Evaluation of open Digital Elevation Models: estimation of topographic indices relevant to erosion risk in the Wadi M’Goun watershed, Morocco

Maryam Khal; Abdellah Algouti; Ahmed Algouti; Nadia Akdim; Sergey A. Stankevich; Massimo Menenti; Maryam Khal; Abdellah Algouti; Ahmed Algouti; Nadia Akdim; Sergey A. Stankevich; Massimo Menenti

doi:10.3934/geosci.2020014

AIMS Geosciences

2020, Volume 6, Issue 2: 231-257. doi: 10.3934/geosci.2020014

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Research article

Evaluation of open Digital Elevation Models: estimation of topographic indices relevant to erosion risk in the Wadi M’Goun watershed, Morocco

1.
Cadi Ayyad University, Faculty of Sciences, Department of Geology, Laboratory of Geosciences, Geotourism, Natural Hazards and Remote Sensing, Bd. BO 2390, 40000 Marrakech, Morocco
2.
Department of Geology, Faculty of Sciences, Chouaib Doukkali University, Route Ben Maachou, B.P 20, 24000, El Jadida, Morocco
3.
Scientific Centre for Aerospace Research of the Earth, NAS of Ukraine, 55-B O. Gonchar str., Kiev, 01054, Ukraine
4.
Geosciences and Remote Sensing Department, Delft University of Technology, Stevinweg 12628 CN Delft, The Netherlands
5.
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

Received: 09 April 2020 Accepted: 11 June 2020 Published: 22 June 2020

Various Global Digital Elevation Models (DEM) are available freely on the Web. The main objective of this work is to evaluate the latest digital elevation models towards the estimation of morphological and topographic erosion parameters in the Wadi M’Goun watershed. We have evaluated multiple DEMs: SRTM (3-arcsec resolution, 90 m), ASTER GDEM (1-arcsec resolution, 30 m), SRTMGL1 V003 (30 m), and ALOS-PALSAR (12.5 m). We have applied for this purpose open source GIS software. To compare and evaluate each DEM, different processing methods have been applied to estimate the Wadi M’Goun watershed characteristics, namely Hypsometry, topographic slope extraction, retrieval of Slope Length and Steepness factor (LS-factor) and topographic wetness index. The accuracy of the ALOS-PALSAR and SRTMGL1 V003 (30 m) DEMs met the requirements applying to the required morphometric parameters. DEMs vertical accuracy has been evaluated by applying the root mean square error (RMSE) metric to DEM elevations vs. actual heights of 353 sample points extracted from an accurate survey-based map (toposheet). The RMSE was 1718 mm for ALOS-PALSAR, 1736 for SRTM 1-arcsec, 1958 for ASTER GDEM 1-arcsec and, 3189 for SRTM 3-arcsec. These results indicate that best accuracy is achieved with the high-resolution of the ALOS PALSAR DEM. This study suggests potential uncertainties in the open-source DEMs, which should be taken into account when estimating topographical and morphometric parameters related to erosion risk in the Wadi M’Goun watershed.
- erosion risk,
- open DEM,
- SRTM,
- ASTER GDEM,
- SRTMGL1 V003,
- ALOS-PALSAR,
- M’Goun watershed,
- Central High Atlas
Citation: Maryam Khal, Abdellah Algouti, Ahmed Algouti, Nadia Akdim, Sergey A. Stankevich, Massimo Menenti. Evaluation of open Digital Elevation Models: estimation of topographic indices relevant to erosion risk in the Wadi M’Goun watershed, Morocco[J]. AIMS Geosciences, 2020, 6(2): 231-257. doi: 10.3934/geosci.2020014

