1. bookVolumen 66 (2018): Edición 3 (September 2018)
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eISSN
1338-4333
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28 Mar 2009
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4 veces al año
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access type Acceso abierto

Conceptual model building inspired by field-mapped runoff generation mechanisms

Publicado en línea: 14 Aug 2018
Volumen & Edición: Volumen 66 (2018) - Edición 3 (September 2018)
Páginas: 303 - 315
Recibido: 07 Aug 2017
Aceptado: 10 Jan 2018
Detalles de la revista
License
Formato
Revista
eISSN
1338-4333
Primera edición
28 Mar 2009
Calendario de la edición
4 veces al año
Idiomas
Inglés
Abstract

Since the beginning of hydrological research hydrologists have developed models that reflect their perception about how the catchments work and make use of the available information in the most efficient way. In this paper we develop hydrologic models based on field-mapped runoff generation mechanisms as identified by a geologist. For four different catchments in Austria, we identify four different lumped model structures and constrain their parameters based on the field-mapped information. In order to understand the usefulness of geologic information, we test their capability to predict river discharge in different cases: (i) without calibration and (ii) using the standard split-sample calibration/ validation procedure. All models are compared against each other. Results show that, when no calibration is involved, using the right model structure for the catchment of interest is valuable. A-priori information on model parameters does not always improve the results but allows for more realistic model parameters. When all parameters are calibrated to the discharge data, the different model structures do not matter, i.e., the differences can largely be compensated by the choice of parameters. When parameters are constrained based on field-mapped runoff generation mechanisms, the results are not better but more consistent between different calibration periods. Models selected by runoff generation mechanisms are expected to be more robust and more suitable for extrapolation to conditions outside the calibration range than models that are purely based on parameter calibration to runoff data.

Keywords

Abbott, M., Bathurst, J., Cunge, J., O’Connell, P., Rasmussen, J., 1986. An introduction to the European Hydrological System - Systeme Hydrologique Europeen, “SHE”, 1: History and philosophy of a physically-based, distributed modelling system. Journal of Hydrology, 87, 45-59.10.1016/0022-1694(86)90114-9Search in Google Scholar

Bai, Y., Wagener, T., Reed, P.M., 2009. A top-down framework for watershed model evaluation and selection under uncertainty. Environemental Modelling and Software, 24, 901-916.10.1016/j.envsoft.2008.12.012Search in Google Scholar

Beven, K.J., 2001. How far can we go in distributed hydrological modelling? Hydrology and Earth System Sciences, 5, 1-12.10.5194/hess-5-1-2001Abierto DOISearch in Google Scholar

Beven, K.J., 2006. A manifesto for the equifinality thesis. Journal of Hydrology, 320, 1-2, 18-36. DOI: 10.1016/j.jhydrol.2005.07.007.10.1016/j.jhydrol.2005.07.007Abierto DOISearch in Google Scholar

Blöschl, G., 2005. Rainfall-runoff modeling of ungauged catchments. In: Anderson, M.G. (Ed.): Encyclopedia of Hydrological Sciences. John Wiley & Sons, Chichester, pp. 2061-2080.10.1002/0470848944.hsa140Search in Google Scholar

Blöschl, G., 2006. Hydrologic synthesis: Across processes, places, and scales. Water Resources Research, 42, 3, W03S02. DOI: 10.1029/2005WR004319. Blöschl, G., Sivapalan, M., Wagener, T., Viglione, A., Savenije, H.H., 2013. Runoff Prediction in Ungauged Basins - Synthesis across Processes, Places and Scales. Cambridge University Press, Cambridge, 484 p.10.1029/2005WR004319Search in Google Scholar

Caylor, K.K., D’Odorico, P., Rodriguez-Iturbe, I., 2006. On the ecohydrology of structurally heterogeneous semiarid landscapes. Water Resources Research, 42, 7. DOI: 10.1029/2005WR004683.10.1029/2005WR004683Abierto DOISearch in Google Scholar

