Evaluation of multi-sensor satellite data for monitoring different drought impacts

Drought is a natural disaster that significantly affects human life; therefore, precise monitoring and prediction is necessary to minimize drought damage. Conventional drought monitoring is based predominantly on ground observation stations; however, satellite imagery can be used to overcome the disadvantages of existing monitoring methods and has the advantage of monitoring wide areas. In this research, we assess the applicability of drought monitoring based on satellite imagery, focusing on historic droughts in 2001 and 2014, which caused major agricultural and hydrological issues in South Korea. To assess the applicability and accuracy of the drought index, drought impact areas in the study years were investigated, and spatiotemporal comparative analyses between the calculated drought index and previously affected areas were conducted. For drought monitoring based on satellite imagery, we used hydro-meteorological factors such as precipitation, land surface temperature, vegetation, and evapotranspiration, and applied remote sensing data from various sensors. We verified the effectiveness of using precipitation data for meteorological drought monitoring, vegetation and land surface temperature data for agricultural drought monitoring, and evapotranspiration data for hydrological drought monitoring. Moreover, we confirmed that the Standard Precipitation Index (SPI) can be indirectly applied to agricultural or hydrological drought monitoring by determining the temporal correlation between SPI, calculated for various time scales, and satellite-based drought indices.     

Spatio-temporal drought analysis in the Trakya region,Turkey

Abstract

Since droughts are natural phenomena, their occurrence cannot be predicted with certainty and thus it must be treated as a random variable. Once drought duration and magnitude have been found objectively, it is possible to plan for the transport of water in known quantities to drought-stricken areas either from alternative water resources or from water stored during wet periods. The summation of deficits over a particular period is referred to as the drought magnitude. Drought intensity is the ratio of drought magnitude to its duration. These drought properties at different truncation levels provide significant hydrological and hydrometeorological design quantities. In this study, the run analysis and z-score are used for determining drought properties of given hydrological series. In addition, kriging is used as a spatial drought analysis for mapping. This study is applied to precipitation records for Istanbul, Edirne, Tekirdag and Kirklareli in the Trakya region, Turkey and then the drought period, magnitude and standardized precipitation index (SPI) values are presented to depict the relationships between drought duration and magnitude.     

Drought impacts on water quality and potential implications for agricultural production in the Maipo River Basin,Central Chile

ABSTRACT

Droughts can have serious negative impacts on the water quality needed for irrigated agriculture. The Metropolitan region of Chile is a relevant producer of high-value crops and is prone to droughts. Standardized Drought Indices were used to characterize meteorological and hydrological droughts for the period from 1985 to 2015. To understand the relationship between droughts and water quality, we evaluated the correlations between daily discharge and surface water quality observations. The threshold level method was used to compare physicochemical parameters during hydrological drought periods with the Chilean water quality thresholds for agricultural uses. A significant (p < 0.05) negative relationship between discharge and electrical conductivity and major ions was found in most of the basin. Hydrological stations located in irrigation districts exceeded the official thresholds for these parameters during hydrological drought periods seriously threatening irrigated agriculture of the region.     

Response of remotely sensed Normalized Difference Water Deviation Index to the 2006 Drought of eastern Sichuan Basin

One of the most serious droughts in last century occurred in eastern Sichuan Basin in the summer of 2006 (hereinafter called the Drought). The response of Moderate Resolution Imaging Spectroradiometer (MODIS, boarding on NASA satellites of Terra and Aqua) to the Drought was analyzed in order to reach one practicable monitoring solution for regional soil moisture. Temporal process and spatial extension of the Drought were firstly estimated with ground meteorological and hydrological observations. Then, for the whole region of Sichuan and Chongqing, the remotely sensed Normalized Difference Water In- dex (NDWI) for the summers of 2001―2006 were calculated based on 8-day composite MODIS products, which were further used to construct a new water index (Normalized Difference Water Deviation Index, NDWDI) to examine the sensitivity of remote sensing in the Drought. The study showed that the NDWDI is more sensitive to regional drought than other absolute-soil-moisture-based indices. With the new index, the study extracted the spatial-temporal characteristics of the 2006 Drought, and explored its developing and withdrawing processes, which agreed with related statistics. Compared with ground method of drought observation, the NDWDI-based remote sensing solution of this paper is more pref- erable and practicable in that the local soil properties of water consumption and supply are implicitly taken into account, and the spatial representativity limit of ground observation is circumvented to a degree as satellite remotely senses the earth surface in a way of two-dimensional pixel matrix. So, the NDWDI-based method can be used to monitor regional soil water stress situation more practically and efficiently.     

