MARRMOT_10
Implementation
MARRMoT v2.1.1 rev eeb7e15 m_10_susannah2_6p_2s; standardized continuous structure, not original model
Time step: daily
Backend: octave-cli + Octave optim
Calibrated parameters: 6
Temperature required: no
Parameters and initial configuration
Parameter |
Supported calibration range |
Default |
|---|---|---|
|
1 to 2000 |
1000.5 |
|
0.05 to 0.95 |
0.5 |
|
0.05 to 0.95 |
0.5 |
|
0 to 1 |
0.5 |
|
0 to 1 |
0.5 |
|
1 to 5 |
3.0 |
|
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;
sb = theta(1); % Maximum soil moisture storage [mm]
phi = theta(2); % Porosity [-]
fc = theta(3); % Field capacity as fraction of sb [-]
r = theta(4); % Fraction of recharge coefficient [-]
c = theta(5); % Subsurface flow constant [1/d]
d = theta(6); % Subsurface flow constant [-]
% delta_t
delta_t = obj.delta_t;
% stores
S1 = S(1);
S2 = S(2);
% 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_eus = evap_7(S1,sb,Ep,delta_t);
flux_rg = saturation_1(P,S1,(sb-S2)*fc/phi);
flux_se = excess_1(S1,(sb-S2)*fc/phi,delta_t);
flux_esat = evap_7(S2,sb,Ep,delta_t);
flux_qse = saturation_1(flux_rg+flux_se,S2,sb);
flux_qss = interflow_3((1-r)*c,d,S2,delta_t);
flux_qr = interflow_3(r*c,d,S2,delta_t);
flux_qt = flux_qse + flux_qss;
% stores ODEs
dS1 = P - flux_eus - flux_rg - flux_se;
dS2 = flux_rg + flux_se - flux_esat - ...
flux_qse - flux_qss - flux_qr;
% outputs
dS = [dS1 dS2];
fluxes = [flux_eus, flux_rg, flux_se, flux_esat,...
flux_qse, flux_qss, flux_qr, flux_qt];
end
% STEP runs at the end of every timestep
function [out] = evap_7(S,Smax,Ep,dt)
%evap_7 evaporation based on scaled current water storage, limited by
%potential rate.
% 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 scaled by relative storage
% Constraints: f <= S/dt
% @(Inputs): S - current storage [mm]
% Smax - maximum contributing storage [mm]
% Ep - potential evapotranspiration rate [mm/d]
% dt - time step size [d]
out = min(S./Smax.*Ep,S/dt);
end
function [out] = saturation_1(In,S,Smax,varargin)
%saturation_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: Saturation excess from a store that has reached maximum capacity
% 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] = excess_1(So,Smax,dt)
%excess_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: Storage excess when store size changes (returns flux [mm/d])
% Constraints: f >= 0
% @(Inputs): So - 'old' storage [mm]
% Smax - 'new' maximum storage [mm]
% dt - time step size [d]
out = max((So-Smax)/dt,0);
end
function [out] = interflow_3(p1,p2,S,dt)
%interflow_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: Non-linear interflow (variant)
% Constraints: f <= S
% S >= 0 - this avoids numerical issues with complex numbers
% @(Inputs): p1 - time delay [d-1]
% p2 - exponential scaling parameter [-]
% S - current storage [mm]
% dt - time step size [d]
out = min(p1*max(S,0)^(p2),max(S/dt,0));
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_10").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.