Agricultural drought periods analysis by using nonhomogeneous poisson models and regionalization of appropriate model parameters

Precipitation has a dominant role in agriculture, and a regular rain pattern is usually vital to agriculture; excessive or inadequate rainfall can be harmful. In this paper, an agricultural drought index is utilized to study the agricultural drought periods and analyze them with their intensities at...

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Autores principales:	Asad Ellahi, Ijaz Hussain, Muhammad Zaffar Hashmi, Mohammed Mohammed Ahmed Almazah, Fuad S. Al-Duais
Formato:	article
Lenguaje:	EN
Publicado:	Taylor & Francis Group 2021
Materias:	standard precipitation index agricultural drought nonhomogeneous poisson process power law process linear intensity function regionalization variogram ordinary kriging Oceanography GC1-1581 Meteorology. Climatology QC851-999
Acceso en línea:	https://doaj.org/article/8ffccd206af449a18be54471948ab40d
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spelling	oai:doaj.org-article:8ffccd206af449a18be54471948ab40d2021-12-01T14:40:58ZAgricultural drought periods analysis by using nonhomogeneous poisson models and regionalization of appropriate model parameters1600-087010.1080/16000870.2021.1948241https://doaj.org/article/8ffccd206af449a18be54471948ab40d2021-01-01T00:00:00Zhttp://dx.doi.org/10.1080/16000870.2021.1948241https://doaj.org/toc/1600-0870Precipitation has a dominant role in agriculture, and a regular rain pattern is usually vital to agriculture; excessive or inadequate rainfall can be harmful. In this paper, an agricultural drought index is utilized to study the agricultural drought periods and analyze them with their intensities at various locations. Some nonhomogeneous Poisson models are also used to calculate the probability of agricultural droughts (number of times occurred) in a time interval of interest. It is to be assumed that the number of agricultural drought event occurrences is a Nonhomogeneous Poisson Process (NHPP) has a rate function, which depends on some parameters that must be estimated. Two cases of these functions are considered: the Weibull and linear intensity function. The Bayesian approach with Gibbs sampling under the Markov Chain Monte Carlo (MCMC) algorithm is used to estimate the parameters of these functions. The most appropriate fitted model is selected by using Deviance Information Criteria (DIC) and use that appropriately fitted model to calculate the accumulated events of agricultural drought in a time interval of interest at each location. Ordinary Kriging (OK) is used to regionalize the parameters and present its spatial behavior. The results based on the DIC indicate that the Power Law Process (PLP) performs better than the linear intensity function, NHPP model. The interpolated parameter values for the appropriate model, their patterns, and fluctuations for the study area are efficiently presented using contour maps. It is a novel and straightforward approach to assess the selected model parameter values used to predict the accumulated drought events at un-sampled locations. The proposed framework might also help to analyze other spatial variables of interest and can be used for climate-change study, ecosystem modeling, etc. The findings can also help to make decisions for sustainable environmental management in Pakistan.Asad EllahiIjaz HussainMuhammad Zaffar HashmiMohammed Mohammed Ahmed AlmazahFuad S. Al-DuaisTaylor & Francis Grouparticlestandard precipitation indexagricultural droughtnonhomogeneous poisson processpower law processlinear intensity functionregionalizationvariogramordinary krigingOceanographyGC1-1581Meteorology. ClimatologyQC851-999ENTellus: Series A, Dynamic Meteorology and Oceanography, Vol 73, Iss 1, Pp 1-16 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	standard precipitation index agricultural drought nonhomogeneous poisson process power law process linear intensity function regionalization variogram ordinary kriging Oceanography GC1-1581 Meteorology. Climatology QC851-999