Ehret, U., Gupta, H.V., Sivapalan, M., Weijs, S.V., Schymanski, S.J., Blöschl, G., Gelfan, A.N., Harman, C., Kleidon, A., Bogaard, T.A., Wang, D., Wagener, T., Scherer, U., Zehe, E., Bierkens, M.F.P., Di Baldassarre, G., Parajka, J., van Beek, L.P.H., van Griensven, A., Westhoff, M.C., WinsemiSearch in Google Scholar

us, H.C., 2014. Advancing catchment hydrology to deal with predictions under change. Hydrology and Earth System Sciences, 18, 649-671. DOI: 10.5194/hess-18-649-2014.10.5194/hess-18-649-2014Abierto DOISearch in Google Scholar

Falkenmark, M., Chapman, T., 1989. Comparative Hydrology: An Ecological Approach to Land and Water Resources. The Unesco Press, Paris, 479 p.Search in Google Scholar

Fenicia, F., Kavetski, D., Savenije, H.H., 2011. Elements of a flexible approach for conceptual hydrological modeling: 1. Motivation and theoretical development. Water Resources Research, 47, 13. DOI:10.1029/2010WR010174.10.1029/2010WR010174Abierto DOISearch in Google Scholar

Gaál, L., Szolgay, J., Kohnová, S., Parajka, J., Merz, R., Viglione, A., Blöschl, G., 2012. Flood timescales: Understanding the interplay of climate and catchment processes through comparative hydrology. Water Resources Research, 48, W04511. DOI: 10.1029/2011WR011509.10.1029/2011WR011509Abierto DOISearch in Google Scholar

Grayson, R.B., Blöschl, G. (Eds.) 2000. Spatial Patterns in Catchment Hydrology: Observation and Modelling, Cambridge University Press, Cambridge, 404 p.Search in Google Scholar

Gutknecht, D., Jolánkai, G., Skinner, K., 2008. Patterns and processes in the catchment. CAB International, Chapter 2, pp. 18-29.10.1079/9781845930028.0018Search in Google Scholar

He, X., Højberg, A.L., Jørgensen, F., Refsgaard, J.C., 2015. Assessing hydrological model predictive uncertainty using stochastically generated geological models. Hydrological Processes, 29, 19, 4293-4311. DOI: 10.1002/hyp.10488.10.1002/hyp.10488Abierto DOISearch in Google Scholar

Hellebrand, H., Müller, C., Matgen, P., Fenicia, F., Savenije, H., 2011. A process proof test for model concepts: Modelling the meso-scale. Physics and Chemistry of the Earth, 36, 42-53.10.1016/j.pce.2010.07.019Search in Google Scholar

Hogue, T.S., Bastidas, L.A., Gupta, H.V., Sorooshian, S., 2006. Evaluating model performance and parameter behavior for varying levels of land surface model complexity. Water Resources Research, 42, 8. DOI: 10.1029/2005WR004440.10.1029/2005WR004440Search in Google Scholar

Holländer, H.M., Blume, T., Bormann, H., Buytaert, W., Chirico, G.B., Exbrayat, J.-F., Gustafsson, D., Hölzel, H., Kraft, P., Stamm, C., Stoll, S., Blöschl, G., Flühler, H., 2009. Comparative predictions of discharge from an artificial catchment (Chicken Creek) using sparse data. Hydrology and Earth System Sciences, 13, 2069-2094. DOI: 10.5194/hess-13- 2069-2009.10.5194/hess-13-2069-2009Abierto DOISearch in Google Scholar

Hrachowitz, M., Fovet, O., Ruiz, L., Euser, T., Gharari, S., Nijzink, R., Freer, J.E., Savenije, H.H.G., Gascuel-Odoux, C., 2014. Process consistency in models: The importance of system signatures, expert knowledge, and process complexity. Water Resources Research, 50, 9, 7445-7469. DOI: 10.1002/2014WR015484.10.1002/2014WR015484Abierto DOISearch in Google Scholar

Kavetski, D., Kuczera, G., Franks, S.W., 2006a. Bayesian analysis of input uncertainty in hydrological modeling: 1. Theory. Water Resources Research, 42, 3, W03407. DOI: 10.1029/2005WR004368.10.1029/2005WR004368Abierto DOISearch in Google Scholar