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Abstract

Various Global Digital Elevation Models (DEM) are available freely on the Web. The main objective of this work is to evaluate the latest digital elevation models towards the estimation of morphological and topographic erosion parameters in the Wadi M’Goun watershed. We have evaluated multiple DEMs: SRTM (3-arcsec resolution, 90 m), ASTER GDEM (1-arcsec resolution, 30 m), SRTMGL1 V003 (30 m), and ALOS-PALSAR (12.5 m). We have applied for this purpose open source GIS software. To compare and evaluate each DEM, different processing methods have been applied to estimate the Wadi M’Goun watershed characteristics, namely Hypsometry, topographic slope extraction, retrieval of Slope Length and Steepness factor (LS-factor) and topographic wetness index. The accuracy of the ALOS-PALSAR and SRTMGL1 V003 (30 m) DEMs met the requirements applying to the required morphometric parameters. DEMs vertical accuracy has been evaluated by applying the root mean square error (RMSE) metric to DEM elevations vs. actual heights of 353 sample points extracted from an accurate survey-based map (toposheet). The RMSE was 1718 mm for ALOS-PALSAR, 1736 for SRTM 1-arcsec, 1958 for ASTER GDEM 1-arcsec and, 3189 for SRTM 3-arcsec. These results indicate that best accuracy is achieved with the high-resolution of the ALOS PALSAR DEM. This study suggests potential uncertainties in the open-source DEMs, which should be taken into account when estimating topographical and morphometric parameters related to erosion risk in the Wadi M’Goun watershed.

