Spatial Characteristics Of Drought Research Articles

Analysis of Meteorological Drought in Cases of North Wello Zone, Ethiopia

Drought is a commonly used term, but the most complex and least realized of all the natural hazards affecting more people than any other hazards. The main objective of the study was to investigate the spatial-temporal occurrence of Meteorological drought indices analysis in the study areas. The study was undertaken to investigate the magnitude, frequency, and trends of drought incidence in North Wello Zone Ethiopia using monthly rainfall records for the period 1990 to 2020 of North Wello zone stations and CHIRPS satellite data. Drought Index Calculator used to analyse standard precipitation index (SPI). The correlation between station data and CHIRPS data in this study was 0.89 which shows highly correlation between them. the result of meteorological drought indices map analysis on the years 1999, 2000, and 2008 severely dry to extremely dry conditions in the Belg season, similarly in 19990, 199308, 201507, 201508, and 201509 have got meteorological drought indices with extremely dry Kiremt season on the North Wello Zone. The drought magnitude of different time scales varied from slight to extremely severe in the studied stations. The identification of the temporal and spatial characteristics of droughts in the North Wello Zone will be useful for the development of a drought preparedness plan in the Zone. Generally increasing tendencies of drought were observed during the main rainy season and decreasing tendencies of drought during the short rainy season and annual scale were observed in the study area.

Analysis of Temporal and Spatial Drought Characteristics in Iraq Using the Standard Precipitation Index (SPI)

Analysis of Temporal and Spatial Drought Characteristics in Iraq Using the Standard Precipitation Index (SPI)

Spatial characterization of drought through CHIRPS and a station-based dataset in the Eastern Mediterranean

Abstract. Drought is a natural hazard which occurs in all climatic zones and affects different sectors, such as irrigation, energy, water supply, and ecology. Monitoring and predicting drought are pressing challenges, as drought is becoming more common and severe owing to the impacts of climate change and increased climatic variability. However, in many areas of the globe, the temporal and spatial characterization of droughts and drought severities are hindered by a lack of reliable, locally-measured long-term data and unevenly distributed, erratic meteorological stations. In this situation, remote sensing datasets such as Climate Hazards Group InfraRed Precipitation with Station Data (CHIRPS) can offer valuable insights into long-term developments and the spatial characteristics of droughts. Nonetheless, it is often uncertain to which extent data such as CHIRPS succeeds in representing local dynamics and how this varies between geographical regions and climate zones. In this analysis, we aim to evaluate spatial drought conditions over the Seyhan River basin in Turkey in the Eastern Mediterranean. Using the Standardized Precipitation Index (SPI) as a drought index, the applicability of CHIRPS as a long-term satellite precipitation product for drought monitoring is investigated. We compare two spatial representations of the SPI: one derived on a per-pixel basis from CHIRPS data since 1981, the other based on data from 19 meteorological stations scattered across the basin, which was spatialized using inverse distance weighted interpolation (IDW). Our results offer insights into the relative accuracy of CHIRPS data and avenues towards optimizing the quality of spatial drought characterization.

Drought Spatial Extent and Dependence Increase During Drought Propagation From the Atmosphere to the Hydrosphere

AbstractAs droughts propagate both in time and space, their impacts increase because of changes in drought properties. Because temporal and spatial drought propagation are mostly studied separately, it is yet unknown how drought spatial extent and connectedness change as droughts propagate though the hydrological cycle from precipitation to streamflow and groundwater. Here, we use a large‐sample dataset of 70 catchments in Central Europe to study the propagation of local and spatial drought characteristics. We show that drought propagation leads to longer, later, and fewer droughts with larger spatial extents. 75% of the precipitation droughts propagate to P‐ET, among these 20% propagate further to streamflow and 10% to groundwater. Of the streamflow droughts, 40% propagate to groundwater. Drought extent and dependence increase during drought propagation along the drought propagation pathway from precipitation to streamflow thanks to synchronizing effects of the land‐surface but decreases again for groundwater because of sub‐surface heterogeneity.

