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The study of drought, one of the many problems caused by climate change, enables the planning of water use and water resources. The increase or decrease in drought severity, which is one of the drought parameters, is an important source of information in terms of predetermining the consequences that may arise due to drought. In this study, drought analysis was conducted for 1-, 3-, 6-, 9- and 12-month time periods with the Standard Precipitation Index (SPI) using long-term precipitation data of four stations in the Tigris River basin from 1960 to 2022. Drought duration and severity series were obtained from drought index values, and the trends of drought severity series were calculated with Mann-Kendall (MK) and Innovative Trend Analysis (ITA) tests. According to the results, the ITA test was found to be more sensitive in detecting trends in drought severity series compared to the MK test. According to the MK test, drought did not show a significant increase or decrease. On the other hand, according to the ITA test, drought increased at 1- and 12-month scales at Siirt and Batman stations, respectively, and at 1- and 12-month scales at Diyarbakır station. Drought increased in all time periods at Mardin station. [ABSTRACT FROM AUTHOR]

Major theoretical and practical hydrological issues may be solved using methods to maintain water balance. Evaluating the climate characteristics and environmental circumstances to be employed in the methods of water managing approach used in the Erbil sub-basin, northern Iraq, is the primary goal of this study. The studied area is a part of the region influenced by the Mediterranean climatological system. The climatic parameters of the research region were evaluated using the climatic data collected in the Erbil meteorological station for the period 1980-2022. The research result shows that the mean annual rainfall is 411.26 mm/year and the average monthly relative humidity is 41.12 %, the mean temperature is 20.62 °C, mean sunshine duration 8.35 hr./day and annual pan evaporation is 1200.96 mm / year. Potential evapotranspiration considered by Thornthwaite method is 1588.94 mm. The water surplus and deficit are 216.14 mm and 1393.81 mm, respectively. The surface runoff calculating from soil conservation system (SCS) technique which is about 86 mm / year and groundwater recharge is about 130.14 mm / year. The groundwater Budgets is about 187661880 m3 / year. The climatic situation in the area is variety from winter its wet to the summer its dry climates. Also, it could be measured that the climate in the area is determined was (Humid to very humid). The draught index according to SPI analysis show that the drought was observed during Moderately drought in (1983, 1999, 2000, 2010, 2015, and 2021) to severely drought in (2022.

The research focuses on investigating the spatial and temporal vulnerability to drought in Odisha, India, utilizing the Standard Precipitation Index (SPI), Drought Index (DI), and Rainfall Anomaly Index (RAI). The historical precipitation data are utilized to identify areas with prolonged rainfall deficits, quantifying the severity and duration of drought conditions. Preliminary analysis includes Normality and Homogeneity tests to ensure the validity of the precipitation datasets. The results depict the use of a non-parametric test for which Mann–Kendall trend test and Sen's Slope test are conducted. The districts exhibiting significant decreasing trends are identified as most critical for drought assessment. The findings from drought indices indicate that most districts have been affected by drought for approximately 50 years, with some districts experiencing severe or extreme conditions for over 10 years. Among the nine districts exhibiting a decreasing trend, four districts demonstrate a significant trend at a 5% significance level. These four districts are experiencing extremely and severely dry conditions, and while they display a significant decreasing trend, they are potentially vulnerable to the adverse impacts of drought conditions in the future. The study will serve in understanding and addressing the vulnerability to drought in Odisha, providing crucial insights for effective mitigation and management strategies. HIGHLIGHTS Using the Normality tests to determine the use of parametric or non-parametric tests.; Using the Homogeneity test to check the consistency of datasets.; Using the Mann–Kendall trend test to detect the pattern of rainfall.; Estimating the magnitude of the trend to check the persistency of rainfall deficit.; Finally, checking the rainfall datasets using drought indices to check the drought vulnerability.;

Abstract The increased global warming has increased the likelihood of recurrent drought hazards. Potential links between the frequency of extreme weather events and global warming have been suggested by earlier research. The spatial variability of meteorological factors over short distances can cause distortions in conclusions or limit the scope of drought analysis in a particular region when extreme values predominate. Therefore, it is challenging to make trustworthy judgments regarding the spatiotemporal characteristics of regional drought. This study aims to improve the quality and accuracy of regional drought characterization and the process of continuous monitoring. The new drought indicator presented in this study is called the Support Vector Machine based drought index (SVM-DI). It is created by adding different weights to an SVM-based X-bar chart that is displayed with regional precipitation aggregate data. The SVM-DI application site is located in Pakistan's northern area. Using the Pearson correlation coefficient for pairwise comparison, the study compares the SVM-DI and the Regional Standard Precipitation Index (RSPI). Interestingly, compared to RSPI, SVM-DI shows more pronounced regional characteristics in its correlations with other meteorological stations, with a significantly lower Coefficient of Variation. These results confirm that SVM-DI is a useful tool for regional drought analysis. The SVM-DI methodology offers a unique way to reduce the impact of extreme values and outliers when aggregating regional precipitation data.

The increased global warming has increased the likelihood of recurrent drought hazards. Potential links between the frequency of extreme weather events and global warming have been suggested by earlier research. The spatial variability of meteorological factors over short distances can cause distortions in conclusions or limit the scope of drought analysis in a particular region when extreme values predominate. Therefore, it is challenging to make trustworthy judgments regarding the spatiotemporal characteristics of regional drought. This study aims to improve the quality and accuracy of regional drought characterization and the process of continuous monitoring. The new drought indicator presented in this study is called the Support Vector Machine based drought index (SVM-DI). It is created by adding different weights to an SVM-based X-bar chart that is displayed with regional precipitation aggregate data. The SVM-DI application site is located in Pakistan's northern area. Using the Pearson correlation coefficient for pairwise comparison, the study compares the SVM-DI and the Regional Standard Precipitation Index (RSPI). Interestingly, compared to RSPI, SVM-DI shows more pronounced regional characteristics in its correlations with other meteorological stations, with a significantly lower Coefficient of Variation. These results confirm that SVM-DI is a useful tool for regional drought analysis. The SVM-DI methodology offers a unique way to reduce the impact of extreme values and outliers when aggregating regional precipitation data. [ABSTRACT FROM AUTHOR]

Droughts have become more severe and frequent due to global warming. In this context, it is widely accepted that for drought assessments, both water supply (rainfall) and demand (standardized precipitation evapotranspiration index, SPEI) should be considered. Using SPEI, we explored the spatial-temporal patterns of dry and wet annual and seasonal changes in five sub-regions of East Asia during 1902–2018. These factors are linked to excess drought frequency and severity on the regional scale, and their effect on vegetation remains an important topic for climate change studies. Our results show that the SPEI significantly improved extreme drought and mostly affected the SPEI-06 and SPEI-12 growing seasons in East Asia during 1981–2018. The dry and wet annual SPEI trends mostly affect the five sub-regions of East Asia. The annual SPEI had two extremely dry spells during 1936–1947 and 1978–2018. Japan, South Korea, and North Korea are wet in the summer compared to other regions of East Asia, with drought frequency occurring at 51.4%, respectively. The mean drought frequencies in China and Mongolia are 57.4% and 54.6%. China and Mongolia are the driest regions in East Asia due to high drought frequency and duration. The spatial seasonal analysis of solar radiation (SR), water vapor pressure (WVP), wind speed (WS), vegetation condition index (VCI), temperature condition index (TCI), and vegetation health index (VHI) have confirmed that the East Asia region suffered from maximum drought events. The seasonal variation of SPEI shows no clear drying trends during summer and autumn seasons. During the winter and spring seasons, there was a dry trend in East Asia region. During 1902–1990, a seasonal SPEI presented diverse characteristics, with clear wet trends in Japan, Mongolia, and North Korea in four different growing seasons, with dry trends in China and South Korea. During 1991–2018, seasonal SPEI presented clear dry trends in Japan, Mongolia, and North Korea in different growing seasons, while China and South Korea showed a wet trend during the spring, autumn, and winter seasons. This ecological and climatic mechanism provides a good basis for the assessment of vegetation and drought-change variations within East Asia. An understandings of long-term vegetation trends and the effects of rainfall and SPEI on droughts of varying severity is essential for water resource management and climate change adaptation. Based on the results, water resources will increase under global warming, which may alleviate the water scarcity issue in the East Asia region. [ABSTRACT FROM AUTHOR]

