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Volume 21, issue 12 |
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Hydrol. Earth Syst. Sci., 21, 5987-6005, 2017
https://doi.org/10.5194/hess-21-5987-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-21-5987-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 21, 5987-6005, 2017
https://doi.org/10.5194/hess-21-5987-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-21-5987-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article 30 Nov 2017
Research article | 30 Nov 2017
Spatial pattern evaluation of a calibrated national hydrological model – a remote-sensing-based diagnostic approach
Gorka Mendiguren et al.Related authors
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Subject: Catchment hydrology | Techniques and Approaches: Remote Sensing and GIS
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Cited articles
Abbott, M. B., Bathurst, J. C., Cunge, J. A., O'Connell, P. E., and Rasmussen, J.: An introduction to the European Hydrological System – Systeme Hydrologique Europeen, “SHE”, 1: History and philosophy of a physically-based, distributed modelling system, J. Hydrol., 87, 45–59, https://doi.org/10.1016/0022-1694(86)90114-9, 1986.
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56, FAO, Rome, 300, D05109, 1998.
Berrisford, P., Dee, D. P., Poli, P., Brugge, R., Fielding, K., Fuentes, M., Kållberg, P. W., Kobayashi, S., Uppala, S., and Simmons, A.: The ERA-Interim archive Version 2.0, in: ERA Report Series, ECMWF, Shinfield Park, Reading, 23, 2011.
Bertoldi, G., Notarnicola, C., Leitinger, G., Endrizzi, S., Zebisch, M., Della Chiesa, S., and Tappeiner, U.: Topographical and ecohydrological controls on land surface temperature in an alpine catchment, Ecohydrology, 3, 189–204, https://doi.org/10.1002/eco.129, 2010.
Boegh, E., Thorsen, M., Butts, M. B., Hansen, S., Christiansen, J. S., Abrahamsen, P., Hasager, C. B., Jensen, N. O., van der Keur, P., Refsgaard, J. C., Schelde, K., Soegaard, H., and Thomsen, A.: Incorporating remote sensing data in physically based distributed agro-hydrological modelling, J. Hydrol., 287, 279–299, https://doi.org/10.1016/j.jhydrol.2003.10.018, 2004.
Bowen, I. S.: The ratio of heat losses by conduction and by evaporation from any water surface, Phys. Rev., 27, 779–787, https://doi.org/10.1103/PhysRev.27.779, 1926.
Breuning Madsen, H. and Platou, S. W.: Land Use Planning in Denmark, The Use of Soil Physical Data in Irrigation Planning, 14, 267–276, 1983.
Brutsaert, W. and Sugita, M.: Application of self-preservation in the diurnal evolution of the surface energy budget to determine daily evaporation, J. Geophys. Res.-Atmos., 97, 18377–18382, https://doi.org/10.1029/92JD00255, 1992.
Campbell, G. S. A. and Norman, J. M.: An Introduction to Environmental BIophysics: 2nd Edn., Springer London, Limited, 1998.
Chen, J., Famigliett, J. S., Scanlon, B. R., and Rodell, M.: Groundwater Storage Changes: Present Status from GRACE Observations, Surv. Geophys., 37, 397–417, https://doi.org/10.1007/s10712-015-9332-4, 2016.
Clark, M. P., Nijssen, B., Lundquist, J. D., Kavetski, D., Rupp, D. E., Woods, R. A., Freer, J. E., Gutmann, E. D., Wood, A. W., Brekke, L. D., Arnold, J. R., Gochis, D. J., and Rasmussen, R. M.: A unified approach for process-based hydrologic modeling: 1. Modeling concept, Water Resour. Res., 51, 2498–2514, https://doi.org/10.1002/2015WR017198, 2015.
Cong, N., Piao, S., Chen, A., Wang, X., Lin, X., Chen, S., Han, S., Zhou, G., and Zhang, X.: Spring vegetation green-up date in China inferred from SPOT NDVI data: A multiple model analysis, Agr. Forest Meteorol., 165, 104–113, https://doi.org/10.1016/j.agrformet.2012.06.009, 2012.
Conradt, T., Wechsung, F., and Bronstert, A.: Three perceptions of the evapotranspiration landscape: comparing spatial patterns from a distributed hydrological model, remotely sensed surface temperatures, and sub-basin water balances, Hydrol. Earth Syst. Sci., 17, 2947–2966, https://doi.org/10.5194/hess-17-2947-2013, 2013.
Corbari, C. and Mancini, M.: Calibration and validation of a distributed energy-water balance model using satellite data of land surface temperature and ground discharge measurements, J. Hydrometeorol., 15, 376–392, 10.1175/JHM-D-12-0173.1, 2014.
