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首页> 外文期刊>Journal of the American Water Resources Association >Forecasting the Probability of Future Groundwater Levels Declining Below Specified Low Thresholds in the Conterminous US
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Forecasting the Probability of Future Groundwater Levels Declining Below Specified Low Thresholds in the Conterminous US

机译：在美国本土，预测未来地下水位下降到指定低阈值以下的可能性

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We present a logistic regression approach for forecasting the probability of future groundwater levels declining or maintaining below specific groundwater-level thresholds. We tested our approach on 102 groundwater wells in different climatic regions and aquifers of the United States that are part of the U.S. Geological Survey Groundwater Climate Response Network. We evaluated the importance of current groundwater levels, precipitation, streamflow, seasonal variability, Palmer Drought Severity Index, and atmosphere/ocean indices for developing the logistic regression equations. Several diagnostics of model fit were used to evaluate the regression equations, including testing of autocorrelation of residuals, goodness-of-fit metrics, and bootstrap validation testing. The probabilistic predictions were most successful at wells with high persistence (low month-to-month variability) in their groundwater records and at wells where the groundwater level remained below the defined low threshold for sustained periods (generally three months or longer). The model fit was weakest at wells with strong seasonal variability in levels and with shorter duration low-threshold events. We identified challenges in deriving probabilistic-forecasting models and possible approaches for addressing those challenges.
机译：我们提出了一种逻辑回归方法来预测未来地下水位下降或维持在特定地下水位阈值以下的可能性。我们在属于美国地质调查局地下水气候响应网络的美国不同气候区域和含水层的102口地下水井中测试了我们的方法。我们评估了当前地下水位，降水量，水流量，季节变化，帕尔默干旱严重度指数以及大气/海洋指数对于发展逻辑回归方程的重要性。模型拟合的几种诊断方法用于评估回归方程，包括残差的自相关测试，拟合优度指标和自举验证测试。概率预测在地下水记录中具有高持久性（月间波动性较低）的井以及地下水位持续低于定义的低阈值的井（通常为三个月或更长时间）的井中最为成功。模型的拟合度在水平季节性变化大且持续时间短的低阈值事件的井中最弱。我们确定了推导概率预测模型的挑战以及应对这些挑战的可能方法。

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