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Among the list of all‐natural hazards, the unique characteristic of drought is its multiplex nature. Besides, the inherited regional characteristics and seasonal variation of drought make it more complicated. Conventional drought indices are inadequate to integrate seasonal and local elements. Therefore, to integrate seasonal components and regional factors, the present study emphasizes the following features: the existence of multiple drought monitoring indicators, the regional broadcasting of drought‐related statistics, and seasonal fluctuations. The seasonally blended regionally integrated drought index (SBRIDI) based on two‐stage Bayesian network theory comprehensively captures seasonal and regional variability embedded in individual drought indicators and regionally scattered homogeneous meteorological stations. It extracts information from a widely accepted standardized precipitation index and other multiscalar variants (standardized precipitation evapotranspiration index, standardized precipitation temperature index). It offers a better estimate of drought severity and pattern in the whole study region. The application of the SBRIDI is based on six meteorological stations located in the Gilgit Baltistan region of Pakistan. Among 216 time series datasets, the stage I Bayesian network selects 72 seasonally relevant standardized drought indices datasets, and the stage II Bayesian network selects 12 of the seasonally most prominent meteorological station datasets. Temporal graphical evidence shows that the SBRIDI can assess the drought risk and depicts the spatial extent of drought conditions at the regional level. The SBRIDI can highlight hotspots of drought‐prone regions, which could help freshwater management agencies and stakeholders. Structure of a simple Bayesian network consisting of five nodes.

Soil moisture in root zone soil layers is one of the most important indicators of agricultural drought. Thus, monitoring agricultural drought requires not only knowledge of rainfall anomaly but also quantification of soil moisture. In this study, the effects of various methods of quantifying the green vegetation fraction green vegetation fraction (GVF) on the land-surface-model (LSM)-based soil moisture drought index (SMDI) were assessed using the harvest area data of the World Meteorological Organization together with the widely used vegetation health index and drought severity index. GVF data used in this study include monthly climatological GVF, weekly advanced very high-resolution radiometer (AVHRR)-normalized difference vegetation index-based and 8-daily moderate-resolution imaging spectroradiometer (MODIS) leaf area index (LAI)-based GVF. The results show that SMDI is optimized when using the near-real-time GVF and that LAI-based GVF increases the accuracy of SMDI when monitoring early agricultural drought. The study shows that we can be confident in the accuracy of signals of emerging drought, particularly during the rapid onset of drought.

This review focuses on understanding the factors and processes affecting Global Positioning System (GPS) vertical annual cycles and the use of GPS data for monitoring drought. Instead, through GPS techniques, annual oscillations of the Earth's crust due to hydrological, climatic and or environmental factors that affect surface deformation can be identified. In order to analyze seasonal vertical crustal movements using GPS observations, assessing patterns, causes, and implications for geophysical processes. These vertical displacements have been recently employed in hydrological contexts like Total Water Storage (TWS) inversion, and the indices from these vertical seasonal shifts seem effective for drought severity assessment. In recent years, extensive research and considerable scientific efforts have been dedicated to leveraging GPS technology as a tool for systematically recording and analyzing various natural processses, including extreme environmental events such as prolonged droughts and sudden, high magnitude earthquakes. However, despite these advancements, the intricate characteristics and underlying mechanisms governing the annual oscillatory movements of the Earth's crust remain largely elusive and not yet fully comprehended. Further, while GPS-based data analysis models have made significant progress in improving the accuracy of geodetic measurements, but still exhibit notable limitations, and precision imperfect, necessitating further refinements, methodological advancements, and the integration of complementary observational datasets to enhance their reliability and effectiveness for geophysical applications. This review also discusses the variation in these movements occurring at the regional level and reasons that finer models for such movements based on specific regional characteristics need to be developed. Future research will have to cause upgrades in the data models, including multi-source data, specifically GRACE satellite observation, and effective computational methods for exacting geodetic applications. By improving the precision of the GPS data analysis and integrating multi-source datasets, this research paves the way for more accurate and real-time environmental monitoring, offering valuable insights for disaster preparedness, water resource management, and climate resilence strategies. Also, these findings will provide a better understanding and guidance for future research in this scope of studies.

