Civil Engineering ETDs

Publication Date

Fall 12-18-2021


Approximately 30% of the Earth’s land surface is characterized as arid or semiarid, including much of the western United States. Accurate runoff predictions are important for informed watershed management, particularly in rapidly urbanizing areas. Infiltration excess overland flow is the dominant mechanism for runoff generation in many dryland basins, and event-based infiltration or loss models are commonly used to estimate runoff. However, predictions are associated with considerable uncertainty due to the role antecedent soil moisture, an initial condition that must be set by the modeler. The objectives of my research were to (1) evaluate the impact of antecedent soil moisture on runoff, (2) investigate methods for monitoring soil moisture conditions at the catchment scale, and (3) quantify the connection between soil moisture and model parameters to improve model performance. Research was conducted in central New Mexico and based on data from the Walnut Gulch experimental watershed in Arizona.

Results under objective 1 show that across spatial scales, soil moisture has a large impact on runoff. High initial moisture content led to substantially higher runoff ratios at the test plot (2.8 m2) and catchment scales (2.8 km2). Failing to account for antecedent conditions caused simulated runoff volume errors of up to one order of magnitude. Given the importance of antecedent conditions, I developed a novel method for monitoring soil moisture conditions at the catchment scale under objective 2. The approach is based on the antecedent precipitation index (API) and uses rainfall estimates from ground-based weather radar. Compared to satellite-derived soil moisture data, the API-based method performed well with respect to accuracy (root mean square error 0.014-0.018 m3 m-3), latency, as well as spatial and temporal resolution. Under objective 3, I optimized parameters for seven simple loss models at the plot scale (2.8 m2) and established relationships between model parameters and antecedent conditions. I then tested model performance at the hillslope (1.5-3.7 ha) and catchment scales (2.4-2.8 km2) based on measured runoff data. At the hillslope scale, rainfall simulation can be used successfully to parameterize models, a valuable tool in data-spares regions. At the catchment scale, most models showed positive bias, indicating that other processes (such as channel- or transmission losses) play an important role in determining the catchment runoff response.


Semiarid, Soil moisture, Runoff, Infiltration, Rainfall simulation, Antecedent conditions

Document Type




Degree Name

Civil Engineering

Level of Degree


Department Name

Civil Engineering

First Committee Member (Chair)

Dr. Mark Stone

Second Committee Member

Dr. John Stormont

Third Committee Member

Dr. Gary Weissmann

Fourth Committee Member

Dr. Todd Caldwell