Special Issue "Drought Monitoring and Prediction"

A special issue of Geosciences (ISSN 2076-3263). This special issue belongs to the section "Natural Hazards".

Deadline for manuscript submissions: closed (15 December 2017)

Special Issue Editor

Guest Editor
Dr. Tsegaye Tadesse

Associate Professor, National Drought Mitigation Center (NDMC), School of Natural Resources, University of Nebraska-Lincoln, USA
Website | E-Mail
Phone: (402) 472 3383
Interests: application of remote sensing on drought monitoring and prediction; drought indices; satellite data; climate data; drought resilience; early warning system; food security

Special Issue Information

Dear Colleagues,

Drought is a complex natural hazard that is global in nature and has cross-cutting impacts on many aspects of livelihoods and sectors of society (e.g., agriculture, energy, food security, health, water resources, migration, and resource conflict). Drought impacts are more complex today, as more economic sectors are affected, creating more conflicts between water users (i.e., societal vulnerability is dramatically different and changing).

The recurrent droughts in several parts of the world that are exacerbated by climate change necessitate the need for more effective drought planning and the development and implementation of appropriate mitigation strategies. Enhancing drought monitoring and early warning capacities is essential to drought risk management. For improved and efficient drought monitoring and early warning systems, decision makers and scientists should work together. This will promote the development of systems that are timely, relevant, understandable, affordable, and people-centered. In order to achieve this goal, it is essential to develop the appropriate social and technological capacity to research and implement programs to better understand, monitor, and communicate drought occurrences and their impacts. This includes fostering the ability of national governments and other planning entities to support the development and sustainability of the required infrastructure and scientific, technological, and institutional capacities needed to research, observe, analyze, map, and predict drought vulnerabilities and impacts.

Reliable drought monitoring and prediction play an important role in coping with drought, which requires integrated drought monitoring, prediction and risk assessment in order to track the drought status, provide prediction information, and assess the risk associated with drought impacts. Several researchers are working to provide an improved drought monitoring and prediction tools that could help in reducing the impacts and mitigate the drought vulnerability.

This Special Issue of Geosciences discusses recent advances in drought monitoring and prediction, presenting case studies conducted all over the world. Among the topics to be discussed are:

  • New and improved drought indices that could help in identifying, classifying, and communicating drought conditions
  • Combined drought indices based on various indicators
  • Remote sensing and GIS applications to drought monitoring and prediction
  • Seasonal forecast models for drought prediction
  • Impact of climate change and variability with a particular emphasis on drought
  • Climate projection models for drought risk management and drought mitigation
  • Earth observations that include satellite and climate data for efficient drought analysis
  • Drought monitoring that includes multiple socio-economic and environmental variables
  • Early warning systems and drought risk management
  • Drought vulnerability, resilience, and food security

Original research on these topics will be welcome for this Special Issue.

Dr. Tsegaye Tadesse
Guest Editor

Manuscript Submission Information

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Keywords

  • Drought monitoring
  • Drought prediction
  • Early warning system
  • Drought indices
  • Seasonal forecast
  • Climate projection
  • Hydro-climate extremes
  • Drought analysis
  • Satellite data
  • Climate data
  • Food security

Published Papers (9 papers)

