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Alan L. Flint

Publications and source records attributed to Alan L. Flint.

At least 55 records · Page 3Linked to original sources
USGS2013

Cross-scale modeling of surface temperature and tree seedling establishment inmountain landscapes

Abstract: Introduction: Estimating surface temperature from above-ground field measurements is important for understanding the complex landscape patterns of plant seedling survival and establishment, processes which occur at heights of only several centimeters. Currently, future climate models predict temperature at 2 m above ground, leaving ground-surface microclimate not well characterized. Methods: Using a network of field temperature sensors and climate models, a ground-surface temperature method was used to estimate microclimate variability of minimum and maximum temperature. Temperature lapse rates were derived from field temperature sensors and distributed across the landscape capturing differences in solar radiation and cold air drainages modeled at a 30-m spatial resolution. Results: The surface temperature estimation method used for this analysis successfully estimated minimum surface temperatures on north-facing, south-facing, valley, and ridgeline topographic settings, and when compared to measured temperatures yielded an R2 of 0.88, 0.80, 0.88, and 0.80, respectively. Maximum surface temperatures generally had slightly more spatial variability than minimum surface temperatures, resulting in R2 values of 0.86, 0.77, 0.72, and 0.79 for north-facing, south-facing, valley, and ridgeline topographic settings. Quasi-Poisson regressions predicting recruitment of Quercus kelloggii (black oak) seedlings from temperature variables were significantly improved using these estimates of surface temperature compared to air temperature modeled at 2 m. Conclusion: Predicting minimum and maximum ground-surface temperatures using a downscaled climate model coupled with temperature lapse rates estimated from field measurements provides a method for modeling temperature effects on plant recruitment. Such methods could be applied to improve projections of species’ range shifts under climate change. Areas of complex topography can provide intricate microclimates that may allow species to redistribute locally as climate changes.

Ecological Processes↗
USGS2013

Fine-scale hydrologic modeling for regional landscape applications: the California Basin Characterization Model development and performance

Introduction Resource managers need spatially explicit models of hydrologic response to changes in key climatic drivers across variable landscape conditions. We demonstrate the utility of a Basin Characterization Model for California (CA-BCM) to integrate high-resolution data on physical watershed characteristics with historical or projected climate data to predict watershed-specific hydrologic responses. Methods The CA-BCM applies a monthly regional water-balance model to simulate hydrologic responses to climate at the spatial resolution of a 270-m grid. The model has been calibrated using a total of 159 relatively unimpaired watersheds for the California region. Results As a result of calibration, predicted basin discharge closely matches measured data for validation watersheds. The CA-BCM recharge and runoff estimates, combined with estimates of snowpack and timing of snowmelt, provide a basis for assessing variations in water availability. Another important output variable, climatic water deficit , integrates the combined effects of temperature and rainfall on site-specific soil moisture, a factor that plants may respond to more directly than air temperature and precipitation alone. Model outputs are calculated for each grid cell, allowing results to be summarized for a variety of planning units including hillslopes, watersheds, ecoregions, or political boundaries. Conclusions The ability to confidently calculate hydrologic outputs at fine spatial scales provides a new suite of hydrologic predictor variables that can be used for a variety of purposes, such as projections of changes in water availability, environmental demand, or distribution of plants and habitats. Here we present the framework of the CA-BCM model for the California hydrologic region, a test of model performance on 159 watersheds, summary results for the region for the 1981–2010 time period, and changes since the 1951–1980 time period.

