Potential of SAR-Derived Flood Maps for Hydrodynamic Model Calibration in Data Scarce Regions
Publication: Journal of Hydrologic Engineering
Volume 25, Issue 9
Abstract
Synthetic aperture radar (SAR) observations of real world flood extents are often the only source of information in data scarce catchments and the only reliable resource for channels with subkilometer widths. Accordingly, this study aimed at evaluating the reliability of SAR-based flood maps for flood model performance assessment for an extremely data poor region in India. SAR images were converted to probabilistic flood maps by combining inundation extents obtained using visual interpretation, histogram thresholding, and texture-based classification. Flood extents simulated by a hydrodynamic model were compared with SAR-derived inundation extents using spatial objective functions to calibrate the lumped channel and floodplain friction parameters. The agreement between the modeled and observed flood extents showed an value of 0.938 and a root mean squared error of 0.278 pixels for the validation. The results indicate that the proposed method has the potential to support flood model calibration and evaluation in ungauged basins.
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References
Aronica, G., P. D. Bates, and M. S. Horritt. 2002. “Assessing the uncertainty in distributed model predictions using observed binary pattern information within GLUE.” Hydrol. Process. 16 (10): 2001–2016. https://doi.org/10.1002/hyp.398.
Bates, P. D., M. D. Wilson, M. S. Horritt, D. C. Mason, N. Holden, and A. Currie. 2006. “Reach scale floodplain inundation dynamics observed using airborne synthetic aperture radar imagery: Data analysis and modeling.” J. Hydrol. 328 (1–2): 306–318. https://doi.org/10.1016/j.jhydrol.2005.12.028.
Beven, K. 1993. “Prophecy, reality and uncertainty in distributed hydrological modeling.” Adv. Water Resour. 16 (1): 41–51. https://doi.org/10.1016/0309-1708(93)90028-E.
Beven, K. 2006. “A manifesto for the equifinality thesis.” J. Hydrol. 320 (1–2): 18–36. https://doi.org/10.1016/j.jhydrol.2005.07.007.
Beven, K., and A. Binley. 1992. “The future of distributed models: Model calibration and uncertainty prediction.” Hydrol. Processes 6 (3): 279–298. https://doi.org/10.1002/hyp.3360060305.
Bhattacharya, B., M. Mazzoleni, and R. Ugay. 2019. “Flood inundation mapping of the sparsely gauged large-scale Brahmaputra basin using remote sensing products.” Remote Sens. 11 (5): 501. https://doi.org/10.3390/rs11050501.
Biswas, N. K., F. Hossain, M. Bonnema, M. A. Okeowo, and H. Lee. 2019. “An altimeter height extraction technique for dynamically changing rivers of South and South East Asia.” Remote Sens. Environ. 221 (Feb): 24–37. https://doi.org/10.1016/j.rse.2018.10.033.
Chini, M., R. Hostache, L. Giustarini, and P. Matgen. 2017. “A hierarchical split-based approach for parametric thresholding of SAR images: Flood inundation as a test case.” IEEE Trans. Geosci. Remote Sens. 55 (12): 6975–6988.
Chow, V. T. 1959. Open channel hydraulics. New York: McGraw-Hill.
Cohen, S., G. R. Brakenridge, A. Kettner, B. Bates, J. Nelson, R. McDonald, Y. F. Huang, D. Munasinghe, and J. Zhang. 2018. “Estimating floodwater depths from flood inundation maps and topography.” J. Am. Water Resour. Assoc. 54 (Aug): 847–858. https://doi.org/10.1111/1752-1688.12609.
CRED (Centre for Research on the Epidemiology of Disasters) and UNISDR (United Nations Office for Disaster Risk Reduction). 2015. The human costs of weather related disasters. Geneva: UNISDR.
CRED (Centre for Research on the Epidemiology of Disasters) and UNISDR (United Nations Office for Disaster Risk Reduction). 2016. Poverty & death: Disaster mortality 1996-2015. Geneva: UNISDR.
Dasgupta, A. 2015. Reduction of uncertainties in a 2D hydrodynamic model using remote sensing data. Enschede, Netherlands: Univ. of Twente.
Dasgupta, A., S. Grimaldi, R. Ramsankaran, V. R. N. Pauwels, J. P. Walker, M. Chini, R. Hostache, and P. Matgen. 2018a. “Flood mapping using synthetic aperture radar sensors from local to global scales.” In Vol. 233 of Global flood hazard: Applications in modeling, mapping, and forecasting: Geophysical monograph series, edited by G. J. Schumann, P. D. Bates, H. Apel, and G. T. Aronica, 55–77. New York: Wiley. https://doi.org/10.1002/9781119217886.ch4.
