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Results for “Journal of Water and Climate Change”

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At least 127 records · Page 7Linked to original sources
USGS2020

Evaluating the effects of downscaled climate projections on groundwater storage and simulated base-flow contribution to the North Fork Red River and Lake Altus, southwest Oklahoma (USA)

Potential effects of projected climate variability on base flow and groundwater storage in the North Fork Red River aquifer, Oklahoma (USA), were estimated using downscaled climate model data coupled with a numerical groundwater-flow model. The North Fork Red River aquifer discharges groundwater to the North Fork Red River, which provides inflow to Lake Altus. To approximate future conditions, Coupled Model Intercomparison Project Phase 5 climate data were downscaled to the watershed and a time-series of scaling factors were developed and interpolated for three climate scenarios (central tendency, warmer and drier, and less warm and wetter) representing future climate conditions for the period 2045–2074. These scaling factors were then applied to a soil-water-balance model to produce groundwater recharge and evapotranspiration estimates. A MODFLOW groundwater-flow model of the North Fork Red River aquifer used the scaled recharge and evapotranspiration data to estimate changes in base flow and water-surface elevation of Lake Altus. Compared to a baseline scenario, the mean percent change in annual base flow during 2045–2074 was −10.8 and −15.9% for the central tendency and warmer/drier scenarios, respectively; the mean percent change in annual base flow for the less-warm/wetter scenario was +15.7%. The mean annual percent change in groundwater storage for the central tendency, warmer/drier, and less-warm/wetter climate scenarios and the baseline are −2.7, −3.2, and +3.0%, respectively. The range of outcomes from the climate scenarios may be influenced by variability in the downscaled climate data for precipitation more than for temperature.

Oklahoma↗
USGS2020

Utilization of multiple microbial tools to evaluate efficacy of restoration strategies to improve recreational water quality at a Lake Michigan Beach (Racine, WI)

Hydro-meteorological conditions facilitate transport of fecal indicator bacteria (FIB) to the nearshore environment, affecting recreational water quality. North Beach (Racine, Wisconsin, United States), is an exemplar public beach site along Lake Michigan, where precipitation-mediated surface runoff, wave encroachment, stormwater and tributary outflow were demonstrated to contribute to beach advisories. Multiple restoration actions, including installation of a stormwater retention wetland, were successfully deployed to improve recreational water quality. Implementation of molecular methods (e.g. human microbial source tracking markers and Escherichia coli ( E. coli ) qPCR) assisted in identifying potential pollution sources and improving public health response time. However, periodic water quality failures still occur. As local beach managers reassess restoration measures in response to climatic changes, use of expanded microbial methods (including bacterial community profiling) may contribute to a better understanding of these dynamic environments. In this 2-year study (2015 and 2019), nearshore/offshore Lake Michigan, stormwater, and tributary samples were collected to determine if, 1) the constructed wetland (~50 m from the shoreline) continued to provide stormwater separation/retention and 2) mixing between onshore sources, Root River and Lake Michigan, was increasing due to rising precipitation/lake levels. Monthly rainfall totals were 1.5× higher in 2019 than 2015, coinciding with a 0.63 m lake-level rise. The prevalence of more intense, onshore winds also increased, facilitating interaction between potential reservoirs of FIB with nearshore water through wind driven waves and lake intrusion, e.g. beach sands and the adjacent Root River. While a strong relationship existed between wet weather wetland and North Beach nearshore E. coli concentrations (all sites), bacterial communities were strikingly different. Conversely, bacterial community overlap existed between the Root River mouth and nearshore/offshore sites. These results suggest the constructed wetland can accommodate the climate-related changes observed in this study. Future restoration activities could be directed towards upstream tributary sources in order to minimize microbial contaminants entering Lake Michigan.

