skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: A box model for representing estuarine physical processes in Earth system models

Authors:
; ; ;
Publication Date:
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1416028
Grant/Contract Number:
SC0006814
Resource Type:
Journal Article: Publisher's Accepted Manuscript
Journal Name:
Ocean Modelling
Additional Journal Information:
Journal Volume: 112; Journal Issue: C; Related Information: CHORUS Timestamp: 2018-01-05 21:00:33; Journal ID: ISSN 1463-5003
Publisher:
Elsevier
Country of Publication:
United Kingdom
Language:
English

Citation Formats

Sun, Qiang, Whitney, Michael M., Bryan, Frank O., and Tseng, Yu-heng. A box model for representing estuarine physical processes in Earth system models. United Kingdom: N. p., 2017. Web. doi:10.1016/j.ocemod.2017.03.004.
Sun, Qiang, Whitney, Michael M., Bryan, Frank O., & Tseng, Yu-heng. A box model for representing estuarine physical processes in Earth system models. United Kingdom. doi:10.1016/j.ocemod.2017.03.004.
Sun, Qiang, Whitney, Michael M., Bryan, Frank O., and Tseng, Yu-heng. Sat . "A box model for representing estuarine physical processes in Earth system models". United Kingdom. doi:10.1016/j.ocemod.2017.03.004.
@article{osti_1416028,
title = {A box model for representing estuarine physical processes in Earth system models},
author = {Sun, Qiang and Whitney, Michael M. and Bryan, Frank O. and Tseng, Yu-heng},
abstractNote = {},
doi = {10.1016/j.ocemod.2017.03.004},
journal = {Ocean Modelling},
number = C,
volume = 112,
place = {United Kingdom},
year = {Sat Apr 01 00:00:00 EDT 2017},
month = {Sat Apr 01 00:00:00 EDT 2017}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record at 10.1016/j.ocemod.2017.03.004

Citation Metrics:
Cited by: 2works
Citation information provided by
Web of Science

Save / Share:
  • Microbes influence soil organic matter (SOM) decomposition and the long-term stabilization of carbon (C) in soils. We contend that by revising the representation of microbial processes and their interactions with the physicochemical soil environment, Earth system models (ESMs) may make more realistic global C cycle projections. Explicit representation of microbial processes presents considerable challenges due to the scale at which these processes occur. Thus, applying microbial theory in ESMs requires a framework to link micro-scale process-level understanding and measurements to macro-scale models used to make decadal- to century-long projections. Here, we review the diversity, advantages, and pitfalls of simulating soilmore » biogeochemical cycles using microbial-explicit modeling approaches. We present a roadmap for how to begin building, applying, and evaluating reliable microbial-explicit model formulations that can be applied in ESMs. Drawing from experience with traditional decomposition models we suggest: (1) guidelines for common model parameters and output that can facilitate future model intercomparisons; (2) development of benchmarking and model-data integration frameworks that can be used to effectively guide, inform, and evaluate model parameterizations with data from well-curated repositories; and (3) the application of scaling methods to integrate microbial-explicit soil biogeochemistry modules within ESMs. With contributions across scientific disciplines, we feel this roadmap can advance our fundamental understanding of soil biogeochemical dynamics and more realistically project likely soil C response to environmental change at global scales.« less
  • Although sediment yield (SY) from water erosion is ubiquitous and its environmental consequences are well recognized, its impacts on the global carbon cycle remain largely uncertain. This knowledge gap is partly due to the lack of soil erosion modeling in Earth System Models (ESMs), which are important tools used to understand the global carbon cycle and explore its changes. This study analyzed sediment and particulate organic carbon yield (CY) data from 1081 and 38 small catchments (0.1-200 km27 ), respectively, in different environments across the globe. Using multiple statistical analysis techniques, we explored environmental factors and hydrological processes important formore » SY and CY modeling in ESMs. Our results show clear correlations of high SY with traditional agriculture, seismicity and heavy storms, as well as strong correlations between SY and annual peak runoff. These highlight the potential limitation of SY models that represent only interrill and rill erosion because shallow overland flow and rill flow have limited transport capacity due to their hydraulic geometry to produce high SY. Further, our results suggest that SY modeling in ESMs should be implemented at the event scale to produce the catastrophic mass transport during episodic events. Several environmental factors such as seismicity and land management that are often not considered in current catchment-scale SY models can be important in controlling global SY. Our analyses show that SY is likely the primary control on CY in small catchments and a statistically significant empirical relationship is established to calculate SY and CY jointly in ESMs.« less
  • Spatially varying water-level regimes are a factor controlling estuarine and tidal-fluvial wetland vegetation patterns. As described in Part I, water levels in the Lower Columbia River and estuary (LCRE) are influenced by tides, river flow, hydropower operations, and coastal processes. In Part II, regression models based on tidal theory are used to quantify the role of these processes in determining water levels in the mainstem river and floodplain wetlands, and to provide 21-year inundation hindcasts. Analyses are conducted at 19 LCRE mainstem channel stations and 23 tidally exposed floodplain wetland stations. Sum exceedance values (SEVs) are used to compare wetlandmore » hydrologic regimes at different locations on the river floodplain. A new predictive tool is introduced and validated, the potential SEV (pSEV), which can reduce the need for extensive new data collection in wetland restoration planning. Models of water levels and inundation frequency distinguish four zones encompassing eight reaches. The system zones are the wave- and current-dominated Entrance to river kilometer (rkm) 5; the Estuary (rkm-5 to 87), comprised of a lower reach with salinity, the energy minimum (where the turbidity maximum normally occurs), and an upper estuary reach without salinity; the Tidal River (rkm-87 to 229), with lower, middle, and upper reaches in which river flow becomes increasingly dominant over tides in determining water levels; and the steep and weakly tidal Cascade (rkm-229 to 234) immediately downstream from Bonneville Dam. The same zonation is seen in the water levels of floodplain stations, with considerable modification of tidal properties. The system zones and reaches defined here reflect geological features and their boundaries are congruent with five wetland vegetation zones« less
  • This project aimed to improve long term global climate simulations by resolving and enhancing the representation of the processes involved in the cycling of freshwater through estuaries and coastal regions. This was a collaborative multi-institution project consisting of physical oceanographers, climate model developers, and computational scientists. It specifically targeted the DOE objectives of advancing simulation and predictive capability of climate models through improvements in resolution and physical process representation. The main computational objectives were: 1. To develop computationally efficient, but physically based, parameterizations of estuary and continental shelf mixing processes for use in an Earth System Model (CESM). 2. Tomore » develop a two-way nested regional modeling framework in order to dynamically downscale the climate response of particular coastal ocean regions and to upscale the impact of the regional coastal processes to the global climate in an Earth System Model (CESM). 3. To develop computational infrastructure to enhance the efficiency of data transfer between specific sources and destinations, i.e., a point-to-point communication capability, (used in objective 1) within POP, the ocean component of CESM.« less