Have a personal or library account? Click to login
Stepwise prediction of runoff using proxy data in a small agricultural catchment Cover

Stepwise prediction of runoff using proxy data in a small agricultural catchment

Open Access
|Jan 2021

References

  1. Ardia, D., Ospina Arango, J.D., Giraldo Gomez, N.D., 2010a. Jump-diffusion calibration using differential evolution. Wilmott Magazine, 55, 76–79.10.1002/wilm.10034
  2. Ardia, D., Boudt, K., Carl, P., Mullen, K.M., Peterson, B.G., 2010b. Differential evolution with ‘DEoptim’: An application to non-convex portfolio optimization. The R Journal, 3, 1, 27–34.10.32614/RJ-2011-005
  3. Ardia, D., Mullen, K.M., Peterson, B.G., Ulrich, J., 2016. ‘DE-optim’: Differential evolution in ‘R’. version 2.2-4.
  4. Avanzi, F., Maurer, T., Glaser, S.D., Bales, R.C., Conklin, M.H., 2020. Information content of spatially distributed ground-based measurements for hydrologic-parameter calibration in mixed rain-snow mountain headwaters. Journal of Hydrology, 582, 124478.10.1016/j.jhydrol.2019.124478
  5. Baroni, G., Schalge, B., Rakovec, O., Kumar, R., Schüler, L., Samaniego, L., Simmer, C., Attinger, S., 2019. A comprehensive distributed hydrological modeling intercomparison to support process representation and data collection strategies. Water Resources Research, 55, 990–1010.10.1029/2018WR023941
  6. Bergström, S., 1976. Development and application of a conceptual runoff model for Scandinavian catchments. Department of Water Resources Engineering, Lund Institute of Technology, University of Lund, Bulletin Series A, no. 52.
  7. Bergström, S., Lindström, G., 2015. Interpretation of runoff processes in hydrological modelling – experience from the HBV approach. Hydrological Processes, 29, 3535–3545.10.1002/hyp.10510
  8. Beven, K.J., Freer, J., 2001. Equifinality, data assimilation, and uncertainty estimation in mechanistic modeling of complex environmental systems using the GLUE methodology. Journal of Hydrology, 249, 1–4, 11–29.10.1016/S0022-1694(01)00421-8
  9. Blöschl, G., Sivapalan, M., Wagener, T., Viglione, A., Savenije, H., 2013. Runoff Prediction in Ungauged Basins: Synthesis across Processes, Places and Scales. Cambridge University Press, United Kingdom, 465 p.10.1017/CBO9781139235761
  10. Blöschl, G., Blaschke, A.P., Broer, M., Bucher, C., Carr, G., Chen, X., Eder, A., Exner-Kittridge, M., Farnleitner, A., Flores-Orozco, Haas, P., Hogan, P., Kazemi Amiri, A., Oismüller, M., Parajka, J., Silasari, R., Stadler, P., Strauss, P., Vreugdenhil, M., Wagner, W., Zessner, M., 2016. The Hydrological Open Air Laboratory (HOAL) in Petzenkirchen: a hypothesis-driven observatory. Hydrology and Earth System Sciences, 20, 227–255.10.5194/hess-20-227-2016
  11. Criss, R.E., Winston, W.E., 2008. Do Nash values have value? Discussion and alternate proposals. Hydrological Processes, 22, 2723–2725.10.1002/hyp.7072
  12. Eder, A., Strauss, P., Kreuger, T., Quinton, J., 2010. Comparative calculation of suspended sediment loads with respect to hysteresis effects. Journal of Hydrology, 389, 1–2, 168–176.10.1016/j.jhydrol.2010.05.043
  13. Eder, A., Exner-Kittridge, M., Strauss, P., Blöschl, G., 2014. Re-suspension of bed sediment in a small stream – results from two flushing experiments. Hydrology and Earth System Sciences, 18, 1043–1052.10.5194/hess-18-1043-2014
  14. Esri, DigitalGlobe, GeoEye, i-cubed, USDA FSA, USGS, AEX, Getmapping, Aerogrid, IGN, IGP, swisstopo, GIS User Community, 2020. “World Imagery” [basemap]. https://services.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer. (March 31, 2020)
  15. Fenicia, F., Savenije, H.H.G., Matgen, P., Pfister, L., 2007. A comparison of alternative multiobjective calibration strategies for hydrological modeling. Water Resources Research, 43, 3, W03434.10.1029/2006WR005098
  16. Gelleszun, M., Kreye, P., Meon, G., 2017. Representative parameter estimation for hydrological models using a lexicographic calibration strategy. Journal of Hydrology, 553, 722–734.10.1016/j.jhydrol.2017.08.015