Drought is the most complex of the recurrent extreme weather events and is defined as a natural disaster with severe environmental, economic, and agricultural impacts resulting from a significant decrease in the average rainfall recorded in an area and the average rainfall recorded in the same place. Droughts have become more frequent and severe in many parts of the world, including Türkiye, due to global warming and climate change (increasing temperatures and changing precipitation patterns). Water resources and the agricultural sector are most severely affected by droughts. In this study, drought analyses of the Burdur Basin, located in the Aegean region, one of Türkiye's seven geographical regions, were carried out. For drought analysis, annual average total precipitation, annual maximum temperature, annual minimum temperature, and annual average temperature data of 17238 Burdur and 17892 Tefenni meteorological observation stations were used. Both meteorological and agricultural drought analyzes are included in the analysis of droughts. Standard Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) methods were used to determine meteorological and agricultural drought, respectively. SPI and RDI values were obtained for 1-, 3-, 6- and 12-month time periods, and the severity, size, and distribution of dry and humid periods were determined for both stations separately. When the results of both methods were examined, severe droughts were observed in the study area in 1973, 1978, 1981, and 2017. [ABSTRACT FROM AUTHOR]

Drought is one of the most serious problems for human societies and ecosystems. Climate change has begun to affect the whole world, but regional climate change can have different effects. Precipitation is frequently used to determine drought; besides, temperature has started to be used in recent years. The effect of temperature on the occurrence of drought was investigated for the Marmara region, located in the northeast of Turkey. The spatiotemporal variability of drought in the Marmara region was analyzed by using the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) for 3-, 6-, and 12-month series. Results show that SPEI droughts occur with longer duration and increased magnitude, which can be attributed to the rise in potential evapotranspiration rates with an increase in temperature. The correlation between SPI and SPEI is strong for the same time series, and the number of extreme drought values for SPI is higher than SPEI, while the number of severe and moderate drought values is lower compared to SPEI. The years 1989, 1990, 2001, 2007, and 2014 were characterized as the highest drought years throughout the region. The study concludes that temperature should be considered in future studies. HIGHLIGHTS This study evaluates drought in terms of short- and long-time periods in the Marmara region.; The drought has been analyzed temporally and spatially.; The study gives an idea about the importance of considering the temperature in the determination of drought.; The drought duration and intensity were analyzed according to the short- and long-time periods.; Standardized precipitation and evapotranspiration index droughts were found to last longer and be more severe than standardized precipitation index.;

Copyright of SDU Journal of Engineering Sciences & Design / Mühendislik Bilimleri ve Tasarım Dergisi is the property of Journal of Engineering Sciences & Design and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Introduction: Drought, as one of the major natural hazards, affects the environment, society, agriculture and economy. Several indices have been developed for drought quantification based on ground data and remote sensing. Traditional drought quantification methods are based on meteorological data and conventional criteria and are usually not available in near real- time. On the other hand, data based on remote sensing are continuously available and can be used to detect several aspects and characteristics of drought. The purpose of this research is to investigate and compare different indices derived from remote sensing and meteorological data for local scale drought monitoring (eastern part of Kurdistan Province). Material and methods: Seven drought indices were compared, including Vegetation Condition Index (VCI), Vegetation Drought Index (VDI), Vegetation Health Index (VHI), Vegetation Supply Water Index (VSWI), Normalized Difference Vegetation Index (NDVI), Temperature Condition Index (TCI) and Standardized Precipitation Index (SPI). Remote sensing indicators are derived from MODIS data. The meteorological index SPI is obtained by combining the data of rain gauge stations and gridded precipitation data. The digital maps of the seven drought indicators have been prepared for the period of 2002-2021 with the same time interval (16-days). To analyze the characteristics of each drought index, a comparative method including the selection of specific periods of drought and spatial drought identification characteristics has been used. The comparison of drought indicators was done May, which is the growing season. Finally, Pearson's correlation analysis was used to evaluate the behavioral similarity of the indicators. Results and discussion: The spatial comparative analysis between the drought indicators showed that all the indicators had certain adaptations in the distribution of the regional scale of drought, especially those derived from similar data sets. Meanwhile, the difference in local scale distribution was found among different groups of indicators. The results showed that the general trend of the VSWI had a better compliance with the standardized precipitation index. Based on the correlation analysis, it was proved that the VSWI can be a better reflection of the amount of rainfall and the severity of drought due to the lack of rainfall. In addition, the land surface temperature (LST) contributes more to the VSWI results than the reflectance information. A two-period (32-day) delay of the indicators indicating the state of vegetation is a good indicator of the meteorological drought conditions in the study area. The absence and lack of rainfall in at least five periods (80 days) earlier can had a serious effect on the state of vegetation in the existing conditions. Plain and mountainside areas located in the central, eastern and south-eastern parts of the study area were more sensitive to drought conditions than other parts due to the dominance of grain farming, especially rainfed farming. Conclusion: While remote sensing drought indicators have many advantages in the analysis of drought in real-time, meteorological drought indicators are still the priority for drought monitoring. This is due to the dependence of hydrological and agricultural systems on meteorological conditions. Mainly, these hydrological and agricultural systems in different regions respond to meteorological fluctuations with different time delays. Understanding these complex relationships between meteorological, hydrological and agricultural systems can be useful in early preparation programs against drought and its management. [ABSTRACT FROM AUTHOR]

Copyright of COMU Journal of Agriculture Faculty / ÇOMÜ Ziraat Fakültesi Dergisi is the property of Canakkale Onsekiz Mart University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A meteorological drought study is performed using monthly time scale data from three separate locations in southern Sindh, Pakistan. Rainfall and temperature have been used to identify the drought. These data were transformed into drought indices known as the standardized precipitation evapotranspiration index (SPEI) and standardized precipitation index (SPI), which were derived using (the Hargreaves equation). In this study, two indices are compared for three separate meteorological stations Chhor, Mithi, and Badin where most socioeconomic livelihoods depend heavily on water. The SPEI is produced through a simple water balance combining precipitation and temperature, in distinction to the SPI, it just considers precipitation. In conclusion, our study showed that both indices were capable of detecting droughts that fluctuated in time across the reference period of 2004-2021. SPI and SPEI's direction of change was similar, however the impact on the drought condition varied. SPEI discovered more droughts with longer durations and greater with 13 moderate droughts at SPEI-3 for Chhor and Badin Station while Mithi indicated 8 moderate droughts during 2004-2021 and SPI-3 indicated 4 moderates for Chhor, Mithi and Badin indicated 6 moderate drought. Conversely, SPEI discovered more moderatelevel droughts than SPI, however they were of shorter length and less frequent occurrence than the severe to moderate droughts. The findings imply that drought characteristics are significantly influenced by temperature variability. [ABSTRACT FROM AUTHOR]