This study reports a comprehensive review on drought indices used in monitoring meteorological, agricultural, hydrological, and socio-economic drought. Drought indices have been introduced as an important approach to quantitative and qualitative calculations of drought's severity and impact. There were 111 drought indices reviewed in this study, which fall into two categories: traditional (location-specific/model) and remote sensing (RS). Out of 111 indices, 44 belong to the traditional indices and 67 belong to the RS section. This study shows that meteorological drought monitoring has the highest number (22) of traditional indices, about 20% overall, while the lowest (7) agricultural drought monitoring is 6.3%. The specialty is that when considering remote sensing-based drought indices, 90% are used for agricultural drought monitoring and 10% for hydrological and meteorological drought monitoring. However, the study found that advances in satellite technology have accelerated the design of new drought indices and that replacing traditional location-specific data with satellite observation makes it easier to calculate more spatial distribution and resolution.

Drought monitoring and early warning (M & EW) systems are a crucial component of drought preparedness. M & EW systems typically make use of drought indicators such as the Standardised Precipitation Index (SPI), but such indicators are not widely used in the UK. More generally, such tools have not been well developed for hydrological (i.e. streamflow) drought. To fill these research gaps, this paper characterises meteorological and hydrological droughts, and the propagation from one to the other, using the SPI and the related Standardised Streamflow Index (SSI), with the objective of improving understanding of the drought hazard in the UK. SPI and SSI time series were calculated for 121 near-natural catchments in the UK for accumulation periods of 1–24 months. From these time series, drought events were identified and for each event, the duration and severity were calculated. The relationship between meteorological and hydrological drought was examined by cross-correlating the 1-month SSI with various SPI accumulation periods. Finally, the influence of climate and catchment properties on the hydrological drought characteristics and propagation was investigated. Results showed that at short accumulation periods meteorological drought characteristics showed little spatial variability, whilst hydrological drought characteristics showed fewer but longer and more severe droughts in the south and east than in the north and west of the UK. Propagation characteristics showed a similar spatial pattern with catchments underlain by productive aquifers, mostly in the south and east, having longer SPI accumulation periods strongly correlated with the 1-month SSI. For catchments in the north and west of the UK, which typically have little catchment storage, standard-period average annual rainfall was strongly correlated with hydrological drought and propagation characteristics. However, in the south and east, catchment properties describing storage (such as base flow index, the percentage of highly productive fractured rock and typical soil wetness) were more influential on hydrological drought characteristics. This knowledge forms a basis for more informed application of standardised indicators in the UK in the future, which could aid in the development of improved M & EW systems. Given the lack of studies applying standardised indicators to hydrological droughts, and the diversity of catchment types encompassed here, the findings could prove valuable for enhancing the hydrological aspects of drought M & EW systems in both the UK and elsewhere.

Under climate change, drought assessment, which can address nonstationarity in drought indicators and anthropogenic implications, is required to mitigate drought impacts. However, the development of drought indices for a reliable drought assessment is a challenging task in the warming climate. Thus, this study discusses factors that should be considered in developing drought indices in changing climate. Inconsistent drought assessment can be obtained, depending on the baseline period defined in developing drought indices. Therefore, the baseline period should represent the contemporary climate but should also correspond to long enough observations for stable parameter estimation. The importance of accurate potential evapotranspiration ( PET ) for drought indices becomes higher under a warming climate. Although the Penman–Monteith method yields accurate PET values, depending on the climate and vegetation cover, other suitable PET formulas, such as the Hargreaves method, with fewer hydrometeorological data can be used. Since a single drought index is not enough to properly monitor drought evolution, a method that can objectively combine multiple drought indices is required. Besides, quantifying anthropogenic impacts, which can add more uncertainty, on drought assessment is also important to adapt to the changing drought conditions and minimize human-induced drought. Drought is expected to occur more frequently with more severe, longer, and larger areal extent under global warming, since a more arid background, which climate change will provide, intensifies land–atmosphere feedback, leading to the desiccation of land and drying atmosphere. Thus, an accurate drought assessment, based on robust drought indices, is required.

