Spatiotemporal Patterns Of Drought Research Articles

Rainfall trends and spatiotemporal patterns of meteorological drought in Menna watershed, northwestern Ethiopia

Understanding the spatiotemporal patterns of drought is crucial for planning, disaster preparedness, vulnerability assessment, impact evaluation, and policy formulation to mitigate drought-induced effects. The purpose of this study was to assess rainfall trends and spatiotemporal patterns of meteorological drought using geospatial techniques in Menna watershed. The Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) rainfall, and station-based observed rainfall were the datasets used. The station-based rainfall was used to confirm the accuracy of CHIRPS rainfall data. The Mann-Kendall (MK) test and Sen's slope estimator were utilized to assess trends and ascertain the extent of change. To characterize meteorological droughts, percent of normal (PN), standardized anomaly index (SAI), and standardized precipitation index (SPI) were computed during the crop growing seasons (2000–2022). The validation result confirmed a strong agreement between the observed and CHIRPS rainfall data (R2 = 0.88). Based on the MK test, an increasing trend has been observed in annual (3.7 mm/year) and belg (3.4 mm/year) rainfall, which was significant at p < 0.05. But the kiremt season was slightly decreasing (−0.7 mm/year). The PN, SAI, and SPI values detected that 2002, 2004, 2009, 2011, 2014, 2015, and 2019 were drought years in the area. Even only 1.4, 0.2, and 0.5% of the watershed were free from drought in 2009, 2014, and 2015, respectively, due to extremely high rainfall deficiency. Conversely, 2001, 2010, and 2016 were notable for having the highest amounts of rainfall compared to the other years. Generally, the region could be classified as an area highly susceptible to meteorological drought in northwestern Ethiopia. There was no even a single year free from drought in the entire study period. To that extent, about 86% of it had repeatedly encountered extreme rainfall deficit (7–23 times) during the study period. Thus, the population has always been repeatedly smashed down by the frequent droughts. To tackle existing challenges and mitigate upcoming risks, continual droughts monitoring and implementation of efficient early warning systems are vital for the region.

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.

Drought characteristics and their impacts on vegetation net primary productivity in the subtropical China

Drought is one of the main factors limiting forest productivity, and thus greatly affects the carbon sink capacity of forests. Here we first chose two drought indices including standardized precipitation evapotranspiration index (SPEI) and self-calibrating Palmer drought severity index (scPDSI) to reflect and analyze the spatiotemporal patterns of drought in the subtropical China. Then, the validated CASA (Carnegie-Amer-Stanford Approach) model was applied to estimate forest net primary productivity (NPP) and further quantify the contributions of drought events and their characteristics on forest NPP. The results showed that drought events during 2000–2015 have resulted in a mean decline of forest NPP of 7.2%. Moderate or severe drought events reduced NPP more significantly than extremely severe drought events. In addition, there was 1–2 years of lagging in the NPP responses to drought, and the lagging time varied with forest types. Our study suggests that forest managers and local governments should pay more attention to the places with moderate and severe drought events, and take measures to avoid NPP decline within the 2 years after drought. Our study also provides data support for further identifying the contribution of drought to ecosystem carbon fluxes in the subtropical China.

Evaluation of TRMM satellite dataset for monitoring meteorological drought in northeastern Brazil

ABSTRACT Although droughts can inflict extreme damage on populations, few studies have characterized drought events in arid and semiarid regions around the globe due to the lack of reliable data. Therefore, precipitation estimates from remote sensing satellites have been increasingly used. In this study, the performance of the Tropical Rainfall Measuring Mission (TRMM) satellite rainfall estimates in monitoring the spatiotemporal patterns of drought at multiple time scales over Paraíba state is evaluated. The drought events are characterized by their quantity, duration, severity, intensity, frequency, and percentage of the area affected, and analyses are performed both for individual points and for four mesoregions at eight different time scales. The results indicate that short-term drought events occur more frequently but are less long-lasting and severe than long-term drought events. On the other hand, relevant changes in the average intensity of events cannot be identified among the time scales.

