Kuttara Volcano, Hokkaido, Japan, consists of temperate Lake Kuttara and the western Noboribetsu geothermal area. In order to explore geothermal relations between Lake Kuttara and the geothermal area, the heat budget of a hydrothermal pond, Okunoyu, was evaluated, and the heat storage change in the lower layer of Lake Kuttara was calculated by monitoring the water temperature at the deepest point. The lake water temperature consistently increased during the thermal stratification in June–November of 2013–2016. The heat flux QB at lake bottom was then calculated at a range of 4.1–10.9 W/m2, which is probably due to the leakage from a hydrothermal reservoir below the lake bottom. Meanwhile, the heat flux HGin by geothermal groundwater input in Okunoyu was evaluated at 3.5–8.5 kW/m2, which is rapidly supplied through faults from underlying hydrothermal reservoirs. With a time lag of 5 months to monthly mean QB values in Lake Kuttara, the correlation with monthly mean HGin in Okunoyu was significant (R2 = 0.586; p < 0.01). Applying Darcy’s law to the leakage from the hydrothermal reservoir at 260–310 m below the lake bottom, the time needed for groundwater’s passage through the media 260–310 m thick was evaluated at 148–149 days (ca. 5 months). These findings suggest that the hydrothermal reservoir below lake bottom and the underlying hydrothermal reservoirs in the western geothermal area are both connected to a unique geothermal source in the deeper zone as a geothermal flow system of Kuttara Volcano.
In order to clarify how groundwater leakage and river runoff occur in a catchment under tectonic movement, the water balance was estimated in the forested (88.3% in area) Oikamanai River catchment (area, 62.6 km 2 ), Hokkaido, Japan. The catchment's geology is early Miocene to Pliocene sedimentary bedrock of partly high permeability, accompanied by currently active faults. Daily evapotranspiration, E, in water balance was calculated by applying the one-layer model to meteorological data in the rainfall season of 2011 and 2012, with the topographic influence on heat balance of the catchment considered. The coupling with the short-term water balance method for river runoff events allows us to estimate groundwater leaking to the other catchments through the faults and bedrock. As a result, the leakage corresponded to 50% -80% of effective rainfall (=P − E: P, rainfall) in 2011, whereas it was lower or negative in 2012. The estimate of leakage then included variability of ca. 80%. In 2012, shallow groundwater storage seems to retain high baseflow during non-rainfall.
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