MARRMOT_29

Implementation

MARRMoT v2.1.1 rev eeb7e15 m_29_hymod_5p_5s; standardized continuous structure, not original model

  • Time step: daily

  • Backend: octave-cli + Octave optim

  • Calibrated parameters: 5

  • Temperature required: no

Inspect the exact implementation.

Parameters and initial configuration

Parameter

Supported calibration range

Default

p01

1 to 2000

1000.5

p02

0 to 10

5.0

p03

0 to 1

0.5

p04

0 to 1

0.5

p05

0 to 1

0.5

s01

Fixed initial/configuration value

0.0

s02

Fixed initial/configuration value

0.0

s03

Fixed initial/configuration value

0.0

s04

Fixed initial/configuration value

0.0

s05

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], 
            b      = theta(2);     % Soil depth distribution parameter [-]
            a      = theta(3);     % Runoff distribution fraction [-]
            kf     = theta(4);     % Fast runoff coefficient [d-1]
            ks     = theta(5);     % Slow runoff coefficient [d-1]
            
            % delta_t
            delta_t = obj.delta_t;
            
            % 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_ea  = evap_7(S1,smax,Ep,delta_t);
            flux_pe  = saturation_2(S1,smax,b,P);
            flux_pf  = split_1(a,flux_pe);
            flux_ps  = split_1(1-a,flux_pe);
            flux_qf1 = baseflow_1(kf,S2);
            flux_qf2 = baseflow_1(kf,S3);
            flux_qf3 = baseflow_1(kf,S4);
            flux_qs  = baseflow_1(ks,S5);

            % stores ODEs
            dS1 = P - flux_ea - flux_pe;
            dS2 = flux_pf - flux_qf1;
            dS3 = flux_qf1 - flux_qf2;
            dS4 = flux_qf2 - flux_qf3;
            dS5 = flux_ps - flux_qs;
            
            % outputs
            dS = [dS1 dS2 dS3 dS4 dS5];
            fluxes = [flux_ea  flux_pe  flux_pf  flux_ps ...
                      flux_qf1 flux_qf2 flux_qf3 flux_qs];
        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_2(S,Smax,p1,In)
%saturation_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:  Saturation excess from a store with different degrees of saturation
% Constraints:  1-S/Smax >= 0       prevents numerical issues with complex
%                                   numbers
% @(Inputs):    S    - current storage [mm]
%               Smax - maximum contributing storage [mm]
%               p1   - non-linear scaling parameter [-]
%               In   - incoming flux [mm/d]

% NOTE: When stores are very slightly below or over their maximum, the
% exponent can push this function into regions where no feasible solutions
% exist. The min(max()) combination prevents this from happening. 

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

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 [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

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_29").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.