1. bookVolume 67 (2019): Issue 3 (September 2019)
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1338-4333
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28 Mar 2009
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Finding behavioral parameterization for a 1-D water balance model by multi-criteria evaluation

Published Online: 26 Jun 2019
Volume & Issue: Volume 67 (2019) - Issue 3 (September 2019)
Page range: 213 - 224
Received: 30 Apr 2018
Accepted: 14 Nov 2018
Journal Details
License
Format
Journal
eISSN
1338-4333
First Published
28 Mar 2009
Publication timeframe
4 times per year
Languages
English

Allen, R.G., Pereira, L.S., Raes, D., Smith, M., others, 1998. Crop evapotranspiration-guidelines for computing crop water requirements. FAO Irrigation and Drainage Paper 56. FAO Rome 300, D05109.Search in Google Scholar

Anderson, M.C., Norman, J.M., Mecikalski, J.R., Otkin, J.A., Kustas, W.P., 2007. A climatological study of evapotranspiration and moisture stress across the continental United States based on thermal remote sensing: 1. Model formulation. J. Geophys. Res.-Atmospheres, 112, Article Number: D10117.10.1029/2006JD007506Search in Google Scholar

Antonetti, M., Buss, R., Scherrer, S., Margreth, M., Zappa, M., 2016. Mapping dominant runoff processes: an evaluation of different approaches using similarity measures and synthetic runoff simulations. Hydrol. Earth Syst. Sci., 20, 2929–2945. https://doi.org/10.5194/hess-20-2929-201610.5194/hess-20-2929-2016Open DOISearch in Google Scholar

Antonetti, M., Zappa, M., 2018. How can expert knowledge increase the realism of conceptual hydrological models? A case study based on the concept of dominant runoff process in the Swiss Pre-Alps. Hydrol. Earth Syst. Sci., 22, 4425–4447.10.5194/hess-22-4425-2018Open DOISearch in Google Scholar

Ayyoub, A., Er-Raki, S., Khabba, S., Merlin, O., Ezzahar, J., Rodriguez, J., Bahlaoui, A., Chehbouni, A., 2017. A simple and alternative approach based on reference evapotranspiration and leaf area index for estimating tree transpiration in semi-arid regions. Agric. Water Manag., 188, 61–68.10.1016/j.agwat.2017.04.005Search in Google Scholar

Bahremand, A., 2016. HESS Opinions: Advocating process modeling and de-emphasizing parameter estimation. Hydrol. Earth Syst. Sci., 20, 1433–1445.10.5194/hess-20-1433-2016Open DOISearch in Google Scholar

Behrens, T., Zhu, A.-X., Schmidt, K., Scholten, T., 2010. Multi-scale digital terrain analysis and feature selection for digital soil mapping. Geoderma, 155, 175–185. http://dx.doi.org/10.1016/j.geoderma.2009.07.01010.1016/j.geoderma.2009.07.010Open DOISearch in Google Scholar

Beven, K., 2006. A manifesto for the equifinality thesis. J. Hydrol., 320, 18–36.10.1016/j.jhydrol.2005.07.007Search in Google Scholar

Beven, K., 1979. A sensitivity analysis of the Penman-Monteith actual evapotranspiration estimates. J. Hydrol., 44, 169–190.10.1016/0022-1694(79)90130-6Open DOISearch in Google Scholar

Bie, W., Casper, M.C., Reiter, P., Vohland, M., 2015. Surface resistance calibration for a hydrological model using evapotranspiration retrieved from remote sensing data in Nahe catchment forest area. Proc. Int. Assoc. Hydrol. Sci., 368, 81–86. https://doi.org/10.5194/piahs-368-81-201510.5194/piahs-368-81-2015Open DOISearch in Google Scholar

Blöschl, G., 2001. Scaling in hydrology. Hydrol. Process., 15, 709–711.10.1002/hyp.432Search in Google Scholar

Bromley, J., Jackson, N.A., Clymer, O., Giacomello, A.M., Jensen, F.V., 2005. The use of Hugin® to develop Bayesian networks as an aid to integrated water resource planning. Environ. Model. Softw., 20, 231–242.10.1016/j.envsoft.2003.12.021Search in Google Scholar

