An Investigation into the Spatial and Temporal Variability of the Meteorological Drought in Jordan

Background: Recently, many parts of Hungary, as well as central Europe, have been hit by successive extreme climatic events. The main aim of this research was to analyze hydrological and agricultural drought episodes in the Debrecen Region in eastern Hungary from 1950 to 2010. Thus, data of monthly precipitation were collected and tested. After that, three indices were applied, the Precipitation Concentration Index (PCI), dry Precipitation Concentration Index (dPCI), and the Standardized Precipitation Index (SPI). Meanwhile, the correlation between SPI and the normalized difference vegetation index (NDVI) was calculated. Results: The results showed that the PCI values ranged between 9.44 and 15.8 with an average of 11.8, while the dPCI values ranged between 8.6 and 20.7 with an average of 10.9, which indicates heterogeneity in rainfall distribution from year to year. More than 103 events of severe agricultural drought were detected for the whole studied period. In connection to this, severe hydrological drought was recorded in 16% of the total monthly rainfall events from 1950 to 2010. Interestingly, a significant correlation was obtained between SPI-3, -6 (i.e., drought), and NDVI in the summer season. Conclusions:The SPI index could provide an easy tool for drought monitoring meanwhile drought evaluation and monitoring should be taken seriously in the central Europe.

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“…3. These results indicate the presence of extreme events in the study area as proposed by (Aladaileh et al 2019).…”

Section: Trends Of R Pci and Dpci In The Study Area From 1951 Untilsupporting

confidence: 67%

Precipitation pattern changes and response of vegetation to drought variability in the eastern Hungary

et al. 2020

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“…Field measurements from meteorological stations are used to calculate continuous data based on interpolation methods and allow prediction of data in areas where in-situ data are not included. Different interpolation methods were used for mapping drought [ 61 , 62 , 63 , 64 , 65 ]. Subedi et al [ 66 ] used the Inverse Distance Weighting IDW, Kriging, and Spline methods to analyze spatiotemporal changes during a drought in Texas, USA based on SPEI index.…”

Section: Discussionmentioning

confidence: 99%

Uncertainty in Determination of Meteorological Drought Zones Based on Standardized Precipitation Index in the Territory of Poland

Wicher-Dysarz

Dysarz

Jaskuła

2022

IJERPH

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The primary aim of this work is to assess the accuracy of the methods for spatial interpolation applied for the reconstruction of the spatial distribution of the Standardized Precipitation Index (SPI). The one-month version called SPI-1 is chosen for this purpose due to the known greatest variability of this index in comparison with its other versions. The analysis has been made for the territory of the entire country of Poland. At the same time the uncertainty related to the application of such computational procedures is determined based on qualitative and quantitative measures. The public data of two kinds are applied: (1) measurements of precipitation and (2) the locations of the meteorological stations in Poland. The analysis has been made for the period 1990–2020. However, all available observations since 1950 have been implemented. The number of available meteorological stations has decreased over the analyzed period. In January 1990 there were over one thousand stations making observations. In the end of the period of the study, the number of stations was below six hundred. Obviously, the temporal scarcity of data had an impact on the obtained results. The main tools applied were ArcGIS supported with Python scripting, including generally used modules and procedures dedicated to geoprocessing. Such an approach appeared crucial for the effective processing of the large number of data available. It also guaranteed the accuracy of the produced results and brought about drought maps based on SPI-1. The methods tested included: Inverse Distance Weighted, Natural Neighbor, Linear, Kriging, and Spline. The presented results prove that all the procedures are inaccurate and uncertain, but some of them provide satisfactory results. The worst method seems to be the interpolation based on Spline functions. The practical aspects related to the implementation of the methods led to removal of the Linear and Kriging interpolations from further use. Hence, Inverse Distance Weighted, as well as Natural Neighbor, seem to be well suited for this problem.

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“…Terefore, the selection of drought indices for a specifc study area depends on many factors. Te most common selection criteria are the number of input data required, data availability, the objective of the study, climate condition, novelty of the index, and validity which are the factors that determine the selection of indicators [38,40].…”

Section: Drought Analysis Methodsmentioning

confidence: 99%

Hydrological and Meteorological Drought Monitoring and Trend Analysis in Abbay River Basin, Ethiopia

Tareke

Awoke

2022

Advances in Meteorology

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The definition of drought is very controversial due to its multi-dimensional impact and slow propagation in onset and end. Predicting the accurate occurrence of drought remains a challenging task for researchers. The study focused on hydrological and meteorological drought monitoring and trend analysis in the Abbay river basin, using the streamflow drought index (SDI), standardized precipitation index (SPI), and reconnaissance drought index (RDI), respectively, to fill this research gap. The study also looked into the interrelationships between the two drought indicators. The SDI, SPI, and RDI were calculated using long-term streamflow, precipitation, and temperature data collected from 1973 to 2014. The data were collected from eight streamflow stations and fifteen meteorological gauge stations. DrinC software (Drought Indices Calculator) was used to calculate the SDI, SPI, and RDI values. The result from meteorological drought using SPI12 and RDI12 shows that 1975, 1981, 1984, 1986, 1991, 1994, and 2010 were extreme drought years, whereas 1983, 1984, 2001, and 2010 were the most extreme hydrological drought years based on the SDI12 result. Except for Bahir Dar and Gondar, a severe drought occurs at least once a decade in all stations considered in this study. In general, the SPI, RDI, and SDI results indicated that the study area was exposed to the most prolonged severe and extreme drought from 1981 to 1991. The findings of this study also demonstrated that the occurrence of hydrometeorological droughts in the Abbay river basin has a positive correlation at long time scales of 6 and 12 months. The trend analysis using the Mann–Kendall test implied that there was a significant meteorological drought trend in two stations (Debre Berhan and Fiche) at SPI12 and RDI12 time scale, but for the remaining thirteen stations, there is no trend in all time scales. The hydrological drought trend analysis in the basin on a seasonal (SDI3) and yearly (SDI12) time scale also revealed that three streamflow stations have a positive trend (Kessie, Gummera, and Border). This implies that water resource management is still a vital tool for the sustainable development of the Abbay river basin in the future.

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An Investigation into the Spatial and Temporal Variability of the Meteorological Drought in Jordan

Cited by 25 publications

References 46 publications

Precipitation pattern changes and response of vegetation to drought variability in the eastern Hungary

Precipitation pattern changes and response of vegetation to drought variability in the eastern Hungary

Uncertainty in Determination of Meteorological Drought Zones Based on Standardized Precipitation Index in the Territory of Poland

Hydrological and Meteorological Drought Monitoring and Trend Analysis in Abbay River Basin, Ethiopia

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