scholarly journals Meteorological drought analysis using copula theory for the case of upper Tekeze river basin, Northern Ethiopia

2021 ◽  
Author(s):  
Biniyam Yisehak ◽  
Henok Shiferaw ◽  
Atkilt Girma ◽  
Zenebe Girmay ◽  
Rahwa Kidane
Keyword(s):  
Soil Moisture ◽  
Statistical Tests ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Extreme Drought ◽  
Trend Detection ◽  
Positive Trend ◽  
Northern Ethiopia ◽  
Drought Analysis ◽  
Copula Theory

Abstract Meteorological drought is a climate-related natural disaster. It indicates a shortage of precipitation over a long period, usually for a season or a year. This study was initiated to analyze meteorological drought using copula theory. Long-year (1982–2020) rainfall and soil moisture data were used to analyze standardized precipitation index (SPI) and standardized soil moisture index (SSI), respectively. The best-fit copula family was selected to construct the joint probability distribution (JPD) of SPI and SSI. Multivariate standardized drought index (MSDI) at 3-, 6-, and 12-month timescales were analyzed using the MSDI toolbox. The non-parametric Mann-Kendall (M-K) statistical test was used for trend detection. The result shows the newly developed MSDI captured all extreme drought events with the highest severity (-3.21) that occurred during the observation period compared to SPI and SSI. MSDI shows the famine caused by the drought of 1984 and 1985 remains well known to the world, with the drought duration and severity of 10 months and 18.7 years, respectively and its joint return period was 33.0 years. The result of the M-K and Sen’s Slope estimator statistical tests shows a positive trend for all drought timescales in the basin. The extreme drought captured by the MSDI most frequently occurred in the basin. This implicated that meteorological drought analysis using multiple indices is better than a single index. The results of this study will help devise drought adaptation and mitigation strategies in the basin and beyond.

scholarly journals Evaluation of Satellite Rainfall Estimates for Meteorological Drought Analysis over the Upper Blue Nile Basin, Ethiopia

Geosciences ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 352
Author(s):  
Mintesinot Taye ◽  
Dejene Sahlu ◽  
Benjamin F. Zaitchik ◽  
Mulugeta Neka
Keyword(s):  
Linear Trend ◽  
Standardized Precipitation Index ◽  
Warning System ◽  
Meteorological Drought ◽  
Extreme Drought ◽  
Drought Analysis ◽  
Blue Nile ◽  
The Mean ◽  
Satellite Rainfall ◽  
Rainfall Estimates

The objective of this study was to evaluate the performance of satellite rainfall estimates (Climate Hazards Group Infrared Precipitation with Stations version 2 (CHIRPSv2) and Multi-Source Weighted-Ensemble Precipitation version 2 (MSWEPv2) from 1981 to 2018 for monthly meteorological drought analysis over the Upper Blue Nile (UBN) basin. The reference for the performance evaluation was rainfall measured in situ selected with reference to the elevation zones of the basin: Highland, midland, and lowland. Both the measured and estimated rainfall datasets were aggregated by month at a spatial resolution of 10 km × 10 km with a temporal coverage of 38 years from 1981 to 2018 and evaluated with respect to raw precipitation statistics and the standardized precipitation index (SPI). The values of SPI were validated with reference to documented meteorological drought records of the country. The mean bias, correlation coefficient, probability of bias (PBias, %), mean error (ME, mm), and root mean square error (RMSE, mm) values across the elevation zones for CHIRPSv2 were found to be 1.07, 0.91, 6.75, 7.74, and 122.34, respectively. The corresponding values were 1.19, 0.87, 18.56, 19.54, and 130.26 for MSWEPv2. Based on this result, CHIRPSv2 was employed to analyze the magnitude of drought in the different elevation zones of the UBN. The magnitude (SPI) of monthly meteorological drought over the entire UBN basin from 1981 to 2018 ranged from 0 to −3.74. The strongest negative SPI value (−3.74) was observed in August 1984 in midland areas. The highest magnitude of drought was −3.0 in July 2015 over the highland and −3.03 in June 2015 over the lowland during 2014–2017. The observed drought was characterized by extreme, severe, and moderate levels. The mean frequency of severe/extreme meteorological drought in the 38-year period over the highland, midland, and lowland parts of the UBN ranged from 7% to 11%. The average of severe/extreme drought events in each of the elevation zones of the basin was 9%, that is, drought occurred almost every 10 years for all elevation zones of the basin. Over the 38-year period, severe/extreme drought occurred at the onset and/or offset time of rainy season over all elevation zones of the basin. The UBN is characterized as a drought-prone basin. However, the frequency and magnitude of drought could neither be described as a decreasing nor as an increasing linear trend. Thus, the farming practices in the basin need to be enhanced with an improved early warning system and drought-resistant seed technologies.

scholarly journals The effect of climate type on timescales of drought propagation in an ensemble of global hydrological models

