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At least 793 records · Page 44Linked to original sources

USGS2009

Assessing the impact of land use change on hydrology by ensemble modelling (LUCHEM) II: Ensemble combinations and predictions

This paper reports on a project to compare predictions from a range of catchment models applied to a mesoscale river basin in central Germany and to assess various ensemble predictions of catchment streamflow. The models encompass a large range in inherent complexity and input requirements. In approximate order of decreasing complexity, they are DHSVM, MIKE-SHE, TOPLATS, WASIM-ETH, SWAT, PRMS, SLURP, HBV, LASCAM and IHACRES. The models are calibrated twice using different sets of input data. The two predictions from each model are then combined by simple averaging to produce a single-model ensemble. The 10 resulting single-model ensembles are combined in various ways to produce multi-model ensemble predictions. Both the single-model ensembles and the multi-model ensembles are shown to give predictions that are generally superior to those of their respective constituent models, both during a 7-year calibration period and a 9-year validation period. This occurs despite a considerable disparity in performance of the individual models. Even the weakest of models is shown to contribute useful information to the ensembles they are part of. The best model combination methods are a trimmed mean (constructed using the central four or six predictions each day) and a weighted mean ensemble (with weights calculated from calibration performance) that places relatively large weights on the better performing models. Conditional ensembles, in which separate model weights are used in different system states (e.g. summer and winter, high and low flows) generally yield little improvement over the weighted mean ensemble. However a conditional ensemble that discriminates between rising and receding flows shows moderate improvement. An analysis of ensemble predictions shows that the best ensembles are not necessarily those containing the best individual models. Conversely, it appears that some models that predict well individually do not necessarily combine well with other models in multi-model ensembles. The reasons behind these observations may relate to the effects of the weighting schemes, non-stationarity of the climate series and possible cross-correlations between models. Crown Copyright ?? 2008.

Advances in Water Resources↗

USGS2025

The acoustic-Doppler current profiler (ADCP): A comprehensive tool for river-reach hydromorphodynamics

This paper introduces the use of acoustic Doppler current profiler (ADCP) measurements as input for the Acoustic Mapping Velocimetry (AMV) method, a technique for characterizing the dynamics of riverine bedforms. The performance of this new approach, ADCP-AMV, is compared with input from a multibeam echosounder through a field study conducted on the Mississippi River (USA). A virtual ADCP tool has been created to support the ADCP-AMV measurements with optimal data density predictions. To the authors’ knowledge, this is the first time ADCP measurements have been used in conjunction with the AMV dune-tracking method. Subsequently, the paper discusses the coupling of ADCP-AMV measurements with ancillary data extracted from the ADCP. These ancillary data are processed using previously developed protocols to characterize hydrodynamics and the suspended sediment distribution in the water column. This paper emphasizes the capability of ADCPs to characterize open-channel river hydromorphodynamic parameters with high spatiotemporal resolution. Recommendations to accurately and efficiently acquire these multi-variable measurements and derived datasets are discussed.

Tennessee↗

USGS2009

Simulated dynamics of carbon stocks driven by changes in land use, management and climate in a tropical moist ecosystem of Ghana

Sub-Saharan Africa is large and diverse with regions of food insecurity and high vulnerability to climate change. This project quantifies carbon stocks and fluxes in the humid forest zone of Ghana, as a part of an assessment in West Africa. The General Ensemble biogeochemical Modeling System (GEMS) was used to simulate the responses of natural and managed systems to projected scenarios of changes in climate, land use and cover, and nitrogen fertilization in the Assin district of Ghana. Model inputs included historical land use and cover data, historical climate records and projected climate changes, and national management inventories. Our results show that deforestation for crop production led to a loss of soil organic carbon (SOC) by 33% from 1900 to 2000. The results also show that the trend of carbon emissions from cropland in the 20th century will continue through the 21st century and will be increased under the projected warming and drying scenarios. Nitrogen (N) fertilization in agricultural systems could offset SOC loss by 6% with 30 kg N ha −1 year −1 and by 11% with 60 kg N ha −1 year −1 . To increase N fertilizer input would be one of the vital adaptive measures to ensure food security and maintain agricultural sustainability through the 21st century.