Development of an operational low-flow index for hydrological drought monitoring over Europe

Near real-time monitoring of hydrological drought requires the implementation of an index capable of capturing the dynamic nature of the phenomenon. Starting from a dataset of modelled daily streamflow data, a low-flow index was developed based on the total water deficit of the discharge values below a certain threshold. In order to account for a range of hydrological regimes, a daily 95th percentile threshold was adopted, which was computed by means of a 31-day moving window. The observed historical total water deficits were statistically fitted by means of the exponential distribution and the corresponding probability values were used as a measure of hydrological drought severity. This approach has the advantage that it directly exploits daily streamflow values, as well as allowing a near real-time update of the index at regular time steps (i.e. 10 days, or dekad). The proposed approach was implemented on discharge data simulated by the LISFLOOD model over Europe during the period 1995–2015; its reliability was tested on four case studies found within the European drought reference database, as well as against the most recent summer drought observed in Central Europe in 2015. These validations, even if only qualitative, highlighted the ability of the index to capture the timing (starting date and duration) of the main historical hydrological drought events, and its good performance in comparison with the commonly used standardized runoff index (SRI). Additionally, the spatial evolution of the most recent event was captured well in a simulated near real-time test case, suggesting the suitability of the index for operational implementation within the European Drought Observatory.     

Observed trends and relationships between ENSO and standardized hydrometeorological drought indices in central Chile

Droughts are natural phenomena that severely affect socio economic and ecological systems. In Chile, population and economic activities are highly concentrated in its central region (i.e. between latitudes 29°S and 40°S), which periodically suffers from severe droughts affecting agriculture, hydropower, and mining. Understanding the dynamics of droughts and large-scale atmospheric processes that influence the occurrence of dry spells is essential for forecasting and efficient early detection of drought events. Central Chile's climate is marked by a significant El Niño Southern Oscillation (ENSO) influence that might help to better characterize droughts as well as to identify the effects of ENSO on the spatial and temporal characteristics of meteorological and hydrological droughts in the region. We analysed the behaviour of the Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Streamflow Index (SSI) time series for 6-month accumulation periods over the austral winter and summer seasons. Multiple linear regression (MLR) and Generalized Linear Models (GLM) showed a significant ENSO influence on dry events for SPEI-6 and SSI-6 during winter and summer. We found that the magnitude of correlation between ENSO and SPEI-6 has changed over the last decades becoming weaker in winter periods and increasing in spring summer periods. Increasing trends in meteorological and hydrological drought events were also identified, along all latitudes, with significant trends during winter in the southern latitudes, and during summer in the semi-arid and Mediterranean zones. These results indicate that drought mitigation actions and policies are necessary to overcome their adverse effects. Given the monthly persistence of ENSO and its relationship to drought indices, there are opportunities for drought monitoring and seasonal forecasting that could become part of national drought management systems.     

