Editorial Type:
Article
Article Type:
Research Article

Calibration and Validation of a Distributed Energy–Water Balance Model Using Satellite Data of Land Surface Temperature and Ground Discharge Measurements

Chiara Corbari Department of Civil and Environmental Engineering, Politecnico di Milano, Milan, Italy

Search for other papers by Chiara Corbari in
Current site
Google Scholar
PubMed Close
and
Marco Mancini Department of Civil and Environmental Engineering, Politecnico di Milano, Milan, Italy

Search for other papers by Marco Mancini in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Feb 2014
Collections:
The Catchment-scale Hydrological Modeling & Data Assimilation (CAHMDA-V)
DOI:
https://doi.org/10.1175/JHM-D-12-0173.1
Page(s):
376–392
Restricted access

Abstract

Distributed hydrological models of energy and mass balance need as inputs many soil and vegetation parameters, which are usually difficult to define. This paper will try to approach this problem by performing a pixel to pixel calibration procedure of soil hydraulic and vegetation parameters based on satellite land surface temperature data as a complementary method to the traditional calibration with ground discharge measurements at river control cross sections. These analyses are performed for the upper Po River basin (Italy) closed at the river cross section of Ponte della Becca with a total catchment area of about 38 000 km2, for a calibration period from 2000 to 2003, and a validation period from 2004 to 2010. Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature data and a distributed hydrological model, Flash-Flood Event-Based Spatially Distributed Rainfall-Runoff Transformation Energy Water Balance model (FEST-EWB), that solves the system of energy and mass balance equations as a function of the representative equilibrium temperature will be used. This equilibrium surface temperature is comparable to the land surface temperature as retrieved from operational remote sensing data. Results suggest that a combined calibration based on satellite land surface temperature and ground discharge is needed to correctly reproduce volume discharge and also spatially distributed maps of representative equilibrium temperature and evapotranspiration. Improvements of about 10 mm/8 days are obtained on evapotranspiration from the model calibrated with Q and land surface temperature (LST) respect to the calibration based only on discharge.

Corresponding author address: Chiara Corbari, Department of Civil and Environmental Engineering, Politecnico di Milano, Piazza Leonardo da Vinci, 32, Milan 20132, Italy. E-mail: chiara.corbari@polimi.it

This article is included in the The Catchment-scale Hydrological Modeling & Data Assimilation (CAHMD-V) special collection.

Abstract

Distributed hydrological models of energy and mass balance need as inputs many soil and vegetation parameters, which are usually difficult to define. This paper will try to approach this problem by performing a pixel to pixel calibration procedure of soil hydraulic and vegetation parameters based on satellite land surface temperature data as a complementary method to the traditional calibration with ground discharge measurements at river control cross sections. These analyses are performed for the upper Po River basin (Italy) closed at the river cross section of Ponte della Becca with a total catchment area of about 38 000 km2, for a calibration period from 2000 to 2003, and a validation period from 2004 to 2010. Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature data and a distributed hydrological model, Flash-Flood Event-Based Spatially Distributed Rainfall-Runoff Transformation Energy Water Balance model (FEST-EWB), that solves the system of energy and mass balance equations as a function of the representative equilibrium temperature will be used. This equilibrium surface temperature is comparable to the land surface temperature as retrieved from operational remote sensing data. Results suggest that a combined calibration based on satellite land surface temperature and ground discharge is needed to correctly reproduce volume discharge and also spatially distributed maps of representative equilibrium temperature and evapotranspiration. Improvements of about 10 mm/8 days are obtained on evapotranspiration from the model calibrated with Q and land surface temperature (LST) respect to the calibration based only on discharge.

Corresponding author address: Chiara Corbari, Department of Civil and Environmental Engineering, Politecnico di Milano, Piazza Leonardo da Vinci, 32, Milan 20132, Italy. E-mail: chiara.corbari@polimi.it

This article is included in the The Catchment-scale Hydrological Modeling & Data Assimilation (CAHMD-V) special collection.

Save
Cover Journal of Hydrometeorology
Journal of Hydrometeorology

  • Anderson, M. C., Norman J. M. , Diak G. R. , Kustas W. P. , and Mecikalski J. R. , 1997: A two-source time-integrated model for estimating surface fluxes using thermal infrared remote sensing. Remote Sens. Environ., 60, 195–216, doi:10.1016/S0034-4257(96)00215-5.

