing a correlation coefficient of 0.75 and 0.62, respectively. On the other hand, the coefficient of correlation between TSDI and SPI12 was 0.42 and between TSDI and SPEI12 was 0.26. A pixel-by-pixel analysis showed MTSDI and SPI/SPEI had a significant correlation in most areas of the basin. Further, the investigation of droughts in Markazi Basin revealed that dry years coincide with the occurrence of strong La Niña events. Overall, the results indicated a good potential of GRACE observations for developing a drought monitoring system, which its performance can be enhanced with respect to large-scale climate signals. [ABSTRACT FROM AUTHOR]

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

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

Abstract: Urban water scarcity from ongoing drought and an increasing population are driving a range of water saving options to be explored in Melbourne (Australia). This paper assesses the cost effectiveness of five water treatment and industrial reuse options in the Fishermans Bend industrial area at Port Melbourne. In consultation with industrial stakeholders and the local water utility, the study design began by identifying potential water sources and sinks in the area. Treatment technologies for each option – using a combination of membrane bioreactors (MBR) and in some cases reverse osmosis (RO) technologies – were developed. In evaluating the potential for future implementation, the cost effectiveness ($/kiloLitre) was assessed relative to water supply augmentation and water demand management options available in Melbourne. Additionally, the opportunities and barriers for option implementation in Port Melbourne were contrasted with the Kwinana Industrial Area, Western Australia where many regional synergy projects have been undertaken. This research identifies that the future implementation of industrial ecology opportunities requires strong and ongoing stakeholder involvement as described in this paper. [Copyright &y& Elsevier]

Abstract: Drought affects natural environment of an area when it persists for a longer period. So, drought forecasting plays an important role in the planning and management of natural resources and water resource systems of a river basin. During last decade neural networks have shown great ability in modeling and forecasting nonlinear and non-stationary time series. This paper compares linear stochastic models (ARIMA/SARIMA), recursive multi-step neural network (RMSNN) and direct multi-step neural network (DMSNN) for drought forecasting. The models were applied to forecast droughts using standardized precipitation index (SPI) series as drought index in the Kansabati River Basin, which lies in the Purulia district of West Bengal, India. The results obtained from three models and their potential to forecast drought over different lead times are presented in this paper. [Copyright &y& Elsevier]

In the era of water scarcity and severe droughts, the accurate estimation of evapotranspiration (ET) is crucial for the efficient management of water resources, understanding hydrological and ecological processes, and comprehending the relationships between the atmosphere, hydrosphere, and biosphere. ET is a complex phenomenon influenced by a set of biophysical and environmental factors. Its estimation becomes more complicated in heterogeneous environments, demanding detailed data and accurate model calibration. Combining remote sensing imagery and machine learning (ML) models has provided a considerable capacity for estimating ET, which relaxes a number of assumptions and requires less data than traditional approaches. Satellite imagery provides influential variables for ET estimation using ML models. Nevertheless, a growing number of ML models and emerging satellite imagery has opened up a wide and complex potential before researchers. While previous studies have reviewed physical-based methods for ET estimation, this paper offers a recent decade review of the progress, challenges, and opportunities provided by the RS and ML models for the ET estimation and future outlook. • Mechanisms and background of remote sensing-based evapotranspiration estimation is provided. • We review the combination of RS imagery and ML models to estimate evapotranspiration. • The most important factors to estimate evapotranspiration are reviewed. • The most important satellites to estimate evapotranspiration are reviewed. • Limitations of contributing factors are discussed. [ABSTRACT FROM AUTHOR]

