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Extreme hydrologic events, including drought and flooding, could significantly influence soil organic matter (SOM) and soil total nitrogen (STN) of arable lands, resulting in carbon (C) emissions to the atmosphere and nitrogen (N) loss downstream. Modeling could be a practical approach to estimating the effects of extreme hydrologic on SOM and STN dynamics. However, studies on model development of SOM and STN and its differences between wheat and paddy lands after a long cultivation history (ie 20-year) are still limited. Hence, a comparison model of SOM and STN from thirteen soil health monitoring stations in China (0-170 cm with different soil layers) were built by six different learning methods with air temperatures, precipitation, humidity, and atmospheric pressure [ie, the annual (semiannual/quarterly/monthly) average (maximum/minimum) value of a climate factor], and regressions between SOM, STN …