Improving the reliability of numerical groundwater modeling in a data-sparse region

Xinqiang Du, Xiangqin Lu, Jiawei Hou, Xueyan Ye*

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    15 Citations (Scopus)

    Abstract

    In data-sparse areas, due to the lack of hydrogeological data, numerical groundwater models have some uncertainties. In this paper, a nested model and a multi-index calibration method are used to improve the reliability of a numerical groundwater model in a data-sparse region, the Nalinggele River catchment in the Qaidam Basin. Referencing this key study area, a regional three-dimensional groundwater flow model is developed in a relatively complete hydrogeological unit. A complex set of calibration indices, including groundwater fitting errors, dynamic groundwater trends, spring discharges, overflow zone location, and groundwater budget status, are proposed to calibrate the regional numerical groundwater model in the Nalinggele alluvial-proluvial fan. Constrained by regional groundwater modeling results, a local-scale groundwater model is developed, and the hydrogeological parameters are investigated to improve modeling accuracy and reliability in this data-sparse region.

    Original languageEnglish
    Article number289
    JournalWater (Switzerland)
    Volume10
    Issue number3
    DOIs
    Publication statusPublished - 8 Mar 2018

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