• The oldest juniper studied in the Fann Mountains in western Tajikistan reached the age of 1320 years. • Moisture conditions are more strongly correlated with growth-ring widths than temperature. • Divergence between dendroclimatic reaction at low and high-elevation sites was confirmed. • Elevation can have stronger effects on the dendroclimatic signal than slope exposure. • Negative growth is triggered by dry conditions and dust storm events at low-elevation sites. This paper reports on a detailed dendrochronological and dendroclimatological study of juniper trees (Juniperus seravschanica Kom. and J. semiglobosa Regel), sampled at seven sites having different elevations (2200 – 3100 m) and exposures (south-north) in the Pamir-Alay mountains, north-western Tajikistan. We developed seven new, well-replicated ring-width chronologies extending back over the last 219–1320 years. Our results confirm that the main climate factor influencing radial growth in this semi-arid region is variability in precipitation. However, they also indicate that there is a divergence in dendroclimatic responses between low- and high-elevation sites, where different limiting factors play a dominant role. The radial growth of J. semiglobosa at the uppermost treeline locations is the most sensitive to winter precipitation. Tree-ring formation in J. seravschanica at low-elevation sites is strongly limited by spring-summer drought conditions and by winter temperatures. The results of PCA analysis indicate that the relationships between growth and climate are linked more to elevation than to exposure. It was also found that negative growth extremes at low elevation sites may be triggered by strong dust storm events. Our findings clearly show that precisely planned selections of topographically differentiated sites, including elevation and exposure, are crucial for the possible reconstruction of different climatic elements in the high mountains of Central Asia for the last hundreds to thousands of years. [ABSTRACT FROM AUTHOR]

Policies on bioeconomy are some of the key emerging ones around the world to support sustainability in terms of using renewable resources. However, these may lead to significant demand for biomass feedstock which relies on limited resources, viz., water, land, and energy. The impact of climate change on water availability makes it more challenging. This paper demonstrates the analysis of the water, energy, and food resource nexus of a bioeconomy-based industrial complex and future climate change impact. The model structure consists of cultivation, crop processing, and urban sectors. Sugarcane is the major crop in the case study area and is the main bioeconomy crop. The results indicate that the average sugarcane yield will be lower than the minimum industrial goal for the 2020s and 2030s decades. Consequently, sugarcane feedstock shortage may often occur. The drought situation tends to be increased, so groundwater resources can be the main reserve source of water. In all improvement scenarios on water supply management, nexus energy used for water acquisition was mainly for groundwater acquisition. Direct energy use in the cultivation process is high and fossil fuels based, while most of the energy used in processing came from biomass waste. This implies that technologies for water acquisition will be more important in the future and should be developed in terms of energy efficiency and the aspect of promoting the usage of renewable energy to reduce greenhouse gases and fossil fuels use. The impact of climate change will cause significant fluctuations in the annual rainfall characteristics of the study area. An additional irrigation water supply of about 250 mm and expansion to cover more than 90% of the cultivation area should be considered to secure the minimum supply of sugarcane for the local biorefinery complex in the following decades. [Display omitted] • Integrate climate change impact to Water-Food-Energy nexus model for bioeconomy. • The water–crop yield response model was set up to analyze interventions for improving yield. • In all scenarios, nexus energy used for water acquisition was mainly for groundwater acquisition. • The area will face a water supply shortage in the 2020s, and groundwater is the primary reserve source. • The irrigation expansion to cover 90% of the cultivation area can secure the supply of sugarcane. [ABSTRACT FROM AUTHOR]

• We advance resistance as a lens to analyse power and agency in adaptation. • We identify overt and covert popular resistance in 56 adaptation studies. • Resistance can mirror adaptation power or structural and historical conditions. • Adaptation resistance occurs globally, not least to relocation and participation. • Sociological resistance informs debates on vulnerability and today's climate politics. Climate adaptation is not a neutral or apolitical process, but one that ignites social resistance. Government responses to risks of floods, droughts, or hurricanes – even those using a language of participation – might follow historical development pathways, strive to maintain the status quo, and directly or indirectly serve elite interests. Little attention has been paid to how people defy or resist top-down adaptation processes, overtly or covertly, in particular cultural, historical, and legal contexts. Drawing on sociological thought on popular resistance, this paper systematises research on people's resistance to climate adaptation by scrutinising the sites, repertoires, and consequences of such resistance. We identified overt and covert resistance in 56 scientific adaptation articles, which concentrated on 5 'sites' of resistance: Rural livelihoods, Urban informal settlements, Islands, First Nations, and Institutional landscapes. The findings imply that resistance to adaptation occurs globally, and not least in the context of relocation processes and participatory adaptation. We show how a resistance lens can help understand contemporary political behaviours, shed light on dynamic and compound vulnerability, and'unlock' more context-sensitive and even transformative adaptation. Meanwhile, resistance and popular movements are not only progressive, and there might be conceptual barriers to moving from resistance to transformation or reconciling resistance with actions by or with the state. [ABSTRACT FROM AUTHOR]

