Comparative evaluation of precipitation-temperature based drought indices (DIs): A case study of Moroccan Lower Sebou basin

Due to the lack of studies on drought in the Lower Sebou basin (LSB), the complexity of drought event and the difference in climate conditions. The identification of the most appropriate drought indices (DIs) to assess drought conditions has become a priority. Therefore, assessing the performance of different drought indices was considered in order to identify the universal drought indices that are well adapted to the LSB. Based on data availability, five DIs were used: Standardized Precipitation Index (SPI), Standardized Precipitation and Evapotranspiration Index (SPEI), Reconnaissance Drought Index (RDI), self-calibrated Palmer Drought Severity Index (sc-PDSI) and Streamflow Drought Index (SDI). The DIs were calculated on an annual scale using monthly time series of precipitation, temperature and river flow from 1984-2016. Thornthwaite's method was used to calculate potential evapotranspiration (PET). Pearson's correlation (r) were analyzed. Furthermore, five decision criteria namely robustness, traceability, transparency, sophistication and scalability were used to evaluate the performance of these indices. The results proved the fact that SPI is suitable to detect the drought duration and intensity compared to other indices with high correlation coefficients especially in sub humid regions, knowing that it tends to give more results that are humid in stations with semi-arid climates. SPI, SPEI and RDI follow the same trend during the period studied. However, sc-PDSI appears to be the most sensitive to temperature and precipitation by overestimating the drought conditions. Eventually, the results of the performance evaluation criteria revealed that SPEI classified first (total score = 137) among other meteorological drought indices, followed by SPI, RDI and sc-PDSI.

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Dynamical delimitation of the Central American Dry Corridor (CADC) using drought indices and aridity values

Progress in Physical Geography Earth and Environment ◽

10.1177/0309133319860224 ◽

2019 ◽

Vol 43 (5) ◽

pp. 627-642 ◽

Cited By ~ 4

Author(s):

Luis Eduardo Quesada-Hernández ◽

Oscar David Calvo-Solano ◽

Hugo G Hidalgo ◽

Paula M Pérez-Briceño ◽

Eric J Alfaro

Keyword(s):

Drought Index ◽

Pacific Coast ◽

Potential Evapotranspiration ◽

Standardized Precipitation Index ◽

Severity Index ◽

Rainfall Anomaly ◽

Central American ◽

Drought Indices ◽

Drought Severity ◽

Southern Mexico

The Central American Dry Corridor (CADC) is a sub-region in the isthmus that is relatively drier than the rest of the territory. Traditional delineations of the CADC’s boundaries start at the Pacific coast of southern Mexico, stretching south through Central America’s Pacific coast down to northwestern Costa Rica (Guanacaste province). Using drought indices (Standardized Precipitation Index, Modified Rainfall Anomaly Index, Palmer Drought Severity Index, Palmer Hydrological Drought Index, Palmer Drought Z-Index and the Reconnaissance Drought Index) along with a definition of aridity as the ratio of potential evapotranspiration (representing demand of water from the atmosphere) over precipitation (representing the supply of water), we proposed a CADC delineation that changes for normal, dry and wet years. The identification of areas that change their classification during extremely dry conditions is important because these areas may indicate the location of future expansion of aridity associated with climate change. In the same way, the delineation of the CADC during wet extremes allows the identification of locations that remain part of the CADC even during the wettest years and that may require special attention from the authorities.

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Drought Monitoring Using Rainfall, Evapotranspiration and Streamflow Data: A Case Study of Kaduna River Catchment Area (Nigeria)

Journal of Scientific Research and Reports ◽

10.9734/jsrr/2020/v26i830303 ◽

2020 ◽

pp. 133-144

Author(s):

A. Dare ◽

E. J. Zakka ◽

Maikano Samson ◽

A. O. Afolabi ◽

S. O. Okechalu ◽

...

