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Abstract Surface meteorological analyses are an essential input (termed “forcing”) for hydrologic modeling. This study investigated the sensitivity of different hydrologic model configurations to temporal variations of seven forcing variables (precipitation rate, air temperature, longwave radiation, specific humidity, shortwave radiation, wind speed, and air pressure). Specifically, the effects of temporally aggregating hourly forcings to hourly daily average forcings were examined. The analysis was based on 14 hydrological outputs from the Structure for Unifying Multiple Modeling Alternatives (SUMMA) model for the 671 Catchment Attributes and Meteorology for Large-Sample Studies (CAMELS) basins across the contiguous United States (CONUS). Results demonstrated that the hydrologic model sensitivity to temporally aggregating the forcing inputs varies across model output variables and model locations. We used Latin hypercube sampling to sample model parameters from eight combinations of three influential model physics choices (three model decisions with two options for each decision, i.e., eight model configurations). Results showed that the choice of model physics can change the relative influence of forcing on model outputs and the forcing importance may not be dependent on the parameter space. This allows for model output sensitivity to forcing aggregation to be tested prior to parameter calibration. More generally, this work provides a comprehensive analysis of the dependence of modeled outcomes on input forcing behavior, providing insight into the regional variability of forcing variable dominance on modeled outputs across CONUS. 

Abstract Tonle Sap Lake in Cambodia is arguably the world's most productive freshwater ecosystems, as well as the dominant source of animal protein for the country. The rapid rise of hydropower schemes, deforestation, land development and climate change impacts in the Mekong River Basin, however, now represent serious concerns in regard to Tonle Sap Lake's ecological health and its role in future food security. To this end, the present study identifies significant recent warming of lake temperature and discusses how each of these anthropogenic perturbations in Tonle Sap's floodplain and the Mekong River Basin may be influencing this trend. The lake's dry season monthly average temperature increased by 0.03°C/year between 1988 and 2018, being largely in synchrony with warming trends of the local air temperature and upstream rivers. The impacts of deforestation and agriculture development in the lake's floodplain also exhibited a high correlation with an increased number of warm days observed in the lake, particularly in its southeast region (agricultureR² = .61; deforestationR² = .39). A total of 79 dams, resulting in 72 km³of volumetric water capacity, were constructed between 2003 and 2018 in the Mekong River Basin. This dam development coincided with a decreasing trend in the number of dry season warm days per year in the lower Mekong River, while Tonle Sap Lake's number of dry season warm days continued to increase during this same period. The present study revealed that Tonle Sap Lake's temperature trends are highly influenced by temperature trends in the local climate, agriculture development and deforestation of the lake's watershed. Although there were no noticeable impacts observed from upstream dam development in the Mekong River Basin, local‐to‐regional agricultural and land management of the lake's watershed appear to be effective strategies for maintaining a stable thermal regime in the lake in order to facilitate maximum ecosystem health.