Regional precipitation patterns may change in a warmer climate, thereby increasing flood and drought risks. In this paper, annual, annual maximum, intense, heavy, moderate, light, and trace precipitation are employed as indicators to assess changes in precipitation patterns under two scenarios in which the global mean temperature increases by 1.5 °C and 2.0 °C relative to pre-industrial levels using the regional climate model COSMO-CLM (CCLM). The results show that annual precipitation in China will be approximately 2.5% higher under 1.5 °C warming relative to the present-day baseline (1980–2009), although it will decrease by approximately 4.0% under an additional 0.5 °C increase in global mean temperature. This trend is spatially consistent for regions with annual precipitation of 400–800 mm, which has experienced a drying trend during the past half century; thus, limiting global warming to 1.5 °C may mitigate these drying conditions. The annual maximum precipitation continues to increase from present day levels to the 2.0 °C warming scenario. Relative to the baseline period, the frequency of trace and light precipitation days exhibits a negative trend, while that of moderate, heavy, and intense precipitation days has a positive trend under the 1.5 °C warming scenario. For the 2.0 °C warming world, the frequency of days is projected to decrease for all precipitation categories, although the intensity of intense precipitation increases. Spatially, a decrease in the number of precipitation days is expected to continue in central and northern China, where a drying trend has persisted over the past half century. Southeastern China, which already suffers greatly from flooding, is expected to face more heavy and intense precipitation with an additional 0.5 °C increase in global mean temperature. Meanwhile, the intensity of intense precipitation is expected to increase in northern China, and the contribution of light and moderate precipitation to the annual precipitation is expected to decrease in southeastern China. Therefore, flood risk in northern China and drought risk in southern China should draw more attention for a global air temperature increase from 1.5 °C to 2.0 °C. [ABSTRACT FROM AUTHOR]

News media plays an important role in shaping public opinions and attitudes about the environment. Tracking and analyzing media coverage can provide insight into public exposure to narratives that impact resource consumption, environmental behavior, and emergency response, which can help to inform model development or provide additional model inputs. This paper presents Articulate , an open-source, flexible tool for discovering, compiling, and quantifying newspaper coverage on a user-specified topic. Articulate is written in Python and interfaces with Google Custom Search Engine API. We demonstrate the tool's application and validate its performance on two case studies of news media coverage in the New York Times about drought in California and flooding in Houston, Texas in recent years. Our results show that Articulate can generate data similar to or better than proprietary databases. Thus, Articulate can help researchers and environmental managers gain important insights to better understand and quantify changing socio-environmental dynamics. [ABSTRACT FROM AUTHOR]

The aim of this study is to test how effective and physically correct are the mathematical approaches of operational indices used by relevant National Agencies across the globe. To do so, the following indices were analysed Standardized Precipitation Index (SPI) -1, 3, 6, 12 and 24, Standardized Precipitation – Evapotranspiration Index (SPEI) – 1, 3, 6, 12 and 24, Effective Drought Index (EDI) and Index of Drying Efficiency of Air (IDEA). To make regions more comparable to each other and follow the spatial development of drought SPI index was advised by World Meteorological Organisation to be used widely by official meteorological services. The SPI and SPEI are used for Drought Early Warning in the USA, National Drought Mitigation Center and NASA, and in the EU by the European Drought Centre (EDC) and in the Balkan Region by National Meteorological Agencies. The EDI Index has wide application in Asia. In this paper four different issues were investigated: 1) how the mathematical method used in a drought indicator's computation influence drought indices' (DI) comparative analyses; 2) the sensitivity of the DIs on any change of the length of observational period; 3) similarities between the DIs time series; 4) and how accurate DIs are when compared to historical drought records. Results suggest that it is necessary to apply a few crucial changes in the Drought Monitoring and Early Warning Systems: 1) reconsider use of SPI and SPEI family indices as a measure of quality of other indices; and for Drought Early Recognition Programs 2) switch to DIs with a solid physical background, such as EDI; 3) Adopt solid physics for modelling drought processes and define the physical measure of drought, e.g. EDI and IDEA indices; 4) investigate further the IDEA index, which, supported by our study as well, is valuable for simulation of a drought process. [ABSTRACT FROM AUTHOR]

