Standardized Precipitation Index Method Research Articles

Application of Rainfall Data in Drought Hazard Prediction in The Bengawan Solo River Basin Using The Rainfall Anomaly Index (RAI) and Standardized Precipitation Index (SPI)

This study investigates the impact of the Southern Oscillation Index (SOI) on meteorological droughts in the Bengawan Solo River Basin, Indonesia, from 2004 to 2023. Indonesia’s climate is influenced by the El Niño Southern Oscillation (ENSO), with negative SOI values (El Niño conditions) linked to drought events and positive values associated with the rainy season. This study analyzed the values of multiple stations' Rainfall Anomaly Index (RAI) and Standardized Precipitation Index (SPI). This study evaluates the compatibility of drought indices obtained from the Rainfall Anomaly Index (RAI) and the Standardized Precipitation Index (SPI) with the Southern Oscillation Index (SOI). The study's results indicate that the drought index using the Standardized Precipitation Index (SPI) method yields a higher percentage of compatibility with the Southern Oscillation Index (SOI), averaging 60.78%. The compatibility of the SPI method can also be observed in the number of meteorological dry months during 2010, the year of the most severe La Niña, and in 2015, during the most severe El Niño. Through the SPI method, it can also be demonstrated that rainfall data can accurately reflect drought events and rainy seasons, consistent with climate change occurrences.

METEOROLOGICAL DROUGHT RISK ASSESSMENT USING SPI NUMERICAL MODEL: A CASE STUDY OF HELMAND RIVER BASIN, AFGHANISTAN

Meteorological droughts, which result from insufficient precipitation, can cause significant economic damage. While preventing meteorological droughts is impossible, their harmful effects can be reduced through close monitoring. This study aims to evaluate the meteorological drought in the Helmand River Basin using the Standardized Precipitation Index (SPI) model. The hydrometeorological data used for this analysis were collected from the Ministry of Energy and Water (MEW) in Afghanistan. The precipitation data collected from MEW covers a 40-year period from 1979 to 2021. The SPI analysis of precipitation shows that 1990, 1991, and 1992 were moderately wet, while 1982, 1983, 1995-1998, 2005, 2014, and 2015 were nearly normal. However, moderately dry conditions were observed in 2000, 2001, 2018, and 2021. Among the sampled stations, Waras and Gardez consistently had low drought levels, while Tarnak, Shila-i-charkha, and Khwabgah stations experienced moderate-level drought. Meanwhile, Lashkargah and Adraskan stations exhibited relatively high levels of drought. In conclusion, this research on the HRB, using the SPI method, has provided valuable knowledge for understanding drought dynamics in the region. The findings underscore the importance of conducting region-specific analyses, the necessity of implementing sustainable water management strategies, and the global significance of addressing drought as a pressing environmental challenge.

An Approach for Future Droughts in Northwest Türkiye: SPI and LSTM Methods

Predetermining the risk of possible future droughts enables proactive measures to be taken in key areas such as agriculture, water management, and food security. Through these predictions, governments, non-governmental organizations, and farmers can develop water-saving strategies, encourage more efficient use of water, and minimize economic losses that may occur due to drought. Thus, future drought forecasts stand out as a strategic planning tool for the protection of natural resources. To achieve this aim, forecasted drought conditions for the next decade (2024–2034) at nine meteorological stations in the Sakarya basin, located northwest of Türkiye, are examined, using historical monthly precipitation data from 1991 to 2023. This study uses the Standardized Precipitation Index (SPI) and Long Short-Term Memory (LSTM) deep learning methods to investigate future meteorological droughts. The research confirms the compatibility and reliability of the LSTM method for forecasting meteorological droughts by comparing historical and forecasted SPI values’ correlograms and trends. In addition, drought maps are created to visually represent the spatial distribution of the most severe droughts expected in the coming years, and areas at risk of drought in the Sakarya Basin are determined. The study contributes to the limited literature on forward-looking drought forecasts in the Sakarya Basin and provides valuable information for long-term water resource planning and drought management in the region.

