scholarly journals Drought severity and change in Xinjiang, China, over 1961–2013

2016 ◽  
Vol 48 (5) ◽  
pp. 1343-1362 ◽  
Author(s):  
Yi Li ◽  
Chunyan Chen ◽  
Changfeng Sun
Keyword(s):  
Global Warming ◽  
Reference Evapotranspiration ◽  
Standardized Precipitation Index ◽  
Drought Severity ◽  
Climatic Data ◽  
Standardized Precipitation Evapotranspiration Index ◽  
Water Utilization ◽  
Monthly Climatic Data ◽  
Increasing Trends ◽  
Southern Xinjiang

Monthly climatic data from 53 sites across Xinjiang, China, were used to compare drought severity from the widely accepted Standardized Precipitation Index (SPI) with the recently proposed Standardized Precipitation Evapotranspiration Index (SPEI), as well as trends in the data from 1961 to 2013. Monthly Thornthwaite based (ETo.TW) and Penman-Monteith based reference evapotranspiration (ETo.PM) were computed and subsequently used to estimate SPEITW and SPEIPM, respectively. The indices' sensitivity, spatiotemporal distributions and trends were analyzed. The results showed that the TW equation underestimated ETo, which affected the accuracy of the SPEI estimation. Greater consistency was found between SPI and SPEIPM than between SPI and SPEITW at different timescales. SPI and SPEIPM were sensitive to precipitation, but SPEITW and SPEIPM were insensitive to ETo. The scope of spatial SPEIPM was wider than that of SPI at the same timescale. Obvious differences in SPI, SPEITW and SPEIPM existed between northern and southern Xinjiang. SPEIPM was a better indicator of global warming than SPI. Both SPI and SPEIPM had increasing trends, which contradict previously reported trends in global drought. In conclusion, the decrease in drought severity observed over the last 53 years may indicate some relief in the water utilization crisis in Xinjiang, China.

A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index

2010 ◽  
Vol 23 (7) ◽  
pp. 1696-1718 ◽  
Author(s):  
Sergio M. Vicente-Serrano ◽  
Santiago Beguería ◽  
Juan I. López-Moreno
Keyword(s):  
Global Warming ◽  
Water Balance ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Severity Index ◽  
Drought Severity ◽  
Standardized Precipitation Evapotranspiration Index ◽  
Drought Assessment ◽  
The Standardized Precipitation Index

Abstract The authors propose a new climatic drought index: the standardized precipitation evapotranspiration index (SPEI). The SPEI is based on precipitation and temperature data, and it has the advantage of combining multiscalar character with the capacity to include the effects of temperature variability on drought assessment. The procedure to calculate the index is detailed and involves a climatic water balance, the accumulation of deficit/surplus at different time scales, and adjustment to a log-logistic probability distribution. Mathematically, the SPEI is similar to the standardized precipitation index (SPI), but it includes the role of temperature. Because the SPEI is based on a water balance, it can be compared to the self-calibrated Palmer drought severity index (sc-PDSI). Time series of the three indices were compared for a set of observatories with different climate characteristics, located in different parts of the world. Under global warming conditions, only the sc-PDSI and SPEI identified an increase in drought severity associated with higher water demand as a result of evapotranspiration. Relative to the sc-PDSI, the SPEI has the advantage of being multiscalar, which is crucial for drought analysis and monitoring.

Uncertainties in the variation of compound dry and hot events due to differences in drought indices

2021 ◽  
Author(s):  
Sifang Feng ◽  
Zengchao Hao
Keyword(s):  
Palmer Drought Severity Index ◽  
Standardized Precipitation Index ◽  
Severity Index ◽  
Drought Indices ◽  
Drought Severity ◽  
Standardized Precipitation Evapotranspiration Index ◽  
The Past ◽  
Drought Indicators ◽  
The Difference ◽  
Negative Impacts

