scholarly journals Constraining water table depth simulations in a land surface model using estimated baseflow

2008 ◽  
Vol 31 (12) ◽  
pp. 1552-1564 ◽  
Author(s):  
Min-Hui Lo ◽  
Pat J.-F. Yeh ◽  
J.S. Famiglietti
Keyword(s):  
Water Table ◽  
Land Surface ◽  
Land Surface Model ◽  
Water Table Depth ◽  
Surface Model

Evaluation of modelled methane emissions over high-latitude wetlands

2020 ◽  
Author(s):  
Yao Gao ◽  
Eleanor Burke ◽  
Sarah Chadburn ◽  
Maarit Raivonen ◽  
Timo Vesala ◽  
...  
Keyword(s):  
Soil Respiration ◽  
Soil Carbon ◽  
Water Table ◽  
High Latitude ◽  
Land Surface ◽  
Water Table Depth ◽  
Surface Model ◽  
Emission Model ◽  
Earth System ◽  
Positive Feedbacks

<p>Atmospheric emissions and concentrations of CH<sub>4</sub> are continuing to increase, making CH<sub>4</sub> the second most important human-influenced greenhouse gas in terms of climate forcing, after CO<sub>2</sub>. Previous studies indicated that wetland CH<sub>4</sub> emission is not only the single largest but also the most uncertain natural source in the global CH<sub>4</sub> budget. Furthermore, the strong sensitivity of wetland CH<sub>4</sub> emissions to environmental conditions has raised concerns on potential positive feedbacks to climate change. Therefore, evaluation of the process-based land surface models of earth system models (ESMs) in simulating CH<sub>4</sub> emission over wetlands is needed for more precise future predictions. In this work, a set of high-latitude wetland sites with various nutrient conditions are studied. The wetland CH<sub>4</sub> fluxes are simulated by the land surface model JULES of the UK Earth System model and the Helsinki peatland methane emission model (HIMMELI), which is developed at Finnish Meteorological Institute and Helsinki University. The differences between the modelled and observed CH<sub>4</sub> fluxes are analyzed, complemented with key environmental variables for interpretation (e.g. soil temperature and moisture, vegetation types, snow depth, NPP, soil carbon). In general, the simulated CH<sub>4</sub> fluxes by HIMMELI is closer to the observed CH<sub>4</sub> fluxes in magnitude and seasonality at sites than those by JULES. The inter-annual variability of simulated CH<sub>4</sub> fluxes by HIMMELI depends on the simulated anoxic soil respiration, which serves as the substrate of the CH<sub>4</sub> fluxes in HIMMELI. The anoxic soil respiration is calculated based on the simulated soil respiration and water table depth in JULES. More accurate simulation of soil carbon pool and water table depth in JULES will lead to improvement in the simulated anoxic soil respiration.</p>

scholarly journals Development of a Coupled Land Surface Hydrologic Model and Evaluation at a Critical Zone Observatory

2013 ◽  
Vol 14 (5) ◽  
pp. 1401-1420 ◽  
Author(s):  
Yuning Shi ◽  
Kenneth J. Davis ◽  
Christopher J. Duffy ◽  
Xuan Yu
Keyword(s):  
Latent Heat ◽  
Water Table ◽  
Land Surface ◽  
Hydrologic Model ◽  
Heat Fluxes ◽  
Water Table Depth ◽  
Surface Model ◽  
Land Surface Scheme ◽  
Model Predictions ◽  
Surface Scheme

Abstract A fully coupled land surface hydrologic model, Flux-PIHM, is developed by incorporating a land surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Because PIHM is capable of simulating lateral water flow and deep groundwater at spatial resolutions sufficient to resolve upland stream networks, Flux-PIHM is able to represent heterogeneities due to topography and soils at high resolution, including spatial structure in the link between groundwater and the surface energy balance (SEB). Flux-PIHM has been implemented at the Shale Hills watershed (0.08 km2) in central Pennsylvania. Multistate observations of discharge, water table depth, soil moisture, soil temperature, and sensible and latent heat fluxes in June and July 2009 are used to manually calibrate Flux-PIHM at hourly temporal resolution. Model predictions from 1 March to 1 December 2009 are evaluated. Both hydrologic predictions and SEB predictions show good agreement with observations. Comparisons of model predictions between Flux-PIHM and the original PIHM show that the inclusion of the complex SEB simulation only brings slight improvement in hourly model discharge predictions. Flux-PIHM adds the ability of simulating SEB to PIHM and does improve the prediction of hourly evapotranspiration, the prediction of total runoff (discharge), and the predictions of some peak discharge events, especially after extended dry periods. Model results reveal that annual average sensible and latent heat fluxes are strongly correlated with water table depth, and the correlation is especially strong for the model grids near the stream.

scholarly journals Ensemble Evaluation of Hydrologically Enhanced Noah-LSM: Partitioning of the Water Balance in High-Resolution Simulations over the Little Washita River Experimental Watershed

2011 ◽  
Vol 12 (1) ◽  
pp. 45-64 ◽  
Author(s):  
Enrique Rosero ◽  
Lindsey E. Gulden ◽  
Zong-Liang Yang ◽  
Luis G. De Goncalves ◽  
Guo-Yue Niu ◽  
...  
Keyword(s):  
Water Table ◽  
Land Surface ◽  
Water Cycle ◽  
Land Surface Model ◽  
Surface Model ◽  
Model Parameters ◽  
Shallow Water Table ◽  
Total Runoff ◽  
Physically Based ◽  
Subsurface Runoff

