Reliability-Based Approach to Hyporheic Zone Depth Delineation for Groundwater Remediation Strategy

Natural phenomena like hyporheic zone depths show intrinsic statistical behavior due to large variability of related parameters. In the previous researches, authors proposed a deterministic method to delineate hyporheic zone depth using a simple field temperature measurement, and studied a probabilistic method to present a proper statistical distribution model for hyporheic zone depth. As a next step forward, this research proposes remediation strategies on contaminated groundwater system in relation to hyporheic zone depth management. Primarily, demand of hyporheic zone depth to achieve a required recovery ratio is predetermined. The field hyporheic zone depth is, then, changed according to each strategies. The two probabilistic variables, demand and field values, are modified such that the difference are reduced. 

The index applied to evaluate each strategy in this paper was adopted from the concept of reliability index. This approach is frequently used in many fields of science and engineering, including a safety design of structures. The key point of safety design involves sufficiency of safety margins between a strength criterion and the requirements, and this is what the reliability index evaluates. The paper is structured to introduce reliability-based approach in terms of general concept and hyporheic zone depth management first, and proceeds to a development of index. The paper concludes with performance evaluation of strategies. This paper is of value because a combination of the previous research on the probabilistic property extraction of hyporheic zone depth and the presented approach of performance evaluation has potential to offer another useful tool to the remediation of contaminated groundwater.

Acknowledgement: This research was funded by the Korea Ministry of Environment through the strategic EcoSSSoil Project at the Korea Environmental Industry and Technology Institute (grant no. 2019002820004) and National Research Foundation of Korea (NRF), funded by the Ministry of Education (grant numbers 2019R1I1A2A01057002 and 2019R1A61A0303