References

[1]	Forsberg R (1984) A study of terrain reductions, density anomalies and geophysical inversion methods in gravity field modelling. No. OSU/DGSS-355, Ohio State University.
[2]	Müller-wohlfeil DI, lahmer W, krysanova V, et al. (1996) Topography-based hydrological modeling in the Elbe River drainage basin. In: Third International Conference/Workshop on Integrating GIS and Environmental Modeling, National Center for Geographic Information and Analysis, C.A, Santa Fe.
[3]	Mark DM, Smith B (2004) A science of topography: from qualitative ontology to digital representations. In: Bishop MP, Shroder JF (Eds.), Geographic Information Science and Mountain Geomorphology, Springer-Praxis, Chichester, England, 75-97.
[4]	Khal M, Algouti Ab, Algouti A (2018) Modeling of Water Erosion in the M'Goun Watershed Using OpenGIS Software. In: World Academy of Science, Engineering and Technology International Journal of Computer and Systems Engineering, 12: 1102-1106.
[5]	Mcluckie D, NFRAC (2008) Flood risk management in Australia. Aust J Emerg Manag 23: 21-27.
[6]	Ait Mlouk M, Algouti Ab, Algouti Ah, et al. (2018) Assessment of river bank erosion in semi-arid climate regions using remote sensing and GIS data: a case study of Rdat River, Marrakech, Morocco. Estud Geol 74: 81. doi: 10.3989/egeol.43217.493
[7]	Williams J (2009) Weather Forecasting. The AMS Weather Book: The Ultimate Guide to America's Weather. American Meteorological Society, Boston, MA. doi: 10.1007/978-1-935704-55-3
[8]	Da ros D, Borga M (1997) Use of digital elevation model data for the derivation of the geomorphological instantaneous unit hydrograph. Hydrol Process 11: 13-33. doi: 10.1002/(SICI)1099-1085(199701)11:1<13::AID-HYP400>3.0.CO;2-M
[9]	Tesfa TK, Tarboton DG, Watson DW, et al. (2011) Extraction of hydrological proximity measures from DEMs using parallel processing. Environ Model Softw 26: 1696-1709. doi: 10.1016/j.envsoft.2011.07.018
[10]	Jobin T, Prasannakumar V (2015) Comparison of basin morphometry derived from topographic maps, ASTER and SRTM DEMs: an example from Kerala, India. Geocarto Int 30: 346-364. doi: 10.1080/10106049.2014.955063
[11]	Kishan SR, Anil KM, Vinay KS, et al. (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 Shahjahanpur district, Uttar Pradesh, India. Geocarto Int 28: 439-452.
[12]	Tian Y, Lei S, Bian Z, et al. (2018) Improving the Accuracy of Open Source Digital Elevation Models with Multi-Scale Fusion and a Slope Position-Based Linear Regression Method. Remote Sens 10: 1861. doi: 10.3390/rs10121861
[13]	Cuartero A, Felicsimo AM, Ariza FJ (2004) Accuracy of DEM generation from TERRA-ASTER stereo data. Int Arch Photogramm Remote Sens 35: 559-563.
[14]	Day T, Muller J (1988) Quality assessment of digital elevation models produced by automatic stereo-matchers from SPOT image pairs. Photogramm Rec 12: 797-808. doi: 10.1111/j.1477-9730.1988.tb00630.x
[15]	Fujisada H (1994) Overview of ASTER instrument on EOS-AM1 platform. In: Proceedings of SPIE, 2268: 14-36. doi: 10.1117/12.185838
[16]	Toutin T (2008) ASTER DEMs for geomatic and geoscientific applications. Int J Remote Sens 29: 1855-1875. doi: 10.1080/01431160701408477
[17]	Bolstad PV, Stowe T (1994) An evaluation of DEM accuracy: elevation, slope, and aspect. Photogramm Eng Remote Sens 60: 1327-1332.
[18]	Blöschl G, Sivapalan M (1995) Scale issues in hydrological modelling: A review. Hydrol Process 9: 251-290. doi: 10.1002/hyp.3360090305
[19]	Vijith H, Seling LW, Dodge-Wan D (2015) Comparison and Suitability of SRTM and ASTER Digital Elevation Data for Terrain Analysis and Geomorphometric Parameters: Case Study of Sungai PatahSubwatershed (Baram River, Sarawak, Malaysia). Environ Res Eng Manag 71: 23-35. doi: 10.5755/j01.erem.71.3.12566
[20]	Beven KJ, Moore ID (1993) Terrain analysis and distributed modelling in hydrology. New York: Wiley.
[21]	Wang XH, Yin ZY (1998) A comparison of drainage networks derived from digital elevation models at two scales. J Hydrol 210: 221-241. doi: 10.1016/S0022-1694(98)00189-9
