DROUGHT ASSESSMENT USING THE RECONNAISSANCE DROUGHT INDEX (RDI): A CASE STUDY OF EASTERN MEDITERRANEAN, SEYHAN, CEYHAN AND ASI BASINS OF TURKEY

In this study, drought analysis was carried out in the region, which includes the Eastern Mediterranean, Seyhan, Ceyhan and Asi Basins located in the south of Turkey. In total, data from 35 meteorological stations has been analyzed. As a drought index, the Reconnaissance Drought Index (RDI) was utilised. The Thornthwaite method was selected in the calculation of Potential Evapotranspiration (PET). According to the results, the PET values of all stations have increased in recent years. 3, 6, 9, and 12 month RDI values have been plotted based on the hydrological years. As stated by RDI results, there was mild drought in the basin. The drought results obtained by Turkish State Meteorological Service (The Ministry of Agriculture and Forestry General Directorate of Meteorology) with the Standardized Precipitation Index (SPI) method were compared with the results in this study. In this study, drought mapping for RDI was carried out using the annual values of stations with common observation years to monitor visually spatial spread of the drought.

Analisis Kekeringan Meteorologi dengan Menggunakan Metode Standardized Precipitation (SPI) dan Reconnaissance Drought Index (RDI) di DAS Lekso Kabupaten Blitar

Kekeringan dapat didefinisikan pengurangan persediaan air yang bersifat sementara secara signifikan di bawah normal. Bencana kekeringan yang terjadi di Indonesia saat ini mengakibatkan daerah kekurangan suplai air untuk kebutuhan hidup, pertanian, dan kegiatan ekonomi dalam masa yang berkepanjangan. Meninjau dampak yang ditimbulkan, maka diperlukan analisis untuk daerah-daerah yang memiliki potensi terjadinya bencana kekeringan. Terdapat beberapa metode yang dikembangkan untuk menganalisis kekeringan, seperti SPI (Standardized Precipitation Index) dan RDI (Reconnaissance Drought Index), sehingga mengetahui tingkat dan karakteristik kekeringan suatu daerah. Setelah melakukan analisis dengan kedua indeks tersebut dilakukan pengambaran peta sebaran kekeringan menggunakan Sistem Informasi Geografi sehingga mempermudah menginterpretasikan daerah yang mengalami potensi kekeringan pada DAS Lekso , serta dapat melakukan upaya-upaya pencegahan dan penanggulangan bahaya bencana kekeringan. hasil penelitian menunjukkan puncak kekeringan metode SPI periode defisit 1 bulan terjadi Mei tahun 2005 dengan wilayah desa yaitu Desa Slumbung, Balerejo, Semen, Tulungrejo dan Soso. Sedangkan pada metode RDI , puncak kekeringan terjadi pada bulan Mei tahun 2005 dengan wilayah desa yang mengalami kekeringan yaitu Desa Slumbung, Balerejo, Semen, Tulungrejo dan Soso. Berdasarkan analisis kesesuaian antara indeks kekeringan dengan data Southern Oscillation Indeks, disimpulkan bahwa perhitungan indeks kekeringan metode RDI memiliki prosentase tingkat kesesuaian lebih tinggi dibandingkan dengan metode indeks kekeringan SPI.

A Non-Stationary and Probabilistic Approach for Drought Characterization Using Trivariate and Pairwise Copula Construction (PCC) Model

Under the variable climatic conditions, the conventional Standardized Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) are inadequate for predicting extreme drought characteristics. So in the present study, two indices namely, Non-stationary Standardized Precipitation Index (NSPI) and Non-stationary Reconnaissance Drought Index (NRDI) are developed by fitting non-stationary gamma (for precipitation series) and lognormal (for initial values,δ0) distributions. The Generalized Additive Model in Location, Scale and Shape (GAMLSS) framework, with time varying location parameters considering the external covariates, is used to fit the non-stationary distributions. This includes various large scale climate indices namely Multivariate ENSO Index (MEI), Southern Oscillation Index (SOI), Sea Surface Temperature (SST), and Indian Ocean Dipole (IOD) as external covariates for the non-stationary drought assessment. The performances of stationary and non-stationary models are compared based on the Akaika Information Criterion (AIC). Additionally, the drought characteristics are evaluated using Run theory analysis for both stationary and non-stationary drought indices. The study also concentrated on the trivariate copula as well as the Pairwise Copula Construction (PCC) models to estimate the drought recurrence intervals. The comparison of two copula models revealed that the PCC model performed better than the trivariate Student’s t copula model. The recurrence intervals arrived at for the drought events are different for trivariate copula model and PCC model. The area taken for the study is the Upper and Lower sub basins of the Godavari River basin. This study shows that non-stationary drought indices will be helpful in the accurate estimate of the drought characteristics under the changing climatic scenario.