The Federal University of Technology at Akure (FUTA) in Nigeria is experiencing ongoing development that is leading to the replacement of agricultural and forestry land cover types. This study aimed to assess and predict changes in land use/land cover (LULC) types and their impact on crop characteristics in 17 plots of FUTA from 1991 to 2031. Crop characteristics were evaluated using the normalized difference vegetation index (NDVI), normalized difference water index (NDWI), normalized difference moisture index (NDMI), vegetation condition index (VCI), watershed delineation, and spectral characteristics using Landsat imageries. The land change modeler in TerraSet software was used to predict future LULC scenarios. Results showed an increase in built-up areas (15%) and bare land areas (14%), but a reduction of 19% in light vegetation cover from 1991 to 2021. The predicted LULC map illustrated a decrease in light vegetation area (11%) and an increase in built-up area (19%) from 1991 to 2031. NDVI values denoting vegetation health and coverage extent, and NDWI & NDMI values indicating water stress in vegetation and soil showed that palm tree (Plot 1) had the highest average indices values (0.31, 0.34, and 0.06, respectively), while mixed cropping of cassava, cashew, and potatoes (Plot 6) had the lowest average indices values (0.23, 0.28, and −0.029 respectively). This indicates that Plot 1 (palm tree) had better vegetation health with higher green canopy coverage and lower water stress in vegetation and soil compared to Plot 6 (cassava, cashew, and mixed potato vegetation). Drought analysis (VCI) showed that light drought areas became severe drought areas during 2001–2021 in Plots 4 and 6. The reduction of green cover and growing built-up areas accelerated the increase in drought severity. This study advocates for sustainable land use management to manage water stress and drought at the field level.

Droughts have become more severe and frequent due to global warming. In this context, it is widely accepted that for drought assessments, both water supply (rainfall) and demand (standardized precipitation evapotranspiration index, SPEI) should be considered. Using SPEI, we explored the spatial-temporal patterns of dry and wet annual and seasonal changes in five sub-regions of East Asia during 1902–2018. These factors are linked to excess drought frequency and severity on the regional scale, and their effect on vegetation remains an important topic for climate change studies. Our results show that the SPEI significantly improved extreme drought and mostly affected the SPEI-06 and SPEI-12 growing seasons in East Asia during 1981–2018. The dry and wet annual SPEI trends mostly affect the five sub-regions of East Asia. The annual SPEI had two extremely dry spells during 1936–1947 and 1978–2018. Japan, South Korea, and North Korea are wet in the summer compared to other regions of East Asia, with drought frequency occurring at 51.4%, respectively. The mean drought frequencies in China and Mongolia are 57.4% and 54.6%. China and Mongolia are the driest regions in East Asia due to high drought frequency and duration. The spatial seasonal analysis of solar radiation (SR), water vapor pressure (WVP), wind speed (WS), vegetation condition index (VCI), temperature condition index (TCI), and vegetation health index (VHI) have confirmed that the East Asia region suffered from maximum drought events. The seasonal variation of SPEI shows no clear drying trends during summer and autumn seasons. During the winter and spring seasons, there was a dry trend in East Asia region. During 1902–1990, a seasonal SPEI presented diverse characteristics, with clear wet trends in Japan, Mongolia, and North Korea in four different growing seasons, with dry trends in China and South Korea. During 1991–2018, seasonal SPEI presented clear dry trends in Japan, Mongolia, and North Korea in different growing seasons, while China and South Korea showed a wet trend during the spring, autumn, and winter seasons. This ecological and climatic mechanism provides a good basis for the assessment of vegetation and drought-change variations within East Asia. An understandings of long-term vegetation trends and the effects of rainfall and SPEI on droughts of varying severity is essential for water resource management and climate change adaptation. Based on the results, water resources will increase under global warming, which may alleviate the water scarcity issue in the East Asia region.

El Niño–Southern Oscillation (ENSO) events influence elements of the terrestrial water cycle such as precipitation and temperature, which in turn have a significant impact on drought. This work assessed the impact of El Niño and La Niña on droughts from 1970 to 2020 in the Weihe River basin (WRB) in China. This study used a standardized precipitation index (SPI) to characterize meteorological drought. The regional drought response to extreme events in El Niño/La Niña was analyzed using principal component analysis (PCA), Wilcoxon and Mann–Whitney tests, and other methods. The results showed that, based on PCA, the WRB is divided into two regions, with the northwest region (67%) comprising more area than the southeast region (33%). El Niño/La Niña significantly impacted drought in the WRB. Droughts mainly occurred in the El Niño year and the year following La Niña. El Niño had the highest number of drought years (44%), followed by the year following La Niña (43%). The number of droughts was lowest in the year following El Niño (22%). At 1-, 3-, and 6-month timescales, significant droughts mainly occurred from July to December in El Niño years and the summer following La Niña. On a 12-month timescale, significant droughts mainly occurred from January to April in El Niño years, while no droughts occurred in La Niña years. The longer the timescale of the SPI, the more months of significant drought in El Niño years; however, the intensity of drought in the basin was reduced. In the year following La Niña, summer droughts intensified on a 6-month timescale compared to a 3-month timescale. El Niño and La Niña had greater impacts on the drought index in the northwest region of the WRB. In the northwest region, 60% of the months showed significant drought, compared to only 2% of the months in the southeast region. The drought intensity was higher in the northwest region. The results of this study provide a reference for drought management and early warning systems in the WRB and support solutions to water shortage.

This study aimed to analyze drought conditions and evaluate irrigation water availability and household water needs in the Krueng Jrue sub-watershed, Aceh Province, Indonesia. The Z-score statistics method was developed to analyze the drought, and the Mock model was used to generate discharges. We performed model validation using linear regression, which produced a coefficient of determination (R2 D 0.90**) and coefficient of regression (r D 0.95**). In general, this area had a normal Z-score for precipitation (ZSP) class with 90 events (75%) and a normal Z-score for a discharge (ZSD) class with 89 events (74.2%). There were 0-11 (0-9.2%) moderate wet, very wet, extreme wet, moderate drought, and severe drought events. The consistency between the ZSP and ZSD indices reached 85.8%, indicating consensus between the meteorological droughts that were analyzed based on rainfall (ZSP) and hydrological droughts analyzed based on water discharge (ZSD). ZSP and ZSD indices showed negative values during the dry season (April to September) and positive values during the rainy season (October to March). There was a surplus of water availability for irrigation and household water needs during the rainy season and a deficit during the dry season. However, water deficits also occurred in certain months during the rainy rendeng planting season, for example, in October 2009, 2013, 2016, and 2017 as well as in February between 2008 to 2011 and from 2014 to 2017. This observation was probably due to the influence of global climate variables that need to be substantiated. This study offers necessary information for farmers, the community, and the local government when anticipating drought phenomenon, organizing the rice planting season, and evaluating water availability in other watersheds. [ABSTRACT FROM AUTHOR]

