Drought and Flood Distribution Variation Based on SPI in Nanjing, China

2013 ◽  
Vol 295-298 ◽  
pp. 2116-2120
Author(s):  
Jian Fen Liu ◽  
Xing Nan Zhang ◽  
Hui Min Wang
Keyword(s):  
Time Series ◽  
Time Scales ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Precipitation Data ◽  
Temporal Scales ◽  
Drought And Flood ◽  
Three Stages ◽  
The Standardized Precipitation Index

Many drought and flood indices have been developed, the Standardized Precipitation Index (SPI) is one which has various temporal scales together to form an overall judgment of drought and flood and can be applied easily to different locations to identify and monitor drought and flood. Take Nanjing, China in the study as an example to analysis drought and flood variation by computing SPI values of four time scales including 3-months, 6-months, 12-months and 24-months, applying precipitation data from 1946-2000 of the study area. The results demonstrated SPI can be appropriate to analyze drought and flood variation of Nanjing, while the precipitation data were divided into three stages(1946-1963,1964-1981,1982-2000), the frequencies of various drought and flood classes from various time scales are different, particularly 12-months and 24-months. The time series is longer, the frequencies are more reliable and the differences more little.

scholarly journals Hydrological response to different time scales of climatological drought: an evaluation of the Standardized Precipitation Index in a mountainous Mediterranean basin

2005 ◽  
Vol 9 (5) ◽  
pp. 523-533 ◽  
Author(s):  
S. M. Vicente-Serrano ◽  
J. I. López-Moreno
Keyword(s):  
Time Scales ◽  
Hydrological Cycle ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Drought Indices ◽  
Long Time ◽  
The Standardized Precipitation Index ◽  
Hydrological Droughts ◽  
Different Time Scales

Abstract. At present, the Standardized Precipitation Index (SPI) is the most widely used drought index to provide good estimations about the intensity, magnitude and spatial extent of droughts. The main advantage of the SPI in comparison with other indices is the fact that the SPI enables both determination of drought conditions at different time scales and monitoring of different drought types. It is widely accepted that SPI time scales affect different sub-systems in the hydrological cycle due to the fact that the response of the different water usable sources to precipitation shortages can be very different. The long time scales of SPI are related to hydrological droughts (river flows and reservoir storages). Nevertheless, few analyses empirically verify these statements or the usefulness of the SPI time scales to monitor drought. In this paper, the SPI at different time scales is compared with surface hydrological variables in a big closed basin located in the central Spanish Pyrenees. We provide evidence about the way in which the longer (>12 months) SPI time scales may not be useful for drought quantification in this area. In general, the surface flows respond to short SPI time scales whereas the reservoir storages respond to longer time scales (7–10 months). Nevertheless, important seasonal differences can be identified in the SPI-usable water sources relationships. This suggests that it is necessary to test the drought indices and time scales in relation to their usefulness for monitoring different drought types under different environmental conditions and water demand situations.

scholarly journals Computation of the Standardized Precipitation Index (SPI) and Its Use to Assess Drought Occurrences in Cameroon over Recent Decades

2014 ◽  
Vol 53 (10) ◽  
pp. 2310-2324 ◽  
Author(s):  
Guy Merlin Guenang ◽  
F. Mkankam Kamga
Keyword(s):  
Time Scales ◽  
Goodness Of Fit ◽  
Standardized Precipitation Index ◽  
Research Unit ◽  
Distribution Functions ◽  
Precipitation Index ◽  
Severe Drought ◽  
East Anglia ◽  
The Standardized Precipitation Index ◽  
Short Time

AbstractThe standardized precipitation index (SPI) is computed and analyzed using 55 years of precipitation data recorded in 24 observation stations in Cameroon along with University of East Anglia Climate Research Unit (CRU) spatialized data. Four statistical distribution functions (gamma, exponential, Weibull, and lognormal) are first fitted to data accumulated for various time scales, and the appropriate functions are selected on the basis of the Anderson–Darling goodness-of-fit statistic. For short time scales (up to 6 months) and for stations above 10°N, the gamma distribution is the most frequent choice; below this belt, the Weibull distribution predominates. For longer than 6-month time scales, there are no consistent patterns of fitted distributions. After calculating the SPI in the usual way, operational drought thresholds that are based on an objective method are determined at each station. These thresholds are useful in drought-response decision making. From SPI time series, episodes of severe and extreme droughts are identified at many stations during the study period. Moderate/severe drought occurrences are intra-annual in short time scales and interannual for long time scales (greater than 9 months), usually spanning many years. The SPI calculated from CRU gridded precipitation shows similar results, with some discrepancies at longer scales. Thus, the spatialized dataset can be used to extend such studies to a larger region—especially data-scarce areas.