    • Search Google Scholar
    • Export Citation

  • Anderson, M. C., Morse A. , and Kustas W. P. , 2012: Use of Landsat thermal imagery in monitoring evapotranspiration and managing water resources. Remote Sens. Environ., 122, 50–65, doi:10.1016/j.rse.2011.08.025.

    • Search Google Scholar
    • Export Citation

  • Bastiaanssen, W. G. M., Menenti M. , Feddes R. A. , and Holtslag A. A. M. , 1998: A remote sensing surface energy balance algorithm for land (SEBAL). 1. Formulation. J. Hydrol., 212–213, 198–212, doi:10.1016/S0022-1694(98)00253-4.

    • Search Google Scholar
    • Export Citation

  • Beven, K. J., 2006: A manifesto for the equifinality thesis. J. Hydrol., 320, 18–36.

  • Beven, K. J., and Binley A. , 1992: The future of distributed models: Model calibration and uncertainty prediction. Hydrol. Processes, 6, 279–298, doi:10.1002/hyp.3360060305.

    • Search Google Scholar
    • Export Citation

  • Brath, A., Montanari A. , and Toth E. , 2004: Analysis of the effects of different scenarios of historical data availability on the calibration of a spatially-distributed hydrological model. J. Hydrol., 291 (3–4), 232–253, doi:10.1016/j.jhydrol.2003.12.044.

    • Search Google Scholar
    • Export Citation

  • Cammalleri, C., Ciraolo G. , La Loggia G. , and Maltese A. , 2012: Daily evapotranspiration assessment by means of residual surface energy balance modeling: A critical analysis under a wide range of water availability. J. Hydrol., 452–453, 119–129, doi:10.1016/j.jhydrol.2012.05.042.

    • Search Google Scholar
    • Export Citation

  • Caparrini, F., Castelli F. , and Entekhabi D. , 2004: Estimation of surface turbulent fluxes through assimilation of radiometric surface temperature sequences. J. Hydrometeor., 5, 145–159, doi:10.1175/1525-7541(2004)005<0145:EOSTFT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Castillo, V. M., Gomez-Plaza A. , and Martinez-Mena M. , 2003: The role of antecedent soil water content in the runoff response of semiarid catchments: A simulation approach. J. Hydrol., 284 (1–4), 114–130, doi:10.1016/S0022-1694(03)00264-6.

    • Search Google Scholar
    • Export Citation

  • Corbari, C., Ravazzani G. , Martinelli J. , and Mancini M. , 2009: Elevation based correction of snow coverage retrieved from satellite images to improve model calibration. Hydrol. Earth Syst. Sci., 13, 639–649, doi:10.5194/hess-13-639-2009.

    • Search Google Scholar
    • Export Citation

  • Corbari, C., Sobrino J. A. , Mancini M. , and Hidalgo V. , 2010: Land surface temperature representativeness in a heterogeneous area through a distributed energy-water balance model and remote sensing data. Hydrol. Earth Syst. Sci., 14, 2141–2151, doi:10.5194/hess-14-2141-2010.

    • Search Google Scholar
    • Export Citation

  • Corbari, C., Ravazzani G. , and Mancini M. , 2011: A distributed thermodynamic model for energy and mass balance computation: FEST-EWB. Hydrol. Processes, 25, 1443–1452, doi:10.1002/hyp.7910.

    • Search Google Scholar
    • Export Citation

  • Corbari, C., Sobrino J. A. , Mancini M. , and Hidalgo V. , 2013: Mass and energy flux estimates at different spatial resolutions in a heterogeneous area through a distributed energy–water balance model and remote-sensing data. Int. J. Remote Sens., 34 (9–10), 3208–3230, doi:10.1080/01431161.2012.716924.

    • Search Google Scholar
    • Export Citation

  • Crow, W. T., and Wood E. F. , 2003: The assimilation of remotely sensed soil brightness temperature imagery into a land surface model using Ensemble Kalman filtering: A case study based on ESTAR measurements during SGP97. Adv. Water Resour., 26, 137–149, doi:10.1016/S0309-1708(02)00088-X.

    • Search Google Scholar
    • Export Citation

  • Crow, W. T., Wood E. F. , and Pan M. , 2003: Multiobjective calibration of land surface model evapotranspiration predictions using streamflow observations and spaceborne surface radiometric temperature retrievals. J. Geophys. Res., 108, 4725, doi:10.1029/2002JD003292.