Global soil moisture drought identification and responses to natural and anthropogenic forcings

• We evaluated soil moisture droughts with duration, magnitude and extremum in monsoon and non-monsoon regions. • We identified more evident impacts of anthropogenic forcing on soil moisture drought in monsoon region than in non-monsoon region. • We found larger impacts of anthropogenic forcing on drought magnitude, relative to drought duration and drought extremum. The spatio-temporal patterns of drought changes and relevant forcings are still open for debate, especially under global warming, even though agricultural drought has long been receiving increasing concern for food security and sustainable development. In this study, we depicted global spatiotemporal patterns of agricultural drought using the Soil Water Deficit Index (SWDI) and reflected on the underlying forcings using the optimal fingerprint method. Three aspects of droughts were analyzed, i.e. drought duration (DD), drought magnitude (DM) and drought extremum (DE) over three regions, i.e. global, monsoon and non-monsoon regions. We found distinct spatial heterogeneity of DD, DM and DE. However, DM (DE) had mainly a decreasing (increasing) tendency. Anthropogenic forcing ([ANT] including greenhouse gas, anthropogenic aerosol, and ozone) and greenhouse gas forcing (GHG) played a prominent role in driving drought changes and were followed by the combination of anthropogenic and natural forcing (ALL). Soil moisture drought (DD, DM and DE) responses to external forcing of ANT and GHG were detected more easily in the monsoon region than in the non-monsoon region. Specifically, DM changes due to ANT (2.58 per century) contributed 39.88% of the DM changes by ALL (6.47 per century) in the monsoon regions, comparatively, the GHG and ANT induced changes of DM in the non-monsoon regions were quite slight. This study further clarified the impacts of anthropogenic warming on agricultural drought over the globe.

Drought Analysis Using Standardized Evapotranspiration and Aridity Index at Bilate Watershed: Sub-Basins of Ethiopian Rift Valley.

In Ethiopia, more prevalent drought happenings have been documented in the past century. The problem has gradually expanded from the north to the rest parts with deepened intensity. The study aimed to examine the magnitudes of spatiotemporal patterns of drought at the Bilate watershed from 1981 to 2016. Monthly rainfall and temperature data were used for the analysis. The Standardized Evapotranspiration Indexes (SPEI) at SPEI-03 and SPEI-12 timescales were applied to evaluate the drought patterns. Among different drought indices, the SPEI is the most valuable and preferred Index for drought studies. The SPEI method considers the role of temperature than other indices to compare drought in time and space. The Mann–Kendall test was used for trend analysis. Accordingly, the result revealed that 1988–2016 were years of continuous drought events in both timescales with (SPEI = −2.5 to −1.2) drought value. Drought severity and frequency were highly detected at Wulberag areas (SPEI: −2.5). Durame, Angacha, and Alaba experienced increasing drought trends (Z = −1.96−1.6) and Welayita Sodo is Z = −0.07−0.03. Bilate-Tena and Hossana area of the watershed were less affected by drought than other areas. Spatially, the drought occurrences were observed in all areas of the watershed with varying magnitude. In the SPEI-12 timescale, more frequent drought occurrences were observed than SPEI-03. It was found that severe drought was observed in 1987, 1993/94, 2000–2005, and 2010. Moreover, the watershed experienced an Aridity Index (AI) of 0.43 (43%) and was subjected to potential high evapotranspiration (PET). The highest PET was observed at Bilate-Tena, Angacha, Hosanna, Wulberag, Alaba, Welayita Sodo, and Durame (151.6, 119.6, 119.3, 140.8, 142, 127.5, and 125.7 mm/year, respectively. Hence, the finding of this study could initiate a further inquiry on drought risk management, early warning responses, and local scale planning.

Socioeconomic vulnerability of pastoralism under spatiotemporal patterns of drought in Eastern Africa

Socioeconomic vulnerability of pastoralism under spatiotemporal patterns of drought in Eastern Africa

Spatiotemporal Variability of Drought and Its Multi-Scale Linkages with Climate Indices in the Huaihe River Basin, Central China and East China

