Intercomparison
1
Ageel I. Bushara 1 , Riccardo Rigon 1 , Thomas Over 2 , Mekonnen Gebremichael 3 1 Department of civil and Environmental Engineering, University of Trento, Italy, 2 Department of Geology/Geography, Eastern Illinois University, USA, 3 Department of civil and environmental engineering, University of Connecticut, USA Intercomparison between model and ESTAR soil moistures during the Southern Great Plain Hydrology Experiments-1997 and 1999 Acknowledgments The fund from the University of Trento for the first author during this research is greatly acknowledged. Also thanks to GEOtop (www.geotop.org ) and JGRASS ( www.jgrass.org ) communities for their help and comments. Conclusions Model shows soil moisture is controlled by soil texture Immediately after rain ESTAR shows high soil moistures and is higher than the modeled soil moistures. The over estimation of ESTAR during wet days are not mainly due to the effects of vegetation, topography and roughness. Therefore, we hypothesized that ESTAR is significantly contaminated by surface runoff and intercepted rain. After the surface runoff drains out, EASTAR and GEOtop soil moistures are comparable. Due to uncertainties in ESTAR soil moisture, different assimilation methods might be needed. Goals The purpose of this work is to evaluate the ESTAR soil moisture products using the intensive ground-based field data collected during the Southern Great Plain hydrology Experiments-1997 (SGP97) and SGP99 field campaigns at the Little Washita basin (611km 2 ), Oklahoma, USA . The physically based distributed hydrological model, GEOtop (Rigon et al. (2006), J.Hydrometeor) will be used to evaluate ESTAR soil moisture products. The model has to well reproduce the heat fluxes (latent heat, sensible heat, ground heat and net radiation), soil temperature profiles at different locations in the basin, soil moisture profiles at different locations in the basin, and discharge at the basin outlet, for both calibration and validation periods. SGP97 dataset will be used for model calibration while SGP99 dataset will be used for model validation. The measured volumetric soil moistures and the measured gravimetric soil moistures will be used for model calibration and validation, respectively. Once the model is capable of reproducing the water and energy budgets at basin scale for both the calibration and validation periods, the Introduction ESTAR soil moistures are widely used in earth system science and have wide range of applications e.g. Regional scale hydrologic or general circulation models (GCM). In spite of its wide use, there are still high degree of uncertainties inherited in ESTAR, and limited studies have focused on evaluating, quantifying and addressing ESTAR uncertainties.Crosson et al.(2005) reported that uncertainties in ESTAR are related to surface roughness and absorption, scattering and emission by vegetation. Ulaby et al. (1983) reported that microwave brightness temperature (ESTAR inverting brightness temperature to volumetric soil moistures) strongly depends on temperature depth profile of the soil, and concluded that the presence of vegetation cover might pose a serious problem for soil moisture detection with passive microwave sensors such as ESTAR. Drusch et al.(2001) reported that variations in integrated atmospheric water vapour only could cause variations in passive microwave remote sensing soil moistures up to 36%. Therefore, in order to use ESTAR with confidence for wide range of applications, it is important to carefully evaluate ESTAR. A powerful tool to evaluate the ESTAR by using physically based distributed hydrological models that have the ability to simulate continuous, high resolution, soil moisture fields. However, distributed hydrological models requires huge amount of data at both temporal and spatial scales. If this huge amount of data become available, it would be great opportunity to calibrate and validate the physically based distributed hydrological models, and then the models could be used to validate ESTAR soil moistures. Method GEOtop model solves Richards equation [Richards, 931, J. Physics] in three dimensions for evolution of water content and pressure coupled with one dimensional solution of soil heat transport. GEOtop model accommodates very complex topography and integrates also all the terms of the surface energy equation. In this study, the model is driven by meteorological forcings taken at an hourly time step from 45 stations. Each station measures precipitation, relative humidity, air temperature, downward solar radiation, wind speed, wind direction and air pressure. The model is initialized for soil moisture profiles, soil temperature profiles, soil thermal properties and soil hydraulic profiles and for land use properties. The model was ran once at basin scale and reproduced the water and energy budgets. The GEOtop model was well calibrated and validated for SGP97 and SGP99 experiments, respectively, and it well reproduced the heat fluxes (sensible heat, latent