Abstract
The Active River Area (ARA) is a spatial approach for identifying the extent of functional riparian area. Given known limitations in terms of input elevation data quality, ARA studies to date have not achieved effective computer-based ARA components delineation, limiting the efficacy of the ARA framework in terms of informing riparian conservation and management. To determine the optimal input elevation data for future ARA studies, this study tested a novel digital elevation model (DEM) smoothing algorithm and assessed ARA outputs derived from a range of DEMs for accuracy and efficiency. It was found that the tested DEM smoothing algorithm allows the ARA framework to take advantage of high-resolution LiDAR DEM and considerably improves the accuracy of high-resolution LiDAR DEM derived ARA results; smoothed LiDAR DEM in 5-m spatial resolution best balanced ARA accuracy and data processing efficiency and is ultimately recommended for future ARA delineations across large regions. The scientific findings provided by this study further enhance the efficacy of the ARA framework, and ultimately the confidence in modelled ARA outputs for application in riparian conservation and management contexts across broad geographic regions.
Similar content being viewed by others
Data Availability
Data used in this study can be downloaded from http://www.snb.ca/geonb1/e/DC/catalogue-E.asp.
References
Bater CW, Coops NC (2009) Evaluating error associated with lidar-derived DEM interpolation. Comput Geosci 35(2):289–300. https://doi.org/10.1016/j.cageo.2008.09.001
Benda L, Hassan AM, Church M, May LC (2007) Geomorphology of steep land headwaters: the transition from hillslopes to channels. J Am Water Resour Assoc 41(4):835–851. https://doi.org/10.1111/j.1752-1688.2005.tb03773.x
Cao Y, Natuhara Y (2020) Effect of anthropogenic disturbance on floristic homogenization in the floodplain landscape: insights from the taxonomic and functional perspectives. Forests 11(10):1036. https://doi.org/10.3390/f11101036
Cohen J (1960) A coefficient of agreement for nominal scales. Educ Psychol Meas 20(1):37–46. https://doi.org/10.1177/001316446002000104
De Sosa LL, Glanville HC, Marshall MR, Abood SA, Williams AP, Jones DL (2018) Delineating and mapping riparian areas for ecosystem service assessment. Ecohydrology 11(2):e1928. https://doi.org/10.1002/eco.1928
Fereshtehpour M, Karamouz M (2018) DEM resolution effects on coastal flood vulnerability assessment: deterministic and probabilistic approach. Water Resour Res 54:4965–4982. https://doi.org/10.1029/2017WR022318
Goyal MK, Panchariya VK, Sharma A et al (2018) Comparative assessment of SWAT model performance in two distinct catchments under various DEM scenarios of varying resolution, sources and resampling methods. Water Resour Manag 32:805–825. https://doi.org/10.1007/s11269-017-1840-1
Hawker L, Bates P, Neal J, Rougier J (2018) Perspectives on digital elevation model (DEM) simulation for flood modeling in the absence of a high-accuracy open access global DEM. Front Earth Sci 6:233. https://doi.org/10.3389/feart.2018.00233
Kuglerová L, Ågren A, Jansson R, Laudon H (2014) Towards optimizing riparian buffer zones: ecological and biogeochemical implications for forest management. For Ecol Manag 334:74–84. https://doi.org/10.1016/j.foreco.2014.08.033
Kuglerová L, Jyväsjärvi J, Ruffing C, Muotka T, Jonsson A, Andersson E, Richardson JS (2020) Cutting edge: a comparison of contemporary practices of riparian buffer retention around small streams in Canada, Finland, and Sweden. Water Resour Res 56(9):e2019WR026381. https://doi.org/10.1029/2019WR026381
Lin S, Jing C, Chaplot V, Yu X, Zhang Z, Moore N, Wu J (2010) Effect of DEM resolution on SWAT outputs of runoff, sediment and nutrients. Hydrol Earth Syst Sci Discuss 7(4):4411–4435. https://doi.org/10.5194/hessd-7-4411-2010
