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Modeling the potential for floodwater recharge to offset groundwater depletion: a case study from the Ramganga basin, India

机译:建立洪水补给潜力以抵消地下水枯竭的模型:以印度拉姆甘加盆地为例

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The Ganges basin faces considerable spatial and temporal imbalance between water demand and availability. Lack of water storage infrastructure has led to this mismatch, wherein there are limited options to store flood water during the wet season and limited groundwater and surface water resources during the dry season. In this current study, a semi-coupled hydrological modeling framework is used to test scenarios that can help bridge this imbalance. A hydrological model (SWAT), groundwater model (MODFLOW) and flood inundation model (HEC-RAS) were applied to the Ramganga basin in India (~19,000 km_(2)) to understand the baseline hydrologic regime and to test scenarios with distributed managed aquifer recharge (MAR) interventions, which when applied to at the basin scale to co-address flooding and groundwater depletion has come to be known as Underground Taming of Floods for Irrigation. The scenarios with MAR, which used available basin runoff to recharge groundwater, yielded favorable results in flood reduction and groundwater level improvement throughout the sub-basin. Groundwater levels improved within 5 years of introducing MAR, resulting in a groundwater elevation increase of up to 7 m when compared to baseline conditions. The HEC-RAS model indicated that a 20% reduction in basin outflow converted a 15-year flood peak to an 8-year flood peak, a 5-year peak to 3 years and a 2-year peak to 1 year. In addition, this resulted in a 10% reduction in the inundated area in all return periods tested. Therefore, distributed MAR practices can be effective in reducing the negative impacts from larger return period floods and increasing the groundwater levels.
机译:恒河盆地在需水量和可利用量之间面临着巨大的时空失衡。缺乏储水基础设施导致这种不匹配,其中在雨季存储洪水的选择有限,而在旱季存储的地下水和地表水资源有限。在本研究中,半耦合水文建模框架用于测试可以帮助弥合这种不平衡的情景。将水文模型(SWAT),地下水模型(MODFLOW)和洪水淹没模型(HEC-RAS)应用于印度Ramganga盆地(〜19,000 km_(2)),以了解基线水文状况并测试分布式管理模式下的情景含水层补给(MAR)干预措施,在流域范围内用于应对洪水和地下水枯竭,已被称为灌溉地下灌溉。 MAR方案利用流域径流补充地下水,在整个次流域减少洪水和改善地下水位方面均取得了良好的效果。引入MAR的5年内,地下水水位有所改善,与基准条件相比,导致地下水高度升高了7 m。 HEC-RAS模型表明,流域流出量减少20%,将15年的洪峰转变为8年的洪峰,将5年的洪峰转变为3年,将2年的洪峰转变为1年。此外,这在所有测试的返还期间都使淹没面积减少了10%。因此,分布式MAR做法可有效减少较大的返还期洪水带来的负面影响并提高地下水位。

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