The Use Of Standardized Indicators (SPI And SPEI) In Predicting Droughts Over The Republic Of Moldova Territory

Maria, Nedealcov; Valentin, Răileanu; Sîrbu, Rodica; Cojocari, Rodica

doi:10.1515/pesd-2015-0032

Cited by 15 publications

(10 citation statements)

References 1 publication

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“…A drought event based on the SPI and SPEI is considered to be a period in which the values of the indices are continuously negative and ≤ −1 (Nedealcov et al, 2015;Lee et al, 2017) that is described by severity, duration and frequency. Run theory is a probabilistic method (Yevjevich, 1967) used to extract drought characteristics based on the SPI and SPEI.…”

Section: Definition Of Drought Characteristics Based On Run Theorymentioning

confidence: 99%

Meteorological drought analysis using copula theory and drought indicators under climate change scenarios (RCP)

Mesbahzadeh

Mirakbari

Saravi

et al. 2019

Meteorological Applications

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The study was carried out to assess meteorological drought on the basis of the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) evaluated in future climate scenarios. Yazd province, located in an arid region in the centre of Iran, was chosen for analysis. The study area has just one synoptic station with a long‐term record (56 years). The impact of climate change on future drought was examined by using the CanESM2 of the CMIP5 model under three scenarios, that is, representative concentration pathways RCP2.6, RCP4.5 and RCP8.5. Given that a drought is defined by several dependent variables, the evaluation of this phenomenon should be based on a multivariate analysis. For this purpose, two main characteristics of drought (severity and duration) were extracted by run theory in a past (1961–2016) and future (2017–2100) period based on the SPI and SPEI, and studied using copula theory. Three functions, that is, Frank, Gaussian and Gumbel copula, were selected to fit with drought severity and duration. The results of the bivariate analysis using copula showed that, according to both indicators, the study area will experience droughts with greater severity and duration in future as compared with the historical period, and the drought represented by the SPEI is more severe than that associated with the SPI. Also, drought simulated using the RCP8.5 scenario was more severe than when using the other two scenarios. Finally, droughts with a longer return period will become more frequent in future.

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Section: Definition Of Drought Characteristics Based On Run Theorymentioning

confidence: 99%

Meteorological drought analysis using copula theory and drought indicators under climate change scenarios (RCP)

Mesbahzadeh

Mirakbari

Saravi

et al. 2019

Meteorological Applications

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“…Since SPI and RDI follow similar methodologies, their values should have the same statistical meaning and, thus, are comparable. Therefore, the same thresholds [34,36,37] for both of them were used to classify drought-wetness conditions (Table 2).…”

Section: Calculation Of Drought Indicesmentioning

confidence: 99%

Monitoring Recent Changes in Drought and Wetness in the Source Region of the Yellow River Basin, China

Ren

Liu

Shalamzari

et al. 2022

Water

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The source region of the Yellow River Basin (SRYRB) is not only sensitive to climate change and the vulnerable region of the ecological environment but also the primary runoff generating region of the Yellow River Basin (YRB). Its changes of drought and wetness profoundly impact water resources security, food production and ecological environment in the middle and downward reaches of YRB. In the context of global warming, based on daily precipitation, maximum and minimum temperature of 12 national meteorological stations around and within SRYRB during 1960–2015, this study obtained standardized precipitation index (SPI) and reconnaissance drought index (RDI) on 1-, 3-, 6- and 12-month scales, and then compared the consistency of SPI and RDI in many aspects. Finally, the temporal and spatial variation characteristics of drought and wetness in the SRYRB during 1960–2015 were analyzed in this study. The results showed that SPI and RDI have high consistency on different time scales (correlation coefficient above 0.92). According to the average distribution and change trend of the RDI, SRYRB presented an overall wetness state on different time scales. We found an increasing trend in wetness since the early 1980s. In terms of wetness events of different magnitudes, the highest frequency for moderate and severe ones was in June (12.7%) and February (5.5%), respectively, and for extreme wetness events, both September and January had the highest frequency (1.8%). Among the four seasons, the change rate of RDI in spring was the largest with a value of 0.38 decade−1, followed by winter (0.36 decade−1) and autumn (0.2 decade−1) and the smallest in summer (0.1 decade−1). There was a greater consistency between RDI values of larger time scales such as annual and vegetation growing seasonal (VGS) scales in SRYRB. There was generally a growing trend in wetness in the VGS time scale. These findings presented in this study can provide data support for drought and wetness management in SRYRB.