Hydrological drought in the west of Iran and possible association with large‐scale atmospheric circulation patterns

Drought is a slow‐onset, creeping natural hazard which is an inevitable part of normal climate fluctuation especially in arid and semiarid regions, and its variability can be explained in terms of large‐scale atmospheric circulation patterns. Standardized streamflow index (SSFI) was utilized to characterize hydrological drought in the west of Iran for the hydrological years of 1969–1970 to 2008–2009. The linkage of atmospheric circulation patterns (ENSO, NAO) to hydrological drought was also used to reveal relations of climate variability affecting hydrological drought. River discharges exhibited negative anomalies during the warm phase of ENSO (El Niño) which caused the extreme and severe droughts in the study area, being strongest during the hydrological years of 2007–2008 and 2008–2009. The analysis also indicated the teleconnection impact of ENSO on the hydrological drought severity in the first half of the hydrological year especially between November and March. Moreover, the concurrent and lag correlations revealed a weak relationship between the SSFI drought severity and the NAO index. Copyright © 2012 John Wiley & Sons, Ltd.     

极端干旱事件中洞庭湖水面变化过程及成因

干旱是洞庭湖区长期以来面临的严重自然灾害之一,给周边人们的生产生活造成了极大的影响.针对2006和2011年洞庭湖区发生的极端干旱事件,借助遥感影像大范围、时空连续的优势,结合湖区水文气象等观测资料,从时空两方面阐释了洞庭湖在典型干旱年份水域分布及变化过程,进一步从温度、降水、径流以及蓄水量等方面对比分析不同干旱事件发生、发展过程的一致性和差异性.研究结果表明:2006年干旱大致从7月开始,至12月结束.水面淹没范围由湖心向周边扩展,到7月达到最大值,8月提前进入枯水期,减小范围主要集中在东洞庭湖外围和南洞庭湖的北边.2006年干旱属于由入湖径流减少主导的水文干旱事件;2011年的干旱则从4月开始,至11月结束,在9月以后干旱继续加重.水面淹没范围在6月急剧增大且一直到8月都维持在较高的水平,涨水期水面由中心向四周淹没,退水期水面变化范围与涨水期相反.2011年干旱是由流域降水减少引起的水文和气象干旱事件.研究结果揭示了洞庭湖区干旱成因的多样性和复杂性,对于制定科学合理的干旱灾害防范措施,减缓区域的生态环境问题等具有一定的指导和借鉴意义.     

Drought hotspot analysis and risk assessment using probabilistic drought monitoring and severity–duration–frequency analysis

Drought hotspot identification requires continuous drought monitoring and spatial risk assessment. The present study analysed drought events in the agriculture‐dominated mid‐Mahanadi River Basin in Odisha, India, using crop water stress as a drought indicator. This drought index incorporated different factors that affect crop water deficit such as the cropping pattern, soil characteristics, and surface soil moisture. The drought monitoring framework utilized a relevance vector machine model‐based classification that provided the uncertainty associated with drought categorization. Using the proposed framework, drought hotspots are identified in the study region and compared with indices based on precipitation and soil moisture. Further, a bivariate copula is employed to model the agricultural drought characteristics and develop the drought severity–duration–frequency (S–D–F) relationships. The drought hotspot maps and S–D–F curves are developed for different locations in the region. These provided useful information on the site‐specific drought patterns and the characteristics of the devastating droughts of 2002 and 2012, characterized by an average drought duration of 7 months at several locations. The site‐specific risk of short‐ and long‐term agricultural droughts are then investigated using the conditional copula. The results suggest that the conditional return periods and the S–D–F curves are valuable tools to assess the spatial variability of drought risk in the region.     

Exploring spatiotemporal relationships among meteorological,agricultural, and hydrological droughts in Southwest China

Each type of drought has different characteristics in different regions. It is important to distinguish different types of droughts and their correlations. Based on gauged precipitation, temperature, simulated soil moisture, and runoff data during the period 1951–2012, the relationships among meteorological, agricultural, and hydrological droughts were analyzed at different time scales in Southwest China. The standardized precipitation evapotranspiration index (SPEI), soil moisture anomaly percentage index (SMAPI), and standardized runoff index (SRI) were used to describe meteorological, agricultural, and hydrological droughts, respectively. The results show that there was a good correlation among the three indices. SMAPI had the best correlation with the 3 month SPEI and SRI values. It indicates that agricultural drought was characterized by a 3-month scale. The three drought indices displayed the similar special features such as drought scope, drought level, and drought center during the extreme drought of 2009–2010. However, the scope and level of SPEI were bigger than those of SMAPI and SRI. The propagation characteristics of the three types of droughts were significantly different. The temporal drought process in typical grids reflect that the meteorological drought occurred ahead of agricultural and hydrological droughts by about 1 and 3 months, respectively. Agricultural drought showed a stable drought process and reasonable time periods for the drought beginning and end. These results showed the quantitative relationships among three types of drought and thus provided an important supporting evidence for regional drought monitoring and strategic decisions.     

