Feature type
Changing existing functionality
Improvement Description
Dear Wflow,
I been successfully using a modified physical Rutter model at a daily time step in my numerous hydrological papers (Pollacco et al., 2022a, 2022b, 2013; Pollacco and Mohanty, 2012). To make the Rutter model in Wflow successful for a daily time step, one requires to fix a physical error in the Rutter interception model which overestimates rainfall interception.
The Wflow_RainfallInterception assumes that the vegetation is composed of 1 layers and does not account that vegetation is composed of layered foliage.
In the Wflow paper (van Verseveld et al., 2024) in Eq 13:
$$E_{canopy}^{t}=\min \left( S_{canopy}^{t}, E_{pot,total}^{t} \right) $$
I suggest to replace the equation following (Deardorff, 1978) which accounts for vegetation layer (without further introducing a parameter), which assumes that evaporation from a wet layered canopy is assumed to be proportional to the fraction of the canopy that is wet. The amended equation is as follow:
$$E_{canopy}^{t}=E_{pot,total}^{t}\min \left( \left( \frac{S_{canopy}^{t}}{S_{canopy,\max}} \right) ^{\frac{2}{3}},1 \right) $$
With kindness,
Joseph A.P. Pollacco
References
Deardorff, J.W., 1978. Efficient prediction of ground surface temperature and moisture, with inclusion of a layer of vegetation. J. Geophys. Res. 83, 1889. https://doi.org/10.1029/JC083iC04p01889
Pollacco, J.A.P., Fernandez-Galvez, J., Ackerer, P., Belfort, B., Lassabatere, L., Angulo-Jaramillo, R., Rajanayaka, C., Lilburne, L., Carrick, S., Peltzer, D.A., 2022a. HyPix: 1D physically based hydrological model with novel adaptive time-stepping management and smoothing dynamic criterion for controlling Newton-Raphson step. Environ. Model. Softw. 153, 105386. https://doi.org/10.1016/j.envsoft.2022.105386
Pollacco, J.A.P., Fernández-Gálvez, J., Rajanayaka, C., Zammit, S.C., Ackerer, P., Belfort, B., Lassabatere, L., Angulo-Jaramillo, R., Lilburne, L., Carrick, S., Peltzer, D.A., 2022b. Multistep optimization of HyPix model for flexible vertical scaling of soil hydraulic parameters. Environ. Model. Softw. 156, 105472. https://doi.org/10.1016/j.envsoft.2022.105472
Pollacco, J.A.P., Mohanty, B.P., 2012. Uncertainties of Water Fluxes in Soil-Vegetation-Atmosphere Transfer Models: Inverting Surface Soil Moisture and Evapotranspiration Retrieved from Remote Sensing. Vadose Zone J. 11. https://doi.org/10.2136/vzj2011.0167
Pollacco, J.A.P., Mohanty, B.P., Efstratiadis, A., 2013. Weighted objective function selector algorithm for parameter estimation of SVAT models with remote sensing data. Water Resour. Res. 49, 6959–6978. https://doi.org/10.1002/wrcr.20554
van Verseveld, W.J., Weerts, A.H., Visser, M., Buitink, J., Imhoff, R.O., Boisgontier, H., Bouaziz, L., Eilander, D., Hegnauer, M., ten Velden, C., Russell, B., 2024. Wflow_sbm v0.7.3, a spatially distributed hydrological model: from global data to local applications. Geosci. Model Dev. 17, 3199–3234. https://doi.org/10/gttd7g
Implementation Description
The following implementation is recommended:
- Option to use Rutter on a daily time step;
- Fix the Rutter interception model to accound for layered foliage.
Additional Context
No response
Feature type
Changing existing functionality
Improvement Description
Dear Wflow,
I been successfully using a modified physical Rutter model at a daily time step in my numerous hydrological papers (Pollacco et al., 2022a, 2022b, 2013; Pollacco and Mohanty, 2012). To make the Rutter model in Wflow successful for a daily time step, one requires to fix a physical error in the Rutter interception model which overestimates rainfall interception.
The Wflow_RainfallInterception assumes that the vegetation is composed of 1 layers and does not account that vegetation is composed of layered foliage.
In the Wflow paper (van Verseveld et al., 2024) in Eq 13:
I suggest to replace the equation following (Deardorff, 1978) which accounts for vegetation layer (without further introducing a parameter), which assumes that evaporation from a wet layered canopy is assumed to be proportional to the fraction of the canopy that is wet. The amended equation is as follow:
With kindness,
Joseph A.P. Pollacco
References
Deardorff, J.W., 1978. Efficient prediction of ground surface temperature and moisture, with inclusion of a layer of vegetation. J. Geophys. Res. 83, 1889. https://doi.org/10.1029/JC083iC04p01889
Pollacco, J.A.P., Fernandez-Galvez, J., Ackerer, P., Belfort, B., Lassabatere, L., Angulo-Jaramillo, R., Rajanayaka, C., Lilburne, L., Carrick, S., Peltzer, D.A., 2022a. HyPix: 1D physically based hydrological model with novel adaptive time-stepping management and smoothing dynamic criterion for controlling Newton-Raphson step. Environ. Model. Softw. 153, 105386. https://doi.org/10.1016/j.envsoft.2022.105386
Pollacco, J.A.P., Fernández-Gálvez, J., Rajanayaka, C., Zammit, S.C., Ackerer, P., Belfort, B., Lassabatere, L., Angulo-Jaramillo, R., Lilburne, L., Carrick, S., Peltzer, D.A., 2022b. Multistep optimization of HyPix model for flexible vertical scaling of soil hydraulic parameters. Environ. Model. Softw. 156, 105472. https://doi.org/10.1016/j.envsoft.2022.105472
Pollacco, J.A.P., Mohanty, B.P., 2012. Uncertainties of Water Fluxes in Soil-Vegetation-Atmosphere Transfer Models: Inverting Surface Soil Moisture and Evapotranspiration Retrieved from Remote Sensing. Vadose Zone J. 11. https://doi.org/10.2136/vzj2011.0167
Pollacco, J.A.P., Mohanty, B.P., Efstratiadis, A., 2013. Weighted objective function selector algorithm for parameter estimation of SVAT models with remote sensing data. Water Resour. Res. 49, 6959–6978. https://doi.org/10.1002/wrcr.20554
van Verseveld, W.J., Weerts, A.H., Visser, M., Buitink, J., Imhoff, R.O., Boisgontier, H., Bouaziz, L., Eilander, D., Hegnauer, M., ten Velden, C., Russell, B., 2024. Wflow_sbm v0.7.3, a spatially distributed hydrological model: from global data to local applications. Geosci. Model Dev. 17, 3199–3234. https://doi.org/10/gttd7g
Implementation Description
The following implementation is recommended:
Additional Context
No response