SEARCH · Engineering Papers

Results for “Environmental Models”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15

All sources NASA NTRS DOE OSTI

DOE OSTI2026

A Hybrid Biophysical‐Machine Learning Framework for Diurnal Surface Energy Flux Estimation Using Proximal Sensing

Thermal infrared-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy ( LE ) and sensible heat ( H ) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal infrared data sets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of a ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R 2 = 0.81–0.94) and H (R 2 = 0.46–0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical-machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.

evapotranspiration↗

DOE OSTI2022

Environmental design of low-head run-of-river hydropower in the United States: A review of facility design models

We state that the goal of run-of-river hydropower is to produce cost-competitive renewable electricity with minimal disruption of the natural riverine ecosystem. Modeling and feasibility analysis of alternative design options are crucial for developing new run-of-river hydropower projects. Our review shows that existing run-of-river hydropower design models focus on maximizing economic potential at high-head diversion schemes with limited consideration of environmental outcomes. Since nearly three-quarters of new hydropower potential in the United States is found at low-head sites and environmental performance standards are imperative to project success, new models are needed to address the multi-dimensional design challenges at these sites. To aid in formulating holistic models, we synthesize the performance objectives and design variables related to early-stage run-of-river facility design. The objectives span six potential impact areas, including hydrologic alteration, sediment continuity, water quality, aquatic species passage, social, and economic. Based on these reviews, we identify three key areas to enhance the capabilities of run-of-river hydropower design models. These are 1) expanded model formulations, 2) assessment of barrier effects, and 3) explicit environmental objectives. The resulting modeling improvements would accelerate the identification of run-of-river hydropower designs that minimize environmental impacts, promote economic competitiveness, and incorporate the value of non-power benefits.

13 HYDRO ENERGY↗

DOE OSTI2025

A modeling study of ocean thermal energy conversion resource and potential environmental effects around Kailua-Kona, Hawaii

Ocean Thermal Energy Conversion (OTEC) offers a promising renewable energy solution through a heat exchange process using the temperature difference between warm surface seawater and cold deep seawater. Because accurate resource characterization is critical for the optimal design and implementation of OTEC systems, a high-resolution numerical model is employed to better characterize the OTEC resource at Kona, Hawaii. Our model provides detailed spatial and temporal variability of the thermal gradient, which is essential for assessing the viability and efficiency of OTEC systems. The model results reveal distinct patterns and dynamics not captured by existing observations or models (e.g., lower-resolution information). These findings highlight the importance of using high-resolution models for accurate predictions of thermal gradient variability, ultimately supporting more efficient and sustainable OTEC deployment. Additionally, the study investigates the impacts of mixed water discharge from OTEC plants that can cause shock to organisms living in the surface water and potentially destabilize the water column. Understanding these effects is vital for minimizing any potential negative environmental consequences and ensuring the long-term viability of OTEC operations. Further, our model improves OTEC resource characterization, which can lead to optimal design and deployment of OTEC systems. The analysis of OTEC water discharge impacts can accelerate the development of OTEC technologies, overcoming permitting/consenting challenges. These findings contribute to the broader adoption of high-resolution modeling in ocean energy resource characterization, particularly for OTEC applications.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2019

