Rainfall risk and "response farming": Using rainfall analysis, simulation modeling and GIS to improve agricultural decisions in Mali

Simple item page
dc.contributor.authorBadini, Oumaren
dc.contributor.departmentSustainable Agriculture and Natural Resource Management (SANREM) Knowledgebaseen
dc.coverage.spatialSahelen
dc.coverage.spatialMalien
dc.date.accessioned2016-04-19T18:07:36Zen
dc.date.available2016-04-19T18:07:36Zen
dc.date.issued2002en
dc.description.abstractIn this study, analyses of historical rainfall records are combined with GIS and biophysical modeling of soil water balance and crop production to predict performance of millet cultivars in Mali. The research improves previous efforts to apply rainy season predictions to agricultural decisions in the Sahel region, by integrating soils and crops information and by using crop simulation modeling. For two data sets defined by (early or late) rainfall onset date, the simulated crop yields, average water stress, and overall stress indices relative to yield potential have been computed and mapped. Research findings indicate that probability analysis and simulation modeling can be used to minimize agro-climatic risk.en
dc.format.mimetypeapplication/pdfen
dc.identifier22en
dc.identifier.citationSANREM CRSP Research Brief 2002 No. 12en
dc.identifier.other22_badiniRev.pdfen
dc.identifier.urihttp://hdl.handle.net/10919/65339en
dc.language.isoen_USen
dc.publisherWatkinsville, GA: SANREM CRSPen
dc.subjectRainfed agricultureen
dc.subjectFood securityen
dc.subjectModelingen
dc.subjectDryland farmingen
dc.subjectSemiarid zonesen
dc.subjectRainfall variabilityen
dc.subjectFertilizationen
dc.subjectSoil typesen
dc.subjectNitrogenen
dc.subjectCrop yieldsen
dc.subjectWater stressen
dc.subjectRisk managementen
dc.subjectCropsysten
dc.subjectMilleten
dc.subjectSoil-water balanceen
dc.subjectResponse farmingen
dc.subjectFarmer agroclimatic decision supporten
dc.subjectFarm/Enterprise Scale Field Scaleen
dc.titleRainfall risk and "response farming": Using rainfall analysis, simulation modeling and GIS to improve agricultural decisions in Malien
dc.typeWorking paperen
dc.type.dcmitypeTexten

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
22_badiniRev.pdf
Size:
605.48 KB
Format:
Adobe Portable Document Format
Download

Collections

Sustainable Agriculture and Natural Resource Management (SANREM) Knowledgebase