As a result of climate change, California is experiencing the impact of more extreme weather patterns including longer drought periods and atmospheric rivers resulting in extreme snow pack and heavy flood flows. CA faces a significant challenge to mitigate these impacts while simultaneously providing resilient sources of water under uncertain future conditions. One approach that addresses both flood mitigation and water storage is the use of Managed Aquifer Recharge (MAR). Ventura County Waterworks District #1 (VCWWD) is designing a MAR recharge facility to divert flood flows in the adjacent Arroyo Las Posas to a series of engineered basins, where water will infiltrate and replenish the local aquifer (estimated recharge: 3000 acre-feet annually). However, large uncertainties in percolation rates and an inability to predict or improve percolation (measured: 5 and 16 cm/day) places large uncertainties on the facility’s ultimate performance (and impact) on VCWWD’s overall strategy for sustainable groundwater management. The goals of this project are to use a suite of geophysical techniques, point sensors and novel modeling approaches to measure the basin(s) spatial recharge rates, where and how the water is infiltrating (fast paths) and how will basin modification improve recharge rates. Selected basins will first be characterized using electromagnetic methods and electrical resistivity tomography (ERT) coupled with soil cores to estimate the distribution of subsurface permeability in order to design the infiltration monitoring layout. During managed flooding events Spontaneous Potential will be used to monitor subsurface leakage from the basins back into the river. Within a basin, novel vertical Distributed Temperature Profiling sensors will measure diurnal temperature fluxes to calculate spatially distributed 1-D vertical recharge rates and 3D time-lapse ERT to monitor and measure the spatially dynamic recharge. ERT results will be coupled with multi-point geostatistical simulations to estimate soil permeability field scenarios and with novel joint inversion codes to estimate volumetric recharge and rates, offering a powerful suite of tools for water managers to quantify, and potentially improve basin recharge rates and develop operational and maintenance plans to maximize recharge.

A multi-scale understanding of processes controlling the nitrogen budget is essential for predicting how nitrogen loads will be affected by climate-induced disturbances. Recent studies in snowmelt-dominated catchments have documented changes in nitrogen retention over time, such as declines in watershed exports of nitrogen, though there is a limited understanding of the controlling processes driving these trends. Working in the mountainous headwater East River Colorado watershed, our study aims to refine this process-based understanding by exploring the effects of riparian hollows as nitrogen cycling hotspots. The objectives of this study are to (1) quantify the influence of riparian hollows on nitrogen retention in snowmelt-dominated catchments, (2) understand how disturbances (i.e. early snowmelt, long summer droughts) and heterogeneities affect the nitrogen-retention capacity of riparian hollows, and (3) quantify the relative contribution of riparian hollows to the watershed nitrogen budget using high-resolution LIDAR watershed data. We used a multi-component flow and reactive transport model, MIN3P, to simulate the biogeochemical kinetics of riparian hollows, using data from the East River watershed to parameterize, constrain, and validate the model. Several hydrological, biogeochemical, and geological perturbations were then imposed across simulations to assess the effects of abrupt and gradual perturbations on riparian hollow hydrobiogeochemical dynamics. Topographic position and wetness indices were used to scale the net yearly storage and flux terms from riparian hollows, and reveal the significant impacts hollows can have on aggregated watershed biogeochemistry. Initial model results suggest that riparian hollows serve as significant nitrogen sinks, and that earlier snowmelt and extended dry season considerably limit denitrifying processes. Our work linking remote sensing and empirical scaling techniques to numerical biogeochemical simulations is an important first-step in assessing nitrogen-retaining features relative to the watershed nitrogen budget.

Agricultural managed aquifer recharge (AgMAR) is a proposed management strategy whereby surface water flows are used to intentionally flood croplands with the purpose of recharging underlying aquifers. However, legacy nitrate (NO3-) contamination in agriculturally-intensive regions poses a threat to groundwater resources under AgMAR. To address these concerns, we use a reactive transport modeling framework to better understand the effects of AgMAR management strategies (i.e., by varying the frequency, duration between flooding events, and amount of water) on N leaching to groundwater under different stratigraphic configurations and antecedent moisture conditions. In particular, we examine the potential of denitrification and nitrogen retention in deep vadose zone sediments using variable AgMAR application rates on two-dimensional representations of differently textured soils, soils with discontinuous bands/channels, and soils with preferential flow paths characteristic of typical agricultural field sites. Our results indicate that finer textured sediments, such as silt loams, alone or embedded within high flow regions, are important reducing zones providing conditions needed for denitrification. Simulation results further suggest that applying recharge water all-at-once, rather than in increments, increases denitrification within the vadose zone, but transports higher concentrations of NO3- deeper into the profile. This transport into deeper depths can be aggravated by wetter antecedent soil moisture conditions. We conclude that ideal AgMAR management strategies can be designed to enhance denitrification in the subsurface and reduce N leaching to groundwater, while specifically accounting for lithologic heterogeneity, antecedent soil moisture conditions, and depth to the water table.