Freeze-thaw　cycles　are　important　processes　relevant　to　terrestrial　hydrological　cycling.　However,　the　representation　of　freeze-thaw　cycles　has　been　often　simplified　in　large　scale　watershed　models.　The　Soil　and　Water　Assessment　Tool　(SWAT),　which　has　been　widely　used　to　understand　and　assess　hydrologic　budgets　and　water　resources　management,　employs　a　simplified　empirical　approach　to　estimate　soil　temperature　and　determine　the　freezing　and　thawing　status　of　soils.　Here,　we　compared　the　performance　of　a　physically-based　soil　temperature　module　and　the　built-in　empirical　approach　in　SWAT　against　field　measurements　at　surface　and　5,　10,　20,　50,　and　100　cm　depths　at　six　stations　of　the　U.S.　Climate　Reference　Network　(USCRN)　within　the　Upper　Mississippi　River　Basin　(UMRB).　In　general,　SWAT　consistently　underestimated　winter　soil　temperatures　and　overestimated　frozen　days　at　all　soil　depths,　while　the　modified　version　of　SWAT　(equipped　with　the　physically-based　soil　temperature　model;　referred　to　as　TSWAT)　pronouncedly　reduced　the　bias　in　estimated　winter　soil　temperatures　and　frozen　days　compared　with　SWAT.　Model　performance　assessment　is　conducted　with　three　statistical　coefficients,　i.e.,　Bias　(°C),　the　coefficient　of　determination　(R　2　),　and　Nash-Sutcliffe　coefficient　(NS).　Statistical　analyses　show　that　TSWAT　accurately　simulated　surface　and　soil　temperatures　at　the　five　depths　with　R　2　and　NS　values　greater　than　0.82　at　most　sites,　and　Bias　values　were　generally　within　the　range　of　−1　to　1　°C　during　winter　and　ranged　between　−2.09　and　2.58　°C　in　non-winter　seasons.　The　differences　in　freeze-thaw　cycle　representation　between　SWAT　and　TSWAT　translate　into　noticeable　discrepancies　in　simulated　key　hydrologic　variables,　such　as　surface　runoff,　percolation,　and　baseflow.　Compared　against　long-term　observed　streamflow　(1980–2015),　TSWAT　outperformed　SWAT　in　capturing　variations　in　monthly　streamflow　in　both　winter　and　non-winter　seasons.　These　results　and　analyses　highlight　the　value　of　improving　freeze-thaw　cycle　representation　for　enhanced　hydrologic　modeling　in　large　watersheds　that　are　subject　to　freeze-thaw　cycles.　©　2019