Rainfall-runoff modeling in the United States has made extensive use of the Soil Conservation Service (SCS) curve number method for computing infiltration losses from rainfall. Even though the method is well established and may be applied to a wide range of environments, it often results in highly erroneous runoff estimates for shallow water table environments. Flat topography, wetlands, and fine sands are characteristics that make places like Florida very different from the environments where the SCS method was originally developed. The SCS method arose from experiments with soils that are dominated by infiltration excess (Hortonian mechanism), where runoff occurs after rainfall intensity exceeds the infiltration capacity of the soil. In contrast, Florida is likely dominated by saturation excess runoff (Dunne mechanism), where the soil storage capacity between a shallow water table and the ground surface is filled, and all remaining rainfall becomes runoff. The sandy soils of Florida have very high infiltration capacities, and thus infiltration excess is less likely than saturation excess. As a consequence of the saturation-excess mechanism, wetlands expand in the wet season as the soil moisture storage around the perimeter is filled. A modified form of the SCS method is proposed with the objective that it is more suitable than the current method in flatly sloped, humid environments. Initial conditions, such as the pre-storm soil moisture profile and depth to water table, are critical when predicting runoff in these areas. Air encapsulation is addressed because its presence causes the soil storage capacity to be filled significantly faster than in its absence. Equations are presented that provide an estimate of the average depth to water table and average soil storage capacity in a catchment. Two Florida catchments and one runoff test bed were selected for testing the new methodology. The runoff test bed demonstrated the saturation-excess mechanism while the catchments provided larger-scale testing of the method. Though more data is needed to fully assess the performance of the method, the approach offers a more plausible mechanism for runoff estimation in shallow water table environments with sandy soils.

further development of the simple and promising analytical probabilistic approach / Urban stormwater management aims at mitigating the adverse impacts of urbanization. Hydrological models are used in support of stormwater management planning and design. There are three main approaches that can be applied for this modeling purpose: (1) continuous simulation approach which is accurate but time-consuming; (2) design storm approach, which is widely used and its accuracy highly depends on the selected antecedent moisture conditions and temporal distribution of design storms; and (3) the analytical probabilistic approach which is recently developed and still not used in practice. Although it is time-effective and it can produce results as accurate as the other two approaches; the analytical probabilistic approach requires further developments in order to make it more reliable and accurate. For this purpose, three subtopics are investigated in this thesis. (1) Rainfall data analysis as required by the analytical probabilistic approach with emphasis on testing the exponentiality of rainfall event duration, volume and interevent time (i.e., time separating it from its preceding rainfall event). A goodness-of-fit testing procedure that is suitable for this kind of data analysis was proposed. (2) Derivation of new analytical probabilistic models for peak discharge rate incorporating trapezoidal and triangular hydrograph shapes in order to include all possible catchment’s responses. And (3) the infiltration process is assumed to continue until the end of the rainfall event; however, the soil may get saturated earlier and the excess amount would contribute to the runoff volume which may have adverse impact if not taken into consideration. Thus, in addition to the infiltration process, the saturation excess runoff is also included and new models for flood frequencies are developed. All the models developed in this thesis are tested and compared to methods used in practice, reasonable results were obtained. / Thesis / Doctor of Philosophy (PhD) / Urban stormwater management aims at mitigating the adverse impacts of urbanization. Hydrological models are used in support of stormwater management planning and design. The analytical probabilistic stormwater management model (APSWM) is a promising tool for planning and design analysis. The purpose of this thesis is to further develop APSWM in order to make it more reliable and accurate. First, a clear procedure for rainfall data analysis as required by APSWM is provided. Second, a new APSWM is derived incorporating other runoff temporal-distribution patterns. Finally, the possibility of soil layer saturation while it is still raining is added to the model. All the models developed in this thesis are tested and compared to methods used in engineering practice, reasonable results were obtained.