<p>Compound dry and hot events (CDHEs) are commonly defined as the concurrent or consecutive occurrences of the two events, which could lead to larger negative impacts than do individual extremes. The variation of CDHEs has gained increased attention in the past decades. Previous studies have detected changes in the frequency, duration, and spatial extent at regional and global scales based on observations and model simulations. However, these studies mainly focus on a single drought indicator. In the past decades, different drought indicators have been applied to characterize drought conditions, such as Standardized Precipitation Index (SPI), and Standardized Precipitation-Evapotranspiration Index (SPEI), and Palmer Drought Severity Index (PDSI). Due to the difference in these drought indicators in characterizing droughts, evaluation of CDHEs based on different drought indices may lead to a different magnitude of changes (or even opposite direction of changes). However, quantitative analysis of the uncertainties in the variation of CDHEs is still lacking. In this study, we quantitatively evaluate the uncertainties of CDHEs variations ove global areas due to differences in drought indices. Results from this study could further our understanding of changes in CDHEs under global warming.</p>

scholarly journals Global Warming Impacts on Severe Drought Characteristics in Asia Monsoon Region

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1360 ◽  
Author(s):  
Jeong-Bae Kim ◽  
Jae-Min So ◽  
Deg-Hyo Bae
Keyword(s):  
Global Warming ◽  
Standardized Precipitation Index ◽  
Global Climate Models ◽  
Cold Climate ◽  
Drought Severity ◽  
Severe Drought ◽  
Monsoon Region ◽  
Climate Zones ◽  
Drought Characteristics ◽  
Dry Spell

Climate change influences the changes in drought features. This study assesses the changes in severe drought characteristics over the Asian monsoon region responding to 1.5 and 2.0 °C of global average temperature increases above preindustrial levels. Based on the selected 5 global climate models, the drought characteristics are analyzed according to different regional climate zones using the standardized precipitation index. Under global warming, the severity and frequency of severe drought (i.e., SPI <−1.5) are modulated by the changes in seasonal and regional precipitation features regardless of the region. Due to the different regional change trends, global warming is likely to aggravate (or alleviate) severe drought in warm (or dry/cold) climate zones. For seasonal analysis, the ranges of changes in drought severity (and frequency) are −11.5%~6.1% (and −57.1%~23.2%) under 1.5 and 2.0 °C of warming compared to reference condition. The significant decreases in drought frequency are indicated in all climate zones due to the increasing precipitation tendency. In general, drought features under global warming closely tend to be affected by the changes in the amount of precipitation as well as the changes in dry spell length. As the warming enhanced, the spatial variation of drought severity will be increased across climate zones, which can lead to increased water stress over Asia. This study demonstrates that precipitation characteristic changes can explicitly modulate severe regional drought features.

Extreme aridity in the south-eastern part of Romania

2021 ◽  
Author(s):  
Viorica Nagavciuc ◽  
Monica Ionita ◽  
Cătălin-Constantin Roibu
Keyword(s):  
Agricultural Land ◽  
Standardized Precipitation Index ◽  
Severity Index ◽  
Drought Indices ◽  
Drought Severity ◽  
Significant Shift ◽  
Strong Impact ◽  
Standardized Precipitation Evapotranspiration Index ◽  
The South ◽  
South Eastern

&lt;p&gt;Drought is one of the most complex phenomena which may have a strong impact on agriculture, society, water resources, and ecosystems. In Romania, drought has a very strong impact on agriculture and affects 7.1 million ha, which represent 48% of the total agricultural land. The south, southeast, and eastern parts of Romania, including the Dobrogea region, are the most affected areas. During extremely dry years the average yields of various crops represent only 35% &amp;#247; 60% of the potential yields. By employing three different drought indices (e.g. the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI) and the Palmer Drought Severity Index (PDSI), we show that there is a significant trend towards aridity especially from the 1980&amp;#8217;s up to present in the south-eastern part of Romania. The Standardized Precipitation-Evapotranspiration Index (SPEI) at Sulina station (situated in the Doborgea region) for 12 months (SPEI12) indicates that over the last 30 years, this region was continuously affected by prolong droughts and there is a statistically significant shift towards dryer periods over the last 30 years compared to the period 1877 &amp;#8211; 1990, thus indicating a critical situation for this region. Over the last 30 years, the long-term drought variability (SPI12, SPEI12, and PDSI) has increased both in duration and intensity up to maximum rates. The driest summers on record, over the region, are 2001, 2003 and 2007. These extremely dry summers are unprecedented throughout the observational record (~145 years). The history of drought in Dobrogea includes also many dry years, of which are to be mentioned: 1894, 1888, 1904, 1918, 1934, 1945.&lt;/p&gt;

scholarly journals Assessment of the Dissimilarities of EDI and SPI Measures for Drought Determination in South Africa