    • Search Google Scholar
    • Export Citation

  • Crow, W. T., Kustas W. P. , and Prueger J. H. , 2008: Monitoring root-zone soil moisture through the assimilation of a thermal remote sensing-based soil moisture proxy into a water balance model. Remote Sens. Environ., 112, 1268–1281, doi:10.1016/j.rse.2006.11.033.

    • Search Google Scholar
    • Export Citation

  • Di Baldassarre, G., and Montanari A. , 2009: Uncertainty in river discharge observations: A quantitative analysis. Hydrol. Earth Syst. Sci., 13, 913–921, doi:10.5194/hess-13-913-2009.

    • Search Google Scholar
    • Export Citation

  • Dooge, J. C. I., 1986: Looking for hydrologic laws. Water Resour. Res., 22, 46S–58S, doi:10.1029/WR022i09Sp0046S.

  • Famiglietti, J. S., and Wood E. F. , 1994: Multiscale modelling of spatially variable water and energy balance processes. Water Resour. Res., 30, 3061–3078, doi:10.1029/94WR01498.

    • Search Google Scholar
    • Export Citation

  • Fawcett, K. R., Anderson M. G. , Bates P. D. , Jordan J.-P. , and Bathhurst J. C. , 1995: The importance of internal validation in the assessment of physically based distributed models. Trans. Inst. Brit. Geogr., 20, 248–265 , doi:10.2307/622435.

    • Search Google Scholar
    • Export Citation

  • Franks, S. W., and Beven K. J. , 1999: Conditioning a multiple patch SVAT model using uncertain space–time estimates of surface fluxes as inferred from remotely sensed data. Water Resour. Res., 35, 2751–2761, doi:10.1029/1999WR900108.

    • Search Google Scholar
    • Export Citation

  • Franks, S. W., Beven K. J. , Quinn P. F. , and Wright I. R. , 1997: On the sensitivity of soil-vegetation-atmosphere transfer (SVAT) schemes: Equifinality and the problem of robust calibration. Agric. For. Meteor., 86 (1–2), 63–75.

    • Search Google Scholar
    • Export Citation

  • Galleguillos, M., Jacob F. , Prévot L. , French A. , and Lagacherie P. , 2011: Comparison of two temperature differencing methods to estimate daily evapotranspiration over a Mediterranean vineyard watershed from ASTER data. Remote Sens. Environ., 115, 1326–1340, doi:10.1016/j.rse.2011.01.013.

    • Search Google Scholar
    • Export Citation

  • Gupta, H. V., Bastidas L. A. , Sorooshian S. , Shuttleworth W. J. , and Yang Z. L. , 1999: Parameter estimation of a land surface scheme using multicriteria methods. J. Geophys. Res., 104 (D16), 19 491–19 503, doi:10.1029/1999JD900154.

    • Search Google Scholar
    • Export Citation

  • Gutmann, E. D., and Small E. E. , 2010: A method for the determination of the hydraulic properties of soil from MODIS surface temperature for use in land surface models. Water Resour. Res., 46, W06520, doi:10.1029/2009WR008203.

    • Search Google Scholar
    • Export Citation

  • Hain, C. R., Mecikalski J. R. , and Anderson M. C. , 2009: Retrieval of an available water-based soil moisture proxy from thermal infrared remote sensing. Part I: Methodology and validation. J. Hydrometeor., 10, 665–683, doi:10.1175/2008JHM1024.1.

    • Search Google Scholar
    • Export Citation

  • Immerzeel, W. W., and Droogers P. , 2008: Calibration of a distributed hydrological model based on satellite evapotranspiration. J. Hydrol., 349, 411–424, doi:10.1016/j.jhydrol.2007.11.017.

    • Search Google Scholar
    • Export Citation

  • Jacob, F., Petitcolin F. , Schmugge T. , Vermote E. , French A. , and Ogawa K. , 2004: Comparison of land surface emissivity and radiometric temperature derived from MODIS and ASTER sensors. Remote Sens. Environ., 90, 137–152, doi:10.1016/j.rse.2003.11.015.

    • Search Google Scholar
    • Export Citation

  • Jarvis, P. G., 1976: The interpretation of the variations in leaf water potential and stomatal conductance found in canopies in the field. Philos. Trans. Roy. Soc., B273, 593–610.