Hydrological identification of drought

The problem of drought identification is considered from a primarily hydrological viewpoint. The problems related to the definition, identification and prediction of drought have not yet been solved. Although rainfall data are analysed as the main indicator and characteristic of drought, other characteristics resulting from a rainfall deficit are also important. A time unit of one month was selected as the most suitable for analysis. Special attention was paid to the selection of truncation levels with respect to their influence on the results of drought identification. Three methods for drought identification were applied to a series of monthly rainfall data in Osijek from January 1882 to December 1990: (1) run analysis; (2) a discrete Markov process; and (3) the percentile method. Although the results of these three methods are encouraging, different methods yielded similar results. Some drawbacks of the application of distribution curves are discussed. Drought events should be identified using a number of different procedures.     

The spatial–temporal variation of dry and wet periods in Iran based on comparing SPI and RDI indices

Drought is a natural hazard which can cause harmful effects on water resources. To monitor drought, the use of an indicator and determination of wet and dry period trend seem to have an important role in quantifying the drought analysis. In this paper, in addition to the comparison of Reconnaissance Drought Index (RDI) and Standardized Precipitation Index (SPI), based on the most appropriate probability distribution function, it was tried to examine the trends of dry and wet periods based on the mentioned indices. Accordingly, the meteorological data of 30 synoptic stations in Iran (1960–2014) was used and the trend was analyzed using the Mann–Kendall test by eliminating the effect of any significant autocorrelation coefficients at 95% confidence level (modified Mann–Kendall). Comparing results between the time series of RDI and SPI drought indices based on statistical indicators (RMSE?<?0.434, R²?>?0.819 and T-statistic?<?0.419) in all studied stations revealed that the behavior of the two indices was roughly the same and the difference between them was not significant. The trend analysis results of RDI and SPI indices based on modified Mann–Kendall test showed that the variation of dry and wet periods was decreasing in most of the studied stations (five cases were significant). In addition, the results of the trend line slope of dry and wet periods related to the drought indices in the studied area indicated that the slope was negative for SPI and RDI indices in 70% and 50% of stations, respectively.     

Drought monitoring

Drought detection, monitoring and indices are closely related to its definition. The specific definition chosen for a particular drought analysis will affect the procedures one uses in drought detection and monitoring. The traditional Palmer Drought Severity Index (PDSI) has been proven to be ineffective in regions of predominantly irrigated agriculture.The recently developed ALERT (Automated Local Evaluation in Real Time) system is proposed for use in monitoring the spatial and temporal variations of drought in real time. The ALERT system uses standardized instruments, radio frequencies, software and hardware. It was originally developed as a flash flood waming system by local flood control districts and the National Weather Service. However, now it has expanded to over 100 other uses in the areas of natural and man-made disaster detection and warning. The successful ALERT system indicates the need for the continued development of a national drought monitoring index that is applicable to a wide range of climate, hydrologic and water resource environments.     

Drought monitoring

Drought detection, monitoring and indices are closely related to its definition. The specific definition chosen for a particular drought analysis will affect the procedures one uses in drought detection and monitoring. The traditional Palmer Drought Severity Index (PDSI) has been proven to be ineffective in regions of predominantly irrigated agriculture.The recently developed ALERT (Automated Local Evaluation in Real Time) system is proposed for use in monitoring the spatial and temporal variations of drought in real time. The ALERT system uses standardized instruments, radio frequencies, software and hardware. It was originally developed as a flash flood waming system by local flood control districts and the National Weather Service. However, now it has expanded to over 100 other uses in the areas of natural and man-made disaster detection and warning. The successful ALERT system indicates the need for the continued development of a national drought monitoring index that is applicable to a wide range of climate, hydrologic and water resource environments.     

