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首页> 外文期刊>Journal of Hydrology >Groundwater discharge into an estuary using spatially distributed radon time series and radium isotopes
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Groundwater discharge into an estuary using spatially distributed radon time series and radium isotopes

机译:利用空间分布的time时间序列和镭同位素将河水排入河口

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Quantifying groundwater discharge remains a challenge due to its large temporal and spatial variability. Here, we quantify groundwater discharge into a small estuary using radon (Rn-222) and radium isotopes (Ra-223 and Ra-224). High temporal resolution (30 min time steps) radon observations at 4 time series stations were used to determine where groundwater discharge is prevalent in the estuary, and to reduce mass balance model uncertainties. A three-endmember mixing model was developed based on short-lived radium isotopes (sampled at a single location) to separate the shallow saline and deep fresh sources of the discharging groundwater. The results show that using multiple Rn-222 time series stations decreased the overall uncertainty of groundwater discharge estimates from about 41% to 23%. The radon derived groundwater flux was 56 +/- 13 and 35 +/- 12 cm d(-1) in wet and dry conditions, respectively. The spatially distributed stations detected a well-defined small area located four kilometers upstream from the mouth of the estuary as a groundwater discharging hotspot. Estimates based on a Ra-223 and Ra-224 mass balance resulted in groundwater discharge estimates of 65 +/- 18 and 84 +/- 48 cm d(-1) in the wet and 18 +/- 5 and 20 +/- 6 cm d(-1) in the dry. The mixing model revealed contrasting results for deep vs. fresh groundwater contribution in wet and dry conditions. In wet conditions, deep fresh groundwater discharging into the estuary contributed 65% compared to the shallow saline groundwater (35%), while during dry conditions a larger contribution (80%) was related to shallow groundwater. A comprehensive spatial and temporal sampling strategy can produce groundwater discharge estimates with lower uncertainty and provides additional insight on where groundwater enters surface waters. (C) 2015 Elsevier B.V. All rights reserved.
机译:由于地下水的时空变化很大,因此量化地下水的排放量仍然是一个挑战。在这里,我们使用ra(Rn-222)和镭同位素(Ra-223和Ra-224)量化了向小河口排放的地下水。在4个时间序列站进行的高时间分辨率(30分钟时间步长)ra观测值可用于确定河口中地下水普遍存在的位置,并减少质量平衡模型的不确定性。基于短寿命镭同位素(在单个位置采样)开发了一个三端混合模型,以分离排放的地下水的浅层盐水和深层新鲜水源。结果表明,使用多个Rn-222时间序列站可以将地下水排放估算的总体不确定性从大约41%降低到23%。 wet在潮湿和干燥条件下的地下水通量分别为56 +/- 13 cm d(-1)和35 +/- 12 cm d(-1)。这些空间分布的气象站发现了一个明确定义的小区域,该区域位于河口口上游四公里处,是地下水排放的热点。根据Ra-223和Ra-224质量平衡进行的估算得出,在湿润地区的地下水排放估算为65 +/- 18和84 +/- 48 cm d(-1),在潮湿地区为18 +/- 5和20 +/-。干燥时为6厘米d(-1)。混合模型揭示了在干湿条件下深层地下水与新鲜地下水的对比结果。在潮湿条件下,排入河口的深层新鲜地下水贡献比浅层盐水地下水(35%)大65%,而在干燥条件下,与浅层地下水相关的贡献更大(80%)。全面的空间和时间采样策略可以得出具有较低不确定性的地下水流量估算值,并提供有关地下水进入地表水位置的更多信息。 (C)2015 Elsevier B.V.保留所有权利。

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