Corbari, C., Mancini, M., Li, J., and Su, Z.: Can satellite land surface temperature data be used similarly to river discharge measurements for distributed hydrological model calibration?, Hydrolog. Sci. J., 60, 202–217, https://doi.org/10.1080/02626667.2013.866709, 2015.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J. J., Park, B. K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J. N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011.
Fang, Z., Bogena, H., Kollet, S., Koch, J., and Vereecken, H.: Spatio-temporal validation of long-term 3D hydrological simulations of a forested catchment using empirical orthogonal functions and wavelet coherence analysis, J. Hydrol., 529, 1754–1767, https://doi.org/10.1016/j.jhydrol.2015.08.011, 2015.
Freeze, R. A. and Harlan, R. L.: Blueprint for a physically-based, digitally-simulated hydrologic response model, J. Hydrol., 9, 237–258, 1969.
Gentine, P., Entekhabi, D., Chehbouni, A., Boulet, G., and Duchemin, B.: Analysis of evaporative fraction diurnal behaviour, Agr. Forest Meteorol., 143, 13–29, https://doi.org/10.1016/j.agrformet.2006.11.002, 2007.
Githui, F., Selle, B., and Thayalakumaran, T.: Recharge estimation using remotely sensed evapotranspiration in an irrigated catchment in southeast Australia, Hydrol. Process., 26, 1379–1389, https://doi.org/10.1002/hyp.8274, 2012.
Graf, A., Bogena, H. R., Drüe, C., Hardelauf, H., Pütz, T., Heinemann, G., and Vereecken, H.: Spatiotemporal relations between water budget components and soil water content in a forested tributary catchment, Water Resour. Res., 50, 4837–4857, https://doi.org/10.1002/2013WR014516, 2014.
Grayson, R. B. and Blöschl, G.: Spatial modelling of catchment dynamics, in: Spatial Patterns in Catchment Hydrology: Observations and Modelling, edited by: Grayson, R. B. and Blöschl, G., Cambridge University Press, 51–81, 2000.
Gutman, G. and Ignatov, A.: The derivation of the green vegetation fraction from NOAA/AVHRR data for use in numerical weather prediction models, Int. J. Remote Sens., 19, 1533–1543, https://doi.org/10.1080/014311698215333, 1998.
Guzinski, R., Anderson, M. C., Kustas, W. P., Nieto, H., and Sandholt, I.: Using a thermal-based two source energy balance model with time-differencing to estimate surface energy fluxes with day-night MODIS observations, Hydrol. Earth Syst. Sci., 17, 2809–2825, https://doi.org/10.5194/hess-17-2809-2013, 2013.
Guzinski, R., Nieto, H., Stisen, S., and Fensholt, R.: Inter-comparison of energy balance and hydrological models for land surface energy flux estimation over a whole river catchment, Hydrol. Earth Syst. Sci., 19, 2017–2036, https://doi.org/10.5194/hess-19-2017-2015, 2015.
Hansen, J. R., Refsgaard, J. C., Ernstsen, V., Hansen, S., Styczen, M., and Poulsen, R. N.: An integrated and physically based nitrogen cycle catchment model, Hydrol. Res., 40, 347–363, https://doi.org/10.2166/nh.2009.035, 2009.
Hendricks Franssen, H. J., Brunner, P., Makobo, P., and Kinzelbach, W.: Equally likely inverse solutions to a groundwater flow problem including pattern information from remote sensing images, Water Resour. Res., 44, W01419, https://doi.org/10.1029/2007WR006097, 2008.
Henriksen, H. J., Troldborg, L., Nyegaard, P., Sonnenborg, T. O., Refsgaard, J. C., and Madsen, B.: Methodology for construction, calibration and validation of a national hydrological model for Denmark, J. Hydrol., 280, 52–71, https://doi.org/10.1016/S0022-1694(03)00186-0, 2003.
Henriksen, H. J., Troldborg, L., Højberg, A. L., and Refsgaard, J. C.: Assessment of exploitable groundwater resources of Denmark by use of ensemble resource indicators and a numerical groundwater–surface water model, J. Hydrol., 348, 224–240, https://doi.org/10.1016/j.jhydrol.2007.09.056, 2008.
Højberg, A. L., Troldborg, L., Stisen, S., Christensen, B. B. S., and Henriksen, H. J.: Stakeholder driven update and improvement of a national water resources model, Environ. Modell. Softw., 40, 202–213, https://doi.org/10.1016/j.envsoft.2012.09.010, 2013.
