Evaluation of Snowmelt Runoff for Extreme Annual Snow Conditions Under Climate Change

International Snow Science Workshop Grenoble – Chamonix Mont-Blanc - 2013

Evaluation of snowmelt runoff for extreme annual snow conditions under climate change

Yoshihiro ASAOKA1,*, Shunsuke KASHIWA2 and So KAZAMA1 1 Graduate School of Engineering, Tohoku University, Japan 2 Tohoku Office, CTI Engineering Co., Ltd., Japan

ABSTRACT: This research investigates the response of snowmelt runoff to change in temperature and precipitation for extreme annual snow conditions such as heavy-snow year and light-snow year. A distributed snowmelt and runoff model is applied in Yoneshiro river basin, Japan to estimate river discharge. Simulation was conducted for two periods: present climate condition (June 2000 to July 2010) and near future climate condition (June 2045 to July 2055). Meteorological forcing for model input was prepared from Automatic Weather station (AWS) and General Circulation Model (GCM). Projection showed that snowmelt-runoff peak under near future climate was almost same as under present climate condition. However, duration of snowmelt runoff was projected to decrease by 1 to 1.5 month in heavy-snow years, whereas there was no significant decrease of snowmelt-flood season in light-snow years.

KEYWORDS: river discharge, heavy and light snow year, distributed runoff model.

1 INTRODUCTION The Sea of Japan side of Japan’s central mountain spine is heavy snow area (Asaoka and Kominami, 2012). However, annual snow condition and winter precipitation pattern vary largely (Asaoka et al., 2002). High snow accumulation has potential to generate intensive snowmelt and low snow accumulation may lead to scarcity of water resource in the catchment. Tempera- ture rise due to climate change is likely to en- hance these trends. Therefore, assessment of snowmelt-runoff pattern is required according to annual snow conditions. The aim of this paper is to evaluate the response of snowmelt runoff to Figure 1. Yoneshiro river catchment, Japan change in temperature and precipitation for ex- tremes annual snow conditions such as heavy- by Japan Meteorological Agency in this chatch- snow and light-snow years under near future ment. climate condition. 3 MODEL DESCRIPTION 2 STUDY AREA The runoff model calculates flow for river A distributed snowmelt and runoff model is channel and slope area. This model calculates the Yoneshiro river basin, Japan (4100km2, Fig- two components of flow for the slope area: sur- ure 1). It located in the Sea of Japan side of Ja- face flow and groundwater flow. River flow and pan’s central mountain spine. River discharge is surface flow are estimated with kinematic wave observed at Futatsui station in this catchment by method. Groundwater flow is estimated with the Ministry of Land, Infrastructure, Transport and storage function method. Flow direction for each Tourism, Japan. In this research, river discharge mesh was determined with elevation data. Grid is estimated at this point. Automatic Meteorolog- size for river rooting is 250m. ical Acquisition System (AMeDAS) is operated Snow water equivalent and snowmelt esti- ______mation were implemented in the distributed runoff model. Spatial snow water equivalent (SWE) Corresponding author address: Yoshihiro was estimated following the methods presented ASAOKA, Graduate School of Engineering, Ja- by Kazama et al. (2008). A degree day method pan; is employed for daily snowmelt estimation. This tel: +81 795 7460; fax: +81 795 7460; research assumes that daily snowmelt is sum of email: [email protected] surface melt and bottom melt.

1406 International Snow Science Workshop Grenoble – Chamonix Mont-Blanc - 2013

Figure 2. Projected river discharge under near future climate conditions

Model simulation was conducted for two pe- runoff decreases by1 to 1.5 months in heavy riods: present climate condition (June 2000 to snow year, whereas there was no significant July 2010) and near future climate condition decrease of snowmelt-flood season in light- (June 2045 to July 2055). Spatial meteorological snow years. dataset for model input was temperature and precipitation. Initially, dataset for present climate 5 CONCLUDING REMARKS condition was prepared from AMeDAS. Second- ly, for temperature data under near future cli- This research projected river discharge for mate, monthly temperature rise between present extreme annual snow conditions under near fu- and near future climate, which was projected by ture climate condition. The projection showed GCM, was added to the time series of observa- that increase in river discharge during winter tion data under present climate condition. For season and decrease during snowmelt season. precipitation data under near future climate, Moreover, it showed that temperature rise caus- monthly increasing ratio of precipitation was es more abrupt runoff and leads to reduction in multiplied to the time series of observation data duration of snowmelt runoff in heavy snow years. under present climate condition. The climate Projected discharge was based on single data projected by MIROC3 (Model for Interdisci- GCM data. Further work is to use multiple GCM plinary Reasearch on Climate), based on sce- data for projection. nario A2 of the Special Report on Emissions Scenarios (SRES), was adopted as increasing 5 ACKNOWLEDGEMENT components of temperature (2.1 to 2.5 °C) and precipitation (90 to 130 %) in the study area. The authors thank the Science and Tech- nology Research Partnership for Sustainable 4 RESULTS Development (SAPTREPS) of Japan Science and Technology Agency (JST) and International Figure 2 displays hydrograph for heavy- Cooperation Agency. We also thank Mitsui Con- snow years and light-snow years during two pe- sultants Co., Ltd. for their helpful support. riods. We categorized light-snow years and heavy-snow years according to annual maxi- mum snowdepth for the present climate condi- 6 REFERENCES tion. Projected river discharge for both snow years under near future climate condition is Asaoka, Y., Kazama, S. and Sawamoto M., 2002. higher in winter than under present climate con- The variation Characteristics of Snow Water dition due to change of precipitation form from Resources in a Wide Area and its Geographical snowfall to rainfall. River discharge in melt sea- and Climatic Dependency. Journal of Japan society of Hydrology and Water Resources, 15(3), son is projected to be lower, especially heavy- pp.279-289 (in Japanease). snow years, due to reduction in snow water Asaoka, Y. and Kominami, Y., 2012. Spatial snowfall equivalent in the catchment. Projection showed distribution in mountainous areas estimated with that peak of discharge for both snow years un- a snow model and satellite remote sensing. der near future climate condition is closely same Hydrological Research Letters, 6, 1-6. as under present climate condition. Kazama, S., Izumi. H., Sarukkalige, PR., Nasu, T. Temperature rise causes more abrupt dis- and Sawamoto, M., 2008. Estimating snow charge in heavy-snow years rather than light- distribution over a large area and its application snow years. Projected duration of snowmelt for water resources, Hydrological Precesses, 22(13): pp.2315-2324.

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