    • Search Google Scholar
    • Export Citation

  • Jia, L., and Coauthors, 2003: Estimation of sensible heat flux using the Surface Energy Balance System (SEBS) and ATSR measurements. Phys. Chem. Earth, 28, 75–88, doi:10.1016/S1474-7065(03)00009-3.

    • Search Google Scholar
    • Export Citation

  • Kalma, J. D., McVicar T. R. , and McCabe M. F. , 2008: Estimating land surface evaporation: A review of methods using remotely sensed surface temperature data. Surv. Geophys., 29, 421–469, doi:10.1007/s10712-008-9037-z.

    • Search Google Scholar
    • Export Citation

  • Kustas, W. P., Li F. , Jackson T. J. , Pruger J. H. , MacPherson J. I. , and Wolden M. , 2004: Effects of remote sensing pixel resolution on modeled energy flux variability of croplands in Iowa. Remote Sens. Environ., 92, 535–547, doi:10.1016/j.rse.2004.02.020.

    • Search Google Scholar
    • Export Citation

  • Mancini, M., 1990: La modellazione distribuita della risposta idrologica: Effetti della variabilità spaziale e della scala di rappresentazione del fenomeno dell'assorbimento. Ph.D. dissertation, Politecnico di Milano, 127 pp.

  • Masseroni, D., Ravazzani G. , Corbari C. , and Mancini M. , 2012: Turbulence integral length and footprint dimension with reference to experimental data measured over maize cultivation in Po Valley, Italy. Atmósfera, 25, 183–198.

    • Search Google Scholar
    • Export Citation

  • Minacapilli, M., and Coauthors, 2009: Estimation of actual evapotranspiration of Mediterranean perennial crops by means of remote-sensing based surface energy balance models. Hydrol. Earth Syst. Sci., 13, 1061–1074, doi:10.5194/hess-13-1061-2009.

    • Search Google Scholar
    • Export Citation

  • Montaldo, N., Ravazzani G. , and Mancini M. , 2007: On the prediction of the Toce alpine basin floods with distributed hydrologic models. Hydrol. Processes, 21, 608–621, doi:10.1002/hyp.6260.

    • Search Google Scholar
    • Export Citation

  • Mu, Q., Zhao M. , and Running S. W. , 2011: Improvements to a MODIS global terrestrial evapotranspiration algorithm. Remote Sens. Environ., 115, 1781–1800, doi:10.1016/j.rse.2011.02.019.

    • Search Google Scholar
    • Export Citation

  • Myneni, R. B., and Coauthors, 2002: Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data. Remote Sens. Environ., 83, 214–231, doi:10.1016/S0034-4257(02)00074-3.

    • Search Google Scholar
    • Export Citation

  • Nash, J. E., and Sutcliffe J. V. , 1970: River flow forecasting through the conceptual models part I—A discussion of principles. J. Hydrol., 10, 282–290, doi:10.1016/0022-1694(70)90255-6.

    • Search Google Scholar
    • Export Citation

  • Noilhan, J., and Planton S. , 1989: A simple parameterization of land surface processes for meteorological models. Mon. Wea. Rev., 117, 536–549, doi:10.1175/1520-0493(1989)117<0536:ASPOLS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Norman, J. M., Kustas W. P. , and Humes K. S. , 1995: Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature. Agric. For. Meteor., 77, 263–293, doi:10.1016/0168-1923(95)02265-Y.

    • Search Google Scholar
    • Export Citation

  • Overgaard, J., Rosbjerg D. , and Butts M. B. , 2006: Land-surface modelling in hydrological perspective—A review. Biogeosciences, 3, 229–241, doi:10.5194/bg-3-229-2006.

    • Search Google Scholar
    • Export Citation

  • Pan, M., Wood E. F. , Wójcik R. , and McCabe M. F. , 2008: Estimation of regional terrestrial water cycle using multi-sensor remote sensing observations and data assimilation. Remote Sens. Environ., 112, 1282–1294, doi:10.1016/j.rse.2007.02.039.

    • Search Google Scholar
    • Export Citation

  • Pelletier, M. P., 1988: Uncertainties in the determination of river discharge: A literature review. Can. J. Civ. Eng., 15, 834–850, doi:10.1139/l88-109.

    • Search Google Scholar
    • Export Citation

  • Pianosi, F., and Ravazzani G. , 2010: Assessing rainfall-runoff models for the management of Lake Verbano. Hydrol. Processes, 24, 3195–3205, doi:10.1002/hyp.7745.