Wisconsin↗
USGS2026

Patterns of recent brook trout invasion in bull trout streams in relation to habitat, source connectivity, biotic resistance, and disturbance

Knowledge of which habitats are at risk of invasion by nonnative species is essential to conservation, but a changing climate often complicates assessments of where future invasions may occur. Nonnative brook trout Salvelinus fontinalis threaten cold-adapted native salmonids throughout western North America, and the extent of future invasions in coldwater streams is recognized as an area of uncertainty with important consequences. We addressed this uncertainty using spatial-stream-network (SSN) modeling to develop a species distribution model (SDM) for brook trout in Idaho, creating high-resolution prediction maps of suitable (i.e., invadable) habitat under baseline (1990–2015) and future (2080s) climate scenarios, and querying predictions within natal bull trout S. confluentus habitat patches (stream–subwatershed scale) for each scenario. Results indicated that brook trout will experience a net loss of suitable habitat in Idaho, but a large increase of suitable habitat in cold streams. The total proportion of bull trout habitat invadable by brook trout increased from 0.33 during the baseline scenario to 0.44 during the future scenario—a result of upstream expansions of brook trout habitat that were partially offset by contractions in bull trout habitat. Changes in the proportion of invadable habitat varied widely among bull trout patches. Between scenarios, the largest increases in suitable habitat occurred in small, low-gradient, unconfined streams with mean August water temperatures of 7–9 °C during the baseline period. A relatively small proportion of patches contained the majority of invadable habitat in both scenarios, particularly patches in “U-shaped” glacial valleys. A changing climate will broadly increase the threat that brook trout pose to bull trout, but the degree of change experienced by individual populations will vary with local context. The high-resolution prediction maps created by our SSN model will help conservation planners identify and prioritize control efforts on the small proportion of brook trout populations that most threaten bull trout.

Idaho↗
USGS2017

Daily reservoir sedimentation model: Case study from the Fena Valley Reservoir, Guam

A model to compute reservoir sedimentation rates at daily timescales is presented. The model uses streamflow and sediment load data from nearby stream gauges to obtain an initial estimate of sediment yield for the reservoir’s watershed; it is then calibrated to the total deposition calculated from repeat bathymetric surveys. Long-term changes to reservoir trapping efficiency are also taken into account. The model was applied to the Fena Valley Reservoir, a water supply reservoir on the island of Guam. This reservoir became operational in 1951 and was recently surveyed in 2014. The model results show that the highest rate of deposition occurred during two typhoons (Typhoon Alice in 1953 and Typhoon Tingting in 2004); each storm decreased reservoir capacity by approximately 2–3% in only a few days. The presented model can be used to evaluate the impact of an extreme event, or it can be coupled with a watershed runoff model to evaluate potential impacts to storage capacity as a result of climate change or other hydrologic modifications.

Journal of Hydraulic Engineering↗
USGS2023

Adjusting design floods for urbanization across groundwater-dominated watersheds of Long Island, NY

The magnitude and variability of floods have increased for many nontidal streams on Long Island (LI), NY since the mid-20th century. One of the most densely populated regions of the United States, LI has experienced amplified floods in step with increases in impervious land cover, storm, and sanitary sewers that have accompanied urban development. To better understand the drivers of observed flood trends and effects of urbanization, a nonstationary flood frequency analysis is conducted, using historical annual peak flow records from 17 gaged watersheds on LI using conditional moments based on physical covariates from a two-stage sequential robust linear regression procedure. Regression results indicate that urban development and precipitation are significant co-predictors of peak flows for LI watersheds that have undergone rapid development during the available peak flow record. In watersheds with less intense urbanization or that were fully developed before the peak flow record began, precipitation alone was a significant explanatory variable. Long-term baseflow patterns identified using a nonparametric smoother explained some patterns of decreasing peak flows and heteroskedasticity in the peak flow records. Fitting a log-Pearson III distribution with these conditional moments, floods corresponding to a 20% annual exceedance probability (AEP) are up to 80% higher under a nonstationary framework compared with stationary under current watershed conditions, and differ significantly (95% confidence) from stationary estimates for 6 out of 17 watersheds. Larger floods corresponding to 1% AEPs do not differ significantly between nonstationary and stationary estimates at a 95% confidence level. Nonmonotonic trends observed in two watersheds indicate that recent stormwater management practices, such as rerouting stormwater outfalls away from the channel, substantially reduce flood frequency. Reduced nonstationary flood quantile estimates at these two watersheds are 20 to 40% lower than stationary estimates when accounting for changing watershed conditions over time. Across LI, stormwater management and water-table fluctuations have increased peak flow variability, characteristic of a late phase urban adjustment period on LI. Results of this study demonstrate that a nonstationary framework is a necessary step forward toward a regional flood-frequency analysis for LI. This nonstationary framework will allow flood managers to update flood discharge estimates to current conditions that reflect altered relationships between urban cover and climate for more targeted planning of flood control, transportation infrastructure, and management of floodplain ecosystems.