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Research

Open AccessArticle
Downscaling Africa’s Drought Forecasts through Integration of Indigenous and Scientific Drought Forecasts Using Fuzzy Cognitive Maps
Geosciences 2018, 8(4), 135; https://doi.org/10.3390/geosciences8040135
Received: 25 November 2017 / Revised: 25 March 2018 / Accepted: 9 April 2018 / Published: 16 April 2018
Cited by 1 | PDF Full-text (30172 KB) | HTML Full-text | XML Full-text
Abstract
In the wake of increased drought occurrences being witnessed in Sub-Saharan Africa, more localized and contextualized drought mitigation strategies are on the agendas of many researchers and policy makers in the region. The integration of indigenous knowledge on droughts with seasonal climate forecasts [...] Read more.
In the wake of increased drought occurrences being witnessed in Sub-Saharan Africa, more localized and contextualized drought mitigation strategies are on the agendas of many researchers and policy makers in the region. The integration of indigenous knowledge on droughts with seasonal climate forecasts is one such strategy. The main challenge facing this integration, however, is the formal representation of highly-structured and holistic indigenous knowledge. In this paper, we demonstrate how the use of fuzzy cognitive mapping can address this challenge. Indigenous knowledge on droughts from five communities was modeled and represented using fuzzy cognitive maps. Maps from one of these case communities were then used in the implementation of the integration framework, called ĩtiki. Full article
(This article belongs to the Special Issue Drought Monitoring and Prediction)
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Open AccessArticle
Estimating Regional Scale Hydroclimatic Risk Conditions from the Soil Moisture Active-Passive (SMAP) Satellite
Geosciences 2018, 8(4), 127; https://doi.org/10.3390/geosciences8040127
Received: 5 February 2018 / Revised: 20 March 2018 / Accepted: 3 April 2018 / Published: 7 April 2018
Cited by 1 | PDF Full-text (16679 KB) | HTML Full-text | XML Full-text
Abstract
Satellite soil moisture is a critical variable for identifying susceptibility to hydroclimatic risks such as drought, dryness, and excess moisture. Satellite soil moisture data from the Soil Moisture Active/Passive (SMAP) mission was used to evaluate the sensitivity to hydroclimatic risk events in Canada. [...] Read more.
Satellite soil moisture is a critical variable for identifying susceptibility to hydroclimatic risks such as drought, dryness, and excess moisture. Satellite soil moisture data from the Soil Moisture Active/Passive (SMAP) mission was used to evaluate the sensitivity to hydroclimatic risk events in Canada. The SMAP soil moisture data sets in general capture relative moisture trends with the best estimates from the passive-only derived soil moisture and little difference between the data at different spatial resolutions. In general, SMAP data sets overestimated the magnitude of moisture at the wet extremes of wetting events. A soil moisture difference from average (SMDA) was calculated from SMAP and historical Soil Moisture and Ocean Salinity (SMOS) data showed a relatively good delineation of hydroclimatic risk events, although caution must be taken due to the large variability in the data within risk categories. Satellite soil moisture data sets are more sensitive to short term water shortages than longer term water deficits. This was not improved by adding “memory” to satellite soil moisture indices to improve the sensitivity of the data to drought, and there is a large variability in satellite soil moisture values with the same drought severity rating. Full article
(This article belongs to the Special Issue Drought Monitoring and Prediction)
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Open AccessArticle
Drought Prediction System for Central Europe and Its Validation
Geosciences 2018, 8(4), 104; https://doi.org/10.3390/geosciences8040104
Received: 16 January 2018 / Revised: 15 February 2018 / Accepted: 15 March 2018 / Published: 21 March 2018
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Abstract
In recent years, two drought monitoring systems have been developed in the Czech Republic based on the SoilClim and AVISO soil moisture models. The former is run by Mendel University and Global Change Research Institute (CAS), while the latter, by the Czech Hydrometeorological [...] Read more.
