A constraint-based search algorithm for parameter identification of environmental models

Hydrology and Earth System Sciences

Volumn 18, Issue 12, 2014, Pages 4861-4870

  Gharari, S ^a,b   Shafiei, M ^a,c   Hrachowitz, M ^a   Kumar, R ^d   Fenicia, F ^a,e   Gupta, H V ^f   Savenije, H H G ^a  

^a DELFT UNIVERSITY OF TECHNOLOGY   (Netherlands)

^b Public Research Center Gabriel Lippmann   (Luxembourg)

^c FERDOWSI UNIVERSITY OF MASHHAD   (Iran)

^d HELMHOLTZ CENTRE FOR ENVIRONMENTAL RESEARCH UFZ   (Germany)

^e SWISS FEDERAL INSTITUTE OF AQUATIC SCIENCE AND TECHNOLOGY   (Switzerland)

^f UNIVERSITY OF ARIZONA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CATCHMENTS; IDENTIFICATION (CONTROL SYSTEMS); LEARNING ALGORITHMS; RUNOFF;

CATCHMENT FUNCTIONS; ENVIRONMENTAL MODEL; ENVIRONMENTAL SYSTEMS; PARAMETER CONSTRAINTS; PREDICTIONS IN UNGAUGED BASINS; PRIOR UNCERTAINTIES; PROCESS CONSTRAINTS; RAINFALL-RUNOFF MODELS;

PARAMETER ESTIMATION;

ALGORITHM; CALIBRATION; CATCHMENT; ENVIRONMENTAL MODELING; PARAMETERIZATION; PREDICTION; RAINFALL-RUNOFF MODELING;

EID: 84916910034     PISSN: 10275606     EISSN: 16077938     Source Type: Journal    
DOI: 10.5194/hess-18-4861-2014     Document Type: Article

References (41)

