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Abstract. Vegetation is known to have strong influence on evapotranspiration (ET), a major component of terrestrial water balance. Yet hydrological models often describe ET by methods unable to include the variability of vegetation characteristics in their predictions. To take advantage of the increasing availability of high-resolution open GIS data on land use, vegetation and soil characteristics in the boreal zone, a modular, spatially distributed model for predicting ET and other hydrological processes from grid cell to catchment level is presented and validated. An improved approach to upscale stomatal conductance to canopy scale using information on plant type (conifer/deciduous) and stand leaf-area index (LAI) is proposed by coupling a common leaf-scale stomatal conductance model with a simple canopy radiation transfer scheme. Further, a generic parametrization for vegetation-related hydrological processes for Nordic boreal forests is derived based on literature and data from a boreal FluxNet site. With the generic parametrization, the model was shown to reproduce daily ET measured using an eddy-covariance technique well at 10 conifer-dominated Nordic forests whose LAI ranged from 0.2 to 6.8 m2 m−2. Topography, soil and vegetation properties at 21 small boreal headwater catchments in Finland were derived from open GIS data at 16 m × 16 m grid size to upscale water balance from stand to catchment level. The predictions of annual ET and specific discharge were successful in all catchments, located from 60 to 68∘ N, and daily discharge was also reasonably well predicted by calibrating only one parameter against discharge measurements. The role of vegetation heterogeneity in soil moisture and partitioning of ET was demonstrated. The proposed framework can support, for example, forest trafficability forecasting and predicting impacts of climate change and forest management on stand and catchment water balance. With appropriate parametrization it can be generalized outside the boreal coniferous forests.

Abstract:The water-energy-food nexus is promoted as a new approach for research and policy-making. But what does the nexus mean in practice and what kinds of benefits does it bring? In this article we share our experiences with using a nexus approach in Cambodia's Tonle Sap Lake area. We conclude that water, energy and food security are very closely linked, both in the Tonle Sap and in the transboundary Mekong River Basin generally. The current drive for large-scale hydropower threatens water and food security at both local and national scales. Hence, the nexus provides a relevant starting point for promoting sustainable development in the Mekong. We also identify and discuss two parallel dimensions for the nexus, with one focusing on research and analysis and the other on integrated planning and cross-sectoral collaboration. In our study, the nexus approach was particularly useful in facilitating collaboration and stakeholder engagement. This was because the nexus approach clearly defines the main themes included in the process, and at the same time widens the discussion from mere water resource management into the broader aspects of water, energy and food security.

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Soil rutting caused by forest operations has negative economic and ecological effects and thus limits for rutting are set by forest laws and sustainability criteria. Extensive data on rut depths are necessary for post-harvest quality control and development of models that link environmental conditions to rut formation. This study explored the use of a Light Detection and Ranging (LiDAR) sensor mounted on a forest harvester and forwarder to measure rut depths in real harvesting conditions in Southern Finland. LiDAR-derived rut depths were compared to manually measured rut depths. The results showed that at 10-20 m spatial resolution, the LiDAR method can provide unbiased estimates of rut depth with root mean square error (RMSE) < 3.5 cm compared to the manual rut depth measurements. The results suggest that a LiDAR sensor mounted on a forest vehicle can in future provide a viable method for the large-scale collection of rut depth data as part of normal forestry operations.