In recent years, two drought monitoring systems have been developed in the Czech Republic based on the SoilClim and AVISO soil moisture models. The former is run by Mendel University and Global Change Research Institute (CAS), while the latter, by the Czech Hydrometeorological Institute. SoilClim is based more on real soil properties and aimed primarily at agriculture, while AVISO complements the system with more theoretical presumptions about soil, showing, rather, climatological potential. Both soil moisture models were complemented by forecasts on a daily basis, taking meteorological inputs from NWP (Numerical Weather Prediction) models and thus giving short- to mid-range outlooks up to 9 days ahead. Validation of the soil moisture and drought intensity prediction was performed and is presented in this article showing its prediction reliability and potential. In the analysis, we focus mainly on the past year, 2017. The tool has strong predictive power for soil moisture and drought intensity so it is suitable for farmers who need to make decisions about irrigation and production activities. The presented system is fully functional and can be applied in the coming years. Full article
(This article belongs to the Special Issue Drought Monitoring and Prediction)
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Open AccessArticle
Comparison of the Performance of Six Drought Indices in Characterizing Historical Drought for the Upper Blue Nile Basin, Ethiopia
Geosciences 2018, 8(3), 81; https://doi.org/10.3390/geosciences8030081
Received: 17 October 2017 / Revised: 22 February 2018 / Accepted: 22 February 2018 / Published: 27 February 2018
Cited by 8 | PDF Full-text (5265 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The Upper Blue Nile (UBN) basin is less-explored in terms of drought studies as compared to other parts of Ethiopia and lacks a basin-specific drought monitoring system. This study compares six drought indices: Standardized Precipitation Index (SPI), Standardized Precipitation Evaporation Index (SPEI), Evapotranspiration [...] Read more.
The Upper Blue Nile (UBN) basin is less-explored in terms of drought studies as compared to other parts of Ethiopia and lacks a basin-specific drought monitoring system. This study compares six drought indices: Standardized Precipitation Index (SPI), Standardized Precipitation Evaporation Index (SPEI), Evapotranspiration Deficit Index (ETDI), Soil Moisture Deficit Index (SMDI), Aggregate Drought Index (ADI), and Standardized Runoff-discharge Index (SRI), and evaluates their performance with respect to identifying historic drought events in the UBN basin. The indices were calculated using monthly time series of observed precipitation, average temperature, river discharge, and modeled evapotranspiration and soil moisture from 1970 to 2010. The Pearson’s correlation coefficients between the six drought indices were analyzed. SPI and SPEI at 3-month aggregate period showed high correlation with ETDI and SMDI (r > 0.62), while SPI and SPEI at 12-month aggregate period correlate better with SRI. The performance of the six drought indices in identifying historic droughts: 1973–1974, 1983–1984, 1994–1995, and 2003–2004 was analyzed using data obtained from Emergency Events Database (EM-DAT) and previous studies. When drought onset dates indicated by the six drought indices are compared with that in the EM-DAT. SPI, and SPEI showed early onsets of drought events, except 2003–2004 drought for which the onset date was unavailable in EM-DAT. Similarly, ETDI, SMDI and SRI-3 showed early onset for two drought events and late onsets in one-drought event. In contrast, ADI showed late onsets for two drought events and early onset for one drought event. None of the six drought indices could individually identify the onsets of all the selected historic drought events; however, they may identify the onsets when combined by considering several input variables at different aggregate periods. Full article
(This article belongs to the Special Issue Drought Monitoring and Prediction)
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Open AccessArticle
ENSO Index-Based Insurance for Agricultural Protection in Southern Peru
Geosciences 2018, 8(2), 64; https://doi.org/10.3390/geosciences8020064
Received: 15 December 2017 / Revised: 30 January 2018 / Accepted: 6 February 2018 / Published: 9 February 2018
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Abstract
Agricultural operations in southern Peru are particularly vulnerable to climate variability due to water resource scarcity. In general, the response to drier than normal conditions in this region is reactive and fairly limited due to challenges associated with climate forecasting and administrative capacity [...] Read more.
