Agricultural drought risk assessment of Northern New South Wales, Australia using geospatial techniques

The role of large reservoirs in drought and flood disaster risk mitigation: A case of the Yellow River Basin

The acceleration of water cycle processes in the context of global warming will exacerbate the frequency and intensity of extreme events and predispose to drought and flood disasters (DFD). The Yellow River Basin (YRB) is one of the basins with significant and sensitive impacts of climate change, comprehensive assessment and prediction of its DFD risk are of great significance for ecological protection and high-quality development. This study first constructed an evaluation index system for drought disaster risk and flood disaster risk based on hazard, vulnerability, exposure and the role of large reservoirs. Secondly, the weights of each evaluation index are established by the analytic hierarchy process. Finally, based on the four-factor theory of disasters, an evaluation model of DFD risk indicators is established. The impact of large reservoirs on DFD risk in the YRB is analyzed with emphasis. The results show that from 1990 to 2020, the drought disaster risk in the YRB is mainly distributed in the source area of the Yellow River and the northwest region (11.26-15.79 %), and the flood disaster risk is mainly distributed in the middle and lower reaches (30.04-31.29 %). Compared to scenarios without considering large reservoirs, the area at risk of high drought and high flood is reduced by 45.45 %, 44.22 % and 31.29 % in 2000, 2010 and 2020, respectively. Large reservoirs in the YRB play an important role in mitigating DFD risk, but their role is weakened with the enhancement of the emission scenario. Under the influence of different scenario models, the DFD risk in the YRB in 2030 and 2060 will increase, and the area of high drought and high flood risk in the middle and upper reaches of the basin will increase by 0.26-25.15 %. Therefore, the YRB should play the role of large reservoirs in DFD risk defense in its actions to cope with future climate change, while improving non-engineering measures such as early warning and emergency management systems to mitigate the impacts of disasters.

Interaction of drought-influencing factors for drought mitigation strategies in Lam Ta Kong Watershed, Khorat Plateau

Generally, drought is influenced by both spatial characteristics and anthropogenic activities within an area. Drought vulnerability assessment is a critical tool that can be effectively used to develop proper drought mitigation strategies to prevent avoidable losses. To develop suitable drought mitigation strategies, the overall drought vulnerability must be assessed, and the interaction among drought-influencing factors in the area should be considered. Consequently, this study aimed to investigate the interactions among critical drought-influencing factors and drought vulnerability in the Lam Ta Kong Watershed via spatial analysis with the analytical hierarchy process (AHP) and geographical information system (GIS) technology. Ten drought-influencing factors were considered in the vulnerability assessment: slope, elevation, soil texture, soil fertility, stream density, precipitation, temperature, precipitation days, evaporation, and land use. The results indicated that the critical drought-influencing factors were precipitation, precipitation days, and land use, resulting in most of the watershed experiencing high drought vulnerability (35.1% of the watershed or 1810.83 km2). Moreover, this research highlighted the interactions among the critical drought-influencing factors. Precipitation interacted with precipitation days to cause drought vulnerability across the watershed, with a p-value <0.05. Similarly, the interactions between precipitation and land use and between precipitation days and land use, with p-values <0.05, showed that they were associated with and influenced by drought in the Lam Ta Kong Watershed. This study further indicated that appropriate drought mitigation strategies for this watershed must consider the interactions among these drought-influencing factors, as well as their specific interactions across the watershed.

Study on agricultural drought disaster risk assessment in Heilongjiang reclamation area based on SSAPSO optimization projection pursuit model

Heilongjiang reclamation area serves as a crucial hub for commodity grain production and strategic reserves in China, playing a vital role in maintaining national food security. Investigating the assessment of agricultural drought risk in this region can yield valuable insights into spatial and temporal variations in drought risk. Such insights can aid in formulating effective strategies for disaster prevention and mitigation, thereby minimizing food losses caused by drought disasters. This study employs a comprehensive indicator system comprising 17 indicators categorized into hazard, exposure, vulnerability, and resistance capacity. The projection pursuit model is applied to evaluate regional drought risk, while the PSO algorithm, optimized by the SSA algorithm, addresses the limitations of low local search ability and search accuracy during the large-scale search process of the PSO optimization algorithm. This study examines and compares the optimization and convergence capabilities of three algorithms: real number encoding-based genetic algorithm (RAGA), particle swarm optimization algorithm (PSO), and sparrow algorithm-based improved particle swarm optimization algorithm (SSAPSO). The analysis demonstrates that SSAPSO exhibits superior optimization performance and convergence properties, establishing it as a highly effective algorithm for optimization tasks. The findings reveal the following trends: over time, agricultural drought risk in Heilongjiang reclamation area has generally declined, with fluctuations observed in hazard and vulnerability, an increase in exposure, and a continuous enhancement of resistance capacity. Spatially, the western region exhibits significantly higher agricultural drought risk compared to the eastern region, primarily due to elevated hazard and vulnerability, coupled with lower resistance capacity. As the agricultural economy grows and agricultural expertise accumulates, the risk of agricultural drought decreases. However, variations in economic growth among different regions lead to diverse spatial distributions of risk.

