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Vittucci, C.; Guerriero, L.; Ferrazzoli, P.; Rahmoune, R.; Barraza, V.; Grings, F. "River water level prediction using passive microwave signatures - A case study: The bermejo basin" (2014) IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 7(9):3903-3914
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Abstract:

The aim of this work is to investigate the exploitation of radiometric acquisitions from satellite sensors at different microwave frequencies in view of the prediction of river water level. A case study has been identified in the Bermejo basin, in northern Argentina. This river is seasonally affected by severe flooding events in the lower part, mostly due to rains occurring in the upper basin, that produce sediment loadings flushing down along the lower basin thus changing the watercourse. While the effectiveness of microwave radiometry at Ka band for flood monitoring is consolidated in the literature, this study also considers X and C bands (provided by the Advanced Microwave Scanning Radiometer (AMSR) series together with the higher frequency) and highlights the better sensitivity to soil conditions of L band data (made recently available, thanks to SMOS) over moderately and densely vegetated areas. This study confirms, first, the well-known capability of passive microwave remote sensing instruments to record brightness temperature variations due to rainfall and floods occurred near river edges under different seasonal conditions. For this purpose, a multifrequency comparative analysis is conducted. Second, it investigates whether these properties can be exploited for flood forecasting: a model which directly links the daily satellite measurements to the river water level has been tested, considering 1- to 7-day forecast horizons. The results show that forecasting models can take advantage of the sensitivity of low frequencies to soil moisture conditions in order to predict flood peaks, despite the instrument's low resolutions. © 2008-2012 IEEE.

Registro:

Documento: Artículo
Título:River water level prediction using passive microwave signatures - A case study: The bermejo basin
Autor:Vittucci, C.; Guerriero, L.; Ferrazzoli, P.; Rahmoune, R.; Barraza, V.; Grings, F.
Filiación:Dipartimento di Ingegneria Civile e Ingegneria Informatica (DICII), Tor Vergata University, Rome, 00133, Italy
Remote Sensing Group, Institute of Astronomy and Space Physics (IAFE), CABA, Buenos Aires, 1428, Argentina
Palabras clave:Flood; forecasting; hydrology; microwave radiometry; Forecasting; Hydrology; Microwave radiometry; Passive microwave signatures; River water; Floods; flood; flooding; forecasting method; microwave radiometer; prediction; river water; satellite sensor; soil moisture; water level; Argentina; Bermejo Basin
Año:2014
Volumen:7
Número:9
Página de inicio:3903
Página de fin:3914
DOI: http://dx.doi.org/10.1109/JSTARS.2014.2321457
Título revista:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Título revista abreviado:IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens.
ISSN:19391404
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_19391404_v7_n9_p3903_Vittucci

Referencias:

  • Madsen, H., Skotner, C., Adaptive state updating in real-time river flow forecasting: A combined filtering and error forecasting procedure (2005) J. Hydrol., 308 (1), pp. 302-312. , Jul
  • De Roo, A., Development of a European flood forecasting system (2003) Int. J. River Basin Manag., 1 (1), pp. 49-59. , Aug
  • Bartholmes, J., Todini, E., Coupling meteorological and hydrological models for flood forecasting (2005) Hydrol. Earth Syst. Sci., 9 (4), pp. 333-346. , Nov
  • Krzysztofowicz, R., Bayesian theory of probabilistic forecasting via deterministic hydrologic model (1999) Water Resour. Res., 35 (9), pp. 2739-2750. , Jul
  • Porporato, A., Ridolfi, L., Multivariate nonlinear prediction of river flows (2001) J. Hydrol., 248 (1), pp. 109-122. , Jul
  • Bruen, M., Yang, J., Functional networks in real-time flood forecasting a novel application (2005) Adv. Water Resour., 28 (9), pp. 899-909. , Sep
  • Todini, E., Role and treatment of uncertainty in real?time flood forecasting (2004) Hydrol. Processes, 18 (14), pp. 2743-2746. , Oct
  • Jacobs, J.M., Myers, D.A., Whitfield, B.M., Improved rainfall/runoff estimates using remotely sensed soil moisture (2003) J. Amer. Water Resour. Assoc., 39 (2), pp. 313-324. , Jun
  • Clark, M.P., Hydrological data assimilation with the ensemble Kalman filter: Use of streamflow observations to update states in a distributed hydrological model (2008) Adv. Water Resour., 31, pp. 1309-1324
  • Schumann, G., Bates, P.D., Horritt, M.S., Matgen, P., Pappenberger, F., Progress in integration of remote sensing derived flood extent and stage data and hydraulic models (2009) Rev. Geophys., 47 (4), 4001p. , Nov
  • Pauwels, V., Hoeben, R., Verhoest, N.E.C., De Troch, F.P., The importance of the spatial patterns of remotely sensed soil moisture in the improvement of discharge predictions for small-scale basins through data assimilation (2001) J. Hydrol., 251 (1), pp. 88-102. , Sep
  • Bates, P.D., Horritt, M.S., Smith, L.C., Mason, D.C., Integrating remote sensing observations of flood hydrology and hydraulic modeling (1997) Hydrol. Processes, 11 (14), pp. 1777-1795. , Nov
  • Henry, J.B., Chastanet, P., Fellah, K., Desnos, Y.L., ENVISAT multipolarised ASAR data for flood mapping (2006) Int. J. Remote Sens., 27, pp. 1921-1929
  • Hess, L.L., Melack, J.M., Novo, E.M.L.M., Barbosa, C.C.F., Gastil, M., Dual-season mapping of wetland inundation and vegetation for the central Amazon basin (2003) Remote Sens. Environ., 87, pp. 404-428
  • Horritt, M.S., Mason, D.C., Luckman, A.J., Flood boundary delineation from synthetic aperture radar imagery using a statistical active contour model (2001) Int. J. Remote Sens., 22, pp. 2489-2507
  • Schumann, G., Di Baldassarre, G., Bates, P.D., The utility of spaceborne radar to render flood inundation maps based on multialgorithm ensembles (2009) IEEE Trans. Geosci. Remote Sens., 50 (7), pp. 2801-2807. , Aug
  • Pulvirenti, L., Chini, M., Pierdicca, N., Guerriero, L., Ferrazzoli, P., Flood monitoring using multi-temporal COSMO-SkyMed data: Image segmentation and signature interpretation (2011) Remote Sens. Environ., 115 (4), pp. 990-1002. , Apr
  • Pulvirenti, L., Pierdicca, N., Chini, M., Guerriero, L., Monitoring flood evolution in vegetated areas using COSMO-SkyMed data: The Tuscany 2009 case study (2013) IEEE J. Sel. Topics Appl. Observ. Remote Sens., 6 (4), pp. 1807-1816. , Aug
  • Bjerklie, D.M., Moller, D., Smith, L.C., Dingman, S.L., Estimating discharge in rivers using remotely sensed hydraulic information (2005) J. Hydrol., 309, pp. 191-209
  • Alsdorf, D.E., Rodriguez, E., Lettenmaier, D.P., Measuring surface water from space (2007) Rev. Geophys., 45 (2), pp. 1-24. , Jun
  • Brakenridge, G.R., Nghiem, S.V., Anderson, E., Mic, R., Orbital microwave measurements of river discharge and ice status (2007) Water Resour. Res., 43, 16p. , W04405
  • Kugler, Z., Degroeve, T., The global flood detection system (2007) JRC Sci. Tech. Rep. JRC 44149
  • Brakenridge, G.R., Calibration of satellite measurements of river discharge using a global hydrology model (2012) J. Hydrol., 475, pp. 123-136
  • Khan, S.I., Microwave satellite data for hydrological modeling in ungauged basins (2012) IEEE Geosci. Remote Sens. Lett., 9 (4), pp. 663-667. , Jul
  • Hirpa, F.A., Upstream satellite remote sensing for river discharge forecasting: Application to major rivers in South Asia (2013) Remote Sens. Environ., 113, pp. 140-151
  • Bindlish, R., Crow, W.T., Jackson, T.J., Role of passive microwave remote sensing in improving flood forecasts (2009) IEEE Geosci. Remote Sens. Lett., 6 (1), pp. 112-116. , Jan
  • Brea, J., Busquets, M., Spalletti, P., Análisis de la dinámica fluviomorfológica del río Bermejo Inferior (1999) Informe LHA, pp. 178-202
  • Morello, J., Adámoli, J., Las grandes unidades de vegetación y ambiente del Chaco argentine. Segunda Parte: Vegetación y ambiente de la Provincia del Chaco (1974) INTA Ser. Fitogeográfica, 13, 130p
  • Kawanishi, T., The advanced microwave scanning radiometer for the earth observing system (AMSR-E), NASDA's contribution to the EOS for global energy and water cycle studies (2003) IEEE Trans. Geosci. Remote Sens., 41 (2), pp. 184-194. , Feb
  • Nakagawa, K., GCOM-W and GCOM-C project status (2010) Proc. IEEE Int. Geosci. Remote Sens. Symp. (IGARSS'10), Jul., pp. 1355-1358
  • De Jeu, R.A.M., Global soil moisture patterns observed by space borne microwave radiometers and scatterometers (2008) Surveys Geophys., 29 (4-5), pp. 399-420. , Oct
  • Fily, M., Royer, A., Goita, K., Prigent, C., A simple retrieval method for land surface temperature and fraction of water surface determination from satellite microwave brightness temperatures in sub-arctic areas (2003) Remote Sens. Environ., 85 (3), pp. 328-338. , May
  • Parinussa, R.M., Holmes, T.R.H., De Jeu, R.A.M., Soil moisture retrievals from the WindSat spaceborne polarimetric microwave radiometer (2012) IEEE Trans. Geosci. Remote Sens., 50 (7), pp. 2683-2694. , Jul
  • Kerr, Y.H., The SMOS soil moisture retrieval algorithm (2012) IEEE Trans. Geosci. Remote Sens., 50 (5), pp. 1384-1403. , May
  • Kerr, Y.H., Soil moisture retrieval from space: The Soil Moisture and Ocean Salinity (SMOS) mission (2001) IEEE Trans. Geosci. Remote Sens., 39 (8), pp. 1729-1735. , Aug
  • Vittucci, C., Study of multifrequency sensitivity to soil moisture variations in the lower Bermejo basin (2013) Eur. J. Remote Sens., 46, pp. 775-788
  • Saleh, K., Estimates of surface soil moisture under grass covers using L-band radiometry (2007) Remote Sens. Environ., 109 (1), pp. 42-53. , Jul
  • Dur, M., The surface water and ocean topography mission: Observing terrestrial surface water and oceanic submesoscale eddies (2010) Proc. IEEE, 98 (5), pp. 766-779. , May
  • Haykin, S., (1991) Adaptive Filter Theory, , Englewood Cliffs NJ USA Prentice Hall
  • Farhang-Boroujeny, B., (1998) Adaptive Filters: Theory and Applications, , Hoboken NJ USA Wiley