Keyword(s):

Catchment Area ◽

Drought Index ◽

Meteorological Data ◽

Standardized Precipitation Index ◽

Hydrological Drought ◽

Crop Damage ◽

Drought Monitoring ◽

Drought Indices ◽

Drought Severity ◽

Drought Conditions

Drought is defined as the lack of adequate precipitation, either rain or snow that causes reduced soil moisture or groundwater, diminished streamflow, crop damage and a general water shortage. The objective of this study focuses on meteorological and hydrological drought monitoring in river Kaduna catchment area. Standardized Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) drought indices were used to characterize meteorological drought while Streamflow Drought Index (SDI) was used for hydrological drought monitoring for a period of 34 years (1967 – 2001). DrinC software, a drought indices calculator, was used for the calculation of SPI, RDI, and SDI respectively. The drought severity classification based on meteorological and hydrological drought indices gave 33% and 37% drought conditions period with the year 1967 – 2001. Based on these indexes, the drought characteristics of the catchment area were investigated by analyzing meteorological data from 1967 to 2001. The results of this analysis show that more non-drought/normal conditions were predominant than drought conditions. During the period under study (34 years), only one-year return period of extreme drought condition.

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Drought monitoring incorporating precipitation and climate variables and its application for future drought projection

10.5194/egusphere-egu2020-13511 ◽

2020 ◽

Author(s):

Jeongeun Won ◽

Sangdan Kim

Keyword(s):

Drought Index ◽

Potential Evapotranspiration ◽

Standardized Precipitation Index ◽

Management Program ◽

Drought Monitoring ◽

Drought Indices ◽

Drought Severity ◽

Climate Variables ◽

Evaporative Demand ◽

Monitoring Method

In drought monitoring, it is very important to select climate variables to interpret drought. Most drought monitoring interprets drought as deficit in precipitation, so drought indices focused on the moisture supply side of the atmosphere have been mainly used. However, droughts can be caused not only by lack of rainfall, but also by various climate variables such as increase in temperature. In this regard, interest in potential evapotranspiration(PET), which is an moisture demand side of the atmosphere, is increasing and a PET-based drought index has been developed. However, complex droughts caused by various climate variables cannot be interpreted as a drought index that only considers precipitation or PET. In this study, we suggest a drought monitoring method that can reflect various future climate variables, including precipitation. In other words, copula-based joint drought index(CJDI), which incorporate standardized precipitation index(SPI) based on precipitation and evaporative demand drought index(EDDI) based on PET, is developed. CJDI, which considers both precipitation and PET, which are key variables related to drought, is able to properly monitor the drought events in Korea. In addition, future Drought severity &#8211; duration - frequency curves are derived to project future droughts compared to various drought indices. It is shown that CJDI can be used as a more reasonable drought index to establish the adaptation policy for future droughts by presenting the pattern of future droughts more realistically.Acknowledgment: This study was funded by the Korea Ministry of Environment (MOE) as Smart Urban Water Resources Management Program. (2019002950004)Keywords: Climate change; Copula; Drought; CJDI; Drought severity-duration-frequency curve

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A novel index for ecological drought monitoring based on ecological water deficit: a case study of Northwestern China

10.5194/egusphere-egu21-5439 ◽

2021 ◽

Author(s):

Tianliang Jiang ◽

Xiaoling Su

Keyword(s):

Water Deficit ◽

Time Scales ◽

Drought Index ◽

Vegetation Index ◽

Standardized Precipitation Index ◽

Northwestern China ◽

Drought Monitoring ◽

Drought Indices ◽

Drought Severity ◽

Different Time Scales

Although the concept of ecological drought was first defined by the Science for Nature and People Partnership (SNAPP) in 2016, there remains no widely accepted drought index for monitoring ecological drought. Therefore, this study constructed a new ecological drought monitoring index, the standardized ecological water deficit index (SEWDI). The SEWDI is based on the difference between ecological water requirements and consumption, referred to as the standardized precipitation index (SPI) method, which was used to monitor ecological drought in Northwestern China (NWRC). The performances of the SEWDI and four widely-used drought indices [standardized root soil moisture index (SSI), self-calibrated Palmer drought index (scPDSI), standardized precipitation-evaporation drought index (SPEI), and SPI) in monitoring ecological drought were evaluated through comparing the Pearson correlations between these indices and the standardized normalized difference vegetation index (SNDVI) under different time scales, wetness, and water use efficiencies (WUEs) of vegetation. Finally, the rotational empirical orthogonal function (REOF) was used to decompose the SEWDI at a 12-month scale in the NWRC during 1982&#8211;2015 to obtain five ecological drought regions. The characteristics of ecological drought in the NWRC, including intensity, duration, and frequency, were extracted using run theory. The results showed that the performance of the SEWDI in monitoring ecological drought was highest among the commonly-used drought indices evaluated under different time scales [average correlation coefficient values (r) between SNDVI and drought indices: SEWDI= 0.34, SSI= 0.24, scPDSI= 0.23, SPI= 0.20, SPEI= 0.18), and the 12-month-scale SEWDI was largely unaffected by wetness and WUE. In addition, the results of the monitoring indicated that serious ecological droughts in the NWRC mainly occurred in 1982&#8211;1986, 1990&#8211;1996, and 2005&#8211;2010, primarily in regions I, II, and V, regions II, and IV, and in region III, IV, and V, respectively. This study provides a robust approach for quantifying ecological drought severity across natural vegetation areas and scientific evidence for governmental decision makers.

