Incorporating Influences of Shallow Groundwater Conditions in Curve Number-Based Runoff Estimation Methods

Abstract

Runoff generation process in any watershed is mainly affected by precipitation, land use and land cover, existing soil moisture conditions and losses. Shallow groundwater table conditions that occur in many regions are known to affect the soil moisture retention capacity, infiltration and ultimately the runoff. A methodology that links soil moisture capacity to the shallow groundwater table or High-Water Table (HWT) using a nonlinear functional relationship within a curve number (CN)-based runoff estimation method, is proposed and investigated using single and continuous event simulation models in this study. The relationship is used to obtain an adjusted CN that incorporates the effect of change in soil moisture conditions due to HWT. The CN defined for average conditions is replaced by this adjusted CN and is used for runoff estimation. A single event model that uses Soil Conservation Service (SCS) CN approach is used for evaluation of variations in runoff depths and peak discharges based on different HWT conditions. A real-life case study from central Florida region in the USA was adopted for application and evaluation of the proposed methodology. Results from the case study application of the models indicate that HWT conditions significantly influence the magnitudes of peak discharge by as much as 43% and runoff depth by 48% as the water table height reaches the land surface. The magnitudes of increases in peak discharges are specific to case study region and are dependent on the functional form of the relationship linking HWT and soil storage capacity. Also, for specific values of HWT, an equivalency between HWT-based CN and wet antecedent moisture condition (AMC)-based CN can be established.