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Abstract A mountain watershed network model is presented for use in decadal to centurial estimation of source‐to‐sink sediment dynamics. The model requires limited input parameters and can be effectively applied over spatial scales relevant to management of reservoirs, lakes, streams, and watersheds (1–100 km²). The model operates over a connected stream network of Strahler‐ordered segments. The model is driven by streamflow from a physically based hydrology model and hillslope sediment supply from a stochastic mass wasting algorithm. For each daily time step, segment‐scale sediment mass balance is computed using bedload and suspended load transport equations. Sediment transport is partitioned between grain size fractions for bedload as gravel and sand, and for suspended load as sand and mud. Bedload and suspended load can deposit and re‐entrain at each segment. We demonstrated the model in the Elwha River Basin, upstream of the former Glines Canyon dam, over the dam's historic 84‐year lifespan. The model predicted the lifetime reservoir sedimentation volume within the uncertainty range of the measured volume (13.7–18.5 million m³) for 25 of 28 model instances. Gravel, sand, and mud fraction volumes were predicted within measurement uncertainty ranges for 18 model instances. The network model improved the prediction of sediment yields compared to at‐a‐station sediment transport capacity relations. The network model also provided spatially and temporally distributed information that allowed for inquiry and understanding of the physical system beyond the sediment yields at the outlet. This work advances cross‐disciplinary and application‐oriented watershed sediment yield modeling approaches. 

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.