Analysis of Overland Flow Generation and Catchment Storm Runoff Using a Distributed Runoff Model in a Headwater Catchment Draining Japanese Cypress Forest

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  • Gomi Takashi
    Graduate School of Agriculture, Tokyo University of Agriculture and Technology
  • Miyata Shusuke
    Disaster Prevention Research Institute, Kyoto University
  • Sidle Roy C.
    Ecosystems Research Division, National Exposure Research Laboratory, U.S. Environmental Protection Agency
  • Kosugi Ken’ichiro
    Graduate School of Agriculture, Kyoto University
  • Onda Yuichi
    Center for Research in Isotopes and Envirinmental Dynamics, University of Tsukuba
  • Hiraoka Marino
    Graduate School of Agriculture, Tokyo University of Agriculture and Technology
  • Furuichi Takahisa
    Science Delivery Division, Department of Science, Information Technology, Innovation and the Arts, Queensland

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Other Title
  • 分布型流出モデルを用いたヒノキ人工林流域における地表流の発生と降雨流出解析
  • ブンプガタ リュウシュツ モデル オ モチイタ ヒノキ ジンコウリン リュウイキ ニ オケル チヒョウリュウ ノ ハッセイ ト コウウ リュウシュツ カイセキ

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Abstract

We developed a distributed runoff model that utilizes a contour-based topographic approximation (TOPOTUBE). The model consists of logical algorithms for water flux and associated routing for Hortonian overland flow, saturation overland flow, and saturated soil matrix flow. The model was applied in a 4.9 ha watershed covered by Japanese cypress forest in Mie Prefecture, central Japan. Changes in infiltration capacity with respect to rainfall intensity and soil water repellency were considered. Because spatial variability of infiltration capacity affects the occurrence and transport of overland flow, we employed detailed field information of soil infiltration capacity based on ground cover distribution. Agreement between observed and estimated catchment storm runoff improved when these spatial patterns of infiltration were considered in the model. In addition to these spatial patterns, further internal spatial variability of infiltration capacity based on the standard deviation of estimated infiltration capacity was included. This assumption means that locally high infiltration pixels are randomly distributed within the hillslopes. Observed and estimated overland flow generation at the hillslope plot scale showed that associating such internal variability of infiltration capacity can further improve the simulation of overland flow generation.

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