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首页> 外文期刊>Hydrology and Earth System Sciences Discussions >Can the dataset of field based recharge estimates in Australia be used to predict recharge in data-poor areas?
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Can the dataset of field based recharge estimates in Australia be used to predict recharge in data-poor areas?

机译:澳大利亚的基于领域的Realharge估计的数据集可用于预测数据贫困地区的充电吗?

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Effective management of water resources requires that all elements of the water balance be estimated. Groundwater recharge measurements are difficult, time consuming and expensive. In some cases a field study cannot be justified and simple empirical relationships are used to estimate recharge, and often the value chosen is simply a percentage of rainfall. This paper aims to use a database of 4386 field based estimates of recharge from 172 studies in Australia to produce simple empirical relationships that relate recharge to nationally available datasets and hence can be used to estimate recharge in data-poor areas in a scientifically defensible way. It was found that the vegetation and soil type were critical determinants in forming relationships between average annual rainfall and average annual recharge. Climate zones and surface geology (lithology) were not found to be significant determinants in the relationship between rainfall and recharge. The method used to estimate recharge had an impact upon the magnitude of the recharge estimates due to the spatial and temporal scales over which the different methods estimate recharge. Relationships have been developed here between average annual rainfall and average annual recharge for combinations of soil and vegetation type that can be used with only nationally available datasets to provide a recharge estimate. These relationships can explain 60% of the variance in recharge measurements across Australia. The uncertainty in the recharge estimated using these relationships is generally greater than an order of magnitude. This means that if these relationships are used to help determine water allocations, then the precautionary principle should limit allocations to less than about 5% of the estimated recharge. If allocations are greater than this, a more detailed site specific study is warranted.
机译:有效管理水资源要求估计水平衡的所有要素。地下水充电测量很困难,耗时且昂贵。在某些情况下,实地研究不能合理,并且简单的经验关系用于估计充电,并且所选择的价值通常只是降雨量的百分比。本文旨在利用澳大利亚172项基于4386个现场对充值的数据库,以产生与国家可用数据集的充值相关的简单实证关系,以便以科学可靠的方式估算数据贫困地区的充值。结果发现,植被和土壤类型是在年平均降雨平均降雨与年平均补给之间的关系中的关键决定因素。气候区和地表地质(岩性)未被发现是降雨和充电之间关系中的重要决定因素。用于估计补给的方法对由于不同方法估计补给的空间和时间尺度而产生的充电估计的大小。这里的平均降雨与土壤和植被类型的年平均补给之间的关系已经开发,只能与国家可用的数据集一起使用,以提供充电估计。这些关系可以解释澳大利亚各种重新充电测量方差的60%。使用这些关系估计的充电中的不确定性通常大于幅度的数量级。这意味着如果这些关系用于帮助确定水分配,则预防原则应将分配限制为估计补给的较少约5%。如果分配大于这一点,则保证更详细的现场研究。

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