New York↗
USGS2016

Understanding the past to interpret the future: Comparison of simulated groundwater recharge in the upper Colorado River basin (USA) using observed and general-circulation-model historical climate data

In evaluating potential impacts of climate change on water resources, water managers seek to understand how future conditions may differ from the recent past. Studies of climate impacts on groundwater recharge often compare simulated recharge from future and historical time periods on an average monthly or overall average annual basis, or compare average recharge from future decades to that from a single recent decade. Baseline historical recharge estimates, which are compared with future conditions, are often from simulations using observed historical climate data. Comparison of average monthly results, average annual results, or even averaging over selected historical decades, may mask the true variability in historical results and lead to misinterpretation of future conditions. Comparison of future recharge results simulated using general circulation model (GCM) climate data to recharge results simulated using actual historical climate data may also result in an incomplete understanding of the likelihood of future changes. In this study, groundwater recharge is estimated in the upper Colorado River basin, USA, using a distributed-parameter soil-water balance groundwater recharge model for the period 1951–2010. Recharge simulations are performed using precipitation, maximum temperature, and minimum temperature data from observed climate data and from 97 CMIP5 (Coupled Model Intercomparison Project, phase 5) projections. Results indicate that average monthly and average annual simulated recharge are similar using observed and GCM climate data. However, 10-year moving-average recharge results show substantial differences between observed and simulated climate data, particularly during period 1970–2000, with much greater variability seen for results using observed climate data.

Upper Colorado River basin↗
USGS2017

Interactive effects of water temperature and salinity on growth and mortality of eastern oysters, Crassostrea virginica: A meta-analysis using 40 years of monitoring data

Despite nearly a century of exploitation and scientific study, predicting growth and mortality rates of the eastern oyster ( Crassostrea virginica ) as a means to inform local harvest and management activities remains difficult. Ensuring that models reflect local population responses to varying salinity and temperature combinations requires locally appropriate models. Using long-term (1988 to 2015) monitoring data from Louisiana's public oyster reefs, we develop regionally specific models of temperature- and salinity-driven mortality (sack oysters only) and growth for spat (<25 mm), seed (25–75 mm), and sack (>75 mm) oyster size classes. The results demonstrate that the optimal combination of temperature and salinity where Louisiana oysters experience reduced mortality and fast growth rates is skewed toward lower salinities and higher water temperatures than previous models have suggested. Outside of that optimal range, oysters are commonly exposed to combinations of temperature and salinity that are correlated with high mortality and reduced growth. How these combinations affect growth, and to a lesser degree mortality, appears to be size class dependent. Given current climate predictions for the region and ongoing large-scale restoration activities in coastal Louisiana, the growth and mortality models are a critical step toward ensuring sustainable oyster reefs for long-term harvest and continued delivery of the ecological services in a changing environment.