Water ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 82
Author(s):  
Omolola M. Adisa ◽  
Muthoni Masinde ◽  
Joel O. Botai
Keyword(s):  
South Africa ◽  
South African ◽  
Correlation Coefficient ◽  
Pearson Correlation ◽  
Standardized Precipitation Index ◽  
Drought Monitoring ◽  
Drought Indices ◽  
Drought Severity ◽  
Pearson Correlation Coefficient ◽  
Drought Duration

This study examines the (dis)similarity of two commonly used indices Standardized Precipitation Index (SPI) computed over accumulation periods 1-month, 3-month, 6-month, and 12-month (hereafter SPI-1, SPI-3, SPI-6, and SPI-12, respectively) and Effective Drought Index (EDI). The analysis is based on two drought monitoring indicators (derived from SPI and EDI), namely, the Drought Duration (DD) and Drought Severity (DS) across the 93 South African Weather Service’s delineated rainfall districts over South Africa from 1980 to 2019. In the study, the Pearson correlation coefficient dissimilarity and periodogram dissimilarity estimates were used. The results indicate a positive correlation for the Pearson correlation coefficient dissimilarity and a positive value for periodogram of dissimilarity in both the DD and DS. With the Pearson correlation coefficient dissimilarity, the study demonstrates that the values of the SPI-1/EDI pair and the SPI-3/EDI pair exhibit the highest similar values for DD, while the SPI-6/EDI pair shows the highest similar values for DS. Moreover, dissimilarities are more obvious in SPI-12/EDI pair for DD and DS. When a periodogram of dissimilarity is used, the values of the SPI-1/EDI pair and SPI-6/EDI pair exhibit the highest similar values for DD, while SPI-1/EDI displayed the highest similar values for DS. Overall, the two measures show that the highest similarity is obtained in the SPI-1/EDI pair for DS. The results obtainable in this study contribute towards an in-depth knowledge of deviation between the EDI and SPI values for South Africa, depicting that these two drought indices values are replaceable in some rainfall districts of South Africa for drought monitoring and prediction, and this is a step towards the selection of the appropriate drought indices.

scholarly journals Developing Objective Operational Definitions for Monitoring Drought

2009 ◽  
Vol 48 (6) ◽  
pp. 1217-1229 ◽  
Author(s):  
Steven M. Quiring
Keyword(s):  
Water Conservation ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Severity Index ◽  
Decision Makers ◽  
Drought Severity ◽  
Specific Method ◽  
The Standardized Precipitation Index ◽  
Spatially Variant ◽  
Objective Methodology

Abstract Drought is a complex phenomenon that is difficult to accurately describe because its definition is both spatially variant and context dependent. Decision makers in local, state, and federal agencies commonly use operational drought definitions that are based on specific drought index thresholds to trigger water conservation measures and determine levels of drought assistance. Unfortunately, many state drought plans utilize operational drought definitions that are derived subjectively and therefore may not be appropriate for triggering drought responses. This paper presents an objective methodology for establishing operational drought definitions. The advantages of this methodology are demonstrated by calculating meteorological drought thresholds for the Palmer drought severity index, the standardized precipitation index, and percent of normal precipitation using both station and climate division data from Texas. Results indicate that using subjectively derived operational drought definitions may lead to over- or underestimating true drought severity. Therefore, it is more appropriate to use an objective location-specific method for defining operational drought thresholds.

scholarly journals Evaluation of a High-Resolution SPI for Monitoring Local Drought Severity

