Advancing the climate data driven crop-modeling studies in the dry areas of Northern Syria and Lebanon: An important first step for assessing impact of future climate

cg.contactP.Dixit@cgiar.orgen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.funderCGIAR Research Program on Policies, Institutions, and Markets - PIMen_US
cg.contributor.projectCommunication and Documentation Information Services (CODIS)en_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.coverage.countryLBen_US
cg.coverage.countrySYen_US
cg.coverage.regionWestern Asiaen_US
cg.date.embargo-end-dateTimelessen_US
cg.identifier.doihttps://dx.doi.org/10.1016/j.scitotenv.2015.01.001en_US
cg.isijournalISI Journalen_US
cg.issn0048-9697en_US
cg.journalScience of the Total Environmenten_US
cg.subject.agrovocsyriaen_US
cg.subject.agrovoclebanonen_US
cg.volume511en_US
dc.contributorTelleria, Robertoen_US
dc.creatorDixit, Prakashen_US
dc.date.accessioned2021-04-23T21:28:43Z
dc.date.available2021-04-23T21:28:43Z
dc.description.abstractInter-annual and seasonal variability in climatic parameters, most importantly rainfall, have potential to cause climate-induced risk in long-term crop production. Short-term field studies do not capture the full nature of such risk and the extent to which modifications to crop, soil and water management recommendations may be made to mitigate the extent of such risk. Crop modeling studies driven by long-term daily weather data can predict the impact of climate-induced risk on crop growth and yield however, the availability of long-term daily weather data can present serious constraints to the use of crop models. To tackle this constraint, two weather generators namely, LARS-WG and MarkSim, were evaluated in order to assess their capabilities of reproducing frequency distributions, means, variances, dry spell and wet chains of observed daily precipitation, maximum and minimum temperature, and solar radiation for the eight locations across cropping areas of Northern Syria and Lebanon. Further, the application of generated long-term daily weather data, with both weather generators, in simulating barley growth and yield was also evaluated. We found that overall LARS-WG performed better than MarkSim in generating daily weather parameters and in 50 years continuous simulation of barley growth and yield. Our findings suggest that LARS-WG does not necessarily, require long-term e.g., >30 years observed weather data for calibration as generated results proved to be satisfactory with >10 years of observed data except in area with higher altitude. Evaluating these weather generators and the ability of generated weather data to perform long-term simulation of crop growth and yield is an important first step to assess the impact of future climate on yields, and to identify promising technologies to make agricultural systems more resilient in the given region. (C) 2015 Elsevier B.V. All rights reserved.en_US
dc.identifierhttps://mel.cgiar.org/dspace/limiteden_US
dc.identifier.citationPrakash Dixit, Roberto Telleria. (1/4/2015). Advancing the climate data driven crop-modeling studies in the dry areas of Northern Syria and Lebanon: An important first step for assessing impact of future climate. Science of the Total Environment, 511, pp. 562-575.en_US
dc.identifier.statusTimeless limited accessen_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/12943
dc.languageenen_US
dc.publisherElsevieren_US
dc.sourceScience of the Total Environment;511,(2015) Pagination 562-575en_US
dc.subjectcrop simulationen_US
dc.subjectclimate data generationen_US
dc.subjectdry environmenten_US
dc.titleAdvancing the climate data driven crop-modeling studies in the dry areas of Northern Syria and Lebanon: An important first step for assessing impact of future climateen_US
dc.typeJournal Articleen_US
dcterms.available2015-01-12en_US
dcterms.extent562-575en_US
dcterms.issued2015-04-01en_US
mel.impact-factor6.551en_US

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