Louisiana↗
USGS2025

Simulation of the impacts of projected climate change on groundwater resources in the urban, semiarid Yucaipa Valley watershed, southern California using an integrated hydrologic model

Managing water resources in semiarid watersheds is challenging due to limited supply and uncertain future climate conditions. This paper examines the impact of future climate changes on an urban watershed in southern California using an integrated hydrologic model. GSFLOW modeling software is used to simulate the nonlinear relationships between climate trends and precipitation partitioning into ET, runoff, and subsurface storage. Four global circulation models (GCMs), each with two greenhouse-gas scenarios, RCP45 and RCP85 are used to project future climate conditions. GCMs include the CanESM2, CNRM-CM5, HadGEM2-ES, and MIROC5 models. The model's simulated hydrologic conditions are compared with historical data to assess changes in water budgets and groundwater supply. Results indicate decreased groundwater storage in most scenarios due to increased natural evapotranspiration, vegetation consumptive use, and streamflow out of the watershed. Only scenarios with substantially increased future precipitation show increased groundwater storage. The study also highlights increased future aridity despite the rise in precipitation and large precipitation events forecast by GCMs, which increase the risk of urban floods and decrease stream leakage and water available to vegetation.

California↗
USGS2013

Dissolved oxygen fluctuations in karst spring flow and implications for endemic species: Barton Springs, Edwards aquifer, Texas, USA

Karst aquifers and springs provide the dissolved oxygen critical for survival of endemic stygophiles worldwide, but little is known about fluctuations of dissolved oxygen concentrations (DO) and factors that control those concentrations. We investigated temporal variation in DO at Barton Springs, Austin, Texas, USA. During 2006–2012, DO fluctuated by as much as a factor of 2, and at some periods decreased to concentrations that adversely affect the Barton Springs salamander (Eurycea sorosum) (&le;4.4 mg/L), a federally listed endangered species endemic to Barton Springs. DO was lowest (&le;4.4 mg/L) when discharge was low (&le;1 m 3 /s) and spring water temperature was >21 °C, although not at a maximum; the minimum DO recorded was 4.0 mg/L. Relatively low DO (<6 mg/L) also was measured at relatively high discharge (3.2 m 3 /s) and maximum T (22.2 °C). A four-segment linear regression model with daily data for discharge and spring water temperature as explanatory variables provided an excellent fit for mean daily DO (Nash–Sutcliffe coefficient for the validation period of 0.90). DO also fluctuated at short-term timescales in response to storms, and DO measured at 15-min intervals could be simulated with a combination of discharge, spring temperature, and specific conductance as explanatory variables. On the basis of the daily-data regression model, we hypothesize that more frequent low DO corresponding to salamander mortality could result from (i) lower discharge from Barton Springs resulting from increased groundwater withdrawals or decreased recharge as a result of climate change, and (or) (ii) higher groundwater temperature as a result of climate change.

Texas↗
USGS2015

Decadal changes in phenology of peak abundance patterns of woodland pond salamanders in northern Wisconsin

Woodland ponds are important landscape features that help sustain populations of amphibians that require this aquatic habitat for successful reproduction. Species abundance patterns often reflect site-specific differences in hydrology, physical characteristics, and surrounding vegetation. Large-scale processes such as changing land cover and environmental conditions are other potential drivers influencing amphibian populations in the Upper Midwest, but little information exists on the combined effects of these factors. We used Blue-spotted (Ambystoma laterale Hallowell) and Spotted Salamander (A. maculatum Shaw) monitoring data collected at the same woodland ponds thirteen years apart to determine if changing environmental conditions and vegetation cover in surrounding landscapes influenced salamander movement phenology and abundance. Four woodland ponds in northern Wisconsin were sampled for salamanders in April 1992-1994 and 2005-2007. While Blue-spotted Salamanders were more abundant than Spotted Salamanders in all ponds, there was no change in the numbers of either species over the years. However, peak numbers of Blue-spotted Salamanders occurred 11.7 days earlier (range: 9-14 days) in the 2000s compared to the 1990s; Spotted Salamanders occurred 9.5 days earlier (range: 3 - 13 days). Air and water temperatures (April 13- 24) increased, on average, 4.8°C and 3.7°C, respectively, between the decades regardless of pond. There were no discernible changes in canopy openness in surrounding forests between decades that would have warmed the water sooner (i.e., more light penetration). Our finding that salamander breeding phenology can vary by roughly 10 days in Wisconsin contributes to growing evidence that amphibian populations have responded to changing climate conditions by shifting life-cycle events. Managers can use this information to adjust monitoring programs and forest management activities in the surrounding landscape to avoid vulnerable amphibian movement periods. Considering direct and indirect stressors such as changing habitat and environmental conditions simultaneously to better understand trends in space and time can help improve monitoring programs for this taxa, which is at major risk of continued declines.