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Elucidating Diverse Drought Characteristics from Two Meteorological Drought Indices (SPI and SPEI) in China

Journal of Hydrometeorology ◽

10.1175/jhm-d-19-0290.1 ◽

2020 ◽

Vol 21 (7) ◽

pp. 1513-1530 ◽

Cited By ~ 3

Author(s):

Lingcheng Li ◽

Dunxian She ◽

Hui Zheng ◽

Peirong Lin ◽

Zong-Liang Yang

Keyword(s):

Clustering Algorithm ◽

Potential Evapotranspiration ◽

Standardized Precipitation Index ◽

Three Dimensional ◽

Meteorological Drought ◽

Drought Indices ◽

Drought Severity ◽

Severe Drought ◽

Small Areas ◽

Drought Characteristics

AbstractThis study elucidates drought characteristics in China during 1980–2015 using two commonly used meteorological drought indices: standardized precipitation index (SPI) and standardized precipitation–evapotranspiration index (SPEI). The results show that SPEI characterizes an overall increase in drought severity, area, and frequency during 1998–2015 compared with those during 1980–97, mainly due to the increasing potential evapotranspiration. By contrast, SPI does not reveal this phenomenon since precipitation does not exhibit a significant change overall. We further identify individual drought events using the three-dimensional (i.e., longitude, latitude, and time) clustering algorithm and apply the severity–area–duration (SAD) method to examine the drought spatiotemporal dynamics. Compared to SPI, SPEI identifies a lower drought frequency but with larger total drought areas overall. Additionally, SPEI identifies a greater number of severe drought events but a smaller number of slight drought events than the SPI. Approximately 30% of SPI-detected drought grids are not identified as drought by SPEI, and 40% of SPEI-detected drought grids are not recognized as drought by SPI. Both indices can roughly capture the major drought events, but SPEI-detected drought events are overall more severe than SPI. From the SAD analysis, SPI tends to identify drought as more severe over small areas within 1 million km2 and short durations less than 2 months, whereas SPEI tends to delineate drought as more severe across expansive areas larger than 3 million km2 and periods longer than 3 months. Given the fact that potential evapotranspiration increases in a warming climate, this study suggests SPEI may be more suitable than SPI in monitoring droughts under climate change.

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Assessing Spatiotemporal Drought Dynamics and Its Related Environmental Issues in the Mekong River Delta

Remote Sensing ◽

10.3390/rs11232742 ◽

2019 ◽

Vol 11 (23) ◽

pp. 2742 ◽

Cited By ~ 3

Author(s):

Tran ◽

Myint ◽

Latorre-Carmona ◽

Ho ◽

...

Keyword(s):

Time Series ◽

Land Surface ◽

Drought Index ◽

Negative Impact ◽

Statistical Significance ◽

Standardized Precipitation Index ◽

Agricultural Drought ◽

Series Data ◽

Drought Indices ◽

Drought Severity

Drought is a major natural disaster that creates a negative impact on socio-economic development and environment. Drought indices are typically applied to characterize drought events in a meaningful way. This study aims at examining variations in agricultural drought severity based on the relationship between standardized ratio of actual and potential evapotranspiration (ET and PET), enhanced vegetation index (EVI), and land surface temperature (LST) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) platform. A new drought index, called the enhanced drought severity index (EDSI), was developed by applying spatiotemporal regression methods and time-series biophysical data derived from remote sensing. In addition, time-series trend analysis in the 2001–2018 period, along with the Mann–Kendal (MK) significance test and the Theil Sen (TS) slope, were used to examine the spatiotemporal dynamics of environmental parameters (i.e., LST, EVI, ET, and PET), and geographically weighted regression (GWR) was subsequently applied in order to analyze the local correlations among them. Results showed that a significant correlation was discovered among LST, EVI, ET, and PET, as well as their standardized ratios (|r| > 0.8, p < 0.01). Additionally, a high performance of the new developed drought index, showing a strong correlation between EDSI and meteorological drought indices (i.e., standardized precipitation index (SPI) or the reconnaissance drought index (RDI)), measured at meteorological stations, giving r > 0.7 and a statistical significance p < 0.01. Besides, it was found that the temporal tendency of this phenomenon was the increase in intensity of drought, and that coastal areas in the study area were more vulnerable to this phenomenon. This study demonstrates the effectiveness of EDSI and the potential application of integrating spatial regression and time-series data for assessing regional drought conditions.