Agriculture, Ecosystems and Environment↗

USGS2022

Connecting regional-scale tree distribution models with seed dispersal kernels

Regional scale forest distribution models are important tools for biogeography and understanding the structure of forest communities in space. These models take climate and geographic variables as input and are therefore helpful for long-term decision support and climate adaptation planning. Generally, local processes of tree germination and seedling survival are resolved probabilistically with explanatory variables such as elevation, latitude, exposure, soil type, moisture availability, climate and weather inputs and `trained’ using landscape and regional presence-absence data and machine learning techniques. How seeds are distributed in these models, that is, determining the dispersal kernel, is far more problematic. The challenge is that variables conditioning vertebrate seed dispersal (motility and probability of utilization or caching in response to cover type) are not represented in large scale distribution models, and in fact vary on scales (10-100 meters) that are much smaller than the smallest pixel size for the distribution model (1-10 kilometers). We present a homogenized seed digestion kernel (HSDK) which incorporates this scale separation. Homogenization naturally links highly variable small-scale processes (like seed foraging and caching by birds and rodents) with large scale effects (like dispersal of seeds over tens of kilometers). We develop a homogenization strategy to predict seed dispersal on landscape scales, analytically linking small-scale variables (landscape fraction cover by tree type, gut residence times and cover type utilization by frugivorous birds) with large scale behaviors. Closed form approximations are developed in two dimensions for two limiting cases of seed handling behavior, and the approach is illustrated using landscape data and piñon-pine dispersal in a 630,000 square kilometer region in the southwestern US.

Applied Mathematics and Computation↗

USGS2004

Composition of water and suspended sediment in streams of urbanized subtropical watersheds in Hawaii

Urbanization on the small subtropical island of Oahu, Hawaii provides an opportunity to examine how anthropogenic activity affects the composition of material transferred from land to ocean by streams. This paper investigates the variability in concentrations of trace elements (Pb, Zn, Cu, Ba, Co, As, Ni, V and Cr) in streams of watersheds on Oahu, Hawaii. The focus is on water and suspended particulate matter collected from the Ala Wai Canal watershed in Honolulu and also the Kaneohe Stream watershed. As predicted, suspended particulate matter controls most trace element transport. Elements such as Pb, Zn, Cu, Ba and Co exhibit increased concentrations within urbanized portions of the watersheds. Particulate concentrations of these elements vary temporally during storms owing to input of road runoff containing elevated concentrations of elements associated with vehicular traffic and other anthropogenic activities. Enrichments of As in samples from predominantly conservation areas are interpreted as reflecting agricultural use of fertilizers at the boundaries of urban and conservation lands. Particulate Ni, V and Cr exhibit distributions during storm events that suggest a mineralogical control. Principal component analysis of particulate trace element concentrations establishes eigenvalues that account for nearly 80% of the total variance and separates trace elements into 3 factors. Factor 1 includes Pb, Zn, Cu, Ba and Co, interpreted to represent metals with an urban anthropogenic enrichment. Factor 2 includes Ni, V and Cr, elements whose concentrations do not appear to derive from anthropogenic activity and is interpreted to reflect mineralogical control. Another, albeit less significant, anthropogenic factor includes As, Cd and U and is thought to represent agricultural inputs. Samples collected during a storm derived from an offshore low-pressure system suggest that downstream transport of upper watershed material during tradewind-derived rains results in a 2-3-fold dilution of the particulate concentrations of Pb, Zn and Cu in the Ala Wai canal watershed. ?? 2004 Elsevier Ltd. All rights reserved.

Conference Paper↗

USGS2005

Historical backcasting of metal concentrations in the Chattahoochee River, Georgia: Population growth and environmental policy

The impact of increasing urbanization on the quality of a river system has been investigated by examining the current concentration of trace metals in the Chattahoochee River south of Atlanta, GA, and comparing these to previously published historical sediment data from reservoirs along the river. The lack of historical data for dissolved metal concentrations prior to ???1980 requires an approach using these historic metal data from sediment cores. Core data are combined with current suspended load and dissolved metal data to "backcast" dissolved metal concentrations in the metro-Atlanta portion of the Chattahoochee River. The data suggest that the per capita input of dissolved trace metals have actually decreased since the 1920s, but anthropogenic inputs of metal are still a substantial water quality issue. ?? 2005 Elsevier Ltd. All rights reserved.