Drought Characterization in Croatia Using E-OBS Gridded Data

Droughts are among the major natural hazards that are spreading to many parts of the world, with huge multi-dimensional impacts. An extensive analysis of drought phenomenon is presented for continental Croatia based on a meteorological E-OBS gridded dataset (0.25° × 0.25°), within the period of 1950–2022. The drought events were characterized by the Standardized Precipitation Evapotranspiration Index (SPEI), applied to different time-scales (6 and 12 months), in order to describe the subannual and annual variability of drought. The spatiotemporal patterns of drought are obtained through principal component analysis (PCA) and K-means clustering (KMC) applied to the SPEI field. An areal drought evolution analysis and the changes in the frequency of occurrence of the periods under drought conditions were achieved using a kernel occurrence rate estimator (KORE). The modified Mann–Kendall (MMK) test, coupled with the Sen’s slope estimator test, are applied to the SPEI series in order to quantify the drought trends throughout the country. According to the history drought events and considering the different morphoclimatic characteristics of the study area, the results showed that Croatia could be divided into three different and spatially well-defined regions with specific temporal and spatial characteristics of droughts (central northern, eastern and southern regions). A manifest increase is shown in the percentage of area affected by drought, as well as in the yearly drought occurrences rates, in both central northern and eastern regions, and an evident decrease is shown in the southern region for both 6- and 12-month SPEI time-scales. In the observation of the drought’s temporal characteristics, it was found that downward trends expressing increasing drought severities were strongly significant in northern and eastern regions, while a few significant upward trends were seen in the southern region. From this study, it is possible to obtain a broader view of the historical behaviour of droughts in Croatia, with the results providing useful support for drought risk assessment and decision-making processes.

Assessment of drought trends in the Upper Ewaso Ng'iro River Basin using the SPI and SPEI

Abstract Drought assessment is necessary for creating adaptation and resilience measures for the livelihoods of the affected communities. This study assessed drought trends in Kenya's Upper Ewaso Ng'iro River Basin (UENB) from 1981 to 2020. A Standardized Precipitation Index (SPI), a precipitation-based index, and a Standardized Precipitation Evapotranspiration Index (SPEI), a multivariate index that considers the difference between precipitation and potential evapotranspiration (PET), were used to evaluate drought severity and frequency over varying timescales. Monthly rainfall and temperature data for 10 stations within the basin were analyzed to calculate the SPI and SPEI time series values for 3, 6, and 12 months. The results demonstrate an alarming increase in the severity and frequency of drought events in the UENB since 1999. Additionally, the study reveals that the SPI and SPEI indices differ in identifying temporal and spatial drought characteristics, with longer timescales showing improved accuracy. Notably, the SPEI identifies more extensive and severe drought periods in the region compared to the SPI. The research findings are crucial in guiding policy decisions related to SDGs as they provide valuable information on drought trends necessary for implementing effective drought adaptation and resilience measures and promoting sustainable development in the UENB.

Temporal and spatial characteristics of drought, future changes and possible drivers over Upper Awash Basin, Ethiopia, using SPI and SPEI

Temporal and spatial characteristics of drought, future changes and possible drivers over Upper Awash Basin, Ethiopia, using SPI and SPEI

Spatiotemporal variability in annual drought severity, duration, and frequency from 1901 to 2020

Drought is currently one of the most severe natural disasters affecting the world. Therefore, characterizing the temporal and spatial characteristics of droughts is critical to managing drought disasters and coping with global climate change. In this study, we apply the ensemble empirical mode decomposition (EEMD), empirical orthogonal function (EOF) decomposition, and the drought event division method of run theory to analyze the temporal and spatial characteristics of meteorological droughts across the globe from 1901 to 2020 using the self-calibrated Palmer drought severity index (scPDSI). We found that the world was gradually becoming wetter from 1901 to 2020, but the severity and duration of severe and extreme drought events also increased. In contrast to the PDSI, which showed no obvious short-period changes, the annual drought severity (ADS) had short cycle changes of 8 and 17 yr. Based on the EOF decomposition results of drought characteristics, dry and wet trends of local PDSI are inconsistent with increasing or decreasing trends of severe and extreme drought events. This research on the temporal and spatial decomposition of severe and extreme drought events provides a new perspective on drought research and analysis, which is critical for the further characterization of drought and the prevention and management of drought disasters.