Burgess, S.S., Adams, M.A., Turner, N.C., Beverly, C.R., Ong, C.K., Khan, A.A., Bleby, T.M., 2001. An improved heat pulse method to measure low and reverse rates of sap flow in woody plants. Tree Physiol., 21, 589–598.10.1093/treephys/21.9.58911390303Open DOISearch in Google Scholar

Campbell, G., Calissendorff, C., Williams, J., 1991. Probe for measuring soil specific heat using a heat-pulse method. Soil Sci. Soc. Am. J., 55, 291–293.10.2136/sssaj1991.03615995005500010052xOpen DOISearch in Google Scholar

Cash, D.W., Clark, W.C., Alcock, F., Dickson, N.M., Eckley, N., Guston, D.H., Jäger, J., Mitchell, R.B., 2003. Knowledge systems for sustainable development. Proc. Natl. Acad. Sci., 100, 8086–8091.10.1073/pnas.123133210016618612777623Open DOISearch in Google Scholar

Casper, M.C., Gronz, O., Gemmar, P., 2015. Process-oriented parameterisation and calibration of a water balance model. Hydrol. Wasserbewirtsch., 59, 136–144.Search in Google Scholar

Casper, M.C., Vohland, M., 2008. Validation of a large scale hydrological model with data fields retrieved from reflective and thermal optical remote sensing data – A case study for the Upper Rhine Valley. Phys. Chem. Earth Parts ABC, 33, 1061–1067. http://dx.doi.org/10.1016/j.pce.2008.06.00110.1016/j.pce.2008.06.001Open DOISearch in Google Scholar

Cullmann, J., Mishra, V., Peters, R., 2006. Flow analysis with WaSiMETH? model parameter sensitivity at different scales. Adv. Geosci., 9, 73–77.10.5194/adgeo-9-73-2006Search in Google Scholar

Droogers, P., Allen, R.G., 2002. Estimating reference evapotranspiration under inaccurate data conditions. Irrig. Drain. Syst., 16, 33–45.10.1023/A:1015508322413Search in Google Scholar

Durigon, A., Van Lier, Q.D.J., Metselaar, K., 2016. Forcing variables in simulation of transpiration of water stressed plants determined by principal component analysis. Int. Agrophysics, 30, 431–445.10.1515/intag-2016-0006Search in Google Scholar

Elfert, S., Bormann, H., 2010. Simulated impact of past and possible future land use changes on the hydrological response of the Northern German lowland ‘Hunte’ catchment. J. Hydrol., 383, 245–255.10.1016/j.jhydrol.2009.12.040Search in Google Scholar

Federer, C.A., Lash, D., 1978. Simulated streamflow response to possible differences in transpiration among species of hardwood trees. Water Resour. Res., 14, 1089–1097.10.1029/WR014i006p01089Open DOISearch in Google Scholar

Fenicia, F., McDonnell, J.J., Savenije, H.H., 2008a. Learning from model improvement: On the contribution of complementary data to process understanding. Water Resour. Res., 44, 6, Article Number: W06419.10.1029/2007WR006386Open DOISearch in Google Scholar

Fenicia, F., Savenije, H.H., Matgen, P., Pfister, L., 2008b. Understanding catchment behavior through stepwise model concept improvement. Water Resour. Res., 44, 1, Article Number: W01402.10.1029/2006WR005563Open DOISearch in Google Scholar

Fox, D.G., 1981. Judging air quality model performance. Bull. Am. Meteorol. Soc., 62, 599–609.10.1175/1520-0477(1981)062<0599:JAQMP>2.0.CO;2Open DOISearch in Google Scholar

Franks, S.W., Gineste, P., Beven, K.J., Merot, P., 1998. On constraining the predictions of a distributed model: the incorporation of fuzzy estimates of saturated areas into the calibration process. Water Resour. Res., 34, 787–797.10.1029/97WR03041Open DOISearch in Google Scholar

