Distributed recharge is commonly predicted from groundwater level data by adopting the water table fluctuation method (WTFM). The simplicity of the technique makes it attractive for groundwater management applications seeking sustainable levels of extraction. While there are variations to the WTFM, the classic approach extends the antecedent recession curve (prior to recharge events) to allow for the estimation of the gross recharge. This is achieved using either the previous (local) recession or a master recession curve obtained from multiple recession events. The most common function used for the recession extension is exponential. Despite the wide application of the WTFM, remarkably, a validation of this approach against known recharge values has not been previously attempted. This is the goal of the current study, which also compares local recession and master recession curve approaches adopting an exponential function for estimating recharge using the WTFM. Stochastic analysis applying an existing analytical solution to water table fluctuations from intermittent recharge was used to produce 1000 hypothetical hydrographs. From these, WTFM-based recharge was estimated for three recession periods of differing lengths, producing 6000 estimates of recharge (1000 simulations, two recession curve approaches, three recharge-recession events). The WTFM produced an average under-estimation error of 14%. The WTFM is more likely to obtain recharge errors within 5% of the true value using the master recession curve approach. This study demonstrates the need to revise the WTFM to eliminate bias, especially in the extrapolation of antecedent recession curves.

中文翻译：

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在地下水位波动法中评估指数衰退的可靠性


分布式补给通常采用地下水位波动法 （WTFM） 从地下水位数据中预测。该技术的简单性使其对寻求可持续开采水平的地下水管理应用具有吸引力。虽然 WTFM 存在变化，但经典方法扩展了前先衰退曲线（在补给事件之前），以允许估计总补给。这是使用先前（局部）衰退或从多个衰退事件中获得的主衰退曲线来实现的。用于衰退扩展的最常见函数是指数函数。尽管 WTFM 应用广泛，但值得注意的是，以前从未尝试过针对已知的充电值对这种方法进行验证。这是当前研究的目标，该研究还比较了局部衰退和主衰退曲线方法，该方法采用指数函数来使用 WTFM 估计补给。随机分析将现有解析解应用于间歇性补给引起的地下水位波动，用于生成 1000 个假设的过程线。从中，估计了三个不同长度的衰退期的基于 WTFM 的补给，产生了 6000 次补给估计（1000 次模拟，两个衰退曲线方法，三个补给-衰退事件）。WTFM 产生的平均低估误差为 14%。WTFM 更有可能使用主衰退曲线方法获得真实值 5% 以内的补给误差。这项研究表明需要修改 WTFM 以消除偏差，尤其是在前先衰退曲线的外推中。