Please use this identifier to cite or link to this item: http://dspace.iitrpr.ac.in:8080/xmlui/handle/123456789/3209
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dc.contributor.authorKapoor, A.-
dc.contributor.authorKashyap, D.-
dc.date.accessioned2021-11-17T23:23:23Z-
dc.date.available2021-11-17T23:23:23Z-
dc.date.issued2021-11-18-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/3209-
dc.description.abstractPilot point methodology (PPM) permits estimation of transmissivity at unsampled pilot points by solving the hydraulic head based inverse problem. Especially relevant to areas with sparse transmissivity data, the methodology supplements the limited field data. Presented herein is an approach for estimating parameters of PPM honoring the objectives of refinement of the transmissivity (T) interpolation and the model calibration. The parameters are the locations and number of pilot transmissivity points. The location parameter is estimated by defining a qualifying matrix Q comprising weighted sum of the hydraulic head-sensitivity and the kriging variance fields. Whereas the former component of Q promotes the model calibration, the latter one leads to improved T interpolation by locating pilot points in un-sampled tracts. Further, a three-stage methodology is proposed for an objective determination of the number of pilot points. It is based upon sequential upgradation of the Variogram as the pilot points are added to the data base, ensuring its convergence with the head-based optimal Variogram. The model has been illustrated by applying it to Satluj-Beas interbasin wherein the pumping test data is not only sparse, but also unevenly distributed.en_US
dc.language.isoen_USen_US
dc.subjectpilot point methoden_US
dc.subjectgroundwater modelingen_US
dc.subjectinverse problemen_US
dc.subjectkrigingen_US
dc.subjectcalibration with sparse dataen_US
dc.titleParameterization of pilot point methodology for supplementing sparse transmissivity dataen_US
dc.typeArticleen_US
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