Drought assessment and monitoring using meteorological indices in a semi-arid region

Haied, Nadjib; Foufou, Atif; Chaab, Salah; Azlaoui, Mohamed; Khadri, S.; Benzahia, K.; Benzahia, I.

doi:10.1016/j.egypro.2017.07.064

Cited by 58 publications

(29 citation statements)

References 18 publications

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“…Hargreaves equation is one of the most precise and simplest empirical equations which is used to estimate ET P and relies on monthly minimum, maximum, and average temperature and extraterrestrial radiation ( R a ) [51][52][53][54] . This method is more accurate for arid and semi-arid regions and gives reliable results [55][56][57] .…”

Section: Study Areas and Datasets Iran's Wrm Comentioning

confidence: 99%

Normalized difference vegetation index as the dominant predicting factor of groundwater recharge in phreatic aquifers: case studies across Iran

Parizi

Hosseini

Ataie-Ashtiani

et al. 2020

Sci Rep

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The estimation of long-term groundwater recharge rate ($${GW}_{r}$$ GW r ) is a pre-requisite for efficient management of groundwater resources, especially for arid and semi-arid regions. Precise estimation of $${GW}_{r}$$ GW r is probably the most difficult factor of all measurements in the evaluation of GW resources, particularly in semi-arid regions in which the recharge rate is typically small and/or regions with scarce hydrogeological data. The main objective of this study is to find and assess the predicting factors of $${GW}_{r}$$ GW r at an aquifer scale. For this purpose, 325 Iran’s phreatic aquifers (61% of Iran’s aquifers) were selected based on the data availability and the effect of eight predicting factors were assessed on $${GW}_{r}$$ GW r estimation. The predicting factors considered include Normalized Difference Vegetation Index (NDVI), mean annual temperature ($$T$$ T ), the ratio of precipitation to potential evapotranspiration ($${P/ET}_{P}$$ P / E T P ), drainage density ($${D}_{d}$$ D d ), mean annual specific discharge ($${Q}_{s}$$ Q s ), Mean Slope ($$S$$ S ), Soil Moisture ($${SM}_{90}$$ SM 90 ), and population density ($${Pop}_{d}$$ Pop d ). The local and global Moran’s I index, geographically weighted regression (GWR), and two-step cluster analysis served to support the spatial analysis of the results. The eight predicting factors considered are positively correlated to $${GW}_{r}$$ GW r and the NDVI has the greatest influence followed by the $$P/{ET}_{P}$$ P / ET P and $${SM}_{90}$$ SM 90 . In the regression model, NDVI solely explained 71% of the variation in $${GW}_{r}$$ GW r , while other drivers have only a minor modification (3.6%). The results of this study provide new insight into the complex interrelationship between $${GW}_{r}$$ GW r and vegetation density indicated by the NDVI. The findings of this study can help in better estimation of $${GW}_{r}$$ GW r especially for the phreatic aquifers that the hydrogeological ground-data requisite for establishing models are scarce.

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Section: Study Areas and Datasets Iran's Wrm Comentioning

confidence: 99%

Normalized difference vegetation index as the dominant predicting factor of groundwater recharge in phreatic aquifers: case studies across Iran

Parizi

Hosseini

Ataie-Ashtiani

et al. 2020

Sci Rep

View full text Add to dashboard Cite

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“…Analyses of SPI and RDI at 9 and 12 mo timescales represent long-term droughts (Haied et al 2017). According to Fig.…”

Section: Nine Month Analysismentioning

confidence: 99%

Historical analysis (1981-2017) of drought severity and magnitude over a predominantly arid region of Pakistan

Hina¹,

Saleem²

2019

Clim. Res.