California↗
USGS2013

Present, future, and novel bioclimates of the San Francisco, California region

Bioclimates are syntheses of climatic variables into biologically relevant categories that facilitate comparative studies of biotic responses to climate conditions. Isobioclimates, unique combinations of bioclimatic indices (continentality, ombrotype, and thermotype), were constructed for northern California coastal ranges based on the Rivas-Martinez worldwide bioclimatic classification system for the end of the 20th century climatology (1971–2000) and end of the 21st century climatology (2070–2099) using two models, Geophysical Fluid Dynamics Laboratory (GFDL) model and the Parallel Climate Model (PCM), under the medium-high A2 emission scenario. The digitally mapped results were used to 1) assess the relative redistribution of isobioclimates and their magnitude of change, 2) quantify the loss of isobioclimates into the future, 3) identify and locate novel isobioclimates projected to appear, and 4) explore compositional change in vegetation types among analog isobioclimate patches. This study used downscaled climate variables to map the isobioclimates at a fine spatial resolution −270 m grid cells. Common to both models of future climate was a large change in thermotype. Changes in ombrotype differed among the two models. The end of 20th century climatology has 83 isobioclimates covering the 63,000 km2 study area. In both future projections 51 of those isobioclimates disappear over 40,000 km2. The ordination of vegetation-bioclimate relationships shows very strong correlation of Rivas-Martinez indices with vegetation distribution and composition. Comparisons of vegetation composition among analog patches suggest that vegetation change will be a local rearrangement of species already in place rather than one requiring long distance dispersal. The digitally mapped results facilitate comparison with other Mediterranean regions. Major remaining challenges include predicting vegetation composition of novel isobioclimates and developing metrics to compare differences in climate space.

California↗
USGS2013

Fens as whole-ecosystem gauges of groundwater recharge under climate change

Currently, little is known about the impact of climate change on groundwater recharge in the Sierra Nevada and southern Cascade Range of California or other mountainous regions of the world. The purpose of this study was to determine whether small alpine peat lands called fens can be used as whole-ecosystem gauges of groundwater recharge through time. Fens are sustained by groundwater discharge and are highly sensitive to changes in groundwater flow due to hydrologic disturbance including climate change. Seven fens in the Sierra Nevada and southern Cascade Range were studied over a 50-80 year period using historic aerial photography. In each aerial photograph, fen areas were identified as open lawn and partially treed areas that exhibited (1) dark brownish-green coloring or various shades of gray and black in black and white imagery and (2) mottling of colors and clustering of vegetation, which signified a distinct moss canopy with overlying clumped sedge vegetation. In addition to the aerial photography study, a climate analysis for the study sites was carried out using both measured data (U.S. Department of Agriculture Natural Resources Conservation Service SNOwpack TELemetry system) and modeled data (a downscaled version of the Parameter-elevation Regressions on Independent Slopes Model) for the period from 1951 to 2010. Over the study period, the five fens in the Sierra Nevada were found to be decreasing between 10% and 16% in delineated area. The climate analysis revealed significant increases through time in annual mean minimum temperature (T min ) between 1951-1980 and 1981-2010. In addition, April 1 snow water equivalent and snowpack longevity also decreased between 1951-1980 and 1981-2010. For the fens in the Cascade Range, there were no discernible changes in delineated area. At these sites, increases in T min occurred only within the past 20-25 years and decreases in snowpack longevity were more subtle. A conceptual model is presented, which illustrates that basic differences in hydrogeology of the Sierra Nevada vs. the Cascade Range may control the threshold at which changes in delineated fen areas are discernible. Overall, the results from this study show that fens in the Sierra Nevada have strong potential as whole ecosystem gauges for determining long-term changes in groundwater recharge under climate change. Due to either more moderate climate change and/or hydrogeological differences, fens in the southern Cascade Range currently do not appear to have the same utility. A greater sample size of fens in the Sierra Nevada is needed to confirm the general applicability of this method. In addition, future work needs to focus on integrating fen monitoring with geochemical and/or isotopic process-level studies in order to quantify changes in groundwater recharge identified using this new approach.

Journal of Hydrology↗
USGS2012

Uncertainty in assessing the impacts of global change with coupled dynamic species distribution and population models

Concern over rapid global changes and the potential for interactions among multiple threats are prompting scientists to combine multiple modelling approaches to understand impacts on biodiversity. A relatively recent development is the combination of species distribution models, land‐use change predictions, and dynamic population models to predict the relative and combined impacts of climate change, land‐use change, and altered disturbance regimes on species' extinction risk. Each modelling component introduces its own source of uncertainty through different parameters and assumptions, which, when combined, can result in compounded uncertainty that can have major implications for management. Although some uncertainty analyses have been conducted separately on various model components – such as climate predictions, species distribution models, land‐use change predictions, and population models – a unified sensitivity analysis comparing various sources of uncertainty in combined modelling approaches is needed to identify the most influential and problematic assumptions. We estimated the sensitivities of long‐run population predictions to different ecological assumptions and parameter settings for a rare and endangered annual plant species ( Acanthomintha ilicifolia , or San Diego thornmint). Uncertainty about habitat suitability predictions, due to the choice of species distribution model, contributed most to variation in predictions about long‐run populations.