Hydrological drought (HD) characterization with different return periods is essential to appropriately design the best water management practices. In particular, characterizing the interactive relations of discharge, drought, and return periods using a novel triple diagram can deepen the interpretation of regional droughts, which have not been adequately considered, especially in semi-arid areas. Considering the critical role of HD in water exploitation and management in Iran, this study was therefore conducted to analyze the HD in different return periods in rivers of the Ardabil Province (area = 17,953 km2). To this end, the streamflow drought index (SDI) was computed using DrinC software at 1-, 3-, and 6-month time scales for 25 hydrometric stations during 1981–2014. Then, the drought severity was evaluated by CumFreq software in different return periods (2, 5, 10, 25, 50, and 100 years). Finally, the relationship between discharge, SDI, and return periods was analyzed using triple diagram models. The results revealed that the drought events had mild (−1 ≤ SDI < 0) and moderate (−1.5 ≤ SDI < −1) severity for most study stations in the study area. The mean values of SDI in the 1-, 3-, and 6-month time scales were 1.08, 0.80, and 0.55, respectively. At all study time scales, the drought severity in both rivers with low and high flows increased with increasing return periods. In such a way, the maximum drought severity has been found for rivers with high flow at a 100-year return period. The current results can be considered a screening tool for the distinctive conservation and directive management of watershed resources. [ABSTRACT FROM AUTHOR]

The Shell Creek Watershed (SCW) is a rural watershed in Nebraska with a history of chronic flooding. Beginning in 2005, a variety of conservation practices have been employed in the watershed. Those practices have since been credited with attenuating flood severity and improving water quality in SCW. This study investigated the impacts of 13 different controlling factors on flooding at SCW by using an artificial neural network (ANN)-based rainfall-runoff model. Additionally, flood frequency analysis and drought severity analysis were conducted. Special emphasis was placed on understanding how flood trends change in light of conservation practices to determine whether any relation exists between the conservation practices and flood peak attenuation, as the strategic conservation plan implemented in the watershed provides a unique opportunity to examine the potential impacts of conservation practices on the watershed. The ANN model developed in this study showed satisfactory discharge–prediction performance, with a Kling–Gupta Efficiency (KGE) value of 0.57. It was found that no individual controlling variable used in this study was a significantly better predictor of flooding in SCW, and therefore all 13 variables were used as inputs, which resulted in the satisfactory ANN model discharge–prediction performance. Furthermore, it was observed that after conservation planning was implemented in SCW, the magnitude of anomalous peak flows increased, while the magnitude of annual peak flows decreased. However, more comprehensive assessment is necessary to identify the relative impacts of conservation practices on flooding in the basin. [ABSTRACT FROM AUTHOR]

The assessment of drought hazards is important due to their socio-economic impacts on water resources, agriculture, and ecosystems. In this study, the effects of drought on changing water area and canopy of the Lake Urmia watershed in the northwest of Iran have been monitored and evaluated. For this purpose, the Standardized Precipitation Index (SPI) was calculated in short and medium periods (1-month and 3-month) to determine the dry-spell periods in the Lake Urmia basin. In reviewing this analysis, the annual average has been examined and evaluated. Furthermore, Moderate Resolution Imaging Spectroradiometer (MODIS) and remote sensing data were used to calculate the Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), the Normalized Difference Water Index (NDWI), and the Temperature–Vegetation–Dryness Index (TVDI) to identify the area of water body, water level, and vegetation changes during 20 years (2000–2020). The Pearson correlation coefficient was also employed to explore the relationship between the drought and the remote sensing-derived indices. According to the results of drought analysis, 2000, 2002, 2004, 2006, 2008, 2010, 2012, 2014, 2016, 2018, and 2020 had experienced dry spells in the Lake Urmia basin. The NDWI changes also showed that the maximum area of the Lake Urmia happened in 2000, and its minimum was recorded in 2014. The variation of NDVI values showed that the highest values of vegetation cover were estimated to be 2,850 km2 in.2000, and its lowest value was 1,300 km2 in.2014. The maximum EVI and TDVI were calculated in 2000, while their minimum was observed in 2012 and 2014. Also, the correlation analysis showed that the SPI had the highest correlation with NDVI. Meanwhile, 1-month SPI had a higher correlation than the 3-month SPI with NDVI and EVI. As a concluding remark, NDVI and NDWI were more suitable indices to monitor the changes in vegetation and drought-related water area. The results can be used to make sound decisions regarding the rapid assessment of remote sensing-derived data and water-related indices. HIGHLIGHTS Performance of the Standardized Precipitation Index (SPI)-1 and SPI-3 enriched the better display of drought intensity.; Monitoring by different vegetation indices reinforces findings and results.; The water level of the Lake Urmia has experienced many changes during the study period.; The Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI) have an excellent performance for identifying changes.; The SPI has the highest and lowest correlations with the NDVI and the Enhanced Vegetation Index (EVI).;

In the present study, a new hybridization strategy for predicting the groundwater table (GWT) and drought analysis is presented. Therefore, a hybrid of the bi-directional long short-term model (BLSTM) and the Harris hawk optimization (HHO) algorithm, namely the BLSTM–HHO algorithm, is applied. In this algorithm, the lagged data of the GWT are used as the input, whereas the current GWT data are used as the output. Additionally, the standalone BLSTM, the long short-term model (LSTM), artificial neural networks (ANN), Seasonal Autoregressive Integrated Moving Average (SARIMA), and the Autoregressive Integrated Moving Average (ARIMA) are employed as benchmark simulating algorithms. The results show that the BLSTM–HHO algorithm has more accuracy than the other investigated simulating algorithms based on the different evaluation criteria such as relative root mean squared error (RRMSE), Nash–Sutcliffe coefficient (NSE), and refined Willmott index (dr). The prediction results (from 2018 to 2022) in all three investigated aquifers show the decline of the GWT (−5.40 m for Brojen aquifer, −7.23 m for Javanmardi aquifer, and −5.81 m for Shahrekord aquifer). Accordingly, the drought analysis by the ground resource index (GRI) in the investigated areas shows that drought is expected to be continued for the next 5 years with an increasing magnitude of severity. HIGHLIGHTS A new hybridization strategy (BLSTM–HHO) has been introduced to predict the GWT and drought analysis.; The BLSTM–HHO algorithm has a high performance compared with other well-known algorithms.; The HHO algorithm has enhanced the accuracy of the BLSTM in simulating the GWT.; The BLSTM–HHO algorithm has the potential to predict various hydrological and geohydrological parameters.;

The present study evaluates the future drought hazard in Morocco using a Multi-Model Ensemble (MME) approach. First, the artificial neural network-based MME is constructed using the General Circulation Models (GCMs) from the Climate Models Intercomparison Project phase 6 (CMIP6) which are most successful in representing the historical temperature and precipitation values. Next, the future changes in the precipitation, Potential EvapoTranspiration (PET) calculated using temperatures data, aridity index, and drought indices calculated via the Standardized Precipitation Evapotranspiration Index (SPEI) values were projected for the historical period 1980-2014, near future 2025-2050, mid future 2051-2075, and far future 2076-2100. The obtained results indicate that there will be a decrease in values of the precipitation and an increase in values of the PET, leading to an increase in aridity risk for Morocco. The future projections using the SPEI results show that the average index values will mostly be in the drought zone, indicating that the drought severity will increase. The spatial analysis of SPEI values in different regions of Morocco demonstrates that the northern part of the country has relatively more drought occurrences, and drought severity tends to increase with each passing period. The study also reveals that drought severity will significantly increase after 2050 in the Shared Socio-economic Pathways 5-8.5 (SSP5-8.5) scenario. The research concludes that the increase in drought severity will significantly impact Morocco's water resources, agriculture and food security among others. • MME predicts increased drought severity in Morocco. • Decrease in precipitation and rise in PET projected. • Northern Morocco faces higher drought occurrences. • Severe future droughts threaten Morocco's cereal crops. • Drought after 2050 could critically impact food security. [ABSTRACT FROM AUTHOR]

