Standardized Precipitation Index Method Research Articles

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.

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.

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

Pemanfaatan Data Global Precipitation Measurement (GPM) dan Standardized Precipitation Index (SPI) untuk Deteksi Kekeringan Meteorologis di Provinsi Papua Barat

Kekeringan merupakan salah satu bencana alam di Indonesia. Badan Nasional Penanggulangan Bencana (BNPB) melaporkan bahwa Provinsi Papua Barat memiliki ancaman kekeringan yang sedang hingga tinggi. Penelitian ini bertujuan untuk menganalisis tingkat kekeringan di Provinsi Papua Barat menggunakan data Global Precipitation Measurement (GPM) dan metode Standardized Precipitation Index (SPI). Hasil penelitian menunjukkan bahwa sepanjang tahun 2019 di Papua Barat tidak terjadi kekeringan meteorologis, hanya beberapa wilayah di Kabupaten Kaimana yang agak kering pada SPI bulan Januari – Maret 2019. Secara umum data GPM dan metode SPI memiliki akurasi yang cukup baik dalam menggambarkan tingkat kekeringan meteorologis di Provinsi Papua Barat dibandingkan dengan analisis data hujan dan peta tingkat kekeringan yang dirilis oleh Badan Meteorologi, Klimatologi, dan Geofisika (BMKG), sehingga data GPM dan metode SPI dapat digunakan untuk memantau tingkat kekeringan di Provinsi Papua Barat khususnya pada kawasan pertanian.

Drought Analysis and Forecast Using Landsat-8 Sattelite Imagery, Standardized Precipitation Index and Time Series

A drought is a phenomenon of shortages in water supply in an area for a long time. Drought usually occurs in areas that have little rain for a long time or in areas with low precipitation. Drought have negative impacts on many sectors such as agriculture, plantations, water resources and environment. This paper describes the results of a research that aims to analyze data to get the level of drought during four yearly periods, and predict the likelihood of drought to occur in the future. The level of drought was analyzed using the Inverse Distance Weighted (IDW) method and the Standardized Precipitation Index (SPI). Least square time series was utilized to forecast the level of drought in the near future. Data consists of drought data collected from electronic news, rainfall data from BMKG, and anual Landsat-8 satellite imagery. All data are for Western Southeast Mallucas in the range of 2015-2018. Analysis using IDW and SPI methods produce similar interpretation for year 2015, i.e. mild dryness, and fro year 2018, i.e. no drought. However, the two methods show discrepancy in analysis of data for 2016 and 2017. The use of least square time series to forecast drought in 2019 gives SPI value of 0.03 which intepretes as normal weather (no drought) that is consistent with the result of field observation.

Precipitación acumulada en las tierras altas entre las secciones Tilarán y Central, Costa Rica

Se analiza el total acumulado de la precipitación cada cinco año, utilizando tres estaciones meteorológicas: Zarcero, Piedades Sur y Montes de Oro en Costa Rica. Estas localidades fueron seleccionadas, ya que cada una se ubica en sectores con distintos niveles de precipitación. De esta manera es posible tener una idea del comportamiento de la precipitación a lo largo de veinte años. Esto debido a que, por ser estaciones ubicadas en sectores muy rurales, solo una de ellas, la primera tiene datos superiores a los cincuenta años, pero para homogenizar los registros se tuvo que considerar solo veinte años. Los periodos históricos cada cinco años secos o húmedos se identifican mediante el método de índice de precipitación estandarizado y sus tendencias se analizan para evaluar la posible relación con el evento ENOS. Todas las estaciones evidencian cierta igualdad en la distribución quinquenal en la precipitación en el transcurso del período de estudio (1994-2013). La tendencia en cada estación es la siguiente, Zarcero, muestran niveles altos en el periodo 2004-2008. En Montes de Oro los niveles de precipitación son muy regulares, aunque con un ligero incremento entre el 2004-2008, pero en realidad es muy leve el incremento. En el caso de Piedades Sur se muestra un fuerte incremento en la lluvia en el quinquenio de 2004-2008. Esto refleja la existencia de una relación entre la precipitación del área en estudio con respecto a evento del ENOS, así como la influencia de la irregularidad en el relieve montañoso.

Analysis of Drought in the Northern Region of Bangladesh Using Standardized Precipitation Index (SPI)

Drought is an extended period when a region notes a deficiency in its water supply. The Standardized Precipitation Index (SPI) method was used in this study to analyze drought. Northern region of Bangladesh was the area of study. Monthly rainfall data of northern region of Bangladesh was obtained from the Meteorological Department of Bangladesh. Obtained rainfall data was from 1991 to 2011 and values from 2012 to 2026 were generated using Markov model. Then SPI values from 1991 to 2026 were calculated by using SPI formula for analyzing drought. Analysis with SPI method showed that droughts in northern region of Bangladesh varied from moderately dry to severely dry conditions and it may vary from moderately dry to severely dry conditions normally in future but in some cases extreme drought may also take place. From the study, it is observed that the northern region of Bangladesh has already experienced severe drought in 1991, 1992, 1994, 1995, 1997, 1998, 2000, 2003, 2005, 2007, 2009 and 2010. The region may experience severe drought in 2012, 2015, 2016, 2018, 2019, 2021, 2022, 2023, 2024, 2025 and 2026 and extreme drought in 2012, 2014, 2016, 2023 and 2024.
 J. Environ. Sci. & Natural Resources, 11(1-2): 199-216 2018

Assessment of Groundwater Drought in the Mangyeong River Basin, Korea

When groundwater drought occurs, baseflow discharges to surface-water bodies will be reduced and then domestic and agricultural water usage becomes at risk of insufficient supply. Thus, in this study, several methods for groundwater drought assessment were tested with long-term monitoring water-level data in the study area to preserve groundwater sustainability from drought, principally caused by reduced precipitation and propagated through agricultural drought and groundwater drought. Because of the Monsoon climate on the Korean Peninsula, the groundwater storage (or water-level) is secured until the end of summer, then falls by natural discharge during the dry seasons of autumn, winter and the following spring. Thus, the rainfall in the wet season seems to mainly influence groundwater storage until the spring of the following year. As the groundwater level (GWL) declines due to natural drainage and the use of agricultural water increases by the end of the dry season (October–May), the GWL will become lowered below the critical level. Below this level, sufficient water supply is not secured. Using the Standardized Precipitation Index (SPI), threshold method and 95% probability occurrence method, drought detection and the frequency of drought are compared. Groundwater drought using the threshold method results in more frequent occurrence than using the SPI method. The 95% occurrence method responds to severe drought but it also has weakness in missing the man-induced GWL decline in every spring season. For groundwater drought assessment, an appropriate drought index should be utilized according to climatic conditions and catchment characteristics. In the study area, variations of the both natural and anthropogenic effects are mixed and the threshold method is more suitable as a measure for preventing water resources shortage.