氡(^(222)Rn)在地下水-地表水相互作用中的应用研究进展

Advances in ^(222)Rn application in the study of groundwater-surface water interactions

地下水地表水相互作用是水资源管理和地表水生态系统保护中重要的一个环节,氡同位素(^(222)Rn)由于其在地下水与地表水中含量差异显著、性质保守、检测难度低,广泛运用于地下水地表水相互作用的研究当中。本文通过总结分析^(222)Rn在不同地表水体(海水、河水、湖水等)中的应用,指出刻画地下水氡浓度的异质性是估算地下水排泄的重点和难点。在估算海底地下水排泄(SGD)时,氡的混合损失项估算不确定、海水氡浓度时空变异性、SGD的多组分特征等可能给估算结果带来较大不确定性;在估算河流地下水排泄时难以确定氡的大气逃逸量;研究人员对氡在示踪地表水补给地下水方面的研究程度相对不足。本文从科学研究和实际生产方面,对^(222)Rn的研究应用提出以下潜在方向:(1)降低地下水氡空间变异性对估算地下水排泄量的影响;(2)针对不同水体、不同水文条件,准确刻画氡的大气逃逸量;(3)拓展^(222)Rn示踪能够解决的科学问题;(4)将氡质量平衡模型计算与不确定分析相结合,实现软件化。

Groundwater-surface water interaction is important for water resource management and aquatic ecosystem protection.Radon(^(222)Rn)has been widely used in the investigation of groundwater-surface water interaction owing to its application advantages,such as its large concentration difference between groundwater and surface water,noble gas properties,and ease of measurement.In this study,we analyzed ^(222)Rn applications in different surface waters(sea,river,lake,etc.)and identified the ^(222)Rn concentration variation in groundwater as a key challenge in the estimation of groundwater discharge into surface water.When estimating submarine groundwater discharge(SGD),^(222)Rn mixing loss and its variable concentrations in seawater,and the complexity of SGD components would produce uncertainties in the estimation results.Also,it is difficult to determine ^(222)Rn atmospheric loss when estimating riverine groundwater discharge using the ^(222)Rn method.Further,little attention has been paid to the application of ^(222)Rn in tracing surface water flow into groundwater.Thus,future studies on ^(222)Rn application in regarding to groundwater-surface water interaction should focus on(1)reducing final uncertainty in ^(222)Rn-based estimation of groundwater discharge due to variable ^(222)Rn concentrations in groundwater;(2)accurately characterizing the ^(222)Rn atmospheric loss for different surface waters under different hydrological conditions;(3)expanding scientific applications of the ^(222)Rn method;and(4)developing a software that integrates the ^(222)Rn mass balance model and uncertainty analysis.