Drought is defined as the amount of precipitation in a region less than the amount of evaporation. Human facts such as population growth, industrialization, deforestation, and uncontrolled irrigation in agriculture are among the factors that cause drought. Today, with the increase of human activities such as population growth and industrialization, drought has become a serious life-threatening issue. With a depth of around 450 m and a volume of over 600 km3, Lake Van (Turkey) is the world's largest soda lake and one of the world's largest closed-basin lakes. Increasing temperatures and decreasing precipitation in recent years indicate that there may be a drought in Lake Ban. It is important to analyze this drought and determine its change. Methods derived from remote sensing and geographic information systems technologies provide speed, practicality, and high accuracy in determining drought. Research to date has not yet determined the change of drought in Van Lake Basin using remote sensing and GIS methods. In this study, the drought in Van Lake Basin was examined periodically from 1989 to 2019. In this context, Land Surface Temperatures (LST) and Land Use/Land Cover (LULC) maps of the basin were obtained from Landsat-5 and Landsat-8 satellite images. In addition to remote sensing and GIS analysis, the Standard Precipitation Index (SPI) was calculated with precipitation data obtained from meteorology stations to determine the drought in the region. According to the results, it was concluded that the drought level in the basin has been increasing from 1989 to 2019. The findings of this research provide insights for drought increase in Van Lake Basin. Also, this study strengthens the idea that remote sensing and GIS methods can be used in drought studies effectively.

Drought is a hidden natural hazard that involves complex climatic systems and has significant environmental and social consequences. Due to the current state of catastrophic climatic occurrences, there has been an increased interest in monitoring droughts in recent years. This study conducted meteorological drought analysis for five monitoring stations in the Great Man-Made River region located in Libya. The Standardized Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) methods were used to determine meteorological droughts utilizing monthly total precipitation data, and mean monthly temperatures and monthly total precipitation data, respectively. The drought analysis of the Great Man-Made River region using DrinC software for 1-, 3-, 6-, and 12-month SPI values were researched. According to the SPI-12-month index values, the driest period was determined by 86% in the Tripoli Airport and Nalut station, and the least dry period was determined in the Sirt station by 39%. It was found that the year 2000–2001 was one of the driest years in all studied stations, and the other years with high drought rates were 1981–1982, 1984–1985, and 1992–1993. [ABSTRACT FROM AUTHOR]

Recent prolonged dry periods in summer 2018 and spring 2020 have reawakened interest in drought in Ireland, prompting questions regarding historical drought occurrence and potential long‐term risks. Employing 250 years of monthly precipitation and flow reconstructions, we investigate historical drought in Irish catchments evaluating the characteristics (number of events, duration, and deficits) of moderate, severe, and extreme droughts as well as the propagation of meteorological to hydrological drought. Using standardized indices, we identify three distinct catchment types. Cluster 1 catchments, located in the wetter northwest are characterized by small areas, low groundwater storage, and the highest frequency of hydrological drought relative to other catchments. Cluster 3 catchments, located in the drier east and southeast have larger areas, greater groundwater storage, the highest frequency of meteorological drought but the least hydrological droughts. However, once established, droughts in Cluster 3 tend to be more persistent with large accumulated deficits. Cluster 2 catchments, located in the southwest and west, are intermediate to Clusters 1 and 3, with hydrological droughts typically of shorter durations, reduced accumulated deficits but greater mean deficits. The most extreme droughts based on accumulated deficits across all catchments occurred in 1803–1806, 1854–1859, 1933–1935, 1944–1945, 1953–1954, and 1975–1977. Although not as severe, droughts in 1887–1888, 1891–1894, and 1971–1974 also appear as significant extremes. Changes in drought characteristics reveal a complex picture with the direction, magnitude, and significance of trends dependent on the accumulation period used to define drought, the period of record analysed, and the reference period used to standardize indices. Of particular note is a tendency towards shorter, more intense meteorological and hydrological droughts. Our findings offer important insight for drought and water management in Ireland given the paucity of extreme droughts in short observed river flow records. [ABSTRACT FROM AUTHOR]

Under global warming, according to results obtained from offline drought indices driven by projections of general circulation models (GCMs), future droughts in China will worsen but the results are not consistent. We analyzed changes in droughts covering the entire hydrologic cycle using outputs of GCMs of the 6th Coupled Model Intercomparison Project (CMIP6) for SSP2-4.5 and SSP5-8.5 climate scenarios, and compared the results with that of popular, offline drought indices [the self-calibrating Palmer Drought Severity Index (scPDSI), Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Precipitation Actual Evapotranspiration Index (SPAEI)]. Among meteorological, agricultural, and hydrological drought indices tested under both SSP scenarios, the results obtained from SPAEI and scPDSI agree better with univariate drought indices than SPEI. scPDSI generally agrees well with agricultural droughts (Standardized Soil Moisture Index with the surface soil moisture content; SSIS). Future droughts estimated using soil moisture analysis are more widespread than that from precipitation and runoff analysis in humid regions of South China by the end of the twenty-first century. In arid northwestern China and Inner Mongolia, drought areas and severity based on scPDSI and SSIS forced with the SSP scenarios show obvious decreasing trends, in contrast to increasing trends projected in South China. Trends projected using SPEI contradict those projected by other drought indices in non-humid regions. Therefore, selecting appropriate drought indices is crucial in project representative future droughts and provides meaningful information needed to achieve effective regional drought mitigation strategies under climate warming impact. [ABSTRACT FROM AUTHOR]

The threat of drought has been felt almost worldwide in recent years. It is critical to determine the causes of drought and how seasonal changes affect it. Additionally, it is necessary to determine the speed and impact area of drought, monitor drought areas, and attempt to find solutions against drought. With the developing satellite sensing systems, remote sensing methods are being used to investigate topics such as the increase and extent of drought, uncontrolled water consumption in agricultural activities, and the effects of unnatural pollutants on freshwater resources such as lakes and rivers. Using Synthetic Aperture Radar (SAR) satellite data to monitor changes in water bodies is a relatively new area of study in remote sensing. The spatial extent and seasonal change (spring and autumn) of droughts between 2017 and 2021 in Akşehir Lake were determined from Sentinel-1A SAR satellite data, and the Normalized Differential Water Index (NDWI) was calculated using Sentinel-2A optical satellite data and Standardized Precipitation Index (SPI) in this research. In addition, a different approach was applied to determine the change of wetland boundaries more accurately by converting the linear Sigma0 band to the decibel (dB) band and applying a non-linear 3 × 3 maximum filter to the dB band to Sentinel-1A data. Consequently, it has been established that Akşehir Lake, which used to have wetlands during the spring seasons but began to dry up in the autumn seasons, had completely dried up in both periods in 2021. [ABSTRACT FROM AUTHOR]

