scholarly journals Meteorological drought trend analysis by standardized precipitation index (SPI) and reconnaissance drought index (RDI): a case study of Gajapati District

2020 ◽  
Vol 8 (3) ◽  
pp. 1741-1746
Author(s):  
Dibya Ranjan Mohanta ◽  
Jogendra Soren ◽  
Shubham Kumar Sarangi ◽  
Sharmistha Sahu
2021 ◽  
Vol 1 (2) ◽  
pp. 672-685
Author(s):  
Amifta Farah Listya ◽  
◽  
Donny Harisuseno ◽  
Ery Suhartanto ◽  
◽  
...  

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.


2020 ◽  
Vol 310 ◽  
pp. 00047
Author(s):  
Patrik Nagy ◽  
Martina Zeleňáková ◽  
Slávka Galas ◽  
Helena Hlavatá ◽  
Dorota Simonová

In the paper we evaluated dry and wet 6 months’ periods, which reflect changes in water resources of the country. We assessed Standardized Precipitation Index (SPI), Standardized Evapotranspiration Index (SPEI), Streamflow Drought Index (SDI), Reconnaissance Drought Index (RDI). The time period was 1960 - 2015 and the study area includes eastern Slovakia – selected water and climatic stations. The results indicate dry periods and wet periods. The results of work are presented in the table for separate evaluated indices.


2021 ◽  
Author(s):  
Soumyashree Dixit ◽  
K V Jayakumar

Abstract 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.


2017 ◽  
Vol 2017 ◽  
pp. 1-17 ◽  
Author(s):  
Md. Anarul Haque Mondol ◽  
Iffat Ara ◽  
Subash Chandra Das

Natural disasters are a major concern in Bangladesh, particularly drought which is one of the most common disaster in Bangladesh. Drought needs to be explained spatially to understand its spatiotemporal variations in different areas. In this paper, the meteorological drought has been shown by using the Standardized Precipitation Index (SPI) method and illustrated through the Inverse Distance Weighted (IDW) method across Bangladesh. We used rainfall data of 30 meteorological stations in Bangladesh during the study period of 1981–2010. The results indicate that drought has been fluctuating and it has become a recurrent phenomenon during the study period. The SPI depicted the drought conditions that plunged dramatically in 1981, 1982, 1985, 1987, 1989, 1992, 1994, and 1996 and then gradually improved in 2004, 2006, and 2009 in the country. The present study demonstrated that drought occurred in Bangladesh on an average of 2.5 years. Drought was more prominent in the northern, south-western, and eastern regions in Bangladesh compared to the rest of the areas of the country. The outcomes of the present study will help in during disaster management strategies, particularly drought, by initiating effective plans and adaptation remedies in different areas of Bangladesh.


2020 ◽  
Vol 11 (S1) ◽  
pp. 29-43 ◽  
Author(s):  
Okan Mert Katipoğlu ◽  
Reşat Acar ◽  
Selim Şengül

Abstract Drought incidents occur due to the fact that precipitation values are below average for many years. Drought causes serious effects in many sectors, such as agriculture, economy, health, and energy. Therefore, the determination of drought and water scarcity, monitoring, management, and planning of drought and taking early measures are important issues. In order to solve these issues, the advantages and disadvantages of five different meteorological drought indices were compared, and the most effective drought index was determined for monitoring drought. Accordingly, in the monthly, 3-month, and 12-month time period, covering the years between 1966 and 2017 (52 years), Standardized Precipitation Index (SPI), Statistical Z-Score Index (ZSI), Rainfall Anomaly Index (RAI), Standardized Precipitation Evapotranspiration Index (SPEI), and Reconnaissance Drought Index (RDI) were used. It was concluded that precipitation-based SPI and ZSI are similar patterns and precipitation, and temperature-based SPEI and RDI are similar patterns. Also, it has been determined that RAI is more effective than other indices in determining the periods of extreme drought or wet. Furthermore, SPEI and RDI have been found to be superior to other indices as they take into account the water consumption and climate effects caused by evapotranspiration.


2019 ◽  
Vol 33 (15) ◽  
pp. 5015-5033 ◽  
Author(s):  
Ruqayah Mohammed ◽  
Miklas Scholz

AbstractInvestigating the spatiotemporal distribution of climate data and their impact on the allocation of the regional aridity and meteorological drought, particularly in semi-arid and arid climate, it is critical to evaluate the climate variability effect and propose sufficient adaptation strategies. The coefficient of variation, precipitation concentration index and anomaly index were used to evaluate the climate variability, while the Mann-Kendall and Sen’s slope were applied for trend analysis, together with homogeneity tests. The aridity was evaluated using the alpha form of the reconnaissance drought index (Mohammed & Scholz, Water Resour Manag 31(1):531–538, 2017c), whereas drought episodes were predicted by applying three of the commonly used meteorological drought indices, which are the standardised reconnaissance drought index, standardized precipitation index and standardized precipitation evapotranspiration index. The Upper Zab River Basin (UZRB), which is located in the northern part of Iraq and covers a high range of climate variability, has been considered as an illustrative basin for arid and semi-arid climatic conditions. There were general increasing trends in average temperature and potential evapotranspiration and decreasing trends in precipitation from the upstream to the downstream of the UZRB. The long-term analysis of climate data indicates that the number of dry years has temporally risen and the basin has experienced succeeding years of drought, particularly after 1994/1995. There was a potential link between drought, aridity and climate variability. Pettitt’s, SNHT, Buishand’s and von Neumann’s homogeneity test results demonstrated that there is an evident alteration in the mean of the drought and aridity between the pre- and post-alteration point (1994).


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