2018 ◽  
Vol 22 (9) ◽  
pp. 4649-4665 ◽  
Author(s):  
Anouk I. Gevaert ◽  
Ted I. E. Veldkamp ◽  
Philip J. Ward
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Spatial Scales ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Hydrological Drought ◽  
Propagation Time ◽  
Hydrological Models ◽  
Land Surface Models ◽  
Surface Models

Abstract. Drought is a natural hazard that occurs at many temporal and spatial scales and has severe environmental and socioeconomic impacts across the globe. The impacts of drought change as drought evolves from precipitation deficits to deficits in soil moisture or streamflow. Here, we quantified the time taken for drought to propagate from meteorological drought to soil moisture drought and from meteorological drought to hydrological drought. We did this by cross-correlating the Standardized Precipitation Index (SPI) against standardized indices (SIs) of soil moisture, runoff, and streamflow from an ensemble of global hydrological models (GHMs) forced by a consistent meteorological dataset. Drought propagation is strongly related to climate types, occurring at sub-seasonal timescales in tropical climates and at up to multi-annual timescales in continental and arid climates. Winter droughts are usually related to longer SPI accumulation periods than summer droughts, especially in continental and tropical savanna climates. The difference between the seasons is likely due to winter snow cover in the former and distinct wet and dry seasons in the latter. Model structure appears to play an important role in model variability, as drought propagation to soil moisture drought is slower in land surface models (LSMs) than in global hydrological models, but propagation to hydrological drought is faster in land surface models than in global hydrological models. The propagation time from SPI to hydrological drought in the models was evaluated against observed data at 127 in situ streamflow stations. On average, errors between observed and modeled drought propagation timescales are small and the model ensemble mean is preferred over the use of a single model. Nevertheless, there is ample opportunity for improvement as substantial differences in drought propagation are found at 10 % of the study sites. A better understanding and representation of drought propagation in models may help improve seasonal drought forecasting as well as constrain drought variability under future climate scenarios.

scholarly journals Analysis of Drought in the Northern Region of Bangladesh Using Standardized Precipitation Index (SPI)

2019 ◽  
Vol 11 (1-2) ◽  
pp. 199-216
Author(s):  
R Afrin ◽  
F Hossain ◽  
SA Mamun
Keyword(s):  
Standardized Precipitation Index ◽  
Extended Period ◽  
Northern Region ◽  
Precipitation Index ◽  
Rainfall Data ◽  
Extreme Drought ◽  
Severe Drought ◽  
Drought Analysis ◽  
Dry Conditions ◽  
The Standardized Precipitation Index

Drought is an extended period when a region notes a deficiency in its water supply. The Standardized Precipitation Index (SPI) method was used in this study to analyze drought. Northern region of Bangladesh was the area of study. Monthly rainfall data of northern region of Bangladesh was obtained from the Meteorological Department of Bangladesh. Obtained rainfall data was from 1991 to 2011 and values from 2012 to 2026 were generated using Markov model. Then SPI values from 1991 to 2026 were calculated by using SPI formula for analyzing drought. Analysis with SPI method showed that droughts in northern region of Bangladesh varied from moderately dry to severely dry conditions and it may vary from moderately dry to severely dry conditions normally in future but in some cases extreme drought may also take place. From the study, it is observed that the northern region of Bangladesh has already experienced severe drought in 1991, 1992, 1994, 1995, 1997, 1998, 2000, 2003, 2005, 2007, 2009 and 2010. The region may experience severe drought in 2012, 2015, 2016, 2018, 2019, 2021, 2022, 2023, 2024, 2025 and 2026 and extreme drought in 2012, 2014, 2016, 2023 and 2024. J. Environ. Sci. & Natural Resources, 11(1-2): 199-216 2018

scholarly journals Commonly Used Drought Indices as Indicators of Soil Moisture in China

2015 ◽  
Vol 16 (3) ◽  
pp. 1397-1408 ◽  
Author(s):  
Hongshuo Wang ◽  
Jeffrey C. Rogers ◽  
Darla K. Munroe
Keyword(s):  
Soil Moisture ◽  
Time Scales ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Severity Index ◽  
Agricultural Drought ◽  
Weather Data ◽  
Drought Indices ◽  
Drought Severity ◽  
Better Than

Abstract Soil moisture shortages adversely affecting agriculture are significantly associated with meteorological drought. Because of limited soil moisture observations with which to monitor agricultural drought, characterizing soil moisture using drought indices is of great significance. The relationship between commonly used drought indices and soil moisture is examined here using Chinese surface weather data and calculated station-based drought indices. Outside of northeastern China, surface soil moisture is more affected by drought indices having shorter time scales while deep-layer soil moisture is more related on longer index time scales. Multiscalar drought indices work better than drought indices from two-layer bucket models. The standardized precipitation evapotranspiration index (SPEI) works similarly or better than the standardized precipitation index (SPI) in characterizing soil moisture at different soil layers. In most stations in China, the Z index has a higher correlation with soil moisture at 0–5 cm than the Palmer drought severity index (PDSI), which in turn has a higher correlation with soil moisture at 90–100-cm depth than the Z index. Soil bulk density and soil organic carbon density are the two main soil properties affecting the spatial variations of the soil moisture–drought indices relationship. The study may facilitate agriculture drought monitoring with commonly used drought indices calculated from weather station data.