Study of the temporal and spatial patterns of drought in the Yellow River basin based on SPEI

Drought is one of the severe natural disasters to impact human society and occurs widely and frequently in China,causing considerable damage to the living environment of humans.The Yellow River basin(YRB)of China shows great vulnerability to drought in the major basins;thus,drought monitoring in the YRB is particularly important.Based on monthly data of 124 meteorological stations from 1961 to 2015,the Standardized Precipitation Evapotranspiration Index(SPEI)was used to explore the temporal and spatial patterns of drought in the YRB.The periods and trends of drought were identified by Extreme-point Symmetric Mode Decomposition(ESMD),and the research stages were determined by Bernaola-Galvan Segmentation Algorithm(BGSA).The annual and seasonal variation,frequency and intensity of drought were studied in the YRB.The results indicated that(1)for the past 55 years,the drought in the YRB has increased significantly with a tendency rate of-0.148(10 a)~(-1),in which the area Lanzhou to Hekou was the most vulnerable affected(-0.214(10 a)~(-1));(2)the drought periods(2.9,5,10.2 and 18.3 years)and stages(1961–1996,1997–2002 and 2003–2015)were characterized and detected by ESMD and BGSA;(3)the sequence of drought frequency was summer,spring,autumn and winter with mean values of 71.0%,47.2%,10.2%and 6.9%,respectively;and(4)the sequence of drought intensity was summer,spring,winter and autumn with mean values of 0.93,0.40,0.05 and 0.04,respectively.     

Revisiting hydrological drought propagation and recovery considering water quantity and quality

Climate extremes, in particular droughts, are significant driving forces towards riverine ecosystem disturbance. Drought impacts on stream ecosystems include losses that can be either direct (e.g., destruction of habitat for aquatic species) or indirect (e.g., deterioration of water quality, soil quality, and increased chance of wildfires). This paper combines hydrologic drought and water quality changes during droughts and represents a multistage framework to detect and characterize hydrological droughts while considering water quality parameters. This method is applied to 52 streamflow stations in the state of California, USA, over the study period of 1950–2010. The framework is assessed and validated based on two drought events declared by the state in 2002 and 2008. Results show that there are two opposite drought propagation patterns in northern and southern California. In general, northern California indicates more frequent droughts with shorter time to recover. Chronology of drought shows that stations located in southern California have not followed a specific pattern but they experienced longer drought episodes with prolonged drought recovery. When considering water quality, results show that droughts either deteriorate or enhance water systems, depending on the parameter of interest. Undesirable changes (e.g., increased temperature and decreased dissolved oxygen) are observed during droughts. In contrast, decreased turbidity is detected in rivers during drought episodes, which is desirable in water systems. Nevertheless, water quality deteriorates during drought recovery, even after drought termination. Depending on climatic and streamflow characteristics of the watersheds, it was found that it would take nearly 2 months on average for water quality to recover after drought termination.     

Evaluating simulated daily discharge for operational hydrological drought monitoring in the Global Drought Observatory (GDO)

ABSTRACT

Hydrological drought is currently underrepresented in global monitoring systems, mainly due the shortage of near real-time estimates of river discharge at the global scale. In this study, the outputs of the Lisflood model are used to define a low-flow drought index, which shows a good correspondence with long-term records of the Global Runoff Data Centre in the period 1980–2014, as well as with verified information from the literature on six major drought events (covering different regions and watershed sizes). In contrast, the near real-time simulation (from 2015 onward) provides temporally inconsistent estimates over about 20% of the modelled cells (mostly over South America and Central Africa), even if reasonable results are obtained over other regions, as confirmed by intercomparison with the operational outcomes of the European Drought Observatory for the 2018 drought. In spite of the highlighted limitations, valuable information for operational drought monitoring can be retrieved from these simulations.     

