Drought indices: aggregation is necessary or it is only the researcher's choice

Abstract Drought is a natural phenomenon caused by extreme and persistent precipitation shortage. This shortfall causes impacts on hydrology, agriculture, and the economy of a country. Secondly, drought/dryness has certain unique characteristics (severity, duration) among the natural hazards which makes it difficult to classify the persistent and subjective network of impacts. Drought classification is important to manage drought, allowing both quantitative evaluation and potential risk assessment planning. The simpler approach of drought indices made it easier for various researchers and organizations to classify drought. Several drought indices have been proposed at the national and global level to characterize hydrological, meteorological and agricultural droughts. Until now, there has been no widely agreed drought index among researchers. Therefore, researchers are trying to modify and reconstruct a simple, complete, and robust drought index for effective use and planning of the management of water resources. Due to the complex terrestrial ecosystem, researchers used to integrate multiple drought indexes for evaluation and monitoring of regional drought conditions. The reviewed composite or aggregated indices revealed that the researchers are mainly focused on regional climatic and environmental conditions, and differences of theoretical backgrounds while integrating a drought index. There is a lack of performance evaluation of these indices because usually the comparative analysis between the integrated index and earlier developed composite indices is not performed. Secondly, the developer researchers did not mention limitations such as data, which is considered a paramount issue while applying these indices in other regions. Therefore, there is still comprehensive work needed for the simple integration of drought indexes for general applications.

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Projection of Future Drought Characteristics under Multiple Drought Indices

Water ◽

10.3390/w13091238 ◽

2021 ◽

Vol 13 (9) ◽

pp. 1238

Author(s):

Muhammad Imran Khan ◽

Xingye Zhu ◽

Xiaoping Jiang ◽

Qaisar Saddique ◽

Muhammad Saifullah ◽

...

Keyword(s):

Series Data ◽

Natural Phenomenon ◽

Drought Indices ◽

Drought Severity ◽

Severe Drought ◽

Drought Analysis ◽

Songhua River ◽

Drought Intensity ◽

Drought Characteristics ◽

Rcp 8.5

Drought is a natural phenomenon caused by the variability of climate. This study was conducted in the Songhua River Basin of China. The drought events were estimated by using the Reconnaissance Drought Index (RDI) and Standardized Precipitation Index (SPI) which are based on precipitation (P) and potential evapotranspiration (PET) data. Furthermore, drought characteristics were identified for the assessment of drought trends in the study area. Short term (3 months) and long term (12 months) projected meteorological droughts were identified by using these drought indices. Future climate precipitation and temperature time series data (2021–2099) of various Representative Concentration Pathways (RCPs) were estimated by using outputs of the Global Circulation Model downscaled with a statistical methodology. The results showed that RCP 4.5 have a greater number of moderate drought events as compared to RCP 2.6 and RCP 8.5. Moreover, it was also noted that RCP 8.5 (40 events) and RCP 4.5 (38 events) showed a higher number of severe droughts on 12-month drought analysis in the study area. A severe drought conditions projected between 2073 and 2076 with drought severity (DS-1.66) and drought intensity (DI-0.42) while extreme drying trends were projected between 2097 and 2099 with drought severity (DS-1.85) and drought intensity (DI-0.62). It was also observed that Precipitation Decile predicted a greater number of years under deficit conditions under RCP 2.6. Overall results revealed that more severe droughts are expected to occur during the late phase (2050–2099) by using RDI and SPI. A comparative analysis of 3- and 12-month drying trends showed that RDI is prevailing during the 12-month drought analysis while almost both drought indices (RDI and SPI) indicated same behavior of drought identification at 3-month drought analysis between 2021 and 2099 in the research area. The results of study will help to evaluate the risk of future drought in the study area and be beneficial for the researcher to make an appropriate mitigation strategy.

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Evaluation of Drought Indices Based on Thermal Remote Sensing of Evapotranspiration over the Continental United States

Journal of Climate ◽

10.1175/2010jcli3812.1 ◽

2011 ◽

Vol 24 (8) ◽

pp. 2025-2044 ◽

Cited By ~ 249

Author(s):

Martha C. Anderson ◽

Christopher Hain ◽

Brian Wardlow ◽

Agustin Pimstein ◽

John R. Mecikalski ◽

...

