Spatiotemporal Characteristics of Meteorological Drought During the Past Half Century in Different Climates Over Iran

The present study compares the main characteristics (intensity, duration, and frequency) of meteorological drought events in the four climates (Hyperarid, Arid, Semiarid, and Humid) of Iran. For this purpose, three drought indices, including Standardized Precipitation Index (SPI), Reconnaissance Drought Index (RDI), and Standardized Precipitation Evapotranspiration Index (SPEI), were employed at the timescales of 1-, 3-, 6-, 9- and 12-months. These indices were compared by utilizing long-term data of 41 synoptic meteorological stations for the recent half century, 1969–2019. The long-term analysis of drought indices indicates that the duration and intensity of drought events have temporally risen after the 1998–99 period. Iran has experienced the longest duration (40 months) of extreme drought during Dec 98–Mar 02 and Jan 18–Mar 18, respectively. Spatial patterns demonstrate that drought intensity uniformly increased in SPI1 to SPI12, and SPEI3 to SPEI12, from humid and semiarid to arid and hyperarid regions. The average drought duration in studied stations for SPI, SPEI and RDI indices equaled 9, 12, and 9 months, respectively. In addition, mean drought frequencies are calculated at 14, 17, and 13 percent for SPI, SPEI and RDI indices, respectively. Generally, SPEI compared to SPI and RDI shows greater duration and frequency of drought events, particularly in arid and hyperarid regions. The research shows the crucial role of climatic variables in detecting drought characteristics and the importance of selecting appropriate drought indices in various climates.

Hydrological Drought Assessment Based on the Standardized Streamflow Index: A Case Study of the Three Cape Provinces of South Africa

Global impacts of drought conditions pose a major challenge towards the achievement of the 2030 Sustainable Development Goals. As a result, a clarion call for nations to take actions aimed at mitigating the adverse negative effects, managing key natural resources and strengthening socioeconomic development can never be overemphasized. The present study evaluated hydrological drought conditions in three Cape provinces (Eastern, Western and Northern Cape) of South Africa, based on the Standardized Streamflow Index (SSI) calculated at 3- and 6-month accumulation periods from streamflow data spanning over the 3.5 decades. The SSI features were quantified by assessing the corresponding annual trends computed by using the Modified Mann–Kendall test. Drought conditions were also characterized in terms of the duration and severity across the three Cape provinces. The return levels of drought duration (DD) and drought severity (DS) associated with 2-, 5-, 10-, 20- and 50-year periods were estimated based on the generalized extreme value (GEV) distribution. The results indicate that hydrological drought conditions have become more frequent and yet exhibit spatial contrasts throughout the study region during the analyzed period. To this end, there is compelling evidence that DD and DS have increased over time in the three Cape provinces. Return levels analysis across the studied periods also indicate that DD and DS are expected to be predominant across the three Cape provinces, becoming more prolonged and severe during the extended periods (e.g., 20- and 50-year). The results of the present study (a) contribute to the scientific discourse of drought monitoring, forecasting and prediction and (b) provide practical insights on the nature of drought occurrences in the region. Consequently, the study provides the basis for policy- and decision-making in support of preparedness for and adaptation to the drought risks in the water-linked sectors and robust water resource management. Based on the results reported in this study, it is recommended that water agencies and the government should be more proactive in searching for better strategies to improve water resources management and drought mitigation in the region.

Framework for Monitoring the Spatiotemporal Distribution and Clustering of Drought Characteristics in Hunan Province

Drought is a widespread phenomenon in the context of global climate change. Owing to the geographical location of Hunan Province in the middle reaches of Yangtze River and the abundance of forests area in this region with a large population, there is a need to focus on the impacts of drought for devising policies. The spatiotemporal distribution scheme of a given area must be determined to plan water management and protect ecosystems effectively. This study proposes a framework for exploring the spatiotemporal distribution model of drought using comprehensive surveys of historical meteorological stations, which consists of two parts, namely the characteristics of drought extraction in the spatiotemporal distribution and drought models discovered by the clustering method. Firstly, we utilized the run theory to extract drought characteristics, such as drought duration, drought severity, and drought intensity. Secondly, the K-means clustering method was adopted to explore the distribution patterns on the basis of the drought characteristics. Lastly, the method was applied to Hunan Province. Results show that historical drought conditions can be monitored with their characteristics of spatiotemporal variability. Three drought distribution clusters exist in this region. Cluster 1 in western Hunan tends to be a long-term, low-intensity drought, cluster 2 in the southern part tends to be a short-term, high-intensity drought, and cluster 3 in the central part is prone to severe drought. The proposed framework is flexible as it allows parameters to be adjusted and extraction methods to achieve reasonable results for a given area.