Trends of meteorological and hydrological droughts and associated parameters using innovative approaches

Climate change and drought have profound effects on hydro-meteorological series. In addition to spatial, these effects could be on annual, seasonal, monthly, or daily temporal scales. In the literature, seasonal Mann-Kendall and Kendall Tau, Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and Standardized Runoff Index are mostly used to detect seasonal effects (autumn, winter, spring, and summer), despite some restrictive assumption. Innovative Polygon Trend Analysis (IPTA) method developed from Innovative Trend Analysis (ITA) analyzes monthly effects on hydro-meteorological variables without restrictive assumptions. In this study, the IPTA method is revised and developed as Periodic Innovative Polygon Trend analysis (P-IPTA) to analyze hydro-meteorological series in periods of 1, 3, 6, 9, and 12 months instead of one-month duration. The method turns to the IPTA for one-month evaluations. Also, ITA method is improved by adding the frequencies for each drought classification (F-ITA). For the precipitation and water availability (Istanbul, Türkiye) and stream flow (Danube River, Romania) series, the P-IPTA method has been used in addition to the SPI, SPEI, and SDI methods to detect the trends in meteorological and hydrological droughts, and their associated parameters. There are generally decreasing trends, increasing drought frequencies, and decreasing wet event frequencies in the study areas. As the period lengths of the hydro-meteorological series increase, drought becomes more evident. Unlike these methods, the method results are consistent with the F-ITA SPI, SPEI, and SDI graphs and can give drought and wet periods. Similarly, the new P-IPTA method will enable researchers to investigate seasonal effects not only on hydro-meteorological series but also on any variable.

PENGUKURAN KINERJA DATA HUJAN CHIRPS DALAM PENILAIAN KEKERINGAN DI LOMBOK TENGAH

PENGUKURAN KINERJA DATA HUJAN CHIRPS DALAM PENILAIAN KEKERINGAN DI LOMBOK TENGAH

A comparative study of SPI, PCI, PCD, and RAI methods for estimating drought in the Palu River Basin, Indonesia

The Palu Watershed is vulnerable to extreme hydrological events, especially periods of heavy rains and prolonged dry seasons. This study aims to determine the drought index and the results of a comparison of the drought index between the Standardized Precipitation Index (SPI) and the Rainfall Anomaly Index (RAI), Rainfall Concentration Index (PCI), Rainfall Concentration Level (PCD), and Rainfall Concentration Period (PCP). The data used are monthly rainfall from Bora, Kalawara, Kulawi, Palolo, and Wuasa stations with observation periods from 1985 to 2021. The Pearson and Spearman correlation coefficients are used to determine the relationship between SPI and RAI, PCI, PCD, and PCP. RMSE and MAE are used to find out the absolute error in predictions. The results obtained show: PCI shows a uniform distribution of rainfall (76.57%) and moderately seasonal (32.43%) there is no distribution of seasonal and strongly seasonal rainfall, the dominant SPI is the normal category followed by mild and moderate drought, PCD and PCP show that rainfall is homogeneous and distributed throughout years and no rain is concentrated at any one time, Comparison of the relationship between SPI and RAI is very strong and significant compared to SPI versus PCI, SPI versus PCD and SPI versus PCP.

PRAKIRAAN INDEKS KEKERINGAN MENGGUNAKAN METODE SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (SARIMA) BERDASARKAN DATA STANDARDIZED PRECIPITATION INDEX (SPI) KOTA BANJARBARU

Drought is a disaster that has a bad impact, especially in the city of Banjarbaru. There are various ways to reduce the impact of drought in the future, one of which is by looking for information regarding the predicted drought index for the following year. The data used in this research to find the drought index value is Banjarbaru City rainfall data for 2007-2022. Seasonal Autoregressive Integrated Moving Average (SARIMA) method is a calculated method for predicting rainfall data and the data obtained is a forecast of rainfall in the city of Banjarbaru for the next 12 periods, namely SARIMA (0,2,3) (0,1,1)12. This model is a model that is suitable for use because it has fulfilled several tests, namely stationarity of variance and mean, significance test, white noise test and normality test with an AIC value of 1022,60 and an equation model obtained from SARIMA (0,2,3) (0,1,1)12 is (1-B)2 (1-B12) Zt=(1+1,77B-0,54B2+ 0,23B3 )(1-0,96B12 )εt. After obtaining forecast rainfall data for the next 12 periods. Rainfall data for 2007-2022 and forecast results for 2023 were used to find the drought index value using the Standardized Precipitation Index (SPI) method. It was found that the highest negative drought index value occurred in January, namely -1,774, including the dry category and the drought index had a positive value The highest occurred in June, namely 0,582, including the normal category. The calculation results of this drought index forecast are used to provide additional information to anticipate drought disasters in the future. Keywords: Drought Index, Rainfall, SPI Method, SARIMA Method, AIC

Evaluating the effect of the SPI and SPEI methods on drought monitoring over Turkey

