Increasing Groundwater Availability and Seasonal Base Flow Through Agricultural Managed Aquifer Recharge in an Irrigated Basin

Groundwater aquifers provide an important “insurance” against climate variability. Due to prolonged droughts and/or irrigation demands, groundwater exploitation results in significant groundwater storage depletion. Managed aquifer recharge (MAR) is a promising management practice that intentionally places or retains more water in groundwater aquifers than would otherwise naturally occur. In this study, we examine the possibility of using large irrigated agricultural areas as potential MAR locations (Ag-MAR). Using the California Central Valley Groundwater-Surface Water Simulation Model we tested four different agricultural recharge land distributions, two streamflow diversion locations, eight recharge target amounts, and five recharge timings. These scenarios allowed a systematic evaluation of Ag-MAR on changes in regional, long-term groundwater storage, streamflow, and groundwater levels. The results show that overall availability of stream water for recharge is critical for Ag-MAR systems. If stream water availability is limited, longer recharge periods at lower diversion rates allow diverting larger volumes and more efficient recharge compared to shorter diversion periods with higher rates. The recharged stream water increases both groundwater storage and net groundwater contributions to streamflow. During the first decades of Ag-MAR operation, the diverted water contributed mainly to groundwater storage. After 80 years of Ag-MAR operation about 34% of the overall diverted water remained in groundwater storage while 66% discharged back to streams, enhancing base flow during months with no recharge diversions. Groundwater level rise is shown to vary with the spatial and temporal distribution of Ag-MAR. Overall, Ag-MAR is shown to provide long-term benefits for water availability, in groundwater and in streams

Bayesian hydrograph separation in a minimally gauged alpine volcanic watershed in central Chile

This study examines the question of how much information one can extract from a tracer-based hydrograph separation in a remote and minimally gaged alpine catchment in Chile. We combine PCA-based endmember mixing analysis to identify the sources of flow contribution to the Diguillín River with a hierarchical Bayesian mixing model to integrate spatial and temporal variability in endmember concentration and quantify the source contributions to streamflow over time. The PCA-analysis shows that precipitation isotopes do not vary by elevation (e.g. snow and rainfall had identical signatures) but vary significantly by season, and that a third endmember is necessary to bound streamflow variability at the basin outlet, which was not captured by our field sampling. One of the main advantages of Bayesian methods is the quasi-machine learning capabilities, where we treated the third endmember as a parameter from which the mixing model could both estimate proportional contributions as well as posterior estimates for the tracer concentrations. The two tracer, three endmember hydrograph separation revealed groundwater to be the largest and precipitation (rain and snow) to be the smallest contributor, on average, to streamflow with the third unknown endmember contributing around 40% of streamflow during the Winter wet season. We hypothesize that interflow is occurring as the third endmember in the Alto Diguillín subwatershed, based on inferred tracer values and the presence of alluvium atop impermeable bedrock along certain reaches. More work is necessary to observe and sample these flowpaths, which was not possible during this study. The results of this work have implications for water resource management, since groundwater sustains the majority of streamflow in the Diguillín, and climate change will impact the timing and quantity of baseflow and interflow. Overall, we demonstrate the utility of combining PCA with Bayesian statistical modeling and inference to extract maximum information from a limited field dataset in a remote alpine catchment. The findings of this work can guide future water management in the Diguillín, but also provide clear questions for future research

Particle tracer transport in a sloping soil lysimeter under periodic, steady state conditions

Colloid transport through complex and dynamic (i.e. non-steady-state) hydrologic systems is rarely studied, owing to the difficulty of constraining initial and boundary conditions and quantifying colloid-porous media and colloid-colloid interactions in transient flow systems. Here we present a particle tracer experiment conducted on a sloped lysimeter receiving periodic rainfall events for 10 days. Four unique, DNA-labelled particle tracers were injected both in sequence and in parallel, together with a conservative tracer (deuterium), over the course of the first day and allowed to move through the system. Discharge-particle tracer concentration curves and the spatial distribution of particle tracer mass retained in the soil at the end of the experiment were found to be highly dependent on the timing of the tracer injection and the precipitation input and subsequent dynamic response of the water table. Overall, neglecting the total DLT recovery rate, the DLT particle tracer breakthrough trend (DNA-labelled particle tracer 4) was similar to deuterium and decreased over time with the exception of a few peaks later in the experiment. The individual particle tracer breakthrough curves suggest a complex system with different fast transport mechanisms (e.g. capillary barrier and size exclusion effect) and slow retention-release mechanisms (e.g. straining, physical-chemical adsorption), which resulted in particle tracers transferring faster than deuterium in the first 10 h of the experiment but being exceeded by deuterium soon after deuterium started to break through. The experiment not only highlights the interaction of repeated colloidal pollution events in hydrologic systems with different pre-event saturation conditions, but also the benefits of using multiple synchronous or sequential tracer applications to dissect explicit formulations of water flow and colloid transport processes in complex and dynamic hydrological systems. Such explicit process formulations could help improve understanding hydrologically-controlled transport through catchments and the quantitative prediction of these processes with water quality models

Three real-space discretization techniques in electronic structure calculations

A characteristic feature of the state-of-the-art of real-space methods in electronic structure calculations is the diversity of the techniques used in the discretization of the relevant partial differential equations. In this context, the main approaches include finite-difference methods, various types of finite-elements and wavelets. This paper reports on the results of several code development projects that approach problems related to the electronic structure using these three different discretization methods. We review the ideas behind these methods, give examples of their applications, and discuss their similarities and differences.Comment: 39 pages, 10 figures, accepted to a special issue of "physica status solidi (b) - basic solid state physics" devoted to the CECAM workshop "State of the art developments and perspectives of real-space electronic structure techniques in condensed matter and molecular physics". v2: Minor stylistic and typographical changes, partly inspired by referee comment

Toward improved prediction of the bedrock depth underneath hillslopes: Bayesian inference of the bottom‐up control hypothesis using high‐resolution topographic data

The depth to bedrock controls a myriad of processes by influencing subsurface flow paths, erosion rates, soil moisture, and water uptake by plant roots. As hillslope interiors are very difficult and costly to illuminate and access, the topography of the bedrock surface is largely unknown. This essay is concerned with the prediction of spatial patterns in the depth to bedrock (DTB) using high‐resolution topographic data, numerical modeling, and Bayesian analysis. Our DTB model builds on the bottom‐up control on fresh‐bedrock topography hypothesis of Rempe and Dietrich (2014) and includes a mass movement and bedrock‐valley morphology term to extent the usefulness and general applicability of the model. We reconcile the DTB model with field observations using Bayesian analysis with the DREAM algorithm. We investigate explicitly the benefits of using spatially distributed parameter values to account implicitly, and in a relatively simple way, for rock mass heterogeneities that are very difficult, if not impossible, to characterize adequately in the field. We illustrate our method using an artificial data set of bedrock depth observations and then evaluate our DTB model with real‐world data collected at the Papagaio river basin in Rio de Janeiro, Brazil. Our results demonstrate that the DTB model predicts accurately the observed bedrock depth data. The posterior mean DTB simulation is shown to be in good agreement with the measured data. The posterior prediction uncertainty of the DTB model can be propagated forward through hydromechanical models to derive probabilistic estimates of factors of safety.Key Points:We introduce an analytic formulation for the spatial distribution of the bedrock depthBayesian analysis reconciles our model with field data and quantifies prediction and parameter uncertaintyThe use of a distributed parameterization recognizes geologic heterogeneitiesPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137555/1/wrcr22005.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137555/2/wrcr22005_am.pd

Availability of high-magnitude streamflow for groundwater banking in the Central Valley, California

California's climate is characterized by the largest precipitation and streamflow variability observed within the conterminous US This, combined with chronic groundwater overdraft of 0.6-3.5 km3 yr-1, creates the need to identify additional surface water sources available for groundwater recharge using methods such as agricultural groundwater banking, aquifer storage and recovery, and spreading basins. High-magnitude streamflow, i.e. flow above the 90th percentile, that exceeds environmental flow requirements and current surface water allocations under California water rights, could be a viable source of surface water for groundwater banking. Here, we present a comprehensive analysis of the magnitude, frequency, duration and timing of high-magnitude streamflow (HMF) for 93 stream gauges covering the Sacramento, San Joaquin and Tulare basins in California. The results show that in an average year with HMF approximately 3.2 km3 of high-magnitude flow is exported from the entire Central Valley to the Sacramento-San Joaquin Delta often at times when environmental flow requirements of the Delta and major rivers are exceeded. High-magnitude flow occurs, on average, during 7 and 4.7 out of 10 years in the Sacramento River and the San Joaquin-Tulare Basins, respectively, from just a few storm events (5-7 1-day peak events) lasting for 25-30 days between November and April. The results suggest that there is sufficient unmanaged surface water physically available to mitigate long-term groundwater overdraft in the Central Valley

Availability of high-magnitude streamflow for groundwater banking in the Central Valley, California

California's climate is characterized by the largest precipitation and streamflow variability observed within the conterminous US This, combined with chronic groundwater overdraft of 0.6-3.5 km3 yr-1, creates the need to identify additional surface water sources available for groundwater recharge using methods such as agricultural groundwater banking, aquifer storage and recovery, and spreading basins. High-magnitude streamflow, i.e. flow above the 90th percentile, that exceeds environmental flow requirements and current surface water allocations under California water rights, could be a viable source of surface water for groundwater banking. Here, we present a comprehensive analysis of the magnitude, frequency, duration and timing of high-magnitude streamflow (HMF) for 93 stream gauges covering the Sacramento, San Joaquin and Tulare basins in California. The results show that in an average year with HMF approximately 3.2 km3 of high-magnitude flow is exported from the entire Central Valley to the Sacramento-San Joaquin Delta often at times when environmental flow requirements of the Delta and major rivers are exceeded. High-magnitude flow occurs, on average, during 7 and 4.7 out of 10 years in the Sacramento River and the San Joaquin-Tulare Basins, respectively, from just a few storm events (5-7 1-day peak events) lasting for 25-30 days between November and April. The results suggest that there is sufficient unmanaged surface water physically available to mitigate long-term groundwater overdraft in the Central Valley