heat, net radiation and ground heat fluxes), soil temperature profiles, soil moisture profiles and discharge at outlet. The soil moisture maps at desirable times [at the same time of ESTAR measurements] were printed and compared to ESTAR maps. The effects of topography, vegetation and surface runoff on ESTAR were investigated in a fixed soil type (this study and previous studies found that soil moisture is mainly controlled by soil texture) by considering soil moistures in only: concave and convex pixels, bare soil pixels, and channel network and non-channel network pixels, respectively. Surface runoff depth and vegetation intercepted water maps are printed at the same time of ESTAR measurements to see whereas the differences between model and ESTAR soil moistures increase or decrease when the surface runoff depth and intercepted water depth changed. Results Soil type map and experimenta l sites in which GEOtop model is calibrated and validated Hydrological network [45 stations, about 5 km a part], used for forcing GEOtop LW22 LW23 LW08 LW09 LW11 LW02 LW06 LW04 LW21 LW05 LW14 LW12 LW13 Measured (red) and modelled (blue) net radiation (left) and ground heat flux (right) at LW02-NOAA site (see network map). Sensible and latent heat fluxes were also well reproduced by the model but are not shown here Measured (red) and modelled (blue) soil temperatures, left at 10cm depth, right at 20cm depth from ground surface at LW02-NOAA site. Soil temperatures at 5cm and 60cm are well reproduced by the model but are not shown here Measured (red) and modelled (blue) soil moistures at different depths from the ground surface at LW02-NOAA site. LW03 LW13 LW21 Measured (site_1 to site_4) and modelled (model_1 to model_4, shown with thick lines) soil moistures for the top 5cm soil layer at LW03, LW13, and LW21 experimental sites (see the soil type map and experimental sites figure). [- ] [-] [-] Measured and modelled discharge at outlet and the total precipitation [-] July 3 July 11 July 12 July 13 Volumetric soil moisture maps, GEOtop (left) and ESTAR (right) Soil moisture content for all soil type 8 (Silt loam) Soil moisture content for soil type 8 in bare soil landuse only Soil moisture content for soil type 8 for only channel pixels Soil moisture content for soil type 8 for only non- channel pixels Soil moisture content for soil type 8 for only concave pixels Soil moisture content for soil type 8 for only concave pixels July 11 July 3 July 13 July 12
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Transcript of Intercomparison
Ageel I. Bushara1, Riccardo Rigon1, Thomas Over2, Mekonnen Gebremichael3 1Department of civil and Environmental Engineering, University of Trento, Italy, 2Department of Geology/Geography, Eastern Illinois University, USA,3Department of civil and environmental engineering, University of Connecticut, USA
Intercomparison between model and ESTAR soil moistures during the Southern Great Plain Hydrology Experiments-1997 and 1999
Acknowledgments
The fund from the University of Trento for the first author during this research is greatly acknowledged. Also thanks to GEOtop (www.geotop.org) and JGRASS (www.jgrass.org) communities for their help and comments.
Conclusions
Model shows soil moisture is controlled by soil textureImmediately after rain ESTAR shows high soil moistures and is higher than the modeled soil moistures.The over estimation of ESTAR during wet days are not mainly due to the effects of vegetation, topography and roughness. Therefore, we hypothesized that ESTAR is significantly contaminated by surface runoff and intercepted rain. After the surface runoff drains out, EASTAR and GEOtop soil moistures are comparable.Due to uncertainties in ESTAR soil moisture, different assimilation methods might be needed.
Goals The purpose of this work is to evaluate the ESTAR soil moisture products using the intensive ground-based field data collected during the Southern Great Plain hydrology Experiments-1997 (SGP97) and SGP99 field campaigns at the Little Washita basin (611km2), Oklahoma, USA . The physically based distributed hydrological model, GEOtop (Rigon et al. (2006), J.Hydrometeor) will be used to evaluate ESTAR soil moisture products.The model has to well reproduce the heat fluxes (latent heat, sensible heat, ground heat and net radiation), soil temperature profiles at different locations in the basin, soil moisture profiles at different locations in the basin, and discharge at the basin outlet, for both calibration and validation periods. SGP97 dataset will be used for model calibration while SGP99 dataset will be used for model validation. The measured volumetric soil moistures and the measured gravimetric soil moistures will be used for model calibration and validation, respectively. Once the model is capable of reproducing the water and energy budgets at basin scale for both the calibration and validation periods, the model performance could be trusted, and then the model could be used to evaluate the ESTAR soil moisture products.