[22]	Wang W, Yang X, Yao T (2012) Evaluation of ASTER GDEM and SRTM and their suitability in hydraulic modelling of a glacial lake outburst flood in southeast Tibet. Hydrol Process 26: 213-225. doi: 10.1002/hyp.8127
[23]	Nikolakopoulos KG, Kamaratakis EK, Chrysoulakis N (2006) SRTM vs ASTER elevation products. Comparison for two regions in Crete, Greece. Int J Remote Sens 27: 4819-4838. doi: 10.1080/01431160600835853
[24]	Pryde JK, Osorio J, Wolfe ML, et al. (2007) USGS. An ASABE Meeting Presentation Paper Number: 072093, Minneapolis Convention Center Minneapolis, Minnesota, June; 072093.
[25]	Jing C, Shortridge A, Lin S, et al. (2014) Comparison and validation of SRTM and ASTER GDEM for a subtropical landscape in Southeastern China. Int J Digit Earth 7: 969-992. doi: 10.1080/17538947.2013.807307
[26]	Dewitt JD, Warner TA, Conley JF (2015) Comparison of DEMS derived from USGS DLG, SRTM, a statewide photogrammetry program, ASTER GDEM and LiDAR: implications for change detection. GIScience Remote Sens 52: 179-197. doi: 10.1080/15481603.2015.1019708
[27]	Moudrý V, Lecours V, Gdulová K, et al. (2018) On the use of global DEMs in ecological modelling and the accuracy of new bare-earth DEMs. Ecol Modell 383: 3-9. doi: 10.1016/j.ecolmodel.2018.05.006
[28]	Zhang K, Gann D, Ross M, et al. (2019) Comparison of TanDEM-X DEM with LiDAR Data for Accuracy Assessment in a Coastal Urban Area. Remote Sens 11: 876. doi: 10.3390/rs11070876
[29]	Kinsey-Henderson AE, Wilkinson SN (2012) Evaluating Shuttle radar and interpolated DEMs for slope gradient and soil erosion estimation in low relief terrain. Environ Modell Softw 40: 128-139. doi: 10.1016/j.envsoft.2012.08.010
[30]	Lin S, Jing C, Coles NA, et al. (2013) Evaluating DEM source and resolution uncertainties in the Soil and Water Assessment Tool. Stoch Environ Res Risk Assess 27: 209-221. doi: 10.1007/s00477-012-0577-x
[31]	Williams JR, Berndt HD (1977) Sediment yield prediction based on watershed hydrology. Transactions of the American Society of Agricultural and Biological Engineers. Trans ASAE 20: 1100-1104. doi: 10.13031/2013.35710
[32]	Rexer M, Hirt C (2014) Comparison of free high-resolution digital elevation data sets (ASTER GDEM2, SRTM v2.1/v4.1) and validation against accurate heights from the Australian National Gravity Database. Aust J Earth Sci 61: 213-226.
[33]	Renard KG, Foster GR, Weesies GA, et al. (1997) Predicting soil erosion by water: a guide to conservation planning with the revised universal soil loss equation (RUSLE). Agriculture Handbook, U.S. Department of Agriculture, No 703, 404.
[34]	Prasuhn V, Liniger H, Gisler S, et al. (2013) A high-resolution soil erosion risk map of Switzerland as strategic policy support system. Land Use Policy 32: 281-291. doi: 10.1016/j.landusepol.2012.11.006
[35]	Mondal A, Khare D, Kundu S, et al. (2016) Uncertainty of soil erosion modelling using open source high resolution and aggregated DEMs. Geosci Front 8: 425-436. doi: 10.1016/j.gsf.2016.03.004
[36]	Mondal A, Khare D, Kundu S (2017) Uncertainty analysis of soil erosion modelling using different resolution of open-source DEMs. Geocarto Int 32: 334-349. doi: 10.1080/10106049.2016.1140822
[37]	Uhlemann S, Thieken AH, Merz B (2014) A quality assessment framework for natural hazard event documentation: application to trans-basin flood reports in Germany. Nat Hazards Earth Syst Sci 14: 189-208. doi: 10.5194/nhess-14-189-2014
[38]	USGS (2006) Earth Resources Observation and Science. Available from: https://www.usgs.gov/centers/eros.
[39]	Wang L, Liu H (2006) An efficient method for identifying and filling surface depressions in digital elevation models for hydrologic analysis and modelling. Int J Geogr Inf Sci 20: 193-213. doi: 10.1080/13658810500433453
[40]	Das A, Agrawala R, Mohan S (2015) Topographic correction of ALOS-PALSAR images using InSAR-derived DEM. Geocarto Int 30: 145-153.
[41]	Jäger R, Kaminskis J, Balodis J (2012) Determination of Quasi-geoid as Height Component of the Geodetic Infrastructure for GNSS-Positioning Services in the Baltic States. Latv J Phys Tech Sci 49: 2.
[42]	Ghilani CD, Wolf PR (2006) Adjustment Computations: Spatial Data Analysis, 4th Edition, John Wiley & Sons, Hoboken.