Kavetski, D., Kuczera, G., Franks, S.W., 2006b. Bayesian analysis of input uncertainty in hydrological modeling: 2. Application. Water Resources Research, 42, 3, W03408. DOI: 10.1029/2005WR004376.10.1029/2005WR004376Abierto DOISearch in Google Scholar

Klemes, V., 1986. Operational testing of hydrological simulation models. Hydrological Sciences Journal - des Sciences Hydrologiques, 31, 1, 13-24. DOI: 10.1080/02626668609491024.10.1080/02626668609491024Abierto DOISearch in Google Scholar

Merz, R., Blöschl, G., 2009. A regional analysis of event runoff coefficients with respect to climate and catchment characteristics in Austria, Water Resources Research, 45, W01405. DOI: 10.1029/2008WR007163.10.1029/2008WR007163Abierto DOISearch in Google Scholar

Merz, R., Blöschl, G., Parajka, J., 2006. Spatio-temporal variability of event runoff coefficients. Journal of Hydrology, 331, 3-4, 591-604. DOI: 10.1016/j.jhydrol.2006.06.008.10.1016/j.jhydrol.2006.06.008Abierto DOISearch in Google Scholar

Milly, P.C.D., Dunne, K.A., 2002. Macroscale water fluxes 2. Water and energy supply control of their interannual variability. Water Resources Research, 38 10, 24-1-24-9. DOI: 10.1029/2001WR000760.10.1029/2001WR000760Abierto DOISearch in Google Scholar

Mullen, K., Ardia, D., Gil, D., Windover, D., Cline, J., 2011. DEoptim: an R package for global optimization by differential evolution. Journal of Statistical Software, 40, 6, 1-26.10.18637/jss.v040.i06Abierto DOISearch in Google Scholar

Müller, C., Hellebrand, H., Seeger, M., Schobel, S., 2009. Identification and regionalization of dominant runoff processes - a GIS-based and a statistical approach. Hydrology and Earth System Sciences, 13, 779-792.10.5194/hess-13-779-2009Search in Google Scholar

Nester, T., Kirnbauer, R., Parajka, J., Blöschl, G., 2012. Evaluating the snow component of a flood forecasting model. Hydrology Research, 43, 6, 762-779. DOI: 10.2166/nh.2012.041.10.2166/nh.2012.041Abierto DOISearch in Google Scholar

Nijzink, R.C., Samaniego, L., Mai, J., Kumar, R., Thober, S., Zink, M., Schäfer, D., Savenije, H.H.G, Hrachowitz, M., 2016. The importance of topography-controlled sub-grid process heterogeneity and semi-quantitative prior constraints in distributed hydrological models. Hydrology and Earth System Sciences, 20, 1151-1176. DOI: 10.5194/hess-20- 1151-2016.10.5194/hess-20-1151-2016Abierto DOISearch in Google Scholar

Parajka, J., Merz, R., Blöschl, G., 2003. Estimation of daily potential evapotranspiration for regional water balance modeling in Austria. In: 11th. International Poster Day Transport of Water, Chemicals and Energy in the Soil - Crop Canopy - Atmosphere System. Slovak Academy of Sciences, Bratislava, pp. 299-306.Search in Google Scholar

Pirkl, H., 2009. Hydrogeologische und geohydrologische Grundlagen für die ausgewählten Leiteinzugsgebiete - Unveröffentl. Bericht im Rahmen Projekt Hochwasser Tirol (HOWATI). Technical Report, Vienna.Search in Google Scholar

Pirkl, H., 2012. Untergrundabhängige Abflussprozesse. Kartierung und Quantifizierung für das Bundesland Tirol. Flächendeckende Aufnahme Osttirols. Endbericht. Unveröffentl. Bericht, Technical Report, Vienna.Search in Google Scholar

Rogger, M., Kohl, B., Pirkl, H., Viglione, A., Komma, J., Kirnbauer, R., Merz, R., Blöschl, G., 2012a. Runoff models and flood frequency statistics for design flood estimation in Austria - Do they tell a consistent story? Journal of Hydrology, 456-457, 30-43. DOI: 10.1016/j.jhydrol.2012.05.068.10.1016/j.jhydrol.2012.05.068Abierto DOISearch in Google Scholar