Drought monitoring and early warning (M&EW) systems are an important component of agriculture/silviculture drought risk assessment. Many operational information systems rely mostly on meteorological indicators, and a few incorporate vegetation state information. However, the relationships between meteorological drought indicators and agricultural/silvicultural drought impacts vary across Europe. The details of this variability have not been elucidated sufficiently on a continental scale in Europe to inform drought risk management at administrative scales. The objective of this study is to fill this gap and evaluate how useful the variety of meteorological indicators are to assess agricultural/silvicultural drought across Europe. The first part of the analysis systematically linked meteorological drought indicators to remote sensing based vegetation indices (VIs) for Europe at NUTs3 administrative regions scale using correlation analysis for crops and forests. In a second step, a stepwise multiple linear regression model was deployed to identify variables explaining the spatial differences observed. Finally, corn crop yield in Germany was chosen as a case study to verify VIs' representativeness of agricultural drought impacts. Results show that short accumulation periods of SPI and SPEI are best linked to crop vegetation stress in most cases, which further validates the use of SPI3 in existing operational drought monitors. However, large regional differences in correlations are also revealed. Climate (temperature and precipitation) explained the largest proportion of variance, suggesting that meteorological indices are less informative of agricultural/silvicultural drought in colder/wetter parts of Europe. These findings provide important context for interpreting meteorological indices on widely used national to continental M&EW systems, leading to a better understanding of where/when such M&EW tools can be indicative of likely agricultural stress and impacts.

In this study, the authors provide a global assessment of the performance of different drought indices for monitoring drought impacts on several hydrological, agricultural, and ecological response variables. For this purpose, they compare the performance of several drought indices [the standardized precipitation index (SPI); four versions of the Palmer drought severity index (PDSI); and the standardized precipitation evapotranspiration index (SPEI)] to predict changes in streamflow, soil moisture, forest growth, and crop yield. The authors found a superior capability of the SPEI and the SPI drought indices, which are calculated on different time scales than the Palmer indices to capture the drought impacts on the aforementioned hydrological, agricultural, and ecological variables. They detected small differences in the comparative performance of the SPI and the SPEI indices, but the SPEI was the drought index that best captured the responses of the assessed variables to drought in summer, the season in which more drought-related impacts are recorded and in which drought monitoring is critical. Hence, the SPEI shows improved capability to identify drought impacts as compared with the SPI. In conclusion, it seems reasonable to recommend the use of the SPEI if the responses of the variables of interest to drought are not known a priori.

This review study examines the state of meteorological drought over Africa, focusing on historical trends, impacts, mitigation strategies, and future prospects. Relevant meteorological drought-related articles were systematically sourced from credible bibliographic databases covering African subregions in the twentieth and twenty-first centuries (i.e. from 1950 to 2021), using suitable keywords. Past studies show evidence of the occurrence of extreme drought events across the continent. The underlying mechanisms are mostly attributed to complex interactions of dynamical and thermodynamical mechanisms. The resultant impact is evidenced in the decline of agricultural activities and water resources and the environmental degradation across all subregions. Projected changes show recovery from drought events in the west/east African domain, while the south and north regions indicate a tendency for increasing drought characteristics. The apparent intricate link between the continent’s development and climate variability, including the reoccurrence of drought events, calls for paradigm shifts in policy direction. Key resources meant for the infrastructural and technological growth of the economy are being diverted to develop coping mechanisms to adapt to climate change effects, which are changing. Efficient service delivery to drought-prone hotspots, strengthening of drought monitoring, forecasting, early warning, and response systems, and improved research on the combined effects of anthropogenic activities and changes in climate systems are valuable to practitioners, researchers, and policymakers regarding drought management in Africa today and in the future.

In the context of disaster management, drought may seem a relatively harmless natural hazard, but according to the Food and Agricultural Organization (FAO) more than 2 billion people have been affected by drought since 1900 and more than 11 million people died because of it since 1900. These alarming numbers show quite clearly that information concerning droughts needs to be gathered and analyzed in a structured manner by using advanced technologies, so the effects of droughts can be minimized. Our research has its focus on the usage of information systems in the management of droughts in South Asia. It is designed as desk research. We concentrate on documents released by institutions such as International Water Management Institute and apply the method of document analysis. First, the paper defines disaster management and its different stages, then the natural hazard drought itself, followed by the state of the art of existing information systems. The conclusion provides improvement proposals for the usage of information systems in the field of disaster management.