Drought indices are one of the most widely used methods for drought monitoring because they are easy to apply and interpret. The two most widely used drought index methods are the Standardized Precipitation Index (SPI) method, using the precipitation parameter as input, and the Standardized Precipitation Evapotranspiration Index (SPEI) method, which uses the Potential Evapotranspiration (PET) values addition to precipitation. The primary goal of this study is to compare the two methods for determining drought characteristics in different climatic and geographical features in Turkey. The drought characteristics are calculated using meteorological data between 1970 and 2021 for 199 synoptic observation stations in seven geographical regions of Turkey with SPI and SPEI methods for the 3-, 6-, and 12-month time scales. The study's findings indicate that while the correlation coefficient (CC) between the two indices is generally high (ranging from 0.81 to 0.93, depending on the region and time scale), it is lower in regions with a low Aridity Index (AI) value, particularly for the 3-month time scale. For the 6- and 12-month time scales, no relationship is observed between AI and CC. Additionally, SPEI detected a higher occurrence percentage of moderate and severe droughts across all geographical regions (with an increase of up to 15 % compared to SPI), while SPI observed higher percentages of extreme droughts. The study results conclude that SPI and SPEI methods demonstrate significant differences in detecting certain drought characteristics after the 1990s, underscoring the necessity to consider temperature variations in drought monitoring, particularly in the context of ongoing climate change.

The Prediction of The Drought Index in The Indragiri Watershed Using SARIMA and SPI Methods

Farmers are concerned about the problem of drought in agriculture because it will disrupt the production system and cause losses. In 2015, the Indragiri Hulu area experienced a drought on 273 hectares of agricultural land. This area is part of the Indragiri River Watershed in Riau Province. To prevent the impact of future droughts, forecasting is required. The level of drought is influenced by rainfall, so the Seasonal Auto Regressive Integrated Moving Average (SARIMA) method is used to model rainfall data. In addition, the Standardized Precipitation Index (SPI) is also used to analyze the drought index. After the analysis, it was found that the best model in forecasting is SARIMA model (1,0,1)(2,1,1)12 with an average residual square of 18.0175, and the drought index in the Indragiri watershed is currently included in the "Normal" category. The results of this forecasting are expected to assist the Riau Province National Disaster Management Agency in anticipating and mitigating the impact of future drought disasters.

Climate Change Impact on Drought Characteristics in North Lombok Regency

Lombok Island is part of Indonesia which has a high vulnerability to drought. The area that often experienced drought severely on Lombok Island is North Lombok Regency. This study wants to examine the effect of climate change on drought characteristics in this region using the standardized precipitation index method using four rain stations in the North Lombok region rainfall recording data of 20 years (1999-2018). The analyses were taken into two groups of a 10-year time scale, 1999-2008 and 2009-2018, to overview both of the 10-years drought characteristics. Drought index values ​​were observed on a period of 1-month (SPI1), 3-months (SPI3), and 6-months (SPI6) to get the map of drought duration, drought magnitude, drought intensity, and relative frequency. The results show that the drought characteristics in Lombok showed a decrease significantly in all measurement parameters used. The SPI3 results have shown the drought duration was decreasing in the last 10 years by 87%, from 2,43 to 0.03 months. The strength of the drought decreased by 88%, from -1.03 to 0.12 (severely dry to normal). Then the drought intensity became lower up to 87% from -0.22 to -0.03 monthly, and the relative frequency of drought events decreased by 83%. Signs of the decline were further followed by the same decreasing trends in the 6-month drought index, SPI6. The decrease in the drought parameter index illustrates that climate change impact has reduced the risk of drought disaster on the island of Lombok in the future

Drought Analysis with Two Different Indices in Yeşilırmak Basin

Reducing the negative effects of drought disaster, which is one of the most important parameters affecting the planning and management of water resources, has become very important today. Many methods have been proposed in the literature for the calculation of drought, which is used to express the periods when precipitation is significantly less than the average, and two of these methods, "Standardized Precipitation Index" and "Reconnaissance Drought Index" were applied to the Yeşilırmak basin in this study.
 12-month standardized precipitation index and reconnaissance drought index analyzes were made and compared by using the monthly precipitation and evapotranspiration totals of 8 stations in the Yeşilırmak Basin for the period 1991-2020. The results show us that standardized precipitation index and reconnaissance drought index methods generally give similar signals for wet periods, but reconnaissance drought index method defines more extreme dry periods than standardized precipitation index method in extreme dry periods. While the reconnaissance drought index method defines more extreme dry periods than the standardized precipitation index method; It was observed that the standardized precipitation index method defined more extreme wet periods than the reconnaissance drought index method. In drought analysis, using an index based on more than one meteorological parameter (such as reconnaissance drought index) will give more reliable results instead of using an index based on a single parameter (i.e, standardized precipitation index). It has shown in this study that the effect of evapotranspiration values in drought calculation is very important by comparing it with reconnaissance drought index analysis and standardized precipitation index analysis.