Dasgupta, A., S. Grimaldi, R. A. A. J. Ramsankaran, V. R. N. Pauwels, and J. P. Walker. 2018b. “Towards operational SAR-based flood mapping using neuro-fuzzy texture-based approaches.” Remote Sens. Environ. 215 (Sep): 313–329. https://doi.org/10.1016/j.rse.2018.06.019.
DHI (Danish Hydraulic Institute). 2014a. Mike11—Reference manual. 8th ed. Lakewood, CO: DHI.
DHI (Danish Hydraulic Institute). 2014b. Mike flood. Lakewood, CO: DHI.
DHI (Danish Hydraulic Institute). 2014c. MIKE 11—User’s manual. Lakewood, CO: DHI.
Di Baldassarre, G., and G. Schumann. 2011. “Recent advances in mapping and modelling flood processes in lowland areas.” Phys. Chem. Earth 36 (7–8): 221–222. https://doi.org/10.1016/j.pce.2011.03.009.
Di Baldassarre, G., G. Schumann, and P. D. Bates. 2009. “A technique for the calibration of hydraulic models using uncertain satellite observations of flood extent.” J. Hydrol. 367 (3–4): 276–282. https://doi.org/10.1016/j.jhydrol.2009.01.020.
Di Baldassarre, G., G. Schumann, L. Brandimarte, and P. Bates. 2011. “Timely low resolution SAR imagery to support floodplain modelling: A case study review.” Surv. Geophys. 32 (3): 255–269. https://doi.org/10.1007/s10712-011-9111-9.
Dobson, M. C., L. Pierce, J. Kellndorfer, and F. Ulaby. 1997. “Use of SAR image texture in terrain classification.” In Vol. 3 of Proc., IEEE Int. Geoscience and Remote Sensing Symp., Remote Sensing-A Scientific Vision for Sustainable Development, 1180–1183. New York: IEEE.
Fischer, M. M. 2006. “Spatial analysis in geography.” In Spatial analysis and geocomputation, 17–28. Berlin: Springer. https://doi.org/10.1007/3-540-35730-0_2.
Fleischmann, A., R. Paiva, and W. Collischonn. 2019. “Can regional to continental river hydrodynamic models be locally relevant? A cross-scale comparison.” J. Hydrol. X 3 (Apr): 100027. https://doi.org/10.1016/j.hydroa.2019.100027.
Frasson, R. P. D. M., T. M. Pavelsky, M. A. Fonstad, M. T. Durand, G. H. Allen, G. Schumann, C. Lion, R. E. Beighley, and X. Yang. 2019. “Global relationships between river width, slope, catchment area, meander wavelength, sinuosity, and discharge.” Geophys. Res. Lett. 46 (6): 3252–3262. https://doi.org/10.1029/2019GL082027.
Gilles, D., and M. Moore. 2010. Review of hydraulic flood modeling software used in Belgium, The Netherlands, and the United Kingdom. Iowa City, IA: International Perspectives in Water Resources Management—Hydroscience & Engineering, Univ. of Iowa.
Giustarini, L., et al. 2011. “Assimilating SAR-derived water level data into a hydraulic model: A case study.” Hydrol. Earth Syst. Sci. 15 (7): 2349–2365. https://doi.org/10.5194/hess-15-2349-2011.
Giustarini, L., R. Hostache, D. Kavetski, M. Chini, G. Corato, S. Schlaffer, and P. Matgen. 2016. “Probabilistic flood mapping using synthetic aperture radar data.” IEEE Trans. Geosci. Remote Sens. 54 (12): 6958–6969. https://doi.org/10.1109/TGRS.2016.2592951.
Giustarini, L., H. Vernieuwe, J. Verwaeren, M. Chini, R. Hostache, P. Matgen, N. E. C. E. C. Verhoest, and B. de Baets. 2015. “Accounting for image uncertainty in SAR-based flood mapping.” Int. J. Appl. Earth Obs. Geoinf. 34 (Feb): 70–77. https://doi.org/10.1016/j.jag.2014.06.017.
Gobeyn, S., et al. 2017. “Impact of the timing of a SAR image acquisition on the calibration of a flood inundation model.” Adv. Water Resour. 100 (Feb): 126–138. https://doi.org/10.1016/j.advwatres.2016.12.005.