Garrigues, S., Boone, A., Decharme, B., Olioso, A., Albergel, C., Calvet, J.-C., Moulin, S., Buis, S., Martin, E., 2018. Impacts of the soil water transfer parameterization on the simulation of evapotranspiration over a 14-year Mediterranean crop succession. J. Hydro-meteorol., 19, 3–25.10.1175/JHM-D-17-0058.1Search in Google Scholar

Gharari, S., Hrachowitz, M., Fenicia, F., Gao, H., Savenije, H., 2014. Using expert knowledge to increase realism in environmental system models can dramatically reduce the need for calibration. Hydrol. Earth Syst. Sci., 18, 4839.10.5194/hess-18-4839-2014Open DOISearch in Google Scholar

Grayson, R., Blöschl, G., 2001. Summary of pattern comparison and concluding remarks. In: Grayson, R., Blöschl, G. (Eds): Spatial Patterns in Catchment Hydrology – Observations and Modelling. Cambridge University Press, Cambridge, UK, pp. 355–367.Search in Google Scholar

Grigoryan, G.V., Casper, M.C., Gauer, J., Vasconcelos, A.C., Reiter, P.P., 2010. Impact of climate change on water balance of forest sites in Rhineland-Palatinate, Germany. Adv. Geosci., 27, 37–43. https://doi.org/10.5194/adgeo-27-37-201010.5194/adgeo-27-37-2010Open DOISearch in Google Scholar

Gupta, H.V., Beven, K.J., Wagener, T., 2005. Model calibration and uncertainty estimation. In: Anderson, M. (Ed.): Encyclopedia of Hydrological Sciences, Vol. 3, Chapter 131, pp. 2015–2032.10.1002/0470848944.hsa138Search in Google Scholar

Gupta, H.V., Sorooshian, S., Yapo, P.O., 1998. Toward improved calibration of hydrologic models: Multiple and noncommensurable measures of information. Water Resour. Res., 34, 751–763.10.1029/97WR03495Open DOISearch in Google Scholar

Gurtz, J., Zappa, M., Jasper, K., Lang, H., Verbunt, M., Badoux, A., Vitvar, T., 2003. A comparative study in modelling runoff and its components in two mountainous catchments. Hydrol. Process., 17, 297–311.10.1002/hyp.1125Search in Google Scholar

Hasenmueller, E.A., Criss, R.E., 2013. Water balance estimates of evapotranspiration rates in areas with varying land use. In: Alexandris, S. (Ed.): Evapotranspiration-An Overview. IntechOpen, DOI: 10.5772/52811.10.5772/52811Open DOISearch in Google Scholar

Hassler, S.K., Weiler, M., Blume, T., 2018. Tree-, stand-and site-specific controls on landscape-scale patterns of transpiration. Hydrol. Earth Syst. Sci., 22, 13–30.10.5194/hess-22-13-2018Open DOISearch in Google Scholar

Haude, W., 1955. Zur Bestimmung der Verdunstung auf möglichst einfache Weise. Dt. Wetterdienst, Bad Kissingen.Search in Google Scholar

Holst, J., Grote, R., Offermann, C., Ferrio, J.P., Gessler, A., Mayer, H., Rennenberg, H., 2010. Water fluxes within beech stands in complex terrain. Int. J. Biometeorol., 54, 23–36.10.1007/s00484-009-0248-xOpen DOISearch in Google Scholar

Hrachowitz, M., Fovet, O., Ruiz, L., Euser, T., Gharari, S., Nijzink, R., Freer, J., Savenije, H., Gascuel-Odoux, C., 2014. Process consistency in models: The importance of system signatures, expert knowledge, and process complexity. Water Resour. Res., 50, 7445–7469.10.1002/2014WR015484Open DOISearch in Google Scholar

Jasper, K., 2001. Hydrological modelling of Alpine river catchments using output variables from atmospheric models (PhD Thesis). ETH Zurich.Search in Google Scholar

Jasper, K., Gurtz, J., Lang, H., 2002. Advanced flood forecasting in Alpine watersheds by coupling meteorological observations and forecasts with a distributed hydrological model. J. Hydrol., 267, 40–52.10.1016/S0022-1694(02)00138-5Search in Google Scholar