Applied Geochemistry↗

USGS2007

A simulation-based approach for estimating premining water quality: Red Mountain Creek, Colorado

Regulatory agencies are often charged with the task of setting site-specific numeric water quality standards for impaired streams. This task is particularly difficult for streams draining highly mineralized watersheds with past mining activity. Baseline water quality data obtained prior to mining are often non-existent and application of generic water quality standards developed for unmineralized watersheds is suspect given the geology of most watersheds affected by mining. Various approaches have been used to estimate premining conditions, but none of the existing approaches rigorously consider the physical and geochemical processes that ultimately determine instream water quality. An approach based on simulation modeling is therefore proposed herein. The approach utilizes synoptic data that provide spatially-detailed profiles of concentration, streamflow, and constituent load along the study reach. This field data set is used to calibrate a reactive stream transport model that considers the suite of physical and geochemical processes that affect constituent concentrations during instream transport. A key input to the model is the quality and quantity of waters entering the study reach. This input is based on chemical analyses available from synoptic sampling and observed increases in streamflow along the study reach. Given the calibrated model, additional simulations are conducted to estimate premining conditions. In these simulations, the chemistry of mining-affected sources is replaced with the chemistry of waters that are thought to be unaffected by mining (proximal, premining analogues). The resultant simulations provide estimates of premining water quality that reflect both the reduced loads that were present prior to mining and the processes that affect these loads as they are transported downstream. This simulation-based approach is demonstrated using data from Red Mountain Creek, Colorado, a small stream draining a heavily-mined watershed. Model application to the premining problem for Red Mountain Creek is based on limited field reconnaissance and chemical analyses; additional field work and analyses may be needed to develop definitive, quantitative estimates of premining water quality.

Colorado↗

USGS2007

Centimeter-scale characterization of biogeochemical gradients at a wetland-aquifer interface using capillary electrophoresis

Steep biogeochemical gradients were measured at mixing interfaces in a wetland-aquifer system impacted by landfill leachate in Norman, Oklahoma. The system lies within a reworked alluvial plain and is characterized by layered low hydraulic conductivity wetland sediments interbedded with sandy aquifer material. Using cm-scale passive diffusion samplers, "peepers", water samples were collected in a depth profile to span interfaces between surface water and a sequence of deeper sedimentary layers. Geochemical indicators including electron acceptors, low-molecular-weight organic acids, base cations, and NH4+ were analyzed by capillary electrophoresis (CE) and field techniques to maximize the small sample volumes available from the centimeter-scale peepers. Steep concentration gradients of biogeochemical indicators were observed at various interfaces including those created at sedimentary boundaries and boundaries created by heterogeneities in organic C and available electron acceptors. At the sediment-water interface, chemical profiles with depth suggest that SO42 - and Fe reduction dominate driven by inputs of organic C from the wetland and availability of electron acceptors. Deeper in the sediments (not associated with a lithologic boundary), a steep gradient of organic acids (acetate maximum 8.8 mM) and NH4+ (maximum 36 mM) is observed due to a localized source of organic matter coupled with the lack of electron acceptor inputs. These findings highlight the importance of quantifying the redox reactions occurring in small interface zones and assessing their role on biogeochemical cycling at the system scale.

Oklahoma↗

USGS2015

Stable-isotope and solute-chemistry approaches to flow characterization in a forested tropical watershed, Luquillo Mountains, Puerto Rico

