Abstract: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 , which involves an increase in the air temperature of 3Ð9°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 1Ð2-3Ð3°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.

We evaluated the past impacts of urbanization and climate change on groundwater-in particular, aquifer temperature-in the Sendai plain, Japan, and further compared with the probable changes due to changing climate in the future. A series of simulations were performed and matched with the observed temperaturedepth profiles as a preliminary step for parameter calibration. The magnitude of ground surface warming estimated from subsurface temperature spans 0.9-1.3 • C, which is consistent with the calibrated ground surface warming rates surrounding various observation wells (0.021-0.015 • C/year) during the last 60 years. We estimate that approximately 75% of the ground surface temperature change can be attributed to the effect of past urbanization. For the climate predictions, climate variables produced by the UK Hadley Centre's Climate Model (HadCM3) under the A2, A1B and B1 scenarios were spatially downscaled by the transfer function method. Downscaled monthly data were used in a water budget analysis to account for the variation in recharge and were further applied in a heat transport equation together with the estimated ground surface warming rates in 2080. Anticipated groundwater recharge under the projected climate in 2080 would decrease by 1-26% compared to the 2007 estimates, despite the projected 7-28% increase in precipitation, due to a higher degree of evapotranspiration resulting from a 2.5-3.9 • C increase in surface air temperature. The overall results from the three scenarios predict a 1.8-3.7 • C subsurface temperature change by 2080, which is notably greater than the previous effect of urbanization and climate change on aquifer temperature in the Sendai plain.

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The reliable prediction of climate variables at finer temporal resolutions, e.g. daily scale, is essential for climate change impact analysis. However, humidity variables remain less focused, although probable changes under changing climate conditions and their effect on impact studies can be significant. The potential of the daily minimum air temperature (Tn) downscaled from general circulation models (GCMs) to predict ground‐scale relative humidity in climate change studies is presented. Daily data over 50 years for Sendai city were obtained from the Japan Meteorological Agency. For GCM data, the INMCM4 model developed by the Institute for Numerical Mathematics, Russia, was selected. Statistically downscaled Tn was used with the linear or second order polynomial relationships developed for each calendar month using observed relative humidity and Tn. This produced predicted relative humidity using the alternative method. Furthermore, relative humidity was directly downscaled using the relative humidity results from the GCM. The results from the two methods were compared with the observed relative humidity data based on the root mean square error and the Kolmogorov–Smirnov test. Results based on root mean square error indicate that the predictions made using the downscaled Tn were less satisfied only for June and September compared to the results from the direct downscaling method. Moreover, the predicted relative humidity using the downscaled Tn matched rather well with the observations for 8 months (except for March, July, August and October) with calculated p values above the 0.05 level. Notably, the proposed method achieved better performance in the winter months when the directly downscaled method failed to satisfy the Kolmogorov–Smirnov test.