A process-based, distributed hydrologic model based on a large-scale method for surface–subsurface coupling

Shen, Chaopeng; Phanikumar, Mantha S.

doi:10.1016/j.advwatres.2010.09.002

Cited by 182 publications

(187 citation statements)

References 53 publications

Supporting

Mentioning

179

Contrasting

Unclassified

Order By: Relevance

“…While these conditions appear challenging, several hydrologic models have implemented these schemes [Downer and Ogden, 2004;Qu and Duffy, 2007;Shen and Phanikumar, 2010], and parsimonious representations of these processes have already been implemented in some land models Miguez-Macho and Fan, 2012a,b].…”

Section: 1002/2015wr017096mentioning

confidence: 99%

“…Table 3 identifies candidate areas to improve the representation of hydrologic processes in land models. The key areas are (1) improve simulations of the storage and transmission of water in the soil matrix, obtained through (a) implementing the mixed form of Richards' equation [Celia et al, 1990;Maxwell and Miller, 2005] and (b) explicitly representing macropore flow [Beven and Germann, 1982;Weiler, 2005;Nimmo, 2010;Yu et al, 2014]; (2) improve representation of hydraulic gradients throughout the soil-plantatmosphere continuum to improve simulations of root water uptake and evapotranspiration [Baldocchi and Meyers, 1998;Mackay et al, 2003;Bonan et al, 2014]; (3) improve representation of groundwater dynamics across a hierarchy of spatial scales, including improving ''among grid'' and ''within grid'' groundwater representations [Famiglietti and Wood, 1994;Troch et al, 2003;Miguez-Macho et al, 2007]; and (4) improve simulations of streamflow, by explicitly representing stream-aquifer interactions and improving parameterizations of channel/floodplain routing [Qu and Duffy, 2007;Shen and Phanikumar, 2010;MiguezMacho and Fan, 2012a;Pappenberger et al, 2012]. Underpinning all of these areas is the need to improve data sets on geophysical attributes, especially data on bedrock depth and permeability [Tesfa et al, 2009;Fan et al, 2015] and data sets on the physical characteristics of rivers [Getirana et al, 2013;Mersel et al, 2013;Gleason and Smith, 2014].…”

Section: Opportunities To Improve the Representation Of Hydrologic Prmentioning

confidence: 99%

“…However, the flux parameterization in equation (A2), i.e., the moisture-based form of Richards' equation, as used in LEAF and MATSIRO, can only simulate unsaturated flow and this separation of the saturated and unsaturated zones complicates representing shallow groundwater dynamics such as perched water tables. A variant of this boundary condition, used in PAWS1CLM [Shen and Phanikumar, 2010;Shen et al, 2013], is a noniterative coupling scheme between saturated groundwater flow and the unsaturated zone. With this method, the water table simulated by the saturated zone is consistent with the soil moisture profile.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Improving the representation of hydrologic processes in Earth System Models

Clark

Fan

Lawrence

et al. 2015

Water Resources Research

Self Cite

468

404

View full text Add to dashboard Cite

Many of the scientific and societal challenges in understanding and preparing for global environmental change rest upon our ability to understand and predict the water cycle change at large river basin, continent, and global scales. However, current large-scale land models (as a component of Earth System Models, or ESMs) do not yet reflect the best hydrologic process understanding or utilize the large amount of hydrologic observations for model testing. This paper discusses the opportunities and key challenges to improve hydrologic process representations and benchmarking in ESM land models, suggesting that (1) land model development can benefit from recent advances in hydrology, both through incorporating key processes (e.g., groundwater-surface water interactions) and new approaches to describe multiscale spatial variability and hydrologic connectivity; (2) accelerating model advances requires comprehensive hydrologic benchmarking in order to systematically evaluate competing alternatives, understand model weaknesses, and prioritize model development needs, and (3) stronger collaboration is needed between the hydrology and ESM modeling communities, both through greater engagement of hydrologists in ESM land model development, and through rigorous evaluation of ESM hydrology performance in research watersheds or Critical Zone Observatories. Such coordinated efforts in advancing hydrology in ESMs have the potential to substantially impact energy, carbon, and nutrient cycle prediction capabilities through the fundamental role hydrologic processes play in regulating these cycles.

show abstract

Section: 1002/2015wr017096mentioning

confidence: 99%

Section: Opportunities To Improve the Representation Of Hydrologic Prmentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Improving the representation of hydrologic processes in Earth System Models

Clark

Fan

Lawrence

et al. 2015

Water Resources Research

Self Cite

468

404

View full text Add to dashboard Cite

show abstract

“…It has been argued that the relevant spatial scale for hydrological state and flux heterogeneity is on the order of 100 m (Wood et al, 2011), while for biogeochemical dynamics it may be as small as 1 m (Burt and Pinay, 2005;Groffman et al, 2009;Frei et al, 2012;McClain et al, 2003). The current suite of land models representing coupled hydrological and biogeochemical cycles and used for analyses of water resources and water quality (e.g., HydroGeoSphere (Li et al, 2008(Li et al, ),al., 2006, MIKE-SHE (McMichael et al, 2006), WEP-L (Jia et al, 2006), and PAWS (Shen, 2009;Shen and Phanikumar, 2010)), as well as regional (e.g., Subin et al, 2011) and global (e.g., Koven et al, 2013;Tang et al, 2013) climate prediction are typically applied at resolutions that are orders of magnitude larger than these scales. Unfortunately, there are few large-scale observational datasets with which to test the impact of the discrepancies in scale between model representation and known variability of coupled hydrological and biogeochemical processes.…”