Grimaldi, S., Y. Li, V. R. N. Pauwels, and J. P. Walker. 2016. “Remote sensing-derived water extent and level to constrain hydraulic flood forecasting models: Opportunities and challenges.” Surv. Geophys. 37 (5): 977–1034. https://doi.org/10.1007/s10712-016-9378-y.
Grimaldi, S., Y. Li, J. P. Walker, and V. R. N. Pauwels. 2018. “Effective representation of river geometry in hydraulic flood forecast models.” Water Resour. Res. 54 (2): 1031–1057. https://doi.org/10.1002/2017WR021765.
Grimaldi, S., G. J. -P. Schumann, A. Shokri, J. P. Walker, and V. R. N. Pauwels. 2019. “Challenges, opportunities and pitfalls for global coupled hydrologic-hydraulic modeling of floods.” Water Resour. Res. 55 (7): 5277–5300. https://doi.org/10.1029/2018WR024289.
Hagen, A. 2003. “Fuzzy set approach to assessing similarity of categorical maps.” Int. J. Geogr. Inf. Sci. 17 (3): 235–249. https://doi.org/10.1080/13658810210157822.
Haile, A. T., and T. H. M. Rientjes. 2007. “Uncertainty issues in hydrodynamic flood modeling.” In Proc., 5th Int. Symp. on Spatial Data Quality SDQ 2007, Modelling Qualities in Space and Time. Enschede, Netherlands: Geo-Information Science and Earth Observation (ITC).
Hamm, N. A. S., A. Stein, and V. Tolpekin. 2009. “Analyzing the effect of the modifiable areal unit problem in remote sensing: Short note.” In Spatial data quality: From process to decisions, edited by R. Devillers and H. Goodchild, 179. New York: Taylor & Francis.
Haralick, R., K. Shanmugan, and I. Dinstein. 1973. “Textural features for image classification.” IEEE Trans. Syst. Man Cybern. SMC-3 (6): 610–621. https://doi.org/10.1109/TSMC.1973.4309314.
Henry, J. -B., P. Chastanet, K. Fellah, and Y. -L. Desnos. 2006. “Envisat multi-polarized ASAR data for flood mapping.” Int. J. Remote Sens. 27 (10): 1921–1929. https://doi.org/10.1080/01431160500486724.
Horritt, M. S. 2000. “Calibration of a two-dimensional finite element flood flow model using satellite radar imagery.” Water Resour. Res. 36 (11): 3279–3291. https://doi.org/10.1029/2000WR900206.
Horritt, M. S. 2006. “A methodology for the validation of uncertain flood inundation models.” J. Hydrol. 326 (1–4): 153–165. https://doi.org/10.1016/j.jhydrol.2005.10.027.
Horritt, M. S. S., and P. D. Bates. 2002. “Evaluation of 1D and 2D numerical models for predicting river flood inundation.” J. Hydrol. 268 (1–4): 87–99. https://doi.org/10.1016/S0022-1694(02)00121-X.
Hostache, R., M. Chini, L. Giustarini, J. Neal, M. Wood, G. Corato, R. M. Pelich, and P. Matgen. 2018. “Near real-time assimilation of SAR derived flood maps for improving flood forecasts.” Water Resour. Res. 54 (8): 5516–5535. https://doi.org/10.1029/2017WR022205.
Hostache, R., P. Matgen, G. Schumann, C. Puech, L. Hoffmann, and L. Pfister. 2009. “Water level estimation and reduction of hydraulic model calibration uncertainties using satellite SAR images of floods. IEEE Trans. Geosci. Remote Sens. 47 (2): 431–441.
Hunter, N. M., M. S. Horritt, P. D. Bates, M. D. Wilson, and M. G. F. Werner. 2005. “An adaptive time step solution for raster-based storage cell modelling of floodplain inundation.” Adv. Water Resour. 28 (9): 975–991. https://doi.org/10.1016/j.advwatres.2005.03.007.
Jaipurkar, P. K. 2014. “2D hydrodynamic modelling on part of Mahanadi delta region.” M.Sc. thesis, Faculty of Geo-information Science and Earth Observation, Univ. of Twente.
Jha, A., J. Lamond, R. Bloch, N. Bhattacharya, A. López, N. Papachristodoulou, A. Bird, D. Proverbs, J. Davies, and R. Barker. 2011. Five feet high and rising: Cities and flooding in the 21st century. World Bank Policy Research Working Paper No. 5648. Washington, DC: The World Bank.
Landuyt, L., A. Van Wesemael, G. J. -P. Schumann, R. Hostache, N. E. C. Verhoest, and F. M. B. Van Coillie. 2019. “Flood mapping based on synthetic aperture radar: An assessment of established approaches.” IEEE Trans. Geosci. Remote Sens. 57 (2): 722–739. https://doi.org/10.1109/TGRS.2018.2860054.
LPS (Leica Photogrammetry Suite). 2011. Leica photogrammetry suite OrthoBASE & OrthoBASE Pro user’s guide. St. Gallen, Switzerland: Leica Geosystems.
Luppi, L., M. Rinaldi, L. B. Teruggi, S. E. Darby, and L. Nardi. 2009. “Monitoring and numerical modelling of riverbank erosion processes: A case study along the Cecina River (central Italy).” Earth Surf. Processes Landforms 34 (4): 530–546. https://doi.org/10.1002/esp.1754.
Mason, D. C. C., P. D. D. Bates, J. T. Dall’ Amico, and J. T. Dall’ Amico. 2009. “Calibration of uncertain flood inundation models using remotely sensed water levels.” J. Hydrol. 368 (1–4): 224–236. https://doi.org/10.1016/j.jhydrol.2009.02.034.
Mason, D. C. C., G. J. -P. Schumann, J. C. Neal, J. Garcia-Pintado, and P. D. Bates. 2012. “Automatic near real-time selection of flood water levels from high resolution synthetic aperture radar images for assimilation into hydraulic models: A case study.” Remote Sens. Environ. 124 (Sep): 705–716. https://doi.org/10.1016/j.rse.2012.06.017.
Matgen, P., G. Schumann, J. -B. Henry, L. Hoffmann, and L. Pfister. 2007. “Integration of SAR-derived river inundation areas, high-precision topographic data and a river flow model toward near real-time flood management.” Int. J. Appl. Earth Obs. Geoinf. 9 (3): 247–263. https://doi.org/10.1016/j.jag.2006.03.003.
Neal, J. C., N. A. Odoni, M. A. Trigg, J. E. Freer, J. Garcia-Pintado, D. C. Mason, M. Wood, and P. D. Bates. 2015. “Efficient incorporation of channel cross-section geometry uncertainty into regional and global scale flood inundation models.” J. Hydrol. 529 (Oct): 169–183. https://doi.org/10.1016/j.jhydrol.2015.07.026.
Otsu, N. 1979. “A threshold selection method from gray-level histograms.” IEEE Trans. Syst. Man. Cybern. 9 (1): 62–66. https://doi.org/10.1109/TSMC.1979.4310076.
Paliwal, A. 2011. The impact of modifiable areal unit problem on estimation of lake extent. Enschede, Netherlands: Univ. of Twente.
Pappenberger, F., K. Beven, K. Frodsham, R. Romanowicz, and P. Matgen. 2007a. “Grasping the unavoidable subjectivity in calibration of flood inundation models: A vulnerability weighted approach.” J. Hydrol. 333 (2–4): 275–287. https://doi.org/10.1016/j.jhydrol.2006.08.017.
Pappenberger, F., K. Beven, M. Horritt, and S. Blazkova. 2005. “Uncertainty in the calibration of effective roughness parameters in HEC-RAS using inundation and downstream level observations.” J. Hydrol. 302 (1–4): 46–69. https://doi.org/10.1016/j.jhydrol.2004.06.036.
Pappenberger, F., K. Frodsham, K. Beven, R. Romanovicz, and P. Matgen. 2007b. “Fuzzy set approach to calibrating distributed flood inundation models using remote sensing observations.” Hydrol. Earth Syst. Sci. 11: 739–752. https://doi.org/10.5194/hess-11-739-2007.
Patro, S., C. Chatterjee, R. Singh, and N. S. Raghuwanshi. 2009. “Hydrodynamic modelling of a large flood-prone river system in India with limited data.” Hydrol. Process. 23 (19): 2774–2791. https://doi.org/10.1002/hyp.7375.
Pekel, J. F., A. Cottam, N. Gorelick, and A. S. Belward. 2016. “High-resolution mapping of global surface water and its long-term changes.” Nature 540 (7633): 418–422. https://doi.org/10.1038/nature20584.
Revilla-Romero, B., et al. 2015. “On the use of global flood forecasts and satellite-derived inundation maps for flood monitoring in data-sparse regions.” Remote Sens. 7 (11): 15702–15728. https://doi.org/10.3390/rs71115702.
Rientjes, T. H. M., A. T. Haile, E. Kebede, C. M. M. Mannaerts, E. Habib, and T. S. Steenhuis. 2011. “Changes in land cover, rainfall and stream flow in Upper Gilgel Abbay catchment, Blue Nile basin—Ethiopia.” Hydrol. Earth Syst. Sci. 15 (6): 1979–1989. https://doi.org/10.5194/hess-15-1979-2011.
Sanyal, J., and X. X. Lu. 2004. “Application of remote sensing in flood management with special reference to monsoon Asia: A review.” Nat. Hazard. 33 (2): 283–301. https://doi.org/10.1023/B:NHAZ.0000037035.65105.95.
Sathyakumar, V., R. A. A. J. Ramsankaran, and R. Bardhan. 2019. “Linking remotely sensed urban green space (UGS) distribution patterns and socio-economic status (SES)—A multi-scale probabilistic analysis based in Mumbai, India.” GIScience Remote Sens. 56 (5): 645–669. https://doi.org/10.1080/15481603.2018.1549819.
Schlaffer, S., M. Chini, L. Giustarini, and P. Matgen. 2017. “Probabilistic mapping of flood-induced backscatter changes in SAR time series.” Int. J. Appl. Earth Obs. Geoinf. 56 (Apr): 77–87. https://doi.org/10.1016/j.jag.2016.12.003.
Schumann, G., P. D. Bates, M. S. Horritt, P. Matgen, and F. Pappenberger. 2009a. “Progress in integration of remote sensing-derived flood extent and stage data and hydraulic models.” Rev. Geophys. 47 (4): 1–20. https://doi.org/10.1029/2008RG000274.
Schumann, G., M. Cutler, A. Black, P. Matgen, L. Pfister, L. Hoffmann, and F. Pappenberger. 2008a. “Evaluating uncertain flood inundation predictions with uncertain remotely sensed water stages.” Int. J. River Basin Manage. 5124 (3): 37–41. https://doi.org/10.1080/15715124.2008.9635347.
Schumann, G., G. Di Baldassarre, and P. D. Bates. 2009b. “The utility of spaceborne radar to render flood inundation maps based on multialgorithm ensembles.” IEEE Trans. Geosci. Remote Sens. 47 (8): 2801–2807. https://doi.org/10.1109/TGRS.2009.2017937.
Schumann, G., R. Hostache, C. Puech, L. Hoffmann, P. Matgen, F. Pappenberger, and L. Pfister. 2007. “High-resolution 3-D flood information from radar imagery for flood hazard management.” IEEE Trans. Geosci. Remote Sens. 45 (6): 1715–1725. https://doi.org/10.1109/TGRS.2006.888103.
Schumann, G., P. Matgen, M. E. J. Cutler, A. Black, L. Hoffmann, and L. Pfister. 2008b. “Comparison of remotely sensed water stages from LiDAR, topographic contours and SRTM.” ISPRS J. Photogramm. Remote Sens. 63 (3): 283–296. https://doi.org/10.1016/j.isprsjprs.2007.09.004.
Schumann, G. J., and D. K. Moller. 2015. “Microwave remote sensing of flood inundation.” Phys. Chem. Earth. 83–84 (Jan): 84–95. https://doi.org/10.1016/j.pce.2015.05.002.
Schumann, G. J., J. C. Neal, N. Voisin, K. M. Andreadis, F. Pappenberger, N. Phanthuwongpakdee, A. C. Hall, and P. D. Bates. 2013. “A first large-scale flood inundation forecasting model.” Water Resour. Res. 49 (10): 6248–6257. https://doi.org/10.1002/wrcr.20521.
Schumann, G. J. -P., and P. D. Bates. 2018. “The need for a high-accuracy, open-access global DEM.” Front. Earth Sci. 6 (Dec): 225. https://doi.org/10.3389/feart.2018.00225.
Schumann, G. J. P., and G. Di Baldassarre. 2010. “The direct use of radar satellites for event-specific flood risk mapping.” Remote Sens. Lett. 1 (2): 75–84. https://doi.org/10.1080/01431160903486685.
Schumann, G. J. P., H. Vernieuwe, B. De Baets, and N. E. C. Verhoest. 2014. “ROC-based calibration of flood inundation models.” Hydrol. Process. 28 (22): 5495–5502. https://doi.org/10.1002/hyp.10019.
Shen, X., E. N. Anagnostou, G. H. Allen, G. Robert Brakenridge, and A. J. Kettner. 2019. “Near-real-time non-obstructed flood inundation mapping using synthetic aperture radar.” Remote Sens. Environ. 221 (Feb): 302–315. https://doi.org/10.1016/j.rse.2018.11.008.