APPLICATION OF THE STANDARDIZED PRECIPITATION INDEX FOR THE ASSESSMENT AND FORECAST OF ATMOSPHERIC DROUGHTS IN ALTAI KRAI

The research objective is to identify and analyze the possibility of using the Standardized Precipitation Index (SPI) in Altai Krai for agroclimatic and meteorological research, including forecasting climate change and predicting the yield of various crops. An agroclimatic assessment of atmospheric droughts within the conditions of Altai Krai was performed using a method relatively new for national agrometeorology. At the moment, in the Russian Federation and the CIS countries, the G. T. Selyaninov Hydrothermic Factor (HF) is mainly used for assessing droughts, which makes it possible to assess the territory water availability by the ratio of the period characteristics with the temperature above 10°С. The authors have compiled the SPI calculator in the Microsoft Excel software environment. The paper presents the graphs of the moisturization course for the period of the active growing season for 31 meteorological stations of Altai Krai, and the frequency of arid events is calculated for compiling a precipitation model for the period of 1964–2020. The paper does not provide formulas described in detail in literature sources. The research results can be used in planning activities in the sphere of agriculture, developing an economic strategy for the region, and strategy in relation to adaptation to climate change. Areas are highlighted that are priority-oriented for taking measures to prevent the adverse consequences of climate change. General tendencies of changes in agrometeorological indicators have been found in those areas where they are the greatest ones. A comparison is made with the work results regarding other entities of the Russian Federation and the near abroad, wherein the possibility of using the SPI method for assessing droughts is analyzed.

Suggestion of Classification Method for Agricultural Drought Using Groundwater Level Change

Since weather factors such as precipitation and temperature etc. show repeated patterns every year, it can be said that future changes can be predicted by analyzing past weather data. Therefore, when a drought occurs, the groundwater level is also lowered, so it can be seen that a change in the groundwater level can represent a drought. Like precipitation, groundwater level changes also have a high correlation with drought, so many researchers use SGI (standardized groundwater level index) to which the SPI (standardized precipitation index) method is applied to evaluate the severity of drought and predict trends. However, these approaches have the limitations to indicate the real groundwater system because the drought grades for the entire area are defined with the observation data of a single monitoring well without surrounding influences. When analyzing groundwater level fluctuations to understand the correlation with drought, it is necessary to calculate and apply the actual groundwater level that reflects groundwater use interference. Therefore, in this study, based on the long-term groundwater level data at 162 monitoring well installed before 2015 in Korea, the characteristics of groundwater level changes were analyzed and compared with the period of agricultural drought over the past five years. From the results, it can be confirmed that agricultural drought in regions is classified using the percentile of the SPI method by conducting a frequency analysis that the current groundwater level increase or decrease compared to the past average groundwater level.

ANALISIS KEKERINGAN DI KABUPATEN SRAGEN DENGAN METODE PALMER, THORNTHWAITE, DAN STANDARDIZED PRECIPITATION INDEX

El Nino and La Nina in Indonesia are one of the reasons that caused climate changes, which has possibility of drought and flood disasters. Sragen Regency wherethe dry season occurs, drought happened meanwhile other areas experience floods and landslides. A study on drought needs to be carried out so as to reduce the risk of losses due to the drought hazard. This study is to determine the drought index in Sragen Regency based on several methods and the correlation of each methods and its suitability to the Southern Oscillation Index (SOI) and rainfall. Drought was analyzed using several methods such as Palmer Drought Severity Index (PDSI), Thornthwaite-Matter, and Standardized Precipitation Index (SPI) then correlated with SOI to determine the most suitable method for SOI. The variables are applied in this method are rainfall, temperature, and evapotranspiration. The results showed that the drought potential of the Palmer method is only in Near Normal conditions, which is 1%, Severe drought conditions are 29% for the Thornthwaite-Matter method, and Extreme Dry conditions only reach 1,11% for the SPI method. The PDSI and SPI methods are inversely proportional to the Thornthwaite-Matter method and the most suitable method for SOI values or rainfall is the SPI method. These three methods can be identified the potential for drought with only a few variables so that they could be applied if they only have those data.Keywords: Drought, PDSI, Thornthwaite-Matter, SPI, SOI