California↗
USGS2012

Modeling a thick unsaturated zone at San Gorgonio Pass, California: lessons learned after five years of artificial recharge

The information flow among the tasks of framework assessment, numerical modeling, model forecasting and hind casting, and system-performance monitoring is illustrated. Results provide an understanding of artificial recharge in high-altitude desert settings where large vertical distances may separate application ponds from their target aquifers. Approximately 3.8 million cubic meters of surface water was applied to spreading ponds from 2003–2007 to artificially recharge the underlying aquifer through a 200-meter thick unsaturated zone in the San Gorgonio Pass area in southern California. A study was conducted between 1997 and 2003, and a numerical model was developed to help determine the suitability of the site for artificial recharge. Ongoing monitoring results indicated that the existing model needed to be modified and recalibrated to more accurately predict artificial recharge at the site. The objective of this work was to recalibrate the model by using observation of the application rates, the rise and fall of the water level above a perching layer, and the approximate arrival time to the water table during the 5-yr monitoring period following initiation of long-term artificial recharge. Continuous monitoring of soil-matric potential, temperature, and water levels beneath the site indicated that artificial recharge reached the underlying water table between 3.75 and 4.5 yr after the initial application of the recharge water. The model was modified to allow the simulation to more adequately match the perching layer dynamics and the time of arrival at the water table. The instrumentation also showed that the lag time between changes in application of water at the surface and the response at the perching layer decreased from about 4 mo to less than 1 mo due to the wet-up of the unsaturated zone and the increase in relative permeability. The results of this study demonstrate the importance of iteratively monitoring and modeling the unsaturated zone in layered alluvial systems in the context of artificial recharge. They show that adequate geologic and hydraulic-property data on perching layers are critical to success. Continuous monitoring in the unsaturated and saturated zones beneath a site provides data to develop and constrain numerical models, better understand local unsaturated zone process, manage artificial recharge operations, and to determine the timing and volume of recoverable water for consumptive use.

California↗
USGS2012

Modeling plant species distributions under future climates: how fine scale do climate projections need to be?

Recent studies suggest that species distribution models (SDMs) based on fine‐scale climate data may provide markedly different estimates of climate‐change impacts than coarse‐scale models. However, these studies disagree in their conclusions of how scale influences projected species distributions. In rugged terrain, coarse‐scale climate grids may not capture topographically controlled climate variation at the scale that constitutes microhabitat or refugia for some species. Although finer scale data are therefore considered to better reflect climatic conditions experienced by species, there have been few formal analyses of how modeled distributions differ with scale. We modeled distributions for 52 plant species endemic to the California Floristic Province of different life forms and range sizes under recent and future climate across a 2000‐fold range of spatial scales (0.008–16 km 2 ). We produced unique current and future climate datasets by separately downscaling 4 km climate models to three finer resolutions based on 800, 270, and 90 m digital elevation models and deriving bioclimatic predictors from them. As climate‐data resolution became coarser, SDMs predicted larger habitat area with diminishing spatial congruence between fine‐ and coarse‐scale predictions. These trends were most pronounced at the coarsest resolutions and depended on climate scenario and species' range size. On average, SDMs projected onto 4 km climate data predicted 42% more stable habitat (the amount of spatial overlap between predicted current and future climatically suitable habitat) compared with 800 m data. We found only modest agreement between areas predicted to be stable by 90 m models generalized to 4 km grids compared with areas classified as stable based on 4 km models, suggesting that some climate refugia captured at finer scales may be missed using coarser scale data. These differences in projected locations of habitat change may have more serious implications than net habitat area when predictive maps form the basis of conservation decision making.

