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Spatial Forest Hydrology (Launiainen et al. Hydrological and Earth System Sciences, 2019)

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SpaFHy v1.0

This is repository for SpaFHy_v1 source code (under MIT copyright licence). Contains working examples of catchment scale and point-scale models (with example data).

Reference:

Launiainen, S., Guan, M., Salmivaara, A., and Kieloaho, A.-J.: Modeling boreal forest evapotranspiration and water balance at stand and catchment scales: a spatial approach, Hydrol. Earth Syst. Sci., https://www.hydrol-earth-syst-sci.net/23/3457/2019/

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 leafarea index (LAI) is proposed by coupling a common leafscale 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 eddycovariance technique well at 10 conifer-dominated Nordic forests whose LAI ranged from 0.2 to 6.8m2 m-2. Topography, soil and vegetation properties at 21 small boreal headwater catchments in Finland were derived from open GIS data at 16m 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 68N, 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.

Drained peatland version (https://github.com/LukeEcomod/SpaFHy-Peat):

Leppä, K., Sarkkola, S., Peltoniemi, M., Hökkä, H., Saarinen, M., Lehtonen, A., Laiho, R., Mäkipää, R., Launiainen, S., Nieminen, M. 2020. Selection cuttings as a tool to control water table level in boreal drained peatland forests. Front. Earth Sci., 09 October 2020, https://doi.org/10.3389/feart.2020.576510

Applications:

Tyystjärvi V., Kemppinen J., Luoto M., Aalto T., Markkanen T., Launiainen S., Kieloaho A-J, Aalto J. 2021. Modelling spatio-temporal soil moisture dynamics in mountain tundra. Hydrological Processes.2022;36:e14450https://doi.org/10.1002/hyp.14450

Salmivaara, A., Launiainen S., et al. 2020. Towards dynamic Forest Trafficability Prediction using Open Spatial Data, Hydrological Modelling and Sensor Technology, Forestry 2020; 1–13, doi:10.1093/forestry/cpaa010

Minimal User-guide to run the model:

  1. clone repository

  2. create folder '/results'

  3. change file paths accordingly in spafhy_parameters

  4. To run catchment-scale model, see demo_spafhy_C3. append parent folder to sys.path if necessary

  5. To run point-scale model, see demo_spafhy_point. append parent folder to sys.path if necessary

Folders:

/data - contains necessary example data

/misc - old and obsolete stuff; may be re-cyclable

/FigsC3 - figures etc.

/results - (create manually!) to store results.

Tested in Py3.6, should also work with 2.7. Required packages: os, sys, numpy, pandas, NetCDF4, pickle, scipy, matplotlib, (seaborn for plotting) Pandas is constantly evolving so depending on version some fixes may be necessary.

Contact: samuli.launiainen@luke.fi

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Spatial Forest Hydrology (Launiainen et al. Hydrological and Earth System Sciences, 2019)

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