Wisconsin↗
USGS2013

Potential climate change impacts on temperate forest ecosystem processes

Large changes in atmospheric CO2, temperature and precipitation are predicted by 2100, yet the long-term consequences for carbon, water, and nitrogen cycling in forests are poorly understood. We applied the PnET-CN ecosystem model to compare the long-term effects of changing climate and atmospheric CO2 on productivity, evapotranspiration, runoff, and net nitrogen mineralization in current Great Lakes forest types. We used two statistically downscaled climate projections, PCM B1 (warmer and wetter) and GFDL A1FI (hotter and drier), to represent two potential future climate and atmospheric CO2 scenarios. To separate the effects of climate and CO2, we ran PnET-CN including and excluding the CO2 routine. Our results suggest that, with rising CO2 and without changes in forest type, average regional productivity could increase from 67% to 142%, changes in evapotranspiration could range from –3% to +6%, runoff could increase from 2% to 22%, and net N mineralization could increase 10% to 12%. Ecosystem responses varied geographically and by forest type. Increased productivity was almost entirely driven by CO2 fertilization effects, rather than by temperature or precipitation (model runs holding CO2 constant showed stable or declining productivity). The relative importance of edaphic and climatic spatial drivers of productivity varied over time, suggesting that productivity in Great Lakes forests may switch from being temperature to water limited by the end of the century.

Michigan;Minnesota;Wisconsin↗
USGS2018

100-year lower Mississippi floods in a global climate model: Characteristics and future changes

Floods in the Mississippi basin can have large negative societal, natural, and economic impacts. Understanding the drivers of floods, now and in the future, is relevant for risk management and infrastructure-planning purposes. We investigate the drivers of 100-yr-return lower Mississippi River floods using a global coupled climate model with an integrated surface water module. The model provides 3400 years of physically consistent data from a static climate, in contrast to available observational data (relatively short records, incomplete land surface data, transient climate). In the months preceding the model’s 100-yr floods, as indicated by extreme monthly discharge, above-average rain and snowfall lead to moist subsurface conditions and the buildup of snowpack, making the river system prone to these major flooding events. The meltwater from snowpack in the northern Missouri and upper Mississippi catchments primes the river system, sensitizing it to subsequent above-average precipitation in the Ohio and Tennessee catchments. An ensemble of transient forcing experiments is used to investigate the impacts of past and projected anthropogenic climate change on extreme floods. There is no statistically significant projected trend in the occurrence of 100-yr floods in the model ensemble, despite significant increases in extreme precipitation, significant decreases in extreme snowmelt, and significant decreases in less extreme floods. The results emphasize the importance of considering the fully coupled land–atmosphere system for extreme floods. This initial analysis provides avenues for further investigation, including comparison to characteristics of less extreme floods, the sensitivity to model configuration, the role of human water management, and implications for future flood-risk management.