Immerzeel, W. W. and Droogers, P.: Calibration of a distributed hydrological model based on satellite evapotranspiration, J. Hydrol., 349, 411–424, https://doi.org/10.1016/j.jhydrol.2007.11.017, 2008.
Immerzeel, W. W., Droogers, P., de Jong, S. M., and Bierkens, M. F. P.: Large-scale monitoring of snow cover and runoff simulation in Himalayan river basins using remote sensing, Remote Sens. Environ., 113, 40–49, https://doi.org/10.1016/j.rse.2008.08.010, 2009.
Jönsson, P. and Eklundh, L.: Seasonality extraction by function fitting to time-series of satellite sensor data, IEEE T. Geosci. Remote, 40, 1824–1832, https://doi.org/10.1109/TGRS.2002.802519, 2002.
Jönsson, P. and Eklundh, L.: TIMESAT – a program for analyzing time-series of satellite sensor data, Comput. Geosci., 30, 833–845, https://doi.org/10.1016/j.cageo.2004.05.006, 2004.
Kalma, J. D., McVicar, T. R., and McCabe, M. F.: Estimating Land Surface Evaporation: A Review of Methods Using Remotely Sensed Surface Temperature Data, Surv. Geophys., 29, 421–469, https://doi.org/10.1007/s10712-008-9037-z, 2008.
Karlsson, I. B., Sonnenborg, T. O., Refsgaard, J. C., Trolle, D., Børgesen, C. D., Olesen, J. E., Jeppesen, E., and Jensen, K. H.: Combined effects of climate models, hydrological model structures and land use scenarios on hydrological impacts of climate change, J. Hydrol., 535, 301–317, https://doi.org/10.1016/j.jhydrol.2016.01.069, 2016.
Koch, J., Jensen, K. H., and Stisen, S.: 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/10.1002/2014WR016607, 2015.
Koch, J., Siemann, A., Stisen, S., and Sheffield, J.: Spatial validation of large-scale land surface models against monthly land surface temperature patterns using innovative performance metrics, J. Geophys. Res.-Atmos., 121, 5430–5452, https://doi.org/10.1002/2015JD024482, 2016.
Koch, J., Mendiguren, G., Mariethoz, G., and Stisen, S.: 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-16-0148.1, 2017.
Komatsu, H.: Forest categorization according to dry-canopy evaporation rates in the growing season: comparison of the Priestley–Taylor coefficient values from various observation sites, Hydrol. Process., 19, 3873–3896, https://doi.org/10.1002/hyp.5987, 2005.
Kustas, W. P. and Norman, J. M.: Evaluation of soil and vegetation heat flux predictions using a simple two-source model with radiometric temperatures for partial canopy cover, Agr. Forest Meteorol., 94, 13–29, https://doi.org/10.1016/S0168-1923(99)00005-2, 1999.
Lettenmaier, D. P., Alsdorf, D., Dozier, J., Huffman, G. J., Pan, M., and Wood, E. F.: Inroads of remote sensing into hydrologic science during the WRR era, Water Resour. Res., 51, 7309–7342, https://doi.org/10.1002/2015WR017616, 2015.
Li, H. T., Brunner, P., Kinzelbach, W., Li, W. P., and Dong, X. G.: Calibration of a groundwater model using pattern information from remote sensing data, J. Hydrol., 377, 120–130, https://doi.org/10.1016/j.jhydrol.2009.08.012, 2009.
Mascaro, G., Vivoni, E. R., and Méndez-Barroso, L. A.: Hyperresolution hydrologic modeling in a regional watershed and its interpretation using empirical orthogonal functions, Adv. Water Resour., 83, 190–206, https://doi.org/10.1016/j.advwatres.2015.05.023, 2015.
Maxwell, R. M. and Kollet, S. J.: Interdependence of groundwater dynamics and land-energy feedbacks under climate change, Nat. Geosci., 1, 665–669, 2008.
Mendiguren, G., Pilar Martín, M., Nieto, H., Pacheco-Labrador, J., and Jurdao, S.: Seasonal variation in grass water content estimated from proximal sensing and MODIS time series in a Mediterranean Fluxnet site, Biogeosciences, 12, 5523–5535, https://doi.org/10.5194/bg-12-5523-2015, 2015.
Miralles, D. G., Holmes, T. R. H., De Jeu, R. A. M., Gash, J. H., Meesters, A. G. C. A., and Dolman, A. J.: Global land-surface evaporation estimated from satellite-based observations, Hydrol. Earth Syst. Sci., 15, 453–469, https://doi.org/10.5194/hess-15-453-2011, 2011.