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Tracking Interannual Streamflow Variability with Drought Indices in the U.S. Pacific Northwest

Journal of Hydrometeorology ◽

10.1175/jhm-d-13-0167.1 ◽

2014 ◽

Vol 15 (5) ◽

pp. 1900-1912 ◽

Cited By ~ 32

Author(s):

John T. Abatzoglou ◽

Renaud Barbero ◽

Jacob W. Wolf ◽

Zachary A. Holden

Keyword(s):

Pacific Northwest ◽

Potential Evapotranspiration ◽

Standardized Precipitation Index ◽

Severity Index ◽

The United States ◽

Drought Indices ◽

Drought Severity ◽

Climate Data ◽

Mountain Watersheds ◽

Streamflow Variability

Abstract Drought indices are often used for monitoring interannual variability in macroscale hydrology. However, the diversity of drought indices raises several issues: 1) which indices perform best and where; 2) does the incorporation of potential evapotranspiration (PET) in indices strengthen relationships, and how sensitive is the choice of PET methods to such results; 3) what additional value is added by using higher-spatial-resolution gridded climate layers; and 4) how have observed relationships changed through time. Standardized precipitation index, standardized precipitation evapotranspiration index (SPEI), Palmer drought severity index, and water balance runoff (WBR) model output were correlated to water-year runoff for 21 unregulated drainage basins in the Pacific Northwest of the United States. SPEI and WBR with time scales encompassing the primary precipitation season maximized the explained variance in water-year runoff in most basins. Slightly stronger correlations were found using PET estimates from the Penman–Monteith method over the Thornthwaite method, particularly for time periods that incorporated the spring and summer months in basins that receive appreciable precipitation during the growing season. Indices computed using high-resolution climate surfaces explained over 10% more variability than metrics derived from coarser-resolution datasets. Increased correlation in the latter half of the study period was partially attributable to increased streamflow variability in recent decades as well as to improved climate data quality across the interior mountain watersheds.

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Forecasting the Future Drought Indices Due to the Effects of Climate Change in Al Najaf City, Iraq.

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/961/1/012040 ◽

2022 ◽

Vol 961 (1) ◽

pp. 012040

Author(s):

H H Mahdi ◽

T A Musa ◽

Z A A Al-Rammahi ◽

E J Mahmood

Keyword(s):

Drought Index ◽

Potential Evapotranspiration ◽

Standardized Precipitation Index ◽

Essential Element ◽

Environmental Data ◽

Exceedance Probability ◽

Drought Indices ◽

Monthly Precipitation ◽

Time Period ◽

The Future

Abstract Drought is a natural disaster associated with a shortage of water availability for specified region within a specific time period. The impacts of drought are significant and extend to damage many important life aspects such as environmental, economic, and social activities. The forecasting of the drought events is an essential element for planning this disaster, reducing its effectiveness and response. The three characteristic frequency, intensity, and time period are the key parts for forecasting and assessment of droughts. Here, two drought indices (The Reconnaissance Drought Index (RDI), standardized precipitation index (SPI)) were used for forecasting of the future drought within Al Najaf city, Iraq. Thirty years meteorological data (average monthly precipitation and temperature) were used for the period (2021–2050) downloaded from the site of the Centre for Environmental Data Analysis (CEDA) for five grid points to cover overall study area. The computation of these indices conducted at a 12-month time scale and included the calculation of potential evapotranspiration by Thorthwaite method. The temporal drought intensity as well as drought frequency configurations were calculated and analyzed for each drought index. The results showed that the general average drought level expected will mildly dry while the maximum drought level expected will extremely dry. The more severe seasons of drought were forecasted in the years 2038, 2034 and 2021, respectively. Also, the prevailing event will be a one year drought and the maximum drought interval occurred within the study period will four consecutive years, with a 3.33% exceedance probability.