With the aggravation of the ocean–atmosphere cycle anomaly, understanding the potential teleconnections between climate indices and drought/flood conditions can help us know natural hazards more comprehensively to better cope with them. This study aims at exploring the spatiotemporal patterns of drought and its multi-scale relations with typical climate indices in the Huaihe River Basin. First, the spatial patterns were identified based on the seasonal Standardized Precipitation Index (SPI)-3 during 1956–2020 by means of the Empirical Orthogonal Function (EOF). The two leading sub-regions of spring and winter droughts were determined. Then, we extracted the periodicity of spring and winter SPI-3 series and the corresponding seasonal climate indices (Arctic Oscillation (AO), Bivariate El Niño–Southern Oscillation (ENSO)Timeseries (BEST), North Atlantic Oscillation (NAO), Niño3, and Southern Oscillation Index (SOI)) and the sunspot number by using the Continuous Wavelet Transform (CWT). We further explored the teleconnections between spring drought, winter drought, and climate indices and the sunspot number by using Cross Wavelet Transform (XWT) and Wavelet Coherence (WTC) analyses. The results show that there are in-phase multi-scale relations between spring/winter PC1 and AO, BEST, and Niño3, of which the climate indices lead spring PC1 by 1.5–2 years and the climate indices lag winter PC1 by 1.5–3 years. Anti-phase relations between spring PCs and SOI and the sunspot number were observed. NAO mainly affects the interdecadal variation in spring drought, while AO and Niño3 focus on the interannual variation. In addition, Niño3 and SOI are more related to the winter drought on interdecadal scales. Moreover, there is a positive correlation between the monthly average precipitation/temperature and Niño3 with a lag of 3 months. The results are beneficial for improving the accuracy of drought prediction, considering taking NAO, AO, and Niño3 as predictors for spring drought and Niño3 and SOI for winter drought. Hence, valuable information can be provided for the management of water resources as well as early drought warnings in the basin.

Use of A MODIS Satellite-Based Aridity Index to Monitor Drought Conditions in Mongolia from 2001 to 2013

The 4D disasters (desertification, drought, dust, and dzud, a Mongolian term for severe winter weather) have recently been increasing in Mongolia, and their impacts on the livelihoods of humans has likewise increased. The combination of drought and dzud has caused the loss of livestock on which nomadic herdsmen depend for their well-being. Understanding the spatiotemporal patterns of drought and predicting drought conditions are important goals of scientific research in Mongolia. This study involved examining the trends of the normalized difference vegetation index (NDVI) and satellite-based aridity index (SbAI) to determine why the land surface of Mongolia has recently (2001–2013) become drier across a range of aridity indices (AIs). The main reasons were that the maximum NDVI (NDVImax) was lower than the NDVImax typically found in other arid regions of the world, and the SbAI throughout the year was large (dry), although the SbAI in summer was comparatively small (wet). Under the current conditions, the capacity of the land surface to retain water throughout the year caused a large SbAI because rainfall in Mongolia is concentrated in the summer, and the conditions of grasslands reflect summer rainfall in addition to grazing pressure. We then proposed a method to monitor the land-surface dryness or drought using only satellite data. The correct identification of drought was higher for the SbAI. Drought is more strongly correlated with soil moisture anomalies, and thus the annual averaged SbAI might be appropriate for monitoring drought during seasons. Degraded land area, defined as annual NDVImax &lt; 0.2 and annual averaged SbAI &gt; 0.025, has decreased. Degraded land area was large in the major drought years of Mongolia.

Analysis of Drought Impact on Croplands from Global to Regional Scale: A Remote Sensing Approach

Drought is one of the extreme climatic events that has a severe impact on crop production and food supply. Our main goal is to test the suitability of remote sensing-based indices to detect drought impacts on crop production from a global to regional scale. Moderate resolution imaging spectroradiometer (MODIS) based imagery, spanning from 2001 to 2017 was used for this task. This includes the normalized difference vegetation index (NDVI), land surface temperature (LST), and the evaporative stress index (ESI), which is based on the ratio of actual to potential evapotranspiration. These indices were used as indicators of drought-induced vegetation conditions for three main crops: maize, wheat, and soybean. The start and end of the growing season, as observed at 500 m resolution, were used to exclude the time steps that are outside of the growing season. Based on the three indicators, monthly standardized anomalies were estimated, which were used for both analyses of spatiotemporal patterns of drought and the relationship with yield anomalies. Anomalies in the ESI had higher correlations with maize and wheat yield anomalies than other indices, indicating that prolonged periods of low ESI during the growing season are highly correlated with reduced crop yields. All indices could identify past drought events, such as the drought in the USA in 2012, Eastern Africa in 2016–2017, and South Africa in 2015–2016. The results of this study highlight the potential of the use of moderate resolution remote sensing-based indicators combined with phenometrics for drought-induced crop impact monitoring. For several regions, droughts identified using the ESI and LST were more intense than the NDVI-based results. We showed that these indices are relevant for agricultural drought monitoring at both global and regional scales. They can be integrated into drought early warning systems, process-based crop models, as well as can be used for risk assessment and included in advanced decision-support frameworks.

