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Integrating field observations and process-based modeling to predict watershed water quality under environmental perturbations

Journal Article · · Journal of Hydrology
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  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  3. California Institute of Technology (CalTech), Pasadena, CA (United States). Jet Propulsion Lab. (JPL)
  4. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Watersheds play a critical role in supplying water resources needed for human use and ecosystem health. Understanding and predicting how, when, and where changes in the quantity and quality of water resources occur under different environmental stresses including extreme events is crucial for sustainable management of water resources under a changing environment. However, few studies have attempted to quantify or identify the factors and process interactions controlling the impact of extreme events across water-shed systems. Only few large-scale studies include coordinated monitoring and modeling efforts, which limits our ability to assess the large-scale impact of extreme events on water supply and quality. Methods are lacking to propagate uncertainty in process understanding through an integrated hydro-biogeochemical model framework and evaluate its importance, thus failing to take full advantage of the information potentially available through transformative advances in characterization technologies from high-resolution mass spectrometry to airborne and satellite-based remote sensing. There are consequent risks to our nations water security and to human and ecosystem health that may become exacerbated with the increasing frequency of extreme events that is projected for the coming decades. This paper reviews the current status of watershed science for both water quantity and quality and identifies critical gaps in our current knowledge and modeling capability in addressing the emergent needs in predicting watershed hydrologic and biogeochemical responses (i.e., water quantity and quality) under natural and anthropogenic perturbations. We highlight the need to (1) understand how environmental perturbations including extreme events like floods and droughts propagate through watershed systems and assess their short- and long-term impacts on watershed biogeochemistry, water quality and their recovery pathways; (2) develop and improve a watershed water quality model that reflects the state of scientific understanding gained from observations; and (3) construct a data-model fusion system for watershed characterization, process identification, and mechanistic model parameterization. A large base of modeling, monitoring and data capabilities have been built by various federal government agencies given the relevance of water to their critical missions. An emerging need is to build an integrated national capability for watershed water availability and quality that can address water-related missions across multiple federal agencies.
Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Los Alamos National Laboratory (LANL), Los Alamos, NM (United States); Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
Grant/Contract Number:
AC02-05CH11231; AC05-76RL01830
OSTI ID:
1842780
Report Number(s):
PNNL-SA--148272
Journal Information:
Journal of Hydrology, Journal Name: Journal of Hydrology Vol. 602; ISSN 0022-1694
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

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Microbes as Engines of Ecosystem Function: When Does Community Structure Enhance Predictions of Ecosystem Processes? journal February 2016
Bacterial Biogeography across the Amazon River-Ocean Continuum journal May 2017
Effects of Urbanization on Rural Drinking Water Quality in Beijing, China journal March 2017
Watershed Hydrology: Scientific Advances and Environmental Assessments journal March 2018
Quantifying the Performances of the Semi-Distributed Hydrologic Model in Parallel Computing—A Case Study journal April 2019
Synchrony and seasonality in bacterioplankton communities of two temperate rivers journal November 2005
Unraveling the role of land use and microbial activity in shaping dissolved organic matter characteristics in stream ecosystems journal March 2010
Biogeochemical cycling at the aquatic–terrestrial interface is linked to parafluvial hyporheic zone inundation history journal January 2017
Coupling a three-dimensional subsurface flow and transport model with a land surface model to simulate stream–aquifer–land interactions (CP v1.0) journal January 2017
The Variable Infiltration Capacity model version 5 (VIC-5): infrastructure improvements for new applications and reproducibility journal January 2018
A high-resolution simulation of groundwater and surface water over most of the continental US with the integrated hydrologic model ParFlow v3 journal January 2015
Searching for the Holy Grail of scientific hydrology: Qt=(S, R, Δt)A as closure journal January 2006
Rainfall threshold for hillslope outflow: an emergent property of flow pathway connectivity journal January 2007
Exploring the impact of forcing error characteristics on physically based snow simulations within a global sensitivity analysis framework journal January 2015
HESS Opinions: Repeatable research: what hydrologists can learn from the Duke cancer research scandal journal January 2016

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