Simple Waterpix model based on Water Balance
SIMPLIFIED VERSION of WaterPix. (E. Salvadore, 2019)
The software computes a vertical water balance at the pixel level using remote sensing inputs and it is a simplified version of the WaterPix model. Main inputs, calibration parameters and outputs with their characteristics are listed in the table below.
| Inputs |
|---|
| Variable |
| Precipitation |
| Actual Evapotranspiration |
| LAI |
| SWI –soil water index- |
| SWIo –SWI first day of the month- |
| SWIx –SWI last day of the month- |
| ET green |
| ET blue |
| Interception |
| Runoff Ratio (SRO/TRO) |
| Saturated Water Content |
| Root depth |
| Land use land cover |
| Parameters |
| Name |
| Rootdepth_par |
| Min Runoff ratio |
| Filter_par |
| Outputs |
| Variable |
| SRO |
| ΔSRO |
| BF |
| ΔBF |
| RO |
| ΔSM |
| perc |
| Δperc |
| Supply |
The main fluxes considered by the model are:
There are five main computational steps:
(1) Compute ΔSM as a function of ASCAT data, root depth and LAI
Similarly we compute for the last day of the month and for the monthly average. This equation is based on Bastiaanssen et al., 2012.
Then 
(2) Estimation of Water Supply for blue pixels.
Assumption of consumed fraction is made for each land use class as follow:
| Land use class | Consumed fraction |
|---|---|
| Forest | 1.00 |
| Scrubland | 1.00 |
| Rainfed crops | 1.00 |
| Forest plantations | 1.00 |
| Natural water bodies | 0.15 |
| Wetland | 0.15 |
| Natural grassland | 0.70 |
| Other (non-manmade) | 0.40 |
| Irrigated crops | 0.80 |
| Managed water bodies | 0.40 |
| Other | 0.40 |
| Residential | 1.00 |
| Greenhouses | 0.95 |
| Aquaculture | 0.20 |
This values can be adjusted in calibration phase.
(3) Estimate surface runoff.
The computation is based on a modified version of the SCS flow equation (Schaake et al., 1996; Choudhury & DiGirolamo, 1998).
Green component in green pixels:
Surface runoff:
Incremental surface runoff is computed as:
(4) Estimate percolation as the residual of the root zone water balance.
Perc=P+supply−ET−∆SM−SRO
To compute the incremental percolation we estimate the green component of percolation in blue pixels:
Percg=P−ETg−∆SM−SROg
Then: ∆perc=Perc−Percg=supply−∆RO−ETb
(5) Estimate base flow as a function of surface runoff and runoff ratio.
Runoff ratio r was distributed over the months using the filter_par and the minimum r parameter.
References
Bastiaansen, W. G. M., Cheema, M. J. M. Immerzeel, W. W., Miltenburg, I. J., and Pelgrum, 2012. Surface energy balance and actual evapotranspiration of the transboundary Indus Basin estimated from satellite measurements and the ETLook model. Water Resources Research, Vol. 48, W11512, doi: 10.1029/2011WR010482.
Choudhury, B. J., and DiGirolamo, N. E., 1998. A biophysical process-based estimate of global land surface evaporation using satellite and ancillary data. I. Model description and comparison with observations. Journal of Hydrology, 205, pp. 164-185.
Schaake, J. C., Koeren, V. I., and Duan, Q.-Y., 1996. Simple water balance model for estimating runoff at different spatial and temporal scales. Journal of Geophysical Research, Vol. 101, No. D3, pp. 7461-7475.