Journal of Hydrometeorology↗
USGS2024

Will there be water? Climate change, housing needs, and future water demand in California

Climate change in California is expected to alter future water availability, impacting water supplies needed to support future housing growth and agriculture demand. In groundwater-dependent regions like California's Central Coast, new land-use related water demand and decreasing recharge is already stressing depleted groundwater basins. We developed a spatially explicit state-and-transition simulation model that integrates climate, land-use change, water demand, and groundwater gain-loss to examine the impact of future climate and land use change on groundwater balance and water demand in five counties along the Central Coast from 2010 to 2060. The model incorporated downscaled groundwater recharge projections based on a Warm/Wet and a Hot/Dry climate future from a spatially explicit hydrological process-based model. Two urbanization projections from a parcel-based, regional urban growth model representing 1) recent historical and 2) state-mandated housing growth projections were used as alternative spatial targets for future urban growth. Agricultural projections were based on recent historical trends from remote sensing data. Annual projected changes in groundwater balance were calculated as the difference between land-use related water demand, based on historical estimates, and climate-driven recharge plus agriculture return flows. Results indicate that future changes in climate-driven groundwater recharge, coupled with cumulative increases in agricultural water demand, result in overall declines in future groundwater balance, with a Hot/Dry future resulting in cumulative groundwater decline in all but Santa Cruz County. Cumulative declines by 2060 are especially prominent in San Luis Obispo (−2.9 to −5.1 Bm 3 ) and Monterey counties (−6.5 to −8.7 Bm 3 ), despite limited changes in agricultural water demand over the model period. These two counties show declining groundwater reserves in a Warm/Wet future as well, while San Benito and Santa Barbara County barely reach equilibrium. These results suggest future groundwater supplies may not be able to keep pace with regional demand and declining climate-driven recharge, resulting in a potential reduction in water security in the region. However, our county-scale projections showed new housing and associated water demand does not conflict with California's groundwater sustainability goals. Rather, future climate coupled with increasing agricultural groundwater demand may reduce water security in some counties, potentially limiting available groundwater supplies for new housing.

California↗
USGS2019

Influences of spawning timing, water temperature, and climatic warming on early life history phenology in western Alaska sockeye salmon

We applied an empirical model to predict hatching and emergence timing for 25 western Alaska sockeye salmon (Oncorhynchus nerka) populations in four lake-nursery systems to explore current patterns and potential responses of early life history phenology to warming water temperatures. Given experienced temperature regimes during development, we predicted hatching to occur in as few as 58 d to as many as 260 d depending on spawning timing and temperature. For a focal lake spawning population, our climate-lake temperature model predicted a water temperature increase of 0.7 to 1.4 °C from 2015 to 2099 during the incubation period, which translated to a 16 d to 30 d earlier hatching timing. The most extreme scenarios of warming advanced development by approximately a week earlier than historical minima and thus climatic warming may lead to only modest shifts in phenology during the early life history stage of this population. The marked variation in the predicted timing of hatching and emergence among populations in close proximity on the landscape may serve to buffer this metapopulation from climate change.

Canadian Journal of Fisheries and Aquatic Sciences↗
USGS2015

Optimal population prediction of sandhill crane recruitment based on climate-mediated habitat limitations

Prediction is fundamental to scientific enquiry and application; however, ecologists tend to favour explanatory modelling. We discuss a predictive modelling framework to evaluate ecological hypotheses and to explore novel/unobserved environmental scenarios to assist conservation and management decision-makers. We apply this framework to develop an optimal predictive model for juvenile (<1 year old) sandhill crane Grus canadensis recruitment of the Rocky Mountain Population (RMP). We consider spatial climate predictors motivated by hypotheses of how drought across multiple time-scales and spring/summer weather affects recruitment. Our predictive modelling framework focuses on developing a single model that includes all relevant predictor variables, regardless of collinearity. This model is then optimized for prediction by controlling model complexity using a data-driven approach that marginalizes or removes irrelevant predictors from the model. Specifically, we highlight two approaches of statistical regularization, Bayesian least absolute shrinkage and selection operator (LASSO) and ridge regression. Our optimal predictive Bayesian LASSO and ridge regression models were similar and on average 37% superior in predictive accuracy to an explanatory modelling approach. Our predictive models confirmed a priori hypotheses that drought and cold summers negatively affect juvenile recruitment in the RMP. The effects of long-term drought can be alleviated by short-term wet spring–summer months; however, the alleviation of long-term drought has a much greater positive effect on juvenile recruitment. The number of freezing days and snowpack during the summer months can also negatively affect recruitment, while spring snowpack has a positive effect. Breeding habitat, mediated through climate, is a limiting factor on population growth of sandhill cranes in the RMP, which could become more limiting with a changing climate (i.e. increased drought). These effects are likely not unique to cranes. The alteration of hydrological patterns and water levels by drought may impact many migratory, wetland nesting birds in the Rocky Mountains and beyond. Generalizable predictive models (trained by out-of-sample fit and based on ecological hypotheses) are needed by conservation and management decision-makers. Statistical regularization improves predictions and provides a general framework for fitting models with a large number of predictors, even those with collinearity, to simultaneously identify an optimal predictive model while conducting rigorous Bayesian model selection. Our framework is important for understanding population dynamics under a changing climate and has direct applications for making harvest and habitat management decisions.