California↗
USGS2012

Downscaling future climate scenarios to fine scales for hydrologic and ecological modeling and analysis

Introduction Evaluating the environmental impacts of climate change on water resources and biological components of the landscape is an integral part of hydrologic and ecological investigations, and the resultant land and resource management in the twenty-first century. Impacts of both climate and simulated hydrologic parameters on ecological processes are relevant at scales that reflect the heterogeneity and complexity of landscapes. At present, simulations of climate change available from global climate models [GCMs] require downscaling for hydrologic or ecological applications. Methods Using statistically downscaled future climate projections developed using constructed analogues, a methodology was developed to further downscale the projections spatially using a gradient-inverse-distance-squared approach for application to hydrologic modeling at 270-m spatial resolution. Results This paper illustrates a methodology to downscale and bias-correct national GCMs to subkilometer scales that are applicable to fine-scale environmental processes. Four scenarios were chosen to bracket the range of future emissions put forth by the Intergovernmental Panel on Climate Change. Fine-scale applications of downscaled datasets of ecological and hydrologic correlations to variation in climate are illustrated. Conclusions The methodology, which includes a sequence of rigorous analyses and calculations, is intended to reduce the addition of uncertainty to the climate data as a result of the downscaling while providing the fine-scale climate information necessary for ecological analyses. It results in new but consistent data sets for the US at 4 km, the southwest US at 270 m, and California at 90 m and illustrates the utility of fine-scale downscaling to analyses of ecological processes influenced by topographic complexity.

Ecological Processes↗
USGS2012

Estimation of stream temperature in support of fish production modeling under future climates in the Klamath River Basin

Stream temperature estimates under future climatic conditions were needed in support of fish production modeling for evaluation of effects of dam removal in the Klamath River Basin. To allow for the persistence of the Klamath River salmon fishery, an upcoming Secretarial Determination in 2012 will review potential changes in water quality and stream temperature to assess alternative scenarios, including dam removal. Daily stream temperature models were developed by using a regression model approach with simulated net solar radiation, vapor density deficit calculated on the basis of air temperature, and mean daily air temperature. Models were calibrated for 6 streams in the Lower, and 18 streams in the Upper, Klamath Basin by using measured stream temperatures for 1999-2008. The standard error of the y-estimate for the estimation of stream temperature for the 24 streams ranged from 0.36 to 1.64°C, with an average error of 1.12°C for all streams. The regression models were then used with projected air temperatures to estimate future stream temperatures for 2010-99. Although the mean change from the baseline historical period of 1950-99 to the projected future period of 2070-99 is only 1.2°C, it ranges from 3.4°C for the Shasta River to no change for Fall Creek and Trout Creek. Variability is also evident in the future with a mean change in temperature for all streams from the baseline period to the projected period of 2070-99 of only 1°C, while the range in stream temperature change is from 0 to 2.1°C. The baseline period, 1950-99, to which the air temperature projections were corrected, established the starting point for the projected changes in air temperature. The average measured daily air temperature for the calibration period 1999-2008, however, was found to be as much as 2.3°C higher than baseline for some rivers, indicating that warming conditions have already occurred in many areas of the Klamath River Basin, and that the stream temperature projections for the 21st century could be underestimating the actual change.

Oregon;California↗
USGS2012

Geohydrology of Big Bear Valley, California: phase 1--geologic framework, recharge, and preliminary assessment of the source and age of groundwater