Keyword(s):

Remote Sensing ◽

Land Surface ◽

Drought Index ◽

Temporal Correlation ◽

Meteorological Drought ◽

Rainfall Data ◽

Added Value ◽

Stress Index ◽

Drought Indices ◽

Shallow Water Table

Abstract The reliability of standard meteorological drought indices based on measurements of precipitation is limited by the spatial distribution and quality of currently available rainfall data. Furthermore, they reflect only one component of the surface hydrologic cycle, and they cannot readily capture nonprecipitation-based moisture inputs to the land surface system (e.g., irrigation) that may temper drought impacts or variable rates of water consumption across a landscape. This study assesses the value of a new drought index based on remote sensing of evapotranspiration (ET). The evaporative stress index (ESI) quantifies anomalies in the ratio of actual to potential ET (PET), mapped using thermal band imagery from geostationary satellites. The study investigates the behavior and response time scales of the ESI through a retrospective comparison with the standardized precipitation indices and Palmer drought index suite, and with drought classifications recorded in the U.S. Drought Monitor for the 2000–09 growing seasons. Spatial and temporal correlation analyses suggest that the ESI performs similarly to short-term (up to 6 months) precipitation-based indices but can be produced at higher spatial resolution and without requiring any precipitation data. Unique behavior is observed in the ESI in regions where the evaporative flux is enhanced by moisture sources decoupled from local rainfall: for example, in areas of intense irrigation or shallow water table. Normalization by PET serves to isolate the ET signal component responding to soil moisture variability from variations due to the radiation load. This study suggests that the ESI is a useful complement to the current suite of drought indicators, with particular added value in parts of the world where rainfall data are sparse or unreliable.

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Effects of different reference periods on drought index (SPEI) estimations from 1901 to 2014

Hydrology and Earth System Sciences ◽

10.5194/hess-21-4989-2017 ◽

2017 ◽

Vol 21 (10) ◽

pp. 4989-5007 ◽

Cited By ~ 11

Author(s):

Myoung-Jin Um ◽

Yeonjoo Kim ◽

Daeryong Park ◽

Jeongbin Kim

Keyword(s):

West Africa ◽

East Asia ◽

The United States ◽

Spatial Extent ◽

Drought Indices ◽

Drought Severity ◽

Climate Change Scenarios ◽

Reference Period ◽

Drought Characteristics ◽

Regional Drought

Abstract. This study aims to understand how different reference periods (i.e., calibration periods) of climate data used to estimate drought indices influence regional drought assessments. Specifically, we investigate the influences of different reference periods on historical drought characteristics, such as the trend, frequency, intensity and spatial extent, using the standardized precipitation evapotranspiration index (SPEI) with a 12-month lag (SPEI-12), which was estimated from the datasets of the Climate Research Unit (CRU) and the University of Delaware (UDEL). For the 1901–1957 (P1) and 1958–2014 (P2) estimation periods, three different types of reference periods are used to compute the SPEI: P1 and P2 together, P1 and P2 separately and P1 only. Focusing on East Asia, Europe, the United States and West Africa, we find that the influence of the reference period is significant in East Asia and West Africa, with dominant drying trends from P1 to P2. The reference period influenced the assessment of drought characteristics, particularly the severity and spatial extent, whereas the influence on the frequency was relatively small. Finally, self-calibration, which is the most common practice for indices such as the SPEI, tends to underestimate the drought severity and spatial extent relative to the other approaches used in this study. Although the conclusions drawn in this study are limited by the use of two global datasets, they highlight the need for clarification of the reference period in drought assessments to better understand regional drought characteristics and the associated temporal changes, particularly under climate change scenarios.

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On The Reduction of Inaccuracies in Drought Monitoring - A Novel Blended Procedure for Standardized Type Drought Indicators

10.21203/rs.3.rs-115294/v1 ◽

2020 ◽

Author(s):

Muhammad Khan ◽

He Jiang ◽

Zulfiqar Ali ◽

Amna Nazeer ◽

Guangheng Ni ◽

...

Keyword(s):

Water Management ◽

Drought Index ◽

Drought Monitoring ◽

Drought Indices ◽

Management Research ◽

Climatic Zones ◽

Data Mining Approach ◽

Gauge Station ◽

Pros And Cons ◽

Increasing Temperature

Abstract Due to climate change and an increasing temperature, drought is prevailing in several parts of the globe. Therefore, drought monitoring is a challenging task in hydrology and water management research. Drought is occurring recurrently in various climatic zones around the world. In literature, in that respect, there are several drought monitoring indicators. Regardless of their pros and cons, their abounded creates a chaotic scenario in analysis and reanalysis in certain gauge station. This research aims to improve drought monitoring system by providing a comprehensive data mining approach under principle component analysis. Consequently, we propose a new index named: Seasonal Mixture Standardized Drought Index (SMSDI). In our preliminary analysis, we have included three multiscaler Standardized Drought Indices (SDIs). In application, we have applied our proposed indicator on three meteorological gauge stations located in Pakistan. For comparative assessment, individual SDI has used to investigate the association and consistency with SMSDI. Results presented in the current study demonstrated that the SMSDI has significant correlation with individual SDIs. Hence, we conclude that the procedure of SMSDI can be deployed in hydrology and water management research for extracting reliable information related to future drought.