Spatio-temporal analysis of dry and wet periods in Iran by using Global Precipitation Climatology Center-Drought Index (GPCC-DI)

In this study, the temporal and spatial characteristics of droughts in Iran, including severity, duration, frequency, and extent, were studied using the GPCC-DI, in a 68-year period from 1952 to 2019. To display and analyze these features, time trend components, intensity, duration, and area diagrams, Mann-Kendall non-parametric test and Kriging geostatistical method were used. The result of plotting intensity-duration-frequency maps shows an increasing trend in regional drought severity and spread. It was also found that the most severe droughts occurred in the 12- and 24-month periods from 2000 onward. Mann-Kendall test results also show that significant increases in droughts occurred in the central desert basins of Hamoon basin and south Baluchistan in the southeastern Iran. In addition, decrease in occurrences of dry and wet periods happened in the western, northwestern, and coastal regions of the Caspian Sea. The pattern of spatial variations of drought severity indicated two major drought foci in southeast and central Iran. The number of drought centers in Iran has also increased over time. The results of the analysis of the time trends of dry and wet periods point to the occurrence of continuous droughts in 12- and 24-month periods.

Analysis of Agricultural Drought Using Remotely Sensed Evapotranspiration in a Data-Scarce Catchment

Understanding spatial drought characteristics is vital for planning adaptation and mitigation measures in river catchments. In many parts of the world, spatial drought information is not available due to lack of adequate evenly distributed data for spatial drought analyses. This study elucidates a spatial drought analysis in a data-scarce tropical catchment using remote sensing actual evapotranspiration (ET) and potential evapotranspiration (PET) data. Firstly, the time series of 690 images of remotely sensed ET and PET between the years 2000 and 2014 were spatially analyzed using the evapotranspiration deficit index (ETDI) approach to obtain ETDIs in the Kilombero River catchment (Tanzania). Then, spatio-temporal patterns of ETDIs were used to characterize drought frequency, total drought durations, total drought severity, and drought intensity. The frequency, durations, severity, and intensity of drought increased from the year 2000 towards 2014, causing substantial drought changes in the catchment. However, drought intensity revealed that those changes were mainly from no drought and mild drought to moderate drought. Between the years 2000 and 2014, no-drought areas and mild drought areas declined from 10% to 0% and from 42% to 19%, respectively, whereas moderate drought areas increased from 47% to 81% of the catchment size. Those changes of drought conditions were partly attributed to anthropogenic land cover change, especially in the southwest grasslands, and were partly attributed to meteorological factors in other parts of the catchment. This information is crucial for further land cover change and climate change investigations, as well as planning water and land resources in the Kilombero River catchment. Moreover, the study also demonstrates the potential of using publicly available remote sensing ET products and the ETDI approach for spatially characterizing drought in ungauged regions.

Prediction of droughts over Pakistan using machine learning algorithms

Climate change has increased frequency, severity and areal extent of droughts across the world in the last few decades magnifying their adverse impacts. Prediction of droughts is immensely helpful in early warning and preparing the most vulnerable communities to their adverse impacts. For the first time, this study investigated the potential of developing drought prediction models over Pakistan using three state-of-the-art Machine Learning (ML) techniques; Support Vector Machine (SVM), Artificial Neural Network (ANN) and k-Nearest Neighbour (KNN). Three categories of droughts; moderate, severe, and extreme considering two major cropping seasons called Rabi and Kharif were estimated using Standardized Precipitation Evaporation Index (SPEI) and then predicted using the predictor data obtained from the National Centres for Environmental Prediction/National Centre for Atmospheric Research (NCEP/NCAR) reanalysis database. Also, for the first time in drought modelling, a novel feature selection approach called Recursive Feature Elimination (RFE) was used for identifying optimum sets of predictors. In validation, SVM-based models were able to better capture the temporal and spatial characteristics of droughts over Pakistan compared to those by ANN and KNN-based models. KNN which was used in developing drought models for the first time displayed limited performance in comparison to that by SVM and ANN-based drought models, in validation. It was found that in the Rabi season SPEI is positively correlated with relative humidity over the Mediterranean Sea and the region north of the Caspian Sea. In the Kharif season, SPEI is positively correlated with the humid region over the south-eastern part of the Bay of Bengal and the regions north of the Mediterranean and Caspian Seas. In developing a drought prediction model for Pakistan, relative humidity, temperature and wind speed should be considered with a domain which encompasses the Mediterranean Sea, the region north of the Caspian Sea, the Indian Ocean and the Arabian Sea.