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Revisiting drought trend over China during 1948-2016: a multivariate perspective

10.5194/egusphere-egu2020-4555 ◽

2020 ◽

Author(s):

Liliang Ren

Keyword(s):

Drought Index ◽

Potential Evapotranspiration ◽

Severity Index ◽

Northeastern China ◽

Trend Detection ◽

Drought Indices ◽

Drought Severity ◽

Main Driver ◽

Land Data Assimilation System ◽

The Individual

How drought changes in the context of global warming is a concerning issue that influences the strategies of drought mitigation and drought management. Based on the simulations of the version 2 of Global Land Data Assimilation System (GLDAS-2.0) during 1948-2016, we revisited the drought trend over China and analyzed the individual contributions of precipitation and potential evapotranspiration (PET) on varied drought patterns. Four composite drought indices including the Aggregate Drought Index (ADI), Joint Drought Deficit Index (JDI), self-calibrating Palmer Drought Severity Index (scPDSI) and Standardized Palmer Drought Index (SPDI) were employed for trend detection. Results showed that all four composite drought indices suggested a significant drying belt spreads from northeastern China to southwestern China, and a significant wetting trend in the &#8220;Three river sources&#8221; areas. Controversial patterns were mainly located in the northwestern China, Xinjiang districts, and the middle and lower reaches of the Yangtze River, where the SPDI and JDI respectively, overestimated and underestimated the moisture conditions at varying degrees. According to the change point tests, it is found that the drying pattern in the northeastern China occurred since 1970s, where precipitation deficits and expanded PET jointly aggravated the drying process, while for the &#8220;Three river sources&#8221; areas, the increased precipitation since 2000s is the main driver for the wetting pattern.

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Mediterranean-Scale Drought: Regional Datasets for Exceptional Meteorological Drought Events during 1975–2019

Atmosphere ◽

10.3390/atmos12080941 ◽

2021 ◽

Vol 12 (8) ◽

pp. 941

Author(s):

Shifa Mathbout ◽

Joan Albert Lopez-Bustins ◽

Dominic Royé ◽

Javier Martin-Vide

Keyword(s):

Drought Index ◽

Standardized Precipitation Index ◽

Principal Component ◽

Meteorological Drought ◽

Western Mediterranean ◽

Drought Indices ◽

Drought Event ◽

Evaporative Demand ◽

Atmospheric Circulation Patterns ◽

Dry Conditions

Drought is one of the most complex climate-related phenomena and is expected to progressively affect our lives by causing very serious environmental and socioeconomic damage by the end of the 21st century. In this study, we have extracted a dataset of exceptional meteorological drought events between 1975 and 2019 at the country and subregional scales. Each drought event was described by its start and end date, intensity, severity, duration, areal extent, peak month and peak area. To define such drought events and their characteristics, separate analyses based on three drought indices were performed at 12-month timescale: the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI), and the Reconnaissance Drought Index (RDI). A multivariate combined drought index (DXI) was developed by merging the previous three indices for more understanding of droughts’ features at the country and subregional levels. Principal component analysis (PCA) was used to identify five different drought subregions based on DXI-12 values for 312 Mediterranean stations and a new special score was defined to classify the multi-subregional exceptional drought events across the Mediterranean Basin (MED). The results indicated that extensive drought events occurred more frequently since the late 1990s, showing several drought hotspots in the last decades in the southeastern Mediterranean and northwest Africa. In addition, the results showed that the most severe events were more detected when more than single drought index was used. The highest percentage area under drought was also observed through combining the variations of three drought indices. Furthermore, the drought area in both dry and humid areas in the MED has also experienced a remarkable increase since the late 1990s. Based on a comparison of the drought events during the two periods—1975–1996 and 1997–2019—we find that the current dry conditions in the MED are more severe, intense, and frequent than the earlier period; moreover, the strongest dry conditions occurred in last two decades. The SPEI-12 and RDI-12 have a higher capacity in providing a more comprehensive description of the dry conditions because of the inclusion of temperature or atmospheric evaporative demand in their scheme. A complex range of atmospheric circulation patterns, particularly the Western Mediterranean Oscillation (WeMO) and East Atlantic/West Russia (EATL/WRUS), appear to play an important role in severe, intense and region-wide droughts, including the two most severe droughts, 1999–2001 and 2007–2012, with lesser influence of the NAO, ULMO and SCAND.

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