Citas:

---------- APA ----------
Vittucci, C., Guerriero, L., Ferrazzoli, P., Rahmoune, R., Barraza, V. & Grings, F. (2014) . River water level prediction using passive microwave signatures - A case study: The bermejo basin. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(9), 3903-3914.
http://dx.doi.org/10.1109/JSTARS.2014.2321457
---------- CHICAGO ----------
Vittucci, C., Guerriero, L., Ferrazzoli, P., Rahmoune, R., Barraza, V., Grings, F. "River water level prediction using passive microwave signatures - A case study: The bermejo basin" . IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 7, no. 9 (2014) : 3903-3914.
http://dx.doi.org/10.1109/JSTARS.2014.2321457
---------- MLA ----------
Vittucci, C., Guerriero, L., Ferrazzoli, P., Rahmoune, R., Barraza, V., Grings, F. "River water level prediction using passive microwave signatures - A case study: The bermejo basin" . IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 9, 2014, pp. 3903-3914.
http://dx.doi.org/10.1109/JSTARS.2014.2321457
---------- VANCOUVER ----------
Vittucci, C., Guerriero, L., Ferrazzoli, P., Rahmoune, R., Barraza, V., Grings, F. River water level prediction using passive microwave signatures - A case study: The bermejo basin. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2014;7(9):3903-3914.
http://dx.doi.org/10.1109/JSTARS.2014.2321457