Intensification of historical drought over China based on a multi‐model drought index

AbstractObservations show that in recent decades, a large area of China has been affected by drought and that frequent droughts have caused damage to the ecological environment and the economy. Because of the differences in data and methods, assessing regional droughts often leads to contradictory conclusions of trending. The self‐calibrated Palmer drought severity index (scPDSI) is based on multiple parameters, and it is considered regionally applicable and is widely used. However, some divergence has been observed in the results of drought in China using different scPDSI_PM (scPDSI based on the Penman–Monteith model) datasets. We establish an integrated scPDSI dataset (scPDSI_PM_INT) by averaging three scPDSI products and analyse the temporal change and spatial characteristics of drought in China from 1950 to 2009. The annual and seasonal drought intensities have increased slightly in the past 60 years, while the disturbed area has broadened significantly, especially in eastern China which has become much drier than before. The drought intensity of most drought‐prone regions is slight and moderate, while severe and extreme droughts occur mostly in the Agro‐Pastoral Transitional Zone and the Beijing–Tianjin–Hebei Region.

TEMPORAL AND SPATIAL CHANGES OF DROUGHT IN BEIJING-TIANJIN-HEBEI REGION BASED ON REMOTE SENSING TECHNOLOGY

Abstract. Drought is an extremely complex natural disaster phenomenon. Sustained drought will lead to the aggravation of water shortage, food production reduction, land desertification and ecological crisis, which will have a great impact on social and economic development, industrial and agricultural production and ecological environment. In recent years, human activities have intensified, the global climate has been warming, and the frequency and intensity of extreme events such as drought have been continuously strengthened, which has been widely concerned by scholars at home and abroad. The Beijing-Tianjin-Hebei region, as the political and cultural center of China, is seriously affected by the drought, which has a certain impact on the social economy of the region. Therefore, it is of great practical significance to carry out remote sensing drought monitoring and understand the temporal and spatial characteristics of drought. Based on MOD13A2 and MOD11A2 in MODIS products, this paper constructed the NDVI-Ts feature space to obtain the Temperature Vegetation Dryness Index (TVDI) in Beijing-Tianjin-Hebei region, and analyzed the spatial and temporal variation characteristics of drought in Beijing-Tianjin-Hebei region from 2001 to 2014 with TVDI as the drought index. The results showed that: (1) the NDVI-Ts feature space in the Beijing-Tianjin-Hebei region showed that when the value of NDVI rose from 0 to 1, the maximum temperature of the surface gradually decreased, while the minimum temperature gradually rose. Both of them had a linear relationship with NDVI, and their spatial shape was similar to a triangle, indicating that the study of drought in Beijing-Tianjin-Hebei was effective by using this spatial feature; (2) the Beijing-Tianjin-Hebei region experienced drought every year in the period of 2001–2014, and the drought was more serious in 2001, 2004, 2008, 2009, 2011 and 2012; (3) The drought in the Beijing-Tianjin-Hebei region was widespread, and the severely arid regions were mainly concentrated in the southern and central regions. In terms of drought intensity, the most frequent occurrences in the period of 2001–2014 were Xingtai, Hengshui, Shijiazhuang, and Handan, and the annual drought in 14 years; the least number of occurrences was Chengde, a total of 4 times; the number of occurrences was second only to Chengde, Tangshan, Zhangjiakou, Qinhuangdao, a total of 7 times. Our results indicated that the Beijing-Tianjin-Hebei region was prone to drought and the drought degree was severe.

Temporal and spatial characteristics of droughts and floods in northern China from 1644 to 1911

