Improving a land surface scheme for estimating sensible and latent heat fluxes above grasslands with contrasting soil moisture zones

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.

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Multi-objective calibration of the land surface scheme TERRA/LM using LITFASS-2003 data

Hydrology and Earth System Sciences ◽

10.5194/hess-9-586-2005 ◽

2005 ◽

Vol 9 (6) ◽

pp. 586-596 ◽

Cited By ~ 6

Author(s):

K.-P. Johnsen ◽

H.-T. Mengelkamp ◽

S. Huneke

Keyword(s):

Heat Flux ◽

Latent Heat ◽

Land Surface ◽

Vegetation Type ◽

Sensible Heat Flux ◽

Heat Fluxes ◽

Land Surface Scheme ◽

Multi Objective ◽

Long Term Study ◽

Surface Scheme

Abstract. The turbulent sensible and latent heat fluxes simulated in the operational weather forecast model LM have been checked with data from the field experiment LITFASS 2003 (Lindenberg Inhomogeneous Terrain - Fluxes between Atmosphere and Surface: a Long-term Study) using both single site measurements and grid box aggregated fluxes. SCE-UA (single objective) and MOSCEM-UA (multi-objective) approaches were applied to calibrate the land-surface scheme TERRA/LM for 11 single sites and for the aggregated fluxes. A large variation is seen among the parameter sets found by calibration but no typical classification according to vegetation type is obvious. This is attributed to the calibrated parameter sets correcting for model deficiencies and data errors rather than describing the physical characteristics of the measurement site. The measured fluxes were combined into a time series of aggregated fluxes by the tile method. Calibration of TERRA/LM with respect to the averaged fluxes resulted in a range of parameter sets which all simulated the area-averaged fluxes in much better agreement with the observed fluxes than the standard parameter set of the operational model. A modified Nash-Sutcliffe measure as a coincidence criterion fell from 0.3 to a range between 0.15 and 0.28 for the latent heat flux and from 0.43 to between 0.26 and 0.36 for the sensible heat flux when the calibrated parameter sets were used instead of the standard parameters.

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An EKF assimilation of AMSR-E soil moisture into the ISBA land surface scheme

Journal of Geophysical Research Atmospheres ◽

10.1029/2008jd011650 ◽

2009 ◽

Vol 114 (D20) ◽

Cited By ~ 93

Author(s):

C. S. Draper ◽

J.-F. Mahfouf ◽

J. P. Walker

Keyword(s):

Soil Moisture ◽

Land Surface ◽

Land Surface Scheme ◽

Surface Scheme

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Influence of Land Cover and Soil Moisture on the Horizontal Distribution of Sensible and Latent Heat Fluxes in Southeast Kansas during IHOP_2002 and CASES-97

Journal of Hydrometeorology ◽

10.1175/jhm554.1 ◽

2007 ◽

Vol 8 (1) ◽

pp. 68-87 ◽

Cited By ~ 71

Author(s):

Margaret A. LeMone ◽

Fei Chen ◽

Joseph G. Alfieri ◽

Mukul Tewari ◽

Bart Geerts ◽

...

Keyword(s):

Soil Moisture ◽

Latent Heat ◽

Land Surface ◽

Field Experiments ◽

Time Of Day ◽

Horizontal Distribution ◽

Heat Fluxes ◽

Surface Model ◽

Green Vegetation ◽

The Impact

Abstract Analyses of daytime fair-weather aircraft and surface-flux tower data from the May–June 2002 International H2O Project (IHOP_2002) and the April–May 1997 Cooperative Atmosphere Surface Exchange Study (CASES-97) are used to document the role of vegetation, soil moisture, and terrain in determining the horizontal variability of latent heat LE and sensible heat H along a 46-km flight track in southeast Kansas. Combining the two field experiments clearly reveals the strong influence of vegetation cover, with H maxima over sparse/dormant vegetation, and H minima over green vegetation; and, to a lesser extent, LE maxima over green vegetation, and LE minima over sparse/dormant vegetation. If the small number of cases is producing the correct trend, other effects of vegetation and the impact of soil moisture emerge through examining the slope ΔxyLE/ΔxyH for the best-fit straight line for plots of time-averaged LE as a function of time-averaged H over the area. Based on the surface energy balance, H + LE = Rnet − Gsfc, where Rnet is the net radiation and Gsfc is the flux into the soil; Rnet − Gsfc ∼ constant over the area implies an approximately −1 slope. Right after rainfall, H and LE vary too little horizontally to define a slope. After sufficient drying to produce enough horizontal variation to define a slope, a steep (∼−2) slope emerges. The slope becomes shallower and better defined with time as H and LE horizontal variability increases. Similarly, the slope becomes more negative with moister soils. In addition, the slope can change with time of day due to phase differences in H and LE. These trends are based on land surface model (LSM) runs and observations collected under nearly clear skies; the vegetation is unstressed for the days examined. LSM runs suggest terrain may also play a role, but observational support is weak.