Plant roots stimulate the decomposition of complex, but not simple, soil carbon

Roots release carbon into soil and can alleviate energy limitation of microbial organic matter decomposition. We know little about the effects of roots on microbial decomposition of different organic matter substrates, despite the importance for soil carbon stocks and turnover. Through implementing root-microbe interactions, the Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment (CORPSE) model was previously shown to represent dynamics of total soil carbon in temperate forest field experiments. However, the model permits alternative hypotheses concerning microbial-substrate affinity. We investigated how root inputs affect decomposition of soil organic carbon (SOC) with variable decomposability. We simulated SOC stocks in CORPSE and compared microbial degradation of two substrates types with varying root-microbe interactions under two alternative hypotheses that varied in microbial-substrate affinity. We compared our modeled hypotheses to a forest field experiment where we quantified decomposition of isotopically-labeled starch and leaf tissues in soils with manipulated root access to microbes. Here, we tested the hypothesis that decomposition of leaves would be more sensitive to root inputs than decomposition of starch, corresponding to the alternative model hypothesis. In the field study, leaf decomposition increased with root density while starch decomposition was unchanged by root density. Microbial biomass and enzyme activity consistently increased with root inputs in CORPSE and the field study. Our field experiment supported the CORPSE simulations with high microbial-substrate affinity. Roots stimulated microbial growth and enzyme production, which increased degradation of more complex substrates such as leaf tissues. Substrates that were easily decomposed, such as starch, may already be degrading at a maximum rate in the absence of rhizosphere influence because their decomposition rate was unchanged by root inputs. We found that the degree to which roots stimulate microbial decomposition depends on the substrate being decomposed, and that root-microbe interactions influenced SOC stocks in both our model and field experiment. Environmental changes that alter root-microbe interactions could, therefore, alter soil C stocks and biogeochemical cycling, and models of these interactions should incorporate differential influence of rhizosphere inputs on different substrates.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

An Enhanced Vertical Ground Heat Exchanger Model for Whole-Building Energy Simulation

This paper presents an enhanced vertical ground heat exchanger (GHE) model for whole-building energy simulation (WBES). WBES programs generally have computational constraints that affect the development and implementation of component simulation sub-models. WBES programs require models that execute quickly and efficiently due to how the programs are utilized by design engineers. WBES programs also require models to be formulated so their performance can be determined from boundary conditions set by upstream components and environmental conditions. The GHE model developed during this work utilizes an existing response factor model and extends its capabilities to accurately and robustly simulate at timesteps that are shorter than the GHE transit time. This was accomplished by developing a simplified dynamic borehole model and then exercising that model to generate exiting fluid temperature response factors. This approach blends numerical and analytical modeling methods. The existing response factor models are then extended to incorporate the exiting fluid temperature response factor to provide a better estimate of the GHE exiting fluid temperature at short simulation timesteps.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

A physics-informed multi-agents model to predict thermo-oxidative/hydrolytic aging of elastomers

This paper introduces a novel physics-informed multi-agents constitutive model to propose prediction in quasi-static constitutive behavior of cross-linked elastomer and the loss of mechanical performance during environmental aging. The presented model is used to simulate the effect of single-mechanism chemical aging (i.e. thermal-inducedor hydrolytic aging) on the behavior of the material in this hybrid framework. Those environmental single-mechanism damages change the polymer matrix over time due to massive chain scission, chain formations, and changing the arrangement of molecules in the polymer matrix. Here we propose a data-driven super-constrained machine-learned engine to represent damage in the polymer matrix and capture the changes in material behavior, including its inelastic features such as Mullins effect and permanent set in the course of aging. We have simplified the 3D stress–strain tensor mapping problem into a small number of super-constrained 1D mapping problems by means of a sequential order reduction. An assembly of multiple replicated conditional neural-network learning-agents (L-agents) is trained to systematically simplify the high-dimensional mapping problem into multiple 1D problems, each represented by a different type of agent. Our hybrid framework is designed to capture the effect of deformation history, aging time, and aging temperature. The model is validated with respect to a comprehensive set of experiments specifically designed to benchmark model capabilities and also against available data in the literature. Thermodynamic consistency and frame independency have been verified. Besides acceptable predictive abilities, a significant reduction of computational cost to predict behavior at multiple states of deformation is the most significant feature of this model.