This study analyses the temporal and spatial distributions of droughts and floods in northern China during the Qing Dynasty (1636–1912), with data ranging from 1644 to 1911, or nearly the entire dynastic period. Variations in the intensities of droughts and floods are investigated across different timescales and with respect to their spatial variation. The impacts and physical mechanisms of solar activity as well as surface temperatures of the Pacific Ocean on drought and flood intensities in northern China are analysed using a cross-wavelet method. The results reveal periodicities on scales of 10–11, 20–22, 45–50 and 90–100 yrs. Seven rapid changes are found on the 10-yr scale and four are found on the 30-yr scale. Analysing the spatial distribution of drought and flood intensities, we found a trend of decreasing precipitation from east to west. Precipitation over the Shandong region, which is in the eastern part of the study area, is significantly higher than that of the other regions, which may be explained by its coastal location and the resultant rich water vapour content of the atmosphere. Analyses of cross-wavelet power spectra and coherence spectra among the different drought and flood intensities and the Niño3 regional sea surface temperature (SST) index series and sunspot series indicate significant correlations between the drought and flood series and the Niño3 SST index series at scales of 2–4 and 8–12 yrs, and the phase difference differs across the different timescales. Furthermore, the drought and flood series and the sunspot series are closely correlated at a scale of 8–14 yrs.

Sensitivity of drought resilience-vulnerability- exposure to hydrologic ratios in contiguous United States

The atmospheric water supply and demand dynamics determine a region’s potential water resources. The hydrologic ratios, such as, aridity index, evaporation ratio and runoff coefficients are useful indicators to quantify the atmospheric water dynamics at watershed to regional scales. In this study, we developed a modeling framework using a machine learning approach to predict hydrologic ratios for watersheds located in contiguous United States (CONUS) by utilizing a set of climate, soil, vegetation, and topographic variables. Overall, the proposed modeling framework is able to simulate the hydrologic ratios at watershed scale with a considerable accuracy. The concept of non-parametric elasticity was applied to study the potential influence of the estimated hydrologic ratios on various drought characteristics (resilience, vulnerability, and exposure) for river basins located in CONUS. Spatial sensitivity of drought indicators to hydrologic ratios suggests that an increase in hydrologic ratios may result in augmentation of magnitude of drought indicators in majority of the river basins. Aridity index seems to have higher influence on drought characteristics in comparison to other hydrologic ratios. It was observed that the machine learning approach based on random forests algorithm can efficiently estimate the spatial distribution of hydrologic ratios provided sufficient data is available. In addition to that, the non-parametric based elasticity approach can identify the potential influence of hydrologic ratios on spatial drought characteristics.

Probabilistic Analysis of Drought Spatiotemporal Characteristics in the Beijing-Tianjin-Hebei Metropolitan Area in China

The temporal and spatial characteristics of meteorological drought have been investigated to provide a framework of methodologies for the analysis of drought in the Beijing-Tianjin-Hebei metropolitan area (BTHMA) in China. Using the Reconnaissance Drought Index (RDI) as an indicator of drought severity, the characteristics of droughts have been examined. The Beijing-Tianjin-Hebei metropolitan area was divided into 253 grid-cells of 27 × 27km and monthly precipitation data for the period of 1960–2010 from 33 meteorological stations were used for global interpolation of precipitation using spatial co-ordinate data. Drought severity was assessed from the estimated gridded RDI values at multiple time scales. Firstly, the temporal and spatial characteristics of droughts were analyzed, and then drought severity-areal extent-frequency (SAF) annual curves were developed. The analysis indicated that the frequency of moderate and severe droughts was about 9.10% in the BTHMA. Using the SAF curves, the return period of selected severe drought events was assessed. The identification of the temporal and spatial characteristics of droughts in the BTHMA will be useful for the development of a drought preparedness plan in the region.

A study on the temporal and spatial characteristics of droughts following earthquakes

According to the “jacking-up” theory, which relates the cause of earthquakes to outer core convection ascension bodies, the crust will gradually recover after an earthquake. In such cases, the crust is stretched, the underground temperature is reduced, precipitation decreases, and drought occurs. In this paper, precipitation is compared with ground temperature and seismic data to determine the spatial and temporal relationship between earthquakes and subsequent droughts. Our objective is to develop a new method of drought prediction. With a few exceptions in location, the analysis of the first drought to occur after the Ms ≥ 7 earthquakes in mainland China and the adjacent areas since 1950 shows that droughts tended to occur in regions near earthquake epicenters and in the eastern regions of the epicenters at the same latitude within six months after the earthquakes. In addition, and the differences between the starting time of the earthquakes and the droughts nearly share the same probability of 0 to 6 months. After careful analysis of 34 Ms ≥ 6.5 earthquakes occurring in western China from 1980 to 2011, we determined that a second drought tends to occur approximately six months following the first drought, indicating a quasi-half-year period. Moreover, the duration of the quasi-half-year fluctuation increases with the magnitude of earthquake, at approximately 2.5 years for Ms 6.5 earthquake and approximately 5 years for Ms 8 earthquake

