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Spatial modeling of rainfall trends using satellite datasets and geographic information system

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Title Spatial modeling of rainfall trends using satellite datasets and geographic information system
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Creator Sanjay Kumar
Deepesh Machiwal
Devi Dayal
 
Subject Rainfall
Satellite dataset
Trend
Statistical test
Geographic information system (GIS)
 
Description Not Available
This study developed a standard methodology for identifying rainfall spatial trends using satellite-based raster datasets, and demonstrated the methodology for Gujarat State of India where trends in seven rainfall series, i.e. annual, pre-monsoon, monsoon, post-monsoon, non-monsoon, monthly-maximum and one-day maximum, are investigated. It involves the novelty of exploring capabilities of geographic information system in implementing procedures of three trend tests, i.e. Spearman rank order correlation (SROC), Kendall rank correlation (KRC), and Mann-Kendall (MK) tests on the rainfall raster datasets of Tropical Rainfall Measurement Mission at 0.25°×0.25° resolution. Comparative evaluation of three tests revealed a fair agreement in of their test results in a major portion for pre-, post-, and non-monsoon and one-day maximum rainfall. Whereas, similar results of the KRC and MK tests are obtained over considerable area for annual, monsoon and monthly-maximum rainfall. This finding suggested that the importance of selection of the trend selecting appropriate tests may be according to depending on rainfall magnitudes at different chosen time scales, which and emphasizes robustness of the KRC and MK tests. The methodology can be adopted to investigate rainfall trends using raster satellite-datasets in other parts of the world.
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Date 2019-04-12T09:28:38Z
2019-04-12T09:28:38Z
2017-07-06
 
Type Research Paper
 
Identifier Not Available
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http://krishi.icar.gov.in/jspui/handle/123456789/18496
 
Language English
 
Relation Not Available;
 
Publisher Taylor & Francis