Juilleret, J., Iffly, J.-F., Hoffmann, L., Hissler, C., 2012. The potential of soil survey as a tool for surface geological mapping: a case study in a hydrological experimental catchment (Huewelerbach, Grand-Duchy of Luxembourg). Geologica Belgica, 15, 1–2, 36–41.Search in Google Scholar

Klok, E., Jasper, K., Roelofsma, K., Gurtz, J., Badoux, A., 2001. Distributed hydrological modelling of a heavily glaciated Alpine river basin. Hydrol. Sci. J., 46, 553–570.10.1080/02626660109492850Search in Google Scholar

Koch, J., Jensen, K.H., Stisen, S., 2015. Toward a true spatial model evaluation in distributed hydrological modeling: Kappa statistics, Fuzzy theory, and EOF-analysis benchmarked by the human perception and evaluated against a modeling case study. Water Resour. Res., 51, 1225–1246. https://doi.org/10.1002/2014WR01660710.1002/2014WR016607Open DOISearch in Google Scholar

Koch, J., Mendiguren, G., Mariethoz, G., Stisen, S., 2017. Spatial sensitivity analysis of simulated land surface patterns in a catchment model using a set of innovative spatial performance metrics. J. Hydrometeorol., 18, 1121–1142. https://doi.org/10.1175/JHM-D-16-0148.110.1175/JHM-D-16-0148.1Open DOISearch in Google Scholar

Koch, J., Siemann, A., Stisen, S., Sheffield, J., 2016. Spatial validation of large-scale land surface models against monthly land surface temperature patterns using innovative performance metrics. J. Geophys. Res. Atmospheres, 121, 5430–5452.10.1002/2015JD024482Search in Google Scholar

Köstner, B., Biron, P., Siegwolf, R., Granier, A., 1996. Estimates of water vapor flux and canopy conductance of Scots pine at the tree level utilizing different xylem sap flow methods. Theor. Appl. Climatol., 53, 105–113.10.1007/BF00866415Search in Google Scholar

Kramer, P.J., Boyer, J.S., 1995. Water Relations of Plants and Soils. Academic Press.10.1016/B978-012425060-4/50003-6Search in Google Scholar

Legates, D.R., McCabe, G.J., 1999. Evaluating the use of “goodness-of-fit” measures in hydrologic and hydroclimatic model validation. Water Resour. Res., 35, 233–241.10.1029/1998WR900018Search in Google Scholar

Livneh, B., 2012. Development of a unified land model with multi-criteria observational data for the simulation of regional hydrology and land-atmosphere interaction. PhD Thesis. University of Washington, Seattle, USA.Search in Google Scholar

Lu, P., Urban, L., Zhao, P., 2004. Granier’s thermal dissipation probe (TDP) method for measuring sap flow in trees: theory and practice. ACTA Bot. Sin. (Engl. Ed.), 46, 631–646.Search in Google Scholar

Martínez-Carreras, N., Krein, A., Gallart, F., Iffly, J.-F., Hissler, C., Pfister, L., Hoffmann, L., Owens, P.N., 2012. The influence of sediment sources and hydrologic events on the nutrient and metal content of fine-grained sediments (Attert River basin, Luxembourg). Water. Air. Soil Pollut., 223, 5685–5705.10.1007/s11270-012-1307-1Search in Google Scholar

Martínez-Carreras, N., Udelhoven, T., Krein, A., Gallart, F., Iffly, J.F., Ziebel, J., Hoffmann, L., Pfister, L., Walling, D.E., 2010. The use of sediment colour measured by diffuse reflectance spectrometry to determine sediment sources: application to the Attert River catchment (Luxembourg). J. Hydrol., 382, 49–63.10.1016/j.jhydrol.2009.12.017Search in Google Scholar

McKeen, S., Wilczak, J., Grell, G., Djalalova, I., Peckham, S., Hsie, E.-Y., Gong, W., Bouchet, V., Menard, S., Moffet, R., others, 2005. Assessment of an ensemble of seven real-time ozone forecasts over eastern North America during the summer of 2004. J. Geophys. Res.-Atmospheres, 110, Article Number: D21307.10.1029/2005JD005858Search in Google Scholar

