MARRMOT_34
Implementation
MARRMoT v2.1.1 rev eeb7e15 m_34_flexis_12p_5s; standardized continuous structure, not original model
Time step: daily
Backend: octave-cli + Octave optim
Calibrated parameters: 12
Temperature required: yes
Parameters and initial configuration
Parameter |
Supported calibration range |
Default |
|---|---|---|
|
1 to 2000 |
1000.5 |
|
0 to 10 |
5.0 |
|
0 to 1 |
0.5 |
|
0 to 20 |
10.0 |
|
0.05 to 0.95 |
0.5 |
|
1 to 5 |
3.0 |
|
1 to 15 |
8.0 |
|
0 to 1 |
0.5 |
|
0 to 1 |
0.5 |
|
0 to 5 |
2.5 |
|
-3 to 5 |
1.0 |
|
0 to 20 |
10.0 |
|
Fixed initial/configuration value |
0.0 |
|
Fixed initial/configuration value |
0.0 |
|
Fixed initial/configuration value |
0.0 |
|
Fixed initial/configuration value |
0.0 |
|
Fixed initial/configuration value |
0.0 |
Ranges/defaults are implementation contracts, not universal priors or a recommended basin calibration. Consult source comments for parameter units and coupling.
Governing equations
The following source is the exact model kernel used by this adapter. For MARRMoT it includes the state derivative and each referenced flux function; the solver and routing are described above. Original notices and source citations are retained in the files.
function [dS, fluxes] = model_fun(obj, S)
% parameters
theta = obj.theta;
smax = theta(1); % Maximum soil moisture storage [mm]
beta = theta(2); % Unsaturated zone shape parameter [-]
d = theta(3); % Fast/slow runoff distribution parameter [-]
percmax = theta(4); % Maximum percolation rate [mm/d]
lp = theta(5); % Wilting point as fraction of s1max [-]
nlagf = theta(6); % Flow delay before fast runoff [d]
nlags = theta(7); % Flow delay before slow runoff [d]
kf = theta(8); % Fast runoff coefficient [d-1]
ks = theta(9); % Slow runoff coefficient [d-1]
imax = theta(10); % Maximum interception storage [mm]
tt = theta(11); % Threshold temperature for snowfall/snowmelt [oC]
ddf = theta(12); % Degree-day factor for snowmelt [mm/d/oC]
% delta_t
delta_t = obj.delta_t;
% unit hydrographs and still-to-flow vectors
uhs = obj.uhs;
uh_f = uhs{1};
uh_s = uhs{2};
% stores
S1 = S(1);
S2 = S(2);
S3 = S(3);
S4 = S(4);
S5 = S(5);
% climate input
t = obj.t; % this time step
climate_in = obj.input_climate(t,:); % climate at this step
P = climate_in(1);
Ep = climate_in(2);
T = climate_in(3);
% fluxes functions
flux_ps = snowfall_1(P,T,tt);
flux_pi = rainfall_1(P,T,tt);
flux_m = melt_1(ddf,tt,T,S1,delta_t);
flux_peff = interception_1( flux_m+flux_pi ,S2,imax);
flux_ei = evap_1(S2,Ep,delta_t);
flux_ru = saturation_3(S3,smax,beta,flux_peff);
flux_eur = evap_3(lp,S3,smax,Ep,delta_t);
flux_rp = percolation_2(percmax,S3,smax,delta_t);
flux_rf = split_1(1-d,flux_peff-flux_ru);
flux_rs = split_1(d,flux_peff-flux_ru);
flux_rfl = route(flux_rf, uh_f);
flux_rsl = route(flux_rs + flux_rp, uh_s);
flux_qf = baseflow_1(kf,S4);
flux_qs = baseflow_1(ks,S5);
% stores ODEs
dS1 = flux_ps - flux_m;
dS2 = flux_m + flux_pi - flux_peff - flux_ei;
dS3 = flux_ru - flux_eur - flux_rp;
dS4 = flux_rfl - flux_qf;
dS5 = flux_rsl - flux_qs;
% outputs
dS = [dS1 dS2 dS3 dS4 dS5];
fluxes = [flux_ps, flux_pi, flux_m, flux_peff, flux_ei,...
flux_ru, flux_eur, flux_rp, flux_rf, flux_rs,...
flux_rfl, flux_rsl, flux_qf, flux_qs];
end
% STEP runs at the end of every timestep.
function [out] = snowfall_1(In,T,p1,varargin)
%snowfall_1
% Copyright (C) 2019, 2021 Wouter J.M. Knoben, Luca Trotter
% This file is part of the Modular Assessment of Rainfall-Runoff Models
% Toolbox (MARRMoT).