The Big Bear Valley, located in the San Bernardino Mountains of southern California, has increased in population in recent years. Most of the water supply for the area is pumped from the alluvial deposits that form the Big Bear Valley groundwater basin. This study was conducted to better understand the thickness and structure of the groundwater basin in order to estimate the quantity and distribution of natural recharge to Big Bear Valley. A gravity survey was used to estimate the thickness of the alluvial deposits that form the Big Bear Valley groundwater basin. This determined that the alluvial deposits reach a maximum thickness of 1,500 to 2,000 feet beneath the center of Big Bear Lake and the area between Big Bear and Baldwin Lakes, and decrease to less than 500 feet thick beneath the eastern end of Big Bear Lake. Interferometric Synthetic Aperture Radar (InSAR) was used to measure pumping-induced land subsidence and to locate structures, such as faults, that could affect groundwater movement. The measurements indicated small amounts of land deformation (uplift and subsidence) in the area between Big Bear Lake and Baldwin Lake, the area near the city of Big Bear Lake, and the area near Sugarloaf, California. Both the gravity and InSAR measurements indicated the possible presence of subsurface faults in subbasins between Big Bear and Baldwin Lakes, but additional data are required for confirmation. The distribution and quantity of groundwater recharge in the area were evaluated by using a regional water-balance model (Basin Characterization Model, or BCM) and a daily rainfall-runoff model (INFILv3). The BCM calculated spatially distributed potential recharge in the study area of approximately 12,700 acre-feet per year (acre-ft/yr) of potential in-place recharge and 30,800 acre-ft/yr of potential runoff. Using the assumption that only 10 percent of the runoff becomes recharge, this approach indicated there is approximately 15,800 acre-ft/yr of total recharge in Big Bear Valley. The INFILv3 model was modified for this study to include a perched zone beneath the root zone to better simulate lateral seepage and recharge in the shallow subsurface in mountainous terrain. The climate input used in the INFILv3 model was developed by using daily climate data from 84 National Climatic Data Center stations and published Parameter Regression on Independent Slopes Model (PRISM) average monthly precipitation maps to match the drier average monthly precipitation measured in the Baldwin Lake drainage basin. This model resulted in a good representation of localized rain-shadow effects and calibrated well to measured lake volumes at Big Bear and Baldwin Lakes. The simulated average annual recharge was about 5,480 acre-ft/yr in the Big Bear study area, with about 2,800 acre-ft/yr in the Big Bear Lake surface-water drainage basin and about 2,680 acre-ft/yr in the Baldwin Lake surface-water drainage basin. One spring and eight wells were sampled and analyzed for chemical and isotopic data in 2005 and 2006 to determine if isotopic techniques could be used to assess the sources and ages of groundwater in the Big Bear Valley. This approach showed that the predominant source of recharge to the Big Bear Valley is winter precipitation falling on the surrounding mountains. The tritium and uncorrected carbon-14 ages of samples collected from wells for this study indicated that the groundwater basin contains water of different ages, ranging from modern to about 17,200-years old.The results of these investigations provide an understanding of the lateral and vertical extent of the groundwater basin, the spatial distribution of groundwater recharge, the processes responsible for the recharge, and the source and age of groundwater in the groundwater basin. Although the studies do not provide an understanding of the detailed water-bearing properties necessary to determine the groundwater availability of the basin, they do provide a framework for the future development of a groundwater model that would help to improve the understanding of the potential hydrologic effects of water-management alternatives in Big Bear Valley.

California↗
USGS2012

Simulation of climate change in San Francisco Bay Basins, California: Case studies in the Russian River Valley and Santa Cruz Mountains

As a result of ongoing changes in climate, hydrologic and ecologic effects are being seen across the western United States. A regional study of how climate change affects water resources and habitats in the San Francisco Bay area relied on historical climate data and future projections of climate, which were downscaled to fine spatial scales for application to a regional water-balance model. Changes in climate, potential evapotranspiration, recharge, runoff, and climatic water deficit were modeled for the Bay Area. In addition, detailed studies in the Russian River Valley and Santa Cruz Mountains, which are on the northern and southern extremes of the Bay Area, respectively, were carried out in collaboration with local water agencies. Resource managers depend on science-based projections to inform planning exercises that result in competent adaptation to ongoing and future changes in water supply and environmental conditions. Results indicated large spatial variability in climate change and the hydrologic response across the region; although there is warming under all projections, potential change in precipitation by the end of the 21st century differed according to model. Hydrologic models predicted reduced early and late wet season runoff for the end of the century for both wetter and drier future climate projections, which could result in an extended dry season. In fact, summers are projected to be longer and drier in the future than in the past regardless of precipitation trends. While water supply could be subject to increased variability (that is, reduced reliability) due to greater variability in precipitation, water demand is likely to steadily increase because of increased evapotranspiration rates and climatic water deficit during the extended summers. Extended dry season conditions and the potential for drought, combined with unprecedented increases in precipitation, could serve as additional stressors on water quality and habitat. By focusing on the relationship between soil moisture storage and evapotranspiration pressures, climatic water deficit integrates the effects of increasing temperature and varying precipitation on basin conditions. At the fine-scale used for these analyses, this variable is an effective indicator of the areas in the landscape that are the most resilient or vulnerable to projected changes. These analyses have shown that regardless of the direction of precipitation change, climatic water deficit is projected to increase, which implies greater water demand to maintain current agricultural resources or land cover. Fine-scale modeling provides a spatially distributed view of locations in the landscape that could prove to be resilient to climatic changes in contrast to locations where vegetation is currently living on the edge of its present-day bioclimatic distribution and, therefore, is more likely to perish or shift to other dominant species under future warming. This type of modeling and the associated analyses provide a useful means for greater understanding of water and land resources, which can lead to better resource management and planning.