Rogger, M., Pirkl, H., Viglione, A., Komma, J., Kohl, B., Kirnbauer, R., Merz, R., Blöschl, G., 2012b. Step changes in the flood frequency curve: Process controls. Water Resources Research, 48, W05544. DOI: 10.1029/2011WR011187.10.1029/2011WR011187Abierto DOISearch in Google Scholar

Rosero, E., Yang, Z.-L., Wagener, T., Gulden, L.E., Yatheendradas, S., Niu, G.-Y., 2010. Quantifying parameter sensitivity, interaction, and transferability in hydrologically enhanced versions of the Noah land surface model over transition zones during the warm season. Journal of Geophysical Research- Atmospheres, 115, D3. DOI: 10.1029/2009JD012035.10.1029/2009JD012035Abierto DOISearch in Google Scholar

Salinas, J.L., Kiss, A., Viglione, A., Viertl, R., Blöschl, G., 2016. A fuzzy Bayesian approach to flood frequency estimation with imprecise historical information. Water Resources Research, 52, 9, 6730-6750. DOI: 10.1002/2016WR019177.10.1002/2016WR019177509163627840456Abierto DOISearch in Google Scholar

Samuel, J.M., Sivapalan, M., Struthers, I., 2008. Diagnostic analysis of water balance variability: A comparative modeling study of catchments in Perth, Newcastle, and Darwin, Australia. Water Resources Research, 44, 6. DOI: 10.1029/2007WR006694.10.1029/2007WR006694Abierto DOISearch in Google Scholar

Savenije, H.H.G., 2009. The art of hydrology. Hydrology and Earth System Sciences, 13, 157-161.10.5194/hess-13-157-2009Search in Google Scholar

Savenije, H., 2010. Topography driven conceptual modelling (FLEX-Topo), Hydrology and Earth System Sciences, 14, 12, 2681-2692. DOI: 10.5194/hess-14-2681-2010, HESS Opinions.10.5194/hess-14-2681-2010Abierto DOISearch in Google Scholar

Van den Bos, R., Hoffmann, L., Juilleret, J., Matgen, P., Pfister, L., 2006. Regional runoff prediction through aggregation of first-order hydrological process knowledge a case study, Hydrological Sciences - Journal - des Sciences Hydrologiques, 51, 1021-1038. van Werkhoven, K., Wagener, T., Reed, P., Tang, Y., 2008. Characterization of watershed model behavior across a hydroclimatic gradient. Water Resources Research, 44, W01429. DOI: 10.1029/2007WR006271.10.1029/2007WR006271Abierto DOISearch in Google Scholar

van Werkhoven, K., Wagener, T., Reed, P., Tang, Y., 2009. Sensitivity- guided reduction of parametric dimensionality for multi- objective calibration of watershed models. Advances in Water Resources, 32, 8, 1154-1169. DOI: 10.1016/j.advwatres.2009.03.002.10.1016/j.advwatres.2009.03.002Search in Google Scholar

Wagener, T., Sivapalan, M., Troch, P., Woods, R., 2007. Catchment Classification and Hydrologic Similarity, Geography Compass, 1, 4, 901-931. DOI: 10.1111/j.1749-8198.2007.00039.x.10.1111/j.1749-8198.2007.00039.xAbierto DOISearch in Google Scholar

Winter, T.C., 2001. The concept of hydrologic landscapes. Journal of the American Water Resources Association, 37, 2, 335-349. DOI: 10.1111/j.1752-1688.2001.tb00973.x.10.1111/j.1752-1688.2001.tb00973.xAbierto DOISearch in Google Scholar

Wolock, D.M., Winter, T.C., McMahon, G., 2004. Delineation and evaluation of hydrologic-landscape regions in the United States using geographic information system tools and multivariate statistical analyses. Environmental Management, 34, 1, S71-S88. DOI: 10.1007/s00267-003-5077-9.10.1007/s00267-003-5077-916044554Abierto DOISearch in Google Scholar

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