Drought risk assessment on the eastern part of Indian peninsula-a study on Purulia district, West Bengal

This study focuses on measuring the spatial nature of drought risk which is conceived as the product of drought severity, drought vulnerability, and drought exposure in the Purulia district, located in the eastern part of the Indian peninsula. Drought severity is measured using the Standard Precipitation Index and drought vulnerability is calculated as the average condition of meteorological, hydrological, agricultural, and socio-economic drought. The drought types and drought exposure conditions are the outcome of multi-criteria analysis where the Fuzzy Analytical Hierarchy Process is used for assigning weights to the respective parameters and the Analytical Hierarchy Process is used for determining the class ranks. 31.46% of the total district area has registered moderate to high and high vulnerability to drought situations, while 16.57% of the entire district area has been found moderate to high and highly exposed to drought situations. Similarly, 39.39% of the district's total area is under a significant drought risk. Blocks like Barabazar (75.49%), Jhalda-I (71.85%), and Purulia-II (52.66%) have the majority of their area under extreme drought risk conditions. The modeled outcome of drought vulnerability was found significant while being tested with phenomena highly correlated to drought events, land surface temperature, and aridity index. The computed spatial profile of the districts' drought risk condition is of substantial help for the policymakers in preparing effective drought mitigation measures to restrict drought impacts reasonably.

Hazard assessment of global warming around the world using GIS

Global warming is among the important environmental problems of the earth. The present research aims to study temperature variations around the world. For this purpose, the monthly temperature data of 178 points from the NOAA site were studied from 1950 to 2019. In this study, the temperature changes were investigated in terms of its increase, decrease, and significance level by the Mann-Kendall method. Geographic Information System (GIS) and interpolation methods were used to determine the changes in temperature in global warming maps. According to the obtained results, except for 3.8% of the designated area, other parts of the world show change toward warmer conditions. Overall, the world's land temperature has increased by 1.08℃ during the study period. Also, about 85% of the designated area shows moderate and severe hazardous conditions in terms of global warming. The spatial analysis showed higher change and hazardous conditions for global warming in mid-longitude and high-latitude close to both poles.

Assessment of dynamic drought-induced ecosystem risk: Integrating time-varying hazard frequency, exposure and vulnerability

Terrestrial ecosystems, occupying 28.26% of Earth's surface, are extensively at risk from droughts, which is likely to propagate into human communities owing to loss of vital services. Ecosystem risk also tends to fluctuate within anthropogenically-forced nonstationary environments, raising considerable concerns about effectiveness of mitigation strategies. This study aims to assess dynamic ecosystem risk induced by droughts and identify risk hotspots. Bivariate nonstationary drought frequency was initially derived as a hazard component of risk. By coupling vegetation coverage and biomass quantity, a two-dimensional exposure indicator was developed. Trivariate likelihood of vegetation decline was calculated under arbitrary droughts to intuitively determine ecosystem vulnerability. Ultimately, time-variant drought frequency, exposure and vulnerability were multiplied to derive dynamic ecosystem risk, followed by hotspot and attribution analyses. Risk assessment implemented in the drought-prevalent Pearl River basin (PRB) of China during 1982-2017 showed that meteorological droughts in eastern and western margins, although less frequent, were prolonged and aggravated in contrast to prevalence of less persistent and severe droughts in the middle. In 86.12% of the PRB, ecosystem exposure maintains high levels (0.62). Relatively high vulnerability (>0.5) occurs in water-demanding agroecosystems, exhibiting a northwest-southeast-directed extension. A 0.1-degree risk atlas unveils that high and medium risks occupy 18.96% and 37.99% of the PRB, while risks are magnified in the north. The most pressing hotspots with high risk continuing to escalate reside in the East River and Hongliu River basins. Our results provide knowledge of composition, spatio-temporal variability and driving mechanism of drought-induced ecosystem risk, which will assist in risk-based mitigation prioritization.

Sources and uncertainties of future global drought risk with ISIMIP2b climate scenarios and socioeconomic indicators

The severity of potential drought impacts is influenced not only by physical characteristics, such as precipitation, soil moisture, and temperature but also by local socioeconomic conditions that influence a region's exposure and vulnerability. This study aims to demonstrate projected future global drought risk, which is quantified based on indicators representing three risk components, namely, hazard, exposure, and vulnerability. Drought hazard is evaluated using the standardized precipitation-evapotranspiration index. Drought exposure considers population and agricultural land use, and drought vulnerability accounts for gross domestic product, total water storage, and water consumption. This global-scale study was conducted for the historical and future periods of 1975-2005 and 2070-2099, respectively, and employed three combined scenarios consisting of Representative Concentration Pathways (RCPs) and Shared Socioeconomic Pathways (SSPs) with datasets from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b). To evaluate the proposed approach, the results obtained for the historical period were compared with drought records. The projections suggest that in addition to increasing drought hazards caused by climate change, populous regions, or areas heavily dependent on agriculture are at a higher risk than other regions because of high water consumption levels. The contributions analysis indicates that agricultural land use is the largest contributor to drought risk, except for Africa, where the population makes the largest contribution. Model uncertainty of the General Circulation Models (GCMs) and Hydrological Models (HMs) is dominant compared to the RCP and SSP scenarios, with uncertainty from the GCMs the most dominant. This study provides possible depictions and their uncertainties of future drought risks and can assist decision-makers in developing better adaptation and mitigation strategies for climatic, environmental, and socioeconomic changes.