Studi Analisa Kekeringan dengan Metode Standardized Precipitation Index (SPI) dan Palmer Drought Severity Index (PDSI) di DAS Kemuning Kabupaten Sampang

Drought is a natural disaster that occurs slowly but harms Sampang Regency people's life sustainability. Consider the negative impact of drought, analyze the drought index and its distribution are necessary. This study aims to know drought level using Standardized Precipitation Index (SPI) and Palmer Drought Severity Index (PDSI), then to know their correlation with Southern Oscillation Index (SOI) that can represent El Nino Southern Oscillation (ENSO). Drought index with bigger correlation mapped by Inverse Distance Weighting method to know the distribution. SPI method produced the most severe drought in April 2004 on one month deficit period (-3.651). PDSI method developed the most severe drought in September 2001 (-20.628). Based on the PDSI average analysis results for the 1998-2017 period, it is well-known that drought disasters generally start in July and end in October, while the peak of drought occurs in September. The PDSI method has 60% conformity to the SOI value derived from the graphical visualization of the annual average surplus and deficit index, better than the SPI method that only scores 53%. The visualization of the drought distribution map shows that the Districts of Sampang, Torjun, and Camplong need to become prioritized to mitigate future drought disasters because they have a great potential for drought disasters compared to other districts.

Muğla İlinde 1960-2018 Dönemi Kuraklık Analizi

Bu çalışmanın amacı, Muğla ilinin 1960-2018 periyodundaki yağış eğilimini ve meteorolojik, tarımsal ve hidrolojik kuraklık durumunu incelemektir. Çalışmada, Meteoroloji Genel Müdürlüğü’nden elde edilen Muğla Meteoroloji İstasyonu’na ait 1960-2018 dönemi aylık toplam yağış verileri kullanılmıştır. Yağış verilerine Run (Swed-Eisenhart) homojenlik testi, Mann-Kendall metodu ve Standart Yağış İndeksi yöntemi uygulanmıştır. Ayrıca, yaşanan kuraklıkların şiddet ve süresi de incelenmiştir. Sonuç olarak, Muğla ilinin uzun yıllar yağış ve kuraklık eğilimleri ortaya konulmuştur. Muğla ili için yıllık toplam yağışların 1960-2018 dönemi ortalaması 1180.2 mm olarak bulunmuştur. Çalışma döneminde en düşük yağış miktarı 2008 yılında 564.6 mm, en yüksek yağış miktarı ise 1969 yılında 1805 mm olarak görülmüştür. Muğla ilinde hafif nemli ve hafif kurak ay sayıları diğer sınıflara göre daha fazla gerçekleşmiştir. Ayrıca, ekstrem kurak dönem, ekstrem nemli döneme göre daha fazla gerçekleşmiştir. Muğla ilinde nemli ve kurak ay sayılarının, çoğunlukla hafif nemli, orta nemli, hafif kurak ve orta kurak şiddet sınıflarında kümelendiği görülmüştür. Ayrıca analizler, zaman periyodu arttıkça, kuraklığın daha az tekrar ettiği ama daha uzun süreli etkili olduğunu göstermektedir. Muğla istasyonunun ölçekler bazında toplam kuraklık şiddeti ve toplam kuraklık süreleri hemen hemen benzer yıllara denk gelmiştir. Ancak, 3 aylık Standart Yağış İndeksi periyodunda en güçlü toplam kuraklık şiddetinin -13.90 değeri ile 2006 Aralık – 2007 Eylül arasında görülmesine karşılık, yaşanan uzun süreli (12 ay) kuraklığın 2000 Haziran – 2001 Mayıs arasında olduğu görülmüştür.

Assessment of Drought Over Parambikulam Aliyar Basin of Tamil Nadu

Rainfall has a greater impact on agricultural, hydrological, economic, environmental and social systems. Inconsistencies in rainfall pattern could lead to extremities like drought and flood. Drought is a long period of unusually low rainfall that severely affects crop production and welfare of the people. Understanding the impacts of drought is crucial for planning, mitigation and responses. The Standardized precipitation index (SPI) method was employed for identifying drought occurrence in Parambikulam aliyar basin based on rainfall data of 37 years (1981–2017). SPI method indicated PAP basin had drought once in 4 years. In 19 per cent times, wet situation found to exist in PAP basin, five years exhibited moderately wet condition (1984, 1996, 2010, 2015 and 2017) and two years (1992 and 2005) fell under extremely wet event. Quantification on the drought events forms the scientific basis for decision makers to reduce the societal vulnerability to drought.