California↗
USGS2011

The source, discharge, and chemical characteristics of water from Agua Caliente Spring, Palm Springs, California

Agua Caliente Spring, in downtown Palm Springs, California, has been used for recreation and medicinal therapy for hundreds of years and currently (2008) is the source of hot water for the Spa Resort owned by the Agua Caliente Band of the Cahuilla Indians. The Agua Caliente Spring is located about 1,500 feet east of the eastern front of the San Jacinto Mountains on the southeast-sloping alluvial plain of the Coachella Valley. The objectives of this study were to (1) define the geologic structure associated with the Agua Caliente Spring; (2) define the source(s), and possibly the age(s), of water discharged by the spring; (3) ascertain the seasonal and longer-term variability of the natural discharge, water temperature, and chemical characteristics of the spring water; (4) evaluate whether water-level declines in the regional aquifer will influence the temperature of the spring discharge; and, (5) estimate the quantity of spring water that leaks out of the water-collector tank at the spring orifice.

California↗
USGS2010

Great Basin Integrated Landscape Monitoring Pilot Summary Report

The Great Basin Integrated Landscape Monitoring Pilot project (GBILM) was one of four regional pilots to implement the U.S. Geological Survey (USGS) Science Thrust on Integrated Landscape Monitoring (ILM) whose goal was to observe, understand, and predict landscape change and its implications on natural resources at multiple spatial and temporal scales and address priority natural resource management and policy issues. The Great Basin is undergoing rapid environmental change stemming from interactions among global climate trends, increasing human populations, expanding and accelerating land and water uses, invasive species, and altered fire regimes. GBLIM tested concepts and developed tools to store and analyze monitoring data, understand change at multiple scales, and forecast landscape change. The GBILM endeavored to develop and test a landscape-level monitoring approach in the Great Basin that integrates USGS disciplines, addresses priority management questions, catalogs and uses existing monitoring data, evaluates change at multiple scales, and contributes to development of regional monitoring strategies. GBILM functioned as an integrative team from 2005 to 2010, producing more than 35 science and data management products that addressed pressing ecosystem drivers and resource management agency needs in the region. This report summarizes the approaches and methods of this interdisciplinary effort, identifies and describes the products generated, and provides lessons learned during the project.

Open-File Report↗
USGS2010

Integrated simulation of consumptive use and land subsidence in the Central Valley, California, for the past and for a future subject to urbanization and climate change

Competition for water resources is growing throughout California, particularly in the Central Valley where about 20% of all groundwater used in the United States is consumed for agriculture and urban water supply. Continued agricultural use coupled with urban growth and potential climate change would result in continued depletion of groundwater storage and associated land subsidence throughout the Central Valley. For 1962-2003, an estimated 1,230 hectare meters (hm3) of water was withdrawn from fine-grained beds, resulting in more than three meters (m) of additional land subsidence locally. Linked physically-based, supply-constrained and emanddriven hydrologic models were used to simulate future hydrologic conditions under the A2 climate projection scenario that assumes continued "business as usual" greenhouse gas emissions. Results indicate an increased subsidence in the second half of the twenty-first century. Potential simulated land subsidence extends into urban areas and the eastern side of the valley where future surface-water deliveries may be depleted.

