Risk assessment of drought in Yun-Gui-Guang of China jointly using the Standardized Precipitation Index and vulnerability curves

Drought disasters cause great economic losses in China every year, especially in its southwest, and they have had a major influence on economic development, lives, and property. In this study, precipitation and drought hazards were examined for a region covering Yunnan, Guizhou, and Guangxi Provinces to assess the spatial and temporal distribution of different drought hazard grades in this region. Annual precipitation data from 90 meteorological stations in or around the study area were collected and organized for the period of 1964–2013. A spatiotemporal covariance model was calculated and fitted. The Bayesian maximum entropy (BME) method, which considers physical knowledge bases to reduce errors, was used to provide an optimal estimation of annual precipitation. Regional annual precipitation distributions were determined. To analyze the spatiotemporal patterns of the drought hazard, the annual standardized precipitation index was used to measure drought severity. A method that involves space–time scan statistics was used to detect the most likely spatiotemporal clusters of the drought hazards. Test-significance p values for all of the calculated clusters were less than 0.001, indicating a high significance level. The results showed that Yunnan Province was a drought-prone area, especially in its northwest and center, followed by Guizhou Province. In addition, Yunnan and Guizhou Provinces were cluster areas of severe and extreme drought. The most likely cluster year was 1966; it was clustered five times during the study period. In this study, the evolutionary process of drought hazards, including spatiotemporal distribution and spatiotemporal clustering characteristics, was considered. The results may be used to provide support for prevention and mitigation of drought in the study area such as optimizing the distribution of drought-resisting resources, drought monitoring, and evaluating potential drought impacts.

Quantitative assessment of soybean drought risk in Bengbu city based on disaster loss risk curve and DSSAT

Natural disasters worldwide regularly impact on human activities. As a frequently occurring natural disaster, drought has adverse impacts on agricultural production. The Lancang-Mekong River is a transnational river running through China and five Southeast Asian countries and it is a vital water resource for irrigation in the region. Drought in the Lancang-Mekong Region (LMR) has occurred frequently in recent years. Assessing the risk of drought in the region is essential for rational planning of agricultural production and formulation of drought relief measures. In this study, an assessment of drought risk has been achieved by combining the hazard and vulnerability assessments for drought. The assessment of the drought hazard depends mainly on the standardized precipitation index (SPI). The assessment of drought vulnerability takes into account various indicators such as climatic factors (e.g., crop water stress index), soil factors (e.g., available water capacity), and irrigation factors (e.g., irrigation support). The results reveal that: (1) Drought distribution in the LMR is characterized by a spreading of the drought to countries along the middle and lower reaches of the Mekong River. Countries located in the middle and lower reaches of the Mekong River are more prone to drought. Laos, Thailand, and Cambodia are the regions with higher and high-drought risk levels. (2) The spatial distributions for the drought hazard and the drought vulnerability in the LMR exhibit significant differences as evidenced in the mapping results. High-hazard and high-vulnerability areas are mainly distributed in the middle LMR, and the middle to higher hazard areas and the middle to higher vulnerability areas are mainly distributed in the south-central LMR, while the low-hazard areas and the low-vulnerability areas are mainly in the north. (3) The majority of planting areas for sugarcane, rice, and cassava are located in the high-hazard areas. The distributions of drought-prone and high-hazard areas also correspond to the main agricultural areas in the LMR.

A critical stage in drought risk assessment is the measurement of drought hazard, the probability of occurrence of a potentially damaging event. The standard approach to assess drought hazard is based on the standardized precipitation index (SPI) and a drought intensity classification established according to a fixed set of SPI values. We show that this method does not allow for the assessment of region-specific hazards, and we propose an alternative method based on the extreme value theory. We model precipitation using an extreme value mixture model, with a normal distribution for the bulk, and a generalized Pareto distribution for the upper and lower tails. The model estimation allows us to identify the threshold value below which precipitation can be qualified as extreme. The quantile function is used to measure the intensity of each category of droughts and calculate the drought hazard index (DHI). By construction, the DHI value varies according to the specific characteristics of the left tail of the precipitation distribution. To test the relevance of our approach, we estimate the DHI over a gridded set of rainfall data covering West Africa, a large and climatically heterogeneous region. The results show that our mixture model fits the data better than the model used for SPI calculation. In particular, our model performs better to identify extreme precipitation in the left tail of the distribution. The DHI map highlights clusters of high drought hazard located in the central part of the region under study.