The Use of a High-Resolution Standardized Precipitation Index for Drought Monitoring and Assessment

2012 ◽  
Vol 51 (1) ◽  
pp. 68-83 ◽  
Author(s):  
D. Brent McRoberts ◽  
John W. Nielsen-Gammon
Keyword(s):  
High Resolution ◽  
Time Scales ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Regional Frequency Analysis ◽  
Drought Monitoring ◽  
Precipitation Data ◽  
Monitoring Tool ◽  
Daily Precipitation Data ◽  
Pearson Type

AbstractA high-resolution drought-monitoring tool was developed to assess drought on multiple time scales using the standardized precipitation index (SPI). Daily precipitation data at 4-km resolution are obtained from the Advanced Hydrologic Prediction Service multisensor precipitation estimates (MPE) and are aggregated on several time scales. Daily station precipitation data available from the Cooperative Observer Program (COOP) provide the historical context for the MPE precipitation data. Pearson type-III distribution parameters were interpolated to the 4-km grid on the basis of a regional frequency analysis of the COOP stations and L-moment ratios of the precipitation data. The resulting high-resolution SPI data can be used as guidance for the U.S. Drought Monitor at the subcounty scale in areas where local precipitation is the primary driver of drought. The temporal flexibility and spatial resolution of the drought-monitoring tool are used to illustrate the onset, intensity, and termination of the 2008–09 Texas drought, and the tool is shown to provide better county- and subcounty-scale information than do gauge-based products.

scholarly journals Hydrological response to different time scales of climatological drought: an evaluation of the standardized precipitation index in a mountainous mediterranean basin

2005 ◽  
Vol 2 (4) ◽  
pp. 1221-1246 ◽  
Author(s):  
S. M. Vicente-Serrano ◽  
J. I. López-Moreno
Keyword(s):  
Time Scales ◽  
Hydrological Cycle ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Drought Indices ◽  
Long Time ◽  
The Standardized Precipitation Index ◽  
Hydrological Droughts ◽  
Different Time Scales

Abstract. At present, the Standardized Precipitation Index (SPI) is the most widely used drought index to provide good estimations about the intensity, magnitude and spatial extent of droughts. The main advantage of the SPI in comparison with other indices is the fact that the SPI enables both determination of drought conditions at different time scales and monitoring of different drought types. It is widely accepted that SPI time scales affect different sub-systems in the hydrological cycle due to the fact that the response of the different water usable sources to precipitation shortages can be very different. The long time scales of SPI are related to hydrological droughts (river flows and reservoir storages). Nevertheless, few analyses empirically verify these statements or the usefulness of the SPI time scales to monitor drought. In this paper, the SPI at different time scales is compared with surface hydrological variables in a big closed basin located in the central Spanish Pyrenees. We provide evidence about the way in which the higher (>12 months) SPI time scales may not be useful for drought quantification in this area. In general, the surface flows respond to short SPI time scales whereas the reservoir storages respond to higher time scales (7–10 months). Nevertheless, important seasonal differences can be identified in the SPI-usable water sources relationships. This suggests that it is necessary to test the drought indices and time scales in relation to their usefulness for monitoring different drought types under different environmental conditions and water demand situations.

scholarly journals COMBINATION OF METEOROLOGICAL INDICES AND SATELLITE DATA FOR DROUGHT MONITORING IN TWO DIFFERENT ENVIRONMENTS IN IRAN

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 197-200
Author(s):  
M. Behifar ◽  
A. A. Kakroodi ◽  
M. Kiavarz ◽  
F. Amiraslani
Keyword(s):  
Satellite Data ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Precipitation Index ◽  
Drought Monitoring ◽  
Spatial Characteristic ◽  
Drought Indices ◽  
Precipitation Data ◽  
Spi Index ◽  
The Standardized Precipitation Index

Abstract. The main problem using meteorological drought indices include inappropriate distribution of meteorological stations. Satellite data have reliable spatial and temporal resolution and provide valuable information used in many different applications. The Standardized precipitation index has several advantages. The SPI is based on rainfall data alone and has a variable time scale and is thus conducive to describing drought conditions for different application.This study aims to calculate SPI using satellite precipitation data and compare the results with traditional methods. To do this, satellite-based precipitation data were assessed against station data and then the standardized precipitation index was calculated. The results have indicated that satellite-based SPI could illustrate drought spatial characteristic more accurate than station-based index. Also, the standardized property of the SPI index allows comparisons between different locations, which is one of the remote sensing drought indices limitations.