Spatio-Temporal Patterns of Drought and Impact on Vegetation in North and West Africa Based on Multi-Satellite Data

Studying the significant impacts of drought on vegetation is crucial to understand its dynamics and interrelationships with precipitation, soil moisture, and temperature. In North and West Africa regions, the effects of drought on vegetation have not been clearly stated. Therefore, the present study aims to bring out the drought fluctuations within various types of Land Cover (LC) (Grasslands, Croplands, Savannas, and Forest) in North and West Africa regions. The drought characteristics were evaluated by analyzing the monthly Self-Calibrating Palmer Drought Severity Index (scPDSI) in different timescale from 2002 to 2018. Then, the frequency of droughts was examined over the same period. The results have revealed two groups of years (dry years and normal years), based on drought intensity. The selected years were used to compare the shifting between vegetation and desert. The Vegetation Condition Index (VCI), the Temperature Condition Index (TCI), the Precipitation Condition Index (PCI), and the Soil Moisture Condition Index (SMCI) were also used to investigate the spatiotemporal variation of drought and to determine which LC class was more vulnerable to drought risk. Our results revealed that Grasslands and Croplands in the West region, and Grasslands, Croplands, and Savannas in the North region are more sensitive to drought. A higher correlation was observed among the Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), Tropical Rainfall Measuring Mission (TRMM), and Soil Moisture (SM). Our findings suggested that NDVI, TRMM, and SM are more suitable for monitoring drought over the study area and have a reliable accuracy (R2 &gt; 0.70) concerning drought prediction. The outcomes of the current research could, explicitly, contribute progressively towards improving specific drought mitigation strategies and disaster risk reduction at regional and national levels.

Prognostic and diagnostic assessment of hydrological drought using water and energy budget-based indices

Long-term meteorological drought can lead to hydrological drought by restricting water resources required by humans, such as streamflow and reservoir storage. We developed two new indices for monitoring hydrologic drought-based satellite-derived evapotranspiration, a major factor in hydrological drought occurrence. The Water Budget-based Drought Index (WBDI) estimates potential runoff by the differences between precipitation and evapotranspiration using water budget analysis while the Energy-based Water Deficit Index (EWDI) is an index of available water capacity through evapotranspiration and soil moisture based on solar radiation using energy budget analysis. We used these, along with the existing Standardized Precipitation-Evapotranspiration Index (SPEI, based on precipitation, atmospheric temperature, and evapotranspiration), to map the spatiotemporal patterns of drought on the Korean Peninsula from 2001 to 2014. For validation against actual drought conditions, we compared the results with streamflow data from five gauging stations in South Korea. EWDI—the diagnostic approach—performed best when assessing current hydrological drought conditions, while WBDI and SPEI—prognostic approach—best captured drought conditions after 2–3 months of lag time. Our results confirmed that evapotranspiration is a major factor affecting hydrological drought; the new methods demonstrated here make it possible to evaluate drought through diagnostic and prognostic perspectives depending on the situation, thereby improving scientific drought evaluation capacity.

Assessing spatiotemporal characteristics of drought and its effects on climate-induced yield of maize in Northeast China

It is important to investigate the potential impacts of global climate change on crop yield especially there have been limited relevant studies conducted in the cold regions such as Northeast China. This study investigated the spatiotemporal characteristics of droughts on different growth stages of maize over Northeast China during 1960–2016 and the effects of droughts on the climate-induced yield of maize separated by the logistic regression model using standardized precipitation evapotranspiration index (SPEI), trend analysis methods, rotated empirical orthogonal function, wavelet method, and Hurst exponent. The results indicated that: 1) the spatiotemporal patterns of drought were identified at different growth stages and the changes in dryness/wetness condition presented significant periodic oscillation on different time scales. 2) The patterns of dryness/wetness conditions and the changing characteristics of each sub-region at the early growth (EG) and middle growth (MG) stages were similar. 3) The future drought trends in most stations would be consistent with the past trends. In addition to the wetting trend in the eastern and southern parts at the EG stage, the whole study area would show a drying trend in future at other growth stages. 4) The cross wavelet transform (XWT) was used to develop the changing relationships between climate-induced yield of maize and the dryness/wetness condition at different growth stages with obvious inter-annual periodicities. 5) For Northeast China, climatic factors that can affect the climate-induced yield of maize are firstly temperature, next precipitation, and thirdly dryness/wetness conditions.

