220 / 2024-02-28 10:52:38

A study on spatial distribution techniques for groundwater depth in GSSHA groundwater modeling

Distributed Model, Groundwater Simulation, GSSHA, Aquifer Depth, Groudwater Surface, Groundwater Discharge

The discharge from groundwater systems is a crucial source for maintaining streamflow in lowland rivers during dry periods. Despite the advancement in hydrological analysis with the adoption of distributed models in the field of water resources, research on groundwater-related parameters, such as aquifer depth, remains insufficient. This study predicts the physical distribution of aquifer depth, a topographical data parameter in distributed models, and evaluates the simulation results of groundwater to ascertain the applicability of this technique. The Soyang River basin, including its ungauged northern catchments, was select ed as the study area, and the detailed distributed model GSSHA (Gridded Surface Hydrologic Analysis) was employed.

The method for estimating aquifer depth was divided into three scenarios for simulation. These include an equal distribution of aquifer depth derived from basin groundwater data (Scenario 1), a linear regression assuming an inverse relationship between surface elevation and aquifer depth (Scenario 2), and the application of a regression in the Log dimension under the same assumption (Scenario 3). The applicability was verified by comparing the calculated discharge and groundwater levels with the Soyang Dam inflow data and observations from six groundwater monitoring stations in the basin.

The error assessment of simulated discharge for each scenario indicated that the equal distribution method, commonly used in previous studies, most accurately reflected observed peak flows. However, the linear regression analysis showed the best results in terms of indicators representing the extent of under or overestimation and the efficiency of the model.

Therefore, applying an inverse relationship between surface elevation and aquifer depth in groundwater simulation is considered more rational than the conventional method of equal distribution. It is anticipated that deriving a precise regression relationship between arbitrary factors and aquifer depth will lead to more rational and reliable outcomes. Furthermore, precise groundwater simulation at the basin level is expected to significantly contribute to research areas of increasing interest, such as maintaining river flow and dry season discharge