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Assessment of Cartosat-1 DEM for Modeling Floods in Data Scarce Regions

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Abstract

Digital Elevation Model (DEM) plays an important role in modeling floods. In data scarce developing countries, unavailability of high resolution topography and river cross-sections data are the prime limitations for simulating hydrodynamic models for modeling floods. In the present study, we assess the quality of Cartosat-1 DEMs in providing accurate river cross-sections and floodplain elevations; and hence their suitability in modeling floods. Cartosat-1 DEMs are prepared using Ground Control Points (GCP) of surveyed elevation and bias corrected Shuttle Radar Topography Mission (SRTM) elevation. Surveyed elevation based Cartosat-1 DEM is found to be of best quality while bias corrected SRTM elevation based Cartosat-1 DEM is found to be of reasonable quality on the basis of cross-section representation as well as elevation statistics. Cross-sections derived from the Cartosat-1 DEMs as well as surveyed cross-sections are later used independently in MIKE11 model for 1-dimensional flow modeling. Simulated water levels from models based on Cartosat-1 DEMs are compared graphically with the observed water levels. Modeling performance is also evaluated using different statistical performance criteria. Results show that the models based on Cartosat-1 DEM derived cross-sections perform similar to the model based on surveyed cross-sections. Study concludes that a reasonably accurate DEM, prepared from moderate survey in data scarce region, can be used for deriving requisite river cross-sections for hydrodynamic modeling.

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References

  1. Abbott MB, Ionescu (1967) On the numerical computation of nearly horizontal flows. J Hydraul Res 5:97–117

  2. Ahmed N, Mahtab A, Agrawal R, Jayaprasad P, Pathan SK, Ajai SDK, Singh AK (2007) Extraction and validation of cartosat-1 DEM. Photonirvachak-J In Soc Remote Sens 35(2):121–127

  3. Ali MA, Solomatine DP, Di Baldassarre G (2014) Assessing the impact of different sources of topographic data on 1-D hydraulic modeling of flood. Hydrol Earth Syst Sci Discuss 11:7375–7408

  4. Bothale RV, Pandey B (2013) Evaluation and comparison of multi resolution DEM derived through cartosat-1 stereo pair - a case study of damanganga basin. J Indian Soc Re Sens 41(3):497–507

  5. Casas A, Benito G, Thorndycraft VR, Rico M (2006) The topographic data source of digital terrain models as a key element in the accuracy of hydraulic flood modelling. Earth Surf Proc Land 31(4):444–456

  6. Castellarin A, Di Baldassarre G, Bates PD, Brath A (2009) Optimal cross-sectional spacing in preissmann scheme 1D hydrodynamic models. J Hydraul Eng 135(2):96–105

  7. Central Water Commission (CWC) (1996) Report of the working group on flood management for the ninth five year plan (1997–2002). CWC, New Delhi

  8. Chatterjee C, Foerster S, Bronstert A (2008) Comparison of hydrodynamic models of different complexities to model floods with emergency storage areas. Hydrol Process 22(24):4695–4709

  9. Chavarri E, Crave A, Bonnet MP, Mejia A, Da Silva JS, Guyot JL (2013) Hydrodynamic modelling of the amazon river: factors of uncertainty. J S Am Earth Sci 44:94–103

  10. Chow VT (1959) Development of uniform flow and its formulas. Open-channel hydraulics. (pp. 101–113). McGraw-Hill Book Company, New York

  11. Cook A, Merwade V (2009) Effect of topographic data, geometric configuration and modeling approach on flood inundation mapping. J Hydrol 377(1–2):131–142. doi:10.1016/j.jhydrol.2009.08.015

  12. DHI (2014) A modelling system for rivers and channels, MIKE 11 reference manual. Danish Hydraulic Institute, Horsholm

  13. Domeneghetti A, Tarpanelli A, Brocca L, Barbetta S, Moramarco T, Castellarin A, Brath A (2014) The use of remote sensing-derived water surface data for hydraulic model calibration. Remote Sens Environ 149:130–141. doi:10.1016/j.rse.2014.04.007

