scholarly journals Geographic Information Systems Application to Drought Distribution Identification with Standardized Precipitation Index (SPI) Method in Trenggalek Regency

2021 ◽  
Vol 5 (2) ◽  
pp. 266-278
Author(s):  
Aditya Utama ◽  
Mohammad Pramono Hadi ◽  
Emilya Nurjani
Keyword(s):  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Analysis Method ◽  
A Value ◽  
Distance Weighted ◽  
Calculation Results ◽  
Negative Impacts ◽  
The Standardized Precipitation Index ◽  
Inverse Distance ◽  
Rain Data

The widespread drought area in Trenggalek Regency in 2019 needs to be analyzed to reduce negative impacts and as a monitoring tool to anticipate future drought events. The Standardized Precipitation Index (SPI) is a drought analysis method by calculating the rainwater deficit at various time scales used to identify the distribution of drought in Trenggalek Regency. This study using rain data on 13 rain stations for the period 1990-2019 and agricultural production data for 2019. The calculation results show that the highest SPI value occurred in March at the highly wet level with a value of 2.11. The lowest SPI value occurred in May at the extremely dry level with a value of -2.31. The results are then mapped using ArcGIS with the Inverse Distance Weighted (IDW) method to identify the spatial distribution of drought.

scholarly journals Meteorological Drought Index Mapping in Bangladesh Using Standardized Precipitation Index during 1981–2010

2017 ◽  
Vol 2017 ◽  
pp. 1-17 ◽  
Author(s):  
Md. Anarul Haque Mondol ◽  
Iffat Ara ◽  
Subash Chandra Das
Keyword(s):  
Drought Index ◽  
Management Strategies ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Precipitation Index ◽  
Spatiotemporal Variations ◽  
Distance Weighted ◽  
Index Mapping ◽  
The Standardized Precipitation Index ◽  
Inverse Distance

Natural disasters are a major concern in Bangladesh, particularly drought which is one of the most common disaster in Bangladesh. Drought needs to be explained spatially to understand its spatiotemporal variations in different areas. In this paper, the meteorological drought has been shown by using the Standardized Precipitation Index (SPI) method and illustrated through the Inverse Distance Weighted (IDW) method across Bangladesh. We used rainfall data of 30 meteorological stations in Bangladesh during the study period of 1981–2010. The results indicate that drought has been fluctuating and it has become a recurrent phenomenon during the study period. The SPI depicted the drought conditions that plunged dramatically in 1981, 1982, 1985, 1987, 1989, 1992, 1994, and 1996 and then gradually improved in 2004, 2006, and 2009 in the country. The present study demonstrated that drought occurred in Bangladesh on an average of 2.5 years. Drought was more prominent in the northern, south-western, and eastern regions in Bangladesh compared to the rest of the areas of the country. The outcomes of the present study will help in during disaster management strategies, particularly drought, by initiating effective plans and adaptation remedies in different areas of Bangladesh.

scholarly journals Đánh giá thực trạng khô hạn tại tỉnh Bến Tre

2021 ◽  
Vol 57 (Environment and Climate change) ◽  
pp. 148-157
Author(s):  
Xuân Mai ◽  
Tấn Lợi Lê
Keyword(s):  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Inverse Distance Weighted ◽  
Distance Weighted ◽  
Inverse Distance

Điều kiện khô hạn trong giai đoạn 2015 - 2019 được đánh giá trong nghiên cứu nhằm phục vụ sản xuất nông nghiệp trên địa bàn tỉnh Bến Tre. Các dữ liệu về điều kiện thời tiết được thu thập tại Đài Khí tượng Thủy văn Bến Tre; phương pháp nội suy IDW (Inverse Distance Weighted) được áp dụng để xây dựng bản đồ khô hạn; mức độ ảnh hưởng của khô hạn được đánh giá dựa vào chỉ số SPI (Standardized Precipitation Index). Kết quả nghiên cứu cho thấy Bến Tre có 4 vùng hạn theo các mức độ nặng, trung bình, nhẹ và không hạn. Mức độ hạn nặng và trung bình cao nhất năm 2015, 2016; các năm còn lại hạn ở mức nhẹ. Tuy nhiên, diện tích khô hạn năm 2019 là cao nhất và giảm dần theo năm 2017, 2016, 2015, 2018. Khô hạn đã và đang ảnh hưởng đến các mô hình canh tác nông nghiệp ở tỉnh Bến Tre. Vì vậy, nghiên cứu thêm về ảnh hưởng của khô hạn đến sản xuất nông nghiệp, có những định hướng sử dụng đất hợp lý và bền vững trong điều kiện ở tỉnh Bến Tre là cần thiết.

scholarly journals Analyzing Wetness and Dryness Severity in Bangladesh: Using Standardized Precipitation Index (SPI) in GIS Environment

2015 ◽  
Vol 7 (2) ◽  
pp. 127-131
Author(s):  
NMR Nasher ◽  
MN Uddin
Keyword(s):  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Eastern Region ◽  
Time Period ◽  
Daily Precipitation Data ◽  
Distance Weighting ◽  
Central Regions ◽  
Gis Environment ◽  
The Standardized Precipitation Index ◽  
Inverse Distance

Daily precipitation data of 33 stations were analyzed to know the Standardized Precipitation Index (SPI). Both spatial and temporal SPI were analyzed. Inverse Distance Weighting (IDW) technique was used to map the spatial SPI with a decadal change. From 1983 to 2013, four maps showed the decadal changes of SPI over Bangladesh. 1993 was a dry year in the regarding time period. Station based trends were analyzed for Dhaka, Srimongol, Khulna, Cox’s bazaar and Rangpur as preventative for five regions in Bangladesh. Dryness is increasing over Northern and Central regions whereas wetness is increasing over Southwestern, Northern and eastern region in Bangladesh.DOI: http://dx.doi.org/10.3329/jesnr.v7i2.22220 Environ. Sci. & Natural Resources, 7(2): 127-131 2014

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.

Sign in / Sign up

Export Citation Format

Share Document