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Drought Monitoring and Forecasting at Regional and Global Scale Using Remote Sensing, Ground Observations and Global Climate Datasets

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A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".

Deadline for manuscript submissions: closed (31 October 2022) | Viewed by 28911

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Special Issue Editors

Dr. Yared Bayissa

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Department of Ecology and Conservation Biology, Texas A&M University, College Station, TX 77843, USA
Interests: hydrological extremes; drought and vegetation monitoring; watershed management; remote sensing; watershed modeling and climate change
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Prof. Dr. Assefa M. Melesse

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Department of Earth and Environment, AHC-5-390, Florida International University, 11200 SW 8th Street, Miami, FL, USA
Interests: remote sensing; watershed modeling; climate change impact; sediment dynamics; river basin management
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Prof. Dr. Tsegaye Tadesse

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National Drought Mitigation Center, School of Natural Resources, University of Nebraska-Lincoln /815 Hardin Hall, Lincoln, NE 68583-0988, USA
Interests: drought and vegetation monitoring; remote sensing; agricultural development; food security, and climate change/variability at national and international levels
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Drought has significant impacts on different socioeconomic sectors, including water availability for agriculture, drinking water supply, and the ecosystem in general. It covers a large area without being recognized, and it is often difficult to characterize its onset and offset. Understanding its characteristics through an integrative approach using the available information is paramount for preparedness and planning of water resources, and to develop a robust drought-resilient system. Basically, drought indices are widely applied to monitor drought using station-based hydrometeorological observations and remote sensing products at regional and global spatial scales. Some of the indices use a single input variable to characterize the hidden aspects of drought while other indices use more than one input variable to characterize the complex nature of drought. Recently, the blending of several input variables representing different components of the hydrological cycle (e.g., precipitation, soil moisture, reservoir levels, river flow, groundwater levels) using data mining and other machine learning approaches has also seen increasing application.

The development of a rigorous real-time drought monitoring tool is a foundation for the effort towards developing drought forecasting and early warning systems to mitigate its adverse impacts and avert catastrophe. Climate change and global warming are intensifying the frequency and severity of drought. However, advances in atmospheric sciences have laid a platform for easily accessible future climate projected data that are mainly derived from global circulation models using different boundary conditions. Projected climate data are potential resources in the process of developing a drought forecasting system at different lead times to a certain uncertainty band.

Therefore, this Special Issue has the theme “Drought monitoring and forecasting at regional and global scale using remote sensing, ground observations and global climate datasets”, and we welcome novel research covering drought monitoring, the development of new drought indexes or the improvement of existing indexes, drought forecasting, risk and vulnerability assessment and management, remote sensing and its application for drought monitoring, vegetation and forest drought monitoring, climate projections and application for drought forecasting, the application of machine learning for the development of drought forecasting systems, the application of in situ measurements to validate drought products, and any other drought-related studies.

Dr. Yared Bayissa
Prof. Dr. Assefa M. Melesse
Prof. Dr. Tsegaye Tadesse
Guest Editors

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Keywords

drought monitoring and forecasting
drought indices
vegetation and forest stress
drought risk assessment and vulnerability
drought resilience
remote sensing of drought
climate change
moisture stress
low flows

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Published Papers (7 papers)

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Research

18 pages, 3981 KiB

Open AccessFeature PaperArticle

The Sensitivity of Meteorological Dynamics to the Variability in Catchment Characteristics

by Shimelash Molla Kassaye, Tsegaye Tadesse, Getachew Tegegne and Kindie Engdaw Tadesse

Water 2022, 14(22), 3776; https://doi.org/10.3390/w14223776 - 20 Nov 2022

Cited by 3 | Viewed by 3302

Abstract

Evaluating meteorological dynamics is a challenging task due to the variability in hydro-climatic settings. This study is designed to assess the sensitivity of precipitation and temperature dynamics to catchment variability. The effects of catchment size, land use/cover change, and elevation differences on precipitation and temperature variability were considered to achieve the study objective. The variability in meteorological parameters to the catchment characteristics was determined using the coefficient of variation on the climate data tool (CDT). A land use/cover change and terrain analysis was performed on Google Earth Engine (GEE) and ArcGIS. In addition, a correlation analysis was performed to identify the relative influence of each catchment characteristic on the meteorological dynamics. The results of this study showed that the precipitation dynamics were found to be dominantly influenced by the land use/cover change with a correlation of 0.65, followed by the elevation difference with a correlation of −0.47. The maximum and minimum temperature variations, on the other hand, were found to be most affected by the elevation difference, with Pearson correlation coefficients of −0.53 and −0.57, respectively. However, no significant relationship between catchment size and precipitation variability was observed. In general, it is of great importance to understand the relative and combined effects of catchment characteristics on local meteorological dynamics for sustainable water resource management. Full article

