MARRMOT_16

Implementation

MARRMoT v2.1.1 rev eeb7e15 m_16_newzealand2_8p_2s; standardized continuous structure, not original model

  • Time step: daily

  • Backend: octave-cli + Octave optim

  • Calibrated parameters: 8

  • Temperature required: no

Inspect the exact implementation.

Parameters and initial configuration

Parameter

Supported calibration range

Default

p01

0 to 5

2.5

p02

1 to 2000

1000.5

p03

0.05 to 0.95

0.5

p04

0.05 to 0.95

0.5

p05

0 to 1

0.5

p06

1 to 5

3.0

p07

0 to 1

0.5

p08

1 to 120

60.5

s01

Fixed initial/configuration value

0.0

s02

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;
            s1max   = theta(1);     % Maximum interception storage [mm] 
            s2max   = theta(2);     % Maximum soil moisture storage [mm] 
            sfc     = theta(3);     % Field capacity as fraction of maximum soil moisture [-]
            m       = theta(4);     % Fraction forest [-]
            a       = theta(5);     % Subsurface runoff coefficient [d-1]
            b       = theta(6);     % Runoff non-linearity [-]
            tcbf    = theta(7);     % Baseflow runoff coefficient [d-1]
            
            % delta_t
            delta_t = obj.delta_t;
            
            % unit hydrographs and still-to-flow vectors
            uhs = obj.uhs;
            uh = uhs{1};
            
            % 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_eint = evap_1(S1,Ep,delta_t);
            flux_qtf  = interception_1(P,S1,s1max);
            flux_veg  = evap_6(m,sfc,S2,s2max,Ep,delta_t);
            flux_ebs  = evap_5(m,S2,s2max,Ep,delta_t);
            flux_qse  = saturation_1(flux_qtf,S2,s2max);
            flux_qss  = interflow_9(S2,a,sfc*s2max,b,delta_t);
            flux_qbf  = baseflow_1(tcbf,S2);
            flux_qt   = route(flux_qse + flux_qss + flux_qbf, uh);

            % stores ODEs
            dS1 = P - flux_eint - flux_qtf;
            dS2 = flux_qtf - flux_veg - flux_ebs -...
                  flux_qse - flux_qss - flux_qbf;
            
            % outputs
            dS = [dS1 dS2];
            fluxes = [flux_eint, flux_qtf, flux_veg, flux_ebs,...
                      flux_qse,  flux_qss, flux_qbf, flux_qt];
        end
        
        % STEP runs at the end of every timestep.
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] = 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_6(p1,p2,S,Smax,Ep,dt)
%evap_6 evaporation based on scaled current water storage, a wilting point,
%a constraining factor and 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:  Transpiration from vegetation at the potential rate if 
%               storage is above a wilting point and scaled by relative 
%               storage if not
% Constraints:  Ea <= Ep
%               Ea <= S/dt
% @(Inputs):    p1   - fraction vegetated area [-]
%               p2   - 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([p1.*Ep,p1*Ep*S./(p2*Smax),S/dt]);

end
function [out] = evap_5(p1,S,Smax,Ep,dt)
%evap_5 evaporation based on scaled current water storage, for a fraction
%of the surface

% 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 from bare soil scaled by relative storage
% Constraints:  Ea <= Ep
%               Ea <= S/dt
% @(Inputs):    p1   - fraction of area that is bare soil [-]
%               S    - current storage [mm]
%               Smax - maximum storage [mm]
%               Ep   - potential evapotranspiration rate [mm/d]
%               dt   - time step size [d]

out = max(min((1-p1).*S./Smax.*Ep,S/dt),0);

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] = interflow_9(S,p1,p2,p3,dt)
%interflow_9 

% 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 if storage exceeds a threshold
% Constraints:  f <= S-p2
%               S-p2 >= 0     prevents numerical issues with complex numbers
% @(Inputs):    p1   - time coefficient [d-1]
%               p2   - storage threshold for flow generation [mm]
%               p3   - exponential scaling parameter [-]    
%               S    - current storage [mm]
%               dt   - time step size [d]

out = min(max((S-p2)/dt,0),(p1.*max(S-p2,0)).^p3);

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 [ 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] = 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_16").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.