Abstract The ability of two versions of the Noah land surface model (LSM) to simulate the water cycle of the Little Washita River experimental watershed is evaluated. One version that uses the standard hydrological parameterizations of Noah 2.7 (STD) is compared another version that replaces STD’s subsurface hydrology with a simple aquifer model and topography-related surface and subsurface runoff parameterizations (GW). Simulations on a distributed grid at fine resolution are compared to the long-term distribution of observed daily-mean runoff, the spatial statistics of observed soil moisture, and locally observed latent heat flux. The evaluation targets the typical behavior of ensembles of models that use realistic, near-optimal sets of parameters important to runoff. STD and GW overestimate the ratio of runoff to evapotranspiration. In the subset of STD and GW runs that best reproduce the timing and the volume of streamflow, the surface-to-subsurface runoff ratio is overestimated and simulated streamflow is much flashier than observations. Both models’ soil columns wet and dry too quickly, implying that there are structural shortcomings in the formulation of STD that cannot be overcome by adding GW’s increased complexity to the model. In its current formulation, GW extremely underestimates baseflow’s contribution to total runoff and requires a shallow water table to function realistically. In the catchment (depth to water table >10 m), GW functions as a simple bucket model. Because model parameters are likely scale and site dependent, the need for even “physically based” models to be extensively calibrated for all domains on which they are applied is underscored.

scholarly journals ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO<sub>2</sub>, water and energy fluxes on daily to annual scales

2017 ◽  
Author(s):  
Chunjing Qiu ◽  
Dan Zhu ◽  
Philippe Ciais ◽  
Bertrand Guenet ◽  
Gerhard Krinner ◽  
...  
Keyword(s):  
Water Table ◽  
Land Surface ◽  
Peat Soil ◽  
Model Performance ◽  
Land Surface Model ◽  
Grid Cell ◽  
Co2 Exchange ◽  
Heat Fluxes ◽  
Surface Model ◽  
Energy Fluxes

Abstract. Peatlands store substantial amount of carbon, are vulnerable to climate change. To predict the fate of carbon stored in peatlands, the complex interactions between water, peat and vegetations need more attention. This study describes a modified version of the ORCHIDEE land surface model for simulating the hydrology, surface energy and CO2 fluxes of peatlands on daily to annual time scales. The model, referred to as ORCHIDEE-PEAT, includes a separate soil tile in each 0.5° grid-cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation with a grid-cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model is evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (Vcmax) being optimized at each site to match the peak of growing season gross primary productivity (GPP), derived from direct EC measurements. Regarding short-term variations from day to day, the model performance was good for the variations in GPP (r2 = 0.76, Nash-Sutcliff modeling efficiency, MEF = 0.76), with lesser accuracy for latent heat fluxes (LE, r2 = 0.42, MEF = 0.14) and Net ecosystem CO2 exchange (NEE, r2 = 0.38, MEF = 0.26). Seasonal variations in GPP, NEE and energy fluxes on monthly scales showed moderate to high r2 values ranging from 0.57 to 0.86. For spatial across-sites gradients of annual mean GPP, NEE and LE, r2 of 0.93, 0.27, and 0.71, respectively, were achieved. The water table variations are not well predicted (r2 < 0.1), likely due to the uncertain water input to the peat from surrounding areas. However, when using the observed water table in the carbon module to define the fraction of oxic and anoxic decomposition instead of the modeled water table, ORCHIDEE-PEAT shows a small improvement in reproducing NEE. Moreover, we found a significant relationship between optimized Vcmax and the latitude (temperature), which can better reflect the spatial gradients of annual NEE than using an average Vcmax value. In a future version of ORCHIDEE-PEAT, the influences of water table on photosynthesis and depth-dependent influences of soil temperature on respiration may be included.

L'apport de la télédétection spatiale à la modélisation des surfaces continentales

2020 ◽  
pp. 052
Author(s):  
Jean-Christophe Calvet ◽  
Jean-Louis Champeaux
Keyword(s):  
Satellite Data ◽  
Land Surface ◽  
Land Surface Model ◽  
Static Model ◽  
Geographic Information ◽  
Surface Model ◽  
Model Parameters

Cet article présente les différentes étapes des développements réalisés au CNRM des années 1990 à nos jours pour spatialiser à diverses échelles les simulations du modèle Isba des surfaces terrestres. Une attention particulière est portée sur l'intégration, dans le modèle, de données satellitaires permettant de caractériser la végétation. Deux façons complémentaires d'introduire de l'information géographique dans Isba sont présentées : cartographie de paramètres statiques et intégration au fil de l'eau dans le modèle de variables observables depuis l'espace. This paper presents successive steps in developments made at CNRM from the 1990s to the present-day in order to spatialize the simulations of the Isba land surface model at various scales. The focus is on the integration in the model of satellite data informative about vegetation. Two complementary ways to integrate geographic information in Isba are presented: mapping of static model parameters and sequential assimilation of variables observable from space.

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