Dimensionality reduction in drought modelling

For monitoring hydrological events characterized by high spatial and temporal variability, the number and location of recording stations must be carefully selected to ensure that the necessary information is collected. Depending on the characteristics of each natural process, certain stations may be spurious or redundant, whereas others may provide most of the relevant data. With the objective of reducing the costs of the monitoring system and, at the same time, improving its operational effectiveness, three procedures were applied to identify the minimum network of rain gauge stations able to capture the characteristics of droughts in mainland Portugal. Drought severity is characterized by the standardized precipitation index applied to the timescales of 1, 3, 6 and 12 consecutive months. The three techniques used to reduce the dimensionality of the network of rain gauges were as follows: (i) artificial neural networks with sensitivity analysis, (ii) application of the mutual information criterion and (iii) K‐means cluster analysis using Euclidean distances. The results demonstrated that the best dimensionality reduction method was case dependent in the three regions of Portugal (northern, central and southern) previously identified by cluster analysis. All the reduction techniques lead to the selection of a subset of rain gauges capable of reproducing the original temporal patterns of drought. For specific severe drought events in Portugal in the past, the comparison between drought spatial patterns obtained with the original stations and the selected subset indicated that the subset produced statistically satisfactory results (correlation coefficients higher than 0.6 and efficiency coefficients higher than 0.5). Copyright © 2012 John Wiley & Sons, Ltd.     

Hydro-meteorological drought assessment under climate change impact over the Vu Gia–Thu Bon river basin,Vietnam

Hydro-meteorological drought was assessed with respect to climate change over an estuary catchment Vu Gia-Thu Bon in Central Vietnam, which economy is dependent on agriculture. The fully-distributed hydrological model MIKE SHE was used to simulate river flow over the study region for the period 1991–2010. Drought were assessed using the Standardized Precipitation Index and the Standardized Runoff Index. The future climate was studied using the regional climate model Weather Research and Forecasting by downscaling an ensemble of three global climate models – CCSM3.0, ECHAM5 and MIROC-medium resolution over current (1961–1990) and future climates (2011–2040), under the A2 emissions scenario. The results suggest that, despite hotter and wetter future climate, the area is likely to suffer more from severe and extreme droughts, increasing about 100% in the median range for drought characteristics. Thus, there is a need for proper adaptation and planning for water resources management in this region.     

Hydrological responses to climatic variability in a cold agricultural region

Extended severe dry and wet periods are frequently observed in the northern continental climate of the Canadian Prairies. Prairie streamflow is mainly driven by spring snowmelt of the winter snowpack, whilst summer rainfall is an important control on evapotranspiration and thus seasonality affects the hydrological response to drought and wet periods in complex ways. A field‐tested physically based model was used to investigate the influences of climatic variability on hydrological processes in this region. The model was set up to resolve agricultural fields and to include key cold regions processes. It was parameterized from local and regional measurements without calibration and run for the South Tobacco Creek basin in southern Manitoba, Canada. The model was tested against snow depth and streamflow observations at multiple scales and performed well enough to explore the impacts of wet and dry periods on hydrological processes governing the basin scale hydrological response. Four hydro‐climatic patterns with distinctive climatic seasonality and runoff responses were identified from differing combinations of wet/dry winter and summer seasons. Water balance analyses of these patterns identified substantive multiyear subsurface soil moisture storage depletion during drought (2001–2005) and recharge during a subsequent wet period (2009–2011). The fractional percentage of heavy rainfall days was a useful metric to explain the contrasting runoff volumes between dry and wet summers. Finally, a comparison of modeling approaches highlights the importance of antecedent fall soil moisture, ice lens formation during the snowmelt period, and peak snow water equivalent in simulating snowmelt runoff.