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Net primary productivity (NPP) is a key component of the terrestrial carbon cycle and is important in ecological, watershed, and forest management studies, and more broadly in global climate change research. Determining the relative importance and magnitude of uncertainty of NPP model inputs is important for proper carbon reporting over larger areas and time periods. This paper presents a systematic evaluation of the boreal ecosystem productivity simulator (BEPS) model in mountainous terrain using an established montane forest test site in Kananaskis, Alberta, in the Canadian Rocky Mountains. Model runs were based on forest (land cover, leaf area index (LAI), biomass) and climate–water inputs (solar radiation, temperature, precipitation, humidity, soil water holding capacity) derived from digital elevation model (DEM) derivatives, climate data, geographical information system (GIS) functions, and topographically corrected satellite imagery. Four sensitivity analyses were conducted as a controlled series of experiments involving (i) NPP individual parameter sensitivity for a full growing season, (ii) NPP independent variation tests (parameter µ ± 1σ), (iii) factorial analyses to assess more complex multiple-factor interactions, and (iv) topographic correction. The results, validated against field measurements, showed that modeled NPP was sensitive to most inputs measured in the study area, with LAI and forest type the most important forest input, and solar radiation the most important climate input. Soil available water holding capacity expressed as a function of wetness index was only significant in conjunction with precipitation when both parameters represented a moisture-deficit situation. NPP uncertainty resulting from topographic influence was equivalent to 140 kg C ha−1·year−1. This suggested that topographic correction of model inputs is important for accurate NPP estimation. The BEPS model, designed originally for flat boreal forests, was shown to be applicable in mountainous terrain given appropriate image terrain corrections using the SCS+C approach. Rocky Mountain carbon dynamics were simulated with average annual NPP of Kananaskis forests estimated at 4.01 t C ha−1·year−1 and compared favourably with the field plot estimate of 4.24 t C ha−1·year−1 for this area.

Sensitivity of a carbon and productivity model to climatic, water, terrain, and biophysical parameters in a Rocky Mountain watershed