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Droughts are one of the multifaceted meteorological disasters affecting agriculture, livestock and water resources worldwide. Pakistan has a semiarid climate system with a high degree of interannual rainfall variability. This study evaluates the applicability and comparison of 3 drought indices (deciles index [DI], standardized precipitation index [SPI] and reconnaissance drought index [RDI]) in Pakistan. Monthly rainfall and temperature data (1981−2017) from 30 weather stations were used to analyze the current status of drought occurrence in terms of severity and magnitude. A nonparametric Mann-Kendall test and Sen's slope estimates were applied on drought indices to determine the statistical significance and magnitude of the trend. The DI captured the dry episodes in the region well, as Baluchistan and Sindh provinces have been seen to be more susceptible to droughts. The indices of SPI and RDI were well correlated at 3, 6, 9 and 12 mo timescales. Province-level analysis revealed the highest number of drought years during the 3 mo timescale and the lowest number of drought years during the 12 mo timescale. Overall, a linearly increasing trend of SPI and RDI (towards wetness) was observed, whereas the province-level analysis showed a statistically significant trend at the 95% confidence level for Khyber Pakhtunkhwa, Punjab and Sindh in the long-term drought analysis. Moreover, analyses of historical drought years and their intensity have been investigated and compared with a recent long drought episode (1999− 2002). The analysis of historical drought events highlights the challenging nature of drought management in Pakistan. The outcomes of this study would help water resource managers to investigate drought response measures for drought preparedness in the country.

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“…Moreover, RDI can be effectively used to compare the drought conditions between areas with different climatic characteristics (Haied et al, 2017). It also has an advantage as it enables universal applicability over the other indices (Haied et al, 2017). By employing monthly or seasonal measures of PET from the general index of meteorological drought, extent of drought spatial pattern and severity for different time scale over the space can be mapped.…”

Section: Drought Indicesmentioning

confidence: 99%

“…Therefore, RDI is a meteorological index used for drought assessment (Mohammad et al, 2011;Mohammed et al, 2018 andZarch et al, 2011) and it was developed to analyse water deficit in a more accurate way, as a sort of balance between input and output in a water system (Tsakiris et al, 2007c). Moreover, RDI can be effectively used to compare the drought conditions between areas with different climatic characteristics (Haied et al, 2017). It also has an advantage as it enables universal applicability over the other indices (Haied et al, 2017).…”

Section: Drought Indicesmentioning

confidence: 99%

Characterizing Spatiotemporal Patterns of Drought among the Pastoralists of Southern Ethiopia, Eastern Africa

Guye¹,

Legesse²,

Yimer³

2021

Preprint

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This paper is an inquiry of investigating trends and spatiotemporal patterns of meteorological drought in semi-arid pastoral areas in southern Ethiopia. Monthly gridded rainfall and temperature data for thirty years between 1986 to 2016 were obtained d from Ethiopian Meteorological Agency. Nonparametric Mann Kendall’s test (MK) along with Sen’s slope estimator was employed to see trends of drought. In addition, Reconnaissance Drought Index (RDI) was used to characterize the drought patterns. The result indicates that under all time scale, drought events tend to show an increasing trend with varying magnitude and intensity. The highest drought severity category for major and small rainy months was identified during May 2000 with RDI= -2.28 and September 2000 with RDI= -2.55 . The drought magnitudes of the small rainy months range from -11.15 in November to -11.76 in September, while it ranges from -10.08 in April to -11.38 in March for the major rainy months. There are some variations of drought magnitude among the seasons while rainfall tend to show gradual decline as a manifestation of spatially varying drought severity, frequency and intensity in the watershed.

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Drought assessment and monitoring using meteorological indices in a semi-arid region

Cited by 58 publications

References 18 publications

Normalized difference vegetation index as the dominant predicting factor of groundwater recharge in phreatic aquifers: case studies across Iran

Normalized difference vegetation index as the dominant predicting factor of groundwater recharge in phreatic aquifers: case studies across Iran

Historical analysis (1981-2017) of drought severity and magnitude over a predominantly arid region of Pakistan

Characterizing Spatiotemporal Patterns of Drought among the Pastoralists of Southern Ethiopia, Eastern Africa

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