  14. Evans AG, Ramachandran B, Zhang Z, Baily GB, Cheng P (2008). An accuracy assessment of Cartosat-1 stereo image data-derived Digital Elevation Models: A case study of the Drum Mountains, Utah. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B1. Beijing, 1161–1164

  15. Fairfield J, Leymarie P (1991) Drainage networks from grid digital elevation models. Water Resour Res 27(5):709–717. doi:10.1029/90wr02658

  16. Farr TG, Rosen PA, Caro E, Crippen R, Duren R, Hensley S, Kobrick M, Paller M, Rodriguez E, Roth L, Seal D, Shaffer S, Shimada J, Umland J, Werner M, Oskin M, Burbank D, Alsdorf D (2007) The shuttle radar topography mission. Reviews of Geophysics 45(2). 10.1029/2005rg000183

  17. Flood workshop (2011) Workshop on floods in Odisha: civil society perspectives. 16th October 2011, Conference Hall, Odisha Environmental Society. http://www.scribd.com/doc/69550673/Brief-Minutes-of-Flood-Workshop-revised#scribd

  18. Forkuor G, Maathuis B (2012) Comparison of SRTM and ASTER derived Digital Elevation Models over two regions in Ghana - Implications for hydrological and environmental modeling. Studies on Environmental and Applied Geomorphology, Dr. Tommaso Piacentini (Ed.), ISBN: 978-953-51-0361-5. http://cdn.intechopen.com/pdfs-wm/32991.pdf

  19. Forster S, Chatterjee C, Bronstert A (2008) Hydrodynamic simulation of the operational management of a proposed flood emergency storage area at the middle Elbe river. River Res Appl 24(7):900–913

  20. Gianinetto M (2009) Evaluation of cartosat-1 multi-scale digital surface modelling over France. Sensors 9(5):3269–3288

  21. Gichamo TZ, Popescu I, Jonoski A, Solomatine D (2012) River cross-section extraction from the ASTER global DEM for flood modeling. Environ Model Softw 31:37–46

  22. Giribabu D, Kumar P, Mathew J, Sharma KP, Murthy YVNK (2013) DEM generation using cartosat-1 stereo data: issues and complexities in Himalayan terrain. Euro J Remote Sens 46:431–443

  23. Jena PP, Chatterjee C, Pradhan G, Mishra A (2014) Are recent frequent high floods in Mahanadi basin in eastern India due to increase in extreme rainfalls? J Hydrol 517:847–862

  24. Liu X (2008) Airborne LiDAR for DEM generation: some critical issues. Prog Phys Geogr 32(1):31–49

  25. Mani P, Chatterjee C, Kumar R (2014) Flood hazard assessment with multiparameter approach derived from coupled 1D and 2D hydrodynamic flow model. Nat Hazards 70(2):1553–1574

  26. Merwade VM, Maidment DR, Hodges BR (2005) Geospatial representation of river channels. J Hydrol Eng 10(3):243–251

  27. Merwade V, Cook A, Coonrod J (2008a) GIS techniques for creating river terrain models for hydrodynamic modeling and flood inundation mapping. Environ Model Softw 23(10–11):1300–1311

  28. Merwade V, Olivera F, Arabi M, Edleman S (2008b) Uncertainty in flood inundation mapping: current issues and future directions. J Hydrol Eng 13(7):608–620

  29. Metz M, Mitasova H, Harmon RS (2011) Efficient extraction of drainage networks from massive, radar-based elevation models with least cost path search. Hydrol Earth Syst Sci 15(2):667–678

  30. Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans ASABE 50(3):885–900

  31. Paiva RCD, Collischonn W, Tucci CEM (2011) Large scale hydrologic and hydrodynamic modeling using limited data and a GIS based approach. J Hydrol 406(3–4):170–181

  32. Patro S, Chatterjee C, Mohanty S, Singh R, Raghuwanshi NS (2009a) Flood inundation modeling using MIKE FLOOD and remote sensing data. J Indian Soc Remote Sens 37(1):107–118

  33. Patro S, Chatterjee C, Singh R, Raghuwanshi NS (2009b) Hydrodynamic modelling of a large flood-prone river system in India with limited data. Hydrol Process 23(19):2774–2791