Major Over- and Underestimation of Drought Found in NOAA’s Climate Divisional SPI Dataset

AbstractEvaluation of the standardized precipitation index (SPI) dataset published monthly in the National Oceanic and Atmospheric Administration/National Centers for Environmental Information (NOAA/NCEI) climate divisional database revealed that drought frequency is being mischaracterized in climate divisions across the United States. The 3- and 6-month September SPI values were downloaded from the database for all years between 1931 and 2019; the SPI was also calculated for the same time scales and span of years following the SPI method laid out by NOAA/NCEI. Drought frequency is characterized as the total number of years that the SPI fell below −1. SPI values across 1931–90, the calibration period cited by NOAA/NCEI, showed regional patterns in climate divisions that are biased toward or away from drought, according to the average values of the SPI. For both time scales examined, the majority of the climate divisions in the central, Midwest, and northeastern United States showed negative averages, indicating bias toward drought, whereas climate divisions in the western United States, the northern Midwest, and parts of the Southeast and Texas had positive averages, indicating bias away from drought. The standard deviation of the SPI also differed from the expected value of 1. These regional patterns in the NCEI’s SPI values are the result of a different (sliding) calibration period, 1895–2019, instead of the cited standardized period of 1931–90. The authors recommend that the NCEI modify its SPI computational procedure to reflect the best practices identified in the benchmark papers, namely, a fixed baseline period.

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

Drought is taken into account as a natural hazard, which might be characterized mainly by its severity, duration, and areal extent. Among the above three dimensions, drought severity is that the main factor through which drought analysis was done. The paper aims at presenting the overall meteorological drought analysis of Gajapati District of Odisha by Reconnaissance Drought Index (RDI)and Standard precipitation Index (SPI), through DrinC software using SPI-3, SPI-6, SPI-9 & SPI-12, and RDI-3, RDI-6, RDI-9 & RDI 12 which were computed at multiple time steps (3, 6,9 and 12-month) for the period 1967-2002. The 12-month SPI and RDI series shows well-defined wet periods and dry periods compared to other months. it has been discussed, for identifying dry/wet periods, SPI 12 and RDI 12 shows greater utility than SPI 3 and RDI 3. The analysis of RDI-12 shows that, there was a Moderate drought was recorded during 1967-68, 1973-74, 1984-85, 1987-88. In the Gajapati region drought index, by SPI & RDI method showed that extremely affected by drought among 35 years was 1972-73 and severe drought occurred in 1979-80. Overall, there was a moderate drought situation within the Gajapati district.

Addition of Criteria for the Drought Level Vulnerability to the Reservoir Location Priority

Blora regency is mostly a water critical region during dry seasons due to its porous soil characteristic. In order to overcome this condition, in 2006, Indonesian Ministry of Public Works and Housing, through Mettana Engineering Consultant, conducted a Study of Identification and Basic Design Development of Reservoirs in Blora Regency. It determined 28 future reservoir locations by considering their technical, economical and socio-environmental aspects. However, for the reservoirs to be the most effective, it is necessary to include regional drought vulnerability aspect into consideration to determine their location priority. The main purpose of this research, to conduct an analysis of meteorogical drought vulnerability in Blora regency region.In more detail the main goal is to determine reservoir location priority in Blora regency region by considering meteorogical drought vulnerability aspect. Drought Index was calculated using SPI (Standardized Precipitation Index ) method using 2009-2018 monthly precipitation data obtained from 15 precipation stations. Mapping of drought vulnerable regions was done using GIS (Geographic Information System) technology using spatial interpolation approach. This research determined new priority, different from that determined by Mettana Engineering Consultant. Priority 1 formerly consisted of Suruhan, Kedungwungu, Bangsri, Sambong and Kalisari reservoirs while the new one consisted of Polaman 1, Polaman 2, Suruhan and Jurangjero reservoirs. Suruhan reservoir appeared in both versions. Kedungwungu, Bangsri, Sambong and Kalisari reservoirs moved to priority 2 in the new priority since they were located in low drought level regions while Polaman 1, Polaman 2 and Jurangjero reservoirs moved to priority 1 since they were located in moderately high to moderate drought level regions. It indicated that is necessary to include drought vulnerability aspect into consideration in determining reservoir location, along with technical, economical and socio-enviromental aspects. The government then may employ this aspect as an additional criteria in developing future reservoir construction program to be more effective that targets drought vulnerable regions