(This article belongs to the Special Issue Drought Monitoring and Forecasting at Regional and Global Scale Using Remote Sensing, Ground Observations and Global Climate Datasets)

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21 pages, 34563 KiB

Open AccessFeature PaperArticle

Developing a Combined Drought Index to Monitor Agricultural Drought in Sri Lanka

by Yared Bayissa, Raghavan Srinivasan, George Joseph, Aroha Bahuguna, Anne Shrestha, Sophie Ayling, Ranjith Punyawardena and K. D. W. Nandalal

Water 2022, 14(20), 3317; https://doi.org/10.3390/w14203317 - 20 Oct 2022

Cited by 3 | Viewed by 3675

Abstract

Developing an agricultural drought monitoring index through integrating multiple input variables into a single index is vital to facilitate the decision-making process. This study aims to develop an agricultural drought index (agCDI) to monitor and characterize the spatial and temporal patterns of drought in Sri Lanka. Long-term (1982 to 2020) remote sensing and model-based agroclimatic input parameters—normalized difference vegetation index (NDVI), land surface temperature (LST), 3-month precipitation z-score (stdPCP), and evaporative demand drought index (EDDI)—were used to develop agCDI. The principal component analysis (PCA) approach was employed to qualitatively determine the grid-based percentage contribution of each input parameter. The agCDI was apparently evaluated using an independent dataset, including the crop yield for the major crop growing districts and observed streamflow-based surface runoff index (SRI) for the two main crop growing seasons locally, called Yala (April to September) and Maha (October to March), using 20-years of data (from 2000 to 2020). The results illustrate the good performance of agCDI, in terms of predominantly capturing and characterizing the historic drought conditions in the main agricultural producing districts both during the Yala and Maha seasons. There is a relatively higher chance of the occurrence of moderate to extreme droughts in the Yala season, compared to the Maha season. The result further depicts that relatively good correlation coefficient values (> 0.6) were obtained when agCDI was evaluated using a rice crop yield in the selected districts. Although the agCDI correlated well with SRI in some of the stations (>0.6), its performance was somehow underestimated in some of the stations, perhaps due to the time lag of the streamflow response to drought. In general, agCDI showed its good performance in capturing the spatial and temporal patterns of the historic drought and, hence, the model can be used to develop agricultural drought monitoring and an early warning system to mitigate the adverse impacts of drought in Sri Lanka. Full article

(This article belongs to the Special Issue Drought Monitoring and Forecasting at Regional and Global Scale Using Remote Sensing, Ground Observations and Global Climate Datasets)

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19 pages, 8740 KiB

Open AccessArticle

Hydrological Response to Meteorological Droughts in the Guadalquivir River Basin, Southern Iberian Peninsula

by Emilio Romero-Jiménez, Matilde García-Valdecasas Ojeda, Juan José Rosa-Cánovas, Patricio Yeste, Yolanda Castro-Díez, María Jesús Esteban-Parra and Sonia R. Gámiz-Fortis

Water 2022, 14(18), 2849; https://doi.org/10.3390/w14182849 - 13 Sep 2022

Cited by 1 | Viewed by 2577

Abstract

Drought is an extreme phenomenon that will likely increase in frequency and severity in the current context of climate change. As such, it must be studied to improve the decision-making process in affected areas. As a semi-arid zone, the Guadalquivir River basin, located in the southern Iberian Peninsula, is an interesting area to perform this study. The relationship between meteorological and hydrological droughts is studied using drought indices with data from 1980 to 2012. The chosen indices are the Standardized Streamflow Index (SSI) and the Standardized Precipitation Evapotranspiration Index (SPEI). Their correlations are calculated, based on SPEI accumulation periods, and these values are analyzed with a principal component analysis to find spatial patterns in drought behavior inside the basin. This analysis was performed for the continuous series and also for monthly series, to account for seasonal changes. It has been found that the relationship of drought types occurs at different time scales depending mainly on orography and catchment area. Two main patterns were found. Generally, for low altitudes and small catchment areas, accumulation periods are shorter indicating that hydrological system in this area respond rapidly to meteorological conditions. In mountainous parts of the basin, longer accumulation periods have a stronger influence due to effects such as snowmelt. Full article

