Skip to main content

Application of Remote Sensing For Hydrological Modelling

  • Chapter
Distributed Hydrological Modelling

Part of the book series: Water Science and Technology Library ((WSTL,volume 22))

Abstract

It has long been recognised that the results obtained by hydrological modelling of a river basin depend heavily on the quality of the input data used. The main problem in many hydrological studies is that there are not enough adequate data to describe quantitatively hydrological processes with sufficient accuracy. Studies on hydrological effects of land use and climate changes in large river basins are possible only if detailed information about topography, geology, soil, vegetation, and climate are available. With the advances of remote sensing techniques hydrological relevant information about large river basins can be derived from different sensors. A major problem facing the user of these data is how to effectively incorporate remotely sensed data into hydrological studies and models (Peck et al. , 1981; Rango, 1987; Schultz, 1988; Engman and Gurney, 1991).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Altese, E., Bolognani, O., Mancini, M. and Troch, P.A. (1995) Retrieving soil moisture over bare soil from ERS-1 SAR data, a sensitivity analysis based on a theoretical surface scattering model and field data, Water Resources Research, in press.

    Google Scholar 

  • Attema, E.P.W. and Ulaby, F.T. (1978) Vegetation modeled as a water cloud, Radio Science 13(2) 357–364.

    Article  Google Scholar 

  • Bahar, E. (1985) Scattering by anisotropic models of composite rough surface, full wave solution, IEEE Trans. Antenna Propagation 33, 106–112.

    Article  Google Scholar 

  • Barrett, E.C. (1993) Precipitation measurements by satellites: Towards community algorithms, Adv. Space Res. 13,5119–5136.

    Google Scholar 

  • Beckman, P. and Spizzichino, A. (1963) The Scattering of Electromagnetic Waves From Rough Surfaces, Macmillan Inc., New York.

    Google Scholar 

  • Beven, K. (1986) Runoff production and flood frequency in catchments of order n: An alternative approach, In V.K. Gupta (ed.), Scale Problems in Hydrology, D. Reidel, Norwell, Mass., pp. 107–131.

    Google Scholar 

  • Brown, G.S. (1978) Backscattering from a Gaussian distributed perfectly conducting rough surface, IEEE Trans. Antenna Propagation 26, 472–482.

    Article  Google Scholar 

  • Browning, K.A. and Collier, C.G. (1989) Nowcasting of precipitation series, Rev. Geophysics 27(3) 345–370.

    Article  Google Scholar 

  • Chang, A.T.C., Foster, J.L., Rango, A. and Joseberger, E.G. (1991) The use of microwave radiometry for characterizing snow storage in large river basins, IAHS Publ. 205, 73–80.

    Google Scholar 

  • Colliage, V. and Kirby, C. (1987) Weather Radar and Flood Forecasting, John Wiley and Sons, Chichester.

    Google Scholar 

  • Colwell, R.N. (ed.) (1983) Manual of Remote Sensing, 2nd ed., American Society of Photogrammetry, Fall Church.

    Google Scholar 

  • Dornier (1993) Erderkundungs-Daten-Service: Landsat 6 Informationen, Dornier GmbH.

    Google Scholar 

  • Engheta, N. and Elachi, C. (1982) Radar scattering from a diffuse vegetation layer over a smooth surface, IEEE Trans. Geosci. Remote Sens. 20, 212–216.

    Article  Google Scholar 

  • Engman, E.T. (1990) Progress in microwave remote sensing of soil moisture, Can. Journ. of Remote Sens. 16(3) 6–13.

    Google Scholar 

  • Engman, E.T. and Gurney, R.J. (1991) Remote Sensing in Hydrology, Chapman and Hill, London.

    Google Scholar 

  • Famiglietti, J.S. and Wood, E.F. (1994) Multiscale modeling of spatially water and energy balance components, Water Resources Research 30(11) 3061–3078.