scholarly journals TREND DETECTION OF METROLOGICAL DROUGHT IN NORTH OF IRAQ

2021 ◽  
Vol 25 (3) ◽  
pp. 60-73
Author(s):  
Ihsan F. Hasan ◽  
Keyword(s):  
Time Series ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Kendall Test ◽  
Northern Region ◽  
Trend Detection ◽  
Precipitation Data ◽  
Study Region ◽  
Slope Estimator ◽  
Mild Drought

This study presents an analysis of meteorological drought using multi time-scales of Standardized Precipitation Index SPI (6, 9 and 12 month), based on observed 49-year daily mean precipitation data records at 11 stations over the Northern region of Iraq. The detection of drought trends in results of SPI analysis was studied to identify whether there is any increase or decrease in the severity of drought at the selected meteorological Stations; Mann Kendall test and Sen's slope estimator were used to detect statistically significant trends. The results indicate that there is a statistically significant decreasing trend of SPI time series at 5% significant level in most of the selected stations. Based on drought categories the meteorological drought in the study region can be classified as mild drought.

scholarly journals Spatio‐temporal characteristics of meteorological drought under changing climate in semi‐arid region of northern Ethiopia

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Biniyam Yisehak ◽  
Henok Shiferaw ◽  
Haftu Abrha ◽  
Amdom Gebremedhin ◽  
Haftom Hagos ◽  
...  
Keyword(s):  
Climate Change ◽  
Meteorological Drought ◽  
Extreme Drought ◽  
Maximum Temperature ◽  
Northern Ethiopia ◽  
Temporal Characteristics ◽  
Changing Climate ◽  
Annual Minimum Temperature ◽  
Rcp 8.5 ◽  
Spatio Temporal

Abstract Background Below-normal availability of water for a considerable period of time induces occurrence of drought. This paper investigates the Spatio-temporal characteristics of meteorological drought under changing climate. The climate change was analyzed using delta based statistical downscaling approach of RCP 4.5 and RCP 8.5 in R software packages. The meteorological drought was assessed using the Reconnaissance Drought Index (RDI). Results The result of climate change projections showed that the average annual minimum temperature will be increased by about 0.8–2.9 °C. The mean annual maximum temperature will be also increased by 0.9–3.75 °C. The rainfall projection generally showed an increasing trend, it exhibited an average annual increase of 3.5–13.4 % over the study area. The projected drought events reached its maximum severity indicated extreme drought in the years 2043, 2044, 2073, and 2074. The RDI value shows drought will occurred after 1–6 and 2–7 years under RCP 4.5 and RCP 8.5 emission scenarios respectively over the study area. Almost more than 72 % of the current and future spatial coverage of drought in the study area will be affected by extreme drought, 22.3 % severely and 5.57 % also moderate drought. Conclusions Therefore, the study helps to provide useful information for policy decision makers to implement different adaptation and mitigation measures of drought in the region.

scholarly journals The effect of climate on timescales of drought propagation in an ensemble of global hydrological models

2018 ◽  
Author(s):  
Anouk I. Gevaert ◽  
Ted I. E. Veldkamp ◽  
Philip J. Ward
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Spatial Scales ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Hydrological Drought ◽  
Propagation Time ◽  
Hydrological Models ◽  
Land Surface Models ◽  
Surface Models

Abstract. Drought is a natural hazard that occurs at many temporal and spatial scales and has severe environmental and socio-economic impacts across the globe. The impacts of drought change as drought evolves from precipitation deficits to deficits in soil moisture or streamflow. Here, we quantified the time taken for drought to propagate from meteorological drought to soil moisture drought, and from meteorological drought to hydrological drought. We did this by cross-correlating the Standardized Precipitation Index (SPI) against standardized indices of soil moisture, runoff, and streamflow from an ensemble of global hydrological models forced by a consistent meteorological dataset. Drought propagation is strongly related to climate, occurring at sub-seasonal timescales in tropical climates and at up to multi-annual timescales in continental and arid climates. Winter droughts are usually related to longer SPI accumulation periods than summer droughts, especially in continental and tropical savanna climates. The difference between the seasons is likely due to winter snow cover in the former and distinct wet and dry seasons in the latter. Model structure appears to play an important role in model variability, as drought propagation to soil moisture drought is slower in land surface models than in global hydrological models, but propagation to hydrological drought is faster in land surface models than in global hydrological models. The propagation time from SPI to hydrological drought in the models was evaluated against observed data at 297 in-situ streamflow stations. On average, errors between observed and modeled drought propagation timescales are small and the model ensemble mean is preferred over the use of a single model. Nevertheless, there is ample opportunity for improvement as substantial differences in drought propagation are found at 20 % of the study sites. A better understanding and representation of drought propagation in models may help improve seasonal drought forecasting as well as constrain drought variability under future climate scenarios.

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