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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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Development of a Next Generation Drought Index: combining multiple global and local data sources to enable detection of sector-specific drought impacts

10.5194/egusphere-egu21-10886 ◽

2021 ◽

Author(s):

Dimmie Hendriks ◽

Pieter Hazenberg ◽

Jonas Gotte ◽

Patricia Trambauer ◽

Arjen Haag ◽

...

Keyword(s):

Drought Index ◽

Agricultural Drought ◽

Data Sources ◽

Drought Indices ◽

Next Generation ◽

Hazard Indices ◽

Local Data ◽

Drought Impacts ◽

Drought Hazard ◽

Impact Data

An increasing number of regions and countries are confronted with droughts as well as an increase in water demand. Inevitably, this leads to an increasing pressure on the available water resources and associated risks and economic impact for the water dependent sectors. In order to prevent big drought impacts, such as agricultural damage and food insecurity, timely and focused drought mitigation measures need to be carried out. To enable this, the detection of drought and its sector-specific risks at early stages needs to be improved. One of the main challenges is to develop compound and impact-oriented drought indices, that make optimal use of innovative techniques, satellite products, local data and other big data sets.Here, we present the development of a Next Generation Drought Index (NGDI) that combines multiple freely available global data sources (eg. ERA5, MODIS, PCR-GLOBWB) to calculate a range of relevant drought hazard indices related to meteorological, hydrological, soil moisture and agricultural drought (eg. SPI, SPEI, SRI, SGI, VCI). The drought hazard indices are aggregated at district level, while considering the percentage area exposure of the drought impacted sector (exposure). In addition, the indices are enriched with local and national scale drought impact information (eg. online news items, social media data, EM-DAT database, GDO Drought news, national drought reports). Results are presented at sub-national scales in interactive spatial and temporal views, showing the combined drought indices and impact data.The NGDI approach is being tested for the agricultural sector in Mali, a country with a vulnerable population and economy that faces frequent dry spells which heavily impact the functioning of the important agricultural activities that sustain a large part of the population. The computed drought indices are compared with local drought data and an analysis is made of the cross-correlations between the indices within the NGDI and collected impact data.We aim at providing the NGDI information to a broad audience as well as co-creation of further NGDI developments. Hence, we would like to reach out to interested parties and identify collaboration opportunities.

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A Comparative Study on Regional Drought Characterization Using Estimated Drought Indices in Conjunction with Trend Analysis in Peninsular India

Water Resources in Arid Lands: Management and Sustainability - Advances in Science, Technology & Innovation ◽

10.1007/978-3-030-67028-3_8 ◽

2021 ◽

pp. 91-110

Author(s):

M. P. Akhtar ◽

L. B. Roy ◽

Abhishek Sinha

Keyword(s):

Comparative Study ◽

Trend Analysis ◽

Drought Indices ◽

Peninsular India ◽

Regional Drought

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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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Using integrated meteorological and hydrological indices to assess drought characteristics in southern Taiwan

Hydrology Research ◽

10.2166/nh.2019.120 ◽

2019 ◽

Vol 50 (3) ◽

pp. 901-914 ◽

Cited By ~ 3

Author(s):

Hsin-Fu Yeh

Keyword(s):

River Basin ◽

Drought Index ◽

Standardized Precipitation Index ◽

Assessment Method ◽

Drought Indices ◽

Trend Test ◽

Integrated Analysis ◽

Drought Assessment ◽

Southern Taiwan ◽

The Standardized Precipitation Index

Abstract Numerous drought index assessment methods have been developed to investigate droughts. This study proposes a more comprehensive assessment method integrating two drought indices. The Standardized Precipitation Index (SPI) and the Streamflow Drought Index (SDI) are employed to establish an integrated drought assessment method to study the trends and characteristics of droughts in southern Taiwan. The overall SPI and SDI values and the spatial and temporal distributions of droughts within a given year (November to October) revealed consistent general trends. Major droughts occurred in the periods of 1979–1980, 1992–1993, 1994–1995, and 2001–2003. According to the results of the Mann–Kendall trend test and the Theil–Sen estimator analysis, the streamflow data from the Sandimen gauging station in the Ailiao River Basin showed a 30% decrease, suggesting increasing aridity between 1964 and 2003. Hence, in terms of water resources management, special attention should be given to the Ailiao River Basin. The integrated analysis showed different types of droughts occurring in different seasons, and the results are in good agreement with the climatic characteristics of southern Taiwan. This study suggests that droughts cannot be explained fully by the application of a single drought index. Integrated analysis using multiple indices is required.

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