    Article  Google Scholar 

  • Feddes, R.A., Menenti, M., Kabat, P. and Bastiaanssen, W.G.M. (1993) Is large scale inverse modelling of unsaturated flow with areal average evaporation and surface soil moisture as estimated from remote sensing feasible? J. Hydrol 143, 125–152.

    Article  Google Scholar 

  • Fung, A.K., Li, Z. and Chen, K.S.(1992) Backscattering from a randomly rough dielectric surface, IEEE Trans. Geosci. Remote Sens. 30, 356–369.

    Article  Google Scholar 

  • Fung, A.K. and Pan, G.W.(1987) A scattering model for perfectly conducting random surfaces, I, Model development, Int. J. Remote Sensing 8, 1579–1593.

    Article  Google Scholar 

  • Giacomelli, A., Bacchiega, U., Troch, P.A. and Mancini M.(1995) Evaluation of surface soil moisture distribution by means of SAR remote sensing techniques and conceptual hydrological modelling, J. Hydrol 166,445–459.

    Article  Google Scholar 

  • Hollenbeck, K.J., Schmugge, T.J., Homberger, G.M and Wang, J.R. (1996) Identifying soil hydraulic heterogeneity by detection of relative change in passive microwave remote sensing observations, Water Resources Research 32(1), 139–148.

    Article  Google Scholar 

  • Jackson, T.J. (1993) Measuring surface soil moisture using passive microwave remote sensing, Hydrological Processes 7(2) 139–152.

    Article  Google Scholar 

  • Klatt, P. and Schultz, G.A. (1983) Flood forecasting on the basis of radar rainfall measurements and rainfall forecasting, in Hydrological Applications of Remote Sensing and Remote Data Transmission, IAHS Publ. no. 145, 307–315.

    Google Scholar 

  • Kouwen, N., Soulis, E.D., Pietroniro, A., Donald, J. and Harrington, R.A. (1993) Grouped response units for distributed hydrologic modeling, J. Water Res. Planning and Management 119 (3) 289–305.

    Article  Google Scholar 

  • Leader, J.C.(1978) Incoherent backscatter from rough surfaces, The two scale model re-examined, Radio Science 13, 441–457.

    Article  Google Scholar 

  • Le Toan, T., Smacchia, P., Souyris, J.C., Beaudoin, A., Merdas, M., Wooding, M. and Lichteneger, J. (1994) On the retrieval of soil moisture from ERS-1 SAR data, Proc. Second ERS-1 Symposium: Space at the Service of our Environment, ESA SP-361, 883–888.

    Google Scholar 

  • Lin, D.S., Wood, E.F., Saatchi, S. and Beven, K. (1993) Soil moisture estimation during MAC-EUROPE’91 using AIRSAR, Proc. 25th Intern. Symp. Remote Sensing and Global Environ. Change, 1-172, Graz.

    Google Scholar 

  • Mancini, M, Rosso, R., Lin, D.S., Wood, E.F. and Troch, P.A. (1993) AIRSAR capability in soil moisture content for different climate scenarios, Proc. 25th Intern. Symp. Remote Sensing and Global Environ. Change, 1-185, Graz.

    Google Scholar 

  • Martinec, J. and Rango, A. (1991) Indirect evaluation of snow reserves in mountain basins, IAHS Pub I. no. 205, 111–119.

    Google Scholar 

  • Menenti, M. (1983) A new geophysical approach using remote sensing techniques to study groundwater table depths and regional evaporation from aquifers in deserts, ICW report 9, Wageningen.

    Google Scholar 

  • Mo, T., Schmugge, T.J. and Jackson, T.J. (1984) Calculations of radar backscattering coefficient of vegetation covered soils, Remote Sens. Env. 15, 119–133.

    Article  Google Scholar 

  • Newton, R.W., Black, Q.R., Makanvand, S., Blanchard, A.J. and Jean, B.R. (1982) Soil moisture information and thermal microwave emission, IEEE Trans. Geosci. Remote Sens. 20, 275–281.