Analysis of meteorological droughts in the Lake’s Region of Ethiopian Rift Valley using reconnaissance drought index (RDI)

This study investigated the intensity, trend and spatio-temporal variability of meteorological drought in the Lakes’ Region of Ethiopian Rift Valley using monthly rainfall and maximum and minimum temperature records for the period 1986–2019. Reconnaissance Drought Index (RDI) was employed to generate the intensity of drought at 3 and 12-months timescale. Mann-Kendall trend test was used to determine the trend of the changes in the RDI time series. The spatial extent of droughts has been interpolated by inverse distance weighted (IDW) method using the spatial analyst tool of ArcGIS. Results indicated the occurrence of different intensity and trend signals across seasons and over space in the study area. A total of 33 extreme drought months were observed in all stations during summer with varying intensity (− 2.01 at Halaba to − 3.52 at Wolaita) and 168 extreme drought months at annual timescale ranging from − 2.10 at Hawassa to − 4.51 at Wolaita. The intensity of drought events observed in Wolaita in 1986 at all timescales (RDI value of − 3.19, − 3.52 and − 4.51 for spring, summer and annual respectively) were very extraordinary and devastating. Drought magnitude showed increasing signal at 6 out of 10 stations, although statistically significant at only two stations (Arsi Negelle at all timescale and Butajira at spring and annual timescale). However, the spatial patterns of drought events didn’t exhibit clear pattern rather more localized distribution and variability. The frequency of drought incidence became intense in the study area from 2008 onwards at all timescales compared to the 1990s and 2000s.The increasing tendency of drought in recent years might be the manifestation of borderless global warming. The empirical evidences showed that drought events and their negative effects are highly localized in the study area and provide useful information for local-scale planning for drought management and response.

Drought Characterization and Trend Detection Using the Reconnaissance Drought Index for Setsoto Municipality of the Free State Province of South Africa and the Impact on Maize Yield

The reconnaissance drought index (RDI) for the Setsoto municipality of the Free State province in South Africa was calculated for the period between 1985 and 2019 at 3 month (October–December), 6 month (October–March), and 12 month (October–September) intervals. Rainfall and minimum and maximum temperature data from four weather stations (Clocolan, Ficksburg, Marquard, and Senekal) were used for this study to characterize drought using “DrinC” software together with the Mann Kendall test with Sen’s slope to detect drought trends and the rate of change. Extreme, severe, and moderate droughts were recorded for all the stations, with RDIs ranging from −3.6 to −1.0 at different temporal scales. The years 1991, 1994, 2006, 2011, and 2015 were highlighted using the RDI 3, 6, and 12 month calculations. Results showed that the yield decreased either in the year of the drought or in the subsequent year, due to the exact timing of the low-rainfall events in the season and soil moisture storage. Yields were low, on average 2.5 tons ha−1 year−1, with high variability. Optimal growing conditions are essential in the early part of the season, October–December, for maximizing yield; if droughts are experienced at this time then the yield is more greatly impacted than if the droughts occur later in the season. Spatial analysis shows a large variability of drought patterns across the Municipality, over the years, with the 3 month RDI values giving a more detailed picture of this variability than the 6 and 12 month RDI values.

Drought indices and trend analysis

In recent times, extremely dry seasons have been occurring more and more often in the eastern Slovakia, alternating with extremely wet seasons like torrential floods from extreme rainfall. Trend of reconnaissance drought index (RDI) and streamflow drought index (SDI) was evaluated in the paper using the Mann-Kendall test. The indices were evaluated at six climatic and river stations in the eastern Slovakia. The Mann-Kendal test results showed that the trend in the SDI index is not significant in 5 stations and only in one station the trend is significant. In the RDI index the trend is not significant in four stations and the trend is significant in two stationshe abstract is to indicate the subject of the paper, how the author proposes to develop the subject and its overall objective, aim or outcome.

Evaluation of Drought Characteristics Using the Reconnaissance Drought Index (RDI) over Parambikulam Aliyar Basin of Tamil Nadu

Drought tends to be a creeping phenomenon occurs gradually with the deficiency in rainfall further extending its impact on sectors which are dependent on water. The drought characteristics were analysed in Parambikulam Aliyar Project (PAP) basin based on the European Centre for Medium range Weather Forecasts Interim Reanalysis (ERA-Interim) gridded data with resolution of 0.125° ×0.125° during 1981-2017. Reconnaissance Drought Index (RDI) was applied for monitoring the drought. The variables used in RDI are rainfall and potential evapotranspiration (ETo), the required meteorological data were taken from the ERA Interim dataset and ETo was calculated using Penman-Monteith method. RDI indicated that 41% of the time had drought condition over 37 years. Two years (1982 and 2012) faced severe drought across all the parts of the PAP basin and the highest number of mild drought events were observed than the other drought conditions in PAP basin. Results showed that Plain areas in PAP basin experienced maximum number of drought events compared to the other areas in PAP basin during the investigation period.