(This article belongs to the Special Issue Drought Monitoring and Forecasting at Regional and Global Scale Using Remote Sensing, Ground Observations and Global Climate Datasets)

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16 pages, 4465 KiB

Open AccessArticle

Spatiotemporal Distribution of Drought Based on the Standardized Precipitation Index and Cloud Models in the Haihe Plain, China

by Yujuan Fu, Xudong Zhang, Ray G. Anderson, Ruiqiang Shi, Di Wu and Qiucheng Ge

Water 2022, 14(11), 1672; https://doi.org/10.3390/w14111672 - 24 May 2022

Cited by 5 | Viewed by 2345

Abstract

The Haihe Plain is the largest component of the agriculturally vital North China Plain, and it is characterized by serious water shortage and frequent droughts, which lead to crop reduction and have adverse effects on agriculture and ecology. We used daily precipitation data from 1955–2017; the region’s spatiotemporal characteristics of drought were analyzed by using the standardized precipitation index (SPI), drought probability, and Mann–Kendall test for seasonal scale including two main crops growth seasons for the region’s main crops. Furthermore, a cloud algorithm model was established to analyze the dispersion and instability of the SPI. The annual drought frequency is 28.57%; the SPI for spring has an increasing tendency, while summer shows a significant decreasing trend (p < 0.05); the Haihe Plain has had a tendency towards drought over the last 63 years. The SPI in northwest is the smallest and increases gradually toward the south; the severity of drought in dry years increased from southeast to northwest. The cloud model shows that the SPI randomness of each site decreased significantly and tended to be stable and uniform. The deterministic and stable SPI of each station is stronger in dry years, and the randomness and instability are stronger in wet years. The inter-annual differences of the characteristic values of the SPI cloud model are bigger than the differences among sites, and the inter-annual randomness and inhomogeneity of the SPI are higher. Full article

(This article belongs to the Special Issue Drought Monitoring and Forecasting at Regional and Global Scale Using Remote Sensing, Ground Observations and Global Climate Datasets)

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17 pages, 3035 KiB

Open AccessArticle

Assessment of Climate and Catchment Control on Drought Propagation in the Tekeze River Basin, Ethiopia

by Ethiopia Bisrat Zeleke, Assefa M. Melesse and Belete Berhanu Kidanewold

Water 2022, 14(10), 1564; https://doi.org/10.3390/w14101564 - 13 May 2022

Cited by 5 | Viewed by 2976

Abstract

It is crucial to understand the development of hydrological drought which is unique to a sub-basin to derive management strategies that can address the cause. In this study, relationships between climate and catchment control against hydrological drought development in the Tekeze River Basin (TRB), Ethiopia, were assessed. The Water Evaluation and Planning (WEAP) modeling tool was selected to mimic the behavior and historical characteristics of the basin which was modeled for the period 1981 to 2018. The most severe drought events and historical drought years were selected and analyzed on a monthly basis, where the classical rainfall deficit drought was identified to be the most common typology within the basin. Once modeled, both meteorological and hydrological drought analyses were performed using the Threshold Level Method (TLM) where 168 months of meteorological drought with magnitudes as high as 110 mm/month and 60 months of streamflow anomalies with magnitudes of up to 17 mm/month were observed. While the temporal resolution impacts results pertaining to hydrological drought development, the analysis showed that the basin is fast responding, where storage characteristics did not play a significant role in delaying a hydrological drought onset. Compared to naturalized streamflow, the construction of the Tekeze Dam on the main river was indicative of an over 900% increase in dry season flows but a reduction of 23% of wet season flows, showing the potential to redistribute runoff in space and time. Full article

(This article belongs to the Special Issue Drought Monitoring and Forecasting at Regional and Global Scale Using Remote Sensing, Ground Observations and Global Climate Datasets)

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21 pages, 4876 KiB

Open AccessArticle

Trends of Rainfall Variability and Drought Monitoring Using Standardized Precipitation Index in a Scarcely Gauged Basin of Northern Pakistan

by Muhammad Farhan Ul Moazzam, Ghani Rahman, Saira Munawar, Aqil Tariq, Qurratulain Safdar and Byung-Gul Lee