% MARRMoT is a free software (GNU GPL v3) and distributed WITHOUT ANY
% WARRANTY. See <https://www.gnu.org/licenses/> for details.
% Flux function
% ------------------
% Description: Snowfall based on temperature threshold
% Constraints: -
% @(Inputs): p1 - temperature threshold below which snowfall occurs [oC]
% T - current temperature [oC]
% In - incoming precipitation flux [mm/d]
% varargin(1) - smoothing variable r (default 0.01)
if size(varargin,2) == 0
out = In.*(smoothThreshold_temperature_logistic(T,p1));
elseif size(varargin,2) == 1
out = In.*(smoothThreshold_temperature_logistic(T,p1,varargin(1)));
end
end
function [out] = rainfall_1(In,T,p1,varargin)
%rainfall_1
% Copyright (C) 2019, 2021 Wouter J.M. Knoben, Luca Trotter
% This file is part of the Modular Assessment of Rainfall-Runoff Models
% Toolbox (MARRMoT).
% MARRMoT is a free software (GNU GPL v3) and distributed WITHOUT ANY
% WARRANTY. See <https://www.gnu.org/licenses/> for details.
% Flux function
% ------------------
% Description: Rainfall based on temperature threshold
% Constraints: -
% @(Inputs): p1 - temperature threshold above which rainfall occurs [oC]
% T - current temperature [oC]
% In - incoming precipitation flux [mm/d]
% varargin(1) - smoothing variable r (default 0.01)
if size(varargin,2) == 0
out = In.*(1-smoothThreshold_temperature_logistic(T,p1));
elseif size(varargin,2) == 1
out = In.*(1-smoothThreshold_temperature_logistic(T,p1,varargin(1)));
end
end
function [out] = melt_1(p1,p2,T,S,dt)
%melt_1
% Copyright (C) 2019, 2021 Wouter J.M. Knoben, Luca Trotter
% This file is part of the Modular Assessment of Rainfall-Runoff Models
% Toolbox (MARRMoT).
% MARRMoT is a free software (GNU GPL v3) and distributed WITHOUT ANY
% WARRANTY. See <https://www.gnu.org/licenses/> for details.
% Flux function
% ------------------
% Description: Snowmelt from degree-day-factor
% Constraints: f <= S/dt
% @(Inputs): p1 - degree-day factor [mm/oC/d]
% p2 - temperature threshold for snowmelt [oC]
% T - current temperature [oC]
% S - current storage [mm]
% dt - time step size [d]
out = max(min(p1*(T-p2),S/dt),0);
end
function [out] = interception_1(In,S,Smax,varargin)
%interception_1
% Copyright (C) 2019, 2021 Wouter J.M. Knoben, Luca Trotter
% This file is part of the Modular Assessment of Rainfall-Runoff Models
% Toolbox (MARRMoT).
% MARRMoT is a free software (GNU GPL v3) and distributed WITHOUT ANY
% WARRANTY. See <https://www.gnu.org/licenses/> for details.
% Flux function
% ------------------
% Description: Interception excess when maximum capacity is reached
% Constraints: -
% @(Inputs): In - incoming flux [mm/d]
% S - current storage [mm]
% Smax - maximum storage [mm]
% varargin(1) - smoothing variable r (default 0.01)
% varargin(2) - smoothing variable e (default 5.00)
if size(varargin,2) == 0
out = In.*(1-smoothThreshold_storage_logistic(S,Smax));
elseif size(varargin,2) == 1
out = In.*(1-smoothThreshold_storage_logistic(S,Smax,varargin(1)));
elseif size(varargin,2) == 2
out = In.*(1-smoothThreshold_storage_logistic(S,Smax,varargin(1),varargin(2)));
end
end
function [out] = evap_1(S,Ep,dt)
%evap_1
% Copyright (C) 2019, 2021 Wouter J.M. Knoben, Luca Trotter
% This file is part of the Modular Assessment of Rainfall-Runoff Models
% Toolbox (MARRMoT).
% MARRMoT is a free software (GNU GPL v3) and distributed WITHOUT ANY
% WARRANTY. See <https://www.gnu.org/licenses/> for details.