Section: Introductionmentioning

confidence: 99%

Characterizing coarse-resolution watershed soil moisture heterogeneity using fine-scale simulations

Riley

2014

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. Watershed-scale hydrological and biogeochemical models are usually discretized at resolutions coarser than where significant heterogeneities in topography, abiotic factors (e.g., soil properties), and biotic (e.g., vegetation) factors exist. Here we report on a method to use fine-scale (220 m grid cells) hydrological model predictions to build reduced-order models of the statistical properties of nearsurface soil moisture at coarse resolution (2 5 times coarser, ∼ 7 km). We applied a watershed-scale hydrological model (PAWS-CLM4) that has been previously tested in several watersheds. Using these simulations, we developed simple, relatively accurate (R 2 ∼ 0.7-0.8), reduced-order models for the relationship between mean and higher-order moments of near-surface soil moisture during the nonfrozen periods over five years. When applied to transient predictions, soil moisture variance and skewness were relatively accurately predicted (R 2 ∼ 0.7-0.8), while the kurtosis was less accurately predicted (R 2 ∼ 0.5). We also tested 16 system attributes hypothesized to explain the negative relationship between soil moisture mean and variance toward the wetter end of the distribution and found that, in the model, 59 % of the variance of this relationship can be explained by the elevation gradient convolved with mean evapotranspiration. We did not find significant relationships between the time rate of change of soil moisture variance and covariances between mean moisture and evapotranspiration, drainage, or soil properties, as has been reported in other modeling studies. As seen in previous observational studies, the predicted soil moisture skewness was predominantly positive and negative in drier and wetter regions, respectively. In individual coarse-resolution grid cells, the transition between positive and negative skewness occurred at a mean soil moisture of ∼ 0.25-0.3. The type of numerical modeling experiments presented here can improve understanding of the causes of soil moisture heterogeneity across scales, and inform the types of observations required to more accurately represent what is often unresolved spatial heterogeneity in regional and global hydrological models.

show abstract

“…Physically based hydrological models provide a refined understanding of hydrologic processes Chen et al, 2015) and quantification of hydrologic states and fluxes (Qu and Duffy, 2007;Shen and Phanikumar, 2010). However, these models are generally data (Bhatt et al, 2014) and computation intensive (Vivoni et al, 2011), and their potential uses are often undercut by equifinality of parameters (Beven, 1993;Kumar et al, 2013;Pokhrel et al, 2008).…”

mentioning

confidence: 99%

Modeling the potential impacts of climate change on the water table level of selected forested wetlands in the southeastern United States

Zhu¹,

Sun²,

Li³

et al. 2017

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. The southeastern United States hosts extensive forested wetlands, providing ecosystem services including carbon sequestration, water quality improvement, groundwater recharge, and wildlife habitat. However, these wetland ecosystems are dependent on local climate and hydrology, and are therefore at risk due to climate and land use change. This study develops site-specific empirical hydrologic models for five forested wetlands with different characteristics by analyzing long-term observed meteorological and hydrological data. These wetlands represent typical cypress ponds/swamps, Carolina bays, pine flatwoods, drained pocosins, and natural bottomland hardwood ecosystems. The validated empirical models are then applied at each wetland to predict future water table changes using climate projections from 20 general circulation models (GCMs) participating in Coupled Model Inter-comparison Project 5 (CMIP5) under the Representative Concentration Pathways (RCPs) 4.5 and 8.5 scenarios. We show that combined future changes in precipitation and potential evapotranspiration would significantly alter wetland hydrology including groundwater dynamics by the end of the 21st century. Compared to the historical period, all five wetlands are predicted to become drier over time. The mean water table depth is predicted to drop by 4 to 22 cm in response to the decrease in water availability (i.e., precipitation minus potential evapotranspiration) by the year 2100. Among the five examined wetlands, the depressional wetland in hot and humid Florida appears to be most vulnerable to future climate change. This study provides quantitative information on the potential magnitude of wetland hydrological response to future climate change in typical forested wetlands in the southeastern US.

show abstract

A process-based, distributed hydrologic model based on a large-scale method for surface–subsurface coupling

Cited by 182 publications

References 53 publications

Improving the representation of hydrologic processes in Earth System Models

Improving the representation of hydrologic processes in Earth System Models

Characterizing coarse-resolution watershed soil moisture heterogeneity using fine-scale simulations

Modeling the potential impacts of climate change on the water table level of selected forested wetlands in the southeastern United States

Contact Info

Product

Resources

About