Temporal variability of meteorological drought monitoring using standardized precipitation index

2021 ◽  
Author(s):  
A. Vijay Kumar ◽  
Sanjeet Kumar
Keyword(s):  
Temporal Variability ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Precipitation Index ◽  
Drought Monitoring

scholarly journals DROUGHT MONITORING OVER PADDY FIELD AREA IN INDRAMAYU DISTRICT, WEST JAVA USING REMOTELY SENSED INDICES

2010 ◽  
Vol 5 (1) ◽  
Author(s):  
Parwati ◽  
Miao Jungang ◽  
Orbita Roswintiarti
Keyword(s):  
Soil Moisture ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Condition Index ◽  
Dry Season ◽  
Precipitation Index ◽  
Agricultural Drought ◽  
Drought Monitoring ◽  
West Java ◽  
Vegetation Health

In this research, several meteorological and agricultural drought indices based on remote sensing data are built for drought monitoring over paddy area in Indramayu District, West Java, Indonesia. The meteorological drought index of Standardized Precipitation Index (SPI) is developed from monthly Outgoing Long Wave Radiation (OLR) data from 1980 to 2005. The SPI represents the deficient of precipitation. Meanwhile, the agricultural drought of Vegetation Health Index (VHI) was developed from daily Moderate-resolution ImagingSpectroradiometer (MODIS) data during dry season (May-August) 2003-2006. The VHI was designed to monitoring vegetation health, soil moisture, and thermal conditions. The result shows that the agricultural drought occurate in Indramayu District, especially in the northern and southern part during the dry season in 2003 and 2004. It is found that there is a strong correlation between VHI and soil moisture measured in the field (r=0.84). Key words:Agricultural drought, Meteorological drought, Standardized Precipitation Index, Temperature Condition Index, Vegetation Condition 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 Prediction of Multi-Scalar Standardized Precipitation Index by Using Artificial Intelligence and Regression Models

Climate ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 28
Author(s):  
Anurag Malik ◽  
Anil Kumar ◽  
Priya Rai ◽  
Alban Kuriqi
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Inference ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Vital Role ◽  
Precipitation Index ◽  
Visual Interpretation ◽  
Inference System ◽  
Drought Prediction ◽  
Optimal Functioning

Accurate monitoring and forecasting of drought are crucial. They play a vital role in the optimal functioning of irrigation systems, risk management, drought readiness, and alleviation. In this work, Artificial Intelligence (AI) models, comprising Multi-layer Perceptron Neural Network (MLPNN) and Co-Active Neuro-Fuzzy Inference System (CANFIS), and regression, model including Multiple Linear Regression (MLR), were investigated for multi-scalar Standardized Precipitation Index (SPI) prediction in the Garhwal region of Uttarakhand State, India. The SPI was computed on six different scales, i.e., 1-, 3-, 6-, 9-, 12-, and 24-month, by deploying monthly rainfall information of available years. The significant lags as inputs for the MLPNN, CANFIS, and MLR models were obtained by utilizing Partial Autocorrelation Function (PACF) with a significant level equal to 5% for SPI-1, SPI-3, SPI-6, SPI-9, SPI-12, and SPI-24. The predicted multi-scalar SPI values utilizing the MLPNN, CANFIS, and MLR models were compared with calculated SPI of multi-time scales through different performance evaluation indicators and visual interpretation. The appraisals of results indicated that CANFIS performance was more reliable for drought prediction at Dehradun (3-, 6-, 9-, and 12-month scales), Chamoli and Tehri Garhwal (1-, 3-, 6-, 9-, and 12-month scales), Haridwar and Pauri Garhwal (1-, 3-, 6-, and 9-month scales), Rudraprayag (1-, 3-, and 6-month scales), and Uttarkashi (3-month scale) stations. The MLPNN model was best at Dehradun (1- and 24- month scales), Tehri Garhwal and Chamoli (24-month scale), Haridwar (12- and 24-month scales), Pauri Garhwal (12-month scale), Rudraprayag (9-, 12-, and 24-month), and Uttarkashi (1- and 6-month scales) stations, while the MLR model was found to be optimal at Pauri Garhwal (24-month scale) and Uttarkashi (9-, 12-, and 24-month scales) stations. Furthermore, the modeling approach can foster a straightforward and trustworthy expert intelligent mechanism for projecting multi-scalar SPI and decision making for remedial arrangements to tackle meteorological drought at the stations under study.

scholarly journals Análisis comparativo de índices de sequía en Andalucía para el periodo 1901-2012

2016 ◽  
Vol 42 (1) ◽  
pp. 67 ◽  
Author(s):  
M. Peña-Gallardo ◽  
S. R. Gámiz-Fortís ◽  
Y. Castro-Diez ◽  
M. J. Esteban-Parra
Keyword(s):  
Time Windows ◽  
Initial Period ◽  
Climatic Variability ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Precipitation Index ◽  
Drought Indices ◽  
Global Evaluation ◽  
Temporal Behaviour ◽  
The Standardized Precipitation Index

The aim of this paper is the analysis of the detection and evolution of droughts occurred in Andalusia for the period 1901-2012, by applying three different drought indices: the Standardized Precipitation Index (SPI), the Standardized Precipitation and Evapotranspiration Index (SPEI) and the Standardized Drought-Precipitation Index (IESP), computed for three time windows from the initial period 1901-2012. This analysis has been carried out after a preliminary study of precipitation trends with the intention of understanding the precipitation behaviour, because this climatic variable is one of the most important in the study of extreme events. The specific objectives of this study are: (1) to investigate and characterize the meteorological drought events, mainly the most important episodes in Andalusia; (2) to provide a global evaluation of the capacities of the three different considered indices in order to characterize the drought in a heterogeneous climatically territory; and (3) to describe the temporal behaviour of precipitation and drought indices series in order to establish the general characteristics of their evolution in Andalusia. The results have shown that not all the indices respond similarly identifying the intensity and duration of dry periods in this kind of region where geographical and climatic variability is one of the main elements to be considered.

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.

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