% Flux function
% ------------------
% Description: Evaporation at the potential rate
% Constraints: f <= S/dt
% @(Inputs): S - current storage [mm]
% Ep - potential evaporation rate [mm/d]
% dt - time step size
out = min(S/dt,Ep);
end
function [out] = saturation_3(S,Smax,p1,In)
%saturation_3
% Copyright (C) 2019, 2021 Wouter J.M. Knoben, Luca Trotter
% This file is part of the Modular Assessment of Rainfall-Runoff Models
% Toolbox (MARRMoT).
% MARRMoT is a free software (GNU GPL v3) and distributed WITHOUT ANY
% WARRANTY. See <https://www.gnu.org/licenses/> for details.
% Flux function
% ------------------
% Description: Saturation excess from a store with different degrees of
% saturation (exponential variant)
% Constraints: -
% @(Inputs): S - current storage [mm]
% Smax - maximum contributing storage [mm]
% p1 - linear scaling parameter [-]
% In - incoming flux [mm/d]
out = (1-(1/(1+exp((S/Smax + 0.5)/p1)))).*In;
end
function [out] = evap_3(p1,S,Smax,Ep,dt)
%evap_3
% Copyright (C) 2019, 2021 Wouter J.M. Knoben, Luca Trotter
% This file is part of the Modular Assessment of Rainfall-Runoff Models
% Toolbox (MARRMoT).
% MARRMoT is a free software (GNU GPL v3) and distributed WITHOUT ANY
% WARRANTY. See <https://www.gnu.org/licenses/> for details.
% Flux function
% ------------------
% Description: Evaporation based on scaled current water storage and wilting point
% Constraints: f <= Ep
% f <= S/dt
% @(Inputs): p1 - wilting point as fraction of Smax [-]
% S - current storage [mm]
% Smax - maximum storage [mm]
% Ep - potential evapotranspiration rate [mm/d]
% dt - time step size [d]
out = min([S/(p1*Smax)*Ep,Ep,S/dt]);
end
function [out] = percolation_2(p1,S,Smax,dt)
%percolation_2
% Copyright (C) 2019, 2021 Wouter J.M. Knoben, Luca Trotter
% This file is part of the Modular Assessment of Rainfall-Runoff Models
% Toolbox (MARRMoT).
% MARRMoT is a free software (GNU GPL v3) and distributed WITHOUT ANY
% WARRANTY. See <https://www.gnu.org/licenses/> for details.
% Flux function
% ------------------
% Description: Percolation scaled by current relative storage
% Constraints: f <= S/dt
% @(Inputs): p1 - maximum percolation rate [mm/d]
% S - current storage [mm]
% Smax - maximum storage [mm]
% dt - time step size [d]
out = min(S/dt,p1.*S/Smax);
end
function [out] = split_1(p1,In)
%split_1 flow splitting
% Copyright (C) 2019, 2021 Wouter J.M. Knoben, Luca Trotter
% This file is part of the Modular Assessment of Rainfall-Runoff Models
% Toolbox (MARRMoT).
% MARRMoT is a free software (GNU GPL v3) and distributed WITHOUT ANY
% WARRANTY. See <https://www.gnu.org/licenses/> for details.
% Flux function
% ------------------
% Description: Split flow (returns flux [mm/d])
% Constraints: -
% @(Inputs): p1 - fraction of flux to be diverted [-]
% In - incoming flux [mm/d]
out = p1.*In;
end
function [ flux_out ] = route(flux_in, uh)
% ROUTE calculates the output of a unit hydrograph at the current timestep
% after routing a flux through it.
% Copyright (C) 2019, 2021 Wouter J.M. Knoben, Luca Trotter
% This file is part of the Modular Assessment of Rainfall-Runoff Models
% Toolbox (MARRMoT).
% MARRMoT is a free software (GNU GPL v3) and distributed WITHOUT ANY
% WARRANTY. See <https://www.gnu.org/licenses/> for details.
% In:
% flux_in - input flux [1x1]
% uh - unit hydrograph [nx2]
% uh's first row contains coeficients to splut flow at each
% of n timesteps forward, the second row contains
% still-to-flow values.
%
% Out:
% flux_out - flux routed through the uh at this step [1x1]
%
flux_out = uh(1,1) * flux_in + uh(2,1);
end
function [out] = baseflow_1(p1,S)
% baseflow_1
% Copyright (C) 2019, 2021 Wouter J.M. Knoben, Luca Trotter
% This file is part of the Modular Assessment of Rainfall-Runoff Models
% Toolbox (MARRMoT).
