Traditional agricultural practices, including paddy farming on terraced uplands, have garnered renewed interest in recent years in response to increasing concerns on environmental sustainability and the expected effects of climate change on global food security. However, little systematic research on the potential vulnerabilities of these traditional agroecosystems to future climatic change has been conducted as most are located in remote areas with limited data availability. This paper is a case study on the Ifugao Rice Terraces of the Philippines, a centuries-old farming system whose success is dependent on the year-round allocation of water resources following an intricate agricultural cycle. We developed a site-specific hydrological model coupling the similar hydrologic element response (SHER) model for surface and vadose zone processes and the modular three-dimensional groundwater flow (MODFLOW) model for saturated groundwater movement to evaluate baseline conditions in a selected first-order catchment within the Kiangan terrace cluster. Output from the SHER–MODFLOW model showed good agreement with in situ observations of stream discharge and hydraulic head measured in 2014–2016. To elucidate the impacts of climate change, we downscaled future projections from three global climate models, MRI-CGCM3, GFDL-CM3, and UKMO-HadGEM3, under greenhouse gas concentration pathways RCP-4.5 and RCP-8.5. We used these future climate projections with the calibrated SHER–MODFLOW model to evaluate the combined surface water and groundwater resources in 2041–2050 and 2091–2100. Results indicated trends of increasing temperature for all months, decreasing rainfall and increased risks of water deficits for future dry seasons, and increasing rainfall and increased risks of excess runoff for future wet seasons. These trends will be more pronounced at the end of the century. These results are important in evaluating the sustainability of this traditional agricultural system under climate change, and in designing appropriate local adaptation measures.