Analysis on spatial and temporal characteristics drought of Yunnan Province

Since the beginning of the 21st century, the global warming trend is an increasing cause for concern. Frequent extreme weather events occur under the conditions of global change. Exploring the relationship between climate change and drought disasters using climate change performance characteristics has become a prime research problem. It is increasingly important to study the temporal and spatial distribution of aridity and drought causes in the southwest region. We collected meteorological data from 16 meteorological stations from 1956 to 2010 in Yunnan Province of Southwest China, and used a composite index (CI) of meteorological drought to analyze temporal and spatial characteristics of droughts in the province. Based on daily CI values of each station during the 50years, drought processes there were confirmed individually. Occurrence frequencies, scopes and severities of meteorological droughts were computed and analyzed to reveal their temporal and spatial occurrence patterns in different parts of the province. The results are as follows: (1) Temperature in the province, showing the well-being of the turn, has an obvious 4-year principal cycle. Temperature gradually rose after 1980. Fluctuation of precipitation was relatively stable, with a cycle of about 2years. (2) On the spatial scale, drought occurred over wide areas in the province. Its overall distribution showed a gradual increase from northwest to southeast. Drought days were the most numerous in the southeast, and fewer in the southwest. (3) Examining seasonal variation, the occurrence of spring droughts was high. The multi-year average of drought frequency exceeded 70%. The frequency of summer and autumn drought was less, and that of winter drought was highest. (4) The causes of drought are complex, comprising the combined effects of atmospheric circulation, geography, and human factors. There was a strong negative correlation between the interannual variation of drought days and precipitation anomaly values. With warming temperatures, the chances for regional drought significantly increased, but the interaction mechanism remains unexplained and should be explored in the future. The climate in Yunnan Province has typical characteristics. The temperature and extreme weather of recent years has certainly changed in response to global climate change, and has caused regional disasters. The aforementioned mechanism represents the next research direction.

Temporal trends and spatial characteristics of drought and rainfall in arid and semiarid regions of Iran

AbstractDrought, a normal recurrent event in arid and semiarid lands such as Iran, is typically of a temporary nature usually leaving little permanent aftermath. In the current study, the rainfall and drought severity time series were analyzed at 10 stations in the eastern half of Iran for the period 1966–2005. The drought severity was computed using the Standardized Precipitation Index (SPI) for a 12‐month timescale. The trend analyses of the data were also performed using the Kendall and Spearman tests. The results of this study showed that the rainfall and drought severity data had high variations to average values in the study period, and these variations increased with increasing aridity towards the south of the study area. The negative serial correlations found in the seasonal and annual rainfall time series were mostly insignificant. The trend tests detected a significant decreasing trend in the spring rainfall series of Birjand station at the rate of 8.56 mm per season per decade and a significant increasing trend in the summer rainfall series of Torbateheydarieh station at the rate of 0.14 mm per season per decade, whereas the rest of the trends were insignificant. Furthermore, the 12‐month values of the standardized precipitation index decreased at all the stations except Zabol during the past four decades. During the study period, all of the stations experienced at least one extreme drought which mainly occurred in the winter season. Copyright © 2011 John Wiley & Sons, Ltd.

Assessing temporal and spatial characteristics of droughts in the Hirfanli dam basin, Turkey.

Regional drought analysis provides useful information for a sustainable water resources management. The characteristics of meteorological droughts in the HirfanlA± Dam Basin, a semi-arid region in Turkey were determined using the Standardized Precipitation Index (SPI) as a measure for drought severity. The region covers upstream drainage areas of the KA±zA±lA±rmak River, one of the major water resources of the country, and is subject to frequent drought events. Using the temporal and spatial characteristics of monthly SPI, drought intensity-areal extent-frequency curves for various return periods were constructed for the region. The intensity area extent and return periods of selected historical droughts in the region were obtained and an evaluation of the drought severities was presented. Key words: Drought, semi-arid region, SPI, frequency curve, return period, kriging, The HirfanlA± dam basin, Turkey.