1. Anderson, R. M., Koren, V. I., and Reed, S. M.: Using SSURGO data to improve Sacramento Model a priori parameter estimates, J. Hydrol., 320, 103-116, doi:10.1016/j.jhydrol.2005.07.020, 2006.
2. Bastidas, L. A., Gupta, H. V., Sorooshian, S., Shuttleworth, W. J., and Yang, Z. L.: Sensitivity analysis of a land surface scheme using multicriteria methods, J. Geophys. Res.-Atmos., 104, 19481-19490, doi:10.1029/1999JD900155 , 1999.
3. Beven, K.: Rainfall-Runoff Modelling, The Primer, JohnWiley and Sons, 2001.
4. Birkel, C., D., T., Dunn, S., and Soulsby, C.: Using time domain and geographic source tracers to conceptualize streamf low generation processes in lumped rainfall-runoff models, Water Resour. Res., 47, W02515, doi:10.1029/2010WR009547, 2011.
5. Boyle, D. P., Gupta, H. V., and Sorooshian, S.: Toward improved calibration of hydrologic mo dels: Combining the strengths of manual and automatic methods, Water Resour. Res., 36, 3663-3674, doi:10.1029/2000WR900207, 2000.
6. Boyle, D. P., Gupta, H. V., Sorooshian, S., Koren, V., Zhang, Z., and Smith, M.: Toward improved streamflow forecasts: value of semidistributed modeling, Water Resour. Res., 37, 2749-2759, doi:10.1029/2000WR000207, 2001.
7. Bulygina, N. and Gupta, H.: Estimating the uncertain mathematic al structure of a water balance model via Bayesian data assimilation, Water Resour. Res., 45, W00B13, doi:10.1029/2007WR006749, 2009.
8. Bulygina, N. and Gupta, H.: How Bayesian data assimilation can be used to estimate the mathematical structure of a model, Stoch. Environ. Res. Risk A., 24, 925- 937, doi:10.1007/s00477-010-0387-y, 2010.
9. Bulygina, N. and Gupta, H.: Correcting the mathematical structure of a hydrological model via Bayesian data assimilation, Water Resour. Res., 47, W05514, doi:10.1029/2010WR009614, 2011.
10. Efstratiadis, A. and Koutsoyiannis, D.: One decade of multi-objective calibration approaches in hydrological modelling: a review, Hydrolog. Sci. J., 55, 58 -78, doi:10.1080/02626660903526292, 2010.
11. Fenicia, F., Savenije, H. H. G., Matgen, P., and Pfister, L.: Understanding catchment behavior through stepwise model concept improvement, Water Resour. Res., 44, W01402, doi:10.1029/2006WR005563, 2008.
12. Freer, J., McDonnell, J. J., Beven, K. J., Peters, N. E., Burns, D. A., Hooper, R. P., Aulenbach, B., and Kendall, C.: The role of bedrock topography on subsurface storm flow, Water Resour. Res., 38, 1269, doi:10.1029/2001WR000872, 2002.
13. Gao, H., Hrachowitz, M., Fenicia, F., Gharari, S., and Savenije, H. H. G.: Testing the realism of a topography-driven model (FLEXTopo) in the nested catchments of the Upper Heihe, China, Hydrol. Earth Syst. Sci., 18, 1895 -1915, doi:10.5194/hess-18-1895-2014, 2014.
14. Gharari, S., Hrachowitz, M., Fenicia, F., and Savenije, H. H. G.: Hydrological landscape classification: investigating the performance of HAND based landscape classifications in a central European meso-scale catchment, Hydrol . Earth Syst. Sci., 15, 3275- 3291, doi:10.5194/hess-15-3275-2011, 2011.
15. Gharari, S., Hrachowitz, M., Fenicia, F., Gao, H., and Savenije, H. H. G.: Using expert knowledge to increase realism i n environmental system models can dramatically reduce the need for calibration, Hydrol. Earth Syst. Sci., 18, 4839- 4859, doi:10.5194/hess-18-4839-2014, 2014.
16. Götzinger, J. and Bárdossy, A.: Comparis on of four regionalisation methods for a distributed hydrological model, J. Hydrol., 333, 374-384, doi:10.1016/j.jhydrol.2006.09.008, 2007.
17. Gupta, H. V., Sorooshian, S., and Yapo, P. O.: Toward improve d calibration of hydrologic models: Multiple and noncommensurable measures of information,Water Resour. Res., 34, 751-763, doi:10.1029/97WR03495, 1998.
18. Gupta, H. V., Bastidas, L. A., Sorooshian, S., Shuttleworth, W. J., and Yang, Z. L.: Parameter estimation of a land surface scheme using multicriteria methods, J. Geophys. Res.-Atmos., 104, 19491-19503, doi:10.1029/1999JD900154, 1999.
19. Hrachowitz, M., Savenije, H., Bogaard, T. A., Tetzlaff, D., and Soulsby, C.: What can flux tracking teach us about water age distribution patterns and their temporal dynamics?, Hydrol. Earth Syst. Sci., 17, 533 -564, doi:10.5194/hess-17-533-2013, 2013.
20. Hrachowitz, M., Fovet, O., Ruiz, L., Euser, T., Gharari, S., Nijzink, R., Freer, J., Savenije, H. H. G., and Gascuel-Odoux, C.: Process consistency in models: The importance of system signatures, expert knowledge, and process complexity,Water Resour. Res., 50, 7445- 7469, doi:10.1002/2014WR015484, 2014.