Spatio-temporal patterns of drought evolution over the Beijing-Tianjin-Hebei region, China

Spatio-temporal patterns of drought from 1961 to 2013 over the Beijing-Tianjin-Hebei (BTH) region of China were analyzed using the Palmer Drought Severity index (PDSI) based on 21 meteorological stations. Overall, changes in the mean-state of drought detected in recent decades were due to decreases in precipitation and potential evapotranspiration. The Empirical Orthogonal Functions (EOF) method was used to decompose drought into spatio-temporal patterns, and the first two EOF modes were analyzed. According to the first leading EOF mode (48.5%), the temporal variability (Principal Components, PC1) was highly positively correlated with annual series of PDSI (r=+0.99). The variance decomposition method was further applied to explain the inter-decadal temporal and spatial variations of drought relative to the total variation. We find that 90% of total variance was explained by time variance, and both total and time variance dramatically decreased from 1982 to 2013. The total variance was consistent with extreme climate events at the inter-decadal scale (r=0.71, p<0.01). Comparing the influence of climate change on the annual drought in two different long-term periods characterized by dramatic global warming (P1: 1961–1989 and P2: 1990–2013), we find that temperature sensitivity in the P2 was three times more than that in the P1.

Identification of Drought Events and Correlations with Large-Scale Ocean–Atmospheric Patterns of Variability: A Case Study in Xinjiang, China

This research analyzed the spatiotemporal patterns of drought in Xinjiang (northwestern China) between 1961 and 2015 using the standardized precipitation evapotranspiration index (SPEI). Furthermore, the correlations between Atlantic Multidecadal Oscillation (AMO)/El Niño–Southern Oscillation (ENSO) events and drought were explored. The results suggested an obvious trend toward aggravated drought, with a significant inflection point in 1997, after which the frequency of drought increased sharply. Spatially, the increase in drought occurred largely in southern and eastern Xinjiang, where occurrences of moderate and extreme drought have become more frequent during the last two decades, whereas northwestern Xinjiang and the Pamir Plateau showed wetting trends. Empirical orthogonal function analysis (EOF) of drought patterns showed a north–south antiphase and an east–west antiphase distribution. The positive (negative) phase of the AMO was related to increased (decreased) drought in Xinjiang, particularly after 1997. During a warm phase (El Niño), major droughts occurred over northern Xinjiang, but they lagged by 12 months. However, not all El Niño and La Niña events were responsible for drought events in northern Xinjiang during this period, and other drivers remain to be identified. This study suggests the possibility of AMO and ENSO links to drought in Xinjiang, but further analysis is needed to better understand such mechanisms.

Analysis of the spatiotemporal variability of droughts and the effects of drought on potato production in northern China

Knowledge about drought variability in the main potato producing areas can provide a scientific basis for management of potato crops. In this study, the variations and patterns of drought in the potato growing period (GP), seedling stage (SS), tuber-growth stage (TS), and mature stage (MS) identified by the Standardized Precipitation Evapotranspiration Index (SPEI) were investigated in the north single cropping zone (NSCZ) in China for the period of 1960–2016 based on the empirical orthogonal function analysis, Mann–Kendall statistical test, Mann–Kendall test, Sen’s slope, Hurst exponent, and continuous wavelet transform. Additionally, grey theory was used to study the relationship between drought and potato production. The results of the study follow: 1) The spatiotemporal patterns of drought of the two leading patterns were identified. 2) Since the 1970s, the NSCZ has become drier in the GP and MS, has become wetter in the TS, but has always remained in an unstable state of alternating wet and dry conditions in the SS. 3) The changes in dryness/wetness conditions include significant periodic oscillation features. 4) The future drought trend is generally consistent with the current state. In addition, it is worth noting that the NSCZ as a whole will become drier in the MS. 5) The drought of SS and TS had a relatively large negative effect on potato production, whereas that of MS had a relatively small positive effect. Because the NSCZ is within the marginal region of the Asian monsoon and the agro-pastoral ecotone, it is an ecologically fragile region. Therefore, under the background of global climate change, studying changes in dryness/wetness conditions has important implications for the ecological security and potato production of the region.