Singh, V. K., P. K. C. Ray, and A. P. T. Jeyaseelan. 2010. “Orthorectification and digital elevation model (DEM) generation using Cartosat-1 satellite stereo pair in Himalayan terrain.” J. Geogr. Inf. Syst. 02 (2): 85–92. https://doi.org/10.4236/jgis.2010.22013.
Slinski, K. M., T. S. Hogue, and J. E. McCray. 2019. “Active-passive surface water classification: A new method for high-resolution monitoring of surface water dynamics.” Geophys. Res. Lett. 46 (9): 4694–4704. https://doi.org/10.1029/2019GL082562.
Smith, A., P. D. Bates, O. Wing, C. Sampson, N. Quinn, and J. Neal. 2019. “New estimates of flood exposure in developing countries using high-resolution population data.” Nat. Commun. 10 (1): 1–7. https://doi.org/10.1038/s41467-019-09282-y.
Srivastava, P. K., T. P. Srinivasan, A. Gupta, S. Singh, J. S. Nain, S. Prakash, B. Kartikeyan, and B. G. Krishna. 2007. “Recent advances in Cartosat-1 data processing.” In ISPRS Hannover Workshop. Amsterdam, Netherlands: Elsevier.
Stephens, E., and P. Bates. 2015. “Assessing the reliability of probabilistic flood inundation model predictions.” Hydrol. Process. 29 (19): 4264–4283. https://doi.org/10.1002/hyp.10451.
Stephens, E., G. Schumann, and P. Bates. 2014. “Problems with binary pattern measures for flood model evaluation.” Hydrol. Process. 28 (18): 4928–4937. https://doi.org/10.1002/hyp.9979.
Stephens, E. M., P. D. Bates, J. E. Freer, and D. C. Mason. 2012. “The impact of uncertainty in satellite data on the assessment of flood inundation models.” J. Hydrol. 414–415 (Jan): 162–173. https://doi.org/10.1016/j.jhydrol.2011.10.040.
Tarekegn, T. H., A. T. Haile, T. Rientjes, P. Reggiani, and D. Alkema. 2010. “Assessment of an ASTER-generated DEM for 2D hydrodynamic flood modeling.” Int. J. Appl. Earth Obs. Geoinf. 12 (6): 457–465. https://doi.org/10.1016/j.jag.2010.05.007.
Uhe, P., D. Mitchell, P. Bates, C. Sampson, A. Smith, and A. S. Islam. 2019. “Enhanced flood risk with 1.5°C global warming in the Ganges-Brahmaputra-Meghna basin.” Environ. Res. Lett. 14 (7): 074031. https://doi.org/10.1088/1748-9326/ab10ee.
Waller, J. A., J. García-Pintado, D. C. Mason, S. L. Dance, and N. K. Nichols. 2018. “Technical note: Analysis of observation uncertainty for flood assimilation and forecasting.” Hydrol. Earth Syst. Sci. Discuss. 22: 3983–3992. https://doi.org/10.5194/hess-22-3983-2018.
Westerhoff, R. S., M. P. H. H. Kleuskens, H. C. Winsemius, H. J. Huizinga, G. R. Brakenridge, and C. Bishop. 2013. “Automated global water mapping based on wide-swath orbital synthetic-aperture radar.” Hydrol. Earth Syst. Sci. 17 (1): 651–663. https://doi.org/10.5194/hess-17-651-2013.
Wood, M., R. Hostache, J. Neal, T. Wagener, L. Giustarini, M. Chini, G. Corato, P. Matgen, and P. Bates. 2016. “Calibration of channel depth and friction parameters in the LISFLOOD-FP hydraulic model using medium-resolution SAR data and identifiability techniques.” Hydrol. Earth Syst. Sci. 20 (12): 4983–4997. https://doi.org/10.5194/hess-20-4983-2016.
Yan, H., and H. Moradkhani. 2014. “Bayesian model averaging for flood frequency analysis.” In Proc., World Environmental and Water Resources Congress 2014, 1886–1895. Reston, VA: ASCE. https://doi.org/10.1061/9780784413548.189.
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Journal of Hydrologic Engineering
Volume 25 • Issue 9 • September 2020
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© 2020 American Society of Civil Engineers.
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Received: Jan 31, 2019
Accepted: May 4, 2020
Published online: Jul 9, 2020
Published in print: Sep 1, 2020
Discussion open until: Dec 9, 2020
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