Agricultural operations in southern Peru are particularly vulnerable to climate variability due to water resource scarcity. In general, the response to drier than normal conditions in this region is reactive and fairly limited due to challenges associated with climate forecasting and administrative capacity to distribute resources. To shift this paradigm, we investigate the potential for an El Niño–Southern Oscillation index-based insurance product. The article presents a demonstration of methodology and application for one specific crop in a department of southern Peru. The purpose of this product is to streamline the ability of decision makers to provide financial relief to affected farmers during, and perhaps before, drought; extending the lead-time of the index that is used to trigger product payouts produces results of similar skill to a product trained on concurrent conditions. Issues explored in this work include basis risk, initial endowment requirements, product longevity, and the potential crossover from index-based insurance to forecast-based financing. The ability of such products to mitigate losses during and after drought may be advantageous in Peru and other regions with notable interannual climate variability. Full article
(This article belongs to the Special Issue Drought Monitoring and Prediction)
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Open AccessArticle
Apprehensive Drought Characteristics over Iraq: Results of a Multidecadal Spatiotemporal Assessment
Geosciences 2018, 8(2), 58; https://doi.org/10.3390/geosciences8020058
Received: 15 December 2017 / Revised: 31 January 2018 / Accepted: 2 February 2018 / Published: 7 February 2018
Cited by 5 | PDF Full-text (4266 KB) | HTML Full-text | XML Full-text
Abstract
Drought is an extreme climate phenomenon that happens slowly and periodically threatens the environmental and socio-economic sectors. Iraq is one of the countries in the Middle East that has been dealing with serious drought-related issues in the 21st century. Here, we investigate meteorological [...] Read more.
Drought is an extreme climate phenomenon that happens slowly and periodically threatens the environmental and socio-economic sectors. Iraq is one of the countries in the Middle East that has been dealing with serious drought-related issues in the 21st century. Here, we investigate meteorological drought across Iraq from 1948 to 2009 at 0.25° spatial resolution. The Standardized Precipitation Evapotranspiration Index (SPEI) has been utilized as a multi-scalar drought index accounting for the effects of temperature variability on drought. Four of the main characteristics of drought including extent, intensity, frequency and duration are studied and the associated spatiotemporal patterns are investigated for each case. Results revealed a significant drought exacerbation over Iraq during the period of 1998–2009. Two significant drought periods of 1998–1999 and 2007–2008 are identified during which severe to extreme droughts covered about 87% and 82% of Iraq, respectively. Analyzing the trends of drought intensity reveals that the central and southwestern parts of Iraq have experienced aggravated intensifying patterns among other regions. In general, droughts are found to be more frequent but shorter at the western, central and southeastern parts of Iraq. Full article
(This article belongs to the Special Issue Drought Monitoring and Prediction)
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Open AccessArticle
Developing a Remotely Sensed Drought Monitoring Indicator for Morocco
Geosciences 2018, 8(2), 55; https://doi.org/10.3390/geosciences8020055
Received: 14 December 2017 / Revised: 29 January 2018 / Accepted: 1 February 2018 / Published: 6 February 2018
Cited by 6 | PDF Full-text (5447 KB) | HTML Full-text | XML Full-text
Abstract
Drought is one of the most serious climatic and natural disasters inflicting serious impacts on the socio-economy of Morocco, which is characterized both by low-average annual rainfall and high irregularity in the spatial distribution and timing of precipitation across the country. This work [...] Read more.
Drought is one of the most serious climatic and natural disasters inflicting serious impacts on the socio-economy of Morocco, which is characterized both by low-average annual rainfall and high irregularity in the spatial distribution and timing of precipitation across the country. This work aims to develop a comprehensive and integrated method for drought monitoring based on remote sensing techniques. The main input parameters are derived monthly from satellite data at the national scale and are then combined to generate a composite drought index presenting different severity classes of drought. The input parameters are: Standardized Precipitation Index calculated from satellite-based precipitation data since 1981 (CHIRPS), anomalies in the day-night difference of Land Surface Temperature as a proxy for soil moisture, Normalized Difference Vegetation Index anomalies from Moderate Resolution Imaging Spectroradiometer (MODIS) data and Evapotranspiration anomalies from surface energy balance modeling. All of these satellite-based indices are being used to monitor vegetation condition, rainfall and land surface temperature. The weighted combination of these input parameters into one composite indicator takes into account the importance of the rainfall-based parameter (SPI). The composite drought index maps were generated during the growing seasons going back to 2003. These maps have been compared to both the historical, in situ precipitation data across Morocco and with the historical yield data across different provinces with information being available since 2000. The maps are disseminated monthly to several main stakeholders’ groups including the Ministry of Agriculture and Department of Water in Morocco. Full article