    Article  Google Scholar 

  • Nieuwenhuis, Q.J.A. (1986) Integration of remote sensing with a water balance simulation model (SWATRE), ICW Techn. Bulletin 59, Wageningen.

    Google Scholar 

  • Njoku, E.G. and O’Neill, P.E. (1982) Multifrequency microwave radiometer measurements of soil moisture, IEEE Trans. Geosci. Remote Sens. 20, 468–475.

    Article  Google Scholar 

  • Oh, Y., Sarabandi, K. and Ulaby, F.T.(1992) An empirical model and an inversion technique for radar scattering from bare soil surfaces, IEEE Trans. Geosci. and Remote Sensing 30(2) 370–381.

    Article  Google Scholar 

  • Ottle, C. and Vidal-Madjar, D. (1994) Assimilation of soil moisture inferred from infrared remote sensing in a hydrological model over the HAPEX-MOBELHY region, J. Hydrol. 158,241–264.

    Article  Google Scholar 

  • Peck, E.L., Keefer, T.N. and Johnson, E.R. (1981) Strategies for using remotely sensed data in hydrologic models, NASA-CR-66729.

    Google Scholar 

  • Pultz, T.J., Leconte, R., Brown, R.J. and Brisco, B. (1990) Quantitative soil moisture extraction from airborne SAR data, Canad. J. Remote Sens. 16, 56–62.

    Google Scholar 

  • Ragab, R. (1995) Towards a continuous operational system to estimate the root-zone soil moisture from intermittent remotely sensed surface moisture, J. Hydrol 173, 1–25.

    Article  Google Scholar 

  • Rango, A.(1987) New technology for hydrological data acquisition and applications, IAHS Pub I. No. 164,511–511.

    Google Scholar 

  • Rango, A.(1993) Snow hydrology processes and remote sensing, Hydrological Processes 7, 121–138.

    Article  Google Scholar 

  • Richards, J.A., Sun, G.Q. and Simonett, D.S. (1987) L-band radar backscatter modelling of forest stands, IEEE Trans. Geosci. Remote Sens. 23, 487–498.

    Article  Google Scholar 

  • Sancer, M.I. (1969) Shadow-corrected electromagnetic scattering from a randomly rough surface, IEEE Trans. Antenna Propagation 17, 577–589.

    Article  Google Scholar 

  • Schmugge, T.J. (1985) Remote sensing of soil moisture, In MG. Anderson and T.P. Burt (eds.), Hydrological Forecasting, John Wiley and Sons, Chichester, pp. 101–124.

    Google Scholar 

  • Schmugge, T.J., Jackson, T.J., Kustas, W.P. and Wang, J.R. (1992) Passive microwave remote sensing of soil moisture: Results from HAPEX, FIFE and MONSOONO, J. Photogrammetry Remote Sens.

    Google Scholar 

  • Schultz, G.A. (1988) Remote sensing in hydrology, J. Hydrol 100, 239–265.

    Article  Google Scholar 

  • Seguin, B., Savane, M. and Guillot, B. (1990) Estimation of large area evaporation from thermal infrared meteorological satellite data: A case study with Meteosat and NOAA for France, Proc. Int. Symp. Remote Sensing and Water Resources, Enschede, 215-228.

    Google Scholar 

  • Su, Z., Neumann, P., Fett, W., Schumann, A.S. and Schultz, G.A. (1992) Application of remote sensing and geographic information systems in hydrological modelling, EAR SeL Adv. Remote Sensing 1(3) 180–185.

    Google Scholar 

  • Su, Z. and Schultz, G.A. (1993) A distributed runoff prediction model developed on the basis of remotely sensed information, Proc. EARSeL Specialist Meeting, Dundee, 50-64.

    Google Scholar 

  • Su, Z., TrochJP.A. and De Troch, F.P. (1996) Remote sensing of soil moisture using EMAC/ESAR data, Int. J. Remote Sensing, submitted.

