scholarly journals Gamma Distribution and its Application of Spatially Monitoring Meteorological Drought in Barind, Bangladesh

2013 ◽  
Vol 5 (2) ◽  
pp. 287-293 ◽  
Author(s):  
ATMJ Alam ◽  
MS Rahman ◽  
AHM Saadat ◽  
MM Huq
Keyword(s):  
Spatial Distribution ◽  
Gamma Distribution ◽  
Monsoon Season ◽  
Standardized Precipitation Index ◽  
Geographical Information ◽  
Critical Threshold ◽  
Drought Severity ◽  
Multiple Time ◽  
Drought Vulnerability ◽  
Weighting Method

The Barind tract of Bangladesh suffers from frequent drought due to erratic rainfall distribution. In the present study details analysis of rainfall data has been carried out for the years 1971-2010. The Standardized Precipitation Index (SPI) which is followed by gamma distribution is used to evaluate drought vulnerability based on frequency and severity of drought events at multiple time steps (3, 5 and 12 months). Drought severity maps are generated in a GIS (Geographical Information System) environment using inverse distance weighting method. Critical (threshold) rainfall values are derived for each station at multiple-time steps in varying drought categories to determine least amount of rainfall required to avoid from drought initiation. The study found that drought vulnerability portrays a very diverse but consistent picture with varying time steps. Analysis and interpretation of the map shows a similar spatial distribution of drought in pre-monsoon season but in monsoon season rainfall deficits shifts its position time to time and occurred in certain discrete pockets. In 12 months period the spatial distribution of drought was almost similar with monsoon season. In pre-monsoon season drought severity was higher in north eastern part of the study area compare to other parts. The study also evident that critical threshold values of rainfall to avoid drought condition was higher in the northern part of high Barind than southern part.DOI: http://dx.doi.org/10.3329/jesnr.v5i2.14832 J. Environ. Sci. & Natural Resources, 5(2): 287-293 2012

scholarly journals Spatio-temporal evaluation of drought characteristics in the Dhasan basin

MAUSAM ◽  
2021 ◽  
Vol 69 (4) ◽  
pp. 589-598
Author(s):  
SASWAT KUMAR KAR ◽  
R. M. SINGH ◽  
T. THOMAS
Keyword(s):  
Time Scale ◽  
Monsoon Season ◽  
Standardized Precipitation Index ◽  
Rain Gauge ◽  
Drought Severity ◽  
Severe Drought ◽  
Multiple Time ◽  
Drought Duration ◽  
Drought Characteristics ◽  
Drought Conditions

ABSTRACT. The meteorological drought characteristics including onset, departure, duration, severity as well as intensity have been evaluated mainly for monsoon season at all the three rain gauge stations located in Dhasan basin. The Standardized Precipitation Index (SPI) has been applied to understand and quantify the drought severity on multiple time scale (1, 3, 6, 12 and 24 months). The spatiotemporal analysis of drought based on 3-month SPI has also carried out to identify drought years and the regions of the study area which is under the grip of continuous drought events. Based on the 3-month SPI, major drought events have been identified. The maximum drought severity of -11.17 occurred during November 1991 to August 1992 having the longest duration of 10 months, in the area under Sagar rain gauging station. The onset of most of the drought events in the basin take place during the beginning of Kharif season and terminate by the end of August or September, so affect the agricultural crops severely. The spatial variation indicates that during June 2002, about 55.74% of basin area was experiencing severe drought conditions, followed by 35.29% area under moderate drought condition and only 8.97% area faced mild drought conditions. The inter-relationship among the drought duration, number of drought events, drought severity and time scale have been studied.  

scholarly journals Climate change effects on drought severity

2008 ◽  
Vol 17 ◽  
pp. 23-29 ◽  
Author(s):  
A. Loukas ◽  
L. Vasiliades ◽  
J. Tzabiras
Keyword(s):  
Climate Change ◽  
Time Scales ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Geographical Information ◽  
Multiple Time Scales ◽  
Drought Severity ◽  
Multiple Time ◽  
Monthly Precipitation ◽  
Climate Change Effects

Abstract. This paper evaluates climate change effects on drought severity in the region of Thessaly, Greece. The Standardized Precipitation Index (SPI) has been used for estimation of drought severity. A geographical information system is applied for the division of Thessaly region to twelve hydrological homogeneous areas based on their geomorphology. Mean monthly precipitation values from 50 precipitation stations of Thessaly for the hydrological period October 1960–September 1990 were used for the estimation of mean areal precipitation. These precipitation timeseries have been used for the estimation of Standardized Precipitation Index (SPI) for multiple time scales (1-, 3-, 6-, 9-, and 12-months) for each sub-basin or area. The outputs of Global Circulation Model CGCM2 were applied for two socioeconomic scenarios, namely, SRES A2 and SRES B2 for the assessment of climate change impact on droughts. The GCM outputs were downscaled to the region of Thessaly using a statistical methodology to estimate precipitation time series for two future periods 2020–2050 and 2070–2100. A method has been proposed for the estimation of annual cumulative drought severity-time scale-frequency curves. These curves integrate the drought severity and frequency for various types of drought. The SPI timeseries and annual weighted cumulative drought severity were estimated and compared with the respective timeseries and values of the historical period 1960–1990. The results showed that the annual drought severity is increased for all hydrological areas and SPI time scales, with the socioeconomic scenario SRES A2 being the most extreme.

scholarly journals Probabilistic analysis of drought spatiotemporal characteristics inThessaly region, Greece

2004 ◽  
Vol 4 (5/6) ◽  
pp. 719-731 ◽  
Author(s):  
A. Loukas ◽  
L. Vasiliades
Keyword(s):  
Standardized Precipitation Index ◽  
Multiple Time Scales ◽  
Drought Severity ◽  
Severe Drought ◽  
Multiple Time ◽  
Monthly Precipitation ◽  
Spatial Characteristics ◽  
Sustainable Water Resources Management ◽  
Temporal And Spatial ◽  
Temporal And Spatial Characteristics

Abstract. The temporal and spatial characteristics of meteorological drought are investigated to provide a framework for sustainable water resources management in the region of Thessaly, Greece. Thessaly is the most intensely cultivated and productive agricultural plain region in Greece. Thessaly's total area is about 13700 km2 and it is surrounded by mountains and traversed by Pinios River. Using the Standardized Precipitation Index (SPI) as an indicator of drought severity, the characteristics of droughts are examined. Thessaly was divided into 212 grid-cells of 8 x 8 km and monthly precipitation data for the period 1960–1993 from 50 meteorological stations were used for global interpolation of precipitation using spatial co-ordinates and elevation data. Drought severity was assessed from the estimated gridded SPI values at multiple time scales. Firstly, the temporal and spatial characteristics of droughts were analyzed and then, Drought Severity – Areal extent – Frequency (SAF) annual and monthly curves were developed. The analysis indicated that moderate and severe droughts are common in Thessaly region. Using the SAF curves, the return period of selected severe drought events was assessed.

scholarly journals TRENDS AND VULNERABILITY ASSESSMENT OF METEOROLOGICAL AND AGRICULTURAL DROUGHT CONDITIONS OVER INDIAN REGION USING TIME-SERIES (1982–2015) SATELLITE DATA

2019 ◽  
Vol XLII-3/W6 ◽  
pp. 453-459 ◽  
Author(s):  
R. Das ◽  
P. K. Das ◽  
S. Bandyopadhyay ◽  
U. Raj
Keyword(s):  
Time Series ◽  
Vegetation Index ◽  
Empirical Distribution ◽  
Monsoon Season ◽  
Standardized Precipitation Index ◽  
Indian Region ◽  
Agricultural Drought ◽  
Drought Vulnerability ◽  
Drought Conditions

<p><strong>Abstract.</strong> The vulnerability and trends of meteorological as well as agricultural drought conditions over Indian region was studied using long-term (1982&amp;ndash;2015) gridded precipitation and time-series normalized difference vegetation index (NDVI) data. The Climate Hazards Group Infra-Red Precipitation with Station (CHIRPS) precipitation data (~5&amp;thinsp;km) was used to compute Standardized precipitation index (SPI) at 3-month time scale for Indian summer monsoon season (June-September). Subsequently, the long-term Global Inventory Modelling and Mapping Studies (GIMMS) time-series NDVI data (~8&amp;thinsp;km) was interpolated at daily scale and smoothened using Savitzky and Golay filtering method. Further, the time-series NDVI data was transformed into several phenological parameters using threshold and derivative approach. As integrated NDVI, i.e. the area under seasonal NDVI curve, is able to represent the anomalies in seasonal agricultural production, it was transformed into standardized vegetation index (SVI) using empirical distribution. Several drought parameters, e.g. magnitude and extent, were computed at district level based on the SPI and SVI values, where values with SPI or SVI less than minus one was considered as meteorological and agricultural drought year, respectively. The trends of drought magnitude and extent for both the meteorological and agricultural drought were estimated using Sen’s slope. The direction of trends and magnitude were found to be varying spatially across different parts of Indian region. Further, the mean SPI/SVI values along with drought frequency were utilized to categorize entire Indian agricultural area into different vulnerable zones during three decades separately. The overall drought vulnerability was found to be decreasing over time.</p>

scholarly journals Seasonal Dynamics of Agro-meteorological Drought in Mberengwa and Zvishavane Districts between 2017 and 2020, Zimbabwe