The prospect of changing climate has led to uncertainty about the resilience of forested mountain watersheds in the tropics. In watersheds where frequent, high rainfall provides ample runoff, we often lack understanding of how the system will respond under conditions of decreased rainfall or drought. Factors that govern water supply, such as recharge rates and groundwater storage capacity, may be poorly quantified. This paper describes 8-year data sets of water stable isotope composition ( δ 2 H and δ 18 O) of precipitation (4 sites) and a stream (1 site), and four contemporaneous stream sample sets of solute chemistry and isotopes, used to investigate watershed response to precipitation inputs in the 1780-ha Río Mameyes basin in the Luquillo Mountains of northeastern Puerto Rico. Extreme δ 2 H and δ 18 O values from low-pressure storm systems and the deuterium excess ( d -excess) were useful tracers of watershed response in this tropical system. A hydrograph separation experiment performed in June 2011 yielded different but complementary information from stable isotope and solute chemistry data. The hydrograph separation results indicated that 36% of the storm rain that reached the soil surface left the watershed in a very short time as runoff. Weathering-derived solutes indicated near-stream groundwater was displaced into the stream at the beginning of the event, followed by significant dilution. The more biologically active solutes exhibited a net flushing behavior. The d- excess analysis suggested that streamflow typically has a recent rainfall component (∼25%) with transit time less than the sampling resolution of 7 days, and a more well-mixed groundwater component (∼75%). The contemporaneous stream sample sets showed an overall increase in dissolved solute concentrations with decreasing elevation that may be related to groundwater inputs, different geology, and slope position. A considerable amount of water from rain events runs off as quickflow and bypasses subsurface watershed flowpaths, and better understanding of shallow hillslope and deeper groundwater processes in the watershed will require sub-weekly data and detailed transit time modeling. A combined isotopic and solute chemistry approach can guide further studies to a more comprehensive model of the hydrology, and inform decisions for managing water supply with future changes in climate and land use.

Applied Geochemistry↗

USGS2026

Evaluating drivers of environmental change in a lake sediment core: Insights from spectroscopic metrics of water-extractable organic matter and stable carbon isotopes

Freshwater lakes play a critical role in the global carbon cycle by storing and transforming organic matter (OM) from both terrestrial and aquatic sources. Small lakes in northern temperate regions, despite their limited surface area, disproportionately influence regional carbon budgets. Buried sediments integrate OM inputs over time and archive ecosystem responses to natural and anthropogenic disturbances. However, the direction and magnitude of recent environmental changes on sediment carbon (C) dynamics remain poorly understood. A 23-cm core was collected from a small temperate lake in northeastern USA to evaluate sediment OM content and composition over timescales relevant to historical land-use change, damming, and recovery from acid deposition. Patterns in OM burial and source contributions were revealed via elemental and isotopic analyses of bulk OM and ultraviolet-visible spectrophotometry of water-extractable organic matter (WEOM). The optical metrics expanded observations of likely OM sources beyond the information gained from bulk carbon metrics (total carbon, δ 13 C). The aromaticity of WEOM increased downcore, which is consistent with a shift from increased terrestrial inputs during early logging and damming activity (pre ∼1920) to more microbial-derived OM in recent surficial sediments. Future applications of WEOM optical properties as complements to traditional geochemical metrics can enhance interpretations of lake ecosystem responses recorded in lake sediments to environmental perturbations in temperate lakes.

New York↗

USGS2007

Soil nematode communities are ecologically more mature beneath late- than early-successional stage biological soil crusts

Biological soil crusts are key mediators of carbon and nitrogen inputs for arid land soils and often represent a dominant portion of the soil surface cover in arid lands. Free-living soil nematode communities reflect their environment and have been used as biological indicators of soil condition. In this study, we test the hypothesis that nematode communities are successionally more mature beneath well-developed, late-successional stage crusts than immature, early-successional stage crusts. We identified and enumerated nematodes by genus from beneath early- and late-stage crusts from both the Colorado Plateau, Utah (cool, winter rain desert) and Chihuahuan Desert, New Mexico (hot, summer rain desert) at 0-10 and 10-30 cm depths. As hypothesized, nematode abundance, richness, diversity, and successional maturity were greater beneath well-developed crusts than immature crusts. The mechanism of this aboveground-belowground link between biological soil crusts and nematode community composition is likely the increased food, habitat, nutrient inputs, moisture retention, and/or environmental stability provided by late-successional crusts. Canonical correspondence analysis of nematode genera demonstrated that nematode community composition differed greatly between geographic locations that contrast in temperature, precipitation, and soil texture. We found unique assemblages of genera among combinations of location and crust type that reveal a gap in scientific knowledge regarding empirically derived characterization of dominant nematode genera in deserts soils and their functional role in a crust-associated food web. ?? 2006 Elsevier B.V. All rights reserved.

