The power of multi-objective calibration: Two case studies with SWAT

Transcription

1 The power of multi-objective calibratio: Two case studies with SWAT Sader Huisma Thorste Pohlert, Lutz Breuer & Has-Georg Frede Justus-Liebig-Uiversität Gieße, Germay Istitut für Ladschaftsökologie ud Ressourcemaagemet

2 The power of multi-objective calibratio: A case study with SWAT Sader Huisma Thorste Pohlert, Lutz Breuer & Has-Georg Frede Justus-Liebig-Uiversität Gieße, Germay Istitut für Ladschaftsökologie ud Ressourcemaagemet

3 Itroductio to Calibratio Vrugt (2004)

4 Maual Calibratio Most widely used calibratio method Visual compariso of measured ad simulated data Semi-itiutive trial ad error process for parameter adjustmet Closeess implicitly evaluated with several (>3) criteria Excellet model calibratios, but maual calibratio... is highly labor-itesive (huma resources) is difficult to lear procedures are model-depedet results are user-depedet

5 Automatic Optimizatio Algorithms that optimize a objective fuctio by systematically searchig the parameter space accordig to a fixed set of rules Local search algorithms - Nelder ad Mead (Simplex) algorithm - Leveberg-Marquardt - Gauss-Newto Global search algorithms - Simulated Aealig - Geetic algorithms - Shuffled Complex Evolutio

6 Objective Fuctios Automatio of calibratio requires the formulatio of closeess measures (objective fuctios) RMSE = 1 ( d i o i ( θ )) i= 1 2 MAE = 1 i= 1 d i o i ( θ ) NS 1 1 i= 1 = 1 1 BIAS = ( d o ( θ )) ( di di ) i= 1 i= 1 i i d i o i 2 ( θ ) 2 TMVOL NSC = Number of sig chages 1 1 ( i) ( = moth day i j= 1 day i= 1 ) ( d o ( θ )) i i 2

7 Differet evaluatio criteria Gupta et al. (1998)

8 Differet output variables Seibert ad McDoell (2002) Calibratio agaist discharge (Q) with a high efficiecy (~0.93) Does a good fit to measured discharge result i good predictios of other state variables?

9 Right for the Wrog Reasos Seibert ad McDoell (2002)

10 Less Right for the Right Reasos Best overall agreemet for GW ad discharge Model efficiecy for discharge decreased from 0.93 to 0.84 Cosistecy with perceptual model strogly icreased Seibert ad McDoell (2002)

11 Multi-Objective Calibratio Differet objective fuctios result i differet optimal parameters Is there a optimal parameter set whe usig multiple objectives? The optimal parameter set for oe sigal might ot be the best parameter set for aother sigal Ca we fid a comprimise that is satisfactory for all sigals? Three commo approaches to multi-objective calibratio Pareto-optimal parameter sets Aggregatio of sigle objectives to a global objective criterio GLUE methodology

12 Calibratio Lysimeter Bradis Calibratio with 12 years of data for mea mothly percolatio, evapotraspiratio ad itrate leachig Calibratio agaist two evaluatio criteria (bias ad NS-efficiecy)

13 Pareto-Optimal Parameter Sets Yapo et al. (1998) Algorithms to fid Pareto frot are MOCOM-UA, MOSCEM-UA ad the approximatio of Madse (2000).

14 Pareto Frot: Multiple Criteria Excessive calibratio o oe evaluatio criteria leads to a detoriatio of other criteria

15 Pareto Frot: Multiple Variables Excessive calibratio o oe output variable leads to a detoriatio of other output variables

16 Aggregatio to Global Objective Criteria Pareto frot esitmatio more computatioally expesive tha sigle objective calibratio (10000 vs. 3000) Aggregatio to save computatio time: GOC j = i= 1, m f i ( OF i, j ) Weights are based o mea ad stadard deviatio of radom sample from parameter space

17 Aggregatio to Global Objective Criteria Aggregatio ofte leads to a good trade-off solutio, but provides o iformatio o how the strog the compromise is.

18 GLUE methodology May parameter combiatios that lead to acceptable simulatios (equifiality) Step 1: defie rages for each model parameter Step 2: defie acceptable Step 3: ru model Step 4: reject uacceptable Step 5: iterate util eough acceptable rus are obtaied

19 Results of GLUE Methodology I

20 Results of GLUE Methodology I Percolatio ad ET ca be simulated correctly despite iadequate represetatio of N (remais of the modular structure of SWAT).

21 Coclusios Use of multiple objectives makes you realize the deficiecies of sigle objective calibratio Aggregatio of objective fuctios is a relatively computatioally iexpesive method to fid a decet compromise solutio. More advaced methods ca idicate model deficiecies, model weakesses, etc.

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