Mu, Q., Heinsch, F. A., Zhao, M., and Running, S. W.: Development of a global evapotranspiration algorithm based on MODIS and global meteorology data, Remote Sens. Environ., 111, 519–536, https://doi.org/10.1016/j.rse.2007.04.015, 2007.
Norman, J. M., Kustas, W. P., and Humes, K. S.: Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature, Agr. Forest Meteorol., 77, 263–293, https://doi.org/10.1016/0168-1923(95)02265-Y, 1995.
Perry, M. A. and Niemann, J. D.: Analysis and estimation of soil moisture at the catchment scale using EOFs, J. Hydrol., 334, 388–404, https://doi.org/10.1016/j.jhydrol.2006.10.014, 2007.
Priestley, C. H. B. and Taylor, R. J.: On the Assessment of Surface Heat Flux and Evaporation Using Large-Scale Parameters, Mon. Weather Rev., 100, 81–92, https://doi.org/10.1175/1520-0493(1972)100<0081:OTAOSH>2.3.CO;2, 1972.
Rajib, M. A., Merwade, V., and Yu, Z.: Multi-objective calibration of a hydrologic model using spatially distributed remotely sensed/in-situ soil moisture, J. Hydrol., 536, 192–207, https://doi.org/10.1016/j.jhydrol.2016.02.037, 2016.
Refsgaard, J. C.: Parameterisation, calibration and validation of distributed hydrological models, J. Hydrol., 198, 69–97, https://doi.org/10.1016/S0022-1694(96)03329-X, 1997.
Refsgaard, J. C., Stisen, S., Højberg, A. L., Olsen, M., Henriksen, H. J., Børgesen, C. D., Vejen, F., Kern-Hansen, C., and Blicher-Mathiesen, G.: Danmarks og grønlands geologiske undersøgelse rapport 2011/77, Geological Survey of Danmark and Greenland (GEUS), 2011.
Richey, A. S., Thomas, B. F., Lo, M.-H., Reager, J. T., Famiglietti, J. S., Voss, K., Swenson, S., and Rodell, M.: Quantifying renewable groundwater stress with GRACE, Water Resour. Res., 51, 5217–5238, https://doi.org/10.1002/2015WR017349, 2015.
Ridler, M.-E., Madsen, H., Stisen, S., Bircher, S., and Fensholt, R.: Assimilation of SMOS-derived soil moisture in a fully integrated hydrological and soil-vegetation-atmosphere transfer model in Western Denmark, Water Resour. Res., 50, 8962–8981, https://doi.org/10.1002/2014WR015392, 2014.
Rientjes, T. H. M., Muthuwatta, L. P., Bos, M. G., Booij, M. J., and Bhatti, H. A.: Multi-variable calibration of a semi-distributed hydrological model using streamflow data and satellite-based evapotranspiration, J. Hydrol., 505, 276–290, https://doi.org/10.1016/j.jhydrol.2013.10.006, 2013.
Ringgaard, R., Herbst, M., Friborg, T., Schelde, K., Thomsen, A. G., and Soegaard, H.: Energy Fluxes above Three Disparate Surfaces in a Temperate Mesoscale Coastal Catchment, Vadose Zone J., 10, 54–66, https://doi.org/10.2136/vzj2009.0181, 2011.
Rodell, M., Velicogna, I., and Famiglietti, J. S.: Satellite-based estimates of groundwater depletion in India, Nature, 460, 999–1002, 2009.
Rouse, J. W., Haas, R. H., Deering, D. W., and Schell, J. A.: Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation, Goddard Space Flight Center, Greenbelt, MD, 87, 1973.
Ruiz-Pérez, G., Koch, J., Manfreda, S., Caylor, K., and Francés, F.: Calibration of a parsimonious distributed ecohydrological daily model in a data scarce basin using exclusively the spatio-temporal variation of NDVI, Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-573, in review, 2016.
Samaniego, L., Kumar, R., and Attinger, S.: Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale, Water Resour. Res., 46, W05523, https://doi.org/10.1029/2008WR007327, 2010.
Savitzky, A. and Golay, M. J. E.: Smoothing and Differentiation of Data by Simplified Least Squares Procedures, Anal. Chem., 36, 1627–1639, https://doi.org/10.1021/ac60214a047, 1964.
Schuurmans, J. M., Troch, P. A., Veldhuizen, A. A., Bastiaanssen, W. G. M., and Bierkens, M. F. P.: Assimilation of remotely sensed latent heat flux in a distributed hydrological model, Adv. Water Resour., 26, 151–159, https://doi.org/10.1016/S0309-1708(02)00089-1, 2003.
