Spatiotemporal characteristics of drought in a semi-arid grassland over the past 56 years based on the Standardized Precipitation Index

2020 ◽  
Author(s):  
Wei Li ◽  
Limin Duan ◽  
Wenjun Wang ◽  
Yingjie Wu ◽  
Tingxi Liu ◽  
...  
Keyword(s):  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
The Past ◽  
Spatiotemporal Characteristics ◽  
The Standardized Precipitation Index ◽  
Semi Arid

scholarly journals Integrated TRMM Data and Standardized Precipitation Index to Monitor the Meteorological Drought

2019 ◽  
Vol 5 (7) ◽  
pp. 1590-1598 ◽  
Author(s):  
Zaidoon T. Abdulrazzaq ◽  
Raghad H. Hasan ◽  
Nadia A. Aziz
Keyword(s):  
Meteorological Data ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Precipitation Index ◽  
Northeast Region ◽  
Drought Assessment ◽  
Monitoring And Forecasting ◽  
Southwest Region ◽  
The Standardized Precipitation Index ◽  
Semi Arid

Droughts are a major problem in Iraq especially in the Arid and Semi-Arid Lands where they are frequent and causes a great deal of suffering and loss. Drought monitoring and forecasting requires extensive climate and meteorological data which is usually largely missing in developing countries or not available in the required spatial and temporal resolutions. In this study, the drought categories were defined for the years 2000, 2005, 2010, 2015 and 2017 using the TRMM data to map the spatiotemporal meteorological drought, and the Standardized Precipitation Index (SPI) to analyze the meteorological drought at 11 stations located in Western Iraq. The SPI analyses were performed on 12-month datasets for five years. The results showed that the northeast region has the higher rainfall indices and the southwest region has the lowest rainfall. An analysis of the drought and rain conditions showed that the quantity of extreme drought events was higher than that expected in the study area, especially in the south and southwest areas. Therefore, an alternate classification is proposed to describe the drought, which spatially classifies the drought type as mild, moderate, severe and extreme. In conclusion, the integration between TRMM data SPI data proved to be an effective tool to map the spatial distribution and drought assessment in the study area.

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 Seasonal forecasts of droughts in African basins using the Standardized Precipitation Index

2013 ◽  
Vol 17 (6) ◽  
pp. 2359-2373 ◽  
Author(s):  
E. Dutra ◽  
F. Di Giuseppe ◽  
F. Wetterhall ◽  
F. Pappenberger
Keyword(s):  
Real Time ◽  
Lead Time ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Seasonal Forecasting ◽  
Monthly Precipitation ◽  
Seasonal Forecasts ◽  
Blue Nile ◽  
Forecasting System ◽  
The Standardized Precipitation Index

Abstract. Vast parts of Africa rely on the rainy season for livestock and agriculture. Droughts can have a severe impact in these areas, which often have a very low resilience and limited capabilities to mitigate drought impacts. This paper assesses the predictive capabilities of an integrated drought monitoring and seasonal forecasting system (up to 5 months lead time) based on the Standardized Precipitation Index (SPI). The system is constructed by extending near-real-time monthly precipitation fields (ECMWF ERA-Interim reanalysis and the Climate Anomaly Monitoring System–Outgoing Longwave Radiation Precipitation Index, CAMS-OPI) with monthly forecasted fields as provided by the ECMWF seasonal forecasting system. The forecasts were then evaluated over four basins in Africa: the Blue Nile, Limpopo, Upper Niger, and Upper Zambezi. There are significant differences in the quality of the precipitation between the datasets depending on the catchments, and a general statement regarding the best product is difficult to make. The generally low number of rain gauges and their decrease in the recent years limits the verification and monitoring of droughts in the different basins, reinforcing the need for a strong investment on climate monitoring. All the datasets show similar spatial and temporal patterns in southern and north-western Africa, while there is a low correlation in the equatorial area, which makes it difficult to define ground truth and choose an adequate product for monitoring. The seasonal forecasts have a higher reliability and skill in the Blue Nile, Limpopo and Upper Niger in comparison with the Zambezi. This skill and reliability depend strongly on the SPI timescale, and longer timescales have more skill. The ECMWF seasonal forecasts have predictive skill which is higher than using climatology for most regions. In regions where no reliable near-real-time data is available, the seasonal forecast can be used for monitoring (first month of forecast). Furthermore, poor-quality precipitation monitoring products can reduce the potential skill of SPI seasonal forecasts in 2 to 4 months lead time.

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