Water 2022, 14(7), 1132; https://doi.org/10.3390/w14071132 - 1 Apr 2022

Cited by 43 | Viewed by 4950

Abstract

This study focused on the trends of rainfall variability and drought monitoring in the northern region of Pakistan (Gilgit-Baltistan). Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) model data were used for the period of 1981 to 2020. The Standardized Precipitation Index (SPI) was applied to assess the dry and wet conditions during the study period. The Mann–Kendall (MK) and Spearman’s rho (SR) trend tests were applied to calculate the trend of drought. A coupled model intercomparison project–global circulation model (CMIP5–GCMs) was used to project the future precipitation in Gilgit-Baltistan (GB) for the 21st century using a multimodel ensemble (MME) technique for representative concentration pathway (RCP) 4.5 and RCP 8.5. From the results, the extreme drought situations were observed in the 12-month SPI series in 1982 in the Diamir, Ghizer, and Gilgit districts, while severe drought in 1982–1983 was observed in Astore, Ghizer, Gilgit, Hunza-Nagar, and Skardu. Similarly, in 2000–2001 severe drought prevailed in Diamir, Ghanche, and Skardu. The results of MK and SR indicate a significant increasing trend of rainfall in the study area, which is showing the conversion of snowfall to rainfall due to climate warming. The future precipitation projections depicted an increase of 4% for the 21st century as compared with the baseline period in the GB region. The results of the midcentury projections depicted an increase in precipitation of about 13%, while future projections for the latter half of the century recorded a decrease in precipitation (about 9%) for both RCPs, which can cause flooding in midcentury and drought in the latter half of the century. The study area is the host of the major glaciers in Pakistan from where the Indus River receives its major tributaries. The area and volume of these glaciers are decreasing due to warming impacts of climate change. Therefore, this study is useful for proper water resource management to cope up with water scarcity in the future. Full article

(This article belongs to the Special Issue Drought Monitoring and Forecasting at Regional and Global Scale Using Remote Sensing, Ground Observations and Global Climate Datasets)

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18 pages, 4109 KiB

Open AccessArticle

Assessment of the Continuous Extreme Drought Events in Namibia during the Last Decade

by Xuan Liu and Jie Zhou

Water 2021, 13(20), 2942; https://doi.org/10.3390/w13202942 - 19 Oct 2021

Cited by 14 | Viewed by 7519

Abstract

In the context of climate change, the intensity, frequency, and duration of drought events have increased significantly, resulting in a profound impact on both natural ecosystems and socio-economic systems. In arid and semi-arid regions, precipitation is the main limiting factor for vegetation growth, and the ecosystems are very sensitive to climate change. Over the past 10 years, the Namibian government has declared national emergencies in 2013, 2016, and 2019 due to extreme drought events. The continued extreme drought has posed serious threat to the country’s food security. Accurately monitoring the continuous drought events in Namibia and assessing their impact on the ecosystem is essential for drought risk management in the region. Based on long-term satellite observation of vegetation index and precipitation, we have evaluated the spatiotemporal dynamics of the three drought events, the vegetation–precipitation relationship across biomes, and the impact of continuous drought events on regional ecosystems. The results suggest that: (1) According to affected area and severity, the drought in 2019 was the most severe one, followed by the drought in 2013; the 2015–2016 drought spread over smaller spatial area, although it continued for two years; (2) Both the accumulated NDVI and precipitation in the growing season in Namibia increased from 2001 to 2010 while showing a significant decreasing trend during 2011–2020; (3) In Namibia, there is a significant correlation between the current season’s accumulated precipitation and the current season’s accumulated NDVI (r = 0.90, p < 0.01). The current season’s accumulated precipitation is also well correlated with the next season’s accumulated NDVI (r = 0.87, p < 0.01), and the correlation between the current season’s accumulated precipitation and the next season’s accumulated NDVI in a wet year is even stronger (r = 0.96, p < 0.01). This indicates that part of the precipitation in the current season may be stored in the soil for the next season’s plant growth, which is more obvious in the northern plains with deep-rooted woody plants; (4) In 2013, the drought event suddenly changed from a long-term relatively humid state to an extremely dry state. During the ecological recovery stage, the NDVI during the growing season could not return to the state before the drought, causing irreversible damage to the Namibian ecosystem. In summary, the continuous extreme drought events during the last decade have caused profound impacts on the regional ecosystem. Much more attention should be paid to whether the extreme drought events will continue into the next decade and how the ecosystem can sustain a new equilibrium under a warmer and drier climate. Full article

(This article belongs to the Special Issue Drought Monitoring and Forecasting at Regional and Global Scale Using Remote Sensing, Ground Observations and Global Climate Datasets)

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