Middelkoop, H., Daamen, K., Gellens, D., Grabs, W., Kwadijk, J.C., Lang, H., Parmet, B.W.A.H., Schädler, B., Schulla, J., Wilke, K., 2001. Impact of climate change on hydrological regimes and water resources management in the Rhine basin. Clim. Change, 49, 105–128.10.1023/A:1010784727448Search in Google Scholar

Mohajerani, H., Kholghi, M., Mosaedi, A., Farmani, R., Sadoddin, A., Casper, M., 2017. Application of Bayesian decision networks for groundwater resources management under the conditions of high uncertainty and data scarcity. Water Resour. Manag., 31, 1859–1879.10.1007/s11269-017-1616-7Open DOISearch in Google Scholar

Monteith, J., 1981. Evaporation and surface temperature. Q. J. R. Meteorol. Soc., 107, 1–27.10.1002/qj.49710745102Search in Google Scholar

Monteith, J., Szeicz, G., Waggoner, P., 1965. The measurement and control of stomatal resistance in the field. J. Appl. Ecol., 345–355.10.2307/2401484Open DOISearch in Google Scholar

Mualem, Y., 1974. A conceptual model of hysteresis. Water Resources Research, 10, 514–520.10.1029/WR010i003p00514Search in Google Scholar

Nash, J.E., Sutcliffe, J.V., 1970. River flow forecasting through conceptual models part I—A discussion of principles. J. Hydrol., 10, 282–290.10.1016/0022-1694(70)90255-6Search in Google Scholar

Paço, T.A., Pôças, I., Cunha, M., Silvestre, J.C., Santos, F.L., Paredes, P., Pereira, L.S., 2014. Evapotranspiration and crop coefficients for a super intensive olive orchard. An application of SIMDualKc and METRIC models using ground and satellite observations. J. Hydrol., 519, 2067–2080.10.1016/j.jhydrol.2014.09.075Search in Google Scholar

Pfister, L., Humbert, J., Hoffmann, L., 2000. Recent trends in rainfall-runoff characteristics in the Alzette river basin, Luxembourg. Clim. Change, 45, 323–337.10.1023/A:1005567808533Search in Google Scholar

Richards, L.A., 1931. Capillary conduction of liquids through porous mediums. Physics, 1, 318–333.10.1063/1.1745010Search in Google Scholar

Sauer, T., 2007. Modellierung von Bodenwasserhaushalt und Abflussprozessen auf der Plotskale in Abhängigkeit von Substrat und Landnutzung (Dissertation). University of Trier, Trier, Germany.Search in Google Scholar

Saugier, B., Granier, A., Pontailler, J., Dufrene, E., Baldocchi, D., 1997. Transpiration of a boreal pine forest measured by branch bag, sap flow and micrometeorological methods. Tree Physiol., 17, 511–519.10.1093/treephys/17.8-9.511Open DOISearch in Google Scholar

Savage, N., Agnew, P., Davis, L., Ordóñez, C., Thorpe, R., Johnson, C., O’Connor, F., Dalvi, M., 2013. Air quality modelling using the Met Office Unified Model (AQUM OS24-26): model description and initial evaluation. Geosci. Model Dev., 6, 353.10.5194/gmd-6-353-2013Search in Google Scholar

Schaap, M.G., Leij, F.J., Van Genuchten, M.T., 2001. Rosetta: A computer program for estimating soil hydraulic parameters with hierarchical pedotransfer functions. J. Hydrol., 251, 163–176.10.1016/S0022-1694(01)00466-8Search in Google Scholar

Schulla, J., 2017. Model Description WaSiM (Water balance Simulation Model), completely revised version 2017. Zür. Switz. Hydrol. Softw. Consult., 347.Search in Google Scholar

Schulla, J., 1997. Hydrologische Modellierung von Flussgebieten zur Abschätzung der Folgen von Klimaänderungen. PhD Thesis. ETH Zurich.Search in Google Scholar

Seibert, J., McDonnell, J.J., 2002. On the dialog between experimentalist and modeler in catchment hydrology: Use of soft data for multicriteria model calibration. Water Resour. Res., 38, 11, Article Number: 1241.10.1029/2001WR000978Open DOISearch in Google Scholar