[43]	Al-Fugara A (2015) Comparison and Validation of the Recent Freely Available DEMs over Parts of the Earth's Lowest Elevation Area: Dead Sea, Jordan. Int J Geosci 6: 1221-1232. doi: 10.4236/ijg.2015.611096
[44]	Shaw EM (1988) Van Nostrand Reinhold International, London, United Kingdom. Hydrology in practice.
[45]	Strahler AN (1964) Quantitative geomorphology of drainage basin and channel network. In Chow VT (ed), Handbook of Applied Hydrology, McGrawHill, NewYork, NY, USA.
[46]	Wanielista MP, Kersten R, Eaglin R (1997) Hydrology: Water Quantity and Quality Control, Wiley, New York.
[47]	Musy A (2001) Ecole Polytechnique Fédérale, Lausanne, Suisse, e-drologie.
[48]	Roche M (1963) Hydrologie de Surface. Gauthier-Villars, Paris, 140: 659.
[49]	Horton RE (1945) Erosional development of streams and their drainage basins: hydro physical approach to quantitative morphology. Geol Soc Am Bull 56: 275-370. doi: 10.1130/0016-7606(1945)56[275:EDOSAT]2.0.CO;2
[50]	Strahler AN (1952) Hypsometric analysis of erosional topography. Bull Geol Soc Am 63: 1117-1142. doi: 10.1130/0016-7606(1952)63[1117:HAAOET]2.0.CO;2
[51]	Schumm SA (1956) Evolution of drainage systems and slopes in badlands at perth amboy, new jersey. Geol Soc Am Bull 67: 597-646. doi: 10.1130/0016-7606(1956)67[597:EODSAS]2.0.CO;2
[52]	Beven KJ, Kirkby MJ (1979) A physically based, variable contributing area model of basin hydrology. Hydrol Sci Bull 24: 43-69. doi: 10.1080/02626667909491834
[53]	Pandey A, Chowdary VM, Mal BC (2007) Identification of critical erosion prone areas in the small agricultural watershed using USLE, GIS and remote sensing. Water Resour Manage 21: 729-746. doi: 10.1007/s11269-006-9061-z
[54]	Freeman TG (1991) Calculating Catchment Area With Divergent Flow Based on a Regular Grid. Comput Geosci 17: 413-422. doi: 10.1016/0098-3004(91)90048-I
[55]	Kamp U, Bolch T, Olsenholler J (2005) Geomorphometry of Cerro Sillajhuay (Andes, Chile/Bolivia): Comparison of digital elevation models (DEMs) from ASTER remote sensing data and contour maps. Geocarto Int 20: 23-33. doi: 10.1080/10106040508542333
[56]	Datta PS, Schack-Kirchner H (2010) Erosion Relevant Topographical Parameters Derived from Different DEMs-A Comparative Study from the Indian Lesser Himalayas. Remote Sens 2: 1941-1961. doi: 10.3390/rs2081941
[57]	Luo W (1998) Hypsometric analysis with a geographic information system. Comput Geosci 24: 815-821. doi: 10.1016/S0098-3004(98)00076-4
[58]	Vaze J, Teng J, Spencer G (2010) Impact of DEM accuracy and resolution on topographic indices. Environ Modell Softw 25: 1086-1098. doi: 10.1016/j.envsoft.2010.03.014
[59]	Holmes KW, Chadwick OA, Kyriankidis PC (2000) Error in USGS 30-meter digital elevation model and its impact on terrain modelling. J Hydrol 233: 154-173. doi: 10.1016/S0022-1694(00)00229-8
[60]	Huggel C, Schneider D, Miranda PJ, et al. (2008) Evaluation of ASTER and SRTM DEM data for lahar modelling: A case study on lahars from Popocatépetl volcano, Mexico. J Volcanol Geotherm Res 170: 99-110. doi: 10.1016/j.jvolgeores.2007.09.005
[61]	De Vente J, Poesen J, Govers G, et al. (2009) The implications of data selection for regional erosion and sediment yield modelling. Earth Surf Process Landf 34: 1994-2007. doi: 10.1002/esp.1884
[62]	Nitheshnirmal S, Thilagaraj P, Abdul Rahaman S, et al. (2019) Erosion risk assessment through morphometric indices for prioritisation of Arjuna watershed using ALOS-PALSAR DEM. Model Earth Syst Environ 5: 907-924. doi: 10.1007/s40808-019-00578-y
[63]	Bhakar R, Srivastav SK, Punia M (2010) Assessment of the relative accuracy of aster and SRTM digital elevation models along irrigation channel banks of Indira Gandhi Canal. J Water Land-use Manage 10: 1-11.
[64]	Hasan A, Pilesjo P, Persson A (2011) The use of LIDAR as a data source for digital elevation models-a study of the relationship between the accuracy of digital elevation models and topographical attributes in northern peatlands. Hydrol Earth Syst Sci Discuss 8: 5497-5522. doi: 10.5194/hessd-8-5497-2011

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