Drought has multiple impacts on socioeconomic sectors, and it is expected to increase in the coming years due to non-stationary nature of climate change and variability. Drought hazard and vulnerability are investigated based on hydro-meteorological and actual socioeconomic data for provinces of Turkey. Drought vulnerability and risk assessment are essential parts of drought phenomenon; however, lack of proper integrated drought risk assessment in Turkey (and elsewhere) might lead to higher socioeconomic impacts. Drought Hazard Index (DHI) is derived based on the probability of drought occurrences using Standardized Precipitation Index (SPI). Besides, Drought Vulnerability Index (DVI) is calculated by utilizing four socioeconomic indicators to quantify drought impact on society. Finally, Drought Risk Index (DRI) is obtained by multiplying DHI and DVI for provinces of Turkey to highlight the relative importance of hazard and vulnerability assessment for drought risk management. A set of drought hazard, vulnerability, and composite risk map is prepared for further interpretations. The analyses reveal that among 81 administrative provinces, 73 are exposed to low drought risk (0 < DRI < 0.25), 6 provinces to moderate drought risk (0.25 < DRI < 0.50), and 1 province (Konya) to high drought risk (0.50 < DRI < 0.75). These maps can assist stakeholders to identify the regional drought vulnerability to help mitigation strategy developments and for effective water resource management.

This study contributes to a proof-of-concept comprehensive drought risk assessment for Vietnam by (i) incorporating drought exposure and vulnerability based on specific socio-economic conditions of the regions; and (ii) using satellite data including World Meteorological Organization (WMO) Space-based Weather and Climate Extremes Monitoring (SWCEM) products, and The National Aeronautics and Space Administration (NASA)-Enhanced U.S Department of Agriculture (USDA)'s Soil Moisture Active Passive (SMAP) Global Data for drought hazard assessment. Drought risk assessment which incorporated hazard, exposure and vulnerability components was conducted for 27 provinces from four administrative areas in Vietnam. Drought Hazard Index (DHI) was derived using the Standardised Precipitation Index (SPI), the Vegetation Health Index (VHI), and surface soil moisture (SSM) to take into account the impact of both meteorological and agricultural drought. Drought Exposure Index (DEI) and Drought Vulnerability Index (DVI) were calculated using statistical data of land use and socio-economic characteristics obtained from Vietnam’s statistical yearbooks. By combining DHI, DEI and DVI, a composite Drought Risk Index (DRI) was derived for drought risk assessment in the selected provinces for 2020. It was shown that the highest at-risk provinces were in the Mekong River Delta, the agricultural production centre of Vietnam. The South East regions were less impacted by drought compared to other regions. The proposed comprehensive approach to drought risk assessment in Vietnam has potential to contribute to improving drought preparedness and resilience of communities at-risk.

The drought has enormous adverse effects on agriculture, water resources and environment, and causes damages around the world. Drought risk assessment and prioritization of drought management can help decision makers and planners to manage the adverse effects of drought. This paper aims to determine the risk of drought in Iran. At the first stage, standardized precipitation index (SPI) was calculated for the period 1981–2016. Then the probability map of different drought classes or drought hazard probability map were prepared. After that the indicator-based vulnerability assessment method was used to determine the drought vulnerability index. Five indices including climate, topography, waterway density, land use and groundwater resources were chosen as the most critical factors of drought in Iran and followed by the analytical hierarchy process questionnaire, the weights of each index were obtained based on expert opinions. Fuzzy membership maps of each index and sub-index were prepared using ArcGIS software. The drought vulnerability map of Iran was plotted using these weights and maps of each indicator. Finally, the drought risk map of Iran was provided by multiplying drought hazard and vulnerability maps. According to the 43-completed questionnaires by experts, climate index has the highest vulnerability to drought. Climate does not have an important role in drought hazard index, but it is the most crucial factor to classified drought vulnerability index. The results showed that central, northeast, southeast and west parts of Iran are at high risks of drought. There are regions with different risks in Iran due to unusual weather and climatic conditions. We realized that the climate and the groundwater situation is almost the same in the central, east and south parts of Iran, because the land use plays a crucial role in the drought vulnerability and risk in these areas. The drought risk decreases from the center of Iran to the southwest and northwest.