Stisen, S., Jensen, K. H., Sandholt, I., and Grimes, D. I. F.: A remote sensing driven distributed hydrological model of the Senegal River basin, J. Hydrol., 354, 131–148, https://doi.org/10.1016/j.jhydrol.2008.03.006, 2008.
Stisen, S., McCabe, M. F., Refsgaard, J. C., Lerer, S., and Butts, M. B.: Model parameter analysis using remotely sensed pattern information in a multi-constraint framework, J. Hydrol., 409, 337–349, https://doi.org/10.1016/j.jhydrol.2011.08.030, 2011.
Stisen, S., Højberg, A. L., Troldborg, L., Refsgaard, J. C., Christensen, B. S. B., Olsen, M., and Henriksen, H. J.: On the importance of appropriate precipitation gauge catch correction for hydrological modelling at mid to high latitudes, Hydrol. Earth Syst. Sci., 16, 4157–4176, https://doi.org/10.5194/hess-16-4157-2012, 2012.
Sugita, M. and Brutsaert, W.: Daily evaporation over a region from lower boundary layer profiles measured with radiosondes, Water Resour. Res., 27, 747–752, https://doi.org/10.1029/90WR02706, 1991.
Sutanudjaja, E. H., de Jong, S. M., van Geer, F. C., and Bierkens, M. F. P.: Using ERS spaceborne microwave soil moisture observations to predict groundwater head in space and time, Remote Sens. Environ., 138, 172–188, https://doi.org/10.1016/j.rse.2013.07.022, 2013.
van der Keur, P., Hansen, J. R., Hansen, S., and Refsgaard, J. C.: Uncertainty in Simulation of Nitrate Leaching at Field and Catchment Scale within the Odense River Basin, Vadose Zone J., 7, 10–21, https://doi.org/10.2136/vzj2006.0186, 2008.
Vansteenkiste, T., Tavakoli, M., Van Steenbergen, N., De Smedt, F., Batelaan, O., Pereira, F., and Willems, P.: Intercomparison of five lumped and distributed models for catchment runoff and extreme flow simulation, J. Hydrol., 511, 335–349, https://doi.org/10.1016/j.jhydrol.2014.01.050, 2014.
Vereecken, H., Pachepsky, Y., Simmer, C., Rihani, J., Kunoth, A., Korres, W., Graf, A., Franssen, H. J. H., Thiele-Eich, I., and Shao, Y.: On the role of patterns in understanding the functioning of soil-vegetation-atmosphere systems, J. Hydrol., 542, 63–86, https://doi.org/10.1016/j.jhydrol.2016.08.053, 2016.
Wanders, N., Bierkens, M. F. P., de Jong, S. M., de Roo, A., and Karssenberg, D.: The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models, Water Resour. Res., 50, 6874–6891, https://doi.org/10.1002/2013WR014639, 2014.
Wang, D.-C., Zhang, G.-L., Zhao, M.-S., Pan, X.-Z., Zhao, Y.-G., Li, D.-C., and Macmillan, B.: Retrieval and Mapping of Soil Texture Based on Land Surface Diurnal Temperature Range Data from MODIS, PLOS ONE, 10, e0129977, https://doi.org/10.1371/journal.pone.0129977, 2015.
Wang, L., Koike, T., Yang, K., and Yeh, P. J.-F.: Assessment of a distributed biosphere hydrological model against streamflow and MODIS land surface temperature in the upper Tone River Basin, J. Hydrol., 377, 21–34, https://doi.org/10.1016/j.jhydrol.2009.08.005, 2009.
Windolf, J., Thodsen, H., Troldborg, L., Larsen, S. E., Bøgestrand, J., Ovesen, N. B., and Kronvang, B.: A distributed modelling system for simulation of monthly runoff and nitrogen sources, loads and sinks for ungauged catchments in Denmark, J. Environ. Monitor., 13, 2645–2658, https://doi.org/10.1039/c1em10139k, 2011.
Yan, J. and Smith, K. R.: Simulation of integrated surface water and ground water systems – model formulation1, J. Am. Water Resour. As., 30, 879–890, https://doi.org/10.1111/j.1752-1688.1994.tb03336.x, 1994.
Zhang, D., Madsen, H., Ridler, M. E., Kidmose, J., Jensen, K. H., and Refsgaard, J. C.: Multivariate hydrological data assimilation of soil moisture and groundwater head, Hydrol. Earth Syst. Sci., 20, 4341–4357, https://doi.org/10.5194/hess-20-4341-2016, 2016.
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