Journal of Animal Ecology↗
USGS2015

Climate change and vulnerability of bull trout (Salvelinus confluentus) in a fire-prone landscape.

Linked atmospheric and wildfire changes will complicate future management of native coldwater fishes in fire-prone landscapes, and new approaches to management that incorporate uncertainty are needed to address this challenge. We used a Bayesian network (BN) approach to evaluate population vulnerability of bull trout ( Salvelinus confluentus ) in the Wenatchee River basin, Washington, USA, under current and future climate and fire scenarios. The BN was based on modeled estimates of wildfire, water temperature, and physical habitat prior to, and following, simulated fires throughout the basin. We found that bull trout population vulnerability depended on the extent to which climate effects can be at least partially offset by managing factors such as habitat connectivity and fire size. Moreover, our analysis showed that local management can significantly reduce the vulnerability of bull trout to climate change given appropriate management actions. Tools such as our BN that explicitly integrate the linked nature of climate and wildfire, and incorporate uncertainty in both input data and vulnerability estimates, will be vital in effective future management to conserve native coldwater fishes.

Canadian Journal of Fisheries and Aquatic Sciences↗
USGS2013

Recent land-use/land-cover change in the Central California Valley

Open access to Landsat satellite data has enabled annual analyses of modern land-use and land-cover change (LULCC) for the Central California Valley ecoregion between 2005 and 2010. Our annual LULCC estimates capture landscape-level responses to water policy changes, climate, and economic instability. From 2005 to 2010, agriculture in the region fluctuated along with regulatory-driven changes in water allocation as well as persistent drought conditions. Grasslands and shrublands declined, while developed lands increased in former agricultural and grassland/shrublands. Development rates stagnated in 2007, coinciding with the onset of the historic foreclosure crisis in California and the global economic downturn. We utilized annual LULCC estimates to generate interval-based LULCC estimates (2000–2005 and 2005–2010) and extend existing 27 year interval-based land change monitoring through 2010. Resulting change data provides insights into the drivers of landscape change in the Central California Valley ecoregion and represents the first, continuous, 37 year mapping effort of its kind.

California↗
USGS2012

Interactive coupling of a lake thermal model with a regional climate model

A one‐dimensional model of lake temperature, evaporation, and ice has been coupled in an interactive mode with the climate version of the National Center for Atmospheric Research/Pennsylvania State University regional (mesoscale) atmospheric model (MM4). The coupled MM4‐lake model makes possible high‐resolution simulations of climate in the proximity of large water bodies. Atmospheric variables required as input for the lake model are supplied by MM4 and simulated values of lake temperature, evaporation, and ice cover axe supplied to MM4 by the lake model. We have tested the coupled model system with a 60‐day, summertime simulation at Pyramid Lake, Nevada, and with a 10‐day, wintertime simulation of the North American Great Lakes and vicinity. Both simulations were conducted at a 60‐km resolution. Results from these tests indicate the coupled model system produces realistic simulations of lake temperature, evaporation, and ice cover and that the coupled system is applicable to simulations of regional climate change.

Journal of Geophysical Research-Atmospheres↗