The aim of this study was to determine if runoff estimates from the curve number model were affected by seasons for different land covers. Eighteen watersheds with varying land covers were delineated using three methods. The delineation methods differ in how internal drainage is evaluated. Runoff estimates from storms for spring, summer, and fall were compared to observed runoff from USGS gaging station data. Errors (difference between estimate runoff and observed runoff) were found to be highest for fall by 3% for all the two delineation methods which do not consider internal drainage. Watersheds were categorized by their dominant land cover (agriculture, forest, or urban). Seasonal differences were found to be significant for certain land covers. The greatest differences between observed and estimated data were found in agriculture and urban especially spring versus fall for all delineations. Forest land cover was found to have no seasonal difference for all three delineation methods. The research suggests that this work contributes to the growing body of research suggesting that vegetative seasonal differences have a greater impact on runoff than is accounted for in the runoff model.
References
[1]
McCuen, R. (2004) Hydrologic Analysis and Design. 3rd Edition, Pearson, Upper Saddle River, 888 p.
[2]
Ponce, V. and Hawkins, R. (1996) Runoff Curve Number: Has It Reached Maturity? Journal of Hydrologic Engineering, 1, 11-19. https://doi.org/10.1061/(ASCE)1084-0699(1996)1:1(11)
[3]
US Department of Agriculture and Natural Resource Conservation Service (NRCS) (2009) Part 630 Hydrology National Engineering Handbook. Chapter 7, Hydrologic Soil Groups. http://directives.sc.egov.usda.gov/OpenNonWebContent.aspx?content=22526.wba
[4]
Garen, D.C. and Moore, D.S. (2005) Curve Number Hydrology in Water Quality Modeling: Uses, Abuses, and Future Directions. Journal of the American Water Resources Association, 41, 377-388. https://doi.org/10.1111/j.1752-1688.2005.tb03742.x
[5]
Lian, H., Yen, H., Huang, J.C., Feng, Q., Qin, L., Bashir, M.A., Wu, S., Zhu, A.X., Luo, J., Di, H., Lei, Q. and Liu, H. (2020) CN-China: Revised Runoff Curve Number by Using Rainfall-Runoff Events Data in China. Water Research, 177, Article ID: 115767. https://doi.org/10.1016/j.watres.2020.115767
[6]
Muche, M., Hutchinson, S., Hutchinson, J. and Johnston, J. (2019) Phenology-Adjusted Dynamic Curve Number for Improved Hydrologic Modeling. Journal of Environmental Management, 235, 403-413. https://doi.org/10.1016/j.jenvman.2018.12.115
[7]
Karen, G., Patrick, W. and Jos, V. (2021) Performance Evaluation of Spatially Distributed, CN-Based Rainfall-Runoff Model Configurations for Implementation in Spatial Land Use Optimization Analyses. Journal of Hydrology, 602, Article ID: 126872. https://doi.org/10.1016/j.jhydrol.2021.126872
[8]
Jenson, S. (1984) Automated Derivation of Hydrological Basin Characteristics from Digital Elevation Data. US Geological Survey Report 14-08-0001-20129, 10 p. http://topotools.cr.usgs.gov/pdfs/automated-derivation-of-hydrologic-basin-characteristics-from-digital-elevatioin-model-data.pdf
[9]
Jenson, S. and Domingue, J. (1998) Extracting Topographic Structure from Digital Elevation Data for Geographic Information System Analysis. Photogrammetric Engineering and Remote Sensing, 54, 1593-1600.
[10]
Khan, A., Richards, K., Parker, G., McRobie, A. and Mukhopadhyay, B. (2014) How Large Is the Upper Indus Basin? The Pitfalls of Auto-Delineation Using DEMs. Journal of Hydrology, 509, 442-453. https://doi.org/10.1016/j.jhydrol.2013.11.028
[11]
Richards, P. and Brenner, A. (2004) Delineating Source Areas for Runoff in Digressional Landscapes: Implications for Hydrologic Modeling. Journal of Great Lakes Research, 30, 9-21. https://doi.org/10.1016/S0380-1330(04)70325-1
[12]
Macholl, J., Clancy, K. and McGinley, P. (2011) Using a GIS Model to Identify Internally Drained Areas and Runoff Contribution in a Glaciated Watershed. Journal of the American Water Resources Association, 47, 114-125. https://doi.org/10.1111/j.1752-1688.2010.00495.x
[13]
Troolin, W. (2015) Impacts of Delineation Methods on Modeled Runoff in Watersheds Containing Non-Contributing Internal Drainage. MSc Thesis, University of Wisconsin, Madison.