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The Effect of Soil and Vegetation Parameters in the ECMWF Land Surface Scheme

Journal of Hydrometeorology ◽

10.1175/jhm-362.1 ◽

2004 ◽

Vol 5 (6) ◽

pp. 1131-1146 ◽

Cited By ~ 21

Author(s):

H. Richter ◽

A. W. Western ◽

F. H. S. Chiew

Keyword(s):

Soil Moisture ◽

Land Surface ◽

Weather Prediction ◽

Lower Boundary ◽

Soil Parameters ◽

Model Parameters ◽

Lower Boundary Condition ◽

Land Surface Scheme ◽

Vegetation Parameters ◽

Surface Scheme

Abstract Numerical Weather Prediction (NWP) and climate models are sensitive to evapotranspiration at the land surface. This sensitivity requires the prediction of realistic surface moisture and heat fluxes by land surface models that provide the lower boundary condition for the atmospheric models. This paper compares simulations of a stand-alone version of the European Centre for Medium-Range Weather Forecasts (ECMWF) land surface scheme, or the Viterbo and Beljaars scheme (VB95), with various soil and vegetation parameter sets against soil moisture observations across the Murrumbidgee River catchment in southeast Australia. The study is, in part, motivated by the adoption of VB95 as the operational land surface scheme by the Australian Bureau of Meteorology in 1999. VB95 can model the temporal fluctuations in soil moisture, and therefore the moisture fluxes, fairly realistically. The monthly model latent heat flux is also fairly insensitive to soil or vegetation parameters. The VB95 soil moisture is sensitive to the soil and, to a lesser degree, the vegetation parameters. The model exhibits a significant (generally wet) bias in the absolute soil moisture that varies spatially. The use of the best Australia-wide available soils and vegetation information did not improve VB95 simulations consistently, compared with the original model parameters. Comparisons of model and observed soil moistures revealed that more realistic soil parameters are needed to reduce the model soil moisture bias. Given currently available continent-wide soils parameters, any initialization of soil moisture with observed values would likely result in significant flux errors. The soil moisture bias could be largely eliminated by using soil parameters that were derived directly from the actual soil moisture observations. Such parameters, however, are only available at very few point locations.

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Comparative Analysis of High-Resolution Soil Moisture Simulations from the Soil, Vegetation, and Snow (SVS) Land Surface Model Using SAR Imagery Over Bare Soil

Water ◽

10.3390/w11030542 ◽

2019 ◽

Vol 11 (3) ◽

pp. 542 ◽

Cited By ~ 3

Author(s):

Mohammed Dabboor ◽

Leqiang Sun ◽

Marco Carrera ◽

Matthew Friesen ◽

Amine Merzouki ◽

...

Keyword(s):

Soil Moisture ◽

High Resolution ◽

Soil Texture ◽

Land Surface ◽

Goodness Of Fit ◽

Retrieval Algorithm ◽

Surface Model ◽

Land Surface Scheme ◽

Sar Imagery ◽

Surface Scheme

Soil moisture is a key variable in Earth systems, controlling the exchange of water andenergy between land and atmosphere. Thus, understanding its spatiotemporal distribution andvariability is important. Environment and Climate Change Canada (ECCC) has developed a newland surface parameterization, named the Soil, Vegetation, and Snow (SVS) scheme. The SVS landsurface scheme features sophisticated parameterizations of hydrological processes, including watertransport through the soil. It has been shown to provide more accurate simulations of the temporaland spatial distribution of soil moisture compared to the current operational land surface scheme.Simulation of high resolution soil moisture at the field scale remains a challenge. In this study, wesimulate soil moisture maps at a spatial resolution of 100 m using the SVS land surface scheme overan experimental site located in Manitoba, Canada. Hourly high resolution soil moisture maps wereproduced between May and November 2015. Simulated soil moisture values were compared withestimated soil moisture values using a hybrid retrieval algorithm developed at Agriculture andAgri-Food Canada (AAFC) for soil moisture estimation using RADARSAT-2 Synthetic ApertureRadar (SAR) imagery. Statistical analysis of the results showed an overall promising performanceof the SVS land surface scheme in simulating soil moisture values at high resolution scale.Investigation of the SVS output was conducted both independently of the soil texture, and as afunction of the soil texture. The SVS model tends to perform slightly better over coarser texturedsoils (sandy loam, fine sand) than finer textured soils (clays). Correlation values of the simulatedSVS soil moisture and the retrieved SAR soil moisture lie between 0.753–0.860 over sand and 0.676-0.865 over clay, with goodness of fit values between 0.567–0.739 and 0.457–0.748, respectively. TheRoot Mean Square Difference (RMSD) values range between 0.058–0.062 over sand and 0.055–0.113over clay, with a maximum absolute bias of 0.049 and 0.094 over sand and clay, respectively. Theunbiased RMSD values lie between 0.038–0.057 over sand and 0.039–0.064 over clay. Furthermore,results show an Index of Agreement (IA) between the simulated and the derived soil moisturealways higher than 0.90.

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