Spatio-temporal evaluation of drought characteristics in the Dhasan basin

ABSTRACT. The meteorological drought characteristics including onset, departure, duration, severity as well as intensity have been evaluated mainly for monsoon season at all the three rain gauge stations located in Dhasan basin. The Standardized Precipitation Index (SPI) has been applied to understand and quantify the drought severity on multiple time scale (1, 3, 6, 12 and 24 months). The spatiotemporal analysis of drought based on 3-month SPI has also carried out to identify drought years and the regions of the study area which is under the grip of continuous drought events. Based on the 3-month SPI, major drought events have been identified. The maximum drought severity of -11.17 occurred during November 1991 to August 1992 having the longest duration of 10 months, in the area under Sagar rain gauging station. The onset of most of the drought events in the basin take place during the beginning of Kharif season and terminate by the end of August or September, so affect the agricultural crops severely. The spatial variation indicates that during June 2002, about 55.74% of basin area was experiencing severe drought conditions, followed by 35.29% area under moderate drought condition and only 8.97% area faced mild drought conditions. The inter-relationship among the drought duration, number of drought events, drought severity and time scale have been studied.

Evaluation and Forecasting Meteorological Drought, Case Study: Kohgilooyeh and Boyer Ahmad

The SPI is the most widely used drought index to provide an acceptable estimation of drought characteristics. The objective of this study was to compare different threshold levels effect on derived drought characteristics, assessment of the spatial variation of meteorological drought properties as well as drought frequency, duration, and value in Kohgilooyeh and Boyer Ahmad Province, Iran, using SPI for 1, 3, 6, 12, 24 and 48 months lead-times, and finally SPI forecasting using Artificial Neural Networks (ANNs). For the first threshold level (scenario), drought properties are extracted based on the standard level of zero, and for the second one, -1 is considered. Results showed that the frequency of drought and wet periods decreased from SPI-1 to 48 for both scenarios in all stations. Max drought duration of stations had an increasing trend from SPI-1 to 48. The average duration of dry periods changed as a function of the time scales; it increased from SPI-1 to 48. Spatial variation of the drought average duration was considerable for long-term drought. Max SPI value did not follow any spatial variation, as it was constant for all lead times in all stations. Average SPI values had a decreasing trend from SPI-1 to 9 but increased from SPI-9 to 48 in all stations. Max average of SPI value observed in short-term drought and min value in medium-term. SPI value general trend was similar in both scenarios, therefore drought threshold level did not affect the results. The third objective was to develop neural network models for drought forecasting. Different architectures are applied to find the best models to forecast SPI over various lead times. The best forecasting results for SPI-3 and 6, obtained from the Quasi-Newton training algorithm, when for SPI-1, 9, 12, 24, and 48, Levenberg-Marquardt was the best. There was an increasing trend in performance measure R2 from SPI-1 to 48 and a decreasing trend in Root Mean Square Error (RMSE). The best input lead-time for SPI-1 to 48 decreased from 11 to 1, the number of hidden layers decreased, but there was no significant trend in hidden neurons. Drought properties could be considered in water resources management to supply water for various demands.

An analysis of drought evolution characteristics based on standardized precipitation index: a case study in Southwest Guizhou Autonomous Prefecture, China

Drought is a worldwide concerned issue which causes huge losses in agriculture, economic and damages in natural ecosystems. The precise assessment of drought evolution characteristics is essential for agricultural water management and drought resistance, while such work is rarely reported. Thus, eight meteorological stations located within the Southwest Guizhou Autonomous Prefecture (SGAP) were selected, and the Standardized Precipitation Index (SPI) was used to assess the drought evolution characteristics. The results revealed that the drought occurrences number in Pu'an station was the largest (23 droughts), and the average drought duration in Xingren station was the longest (48.75 months). Moreover, the drought characteristics of the eight stations have account for the largest proportion under normal conditions, was more than 60%, the frequency of drought disaster occurring in Xingren is the highest (30.05%), followed by Wangmo (23.73%). The results of this study will provide theoretical guidance for drought resistance and agricultural production in Southwest Guizhou Autonomous Prefecture of China.