Drought indices are commonly used to monitor the duration and severity of droughts. In this regard, the continuously changing climate regardless of its cause or effect pushes the limit of the water deficit through time and space. Izmir is a raising city in Turkey, which owns various water resources including but not limited to seashores, lakes, river streams, and groundwater aquifers. In this study, the long-term precipitation and temperature records from 14 meteorological stations between 1973 and 2020 (for 47 years) are used to investigate the drought characteristics in Buyuk Menderes, Kucuk Menderes, and Gediz basins located in the Aegean region of Turkey. For this, the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI), Percent of Normal (PNI), and the so-called Discrepancy Precipitation Index (DPI) are used with consideration to 1-, 3-, 6-, and 12-month moving averages to investigate the drought patterns. Results showed that the monthly indices depict very similar results for the entire region. However, in the 1980s and 2010s droughts were more severe than the rest of the historical records. When the moving average operator is implemented in the analysis (3-, 6- and 12-month periods), neither SPI nor the SPEI showed the same results at any stations. It is illustrated that the periods of severe and normal drought have occurred in the past, yet the indices that are obtained using average values are generally within the normal limits, but extreme values (extremely arid or extremely wet) occurred occasionally. It is also concluded that although there is a similarity between the implemented indices, the DPI and PNI depict the highest resemblance. [ABSTRACT FROM AUTHOR]

Unlike other natural disasters, drought takes longer to develop and its effects last longer. With this feature, monitoring a possible drought makes it possible to reduce the negative effects of drought more effectively. The Standardized Precipitation Index (SPI) is one of the few drought indexes proposed by researchers to describe droughts between different climatic conditions on different time periods and regions. This study aims to perform the past and future drought analysis of the Eastern Black Sea Basin (EBSB), which is one of the most important hydrological basins in terms of precipitation amount of Turkey, with SPI. In this context, SPI values were calculated using the monthly total precipitation data for the 1981-2010 period, which were measured from 12 meteorological stations in and around the EBSB. In addition, the same processes were applied to the 2021-2050 period outputs of the GFDL-ESM-2M general circulation model in the CMIP5 archive, which was downscaled to regional scale under optimistic (RCP4.5) and pessimistic (RCP8.5) scenarios. For trend analysis of meteorological drought, trend analysis was carried out in three different groups and 95% confidence interval, using Innovative Trend Analysis method on 1- and 3- monthly SPI values. In the observation values and RCP scenarios, about 25% of the stations saw an increase in severe wet class and in severe drought class. However, in the historical period, except for the Akçaabat station (decreasing trend), significant monotonic increasing trends were observed in the SPI values, while a decreasing trend was observed in the next period for both scenarios. [ABSTRACT FROM AUTHOR]

Drought, a natural disaster, affects various sectors such as water supply, hydropower generation, agriculture, and industry. It is important to determine temporal change of drought in order to use water resources effectively and efficiently. In this study, drought analysis is performed using monthly total precipitation data measured between 1929-2016 at the meteorology observation station in Diyarbakır, Turkey. A homogeneity test is also made before drought analysis. The Standardized Precipitation Index (SPI) method is used to determine drought for 1, 3, 6 and 12 months’ time scales, and Innovative Şen Method (also known as Innovative Trend Analysis-ITA) is used to identify the trend of drought indices values for different time scales. The driest periods are determined according to time scales of 1, 3, 6 and 12 months are found as 8, 18, 21 and 53 months, respectively. While the percentage of dry periods is 40% for the 1-month time scale (SPI-1), and about 50% for the other time scales. The percentage of droughts (sum of moderate, severe, and extreme drought) for 3-months (SPI-3), 6-months (SPI-6) and 12-months (SPI-12) is between 15% and 16.5%. The ITA method results show that a weak decreasing trend found on SPI-12 for indices value greater than 0.8, and a strong decreasing trend (more than 5%) is calculated for moderate wet values. In addition, it is determined that the index values, less than -3 and -3, in SPI-12 values shows a very strong increasing trend (more than 10%). Its means that the extreme dry situation has decreased in recent years.

Drought is a natural disaster that may affect our lives in different ways. In this study, a meteorological drought analysis in the Kizilirmak river basin of Turkey was presented. The basin is located in a region with semi-arid climate characteristics. The monthly precipitation data for the 1960–2017 period from 22 meteorological stations within the basin were utilized for the drought analysis. In the scope of this research, firstly the most appropriate probability distributions for the monthly precipitation data were investigated using the goodness-of-fit tests. The Standardized Precipitation Index (SPI) was employed to examine drought characteristics in the basin. The spatial maps of droughts were constructed to identify the spatial variations of droughts for the selected years. According to the study results, the Pearson Type III probability distribution was determined as the best-fit probability distribution for the monthly precipitation at most of the stations within the basin. With the use of SPI time series, it was found that 31 years of the study period were affected by droughts with varying severities. The evaluation of spatial maps also revealed that the Kizilirmak river basin was under the impact of widespread droughts across the country during the study period. [ABSTRACT FROM AUTHOR]

Climate change is expected to increase the occurrence of droughts, with the hydrology in alpine systems being largely determined by snow dynamics. In this paper, we propose a methodology to assess the impact of climate change on both meteorological and hydrological droughts, taking into account the dynamics of the snow cover area (SCA). We also analyze the correlation between these types of droughts. We generated ensembles of local climate scenarios based on regional climate models (RCMs) representative of potential future conditions. We considered several sources of uncertainty: different historical climate databases, simulations obtained with several RCMs, and some statistical downscaling techniques. We then used a stochastic weather generator (SWG) to generate multiple climatic series preserving the characteristics of the ensemble scenario. These were simulated within a cellular automata (CA) model to generate multiple SCA future series. They were used to calculate multiple series of meteorological drought indices, the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and a novel hydrological drought index (Standardized Snow Cover Index (SSCI)). Linear correlation analysis was applied to both types of drought to analyze how they propagate and the time delay between them. We applied the proposed methodology to the Sierra Nevada (southern Spain), where we estimated a general increase in meteorological and hydrological drought magnitude and duration for the horizon 2071–2100 under the RCP 8.5 emission scenario. The SCA droughts also revealed a significant increase in drought intensity. The meteorological drought propagation to SCA droughts was reflected in an immediate or short time (1 month), obtaining significant correlations in lower accumulation periods of drought indices (3 and 6 months). This allowed us to obtain information about meteorological drought from SCA deficits and vice versa. [ABSTRACT FROM AUTHOR]

In this study, it was aimed to determine the meteorological drought trends in the Euphrates Basin by using rainfall-based Standardised Precipitation Index (SPI), Statistical Z Score Index (ZSI), Rainfall Anomaly Index (RAI) and rainfall and temperature-based Standardised Precipitation Evapotranspiration Index (SPEI) and Reconnaissance Drought Index (RDI). Mann-Kendall (MK) and Modified Mann-Kendall (MMK) tests were applied during the monthly and annual periods to determine drought trends. The trend analysis results of meteorological drought indices are mapped in 90% (z > 1.65) and 95% (z > 1.96) confidence intervals. According to the analyses applied, it was determined that the trend analysis results of SPI, ZSI and RDI indicate almost the same results. In addition, SPEI was found to be more sensitive in detecting drought trends compared to other indices. Moreover, it has been concluded that the Euphrates Basin is at great risk of meteorological drought due to the dominance of decreasing drought trends and trends in the basin. Making a drought management plan and going into alarm in endangered areas is recommended to prevent existing risks. [ABSTRACT FROM AUTHOR]