42 ENGINEERING↗

DOE OSTI2024

Global-Scale Convergence Obscures Inconsistencies in Soil Carbon Change Predicted by Earth System Models

Soil carbon (C) responses to environmental change represent a major source of uncertainty in the global C cycle. Feedbacks between soil C stocks and climate drivers could impact atmospheric CO 2 levels, further altering the climate. Here, we assessed the reliability of Earth system model (ESM) predictions of soil C change using the Coupled Model Intercomparison Project phases 5 and 6 (CMIP5 and CMIP6). ESMs predicted global soil C gains under the high emission scenario, with soils taking up 43.9 Pg (95% CI: 9.2–78.5 Pg) C on average during the 21st century. The variation in global soil C change declined significantly from CMIP5 (with average of 48.4 Pg [95% CI: 2.0–94.9 Pg] C) to CMIP6 models (with average of 39.3 Pg [95% CI: 23.9–54.7 Pg] C). For some models, a small C increase in all biomes contributed to this convergence. For other models, offsetting responses between cold and warm biomes contributed to convergence. Although soil C predictions appeared to converge in CMIP6, the dominant processes driving soil C change at global or biome scales differed among models and in many cases between earlier and later versions of the same model. Random Forest models, for soil carbon dynamics, accounted for more than 63% variation of the global soil C change predicted by CMIP5 ESMs, but only 36% for CMIP6 models. Although most CMIP6 models apparently agree on increased soil C storage during the 21st century, this consensus obscures substantial model disagreement on the mechanisms underlying soil C response, calling into question the reliability of model predictions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Development of Saturated Zone Three-Dimensional Initial Condition Plumes for the Composite Analysis and Cumulative Impacts Evaluation Modeling

The purpose of this environmental calculation file (ECF) is to document and present the methodology, input data, and results of extending two-dimensional (2-D) plume depictions documented in DOE/RL- 2017-66, Hanford Site Groundwater Monitoring for 2017, into three dimensions (3-D) for select contaminants of interest (COIs) in the 200-BP-5, 200-UP-1, 200-ZP-1, and 200-PO-1 Groundwater Operable Units at the Hanford Site. Plumes with sufficient available vertical profile data were interpolated in 3-D using the Leapfrog Geo®1 geologic modeling platform, which includes an interpolation engine for analyzing and visualizing 3-D data. Results of these interpolations are intended for use in developing inputs for transport modeling to support forecasts of Central Plateau contaminant plume fate and transport.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Life Cycle Analysis and Life Cycle Costing for Municipal Solid Waste (MSW) Management and Materials Redeployment to Support ARPA-E’s Potential Program on Waste to Energy and Materials

Municipal solid waste infrastructure in the United States contains complex supply chains to transport, sort, and sequester waste. This project developed models to estimate the environmental and economic costs of waste infrastructure in the U.S. using data from several municipalities. Life cycle costing (LCC) models were developed for waste management relevant supply chain steps, including waste collection, sorting, landfilling, waste-to-energy, ash processing, and recycling. A waste-to-materials and energy (WTM&E) life cycle analysis (LCA) and LCC dashboard was developed in collaboration with Argonne National Laboratory (ANL) and an LCC tool was developed for additional analysis.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2026

Modelling the Sensitivity of Yukon River Biogeochemical Dynamics to Environmental and Chemical Drivers: Implications for Dissolved Organic Carbon