(This article belongs to the Special Issue Drought Monitoring and Prediction)
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Open AccessArticle
Semi-Automatic Operational Service for Drought Monitoring and Forecasting in the Tuscany Region
Geosciences 2018, 8(2), 49; https://doi.org/10.3390/geosciences8020049
Received: 15 December 2017 / Revised: 24 January 2018 / Accepted: 29 January 2018 / Published: 2 February 2018
Cited by 1 | PDF Full-text (8395 KB) | HTML Full-text | XML Full-text
Abstract
A drought-monitoring and forecasting system developed for the Tuscany region was improved in order to provide a semi-automatic, more detailed, timely and comprehensive operational service for decision making, water authorities, researchers and general stakeholders. Ground-based and satellite data from different sources (regional meteorological [...] Read more.
A drought-monitoring and forecasting system developed for the Tuscany region was improved in order to provide a semi-automatic, more detailed, timely and comprehensive operational service for decision making, water authorities, researchers and general stakeholders. Ground-based and satellite data from different sources (regional meteorological stations network, MODIS Terra satellite and CHIRPS/CRU precipitation datasets) are integrated through an open-source, interoperable SDI (spatial data infrastructure) based on PostgreSQL/PostGIS to produce vegetation and precipitation indices that allow following of the occurrence and evolution of a drought event. The SDI allows the dissemination of comprehensive, up-to-date and customizable information suitable for different end-users through different channels, from a web page and monthly bulletins, to interoperable web services, and a comprehensive climate service. The web services allow geospatial elaborations on the fly, and the geo-database can be increased with new input/output data to respond to specific requests or to increase the spatial resolution. Full article
(This article belongs to the Special Issue Drought Monitoring and Prediction)
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Open AccessArticle
Drought Occurrences and Their Characteristics across Selected Spatial Scales in the Contiguous United States
Geosciences 2017, 7(3), 59; https://doi.org/10.3390/geosciences7030059
Received: 25 March 2017 / Revised: 26 June 2017 / Accepted: 14 July 2017 / Published: 19 July 2017
PDF Full-text (9510 KB) | HTML Full-text | XML Full-text
Abstract
An understanding of drought occurrences and their characteristics such as intensity, duration, frequency, and areal coverage, and their variations on different spatial scales, is crucial to plan for droughts in different regions and in different sized areas. This study investigated the variations of [...] Read more.
An understanding of drought occurrences and their characteristics such as intensity, duration, frequency, and areal coverage, and their variations on different spatial scales, is crucial to plan for droughts in different regions and in different sized areas. This study investigated the variations of spatio-temporal characteristics of droughts under selected spatial scales: National (Contiguous U.S.), regional (High Plains), state (North Dakota, ND), climatic division (South Central, ND), and county (Grant, ND). Weekly drought area coverage data for the period spanning the years 2000–2014 from the U.S. Drought Monitor of the National Drought Mitigation Center were used. The study captured the areal coverages and occurrence frequency of droughts with different intensity levels for the years 2000 to 2014 for the contiguous U.S. Year to year variability in spatial distribution of the areal coverages of droughts with different intensity levels were also analysed. The study further investigated how the weekly percentage area under different intensity categories varied along time, and extracted the spatio-temporal characteristics of different drought intensity categories at different spatial scales. The study identified areas that are frequently affected by droughts of different intensity categories in the U.S. at the national scale, and reported the spatial scale dependence of drought characteristics. Full article
(This article belongs to the Special Issue Drought Monitoring and Prediction)
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