The drought phenomenon is a primary natural hazard in Iran. The drought can be analyzed using different indices. Therefore, the use of suitable indices will have an essential role in quantitatively investigating this phenomenon. Since precipitation is one of the most critical factors in drought analysis, different drought indices consist of precipitation and have been developed based on this parameter. In this study, the time series of nine precipitation-based drought indices were compared in 30 synoptic stations of Iran, and the superior index was determined during 1960–2014. Then, using the selected drought index, the annual trend of wet and dry periods was calculated by the modified Mann–Kendall test. Among studied indices, the SPI index was selected as the superior one. This index was well fitted by the Normal distribution and had a correlation coefficient of more than 0.92 with precipitation. Also, this index was sensitive to the amount of precipitation, and it could detect drought events corresponding to the minimum precipitation. In other words, the SPI had the best capability to determine extreme drought based on minimum precipitation. The results of drought analysis based on the SPI index showed that at least one drought event happened in the majority of studied years (82%). It reflects drought conditions in the studied area, especially in 2008 and 2010. The trend analysis of wet and dry periods showed the decreasing trend of the SPI index in the most studied stations. The decreasing trend of the mentioned index was significant (at 95% confidence level) in the northwest and west of Iran. The trend line slope values corresponding to the SPI index were negative in most studied stations. Tabriz and Esfahan stations had the maximum value of negative (-0.027) and positive (0.025) trend line slope, respectively. [ABSTRACT FROM AUTHOR]

In recent years, the negative effects of climate change on water resources have been observed. Due to the decrease in precipitation in the Burdur Lake basin, there is serious volume loss especially in surface waters. In this study, basin drought analysis was performed using standardized precipitation index (SPI) and China Z index (CZI) methods. For this, precipitation data of 6 different meteorological stations located in and around the basin were used. In addition, the relationships between SPI and CZI indices are statistically revealed. In Burdur Meteorology station, it was determined that the longest drought period was experienced in the 24-month time scale with the SPI method since January 1951 with 1612 days. However, the most severe drought has been determined to have lasted 2250 days with a severity of 70.027 since January 1989. According to the drought analysis using the China Z index at the same meteorology station, the longest drought periods were 1553 days since January 1989, with a severity of 70.782. According to the obtained results, medium and mild droughts were detected around the Burdur Lake and south of the basin in 2019. In addition, the R2 values of both methods (0.96-0.98) are quite high and very close index values were calculated.

The objective of this study is to investigate the meteorological, agricultural and hydrological drought of Muğla city for the period of 1960-2018 as well as to analyse precipitation trend. Monthly total precipitation data for the period of 1960-2018 belonging to Muğla meteorological station obtained from the Turkish State Meteorological Service were used in this study. Run (Swed-Eisenhart) homogeneity test, Mann-Kendall method and Standardized Precipitation Index method were applied to precipitation data. In addition, the severity and duration of droughts were examined. As a result, long years’ precipitation and drought trend were demonstrated for Muğla city. The annual total precipitation for Muğla city in the period 1960-2018 was found to be 1180.2 mm. The lowest amount of precipitation in the study period was 564.6 mm in 2008 and the highest amount of rainfall was 1805 mm in 1969. In the province of Muğla, the number of the humid months was slightly higher than the other classes. In the province of Muğla, the numbers of the mildly humid and moderately dry months were slightly higher than the other classes. It was seen that the numbers of humid and dry months in Muğla province were mostly clustered in mildly humid, moderately humid, mildly dry and moderately dry classes. In addition, analyzes show that drought is less repetitive as the time period increases, but has a longer duration effect. Total drought severity and total drought duration of Muğla station on scales basis coincided with almost similar years. However, in the 3-monthly Standardized Precipitation Index period, the strongest total drought intensity (-13.90) was observed between 2006 December – 2007 September, whereas the long-term (12 months) drought occurred between 2000 June – 2001 May.

Drought is generally defined as a disaster affecting vital activities negatively because of water scarcity as a result of precipitation falling below the recorded normal levels. In the present study, the Standardized Precipitation Evapotranspiration Index was applied for the first time in Hirfanli Dam basin, which has the characteristics of a semiarid climate in Turkey. The annual drought events in the basin between 1968 and 2017 were investigated by using the precipitation and temperature data obtained from Gemerek, Kayseri, Kirsehir, Nevsehir, Sivas, and Zara meteorology observation stations located in Hirfanli Dam basin. The dry and wet years were determined in the basin, and evaluations were made in this respect. The years when the most severe droughts happened in the basin were determined, and drought maps, which showed the spatial distribution of drought, were prepared. In the light of the analyses and maps made, it was found that the most severe drought happened in 2001 in Hirfanlı Dam basin. [ABSTRACT FROM AUTHOR]

Drought is a natural phenomenon with various social, environmental, and economic effects. Adverse impacts of drought at a regional and global scale have become more evident with climate change. The Seyhan and Ceyhan basins were chosen as study areas in Turkey. Drought analyses were performed using data from 14 meteorological stations gathered between January 1989 and July 2020 in Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI), based on 3-4-6-12 monthly scales. SPI and SPEI are common indices used for drought tracking. The coefficient of determination (R² ) was found to be 0.954 and used to analyze the regression between the annual SPI and SPEI. According to SPI and SPEI annual analyses results of study area, the driest year was found to be 2014. SPEI determined more arid periods than SPI for the same time scales. Analyses reveal that the dry period in basins has increased in the last decade and the region is facing a risk of drought. Analyses were made to predict and evaluate risks and to help the efficient use of agricultural lands and water resources in the study area during dry periods. [ABSTRACT FROM AUTHOR]

Drought is defined as the amount of precipitation in a region less than the amount of evaporation. Human facts such as population growth, industrialization, deforestation, and uncontrolled irrigation in agriculture are among the factors that cause drought. Today, with the increase of human activities such as population growth and industrialization, drought has become a serious life-threatening issue. With a depth of around 450 m and a volume of over 600 km3, Lake Van (Turkey) is the world's largest soda lake and one of the world's largest closed-basin lakes. Increasing temperatures and decreasing precipitation in recent years indicate that there may be a drought in Lake Ban. It is important to analyze this drought and determine its change. Methods derived from remote sensing and geographic information systems technologies provide speed, practicality, and high accuracy in determining drought. Research to date has not yet determined the change of drought in Van Lake Basin using remote sensing and GIS methods. In this study, the drought in Van Lake Basin was examined periodically from 1989 to 2019. In this context, Land Surface Temperatures (LST) and Land Use/Land Cover (LULC) maps of the basin were obtained from Landsat-5 and Landsat-8 satellite images. In addition to remote sensing and GIS analysis, the Standard Precipitation Index (SPI) was calculated with precipitation data obtained from meteorology stations to determine the drought in the region. According to the results, it was concluded that the drought level in the basin has been increasing from 1989 to 2019. The findings of this research provide insights for drought increase in Van Lake Basin. Also, this study strengthens the idea that remote sensing and GIS methods can be used in drought studies effectively. [ABSTRACT FROM AUTHOR]