California↗
USGS2008

Artificial recharge through a thick, heterogeneous unsaturated zone

Thick, heterogeneous unsaturated zones away from large streams in desert areas have not previously been considered suitable for artificial recharge from ponds. To test the potential for recharge in these settings, 1.3 x 10 6 m 3 of water was infiltrated through a 0.36-ha pond along Oro Grande Wash near Victorville, California, between October 2002 and January 2006. The pond overlies a regional pumping depression 117 m below land surface and is located where thickness and permeability of unsaturated deposits allowed infiltration and saturated alluvial deposits were sufficiently permeable to allow recovery of water. Because large changes in water levels caused by nearby pumping would obscure arrival of water at the water table, downward movement of water was measured using sensors in the unsaturated zone. The downward rate of water movement was initially as high as 6 m/d and decreased with depth to 0.07 m/d; the initial time to reach the water table was 3 years. After the unsaturated zone was wetted, water reached the water table in 1 year. Soluble salts and nitrate moved readily with the infiltrated water, whereas arsenic and chromium were less mobile. Numerical simulations done using the computer program TOUGH2 duplicated the downward rate of water movement, accumulation of water on perched zones, and its arrival at the water table. Assuming 10 3 106 m3 of recharge annually for 20 years, a regional ground water flow model predicted water level rises of 30 m beneath the ponds, and rises exceeding 3m in most wells serving the nearby urban area.

California↗
USGS2007

Geophysical Methods for Investigating Ground-Water Recharge

While numerical modeling has revolutionized our understanding of basin-scale hydrologic processes, such models rely almost exclusively on traditional measurements?rainfall, streamflow, and water-table elevations?for calibration and testing. Model calibration provides initial estimates of ground-water recharge. Calibrated models are important yet crude tools for addressing questions about the spatial and temporal distribution of recharge. An inverse approach to recharge estimation is taken of necessity, due to inherent difficulties in making direct measurements of flow across the water table. Difficulties arise because recharging fluxes are typically small, even in humid regions, and because the location of the water table changes with time. Deep water tables in arid and semiarid regions make recharge monitoring especially difficult. Nevertheless, recharge monitoring must advance in order to improve assessments of ground-water recharge. Improved characterization of basin-scale recharge is critical for informed water-resources management. Difficulties in directly measuring recharge have prompted many efforts to develop indirect methods. The mass-balance approach of estimating recharge as the residual of generally much larger terms has persisted despite the use of increasing complex and finely gridded large-scale hydrologic models. Geophysical data pertaining to recharge rates, timing, and patterns have the potential to substantially improve modeling efforts by providing information on boundary conditions, by constraining model inputs, by testing simplifying assumptions, and by identifying the spatial and temporal resolutions needed to predict recharge to a specified tolerance in space and in time. Moreover, under certain conditions, geophysical measurements can yield direct estimates of recharge rates or changes in water storage, largely eliminating the need for indirect measures of recharge. This appendix presents an overview of physically based, geophysical methods that are currently available or under development for recharge monitoring. The material is written primarily for hydrogeologists. Uses of geophysical methods for improving recharge monitoring are explored through brief discussions and case studies. The intent is to indicate how geophysical methods can be used effectively in studying recharge processes and quantifying recharge. As such, the material constructs a framework for matching the strengths of individual geophysical methods with the manners in which they can be applied for hydrologic analyses. The appendix is organized in three sections. First, the key hydrologic parameters necessary to determine the rate, timing, and patterns of recharge are identified. Second, the basic operating principals of the relevant geophysical methods are discussed. Methods are grouped by the physical property that they measure directly. Each measured property is related to one or more of the key hydrologic properties for recharge monitoring. Third, the emerging conceptual framework for applying geophysics to recharge monitoring is presented. Examples of the application of selected geophysical methods to recharge monitoring are presented in nine case studies. These studies illustrate hydrogeophysical applications under a wide range of conditions and measurement scales, which vary from tenths of a meter to hundreds of meters. The case studies include practice-proven as well as emerging applications of geophysical methods to recharge monitoring.

Professional Paper↗