This study attempts to determine the spatial and temporal patterns of drought hazard and risk in Semnan province, Iran. Drought risk assessment has been conducted in eight counties of Semnan province using a conceptual framework which emphasizes on the combined role of hazard and vulnerability in defining droughts. The standardized precipitation index (SPI) at synoptic stations at 3 and 12-month time step for period 1985–2011 were used to provide drought hazard index (DHI) map using kriging interpolation and natural break methods by ArcGIS 9.3 software. Eight obtainable/quantifiable socioeconomic and physical indicators including population density, rural ratio, agricultural occupation, irrigated land, food production, and municipal, industrial, and agricultural water consumption were used to provide the map of drought vulnerability index (DVI). Finally, the map of drought risk index (DRI) was provided through the integration of DHI and DVI maps. The overall results showed that at 3-month timescale Shahroud and Damghan and at 12-month timescale Shahroud, Damghan, and Semnan are the most susceptible regions to drought in central Iran. Therefore, consideration of virtual water, cultivation of products with less water requirement and use of appropriate irrigation methods can be two important factors in water demand management which should be addressed by water resource managers.

In this paper standardized precipitation index (SPI) is used to assess meteorological drought for all 30 districts covering 10 agro-climatic zones in an eastern Indian state, Odisha. Monthly rainfall data of 115 years (1901-2015) for all 30 districts of Odisha are analyzed using SPI on 1, 3, 6, 9 and 12-month timescale. These timescales reflect the impact of drought on the availability of different water resources. Results indicate that in all the agro-climatic zones of Odisha, mild drought events have the highest frequencies of occurrence followed by moderate drought events for different timescales. Severe and extreme drought frequencies are comparatively lesser than mild and moderate drought frequencies. SPI analysis shows that 32-46 years are affected by mild drought, 4-16 years affected by moderate drought, 1-9 years are affected by severe drought and 1-5 years are affected by extreme drought during study period of 115 years in different agro-climatic zones of Odisha. It is observed 50.3% areas in the state are affected by drought in June out of which chances of occurrence of mild drought is maximum (28.7%). In the months of July, August and September, 51.7, 48.5 and 46.1% areas are affected by droughts. On average 49.15% areas of the entire state is affected by drought of various intensities out of which the share of mild, moderate, severe and extreme drought is 28.38, 13.28, 5.06 and 2.43%, respectively.

Drought characterization and risk assessment are of great significance due to drought’s negative impact on human health, economy, and ecosystem. This paper investigates drought characterization and risk assessment in the Lempa River basin in Central America. We applied the Standardized Evapotranspiration Deficit Index (SEDI) for drought characterization and drought hazard index (DHI) calculation. Although SEDI’s applicability is theoretically proven, it has been rarely applied. Drought risk is generally derived from the interactions between drought hazard (DHI) and vulnerability (DVI) indices but neglects resilience’s inherent impact. Accordingly, we propose incorporating DHI, DVI, and drought resilience index (DREI) to calculate drought risk index (DRI). Since system factors are not equally vulnerable, i.e., they are heterogeneous, our methodology applies the Analytic Hierarchy Process (AHP) to find the weights of the selected factors for the DVI computation. Finally, we propose a geometric mean method for DRI calculation. Results show a rise in DHI during 2006–2010 that affected DRI. We depict the applicability of SEDI via its relationship with El Nino-La Nina and El Salvador’s cereal production. This research provides a systematic drought risk assessment approach that is useful for decision-makers to allocate resources more smartly or intervene in Drought Risk Reduction (DRR). This research is also useful for those interested in socioeconomic drought.

