Soil water retention (SWR) function is an important model that provides an empirical relationship between soil moisture and capillary pressure. We present a simple Python tool for fitting different types of SWR functions to laboratory-measured soil moisture data. Three different optimization methods including the Levenberg-Marquardt (LM) method, Trust Region Reflective (TR) method, and Dog Box (DB) method are considered. We used all three methods to fit the van Genuchten (VG) and Brooks and Corey (BC) models to ten soil moisture datasets. Our results show that the TR method, which allows the user to search for optimal parameter values within a constrained region, is the best approach for fitting these models. We developed a new graphical procedure for evaluating the guesstimates and bounds for different SWR model parameters. Overall, the TR method available in Python, together with the proposed graphical procedure, is an excellent approach for fitting both VG and BC models to soil moisture data.

The Theis equation is an important mathematical model used for analyzing drawdown data obtained from pumping tests to estimate aquifer parameters. Since the Theis model is a nonlinear equation, a complex graphical procedure is employed for fitting this equation to pump test data. This graphical method was originally proposed by Theis in the late 1930s, and since then, all the groundwater textbooks have included this fitting method. Over the past 90 years, every groundwater hydrologist has been trained to use this tedious procedure for estimating the values of aquifer transmissivity (T) and storage coefficient (S). Unfortunately, this mechanical procedure does not provide any intuition for understanding the inherent limitations in this manual fitting procedure. Furthermore, it does not provide an estimate for the parameter error. In this study, we employ the public domain coding platform Python to develop a script, namely, PyTheis, which can be used to simultaneously evaluate T and S values, and the error associated with these two parameters. We solve nine test problems to demonstrate the robustness of the Python script. The test problems include several published case studies that use real field data. Our tests show that the proposed Python script can efficiently solve a variety of pump test problems. The code can also be easily adapted to solve other hydrological problems that require nonlinear curve fitting routines.

Soil moisture plays a key role in land-atmosphere interactions and is an important variable in hydrological modeling. Satellite-based microwave sensors have been demonstrated for estimating surface soil moisture, but the spatial resolution is poor. Retrieval of soil moisture over inhomogeneous terrain is difficult. There is a need for fine-resolution soil moisture data to support both scientific modeling research and operational applications.The Remote Sensing Center at the University of Alabama has developed a compact, ultra-wideband microwave radar operating over the frequency range of 2-6 GHz for airborne soil moisture measurements. A highly linear, highly configurable chirp is generated by a direct digital synthesizer (DDS) driven voltage-controlled oscillator (VCO) with phase-locked loop (PLL). This system enables us to generate an ultra-linear chirp of up to 10 GHz bandwidth. We have also developed a custom ultrawideband antenna to collect data over incidence angles between 0 and 50 degrees with an adequate signal-to-noise ratio and meet the bandwidth requirements. The radar performance is verified using simulated targets in the laboratory, and the measured impulse response is close to the ideal response.We have integrated the radar with a hybrid multirotor unmanned aircraft system (UAS) that can be operated within FAA limits. The long endurance and low-speed capability of the hybrid multirotor aircraft minimizes motion-related errors. We have operated the radar and collected data at test sites near Tuscaloosa, AL. Radar measurements are being calibrated and validated against detailed in-situ measurements collected using soil moisture probes. In this paper, we will discuss the design and development of the radar, measurements, and field results.

A novel radial flow experimental system to study saltwater intrusion processes in an island aquifer is presented. The study investigated steady state and transient scenarios involving advancing and receding saltwater wedges in a circular island. The experimental results were simulated using the density-coupled version of the MODFLOW-USG code. The experimental data along with the model simulation results are employed to develop a new radial benchmark problem for testing density-coupled models used for simulating saltwater intrusion processes. The experimental data for transient changes in toe position and freshwater storage level indicated an asymmetric pattern where the intrusion time scale is greater than the recession time scale. Numerical experiments were completed to further investigate this asymmetric effect and to intercompare the associated transient transport processes in circular and linear strip islands. We also analyzed the sensitivity of island geometry in controlling the freshwater storage levels under different recharge conditions. Modeling results show that for similar-sized systems, circular islands are more efficient in storing freshwater than linear strip islands.

Fresh groundwater in an island aquifer is an extremely important resource that is highly vulnerable to variations in natural weather cycles and climate change effects. On small islands, precipitation creates subsurface freshwater lenses that float on top of coalesced saltwater that has intruded from the surrounding seawater. The volume and shape of these highly vulnerable freshwater lenses depend on the size and shape of the island, underlying geology, and the rate and duration of groundwater recharge. This study focuses on the transient changes in freshwater storage volume within these lenses. We completed a sand tank experiment to visualize an evolving freshwater lens that undergoes a dry- and -wet recharge cycle resulting in forming a shrinking and an expanding lens. The physical experiments provided a dataset to develop a robust numerical model that can rigorously simulate different types of evolving transient freshwater lenses. Our laboratory data along with past literature information have indicated that the shrinking of a freshwater lens occurred at a slower rate relative to an expanding freshwater lens. This aspect of a rather rapid freshwater volume recovery was investigated further using the numerical model by imposing cyclic recharge patterns to study the impacts of shortened recharge periods on freshwater storage in island aquifers. The results show that a sustainable dynamic equilibrium condition can be achieved within a few cycles of periodic recharge. Unsustainable conditions were only encountered at extremely short recharge periods. The model was then extended to simulate a freshwater lens in Dauphin Island, Alabama, to assess changes in freshwater storage under realistic wet and dry recharge cycles. The experimental data together with the modeling results presented in this study provide a better understanding of transient changes in freshwater storage patterns in small islands.