Twin experiment

This model was created from a very similar example, but with domain-decomposition added. The results should be the
came as for that experiment. Note that domain-decomposition does not work for delft3d version 4 on linux.

1D-channel
- grid 200x3 dx=500m L=100km
-
- 10min timestep
- initial wl 1m
- observations 66,132,198

truth:
- 1-jan-1991 to 17-1-1991
- depth -7m to -5m linear slope
- boundary M2 0.6m/0dgr S2 0.2m/0dgr
- 200m3/s upstream inflow
- manning 0.02 (m=1:66), 0.023 (m=67:132), 0.026 (m=133:200)

first-gues:
- depth 1m deeper
- boundary M2 0.6m/0dgr S2 0.1m/0dgr
- manning +0.005
- delete first day from obs 48values

ObsID		Num of data		Min		Max		Bias		STD		RMS
 -------------------------------------------------------------------------------------------------------------------------------------------
 STATION02.waterlevel		97	-0.05769823290252685	0.15243836695289611	0.06646231492640034	0.06381258570051675	0.09190922446917307
 STATION03.waterlevel		97	-0.019720557567596386	0.23311161918315887	0.0980724825065372	0.08101202903855025	0.1269389672537712
 STATION01.waterlevel		97	-0.10562171675109866	0.11844644384391308	0.033201351641527835	0.0630232707490217	0.0709458571545207
 -------------------------------------------------------------------------------------------------------------------------------------------

depth only
===================================================================
SimulationKwadraticCostfunction: optimal results
    number of evaluations: 5
    all cost values:
        [574.126,1.223E3,140.587,134.804,134.213]
    all parameter values
        [0,0.5,-0.734,-0.8,-0.825]
    number of observations: 291
    best cost:
        cost = 134.213
    best parameters:
        
        Params - containing:
           depth= -0.825
===================================================================
ObsID		Num of data		Min		Max		Bias		STD		RMS
 -------------------------------------------------------------------------------------------------------------------------------------------
 STATION02.waterlevel		97	-0.032597531782150246	0.09698585193037987	0.02353430683738549	0.038223267171623165	0.04471934378736168
 STATION03.waterlevel		97	-0.02901331699752807	0.15513668864440916	0.03052590479522601	0.04020610985829039	0.050315970254781184
 STATION01.waterlevel		97	-0.050791257736110686	0.09914643285728693	0.013182287387390782	0.04728599580216731	0.04885372974590482
 -------------------------------------------------------------------------------------------------------------------------------------------


depth and M2
===================================================================
SimulationKwadraticCostfunction: optimal results
    number of evaluations: 6
    all cost values:
        [574.126,577.127,839.461,1.942E3,19.062,8.357]
    all parameter values
        [0,0.05,0,0,0.052,0.041;0,0,10,0,-9.659,-7.987;0,0,0,0.9,-1.028,-0.915]
    number of observations: 291
    best cost:
        cost = 8.357
    best parameters:
        
        Params - containing:
           M2.Amplitude= 0.041
           M2.Phase= -7.987
           depth= -0.915
===================================================================

ObsID		Num of data		Min		Max		Bias		STD		RMS
 -------------------------------------------------------------------------------------------------------------------------------------------
 STATION02.waterlevel		97	-0.024277691633129123	0.02432624160385133	5.103550147048708E-4	0.010820168667506415	0.010776341802613828
 STATION03.waterlevel		97	-0.051218319332122786	0.0317988603935242	0.001732929384810205	0.013713248016467136	0.013752000688179198
 STATION01.waterlevel		97	-0.026715748287200913	0.02569934968948362	9.846527489116345E-4	0.011217751488278237	0.01120313309083894
 -------------------------------------------------------------------------------------------------------------------------------------------

Long run
change Tstop from/to
Tstop  =  5.7600000e+003
Tstop  =  2.3040000e+004 until 17-1-1991

Long calibration
SimulationKwadraticCostfunction: optimal results
    number of evaluations: 16
    all cost values:
        [5.281E3,5.865E3,4.912E3,4.439E3,5.298E3,1.054E4,108.591,7.838,3.242,1.473,1.458,1.459,1.459,1.459,1.458,1.457]
    all parameter values
        [0,0.05,0,0,0,0,0.018,1.881E-3,2.3E-3,1.615E-3,1.809E-3,1.677E-3,1.743E-3,1.776E-3,1.792E-3,1.96E-3;0,0,10,0,0,0,-1.583,0.047,0.301,0.371,0.415,0.416,0.415,0.415,0.415,0.414;0,0,0,0.05,0,0,0.09,0.099,0.101,0.101,0.101,0.101,0.101,0.101,0.101,0.101;0,0,0,0,10,0,3.661,-1.512,1.449,0.348,0.341,0.338,0.34,0.34,0.341,0.345;0,0,0,0,0,0.5,-0.974,-0.917,-0.925,-0.923,-0.922,-0.922,-0.922,-0.922,-0.922,-0.923]
    number of observations: 2019
    best cost:
        cost = 1.457
    best parameters:
        
        Params - containing:
           M2.Amplitude= 1.96E-3
           M2.Phase= 0.414
           S2.Amplitude= 0.101
           S2.Phase= 0.345
           depth= -0.923
 
ObsID		Num of data		Min		Max		Bias		STD		RMS
 -------------------------------------------------------------------------------------------------------------------------------------------
 STATION02.waterlevel		673	-0.003630226333618203	0.0029722713012695356	-6.454567594564689E-4	0.0010473242317012386	0.0012295822974197398
 STATION03.waterlevel		673	-0.009401301568984999	0.0027366625976561476	3.623513034574482E-4	0.0019158263014225688	0.001948392955636575
 STATION01.waterlevel		673	-0.007484325305938733	0.002578179718017548	-0.001078064828119935	0.0020887445841976443	0.0023491690054873856
 -------------------------------------------------------------------------------------------------------------------------------------------