[14]
Troolin, W. and Clancy, K. (2016) Comparison of Three Delineation Methods Using the Curve Number Method to Model Runoff. Journal of Water Resources and Protection, 8, 945-964. https://doi.org/10.4236/jwarp.2016.811077
[15]
Miller, K. and Clancy, K. (2017) Improving Curve Number Runoff Estimates Using Dual Hydrologic Soil Classification and Potential Contributing Source Areas Delineation Methods. Journal of Water Resources and Protection, 9, 20-39. https://doi.org/10.4236/jwarp.2017.91003
[16]
Peel, M. (2009) Hydrology: Catchment Vegetation and Runoff. Progress in Physical Geography, 33, 837-844. https://doi.org/10.1177/0309133309350122
[17]
Descheemaeker, K., Poesen, J., Borselli, L., Nyssen, J., Raes, D., Haile, M., Muys, B. and Deckers, J. (2008) Runoff Curve Numbers for Steep Hillslopes with Natural Vegetation in Semi-Arid Tropical Highlands, Northern Ethiopia. Hydrological Processes, 22, 4097-4105. https://doi.org/10.1002/hyp.7011
[18]
Geng, X., Zhou, X., Yin, G., Hao, F., Zhang, X., Hao, Z., Singh, V. and Fu, Y. (2020) Extended Growing Season Reduced River Runoff in Luanhe River Basin. Journal of Hydrology, 582, Article ID: 124538. https://doi.org/10.1016/j.jhydrol.2019.124538
[19]
Hwang, T., Martin, K.L., Vose, J.M., Wear, D., Miles, B., Kim, Y. and Band, L.E. (2018) Nonstationary Hydrologic Behavior in Forested Watersheds Is Mediated by Climate-Induced Changes in Growing Season Length and Subsequent Vegetation Growth. Water Resources Research, 54, 5359-5375. https://doi.org/10.1029/2017WR022279
[20]
Gal, L., Grippa, M., Hiernaux, P., Pons, L. and Kergoat, L. (2016) The Paradoxical Evolution of Runoff in the Pastoral Sahel: Analysis of the Hydrological Changes over the Agoufou Watershed (Mali) Using the KINEROS-2 Model. Hydrology and Earth System Sciences, 21, 4591-4613. https://doi.org/10.5194/hess-21-4591-2017
[21]
Ji, G., Song, H., Wei, H. and Wu, L. (2021) Attribution Analysis of Climate and Anthropic Factors on Runoff and Vegetation Changes in the Source Area of the Yangtze River from 1982 to 2016. Land, 10, Article No. 612. https://doi.org/10.3390/land10060612
[22]
Homer, C., Dewitz, J., Fry, J., Coan, M., Hossain, N., Larson, C., Herold, N., McKerrow, A., Van Driel, J.N. and Wickham, J. (2007) Completion of the 2001 Land Cover Database for the Conterminous United States. Photogrammetric Engineering and Remote Sensing, 73, 337-341.
[23]
USGS (US Geological Survey) (2021) Geological Survey, National Water Information System: Web Interface, Surface Water for Wisconsin. http://waterdata.usgs.gov/wi/nwis/rt
[24]
NCDC (National Climate Data Center) (2020) NCDC Surface Data: Daily. US High Resolution-Cooperative, NWS. https://www.ncdc.noaa.gov/
[25]
USGS (US Geological Survey) (2001) NED (National Elevation Data) 2011 Elevation. SDE Raster Digital Data. http://nationalmap.gov/elevation.html
[26]
USGS (US Geological Survey) (2011) NLCD (National Land Cover Database) 2011 Land Cover. SDE Raster Digital Data. https://www.mrlc.gov/
[27]
Soil Survey Staff, Natural Resources Conservation Service and United States Department of Agriculture (2003) Soil Surge Geographic (SSURGO) Database. http://sdmdataaccess.nrcs.usda.gov
[28]
WDNR (Wisconsin Department of Natural Resources) (2007) 24,000 Hydrography Data. Version 6.
[29]
Sloto, R. and Crouse, M. (1996) HYSEP: A Computer Program for Streamflow Hydrograph Separation and Analysis. US Geological Survey Water-Resources Investigations Report.
[30]
Lim, K., Engel, B., Tang, Z., Choi, J., Kim, K., Muthukrishnan, S. and Tripathy, D. (2005) Automated Web GIS Based Hydrograph Analysis Tool, WHAT. Journal of the American Water Resources Association, 41, 1407-1416. https://doi.org/10.1111/j.1752-1688.2005.tb03808.x