Drought analysis in New Zealand using the standardized precipitation index

2017 ◽  
Vol 76 (16) ◽  
Author(s):  
Tommaso Caloiero
2019 ◽  
Vol 11 (1-2) ◽  
pp. 199-216
Author(s):  
R Afrin ◽  
F Hossain ◽  
SA Mamun

Drought is an extended period when a region notes a deficiency in its water supply. The Standardized Precipitation Index (SPI) method was used in this study to analyze drought. Northern region of Bangladesh was the area of study. Monthly rainfall data of northern region of Bangladesh was obtained from the Meteorological Department of Bangladesh. Obtained rainfall data was from 1991 to 2011 and values from 2012 to 2026 were generated using Markov model. Then SPI values from 1991 to 2026 were calculated by using SPI formula for analyzing drought. Analysis with SPI method showed that droughts in northern region of Bangladesh varied from moderately dry to severely dry conditions and it may vary from moderately dry to severely dry conditions normally in future but in some cases extreme drought may also take place. From the study, it is observed that the northern region of Bangladesh has already experienced severe drought in 1991, 1992, 1994, 1995, 1997, 1998, 2000, 2003, 2005, 2007, 2009 and 2010. The region may experience severe drought in 2012, 2015, 2016, 2018, 2019, 2021, 2022, 2023, 2024, 2025 and 2026 and extreme drought in 2012, 2014, 2016, 2023 and 2024. J. Environ. Sci. & Natural Resources, 11(1-2): 199-216 2018


2005 ◽  
Vol 9 (5) ◽  
pp. 523-533 ◽  
Author(s):  
S. M. Vicente-Serrano ◽  
J. I. López-Moreno

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.


2013 ◽  
Vol 17 (6) ◽  
pp. 2359-2373 ◽  
Author(s):  
E. Dutra ◽  
F. Di Giuseppe ◽  
F. Wetterhall ◽  
F. Pappenberger

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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