Applied Soil Ecology↗

USGS2011

Modules based on the geochemical model PHREEQC for use in scripting and programming languages

The geochemical model PHREEQC is capable of simulating a wide range of equilibrium reactions between water and minerals, ion exchangers, surface complexes, solid solutions, and gases. It also has a general kinetic formulation that allows modeling of nonequilibrium mineral dissolution and precipitation, microbial reactions, decomposition of organic compounds, and other kinetic reactions. To facilitate use of these reaction capabilities in scripting languages and other models, PHREEQC has been implemented in modules that easily interface with other software. A Microsoft COM (component object model) has been implemented, which allows PHREEQC to be used by any software that can interface with a COM server—for example, Excel®, Visual Basic®, Python, or MATLAB". PHREEQC has been converted to a C++ class, which can be included in programs written in C++. The class also has been compiled in libraries for Linux and Windows that allow PHREEQC to be called from C++, C, and Fortran. A limited set of methods implements the full reaction capabilities of PHREEQC for each module. Input methods use strings or files to define reaction calculations in exactly the same formats used by PHREEQC. Output methods provide a table of user-selected model results, such as concentrations, activities, saturation indices, and densities. The PHREEQC module can add geochemical reaction capabilities to surface-water, groundwater, and watershed transport models. It is possible to store and manipulate solution compositions and reaction information for many cells within the module. In addition, the object-oriented nature of the PHREEQC modules simplifies implementation of parallel processing for reactive-transport models. The PHREEQC COM module may be used in scripting languages to fit parameters; to plot PHREEQC results for field, laboratory, or theoretical investigations; or to develop new models that include simple or complex geochemical calculations.

Computers & Geosciences↗

USGS2017

Application of synthetic scenarios to address water resource concerns: A management-guided case study from the Upper Colorado River Basin

Water managers are increasingly interested in better understanding and planning for projected resource impacts from climate change. In this management-guided study, we use a very large suite of synthetic climate scenarios in a statistical modeling framework to simultaneously evaluate how (1) average temperature and precipitation changes, (2) initial basin conditions, and (3) temporal characteristics of the input climate data influence water-year flow in the Upper Colorado River. The results here suggest that existing studies may underestimate the degree of uncertainty in future streamflow, particularly under moderate temperature and precipitation changes. However, we also find that the relative severity of future flow projections within a given climate scenario can be estimated with simple metrics that characterize the input climate data and basin conditions. These results suggest that simple testing, like the analyses presented in this paper, may be helpful in understanding differences between existing studies or in identifying specific conditions for physically based mechanistic modeling. Both options could reduce overall cost and improve the efficiency of conducting climate change impacts studies.

Arizona, Colorado, New Mexico, Utah, Wyoming↗

USGS2022

New projections of 21st century climate and hydrology for Alaska and Hawaiʻi

In the United States, high-resolution, century-long, hydroclimate projection datasets have been developed for water resources planning, focusing on the contiguous United States (CONUS) domain. However, there are few statewide hydroclimate projection datasets available for Alaska and Hawaiʻi. The limited information on hydroclimatic change motivates developing hydrologic scenarios from 1950 to 2099 using climate-hydrology impact modeling chains consisting of multiple statistically downscaled climate projections as input to hydrologic model simulations for both states. We adopt an approach similar to the previous CONUS hydrologic assessments where: 1) we select the outputs from ten global climate models (GCM) from the Coupled Model Intercomparison Project Phase 5 with Representative Concentration Pathways 4.5 and 8.5; 2) we perform statistical downscaling to generate climate input data for hydrologic models (12-km grid-spacing for Alaska and 1-km for Hawaiʻi); and 3) we perform process-based hydrologic model simulations. For Alaska, we have advanced the hydrologic model configuration from CONUS by using the full water-energy balance computation, frozen soils and a simple glacier model. The simulations show that robust warming and increases in precipitation produce runoff increases for most of Alaska, with runoff reductions in the currently glacierized areas in Southeast Alaska. For Hawaiʻi, we produce the projections at high resolution (1 km) which highlight high spatial variability of climate variables across the state, and a large spread of runoff across the GCMs is driven by a large precipitation spread across the GCMs. Our new ensemble datasets assist with state-wide climate adaptation and other water planning.

