Climate change impacts on groundwater temperature change in the Sendai plain, Japan

Groundwater temperature is a key parameter regulating the ecological balance of the ecosystems in groundwater dominated wetlands, estuaries and ponds. This study evaluated the potential impacts of climate change on groundwater temperature and proposed a methodology for use in areas with limited hydrological and metrological data. Groundwater temperatures were measured in 1 m intervals in five observation wells and used for groundwater recharge estimation. Three different techniques, the water balance method, the water level fluctuation (WLF) method and Darcy's method, were performed to verify the estimated recharge rates from the temperature-depth profiles. Of the six sets of global climate model (GCM) predictions analysed, three of them were selected by considering a range of potential climate changes in the future. The transfer function method was used to downscale the GCM outputs of precipitation and temperature of the Sendai plain. Raw GCM data for nine scenarios (A2, A1B, and B1 from HADCM3, MRI, and ECHAM5 models) and observed data from 1967 to 2006 were used to develop the transfer functions. Derived functions, which were tested for 1927-1966, were used to downscale GCM data for 2060-2099. These predictions were used in a one-dimensional heat transport model, which was calibrated to the existing site conditions by the water budget technique. There are marked differences among the scenarios and GCMs. However, all the model scenarios projected increasing trends in temperature and precipitation for the 2060-2099 time period. HADCM3 A2 scenario shows the strongest effect compared with the base line climate (1967-2006), which involves an increase in the air temperature of 3·9 °C and an increase in annual precipitation of 345 mm. When considering all GCM scenarios compared with observations in 2006, the aquifer temperature at 8 m depth from the ground surface could possibly increase within the range of 1·2-3·3 °C by 2080. The above findings from the methodology developed here will be important for estimating the impact of climate change and will be useful for environmental management programs.