Anthropogenic industrial dust decreases productivity and slows down the growth of plants. Quantifying the effects of industrial dust on vegetation and determining the distance over which factories scatter dust are of paramount importance for biodiversity conservation and sustaining ecosystem services. This study aims at quantifying the effect of dust emitted by the Neka cement plant (NCP), Mazandaran province, northern Iran, on the surrounding Hyrcanian forests based on an analysis of the Leaf Area Index (LAI) retrieved from Sentinel-2 imagery. An Inductively Coupled Plasma Mass Spectrometer (ICP-MS) was used to quantify the concentrations of cadmium (Cd), chromium (Cr), copper (Cu), lead (Pb), calcium (Ca), magnesium (Mg), sodium (Na), silicon (Si) and zinc (Zn) in leaves of the dominant Chestnut-leaved Oak (Quercus castaneifolia). A feed-forward neural network algorithm and field measurements were used to retrieve the leaf area index (LAI) from Sentinel-2 data with a RMSE of 0.42 (m2/m2). MODIS-NDVI and EVI time series spanning 17 years (2000 to 2017) were analysed to ensure the independence of the variation in the condition of the vegetation from drought or other environmental factors. The results indicate that Sentinel-2 data can be used to map degradation due to pollution from the cement plant and quantify the effect of the dust spatially. Dust from the cement plant (dust source) was carried approximately 4700 meters in the direction of the prevailing wind. A significant correlation of 0.849 was recorded between LAI and distance from the NCP. It is concluded that dust from the NCP had adverse ecological effects on the neighbouring forest ecosystems recently designated a UNESCO World Heritage Site.

The Shell Creek Watershed (SCW) is a rural watershed in Nebraska with a history of chronic flooding. Beginning in 2005, a variety of conservation practices have been employed in the watershed. Those practices have since been credited with attenuating flood severity and improving water quality in SCW. This study investigated the impacts of 13 different controlling factors on flooding at SCW by using an artificial neural network (ANN)-based rainfall-runoff model. Additionally, flood frequency analysis and drought severity analysis were conducted. Special emphasis was placed on understanding how flood trends change in light of conservation practices to determine whether any relation exists between the conservation practices and flood peak attenuation, as the strategic conservation plan implemented in the watershed provides a unique opportunity to examine the potential impacts of conservation practices on the watershed. The ANN model developed in this study showed satisfactory discharge–prediction performance, with a Kling–Gupta Efficiency (KGE) value of 0.57. It was found that no individual controlling variable used in this study was a significantly better predictor of flooding in SCW, and therefore all 13 variables were used as inputs, which resulted in the satisfactory ANN model discharge–prediction performance. Furthermore, it was observed that after conservation planning was implemented in SCW, the magnitude of anomalous peak flows increased, while the magnitude of annual peak flows decreased. However, more comprehensive assessment is necessary to identify the relative impacts of conservation practices on flooding in the basin.

Climate change increases the odds of worsening drought in many parts of the World. Climate projections for the Mediterranean basin in which Turkey is located expresses alarming conclusions about severe droughts. Droughts are expected to prevail in different severities and periods throughout Turkey. Iğdır plain, which lies in eastern part of Turkey is convenient for cultivation of many agricultural products because of its fertile soils and micro-climatic properties. In this study, drought analysis were carried out for Iğdır by using Standardized Precipitation Index (SPI), Reconnaissance Drought Index (RDI) and Streamflow Drought Index (SDI). The data (precipitation and flow) were obtained in monthly intervals from Turkish institutions, namely General Directorate of Meteorology and General Directorate of State Hydraulic Works. Study was aimed to examine the integrated effect of low precipitations and high temperatures on hydrological and meteorological drought. Annual SPI results show that four severe and three moderate drought events whereas RDI detected four severe and four moderate drought events for the study period (47 years, 1971-2018). SPI index detected severe category droughts in the water years of 1980, 1989 and 1997. RDI detected severe category droughts in the mentioned years together with one more event in 2000. SDI identified 2002 as extreme drought year, and identified 1982, 1984, 1986 and 2002 as moderate drought years. The output of the study is aimed to serve for better understanding of droughts in the Igdir Plain.

Drought is considered to be one of the most devastating natural disasters. In recent years, determination of historical droughts has gained more importance. This can be attributed to the fact that once the trend of historical droughts is determined, it should be possible to struggle against drought more effectively. In this study, the drought analysis is performed in the Southeastern Anatolia Project (GAP) region, which is Turkey's biggest integrated project, using the monthly total precipitation data from 15 stations in nine provinces. Standardized precipitation index (SPI), being one of the most frequently used methods in the literature, is used to determine the drought indices. Temporal drought and occurrence of drought are calculated for 3, 6 and 12 month time scales. The non-parametric Mann–Kendall and Mann–Kendall Rank Correlation tests are used to determine the monotonic trends of drought indices and its year of initiation. The "Pre-whitened" method is used to remove serial correlation from time series before analysis. Linear slope of the trend is determined by Sen's Slope method, and Inverse Distance Weighting method is used for the spatial analysis. According to trends of temporal drought of the GAP region, a decreasing trend is found in 30% of the stations for 12-month SPI values with a statistical significance. Based on the results obtained from spatial analysis, there is a decreasing trend in most of the region for almost all time scales, and the slopes of trend are relatively higher in the north and south of the region. [ABSTRACT FROM AUTHOR]

The Tehuacán-Cuicatlán Biosphere Reserve, Mexico (TCBR) is the southernmost arid or semi-arid zone with the highest biodiversity in North America and is a UNESCO World Heritage site. Two main hydrographic streams cross the TCBR, the Salado River (an endogenous river) and the Grande River (an exogenous river). This study investigated temperature anomalies over the past 40 years. We analyzed potential differences between sub-basins and riparian areas on both streams using various indices, namely the Global Warming Index (GWI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and Normalized Difference Drought Index (NDDI), and analyzed the potential relationship of these indices with climate change. Time series of satellite-based precipitation (June 2000–December 2020) and air temperature (January 1980–December 2020) were analyzed. A set of Landsat 8 OLI TIRS imagery from the driest and wettest months (2013–2020) was used to estimate NDVI, NDWI, and NDDI. These indices were evaluated separately for the sub-basins and river corridors in the dry and rainy seasons. The precipitation records indicate that in the Grande river sub-basin, precipitation is higher than in the Salado river sub basin. Normalized temperature anomalies and the GWI suggest a warming trend from 1994 to 2020, increasing up to 0.86°C in the Salado River and 0.52°C in the Grande River. The Grande and Salado sub basins showed significant differences between dry and wet seasons for each index (NDVI, NDWI, and NDDI). A Discriminant Analysis showed that the Salado sub-basin and the Salado River corridor are associated with severe drying conditions in the dry season (highest NDDI values). In the wet season, the Grande River corridor showed intermediate values of NDVI and NDWI but low values of NDDI. The Grande River corridor in the dry season was characterized by intermediate values of NDVI, NDWI, and NDDI. These river corridors provide environmental services in a trade-off with the stream and should be considered biodiversity hotspots. Due to the accentuated warming trend and the lowest precipitation, the Salado River sub-basin showed desertification signs associated with climate change. Both the Salado and the Grande River corridors showed resilience strategies to face climatic conditions.