2016 ◽  
Vol 55 (10) ◽  
pp. 2247-2262 ◽  
Author(s):  
Rebecca V. Cumbie-Ward ◽  
Ryan P. Boyles
Keyword(s):  
United States ◽  
High Resolution ◽  
Standardized Precipitation Index ◽  
Stage Iv ◽  
Drought Severity ◽  
Cluster Solution ◽  
Historical Distribution ◽  
Drought Conditions ◽  
Hydrologic Prediction ◽  
Strong Agreement

AbstractA standardized precipitation index (SPI) that uses high-resolution, daily estimates of precipitation from the National Weather Service over the contiguous United States has been developed and is referred to as HRD SPI. There are two different historical distributions computed in the HRD SPI dataset, each with a different combination of normals period (1971–2000 or 1981–2010) and clustering solution of gauge stations. For each historical distribution, the SPI is computed using the NCEP Stage IV and Advanced Hydrologic Prediction Service (AHPS) gridded precipitation datasets for a total of four different HRD SPI products. HRD SPIs are found to correlate strongly with independently produced SPIs over the 10-yr period from 2005 to 2015. The drought-monitoring utility of the HRD SPIs is assessed with case studies of drought in the central and southern United States during 2012 and over the Carolinas during 2007–08. A monthly comparison between HRD SPIs and independently produced SPIs reveals generally strong agreement during both events but weak agreement in areas where radar coverage is poor. For both study regions, HRD SPI is compared with the U.S. Drought Monitor (USDM) to assess the best combination of precipitation input, normals period, and station clustering solution. SPI generated with AHPS precipitation and the 1981–2010 PRISM normals and associated cluster solution is found to best capture the spatial extent and severity of drought conditions indicated by the USDM. This SPI is also able to resolve local variations in drought conditions that are not shown by either the USDM or comparison SPI datasets.

scholarly journals COMPARAÇÃO ENTRE MÉTODOS DE ESTIMATIVA DA EVAPOTRANSPIRAÇÃO DE REFERÊNCIA PARA O MUNICÍPIO DE PETROLINA, PE

Irriga ◽  
2017 ◽  
Vol 1 (1) ◽  
pp. 31-39 ◽  
Author(s):  
Roberta Daniela Silva Santos ◽  
Marcello Henryque Costa de Souza ◽  
Regiane De Carvalho Bispo ◽  
Kevim Muniz Ventura ◽  
Luis Henrique Bassoi
Keyword(s):  
Reference Evapotranspiration ◽  
Estimation Method ◽  
Arid Climate ◽  
Estimation Methods ◽  
Coefficient Of Determination ◽  
Climatic Data ◽  
Test Field ◽  
Rating Method ◽  
And Performance ◽  
Semi Arid