Introduction ESTAR soil moistures are widely used in earth system science and have wide range of applications e.g. Regional scale hydrologic or general circulation models (GCM). In spite of its wide use, there are still high degree of uncertainties inherited in ESTAR, and limited studies have focused on evaluating, quantifying and addressing ESTAR uncertainties.Crosson et al.(2005) reported that uncertainties in ESTAR are related to surface roughness and absorption, scattering and emission by vegetation. Ulaby et al. (1983) reported that microwave brightness temperature (ESTAR inverting brightness temperature to volumetric soil moistures) strongly depends on temperature depth profile of the soil, and concluded that the presence of vegetation cover might pose a serious problem for soil moisture detection with passive microwave sensors such as ESTAR. Drusch et al.(2001) reported that variations in integrated atmospheric water vapour only could cause variations in passive microwave remote sensing soil moistures up to 36%. Therefore, in order to use ESTAR with confidence for wide range of applications, it is important to carefully evaluate ESTAR. A powerful tool to evaluate the ESTAR by using physically based distributed hydrological models that have the ability to simulate continuous, high resolution, soil moisture fields. However, distributed hydrological models requires huge amount of data at both temporal and spatial scales. If this huge amount of data become available, it would be great opportunity to calibrate and validate the physically based distributed hydrological models, and then the models could be used to validate ESTAR soil moistures.
Method
GEOtop model solves Richards equation [Richards, 931, J. Physics] in three dimensions for evolution of water content and pressure coupled with one dimensional solution of soil heat transport. GEOtop model accommodates very complex topography and integrates also all the terms of the surface energy equation.
In this study, the model is driven by meteorological
forcings taken at an hourly time step from 45 stations. Each station measures precipitation, relative humidity, air temperature, downward solar radiation, wind speed, wind direction and air pressure. The model is initialized for soil moisture profiles, soil temperature profiles, soil thermal properties and soil hydraulic profiles and for land use properties. The model was ran once at basin scale and reproduced the water and energy budgets.
The GEOtop model was well calibrated and validated for SGP97 and SGP99 experiments, respectively, and it well reproduced the heat fluxes (sensible heat, latent heat, net radiation and ground heat fluxes), soil temperature profiles, soil moisture profiles and discharge at outlet. The soil moisture maps at desirable times [at the same time of ESTAR measurements] were printed and compared to ESTAR maps.
The effects of topography, vegetation and surface runoff on ESTAR were investigated in a fixed soil type (this study and previous studies found that soil moisture is mainly controlled by soil texture) by considering soil moistures in only: concave and convex pixels, bare soil pixels, and channel network and non-channel network pixels, respectively.
Surface runoff depth and vegetation intercepted water maps are printed at the same time of ESTAR measurements to see whereas the differences between model and ESTAR soil moistures increase or decrease when the surface runoff depth and intercepted water depth changed.
Results
Soil type map and experimental sites in which GEOtop model is calibrated and validated
Hydrological network [45 stations, about 5 km a part], used for forcing GEOtop
LW22 LW23
LW08
LW09
LW11
LW02LW06
LW04
LW21
LW05
LW14 LW12
LW13
Measured (red) and modelled (blue) net radiation (left) and ground heat flux (right) at LW02-NOAA site (see network map). Sensible and latent heat fluxes were also well reproduced by the model but are not shown here
Measured (red) and modelled (blue) soil temperatures, left at 10cm depth, right at 20cm depth from ground surface at LW02-NOAA site. Soil temperatures at 5cm and 60cm are well reproduced by the model but are not shown here
Measured (red) and modelled (blue) soil moistures at different depths from the ground surface at LW02-NOAA site.
LW03 LW13
LW21 Measured (site_1 to site_4) and modelled (model_1 to model_4, shown with thick lines) soil moistures for the top 5cm soil layer at LW03, LW13, and LW21 experimental sites (see the soil type map and experimental sites figure).
[-]
[-]
[-]
Measured and modelled discharge at outlet and the total precipitation
[-]
July 3
July 11
July 12
July 13
Volumetric soil moisture
maps, GEOtop (left) and ESTAR
(right)
Soil moisture content for all soil type 8 (Silt loam)
Soil moisture content for soil type 8 in bare soil landuse only
Soil moisture content for soil type 8 for only channel pixels
Soil moisture content for soil type 8 for only non-channel pixels
Soil moisture content for soil type 8 for only concave pixels
Soil moisture content for soil type 8 for only concave pixels
July 11
July 3
July 13
July 12
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