  34. Pieczonka T, Bolch T, Buchroithner M (2011) Generation and evaluation of multitemporal digital terrain models of the Mt. Everest area from different optical sensors. ISPRS J Photogramm Remote Sens 66(6):927–940

  35. Pramanik N, Panda RK, Sen D (2010) One dimensional hydrodynamic modeling of river flow using DEM extracted river cross-sections. Water Resour Manag 24(5):835–852

  36. Rawat KS, Mishra AK, Sehgal VK, Ahemd N, Tripathi VK (2012) Comparative evaluation of horizontal accuracy of elevations of selected ground control points from ASTER and SRTM DEM with respect to CARTOSAT-1 DEM: a case study of Sahjahanpurdistrict, Uttar Pradesh, India. 10.1080/10106049.2012. 724453

  37. Sahoo B, Chatterjee C, Raghuwanshi NS, Singh R, Kumar R (2006) Flood estimation by GIUH-based Clark and Nash models. J Hydrol Eng 11(6):515–525

  38. Samantaray D, Chatterjee C, Singh R, Gupta PK, Panigrahy S (2015) Flood risk modeling for optimal rice planning for delta region of Mahanadi river basin in India. Nat Hazards 76:347–372

  39. Sanders BF (2007) Evaluation of on-line DEMs for flood inundation modeling. Adv Water Resour 30(8):1831–1843

  40. Sharma CS, Mishra A, Panda SN (2014) Assessing impact of flood on river dynamics and susceptible regions: geomorphometric analysis. Water Resour Manag 28(9):2615–2638

  41. Shenk T (1996) Digital areal triangulation. Int Arch of Photogramm Remote sens Vol. XXXI, PartB3, Vienna

  42. Tarekegn TH, Haile AT, Rientjes T, Reggiani P, Alkema D (2010) Assessment of an ASTER-generated DEM for 2D hydrodynamic flood modeling. Int J Appl Earth Obs 12(6):457–465

  43. Tarolli P (2014) High-resolution topography for understanding earth surface processes: opportunities and challenges. Geomorphology 216:295–312

  44. Teng J, Vaze J, Dutta D, Marvanek S (2015) Rapid inundation modeling in large floodplains using LiDAR DEM. Water Resour Manag 29(8):2619–2636

  45. Vogt EV, Colombo R, Bertolo F (2003) Deriving drainage networks and catchment boundaries: a new methodology combining digital elevation data and environmental characteristics. Geomorphology 53(3–4):281–298

  46. Wilson M, Bates P, Alsdorf D, Forsberg B, Horritt M, Melack J, Frappart F, Famiglietti J (2007) Modeling large-scale inundation of Amazonian seasonally flooded wetlands. Geophys Res Lett 34(15)

  47. Yamazaki D, Baugh CA, Bates PD, Kanae S, Alsdorf DE, Oki T (2012) Adjustment of a spaceborne DEM for use in floodplain hydrodynamic modeling. J Hydrol 436:81–91

  48. Yan K, Tarpanelli A, Balint G, Moramarco T, Baldassarre G (2015) Exploring the potential of SRTM topography and radar altimetry to support flood propagation modeling: Danube case study. J Hydrol Eng 20(2):04014048

  49. Yarrakula K, Deb D, Samant B (2013) Comparative evaluation of cartosat-1 and SRTM imageries for digital elevation modeling. Geo Spat Inf Sci 16(2):75–82

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Acknowledgments

This study is a part of the project titled “Flood inundation zoning for different return periods in Mahanadi River basin” sponsored by Indian National Committee on Surface Water (INCSW), Ministry of Water Resources, Govt. of India.

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Correspondence to Prachi Pratyasha Jena.

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Jena, P.P., Panigrahi, B. & Chatterjee, C. Assessment of Cartosat-1 DEM for Modeling Floods in Data Scarce Regions. Water Resour Manage 30, 1293–1309 (2016). https://doi.org/10.1007/s11269-016-1226-9

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Keywords

  • Digital elevation model
  • Vertical bias
  • Cartosat-1 DEM
  • Flood modeling
  • MIKE-11 model
  • SRTM DEM