Alaska, Hawaii↗

USGS2007

Organic petrology of Paleocene Marcelina Formation coals, Paso Diablo mine, western Venezuela: Tectonic controls on coal type

About 7??Mt of high volatile bituminous coal are produced annually from the four coal zones of the Upper Paleocene Marcelina Formation at the Paso Diablo open-pit mine of western Venezuela. As part of an ongoing coal quality study, we have characterized twenty-two coal channel samples from the mine using organic petrology techniques. Samples also were analyzed for proximate-ultimate parameters, forms of sulfur, free swelling index, ash fusion temperatures, and calorific value. Six of the samples represent incremental benches across the 12-13??m thick No. 4 bed, the stratigraphically lowest mined coal, which is also mined at the 10??km distant Mina Norte open-pit. Organic content of the No. 4 bed indicates an upward increase of woody vegetation and/or greater preservation of organic material throughout the life of the original mire(s). An upward increase in telovitrinite and corresponding decrease in detrovitrinite and inertinite illustrate this trend. In contrast, stratigraphically higher coal groups generally exhibit a 'dulling upward' trend. The generally high inertinite content, and low ash yield and sulfur content, suggest that the Paso Diablo coals were deposited in rain-fed raised mires, protected from clastic input and subjected to frequent oxidation and/or moisture stress. However, the two thinnest coal beds (both 0.7??m thick) are each characterized by lower inertinite and higher telovitrinite content relative to the rest of Paso Diablo coal beds, indicative of less well-established raised mire environments prior to drowning. Foreland basin Paleocene coals of western Venezuela, including the Paso Diablo deposit and time-correlative coal deposits of the Ta??chira and Me??rida Andes, are characterized by high inertinite and consistently lower ash and sulfur relative to Eocene and younger coals of the area. We interpret these age-delimited coal quality characteristics to be due to water availability as a function of the tectonic control of subsidence rate. It is postulated that slower subsidence rates dominated during the Paleocene while greater foreland basin subsidence rates during the Eocene-Miocene resulted from the loading of nappe thrust sheets as part of the main construction phases of the Andean orogen. South-southeastward advance and emplacement of the Lara nappes during the oblique transpressive collision of the Caribbean and South American tectonic plates in the Paleocene was further removed from the sites of peat deposition, resulting in slower subsidence rates. Slower subsidence in the Paleocene may have favored the growth of raised mires, generating higher inertinite concentrations through more frequent moisture stress. Consistently low ash yield and sulfur content would be due to the protection from clastic input in raised mires, in addition to the leaching of mineral matter by rainfall and the development of acidic conditions preventing fixation of sulfur. In contrast, peat mires of Eocene-Miocene age encountered rapid subsidence due to the proximity of nappe emplacement, resulting in lower inertinite content, higher and more variable sulfur content, and higher ash yield.

International Journal of Coal Geology↗

USGS2011

Prediction and assimilation of surf-zone processes using a Bayesian network: Part I: Forward models

Prediction of coastal processes, including waves, currents, and sediment transport, can be obtained from a variety of detailed geophysical-process models with many simulations showing significant skill. This capability supports a wide range of research and applied efforts that can benefit from accurate numerical predictions. However, the predictions are only as accurate as the data used to drive the models and, given the large temporal and spatial variability of the surf zone, inaccuracies in data are unavoidable such that useful predictions require corresponding estimates of uncertainty. We demonstrate how a Bayesian-network model can be used to provide accurate predictions of wave-height evolution in the surf zone given very sparse and/or inaccurate boundary-condition data. The approach is based on a formal treatment of a data-assimilation problem that takes advantage of significant reduction of the dimensionality of the model system. We demonstrate that predictions of a detailed geophysical model of the wave evolution are reproduced accurately using a Bayesian approach. In this surf-zone application, forward prediction skill was 83%, and uncertainties in the model inputs were accurately transferred to uncertainty in output variables. We also demonstrate that if modeling uncertainties were not conveyed to the Bayesian network (i.e., perfect data or model were assumed), then overly optimistic prediction uncertainties were computed. More consistent predictions and uncertainties were obtained by including model-parameter errors as a source of input uncertainty. Improved predictions (skill of 90%) were achieved because the Bayesian network simultaneously estimated optimal parameters while predicting wave heights.

