Resource communication: Variability in estimated runoff in a forested area based on different cartographic data sources

  • Laura Fragoso Universidad de Extremadura, Avda Universidad s/n 10005, Cáceres
  • Elia Quirós Universidad de Extremadura, Avda Universidad s/n 10005, Cáceres
  • Pablo Durán-Barroso Universidad de Extremadura, Avda Universidad s/n 10005, Cáceres
Keywords: runoff estimation, Soil Conservation Service curve number, land use map, Geographic Information System, forested watershed, tree canopy cover factor

Abstract

Aim of study: The goal of this study is to analyse variations in curve number (CN) values produced by different cartographic data sources in a forested watershed, and determine which of them best fit with measured runoff volumes.

Area of study: A forested watershed located in western Spain.

Material and methods: Four digital cartographic data sources were used to determine the runoff CN in the watershed.

Main results: None of the cartographic sources provided all the information necessary to determine properly the CN values. Our proposed methodology, focused on the tree canopy cover, improves the achieved results.

Research highlights: The estimation of the CN value in forested areas should be attained as a function of tree canopy cover and new calibrated tables should be implemented in a local scale.

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References

Ajmal M, Kim TW, Ahn JH, 2016. Stability assessment of the curve number methodology used to estimate excess rainfall in forest-dominated watersheds. Arab J Geosci 9 (5): 1-14. https://doi.org/10.1007/s12517-016-2421-y

Carpenter TM, Sperfslage JA, Georgakakos KP, Sweeney T, Fread DL, 1999. National threshold runoff estimation utilizing GIS in support of operational flash flood warning systems. J Hydrol 224 (1–2): 21-44. https://doi.org/10.1016/S0022-1694(99)00115-8

Choi HT, Kim J, Lim HG, 2016. Estimating the SCS runoff curve number in forest catchments of Korea. EGU General Assembly Conference Abstracts.

Ferrer i Juliá M, 2003. Análisis de nuevas fuentes de datos para la estimación del parámetro número de curva: perfiles de suelos y teledetección. CEDEX, Spain.

Kim NW, Lee J, 2008. Temporally weighted average curve number method for daily runoff simulation. Hydrol Proces 22 (25): 4936-4948. https://doi.org/10.1002/hyp.7116

Lim KJ, Engel BA, Tang Z, Choi J, Kim KS, Muthukrishnan S, Tripathy D, 2005. Automated Web GIS based Hydrograph Analysis Tool, WHAT. JAWRA 41 (6): 1407-1416. https://doi.org/10.1111/j.1752-1688.2005.tb03808.x

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. T ASABE 50 (3): 885-900. https://doi.org/10.13031/2013.23153

NRCS, 2009. National Engineering Handbook, section 4, Hydrology, version (1956, 1964, 1971, 1985, 1993, 2004, 2009). USDA, Washington, DC. Engineering Division.

Tedela NH, McCutcheon SC, Rasmussen TC, Hawkins RH, Swank WT, Campbell JL, Adams MB, Jackson CR, Tollner EW, 2011. Runoff curve numbers for 10 small forested watersheds in the mountains of the Eastern United States. J Hydrol Eng 17 (11): 1188-1198. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000436

Témez JR, 1987. Cálculo hidrometereológico de caudales máximos en pequeñas cuencas naturales. MOPU, Spain.

Published
2017-10-20
How to Cite
Fragoso, L., Quirós, E., & Durán-Barroso, P. (2017). Resource communication: Variability in estimated runoff in a forested area based on different cartographic data sources. Forest Systems, 26(2), eRC02. https://doi.org/10.5424/fs/2017262-10921
Section
Resource communications