scholarly journals Assessing the changes in drought conditions during summer in the Republic of Moldova based on RegCM simulations

2013 ◽  
Vol 2 (3) ◽  
pp. 63 ◽  
Author(s):  
Vera Potop ◽  
Constanta Boroneant ◽  
Mihaela Caian
Keyword(s):  
Standardized Precipitation Index ◽  
Horizontal Resolution ◽  
Precipitation Index ◽  
Monthly Precipitation ◽  
Precipitation Data ◽  
Republic Of Moldova ◽  
Drought Conditions ◽  
The Republic ◽  
The Standardized Precipitation Index ◽  
Monthly Precipitation Data

We assess the changes in drought conditions during summer in the Republic of Moldova based on the Standardized Precipitation Index (SPI) calculated from monthly precipitation data simulated by the regional climatic model RegCM3. The RegCM simulations were conducted at a horizontal resolution of 10 km in the framework of EU-FP6 project -CECILIA. The domain was centered over Romania at 46°N, 25°E and included the Republic of Moldova.

scholarly journals Análise de Eventos Extremos na Região Amazônica (Analysis of Extreme Events in the Amazon Region)

2013 ◽  
Vol 6 (5) ◽  
pp. 1356 ◽  
Author(s):  
Thalyta Soares dos Santos ◽  
Ana Carla Dos Santos Gomes ◽  
Maytê Duarte Leal Coutinho ◽  
Allan Rodrigues Silva ◽  
Aline Anderson de Castro
Keyword(s):  
Time Series ◽  
Time Scales ◽  
Maximum Likelihood Method ◽  
Global Climate ◽  
Standardized Precipitation Index ◽  
Amazon Region ◽  
Likelihood Method ◽  
Monthly Precipitation ◽  
The Standardized Precipitation Index ◽  
Porto Velho

A frequência de eventos severos e extremos de seca e chuva na Amazônia foi analisada utilizando o Índice de Precipitação Normalizada (SPI) nas escalas de 6 (sazonal estação seca/chuvosa) e 12 meses (interanual). A frequência de eventos secos e chuvosos é importante para a climatologia da região, que é considerada um regulador climático global. Para isso foram selecionadas as séries climatológicas, de 1925 a 2000, de seis localidades da região Amazônica: Belém, Cuiabá, Iauretê, Manaus, Porto Velho, Taguatinga. Os SPIs, 6 e 12, que quantificam excesso ou déficit de chuva, nestas duas escalas de tempo, foram calculados a partir dos ajustes de distribuição gama, pelo método da máxima verossimilhança às médias móveis de 6 e 12 meses das precipitações mensais. Esses foram computados a partir da normalização das probabilidades gama, pelos seus respectivos desvios padrões. As séries temporais dos SPIs 6 e 12, mostram longos períodos de oscilação entre eventos secos e chuvosos. A frequência decenal de ambos SPIs indica variações entre as décadas mais chuvosas e secas nos municípios estudados. As décadas mais chuvosas e secas são periódicas para as duas escalas de tempo analisadas em todas as estações, exceto Iauretê. A B S T R A C T The frequency of severe and extremes events of drought and rainfall in the Amazon was analyzed using the Standardized Precipitation Index (SPI) in the scales of six months (dry/wet seasons) and 12 months (inter-annual). This is important for the climatology of the region, which is considered a global climate regulator. With this objective, the climatological series from 1925 to 2000 were selected for six locations in the Amazon region: Belém, Cuiabá, Iauretê, Manaus, Porto Velho and Taguatinga. With the aim of quantify the excess or deficit of rainfall in the selected time scales, the SPIs 6 and 12 were calculated using the fit of the gamma distribution by the maximum likelihood method for the moving averages 6 and 12 months of monthly precipitation. These were computed from the normalization of gamma probabilities by its standard deviation. The time series of SPIs 6 and 12, show long periods of oscillation between dry and wet events. The frequency of both SPIs indicates variations between wet and dry decades in the cities studied. Wetter and drier decades were shown to be periodic for the two time scales considered in all locations, except for Iauretê. Key-Words: SPI, Amazon, Drought, Rain

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