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

Concerns about hydrological drought risk and irrigation water supply reliability have grown in recent years due to the increasing demand for water for irrigation and other uses, and the decline in water availability due to climate change. Hydrological drought insurance hedging against water supply gaps can be a key instrument for adapting irrigated agriculture to this new scenario, since it improves the resilience of the irrigation sector, which is having to cope with increasing uncertainty and vulnerability. The objective of this paper is to assess farmers' willingness to pay (WTP) for index-based hydrological drought insurance under different policy designs, considering several different amounts of insured capital, insurance deductibles, and contract terms. To that end, it uses a discrete choice experiment as the valuation method and the Sector BXII irrigation district (southern Spain) as a case study. The results show that farmers would be willing to pay for the proposed hydrological drought insurance, stating a higher preference for policy designs with lower amounts of insured capital, lower deductibles, and shorter contract terms. Moreover, the results also show the existence of heterogeneity among farmers' preferences, depending on their socio-economic characteristics. Finally, we compare the distribution of farmers' WTP for different policy design options of the proposed insurance with the commercial premium estimated using actuarial analysis. The comparison confirms that only the options with lower levels of insured capital present a mean WTP below the commercial premium, while the rest of the policy design options would need to be subsidized like other agricultural insurance schemes to make them attractive to most farmers. • Farmers are willing to pay for hydrological drought insurance. • Farmers prefer policies with low levels of insured capital, low deductibles, and short contract terms. • WTP is heterogeneous depending on farmers' socio-economic characteristics. • Only policy designs with low levels of insured capital are currently commercially viable. • Once the new drought insurance is implemented, it will become more attractive for farmers. [ABSTRACT FROM AUTHOR]

Drought indices are commonly used tools for drought characterisation and analysis. The Reconnaissance Drought Index (RDI) is one of the widely used indices, due to its high sensitivity and resilience. The basic form of the index is the ratio of the cumulative precipitation to potential evapotranspiration, for a specified reference period. The RDI is also transferred to a normalised and a standardised expression. Since the RDI incorporates both the main input and the main output of a natural water system, it is considered as an appropriate index of water availability. Based on this notion, as shown in recent studies, the RDI is suitable for the assessment of drought impacts on agriculture. In this paper, a modified version of the index, RDIe, is presented, in which precipitation is replaced by the effective precipitation. With the proposed modification, the amount of water beneficially exploited by the agricultural systems can be represented more accurately, enhancing the performance of the index for agricultural drought analysis. Further, alternative ways for the calculation of effective precipitation are presented and discussed. An application of the modified RDI in an agricultural area demonstrates its better performance in assessing the impacts of drought on the rainfed agricultural production. [ABSTRACT FROM AUTHOR]

Climate change is projected to cause an increase in the severity and frequency of extreme weather events such as heat waves and droughts. Such changes present planning and operating challenges and risks to many economic sectors. In the electricity sector, statistics of extreme events in the past have been used to help plan for future peak loads, determine associated infrastructure requirements, and evaluate operational risks, but industry-standard planning tools have yet to be coupled with or informed by temperature models to explore the impacts of the “new normal” on planning studies. For example, high ambient temperatures during heat waves reduce the output capacity and efficiency of gas-fired combustion turbines just when they are needed most to meet peak demands. This paper describes the development and application of a production cost and unit commitment model coupled to high resolution, hourly temperature data and a temperature-dependent load model. The coupled system has the ability to represent the impacts of hourly temperature on load conditions and available capacity and efficiency of combustion turbines, and therefore capture the potential impacts on system reserve and production cost. Ongoing work expands this capability to address the impacts of water availability and temperature on power grid operation. [ABSTRACT FROM AUTHOR]

Extreme environmental events such as droughts affect millions of people all around the world. Although it is not possible to prevent this type of event, its prediction under different time horizons enables the mitigation of eventual damages caused by its occurrence. An important variable for identifying occurrences of droughts is the sea surface temperature (SST). In the tropical Atlantic Ocean, SST data are collected and provided by the Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) project, which is an observation network composed of sensor buoys arranged in this region. Sensors of this type, and more generally Internet of Things (IoT) sensors, commonly lead to data losses that influence the quality of datasets collected for adjusting prediction models. In this paper, we explore the influence of temporal aggregation in predicting step-ahead SST considering different prediction horizons and different sizes for training datasets. We have conducted several experiments using data collected by PIRATA project. Our results point out scenarios for training datasets and prediction horizons indicating whether or not temporal aggregated SST time series may be beneficial for prediction. [ABSTRACT FROM AUTHOR]