scholarly journals DROUGHT FORECAST USING ARIMA MODEL FOR THE STANDARDIZED PRECIPITATION INDEX (SPI) AND PRECIPITATION DATA

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Amr M El Dakak ◽  
Saleh O. K. ◽  
Eman A Elnikhely
Keyword(s):  
Arima Model ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Precipitation Data ◽  
The Standardized Precipitation Index

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 A Hybrid Wavelet-Arima Model for Standardized Precipitation Index Drought Forecasting

MATEMATIKA ◽  
2020 ◽  
Vol 36 (2) ◽  
pp. 141-156
Author(s):  
Alfa Mohammed Salisu ◽  
Ani Shabri
Keyword(s):  
Wavelet Transform ◽  
Arima Model ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Discrete Wavelet ◽  
Mean Square ◽  
Drought Forecasting ◽  
Error Measure ◽  
Auto Regressive ◽  
The Standardized Precipitation Index

ABSTRACTThis paper proposes A Hybrid Wavelet-Auto-Regressive Integrated MovingAverage (W-ARIMA) model to explore the ability of the hybrid model over an ARIMAmodel. It combines two methods, a Discrete Wavelet Transform (DWT) and ARIMAmodel using the Standardized Precipitation Index (SPI) drought data for forecastingdrought modeling development. SPI data from January 1954 to December 2008 used wasdivided into two - (80%/20% for training/testing respectively). The results were comparedwith the conventional ARIMA model with Mean Square Error (MSE) and Mean AverageError (MAE) as an error measure. The results of the proposed method achieved the bestforecasting performance.

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.

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 Categorical Forecast of Precipitation Anomaly Using the Standardized Precipitation Index SPI

2016 ◽  
Author(s):  
Leszek Łabędzki
Keyword(s):  
Contingency Table ◽  
Standardized Precipitation Index ◽  
Forecast Accuracy ◽  
Precipitation Anomaly ◽  
Precipitation Index ◽  
Precipitation Data ◽  
Precipitation Anomalies ◽  
The Standardized Precipitation Index ◽  
Good Agreement

In the paper the verification of forecasts of precipitation conditions measured by the standardized precipitation index SPI is presented. For the verification of categorical forecasts a contingency table was used. Standard verification measures were used for the SPI value forecast. The 30 day SPI moved every 10 days by 10 days was calculated in 2013-2015 from April to September on the basis of precipitation data from 35 meteorological stations in Poland. Predictions of the 30 day SPI were created in which precipitation was forecasted in the next 10 days (the SPI 10-day forecast) and 20 days (the SPI 20-day forecast). Both for the 10 and 20 days, the forecasts were skewed towards drier categories at the expense of wet categories. There was a good agreement between observed and 10-day forecast categories of precipitation. Less agreement is obtained for 20-day forecasts – these forecasts evidently “over-dry” the assessment of precipitation anomalies. The 10-day SPI value forecast accuracy is acceptable, whereas for the 20-day forecast is unsatisfactory. Both for the SPI categorical and the SPI value forecast, the 10-day SPI forecast is reliable and the 20-day forecast should be accepted with reservation and used with caution.

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.

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