Lindsay JB, Francioni A, Cockburn JM (2019) LiDAR DEM smoothing and the preservation of drainage features. Remote Sens 11(16):1926. https://doi.org/10.3390/rs11161926
Naiman RJ, Décamps H (1997) The ecology of interfaces: riparian zones. Annu Rev Ecol Syst 28(1):621–658
Reid AJ, Carlson AK, Creed IF, Eliason EJ, Gell PA, Johnson PT, Kidd KA, MacCormack TJ, Olden JD, Ormerod SJ, Smol JP, Taylor WW, Tockner K, Vermaire JC, Dudgeon D, Cooke SJ (2019) Emerging threats and persistent conservation challenges for freshwater biodiversity. Biol Rev 94(3):849–873. https://doi.org/10.1111/brv.12480
Roostaee M, Deng Z (2020) Effects of digital elevation model resolution on watershed-based hydrologic simulation. Water Resour Manag 34:2433–2447. https://doi.org/10.1007/s11269-020-02561-0
Singh R, Tiwari AK, Singh GS (2021) Managing riparian zones for river health improvement: an integrated approach. Landsc Ecol Eng 17:1–29. https://doi.org/10.1007/s11355-020-00436-5
Smith MP, Schiff R, Olivero A, MacBroom JG (2008) The active river area: a conservation framework for protecting rivers and streams. The Nature Conservancy, Boston
Stengård E, Räsänen A, Ferreira CSS, Kalantari Z (2020) Inventory and connectivity assessment of wetlands in Northern landscapes with a depression-based DEM method. Water 12(12):3355. https://doi.org/10.3390/w12123355
Strahler AN (1957) Quantitative analysis of watershed geomorphology. Am Geophys Union Trans 38:913–920. https://doi.org/10.1029/TR038i006p00913
Tan ML, Ramli HP, Tam TH (2018) Effect of DEM resolution, source, resampling technique and area threshold on SWAT outputs. Water Resour Manag 32:4591–4606. https://doi.org/10.1007/s11269-018-2072-8
Tate E, Muñoz C, Suchan J (2015) Uncertainty and sensitivity analysis of the HAZUS-MH flood model. Nat Hazards Rev 16(3):04014030. https://doi.org/10.1061/(ASCE)NH.1527-6996.0000167
Van Nieuwenhuizen N, Lindsay JB, DeVries B (2021) Smoothing of digital elevation models and the alteration of overland flow path length distributions. Hydrol Process 35(7):e14271. https://doi.org/10.1002/hyp.14271
Wu Q, Lane CR (2017) Delineating wetland catchments and modeling hydrologicconnectivity using lidar data and aerial imagery. Hydrol Earth Syst Sci 21(7):3579–3595. https://doi.org/10.5194/hess-21-3579-2017
Zhao Z, Benoy G, Chow TL et al (2010) Impacts of accuracy and resolution of conventional and LiDAR based DEMs on parameters used in hydrologic modeling. Water Resour Manag 24:1363–1380. https://doi.org/10.1007/s11269-009-9503-5
Acknowledgements
The authors acknowledge The Nature Conservancy for providing technical advice related to the Active River Area Framework.
Funding
The financial support of this study was received in the form of graduate scholarships awarded to S.M., including Dalhousie University’s Faculty of Graduate Studies scholarship, Colin Stewart Award, and Neil Munro award.
Author information
Authors and Affiliations
Contributions
S.M. was involved in the study design, acquired and analyzed geospatial data, and wrote the main manuscript text. K.F.B led the research supervision, was involved in the study design, and made substantial contributions to manuscript preparation. P.N. and C.S.G. were involved in research supervision, study design, and manuscript preparation.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare no conflicts of interest.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Ma, S., Beazley, K.F., Nussey, P. et al. Assessing Optimal Digital Elevation Model Selection for Active River Area Delineation Across Broad Regions. Water Resour Manage 35, 4825–4840 (2021). https://doi.org/10.1007/s11269-021-02948-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11269-021-02948-7