Drought happen when the rainfall decreases in the extreme condition for long period of time (above normal). Drought hazard mapping can be analyzed by various approaches, like environmental approach, ecological approach, hydrological approach, meteorological approach, geological approach, agricultural approach, and many other. Meteorological, Climatological, and Geophysical Agency (in Indonesia a.k.a BMKG) measures the drought hazard by utilizing Standardized Precipitation Index (SPI)The comparison of rainfall rate through SPI has positive correlation with drought type, for example SPI 3 indicates agricultural drought; while SPI 6, SPI 9 and SPI 12 indicate hydrological drought. The analysis of drought hazard level also can be done using soil moisture level measurement. Soil moisture is the result of water shortages in the hydroclimatological concept. Soil moisture analysis utilizes several influenced variables, such as soil water, precipitation, evapotranspiration, and percolation. Each of variables was analyzed using GIS as a method of soil moisture modeling. Drought index level analysis is using soil moisture deficit index, which indicates that drought occurs if the index score less than (-0.5). Some assumptions used in this modeling are both SMDI modeling using WHC (Water Holding Capacity) and without using WHC. This modeling used medium term analysis during 2007-2012 to prove the occurrence of extreme drought on 2009 and 2012 for measurement of drought level in agriculture area. Based on SMDI, it is known that the dangers of SMDI drought have positive correlation to SPI 3, SPI 6, SPI 9, and SPI 12, where SPI is in accordance with the interpretation of meteorolgy, agriculture, and hydrological drought indices.

&amp;lt;p&amp;gt;Droughts have huge negative impacts on livelihoods and economies throughout the world, and climate change is expected to increase their future frequency and severity. For an effective drought management, drought risk assessment is considered of major importance. However, despite the high number of studies, shared and clear guidelines to perform drought risk assessments are missing, undermining the overall reliability of this procedure. A significant limitation common to most drought risk assessments is the lack of any form of validation. Moreover, checking the robustness of the assessment tools is of paramount importance, but appropriate data are usually not available for external validation; hence, internal validations are in many cases the only option. For this scope, we propose a simple but robust uncertainty analysis, using the methodology presented in the &amp;amp;#8220;Handbook on constructing composite indicators&amp;amp;#8221; of OECD (2008). An additional deficiency of most drought risk assessments is the missing link between the results and possible adaptation strategies. To address this limitation, we propose to use archetype analysis, which is an emerging approach for identifying recurrent patterns within cases and supporting a context-specific generalization of insights.&amp;amp;#160;&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The innovations introduced were applied to a drought risk assessment performed for the agricultural systems of five coastal watersheds of central and southern Tuscany, Italy. These watersheds are particularly prone to drought impacts because of the high concurrent water demand for domestic and agricultural uses during the summer months. To allow a better discretization, municipalities were selected as units of analysis. A total of 42 indicators were used to represent drought hazard, exposure, and vulnerability. Multiple drought hazard indicators were selected to estimate both past and future drought hazards, using ready-to-use data from public institutions. Overall, the southern part of Tuscany showed to be the most at risk, in particular the Grosseto province. For the robustness evaluation, we (1) excluded individual exposure and vulnerability indicators, (2) included the excluded indicators with the multicollinearity analysis, (3) assigned different weights, and (4) used an alternative aggregation method to calculate the composite risk indicator. Results in terms of average shifts in rankings and new rankings assigned revealed that the most uncertain parts were the selection of exposure indicators and the assignment of weights, but overall, the rankings were confirmed. The archetype analysis yielded as result seven clusters of municipalities; their characteristics were analysed and tailored adaptation strategies were proposed according to their specific drought risk profiles.&amp;lt;/p&amp;gt;

Drought is considered a natural hazard and has become a recurrent phenomenon in Algeria since the 1970s. Algeria is characterized by three different climates, namely, sub-humid, semi-arid and arid climates. In this study, we aimed to spatiotemporally assess drought hazard, vulnerability and risk in the three climates of three sub-basins, namely, the Seybouse Maritime, Wadi Djelfa-Hadjia and Wadi M’Zi sub-basins. To this end, the standardized precipitation index (SPI) and the reconnaissance drought index (RDI) were used to evaluate drought physical characteristics on a 12-month timescale, based on precipitation and temperature monthly data covering the period of 1979–2019. High values of the coefficient of determination (R2) (0.76–0.99) confirmed by low values of the root-mean-square error (RMSE) (0.08–0.49) proved that the drought indices displayed a high correlation. Drought hazard and vulnerability were evaluated based on physical characteristics and socioeconomic aspects, respectively. The results led to the determination of a high correlation between the two indices used; the determination of the main drought events; and the mapping of the drought hazard, vulnerability and risk using a geographic information system (GIS). These findings suggest that the SPI provided the highest intensities, while the longest periods and the strongest magnitudes were given by the RDI. The spatiotemporal drought distributions varied with time from station to station and from sub-basin to sub-basin. Risk maps revealed that vulnerability based on socioeconomic factors controls drought risk.