COMPARAÇÃO ENTRE MÉTODOS DE ESTIMATIVA DA EVAPOTRANSPIRAÇÃO DE REFERÊNCIA PARA O MUNICÍPIO DE PETROLINA, PE  ROBERTA DANIELA DA SILVA SANTOS1; MARCELLO HENRYQUE COSTA DE SOUZA1; REGIANE DE CARVALHO BISPO1; KEVIM MUNIZ VENTURA1 E LUÍS HENRIQUE BASSOI2 1Programa de Pós-Graduação em Irrigação e Drenagem, Universidade Estadual Paulista “Júlio de Mesquita Filho”- UNESP/FCA, Rua Dr. José Barbosa de Barros, 1780, Botucatu, SP, [email protected], [email protected], [email protected], [email protected] Embrapa Instrumentação, São Carlos, SP, [email protected]  1 RESUMO O conhecimento da evapotranspiração é vital na determinação das necessidades hídricas de uma cultura. Diante disso, o objetivo deste trabalho foi comparar o desempenho de sete métodos de estimativa da evapotranspiração de referência em relação ao método de Penman-Monteith, adotado como padrão, para o município de Petrolina, PE. Foram utilizados dados climáticos diários de 2004 a 2015, para estimar da ET0, obtidos na estação meteorológica automática do Campo Experimental de Bebedouro da Embrapa Semiárido, Petrolina, PE. Os indicadores estatísticos utilizados na avaliação foram: coeficiente de determinação (r²); coeficiente de correlação (r); índice de concordância (d) e índice de desempenho (c). Os valores do r² mostraram que o método de estimativa que melhor se ajustou ao método de Penman-Monteith foi o de Ivanov (0,73); seguido pelos métodos de Jensen-Haise (0,64); Makkink e Priestley-Taylor (0,63); Villa Nova (0,62); Hargreaves e Samani (0,53) e Hamon (0,45). No entanto, com relação ao do índice “c”, Hamon foi classificado com “péssimo”; Makkink como “mau”; Hargreaves e Samani e Villa Nova como “sofrível”; Ivanov e Priestley-Taylor como “mediano”; e Jensen-Haise como “bom”. Esse último método foi considerado como o de melhor classificação de desempenho. Palavras-chave: Penman-Monteith, correlação, semiárido.  SANTOS, R. D. S.; SOUZA, M. H. C.; BISPO, R. de C.; VENTURA, K. M.; BASSOI, L. H.METHOD-COMPARISON STUDY TO ESTIMATE THE REFERENCE EVAPOTRANSPIRATION IN PETROLINA, PE  2 ABSTRACT The knowledge on evapotranspiration is vital in determining the water requirements of a crop. Therefore, this paper aims to compare the performance of seven of estimation methods for the reference evapotranspiration in relation to the Penman-Monteith method, adopted as standard, for the municipality of Petrolina, state of Pernambuco, Brazil. We used daily climatic data from 2004 to 2015 to estimate the ET0 coefficient, obtained in the automatic weather station of the Test Field in Bebedouro, Embrapa in the Semi-arid climate. The statistical indicators used in the evaluation were: coefficient of determination (r²), correlation coefficient (r), agreement index (d) and performance index (c). The r2 values showed that the estimation method that best fitted to the Penman-Monteith method was Ivanov's (0.73), followed by Jensen-Haise (0.64), Makkink and Priestley-Taylor (0.63), Villa Nova (0.62), Hargreaves and Samani (0.53) and Hamon (0.45) methods. However, in relation to the index "c", Hamon was classified as "very poor"; Makkink as "poor"; Hargreaves and Samani and Villa Nova as "tolerable"; Ivanov and Priestley-Taylor as "medium"; and Jensen-Haise as "good". The last one was considered as the best performance rating method. Keywords: Penman-Monteith, correlation, semi-arid climate.

scholarly journals Modeling, prediction and trend assessment of drought in Iran using standardized precipitation index

2018 ◽  
Vol 10 (1) ◽  
pp. 181-196 ◽  
Author(s):  
Mehdi Bahrami ◽  
Samira Bazrkar ◽  
Abdol Rassoul Zarei
Keyword(s):  
Time Series ◽  
Moving Average ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Occurrence Frequency ◽  
Natural Phenomenon ◽  
Drought Severity ◽  
Data Series ◽  
Climate Data ◽  
Seasonal Drought

Abstract Drought as an exigent natural phenomenon, with high frequency in arid and semi-arid regions, leads to enormous damage to agriculture, economy, and environment. In this study, the seasonal Standardized Precipitation Index (SPI) drought index and time series models were employed to model and predict seasonal drought using climate data of 38 Iranian synoptic stations during 1967–2014. In order to model and predict seasonal drought ITSM (Interactive Time Series Modeling) statistical software was used. According to the calculated seasonal SPI, within the study area, drought severity classes 4 and 3 had the greatest occurrence frequency, while classes 6 and 7 had the least occurrence frequency. Results indicated that the best fitted models were Moving-Average or MA (5) Innovations and MA (5) Hannan-Rissenen, with 60.53 and 15.79 percentage, respectively. On the other hand, results of the prediction as well, indicated that drought class 4 with the highest percentages, was the most abundant class over the study area and drought class 7 was the least frequent class. According to results of trend analysis, without attention to significance of them, observed seasonal SPI data series (1967–2014), in 84.21% of synoptic stations had a negative trend, but this percentage changes to 86.84% when studying the combination of observed and predicted simultaneously (1967–2019).

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