% MARRMoT is a free software (GNU GPL v3) and distributed WITHOUT ANY
% WARRANTY. See <https://www.gnu.org/licenses/> for details.
% Flux function
% ------------------
% Description: Outflow from a linear reservoir
% Constraints: -
% @(Inputs): p1 - time scale parameter [d-1]
% S - current storage [mm]
out = p1.*S;
end
function [out] = smoothThreshold_temperature_logistic(T,Tt,r)
%smoothThreshold_temperature_logistic Logisitic smoother for temperature threshold functions.
% Copyright (C) 2018 Wouter J.M. Knoben
% This file is part of the Modular Assessment of Rainfall-Runoff Models
% Toolbox (MARRMoT).
% MARRMoT is a free software (GNU GPL v3) and distributed WITHOUT ANY
% WARRANTY. See <https://www.gnu.org/licenses/> for details.
% Smooths the transition of threshold functions of the form:
%
% Snowfall = { P, if T < Tt
% { 0, if T >= Tt
%
% By transforming the equation above to Sf = f(P,T,Tt,r):
% Sf = P * 1/ (1+exp((T-Tt)/r))
%
% Inputs:
% P : current precipitation
% T : current temperature
% Tt : threshold temperature below which snowfall occurs
% r : [optional] smoothing parameter rho, default = 0.01
%
% NOTE: this function only outputs the multiplier. This needs to be
% applied to the proper flux utside of this function.
% Check for inputs and use defaults if not provided
% NOTE: this is not very elegant, but it is more than a factor 10 faster then:
% if ~exist('r','var'); r = 0.01; end
if nargin == 2
r = 0.01;
end
% Calculate multiplier
out = 1 ./ (1+exp((T-Tt)/(r)));
end
function [out] = smoothThreshold_storage_logistic(S,Smax,r,e)
%smoothThreshold_storage_logistic Logisitic smoother for storage threshold functions.
% Copyright (C) 2018 Wouter J.M. Knoben
% This file is part of the Modular Assessment of Rainfall-Runoff Models
% Toolbox (MARRMoT).
% MARRMoT is a free software (GNU GPL v3) and distributed WITHOUT ANY
% WARRANTY. See <https://www.gnu.org/licenses/> for details.
% Smooths the transition of threshold functions of the form:
%
% Q = { P, if S = Smax
% { 0, if S < Smax
%
% By transforming the equation above to Q = f(P,S,Smax,e,r):
% Q = P * 1/ (1+exp((S-Smax+r*e*Smax)/(r*Smax)))
%
% Inputs:
% S : current storage
% Smax : maximum storage
% r : [optional] smoothing parameter rho, default = 0.01
% e : [optional] smoothing parameter e, default 5
%
% NOTE: this function only outputs the multiplier. This needs to be
% applied to the proper flux utside of this function.
%
% NOTE: can be applied for temperature thresholds as well (i.e. snow
% modules). This simply means that S becomes T, and Smax T0.
% Check for inputs and use defaults if not provided
% NOTE: this is not very elegant, but it is more than a factor 10 faster then:
% if ~exist('r','var'); r = 0.01; end
% if ~exist('e','var'); e = 5.00; end
if nargin == 2
r = 0.01;
e = 5.00;
elseif nargin == 3
r = r{1};
e = 5.00;
elseif nargin == 4
r = r{1};
e = e{1};
end
% Calculate multiplier
Smax = max(Smax,0); % this avoids numerical instabilities when Smax<0
if r*Smax == 0
out = 1 ./ (1+exp((S-Smax+r*e*Smax)/(r)));
else
out = 1 ./ (1+exp((S-Smax+r*e*Smax)/(r*Smax)));
end
end
Note
This standardized MARRMoT structure is not identical to the original named model. p01... follow exact source order; s01... are fixed initial stores, defaulting to zero. Octave + optim are required. Solver behavior can differ across runtime versions.
Simulation
from basinforge import Basin, get_model
basin = Basin.from_csv("basin.csv", basin_id="A", area_km2=1200,
q_unit="m3/s", timestep="daily")
q_mm = get_model("MARRMOT_34").simulate(basin)
q_m3s = basin.to_m3s(q_mm)
Supply your actual data and catchment area; temperature-dependent models require a temperature column. For non-daily models, choose an appropriate warmup in model steps.
See calibration, input requirements, sources and verification limitations.