Quantitative Evaluation and Obstacle Factor Diagnosis of Agricultural Drought Disaster Risk Using Connection Number and Information Entropy

To promote the application of entropy concepts in uncertainty analysis of water resources complex system, a quantitative evaluation and obstacle factor diagnosis model of agricultural drought disaster risk was proposed using connection number and information entropy. The results applied to Suzhou City showed that the agricultural drought disaster risks in Suzhou during 2007–2017 were all in middle-risk status, while it presented a decreasing trend from 2010. The information entropy values of the difference degree item bI were markedly lower than those of the difference degree b, indicating that bI provided more information in the evaluation process. Furthermore, the status of drought damage sensitivity and drought hazard were improved significantly. Nevertheless, high exposure to drought and weak drought resistance capacity seriously impeded the reduction of risk. Thus, the key to decreasing risk was to maintain the level of damage sensitivity, while the difficulties were to reduce exposure and enhance resistance. In addition, the percentage of the agricultural population, population density, and percentage of effective irrigation area were the main obstacle factors of risk and also the key points of risk control in Suzhou. In short, the results suggest that the evaluation and diagnosis method is effective and conducive to regional drought disaster risk management.

Drought Vulnerability Assessment Using Geospatial Techniques in Southern Queensland, Australia

In Australia, droughts are recurring events that tremendously affect environmental, agricultural and socio-economic activities. Southern Queensland is one of the most drought-prone regions in Australia. Consequently, a comprehensive drought vulnerability mapping is essential to generate a drought vulnerability map that can help develop and implement drought mitigation strategies. The study aimed to prepare a comprehensive drought vulnerability map that combines drought categories using geospatial techniques and to assess the spatial extent of the vulnerability of droughts in southern Queensland. A total of 14 drought-influencing criteria were selected for three drought categories, specifically, meteorological, hydrological and agricultural. The specific criteria spatial layers were prepared and weighted using the fuzzy analytical hierarchy process. Individual categories of drought vulnerability maps were prepared from their specific indices. Finally, the overall drought vulnerability map was generated by combining the indices using spatial analysis. Results revealed that approximately 79.60% of the southern Queensland region is moderately to extremely vulnerable to drought. The findings of this study were validated successfully through the receiver operating characteristics curve (ROC) and the area under the curve (AUC) approach using previous historical drought records. Results can be helpful for decision makers to develop and apply proactive drought mitigation strategies.

Evaluating the performance of eight drought indices for capturing soil moisture dynamics in various vegetation regions over China

Drought is pervasive global hazard and seriously impacts ecology. Particularly, vegetation drought, which is chiefly driven by soil moisture (SM) deficiency, has a direct bearing on grain production and human livelihoods. Various drought indices associated with vegetation and SM conditions have been proposed to monitor and detect vegetation drought. In this study, we evaluated the performance of eight drought indices, including Drought Severity Index (DSI), Evaporation Stress Index (ESI), Normalized Vegetation Supply Water Index (NVSWI), Temperature-Vegetation Dryness Index (TVDI), Temperature Vegetation Precipitation Dryness Index (TVPDI), Vegetation Health Index (VHI), Self-calibrating Palmer Drought Severity Index (SC-PDSI) and Standardized Precipitation Evapotranspiration Index (SPEI), for capturing SM dynamic (derived from Copernicus Climate Change Service) across the six main vegetation coverage types of China. Our results showed DSI and ESI had the best overall performance. When exploring the reasons for the uncertainty of these indices (except SC-PDSI and SPEI) in the evaluation, we found that, in the non-arable regions, the time lag effect of drought indices on SM, the average state and rangeability of corresponding variables and the climatic conditions (precipitation and temperature) all impacted the performance of DSI, ESI, NVSWI, TVPDI and VHI. In the arable region, cropland types (paddy field and non-paddy field) and the uncertainty of SM data mainly caused the uncertainties of the above five indices. With regard to the TVDI, abnormalities of dry and wet edges fitting may be the primary factor affecting its performance. These results demonstrated that these drought indices with reliable and robust performance of capturing SM dynamics can be suggested to characterize the trend of SM. Certainly, this study can provide a reference for the improvement of existing drought indices and the establishment of new drought indices.