Analysis of Changes in Spatio-Temporal Patterns of Drought across South Korea

Since the climatic features of South Korea are highly complex and time variable, spatio-temporal-based drought frequency analysis is a prerequisite for drought risk management. The spatial extent of drought risk analysis in a bivariate framework has scarcely been applied in South Korea before. In this study, the spatio-temporal changes in drought events are investigated at 55 stations across South Korea during 1980–2015. A variety of probability distributions and copulas are applied, and the best fitted is selected on the basis the goodness of fit. The spatial distributions of primary and secondary return periods showed a high risk of drought due to the unusual precipitation pattern in the western coast areas and at Uljin station and a relative low risk of drought in the northwestern portion and surrounding areas of Yeongju, Uiseong, Boeun and Daejeon stations. Overall, the spatial distribution patterns of primary and secondary (Kendall) return periods are similar. However, their applicability changes according to the type of drought risk to be considered. The spatio-temporal quantification of the return period can be used for establishing the proper water demand and supply system and helps to overcome the challenges faced in the hydrometeorological regulations of reservoirs in the southwest coast.

Characteristics of meteorological drought pattern and risk analysis for maize production in Xinjiang, Northwest China

Xinjiang is an important maize cultivation area in Northwest China. Investigating the relationship between meteorological drought and climate-driven maize yield can help to mitigate the negative impacts of drought on agricultural production in Xinjiang. In this study, multi-source data, including meteorological, agricultural, and socio-economic data, are collected to analyze the spatiotemporal patterns of drought and assess drought disaster risk. The standardized precipitation evapotranspiration index is calculated to classify different drought grades in the study area. The main results are as follows: (1) the relationship between drought and climate-driven maize yield is determined using a stepwise regression analysis, which indicates that drought conditions occurring from May to July are crucial for the yield in Xinjiang; (2) the modified Mann-Kendall test detects that the frequency-intensity-coverage of drought from May to July shows a decreasing tendency as a whole in the study area; (3) the correlation analysis shows that the multivariate ENSO index may be the dominant force in regional drought evolution; and (4) a drought disaster risk assessment system is constructed based on principles of natural disaster management. The drought disaster risk is higher in southwestern and northwestern Xinjiang, areas that should deserve more attention.

Drought sensitivity mapping using two one-class support vector machine algorithms

This paper investigates the use of standardised precipitation index (SPI) and the enhanced vegetation index (EVI) as indicators of soil moisture. On the other hand, we attempted to produce a drought sensitivity map (DSM) for vegetation cover using two one-class support vector machine (OC-SVM) algorithms. In order to achieve promising results a combination of both 30years statistical data (1978 to 2008) of synoptic stations and 10years MODIS imagery archive (2001 to 2010) are used within the boundary of Kermanshah province, Iran. The synoptic data and MODIS imagery were used for extraction of SPI and EVI, respectively. The objective is, therefore, to explore meaningful changes of vegetation in response to drought anomalies, in the first step, and further extraction of reliable spatio-temporal patterns of drought sensitivity using efficient classification technique and spatial criteria, in the next step. To this end, four main criteria including elevation, slope, aspect and geomorphic classes are considered for DSM using two OC-SVM algorithms. Results of the analysis showed distinct spatio-temporal patterns of drought impacts on vegetation cover. The receiver operating characteristics (ROC) curves for the proposed DSM was used along with the simple overlay technique for accuracy assessment phase and the area under curve (AUC=0.80) value was calculated.

Quantitative and detailed spatiotemporal patterns of drought in China during 2001–2013

Investigation of spatiotemporal patterns of drought is essential to understand the mechanism and influencing factors of drought occurrence and development. Due to the differences in designation of various drought indices, it remains a great challenge to obtain an accurate result in spatiotemporal patterns investigation of drought. In this study, a quantitative drought monitoring index (i.e., Integrated Surface Drought Index, ISDI) was used to identify spatiotemporal patterns of drought and the drought variation trend at the pixel level during 2001–2013 over China. Eco-geographical regionalization was used as an evaluation unit to distinguish the ecological and climatic background of drought over the whole country. The results showed that the spatial distribution of drought intensity has a strong correlation with eco-geographical regionalization in China. The severe drought areas were mainly concentrated in sub-humid regions and semi-arid regions of medium temperate zones, and humid regions of middle subtropical zones. The regions with higher drought probabilities were most distributed in the south and north of China, while the regions in central and western China exhibited lower drought probabilities. The most obvious decreasing trend of ISDI from 2001 to 2013 was located in the northeast of China and south of the Yangtze River. This decrease in ISDI over time indicates a trend for progressive aggravation of drought severity in these areas. This study shows great promise in informing the future drought prevention measures and management policies under the background of more frequent extreme climate events.