Riverine dissolved organic carbon (DOC) is a critical biogeochemical component that transmits information from Arctic soils to the Arctic Ocean, significantly influencing carbon dynamics in this unique ecosystem. As DOC travels downstream, it undergoes transformations that alter its composition and fate. The Yukon River serves as an effective testbed for modelling these dynamics, offering sufficient scale to capture key biogeochemical processes while having a simpler hydrology than other major Arctic rivers, as well as long-term DOC observational data for model validation. To investigate DOC transformations during transit in the Yukon River, we adapted our Arctic Riverine Organic Macromolecular Model by applying regional-specific parameterisations. Our model simulates the transport and transformation of 15 organic macromolecules, including CDOM (coloured dissolved organic matter), proteins, polysaccharides, lipids, lignin phenols, and humic substances. Initial DOC concentrations were derived from observed soil organic carbon stocks in the surrounding watershed, while chemical transformations and hydrological dynamics were modelled along the river's course. Sensitivity and uncertainty analyses were conducted using a Monte Carlo approach under two experimental setups. Results revealed that variability in DOC and CDOM concentrations at the river mouth were predominantly driven by initial DOC concentration (~70% of variability explained) and dilution at confluence points (~10%). The refractory fraction of DOC explained 21%–88% of the variability in 14 macromolecular concentrations and ranked in the top five sensitive parameters for all outputs when a uniform parameter distribution was assumed. However, when a more likely variability was applied to this parameter, its influence on DOC and CDOM decreased. Given that refractory DOC accounts for ~80% of total DOC in Arctic Rivers, this suggests that most DOC resists degradation and retains its chemical composition during transport to the coastal environment. River velocity, which determines residence time, explained 8%–47% of the variability in protein, polysaccharide, lipid, pigments, and lignin phenols at the river mouth. In contrast, chemical turnover times contributed only 1%–5% to output variability. Our findings underscore the need for improved land-specific headwater observations, including seasonal soil moisture and lateral transport dynamics that control the initial tributary-specific DOC inputs. With accelerated permafrost thaw and increasing river discharge, extending our model to other Arctic River systems and seasons will enhance understanding of Arctic riverine carbon fluxes and their contributions to the Arctic Ocean.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Rapid Refresh 20km

Rapid Refresh 20km forecast model data converted from GRIB data files generated by NCEP.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Screening green solvents for multilayer plastic film recycling processes

Multilayer (ML) plastic films are essential packaging materials that help protect products from diverse external factors; however, only 5% of all ML films are recycled in the United States. Solvent-based technologies are a promising alternative for recycling ML films because they enable recovery of constituent polymer resins. For example, the Solvent Targeted Recovery and Precipitation (STRAPTM) process sequentially dissolves and separates polymer components using a series of targeted solvent washes. A crucial design aspect of this process is the impact of selected solvents on human health and on the environment. Here, this work introduces a computational framework that integrates molecular modeling, process modeling, techno-economic analysis (TEA), and life-cycle analysis (LCA) to quickly screen green solvents for solvent-based ML recycling processes. Initial screening for solvents based on selectivity is performed by estimating temperature-dependent solubilities using molecular-scale models. Subsequent screening uses basic estimates of energy use and octanol-water partition coefficients (logP) as key measures of health, safety, and environmental hazards. Detailed process modeling, TEA, and LCA are used on a reduced set of promising solvents identified in early screening steps to more accurately determine how solvent selection and associated operating conditions impact overall economics and environmental impacts. The framework is used for the identification of green solvents (from a database of 1,000 solvents) that separate an industrial ML film composed of polyethylene (PE), ethylene vinyl alcohol (EVOH), and polyethylene terephthalate (PET). Our analysis shows the effectiveness of the framework and reveals fundamental trade-offs between solvent greenness, solubility, and economics. Our work emphasizes the importance of taking a holistic systems view during solvent design and aims to inform the development of new processes for ML film recycling and the identification of new ML films that are easier to recycle.

economics↗

DOE OSTI2020

A Physically-Based Model for Thermo-Oxidative and Hydrolytic Aging of Elastomers

A computationally efficient model is proposed to capture the loss of mechanical performance due to chemical aging that are formed as the competition of chain scission and cross-link formation/dissolution, such as thermo-oxidative aging or hydrolytic aging. The model should be considered an extension of our recent models [1, 2, 3] which further simplifies the matrix behavior based on the assumption of independence of environmental and mechanical damage. The model uses this assumption to reduce the necessary material parameters needed to model constitutive and inelastic behavior of elastomers during aging. To this end, the model can provide accurate predictions of the material performance with the significantly fewer number of fitting parameters. The model is relevant for all decay mechanisms formed by the occurrence of two simultaneous micro-mechanisms; (i) formation/reduction of the cross-links, and (ii) chain scission, both of which are present in thermo-oxidation and hydrolytic aging. Assuming the alteration of the chain density along the aging trajectory is identical to the peroxide cross-link density for thermo-oxidation, and the change of the average molecular weight for hydrolysis, the strain energy of polymer matrix can be rewritten as a function of deformation, deformation history, storage time and aging temperature. Next, the modified network alteration model is formulated for implementation into Finite Element (FE) simulations. The model is built on the presumption of homogeneous and consistent oxygen/water absorption and thus is mainly relevant for relatively thin samples exposed to environmental loads for a long time. The proposed model includes only six physically inspired material parameters. Therefore, while it is computationally efficient, it shows good agreement with own experimental data, which performed on various range of accelerated aging temperatures and times. With respect to its computational efficiency, simplicity, accuracy, and interpret-ability, the model is the right choice for advanced implementations in FE programs.