Senapati, N., Jansson, P.-E., Smith, P., Chabbi, A., 2016. Modelling heat, water and carbon fluxes in mown grassland under multi-objective and multi-criteria constraints. Environ. Model. Softw., 80, 201–224.10.1016/j.envsoft.2016.02.025Search in Google Scholar

Sprenger, M., Seeger, S., Blume, T., Weiler, M., 2016. Travel times in the vadose zone: Variability in space and time. Water Resour. Res., 52, 5727–5754.10.1002/2015WR018077Open DOISearch in Google Scholar

Steinbrich, A., Leistert, H., Weiler, M., 2016. Model-based quantification of runoff generation processes at high spatial and temporal resolution. Environ. Earth Sci., 75, 1423.10.1007/s12665-016-6234-9Open DOISearch in Google Scholar

Teepe, R., Dilling, H., Beese, F., 2003. Estimating water retention curves of forest soils from soil texture and bulk density. J. Plant Nutr. Soil Sci., 166, 111–119.10.1002/jpln.200390001Search in Google Scholar

Van Genuchten, M.T., 1980. A closed-form equation for predicting the hydraulic conductivity of unsaturated soils 1. Soil Sci. Soc. Am. J., 44, 892–898.10.2136/sssaj1980.03615995004400050002xSearch in Google Scholar

Van Genuchten, M.T., Leij, F.J., Yates, S.R., Williams, J.R., 1991. The RETC code for quantifying the hydraulic functions of unsaturated soils. U.S. Salinity Laboratory, USDA, Riverside, California.Search in Google Scholar

Verbunt, M., Gurtz, J., Jasper, K., Lang, H., Warmerdam, P., Zappa, M., 2003. The hydrological role of snow and glaciers in alpine river basins and their distributed modeling. J. Hydrol., 282, 36–55.10.1016/S0022-1694(03)00251-8Search in Google Scholar

Vose, J.M., Harvey, G.J., Elliott, K.J., Clinton, B.D., 2003. Measuring and modeling tree and stand level transpiration. In: Lehr, J.H., Keeley, J. (Eds.): Water Encyclopedia, Volume 3, Surface and Agricultural Water. Wiley, pp. 732–740.Search in Google Scholar

Wagener, T., Boyle, D.P., Lees, M.J., Wheater, H.S., Gupta, H.V., Sorooshian, S., 2001. A framework for development and application of hydrological models. Hydrol. Earth Syst. Sci., 5, 13–26.10.5194/hess-5-13-2001Search in Google Scholar

Walker, G.R., Zhang, L., 2002. Plot Scale Models and their Application to Recharge Studies. Part 10 of Basics of Recharge and Discharge Series. CSIRO Publishing.10.1071/9780643105423Search in Google Scholar

Wendling, U., 1975. Zur Messung und Schätzung der potentiellen Verdunstung. Z. Für Meteorol., 25, 103–111.Search in Google Scholar

Willmott, C.J., 1982. Some comments on the evaluation of model performance. Bull. Am. Meteorol. Soc., 63, 1309–1313.10.1175/1520-0477(1982)063<1309:SCOTEO>2.0.CO;2Open DOISearch in Google Scholar

Wilson, K.B., Hanson, P.J., Mulholland, P.J., Baldocchi, D.D., Wullschleger, S.D., 2001. A comparison of methods for determining forest evapotranspiration and its components: sap-flow, soil water budget, eddy covariance and catchment water balance. Agric. For. Meteorol., 106, 153–168.10.1016/S0168-1923(00)00199-4Search in Google Scholar

Zehe, E., Ehret, U., Pfister, L., Blume, T., Schröder, B., Westhoff, M., Jackisch, C., Schymanski, S. J., Weiler, M., Schulz, K., Allroggen, N., Tronicke, J., van Schaik, L., Dietrich, P., Scherer, U., Eccard, J., Wulfmeyer, V., Kleidon, A., 2014. HESS Opinions: From response units to functional units: a thermodynamic reinterpretation of the HRU concept to link spatial organization and functioning of intermediate scale catchments. Hydrol. Earth Syst. Sci., 18, 4635–4655.10.5194/hess-18-4635-2014Open DOISearch in Google Scholar

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