    • Search Google Scholar
    • Export Citation

  • Rabuffetti, D., Ravazzani G. , Corbari C. , and Mancini M. , 2008: Verification of operational Quantitative Discharge Forecast (QDF) for a regional warning system—The AMPHORE case studies in the upper Po River. Nat. Hazards Earth Syst. Sci., 8, 161–173, doi:10.5194/nhess-8-161-2008.

    • Search Google Scholar
    • Export Citation

  • Ravazzani, G., Mancini M. , Giudici I. , and Amadio P. , 2007: Effects of soil moisture parameterization on a real-time flood forecasting system based on rainfall thresholds. Quantification and Reduction of Predictive Uncertainty for Sustainable Water Resources Management, E. Boegh et al., Eds., IAHS Publ. 313, 407–416.

  • Ravazzani, G., Rametta D. , and Mancini M. , 2011: Macroscopic cellular automata for groundwater modelling: A first approach. Environ. Modell. Software, 26, 634–643, doi:10.1016/j.envsoft.2010.11.011.

    • Search Google Scholar
    • Export Citation

  • Rawls, W. J., and Brakensiek D. L. , 1985: Prediction of Soil water properties for hydrologic modelling. Watershed Management in the Eighties, ASCE, 293–299.

  • Refsgaard, J. C., 1997: Parameterisation, calibration and validation of distributed hydrological models. J. Hydrol., 198, 69–97, doi:10.1016/S0022-1694(96)03329-X.

    • Search Google Scholar
    • Export Citation

  • Refsgaard, J. C., and Knudsen J. , 1996: Operational validation and intercomparison of different types of hydrological models. Water Resour. Res., 32, 2189–2202, doi:10.1029/96WR00896.

    • Search Google Scholar
    • Export Citation

  • Roerink, G. J., Su Z. , and Menenti M. , 2000: S-SEBI: A simple remote sensing algorithm to estimate the surface energy balance. Phys. Chem. Earth, 25B, 147–157, doi:10.1016/S1464-1909(99)00128-8.

    • Search Google Scholar
    • Export Citation

  • Rosso, R., 1994: An introduction to spatially distributed modeling of basin response. Advances in Distributed Hydrology, R. Rosso et al., Eds., Water Resources Publications, 3–30.

  • Sobrino, J. A., Li Z. L. , Stoll M. P. , and Becker F. , 1994: Improvements in the split-window technique for land surface temperature determination. IEEE Geosci. Remote Sens. Lett., 32, 243–253, doi:10.1109/36.295038.

    • Search Google Scholar
    • Export Citation

  • Soria, G., and Sobrino J. A. , 2007: ENVISAT/AATSR derived land surface temperature over a heterogeneous region. Remote Sens. Environ., 111, 409–422, doi:10.1016/j.rse.2007.03.017.

    • Search Google Scholar
    • Export Citation

  • Su, Z., 2002: The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes. Hydrol. Earth Syst. Sci., 6, 85–100, doi:10.5194/hess-6-85-2002.

    • Search Google Scholar
    • Export Citation

  • Sun, S. F., 1982: Moisture and heat transport in a soil layer forced by atmospheric conditions. M.S. thesis, Dept. of Civil Engineering, University of Connecticut, 72 pp.

  • Thom, A. S., 1975: Momentum, mass and heat exchange of plant communities. Vegetation and Atmosphere, J. L. Monteith, Ed., Academic Press, 57–110.

  • Timmermans, W. J., and Coauthors, 2011: Estimation of the spatially distributed surface energy budget for AgriSAR 2006, part I: Remote sensing model intercomparison. IEEE J. Sel. Top. Appl. Earth. Obs. Remote Sens., 4, 465–481.

    • Search Google Scholar
    • Export Citation

  • Verstraeten, W. W., Veroustraete F. , and Feyen J. , 2008: Assessment of evapotranspiration and soil moisture content across different scales of observation. Sensors, 8, 70–117, doi:10.3390/s8010070.

    • Search Google Scholar
    • Export Citation

  • Wang, W., Liang S. , and Meyers T. , 2008: Validating MODIS land surface temperature products using long-term nighttime ground measurements. Remote Sens. Environ., 112, 623–635, doi:10.1016/j.rse.2007.05.024.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 6663 5261 1519
PDF Downloads 946 155 9