2021 ◽  
Author(s):  
Oshneck Mupepi ◽  
Mark M Matsa
Keyword(s):  
Spatial Distribution ◽  
Temporal Dynamics ◽  
Late Onset ◽  
Meteorological Drought ◽  
Geographical Information ◽  
Drought Severity ◽  
Drought Resilience ◽  
Spatial Coverage ◽  
Study Results ◽  
Rain Season

Abstract Drought severity is increasing in Southern Africa which is affecting rain-fed agriculture, the main source of livelihood in most countries in this region. The study assessed the seasonal spatio-temporal dynamics of agro-meteorological drought between 2017 and 2020 in Mberengwa and Zvishavane Districts. An empirical research design supported by quantitative geographical information system and remote sensing techniques was adopted in this study. Microsoft excel 2013, SPI generator and ArcMap 10.5 software were used for data analysis in this study. Results showed that both Mberengwa and Zvishavane Districts experienced an increasing trend in spatial coverage of drought from 2017 to 2019 before a slight decline in 2020. From 2017, drought severity increased in terms of spatial coverage with this spatial distribution increasing to almost over ¾ of the wards in both Mberengwa and Zvishavane Districts between 2018 and 2020. Since 2017, on a ward level basis, both districts have been experiencing late onset and early cessation of the rain season as shown by increasingly dry October, November and March, months which determine the length of crop growing season in these two districts. Results indicated that the month of March was drier in Mberengwa whilst the month of December was drier in Zvishavane, an indication of more mid-season dry spells in Zvishavane and earlier rainfall cessation in Mberengwa. Drought is worsening in both Mberengwa and Zvishavane Districts hence long term drought resilience interventions are required to improve drought resilience of communities in these areas. The study recommends the Government of Zimbabwe and other stakeholders of drought resilience building like CARE International, World Vision among others to prioritize launching of resilience building initiatives in most vulnerable areas whilst guided by fine empirical information on spatial distribution of drought.

scholarly journals Spatial Distribution of Soil Nutrients in Farmland in a Hilly Region of the Pearl River Delta in China Based on Geostatistics and the Inverse Distance Weighting Method

Agriculture ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 50
Author(s):  
Rumi Wang ◽  
Runyan Zou ◽  
Jianmei Liu ◽  
Luo Liu ◽  
Yueming Hu
Keyword(s):  
Spatial Distribution ◽  
Pearl River Delta ◽  
Pearl River ◽  
Weighting Method ◽  
Farmland Protection ◽  
The Pearl River Delta ◽  
Hilly Region ◽  
Distance Weighting ◽  
The Pearl River ◽  
Inverse Distance

Soil nutrients are essential factors that reflect farmland quality. Nitrogen, phosphorus, and potassium are essential elements for plants, while silicon is considered a “quasi-essential” element. This study investigated the spatial distribution of plant nutrients in soil in a hilly region of the Pearl River Delta in China. A total of 201 soil samples were collected from farmland topsoil (0–20 cm) for the analysis of total nitrogen (TN), available phosphorus (AP), available potassium (AK), and available silicon (ASi). The coefficients of variation ranged from 47.88% to 76.91%. The NSRs of TN, AP, AK, and ASi were 0.15, 0. 07, 0.12, and 0.13, respectively. The NSRs varied from 0.02 to 0.20. All variables exhibited weak spatial dependence (R2 < 0.5), except for TN (R2 = 0.701). After comparing the prediction accuracy of the different methods, we used the inverse distance weighting method to analyze the spatial distribution of plant nutrients in soil. The uniform spatial distribution of AK, TN overall showed a trend of increasing from northeast to southwest, and the overall spatial distribution of AP and ASi showed that the northeast was higher than the southwest. This study provides support for the delimitation of basic farmland protection areas, the formulation of land use spatial planning, and the formulation of accurate farmland protection policies.

scholarly journals Assessment of the Dissimilarities of EDI and SPI Measures for Drought Determination in South Africa

Water ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 82
Author(s):  
Omolola M. Adisa ◽  
Muthoni Masinde ◽  
Joel O. Botai
Keyword(s):  
South Africa ◽  
South African ◽  
Correlation Coefficient ◽  
Pearson Correlation ◽  
Standardized Precipitation Index ◽  
Drought Monitoring ◽  
Drought Indices ◽  
Drought Severity ◽  
Pearson Correlation Coefficient ◽  
Drought Duration