spellingShingle	standard precipitation index agricultural drought nonhomogeneous poisson process power law process linear intensity function regionalization variogram ordinary kriging Oceanography GC1-1581 Meteorology. Climatology QC851-999 Asad Ellahi Ijaz Hussain Muhammad Zaffar Hashmi Mohammed Mohammed Ahmed Almazah Fuad S. Al-Duais Agricultural drought periods analysis by using nonhomogeneous poisson models and regionalization of appropriate model parameters
description	Precipitation has a dominant role in agriculture, and a regular rain pattern is usually vital to agriculture; excessive or inadequate rainfall can be harmful. In this paper, an agricultural drought index is utilized to study the agricultural drought periods and analyze them with their intensities at various locations. Some nonhomogeneous Poisson models are also used to calculate the probability of agricultural droughts (number of times occurred) in a time interval of interest. It is to be assumed that the number of agricultural drought event occurrences is a Nonhomogeneous Poisson Process (NHPP) has a rate function, which depends on some parameters that must be estimated. Two cases of these functions are considered: the Weibull and linear intensity function. The Bayesian approach with Gibbs sampling under the Markov Chain Monte Carlo (MCMC) algorithm is used to estimate the parameters of these functions. The most appropriate fitted model is selected by using Deviance Information Criteria (DIC) and use that appropriately fitted model to calculate the accumulated events of agricultural drought in a time interval of interest at each location. Ordinary Kriging (OK) is used to regionalize the parameters and present its spatial behavior. The results based on the DIC indicate that the Power Law Process (PLP) performs better than the linear intensity function, NHPP model. The interpolated parameter values for the appropriate model, their patterns, and fluctuations for the study area are efficiently presented using contour maps. It is a novel and straightforward approach to assess the selected model parameter values used to predict the accumulated drought events at un-sampled locations. The proposed framework might also help to analyze other spatial variables of interest and can be used for climate-change study, ecosystem modeling, etc. The findings can also help to make decisions for sustainable environmental management in Pakistan.
format	article
author	Asad Ellahi Ijaz Hussain Muhammad Zaffar Hashmi Mohammed Mohammed Ahmed Almazah Fuad S. Al-Duais
author_facet	Asad Ellahi Ijaz Hussain Muhammad Zaffar Hashmi Mohammed Mohammed Ahmed Almazah Fuad S. Al-Duais
author_sort	Asad Ellahi
title	Agricultural drought periods analysis by using nonhomogeneous poisson models and regionalization of appropriate model parameters
title_short	Agricultural drought periods analysis by using nonhomogeneous poisson models and regionalization of appropriate model parameters
title_full	Agricultural drought periods analysis by using nonhomogeneous poisson models and regionalization of appropriate model parameters
title_fullStr	Agricultural drought periods analysis by using nonhomogeneous poisson models and regionalization of appropriate model parameters
title_full_unstemmed	Agricultural drought periods analysis by using nonhomogeneous poisson models and regionalization of appropriate model parameters
title_sort	agricultural drought periods analysis by using nonhomogeneous poisson models and regionalization of appropriate model parameters
publisher	Taylor & Francis Group
publishDate	2021
url	https://doaj.org/article/8ffccd206af449a18be54471948ab40d
work_keys_str_mv	AT asadellahi agriculturaldroughtperiodsanalysisbyusingnonhomogeneouspoissonmodelsandregionalizationofappropriatemodelparameters AT ijazhussain agriculturaldroughtperiodsanalysisbyusingnonhomogeneouspoissonmodelsandregionalizationofappropriatemodelparameters AT muhammadzaffarhashmi agriculturaldroughtperiodsanalysisbyusingnonhomogeneouspoissonmodelsandregionalizationofappropriatemodelparameters AT mohammedmohammedahmedalmazah agriculturaldroughtperiodsanalysisbyusingnonhomogeneouspoissonmodelsandregionalizationofappropriatemodelparameters AT fuadsalduais agriculturaldroughtperiodsanalysisbyusingnonhomogeneouspoissonmodelsandregionalizationofappropriatemodelparameters
_version_	1718405005846773760

Agricultural drought periods analysis by using nonhomogeneous poisson models and regionalization of appropriate model parameters

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