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“…In drought years, drought has been determined in 16 years winter, 15 years spring, 17 years summer and 20 years autumn season. Nedealcov et al (2015) compared the temporal and spatial distributions of drought for 3 and 6 monthly periods with SPEI and SPI indexes in Moldova between the 1980-2014 periods. In temporal distribution both index showed similar results.…”

Section: Figure 5 Comparison Of Long-term Drought Indices Spi-6 (Top)...mentioning

confidence: 99%

“…The Standardized Precipitation Evapotranspiration Index (SPEI) has been developed to evaluate the severity of agricultural drought by taking into account the evapotranspiration and meteorological drought in the environment where the crop is located (Vicente-Serrano, 2010a). In the determination of meteorological and agricultural drought, SPI and SPEI indexes have been conducted by different researchers on issues such as analysis, monitoring and comparison of the drought's spatial and temporal distribution (Alkan and Tombul, 2022;Şener, 2021;Bakanoğulları, 2020;Falzoi et al, 2019;Keskiner et al, 2019;Tefera et al, 2019;Bae et al, 2018;Çetin et al, 2018;Chen et al, 2018;Çamalan et al, 2017;Tong et al, 2017;Nedealcov et al, 2015;Stagge et al, 2015;Bakanoğulları and Yeşilköy, 2014;Kwak et al, 2013;Türkeş and Tatlı, 2009;Wilhite et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Assessment of Meteorological and Agricultural Drought Analysis in Kırklareli province

Bakanoğulları¹,

BAHAR²,

KIVRAK>³

et al. 2022

Tekirdağ Ziraat Fakültesi Dergisi

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The Global warming in the world cause to the climate change in this century. Agriculture is one of the sectors that can be most affected by climate change. Agricultural production is affected by precipitation and temperature variables. Due to the changes in these two parameters, the increase in the temperatures and the changes in the amount of precipitation in parallel with this disrupt the ecological balance and bring along the problems of desertification and drought. Agricultural production is highly dependent on meteorological factors in Thrace region. For this reason, it is expected that changes in climatic factors will affect the agriculture of the region positively or negatively. The aim of this study is to determine the frequency and severity of meteorological and agricultural drought with two indexes between 1963-2019 years in Kırklareli province. Standardized Precipitation Evapotranspiration Index (SPEI) was used to determine monthly, seasonal, six monthly and annual agricultural drought. According to annual agricultural drought results, it was calculated ten years mild arid (1969, 1985, 1986, 1990, 1991, 1992, 1993, 2011, 2016, and 2019), five years moderate arid (1983, 1989, 1996, 2008, and 2015), one year severe arid (1994), and two years extreme arid (2000 and 2001). Another drought index which is Standardized Precipitation Index (SPI) was used to determine meteorological drought. According to annual meteorological drought results, Eight years mild arid (1964, 1969, 1982, 1985, 1986, 1990, 1991, and 2011), seven years moderate arid (1983, 1989, 1992, 1993, 1994, 1996, and 2008), and two years extreme arid (2000, 2001) was figured out. According to linear correlation analysis, a good correlation was obtained for SPI and SPEI values, between annual, six monthly (Spring-Summer), and three monthly only winter and spring periods (R2=0.871, R2=0.901, R2=0.974, and R2=0.919), respectively. In the 57-year observation period; 18 years were determined as the arid year with SPEI index and 67% of these total arid years (12 arid years) occurred and 17 years were determined as the arid year with SPI index and 76% of these total arid years (13 arid years) occurred, between 1982 and 2002 years. The SPEI drought index which use precipitation, temperature and evapotranspiration data could give much good results to policy makers in drought mitigation policies in terms of giving results that are more accurate in agricultural production and drought assessments.

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The Use Of Standardized Indicators (SPI And SPEI) In Predicting Droughts Over The Republic Of Moldova Territory

Abstract: The drought events frequent manifestation over the Republic of Moldova territory, in the context of climate change requires a scientific monitoring adjusted to international researchers.

Cited by 15 publications

References 1 publication

Meteorological drought analysis using copula theory and drought indicators under climate change scenarios (RCP)

Meteorological drought analysis using copula theory and drought indicators under climate change scenarios (RCP)

Monitoring Recent Changes in Drought and Wetness in the Source Region of the Yellow River Basin, China

Assessment of Meteorological and Agricultural Drought Analysis in Kırklareli province

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