This study examines the (dis)similarity of two commonly used indices Standardized Precipitation Index (SPI) computed over accumulation periods 1-month, 3-month, 6-month, and 12-month (hereafter SPI-1, SPI-3, SPI-6, and SPI-12, respectively) and Effective Drought Index (EDI). The analysis is based on two drought monitoring indicators (derived from SPI and EDI), namely, the Drought Duration (DD) and Drought Severity (DS) across the 93 South African Weather Service’s delineated rainfall districts over South Africa from 1980 to 2019. In the study, the Pearson correlation coefficient dissimilarity and periodogram dissimilarity estimates were used. The results indicate a positive correlation for the Pearson correlation coefficient dissimilarity and a positive value for periodogram of dissimilarity in both the DD and DS. With the Pearson correlation coefficient dissimilarity, the study demonstrates that the values of the SPI-1/EDI pair and the SPI-3/EDI pair exhibit the highest similar values for DD, while the SPI-6/EDI pair shows the highest similar values for DS. Moreover, dissimilarities are more obvious in SPI-12/EDI pair for DD and DS. When a periodogram of dissimilarity is used, the values of the SPI-1/EDI pair and SPI-6/EDI pair exhibit the highest similar values for DD, while SPI-1/EDI displayed the highest similar values for DS. Overall, the two measures show that the highest similarity is obtained in the SPI-1/EDI pair for DS. The results obtainable in this study contribute towards an in-depth knowledge of deviation between the EDI and SPI values for South Africa, depicting that these two drought indices values are replaceable in some rainfall districts of South Africa for drought monitoring and prediction, and this is a step towards the selection of the appropriate drought indices.

scholarly journals Developing Objective Operational Definitions for Monitoring Drought

2009 ◽  
Vol 48 (6) ◽  
pp. 1217-1229 ◽  
Author(s):  
Steven M. Quiring
Keyword(s):  
Water Conservation ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Severity Index ◽  
Decision Makers ◽  
Drought Severity ◽  
Specific Method ◽  
The Standardized Precipitation Index ◽  
Spatially Variant ◽  
Objective Methodology

Abstract Drought is a complex phenomenon that is difficult to accurately describe because its definition is both spatially variant and context dependent. Decision makers in local, state, and federal agencies commonly use operational drought definitions that are based on specific drought index thresholds to trigger water conservation measures and determine levels of drought assistance. Unfortunately, many state drought plans utilize operational drought definitions that are derived subjectively and therefore may not be appropriate for triggering drought responses. This paper presents an objective methodology for establishing operational drought definitions. The advantages of this methodology are demonstrated by calculating meteorological drought thresholds for the Palmer drought severity index, the standardized precipitation index, and percent of normal precipitation using both station and climate division data from Texas. Results indicate that using subjectively derived operational drought definitions may lead to over- or underestimating true drought severity. Therefore, it is more appropriate to use an objective location-specific method for defining operational drought thresholds.

scholarly journals Evaluation of a High-Resolution SPI for Monitoring Local Drought Severity

2016 ◽  
Vol 55 (10) ◽  
pp. 2247-2262 ◽  
Author(s):  
Rebecca V. Cumbie-Ward ◽  
Ryan P. Boyles
Keyword(s):  
United States ◽  
High Resolution ◽  
Standardized Precipitation Index ◽  
Stage Iv ◽  
Drought Severity ◽  
Cluster Solution ◽  
Historical Distribution ◽  
Drought Conditions ◽  
Hydrologic Prediction ◽  
Strong Agreement

AbstractA standardized precipitation index (SPI) that uses high-resolution, daily estimates of precipitation from the National Weather Service over the contiguous United States has been developed and is referred to as HRD SPI. There are two different historical distributions computed in the HRD SPI dataset, each with a different combination of normals period (1971–2000 or 1981–2010) and clustering solution of gauge stations. For each historical distribution, the SPI is computed using the NCEP Stage IV and Advanced Hydrologic Prediction Service (AHPS) gridded precipitation datasets for a total of four different HRD SPI products. HRD SPIs are found to correlate strongly with independently produced SPIs over the 10-yr period from 2005 to 2015. The drought-monitoring utility of the HRD SPIs is assessed with case studies of drought in the central and southern United States during 2012 and over the Carolinas during 2007–08. A monthly comparison between HRD SPIs and independently produced SPIs reveals generally strong agreement during both events but weak agreement in areas where radar coverage is poor. For both study regions, HRD SPI is compared with the U.S. Drought Monitor (USDM) to assess the best combination of precipitation input, normals period, and station clustering solution. SPI generated with AHPS precipitation and the 1981–2010 PRISM normals and associated cluster solution is found to best capture the spatial extent and severity of drought conditions indicated by the USDM. This SPI is also able to resolve local variations in drought conditions that are not shown by either the USDM or comparison SPI datasets.

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