Coastal Engineering↗

USGS2010

Sediment transport on the Palos Verdes shelf, California

Sediment transport and the potential for erosion or deposition have been investigated on the Palos Verdes (PV) and San Pedro shelves in southern California to help assess the fate of an effluent-affected deposit contaminated with DDT and PCBs. Bottom boundary layer measurements at two 60-m sites in spring 2004 were used to set model parameters and evaluate a one-dimensional (vertical) model of local, steady-state resuspension, and suspended-sediment transport. The model demonstrated skill (Brier scores up to 0.75) reproducing the magnitudes of bottom shear stress, current speeds, and suspended-sediment concentrations measured during an April transport event, but the model tended to underpredict observed rotation in the bottom-boundary layer, possibly because the model did not account for the effects of temperature-salinity stratification. The model was run with wave input estimated from a nearby buoy and current input from four to six years of measurements at thirteen sites on the 35- and 65-m isobaths on the PV and San Pedro shelves. Sediment characteristics and erodibility were based on gentle wet-sieve analysis and erosion-chamber measurements. Modeled flow and sediment transport were mostly alongshelf toward the northwest on the PV shelf with a significant offshore component. The 95th percentile of bottom shear stresses ranged from 0.09 to 0.16 Pa at the 65-m sites, and the lowest values were in the middle of the PV shelf, near the Whites Point sewage outfalls where the effluent-affected layer is thickest. Long-term mean transport rates varied from 0.9 to 4.8 metric tons m -1 yr -1 along the 65-m isobaths on the PV shelf, and were much higher at the 35-m sites. Gradients in modeled alongshore transport rates suggest that, in the absence of a supply of sediment from the outfalls or PV coast, erosion at rates of ???0.2 mm yr -1 might occur in the region southeast of the outfalls. These rates are small compared to some estimates of background natural sedimentation rates (???5 mm yr -1 ), but do not preclude higher localized rates near abrupt transitions in sediment characteristics. However, low particle settling velocities and strong currents result in transport length-scales that are long relative to the narrow width of the PV shelf, which combined with the significant offshore component in transport, means that transport of resuspended sediment towards deep water is as likely as transport along the axis of the effluent-affected deposit.

Continental Shelf Research↗

USGS2008

An improved state-parameter analysis of ecosystem models using data assimilation

Much of the effort spent in developing data assimilation methods for carbon dynamics analysis has focused on estimating optimal values for either model parameters or state variables. The main weakness of estimating parameter values alone (i.e., without considering state variables) is that all errors from input, output, and model structure are attributed to model parameter uncertainties. On the other hand, the accuracy of estimating state variables may be lowered if the temporal evolution of parameter values is not incorporated. This research develops a smoothed ensemble Kalman filter (SEnKF) by combining ensemble Kalman filter with kernel smoothing technique. SEnKF has following characteristics: (1) to estimate simultaneously the model states and parameters through concatenating unknown parameters and state variables into a joint state vector; (2) to mitigate dramatic, sudden changes of parameter values in parameter sampling and parameter evolution process, and control narrowing of parameter variance which results in filter divergence through adjusting smoothing factor in kernel smoothing algorithm; (3) to assimilate recursively data into the model and thus detect possible time variation of parameters; and (4) to address properly various sources of uncertainties stemming from input, output and parameter uncertainties. The SEnKF is tested by assimilating observed fluxes of carbon dioxide and environmental driving factor data from an AmeriFlux forest station located near Howland, Maine, USA, into a partition eddy flux model. Our analysis demonstrates that model parameters, such as light use efficiency, respiration coefficients, minimum and optimum temperatures for photosynthetic activity, and others, are highly constrained by eddy flux data at daily-to-seasonal time scales. The SEnKF stabilizes parameter values quickly regardless of the initial values of the parameters. Potential ecosystem light use efficiency demonstrates a strong seasonality. Results show that the simultaneous parameter estimation procedure significantly improves model predictions. Results also show that the SEnKF can dramatically reduce the variance in state variables stemming from the uncertainty of parameters and driving variables. The SEnKF is a robust and effective algorithm in evaluating and developing ecosystem models and in improving the understanding and quantification of carbon cycle parameters and processes. ?? 2008 Elsevier B.V.

Ecological Modelling↗