Over the past decade, the Horn of Africa (HoA) has been plagued by recurrent drought events that have had devastating impacts on the population. The frequency, duration and severity of these droughts are expected to increase in the wake of global warming, leading to higher losses and damages if the vulnerability of the population is not reduced. Monitoring and early warning systems for droughts are based on various drought hazard indicators. However, assessments of how these indicators are linked to impacts are rare. For adequate drought management, it is essential to understand and characterise the drivers of drought impacts, especially in the HoA, where most studies focus either on meteorological droughts, agricultural droughts or the propagation of droughts through the hydrological cycle, without considering the relationship between hazard and impact. Drought hazard indices alone cannot capture the vulnerability of the system. In this study, we identify meaningful indices for the occurrence of region- and sector-specific impacts. We assess the effectiveness of socio-economic clustering in categorising counties based on common characteristics and their correlation with historical drought impacts (malnutrition, milk production and trekking distances to water sources). Using Random Forest (RF) and Spearman correlation analyses, we examine the link between drought indices (Standardised Precipitation Index, Standardised Precipitation Evapotranspiration Index, Standardised Soil Moisture Index, Standardised Streamflow Index and Vegetation Condition Index) with different accumulation periods and the impact data. We find that clustering regions based on vulnerability proxies significantly improves the hazard-impact relationship, emphasising the importance of considering vulnerability factors in drought risk assessment. Our results indicate an impact-specific relationship that is strongly influenced by the vulnerability of the region. In particular, household and livestock distance to water is most strongly associated with medium- to long-term precipitation-based indices (2-10 months), while milk production can be associated with a variety of indices with different accumulation periods (5-24 months), and malnutrition is correlated with precipitation- and streamflow-based indices (5-24 months). Household and livestock distance to water is well modelled by clusters reflecting low access to improved sanitation and safe water sources, high poverty, aridity and gender disparities. Malnutrition was well modelled by clusters related to aridity, average precipitation, food consumption score, access to water sources, improved sanitation and poverty levels. The type of clustering used in modelling the impact of drought on milk production does not have a major impact on the performance of the models. We then apply this relationship to hindcast drought indices to obtain impact data on individual counties for periods when no impact monitoring was done yet. With that information we estimate the associated risk under specific climatic conditions. By recognising the drivers and vulnerability factors that influence the sensitivity of counties to drought, communities can better prepare and mitigate the impacts of drought.

Groundwater plays an important role in mitigating drought. It is necessary to analyze the spatiotemporal variation characteristics of groundwater and establish an appropriate assessment for the risk of drought for disaster prevention. This study developed a novel approach for the drought risk assessment system based on the Hilbert Huang Transform (HHT) method to understand the spatial distribution of the risk of drought in terms of groundwater. We analyzed drought vulnerability applying the HHT to analyze the variation characteristics of groundwater level spatiotemporally and the physical mechanism of groundwater factors to quantify groundwater sensitivity to the environment, and present the resilience of each region. Furthermore, the drought hazard was determined using the standardized precipitation index and the dynamic drought intensity gave the durability characteristics of each region. The drought exposure was also investigated, which quantifies the water demand to satisfy people’s livelihoods for a certain population density. Based on the framework proposed in this study, an overall risk map of droughts in the Pingtung Plain was obtained. This study effectively classified the main time–frequency characteristics, the availability of groundwater, and the risk of drought in each region. A total of 11 of the 45 groundwater monitoring stations are located at the highest risk of level 5, most of which are located in the coastal area of Gaoping River and Linbian River. Over-pumping should be avoided in these areas. On the contrary, the alluvial fan area showed the lowest groundwater risk of drought. The results can be adopted for water management, drought resilience, sustainable development of groundwater resources, and decision making in determining drought risk.