21. Hu ghes, D. A., Andersson, L., Wilk, J., and Savenije, H. H.: Regional calibration of the Pitman model for the Okavango River, J. Hydrol., 331, 30-42, doi:10.1016/j.jhydrol.2006.04.047, 2006.
22. Kapangaziwiri E.,Hughes D.,Wagener T., Incorporating uncertainty in hydrological predictions for gauged and ungauged basins in southern Africa, Hydrolog. Sci. J., 57, 1000-1019,doi 10.1080/02626667.2012.690881, 2012.
23. Khu, S. T. and Madsen, H.: Multiobjective calibration with Pareto preference ordering: An application to rainfallrunoff model calibration, Water Resour. Res., 41, W03004, doi:10.1029/2004WR003041, 2005.
24. Kling, H. and Gupta, H.: On the development of regionalization relationships for lumped watershed models: The impact of ignoring sub-basin scale variability, J. Hydrol., 373, 337-351, doi:10.1016/j.jhydrol.2009.04.031, 2009.
25. Koren, V., Smith, M.,Wang, D., and Zhang, Z.: Use of soil property data in the derivation of conceptual rainfall-runoff model parameters, in: 15th Conference on Hydrology, Long Beach, California, American Meteorological Society, 2000.
26. Koren, V., Smith, M., and Duan, Q.: Use of a priori parameter estimates in the derivation of spatially consistent parameter sets of rainfall-runoff models, Water Science and Application, 6, 239-254, 2003.
27. Kumar, R., Samaniego, L., and Attinger, S.: The effects of spatial discretization and model parameterization on the prediction of extreme runoff characteristics, J. Hydrol., 392, 54- 69, doi:10.1016/j.jhydrol.2010.07.047, 2010.
28. Kumar, R., Samaniego, L., and Attinger, S.: Implications of distributed hydrologic model parameterization on water fluxes at multiple scales and locations,Water Resour. Res., 491, 360- 379, doi:10.1029/2012WR012195, 2013.
29. Martinez, G. F. and Gupta, H. V.: Hydrologic consistency as a basis for assessing complexity of monthly water balance models for the continental United States, Water Resour. Res., 47, W12540, doi:10.1029/2011WR011229, 2011.
30. Merz, R. and Blö schl, G.: Regionalisation of catchment model parameters, J. Hydrol., 287, 95-123, 2004.
31. Nash, J. E. and Sutcliffe, J. V.: River flow forecasting through conceptual models part I-A discussion of principles, J. Hydrol., 10, 282-290, doi:10.1016/0022-1694(70)90255-6, 1970.
32. Perrin, C., André assian, V., Serna, C. R., Mathevet, T., and Moine, N. L.: Discrete parameterization of hydr ological models: Evaluating the use of parameter sets libraries over 900 catchments, Water Resour. Res., 44, W08447, doi:10.1029/2007WR006579, 2008.
33. Pokhrel, P., Gupta, H. V., and Wagener, T.: A spatial regulari zation approach to parameter estimation for a distributed watershed model, Water Resour. Res., 44, W12419, doi:10.1029/2007WR006615, 2008.
34. Pokhrel, P., Yilmaz, K. K., and Gupta, H. V.: Multiple-criteria cal ibration of a distributed watershed model using spatial regularization and response signatures, J. Hydrol., 418-419, 49- 60, doi:10.1016/j.jhydrol.2008.12.004, 2012.
35. Samaniego, L., Bá rdossy, A., and Kumar, R.: Streamflow prediction in ungauged catchments using copula-based dissimilarity measures, Water Resour. Rese., 46, W02506, doi:10.1029/2008WR007695, 2010.
36. Seibert, J. and McDonnell, J. J.: On the dialog between exper imentalist and modeler in catchment hydrology: Use of soft data for multicriteria model calibration, Water Resour. Res., 38, 1241, doi:10.1029/2001WR000978, 2002.
37. Seibert, J. and McDonnell, J. J.: Gauging the Ungaug ed Basin: Relative Value of Soft and Hard Data, J. Hydrol. Eng., 0, A4014004, doi:10.1061/(ASCE)HE.1943-5584.0000861, 2013.
38. Wheater, H. S., Jakeman, A. J., and Beven, K. J.: Progress and directions in rainfall-runoff modeling, JohnWiley&Sons, Chichester, 1993.
39. Winsemius, H. C., Savenije, H. H. G., and Bastiaanssen, W. G. M.: Constraining model parameters on remo tely sensed evaporation: justification for distribution in ungauged basins?, Hydrol. Earth Syst. Sci., 12, 1403-1413, doi:10.5194/hess-12-1403-2008, 2008.
40. Yadav, M., Wagener, T., and Gupta, H.: Regionalization o f constraints on expected watershed response behavior for improved predictions in ungauged basins, Adv. Water Resour., 30, 1756-1774, doi:10.1016/j.advwatres.2007.01.005, 2007.
41. Zhang, Z., Wagener, T., Reed, P., and Bhushan, R.: Reducing uncertainty in predictions in ungauged basins by combining hydrologic indices regionalization and multiobjective optimization, Water Resour. Res., 44, W00B04, doi:10.1029/2008WR006833, 2008.