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changes.txt
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Changelog and remarks
## 3 aug 2021
main_weekly.py
Moved all configurations to a configuration file, configuration_weekly.py
Created an option in the configuration file (calculateUpstreamTotals) which switches on or off the extra accu operations in subsurfacwateronelayer.py as well as interceptionuptomaxstore.py, which are only used for reporting (or possibly for budget checks).
main.py
Created an option in the configuration file (calculateUpstreamTotals) which switches on or off the extra accu operations in subsurfacwateronelayer.py as well as interceptionuptomaxstore.py, which are only used for reporting (or possibly for budget checks). They are also used for numpy reports but this was not tested thus far.
## 6 July 2021
Test for github
## 19 May 2021
Added main_weekly.py to the repo
## 21 March 2013
Create scenarios in pyhydroScenarios
Swaps:
swapAll:
alles op True
swapVeg:
** Op true:
leafAreaIndex=generalfunctions.swapValuesOfTwoRegions(areas,leafAreaIndex,True)
albedo=generalfunctions.swapValuesOfTwoRegions(areas,albedo,True)
maxStomatalConductance=generalfunctions.swapValuesOfTwoRegions(areas,maxStomatalConductance,True)
vegetationHeight=generalfunctions.swapValuesOfTwoRegions(areas,vegetationHeight,True)
** Op false
regolithThicknessHomogeneous=generalfunctions.swapValuesOfTwoRegions(areas,regolithThicknessHomogeneous,False)
initialSoilMoistureFractionFromDisk=generalfunctions.swapValuesOfTwoRegions(areas,initialSoilMoistureFractionFromDisk,False)
soilPorosityFraction=generalfunctions.swapValuesOfTwoRegions(areas,soilPorosityFraction,False)
limitingPointFraction=generalfunctions.swapValuesOfTwoRegions(areas,limitingPointFraction,False)
mergeWiltingPointFractionFS=generalfunctions.swapValuesOfTwoRegions(areas,mergeWiltingPointFractionFS,False)
fieldCapacityFraction=generalfunctions.swapValuesOfTwoRegions(areas,fieldCapacityFraction,False)
## 18 Februari 2013
Copied two new input maps from Noemi's directory
We asssume that incoming radiation is everywhere the same, except for shaded areas, there it is zero. To
allow for this I added shaded to the shading module, and this is used in main.py.
In Penman we import now LAI, as this is needed for the evapotranspiration calculation.
NOTE!!! For calibration we want two different timeseries for the two catchments. For the scenarios
we want the other one (one time series for both)! So this should be changed, then.
## 21 January 2010
Included evapotranspiration in main.py script
Corrected the units of the returned evapotranspiration in the evapotranspiration class (see bottom).
Included shading effect
## 2 April 2010
Included the timeseries files (main.py)
Replaced the interception module with the interceptionuptomaxstore module
Rewrote some minor things in main.py, particularly to prepare for map inputs
Wrote budgets for all components, see component classes and bottom of main.py, budgets
not yet 100% fine it seems. need to compare with subsurf module alone
## 4 April 2010
added fractionReceivedFlatSurface to shading.py and included this in main.py
to correct for solar angle in incoming shortwave radiation
included incomingShortwaveRadiationAtSurface to account for effect of topography on incoming
radiation (main.py)
## 6 April 2010
changed in main.py how evapotranspiration is dealt with: it takes it now first from the
interception store and the remainder from the subsurface store (if available)
extended the dem in the horizontan calculation (shading.py) else you get mv's at the edge
added more structured reports (see below)
## 9 April 2010
Added method to calculate clear sky solar radiation to penman module.
Modified main.py to deal with this change (how penman function is called).
Changed albedo input in penman module (is fixed over time).
Added the soil moisture reduction function to the subsurface module.
penman.py reads this and uses it to modify the conductance
Added new static map inputs to the penman module.
Added a major optimization scheme in shading.py to speed up run time. Horizontan
is precalculated for all angles and afterwards used each time step. This results in
a somewhat longer time to get the model started, but afterwards it is 5 times faster or so (per
timestep).
Changed names of reports in shading.py.
## 7 Feb 2010
Included gap fraction in interception module and tested it.
Added stuff for particle filtering.
Included calculation of reg. thickness:
- need to check slope calculation
Changed evapotranspiration module regarding canopy evap:
- module itself reports evapo with and without resistance
check whether also aerodynamic roughness needs to be changed
- main script calculates fraction of soil evapo based upon
canopy evapo
Changed evapotranspiration module regarding zero evapo during rainfall
- additional input
- used at bottom of evapotranspiration module
## 3 May 2012
Added a class in randomparameters.py to store the random parameters (the ones that are
calibrated). It writes the values over time, and the final value with .map extension.
By setting readDistributionOfParametersFromDisk=True or False it either generates random
maps or reads them from the folder indicated.
Added statements to select either random parameter values (for calibration) or to read the
parameter values from disk.
Added statements to swap properties of the two catchments.
# User manual
To run the model you need to copy the contents of the included pysolar.zip to the current
directory.
Use rosetta software to estimate values
## To do's:
Noemi:
Check new version of Penman module, in particular the radiation, I added reports that store these
outputs calculated by the module.
Run THIS model (no new inputs), and check the outputs on budgets etc. Change parameters such
that certain stores are on/off, and see whether fluxes and changes in stores are correct at
a given rainfall input.
Potential evapotranspiration flux returned from the Penman equation (evapotranspirationpenman.py)
is sometimes negative (see pef0* maps). This is strange. Find out cause. It most likely
occurs only when incoming short wave radiation is zero. Currently solved by
potentialEvapotranspirationFluxNoNegativeValues=max(0.0,potentialEvapotranspirationFlux) (main.py).
Reduction factor soil moisture, is this beta i (Eq. 8.40, van der Kwast, thesis) or is this
rs (Eq. 8.14, van der Kwast, thesis)? In the Word doc of Noemi it is proposed to use 8.14, however
I am almost sure Hans really uses 8.40 to represent 'shortage' of water resulting in reduced
evapotranspiration
enter correct start time in days hours.
enter correct location coordinates.
Derek:
Budget needs further attention.
Timeseries output we probably want. Use existing map converts or write new one.
Surface store, concept is a bit different from other stores
no evapotranspiration during rain??? Note that there are clouds anyway during rain.
albedo to init of penman
more inputs to penman
what about bare soil evapotranspiration??
penman: extra input wet /dry canopy
if wet: resistance is zero
else:calculate resistance:
get map with max r values
linear function between wilting point and limiting point, note that limiting point
is between wilting point and field capacity
in this map bare soil has zero r value ????
green and ampt infiltration
store remains full (no emptying of cumulative infiltration over time!!!)
Choose inputs that are random
- parameters
- inputs (eg precipitation?)
Modify options for reports
- all
- subset
- only for calibration..
- intervals
Random inputs selection
Create random values with flag either random or mean,
with additional mean argument, and
mean argument also used for reading maps from realizations
Select timesteps for filtering
- fixed interval plus
- days with rain
- and days after days with rain (?)
OR
- fixed interval
- each time step when Q is above threshold..
Create script to merge maps
## remarkts concerning the data preparation
We probably need very low (or zero) infiltration in main streams. Ie either Green and Ampt
ksat zero or zero soil depth.