    Google Scholar 

  • Troch, P.A., De Troch, F.P. and Brutsaert, W.(1993a) Effective water table depth to describe initial conditions prior to storm rainfall in humid regions, Water Resources Research 29(2) 427–434.

    Article  Google Scholar 

  • Troch, P.A., Mancini, M., Paniconi, C. and Wood, E.F.(1993b) Evaluation of a distributed catchment scale water balance model. Water Resources Research 29(6) 1805–1818.

    Article  Google Scholar 

  • Ulaby, F.T., Batlivala, P.P. and Dobson, M.C. (1978) Microwave backscatter dependence on surface roughness, soil moisture, and soil texture: Part I, Bare soil, IEEE Trans. Geosci. Remote Sens. 16, 286–295.

    Google Scholar 

  • Ulaby, F.T., Bradley, G.A. and Dobson, M.C. (1979) Microwave backscatter dependence on surface roughness, soil moisture, and soil texture: Part II, Vegetation covered soil, IEEE Trans. Geosci. Remote Sens. 17, 33–40.

    Google Scholar 

  • Ulaby, F.T., Aslam, A. and Dobson, M.C. (1982) Effect of vegetation cover on radar sensitivity to soil moisture, IEEE Trans. Geosci. Remote Sens. 20, 476–481.

    Article  Google Scholar 

  • Ulaby, F.T., Allen, C.T. and Eger, G. (1984) Relating the microwave backscattering coefficient to leaf area index, Remote Sensing Environ. 14, 113–133.

    Article  Google Scholar 

  • Ulaby, F.T., Moore, R.K. and Fung, A.K. (1986) Microwave remote sensing: Active and passive, vol. Ill, From theory to applications, Arctech House, Inc., Dedham, MA.

    Google Scholar 

  • Valenzuela, G.R.(1967) Depolarization of EM waves by slightly rough surfaces, IEEE Trans. Antenna Propagation 15, 552–557

    Article  Google Scholar 

  • Wang, J.R., O’Neill, P.E., Jackson, T.J. and Engman, E.T. (1983) Multifrequency measurements of the effect of soil moisture, soil texture and surface roughness, IEEE Trans. Geosci. Remote Sens. 21, 44–51.

    Article  Google Scholar 

  • Winebemer, D. and Ishimara, A. (1985) Investigation of a surface field phase perturbation technique for scattering from rough surfaces, Radio Sci. 20, 161–170.

    Article  Google Scholar 

  • Wood, E.F., Lin, D.S., Mancini, M., Thongs, D., Troch, P., Famiglietti, J. and Jackson, T.J. (1993) Intercomparison betw een passive and active microwave remote sensing and hydrological modelling for soil moisture, Adv. Space Res. 13(5) 167–176.

    Article  Google Scholar 

  • Wood, E.F., Sivapalan, M., Beven, K. and Band, L. (1988) Effects of spatial variability and scale with implications to hydrological modeling, J. Hydrol. 102, 29–47.

    Article  Google Scholar 

  • Wright, J.W.(1968) A new model for sea clutter, IEEE Trans. Antenna Propagation 16, 217–223.

    Article  Google Scholar 

  • Wu, S.T. and Fung, A.K. (1972) A noncoherent model for microwave emission backscattering from the sea surface, J. Geophys. Res. 77, 5917–5929.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1990 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

De Troch, F.P., Troch, P.A., Su, Z., Lin, D.S. (1990). Application of Remote Sensing For Hydrological Modelling. In: Abbott, M.B., Refsgaard, J.C. (eds) Distributed Hydrological Modelling. Water Science and Technology Library, vol 22. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-0257-2_9

Download citation

  • DOI: https://doi.org/10.1007/978-94-009-0257-2_9

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-6599-3

  • Online ISBN: 978-94-009-0257-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics