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

Evaluation of Analytical Methods to Study Aquifer Properties with Pumping Tests in Coastal Aquifers with Numerical Modelling (Motril-Salobreña Aquifer)

Two pumping tests were performed in the unconfined Motril-Salobreña detrital aquifer in a 250 m-deep well 300 m from the coastline containing both freshwater and saltwater. It is an artesian well as it is in the discharge zone of this coastal aquifer. The two observation wells where the drawdowns are measured record the influence of tidal fluctuations, and the well lithological columns reveal high vertical heterogeneity in the aquifer. The Theis and Cooper-Jacob approaches give average transmissivity (T) and storage coefficient (S) values of 1460 m2 /d and 0.027, respectively. Other analytical solutions, modified to be more accurate in the boundary conditions found in coastal aquifers, provide similar T values to those found with the Theis and Cooper-Jacob methods, but give very different S values or could not estimate them. Numerical modelling in a synthetic model was applied to analyse the sensitivity of the Theis and Cooper-Jacob approaches to the usual boundary conditions in coastal aquifers. The T and S values calculated from the numerical modelling drawdowns indicate that the regional flow, variable pumping flows, and tidal effect produce an error of under 10 % compared to results obtained with classic methods. Fluids of different density (freshwater and saltwater) cause an error of 20 % in estimating T and of over 100 % in calculating S. The factor most affecting T and S results in the pumping test interpretation is vertical heterogeneity in sediments, which can produce errors of over 100 % in both parameters.This research has been financed by Project CGL2012-32892 (Ministerio de Economía y Competitividad of Spain) and by the Research Group Sedimentary Geology and Groundwater (RNM-369) of the Junta de Andalucía

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

Identifying Agricultural Managed Aquifer Recharge Locations to Benefit Drinking Water Supply in Rural Communities

The southern Central Valley of California is one of the most productive agricultural regions in the world. Yet, decades of groundwater use beyond sustainable yield have left rural communities highly vulnerable to shortages and contamination of their drinking water supply. As state regulation begins to address these issues, a need exists to design adaptive and appropriate management systems to increase resilience of rural communities. Targeted managed aquifer recharge on agricultural land (Ag-MAR) near rural communities is one such strategy that could potentially stabilize groundwater tables and maintain or improve groundwater quality in domestic supply wells. Here we present a geographic information system-based multicriteria decision analysis that combines biophysical data (soils, land use, and surface water conveyance) with groundwater modeling and particle tracking to identify suitable agricultural land parcels for multibenefit groundwater recharge within well capture zones of 288 rural communities. Parcels are prioritized using a vulnerability index to change in groundwater supply, derived from well reliance and failures, pesticide applications, land subsidence, and socio-economic data. Our analysis identifies 2,998 suitable land parcels for Ag-MAR within the well capture zones of 149 of the 288 communities, of which 144 rely mainly on groundwater for drinking water. The majority of identified Ag-MAR parcels serve communities ranked as having extreme or very high vulnerability to changes in groundwater supply. Our research produces new understanding of factors contributing to community vulnerability and resilience to changes in drinking water supply and can be used to discuss actions to help achieve a stable and high-quality water supply

A Bayesian approach to infer nitrogen loading rates from crop and land-use types surrounding private wells in the Central Valley, California

This study is focused on nitrogen loading from a wide variety of crop and land-use types in the Central Valley, California, USA, an intensively farmed region with high agricultural crop diversity. Nitrogen loading rates for several crop types have been measured based on field-scale experiments, and recent research has calculated nitrogen loading rates for crops throughout the Central Valley based on a mass balance approach. However, research is lacking to infer nitrogen loading rates for the broad diversity of crop and land-use types directly from groundwater nitrate measurements. Relating groundwater nitrate measurements to specific crops must account for the uncertainty about and multiplicity in contributing crops (and other land uses) to individual well measurements, and for the variability of nitrogen loading within farms and from farm to farm for the same crop type. In this study, we developed a Bayesian regression model that allowed us to estimate land-use-specific groundwater nitrogen loading rate probability distributions for 15 crop and land-use groups based on a database of recent nitrate measurements from 2149 private wells in the Central Valley. The water and natural, rice, and alfalfa and pasture groups had the lowest median estimated nitrogen loading rates, each with a median estimate below 5 kg N ha−1 yr−1. Confined animal feeding operations (dairies) and citrus and subtropical crops had the greatest median estimated nitrogen loading rates at approximately 269 and 65 kg N ha−1 yr−1, respectively. In general, our probability-based estimates compare favorably with previous direct measurements and with mass-balance-based estimates of nitrogen loading. Nitrogen mass-balance-based estimates are larger than our groundwater nitrate derived estimates for manured and nonmanured forage, nuts, cotton, tree fruit, and rice crops. These discrepancies are thought to be due to groundwater age mixing, dilution from infiltrating river water, or denitrification between the time when nitrogen leaves the root zone (point of reference for mass-balance-derived loading) and the time and location of groundwater measurement