42 ENGINEERING↗

DOE OSTI2021

Vadose and Saturated Zone Flow and Transport Calculations for the Active Trenches of the Low-Level Burial Grounds, Hanford Site, Washington

The purpose of the fate and transport modeling described in this environmental calculation file (ECF) is to evaluate the impacts to groundwater associated with waste disposal operations at Mixed Waste Low-Level Burial Ground (LLBG) Trenches 31 and 34 to satisfy requirements in DOE O 435.1, Radioactive Waste Management. The model integrates the flow and transport in the vadose zone beneath the active trenches with the saturated zone downgradient of the trenches to predict the radionuclide concentration at the point of assessment (POA). DOE M 435.1-1, Radioactive Waste Management Manual, defines the POA as the point of highest projected dose or concentration beyond a 100 m (328 ft) buffer zone surrounding the disposed waste. The modeling is conducted in accordance with the DOE G 435.1, Implementation Guide for Use with DOE M 435.1-1, performance assessment (PA) guidelines. The modeling involves evaluation of the groundwater concentrations and radionuclide arrival times during the 1,000-year compliance and 10,000-year sensitivity-uncertainty periods per DOE O 435.1 and DOE M 435.1. This analysis does not consider radionuclide release during facility operations, only the post-closure impacts of the radionuclides to the environment. The evaluation of potential radiological dose to groundwater receptors caused by releases from a closed facility containing radioactive waste typically includes the following: (1) Release of radionuclides from that facility (2) Transport of those radionuclides through the environment, and (3) Exposure to humans to environmental concentration levels of those radionuclides The fate and transport three-dimensional (3D) model analysis involves the post-closure impacts to the environment of the technetium-99, iodone-129, and uranium (all isotopes in the waste). The residual inventory estimates include several radionuclides, but technetium-99 is typically responsible for almost all of the beta-gamma dose equivalent associated with groundwater (water resources) protection per 40 CFR 141, “National Primary Drinking Water Regulations” (e.g., see the results in WCH-520, Performance Assessment of Environmental Restoration Disposal Facility, Hanford Site, Washington; hereinafter referred to as the ERDF PA), and iodone-129 can also be a significant dose contributor for some waste (e.g., RPP-RPT-59958, Performance Assessment for the Integrated Disposal Facility, Hanford Site, Washington; hereinafter referred to as the IDF PA). Uranium does not typically factor significantly into the impacts to groundwater, even during the 10,000-year sensitivity-uncertainty period, but always remains of interest as a contaminant. This ECF does not address vadose and saturated zone modeling for Trench 94 of the 200 East Area LLBG. Current information confirms the validity of the low corrosion rate of the naval reactor plant carbon steel (HY-80), and the even lower corrosion rate of the nickel-iron-chromium alloy reactor vessel (Inconel Alloy 600) presented in DOE/EIS-0259, Final Environmental Impact Statement on the Disposal of Decommissioned, Defueled Cruiser, Ohio Class, and Los Angeles Class Naval Reactor Plants. Based on these low corrosion rates, the time to breach the reactor vessel to allow release of radionuclides from the activated metal of the reactor vessel internal structure is at least 10,000 years. This time to breach precludes the need to evaluate the vadose and saturated zone transport of contaminants released from the reactor compartment disposal packages in the 200 East Area LLBGs PA (CP-63826, Waste Release Model Package Report for the Active Trenches of the Low-Level Burial Grounds, Hanford Site, Washington).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