CMIP6 Model-projected Hydroclimatic and Drought Changes and Their Causes in the 21st Century

Drought is projected to become more severe and widespread as global warming continues in the 21st century, but hydroclimatic changes and their drivers are not well examined in the latest projections from the Phase Six of the Coupled Model Inetercomparison Project (CMIP6). Here, precipitation (P), evapotranspiration (E), soil moisture (SM), and runoff (R) from 25 CMIP6 models, together with self-calibrated Palmer Drought Severity Index with Penman-Monteith potential evapotranspiration (scPDSIpm), are analyzed to quantify hydroclimatic and drought changes in the 21st century and the underlying causes. Results confirm consistent drying in these hydroclimatic metrics across most of the Americas (including the Amazon), Europe and the Mediterranean region, southern Africa, and Australia; although the drying magnitude differs, with the drying being more severe and widespread in surface SM than in total SM. Global drought frequency based on surface SM and scPDSIpm increases by ~25%–100% (50%–200%) under the SSP2-4.5 (SSP5-8.5) scenario in the 21st century together with large increases in drought duration and areas, which result from a decrease in the mean and flattening of the probability distribution functions of SM and scPDSIpm; while the R-based drought changes are relatively small. Changes in both P and E contribute to the SM change, whereas scPDSIpm decreases result from ubiquitous PET increases and P decreases over subtropical areas. The R changes are determined primarily by P changes, while the PET change explains most of the E increase. Inter-model spreads in surface SM and R changes are large, leading to large uncertainties in the drought projections.

Plant structural and nutritional responses to drought differ among common pasture species

In the face of a changing climate, research indicates that more frequent and severe drought conditions are critical problems that will constrain production of high-quality forage and influence the performance of grazing animals in the future. In addition, the duration of drought and potential trade-offs between plant morphology and nutritional composition may influence plant drought adaptation strategies across pasture species, and the consequences for forage quality are not well understood. Here we present the results of a study investigating the effects of drought on biomass productivity, dead material, leaf:stem biomass allocation and nutritional composition (whole-plant and tissue-specific) across nine diverse pasture species. For this, we conducted a field experiment exposing species to a 6-month period of simulated severe drought (60% rainfall reduction during winter and spring) and samples were collected at multiple harvests. We found that drought had different, harvest-specific effects on plant biomass structure and nutritional composition among pasture species. The severity of drought impacts on productivity, but not on nutritional quality, increased with drought duration. In general, drought strongly reduced productivity, increased the percentage of dead material and had mixed effects (increases, decreases and no effect) on leaf:stem ratio and concentrations of crude protein, non-structural carbohydrates, neutral detergent fibre and lignin. Changes in plant-level nutritional quality were driven by simultaneous changes in both leaf and stem tissues for most, but not all, species. Our findings may be especially helpful for selection of adapted species/cultivars that could minimize potential drought risks on forage, thereby optimising pasture performance under future drought scenarios.

Extreme Droughts Change in the Mekong River Basin: A Multidisciplinary Analysis Based on Satellite Data

This study evaluates droughts in the Mekong River Basin (MKB) based on a multidisciplinary method, mainly using the Standardized Precipitation Index (SPI) and Mann–Kendall (MK) test. Precipitation data corresponding to the seasonality of the regional climate were retrieved from Integrated Multi-satellitE Retrievals for Global Precipitation Measurement from 2001 to 2020, at a monthly temporal scale and 0.1 degree spatial resolution. Drought events and their average interval, duration, and severity were determined based on Run theory. Our results revealed the most extreme drought period was in January 2014, at the time the lowest precipitation occurred. Spatial extreme drought results indicated that Zone 2 in the upstream MKB has the highest frequency of drought, with 44 events observed during 19 years, and experiences the most severe droughts, whereas Zone 24 in the downstream MKB has the most prolonged drought duration of seven months. The periods and locations of extreme drought were identified using the SPI, corresponding to historic droughts of the MKB. Furthermore, the MK test shows an increasing trend of droughts in the lower MKB and the cluster analysis identified six clusters of times series. Overall, our study provides essential findings for international and national water resource stakeholders in identifying trends of extreme drought in the MKB.