An evolutionary algorithm for designing microbial communities via environmental modification

Despite a growing understanding of how environmental composition affects microbial communities, it remains difficult to apply this knowledge to the rational design of synthetic multispecies consortia. This is because natural microbial communities can harbour thousands of different organisms and environmental substrates, making up a vast combinatorial space that precludes exhaustive experimental testing and computational prediction. Here, we present a method based on the combination of machine learning and metabolic modelling that selects optimal environmental compositions to produce target community phenotypes. In this framework, dynamic flux balance analysis is used to model the growth of a community in candidate environments. A genetic algorithm is then used to evaluate the behaviour of the community relative to a target phenotype, and subsequently adjust the environment to allow the organisms to approach this target. We apply this iterative process to thousands of in silico communities of varying sizes, showing how it can rapidly identify environments that yield desired taxonomic compositions and patterns of metabolic exchange. Moreover, this combination of approaches produces testable predictions for the assembly of experimental microbial communities with specific properties and can facilitate rational environmental design processes for complex microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Hanford Site-wide Natural Recharge Boundary Condition for Groundwater Models

The purpose of this environmental calculation file (ECF) is to document the development of a tool that generates temporally and spatially variable representations of natural recharge for the Hanford Site. A key feature of the recharge evolution tool (RET) is that it applies sanctioned natural re-charge rates varying as a function of the condition/cover of the ground surface and soil type at different points in time. No hydrologic calculations are performed by the RET, this script works as a lookup data base between spatial and temporal datasets to assign research-based recharge rates to corresponding regions throughout the Hanford Site. This work will support vadose zone and groundwater models for the Hanford Site. Although efforts will focus on generating recharge estimates for the entirety of the Hanford Site, the focus scope of this work will be the Central Plateau Area to support the Composite Analysis Vadose Zone facet. In other words, the reliability of this calculation will be greatest within the Central Plateau Area and decrease with departures from that geographic region.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Hanford Site-wide Natural Recharge Boundary Condition for Groundwater Models

The purpose of this environmental calculation file (ECF) is to document the development of a tool that generates temporally and spatially variable representations of natural recharge for the Hanford Site. A key feature of the recharge evolution tool (RET) is that it applies sanctioned natural recharge rates varying as a function of the condition/cover of the ground surface and soil type at different points in time. No hydrologic calculations are performed by the RET, this script works as a lookup database between spatial and temporal datasets to assign research-based recharge rates to corresponding regions throughout the Hanford Site. This work will support vadose zone and groundwater models for the Hanford Site. Although efforts will focus on generating recharge estimates for the entirety of the Hanford Site, the focus scope of this work will be the Central Plateau Area to support the Composite Analysis Vadose Zone facet. In other words, the reliability of this calculation will be greatest within the Central Plateau Area and decrease with departures from that geographic region.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Hanford Site-wide Natural Recharge Boundary Condition for Groundwater Models

The purpose of this environmental calculation file (ECF) is to document the development of a tool that generates temporally and spatially variable representations of natural recharge for the Hanford Site. A key feature of the recharge evolution tool (RET) is that it applies sanctioned natural recharge rates varying as a function of the condition/cover of the ground surface and soil type at different points in time. No hydrologic calculations are performed by the RET, this script works as a lookup database between spatial and temporal datasets to assign research-based recharge rates to corresponding regions throughout the Hanford Site. This work will support vadose zone and groundwater models for the Hanford Site. Although efforts will focus on generating recharge estimates for the entirety of the Hanford Site, the focus scope of this work will be the Central Plateau Area to support the Composite Analysis Vadose Zone facet. In other words, the reliability of this calculation will be greatest within the Central Plateau Area and decrease with departures from that geographic region.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