  17. Gui, Z., Liu, P., Cheng, L., Guo, S., Wang, H., Zhang, L., 2019. Improving Runoff Prediction Using Remotely Sensed Actual Evapotranspiration during Rainless Periods. Journal of Hydrologic Engineering, 24, 12, 04019050.10.1061/(ASCE)HE.1943-5584.0001856
  18. Hall, D.K., Riggs, G.A., 2016a. MODIS/Terra Snow Cover Daily L3 Global 500m Grid, Version 6. [January 2013 – December 2017]. Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center. DOI: 10.5067/MODIS/MOD10A1.006 [24 January 2018].
  19. Hall, D.K., Riggs, G.A., 2016b. MODIS/Aqua Snow Cover Daily L3 Global 500m Grid, Version 6. [January 2013 – December 2017]. Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center. DOI: 10.5067/MODIS/MYD10A1.006. [24 January 2018].
  20. Hay, L.E., Leavesley, G.H., Clark, M.P., Markstrom, S.L., Viger, R.J., Umemoto, M., 2006. Step wise, multiple objective calibration of a hydrologic model for a snowmelt dominated basin. Journal of the American Water Resources Association, 42, 4, 877–890.10.1111/j.1752-1688.2006.tb04501.x
  21. Hogue, T.S., Sorooshian, S., Gupta, H., Holz, A., Braatz, D., 2000. A multistep automatic calibration scheme for river forecasting models. Journal of Hydrometeorology, 1, 524–542.10.1175/1525-7541(2000)001<0524:AMACSF>2.0.CO;2
  22. Hrachowitz, M., Savenije, H.H.G., Blöschl, G., McDonnell, J.J., Sivapalan, M., Pomeroy, J.W., Arheimer, B., Blume, T., Clark, M.P., Ehret, U., Fenicia, F., Freer, J.E., Gelfan, A., Gupta, H.V., Hughes, D.A., Hut, R.W., Montanari, A., Pande, S., Tetzlaff, D., Troch, P.A., Uhlenbrook, S., Wagener, T., Winsemius, H.C., Woods, R.A., Zehe, E., Cudennec, C., 2013. A decade of Predictions in Ungauged Basins (PUB) -a review. Hydrological Sciences Journal, 58, 6, 1198–1255.10.1080/02626667.2013.803183
  23. Kuppel, S., Tetzlaff, D., Maneta, M.P., Soulsby, C., 2018. What can we learn from multi-data calibration of a process-based ecohydrological model? Environmental Modelling & Software, 101, 301–316.10.1016/j.envsoft.2018.01.001
  24. Kuras, P.K., Alila, Y., Weiler, M., Spittlehouse, D., Winkler, R., 2011. Internal catchment process simulation in a snow-dominated basin: performance evaluation with spatiotempo-rally variable runoff generation and groundwater dynamics. Hydrological Processes, 25, 3187–3203.10.1002/hyp.8037
  25. Lindström, G., Johansson, B., Persson, M., Gardelin, M., Bergström, S., 1997. Development and test of the distributed HBV-96 hydrological model. Journal of Hydrology, 201, 1–4, 272–288.10.1016/S0022-1694(97)00041-3
  26. López, L.P., Sutanudjaja, E.H., Schellekens, J., Sterk, G., Bier-kens, M.F.P., 2017. Calibration of a large-scale hydrological model using satellite-based soil moisture and evapotranspi-ration products. Hydrology and Earth System Sciences, 21, 3125–3144.10.5194/hess-21-3125-2017
  27. Lu, M., Li, X., 2015. Strategy to automatically calibrate parameters of a hydrological model: a multi-step optimization scheme and its application to the Xinanjiang model. Hydro-logical Research Letters, 9, 4, 69–74.10.3178/hrl.9.69
  28. Merz, R., Blöschl, G., 2004. Regionalisation of catchment model parameters. Journal of Hydrology, 287, 95–123.10.1016/j.jhydrol.2003.09.028
  29. Merz, R., Parajka, J., Blöschl, G., 2011. Time stability of catchment model parameters: Implications for climate impact analyses. Water Resources Research, 47, 1015–1031.10.1029/2010WR009505
  30. 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.i06
  31. Murer, E., Wagenhofer, J., Aigner, F., Cline, J., 2004. Die nutzbare Feldkapazität der mineralischen Böden der land-wirtschaftlichen Nutzfläche Österreichs. Schriftenreihe BAW, Band 20, 72–78.
  32. Nijzink, R.C., Almeida, S., Pechlivanidis, I.G., Capell, R., Gustafssons, D., Arheimer, B., Parajka, J., Freer, J., Han, D., Wagener, T., van Nooijen, R.R.P., Savenije, H.H.G., Hrachowitz, M., 2018. Constraining conceptual hydrological models with multiple information sources. Water Resources Research, 54, 8332–8362.10.1029/2017WR021895
  33. Ning, S., Ishidaira, H., Wang, J., 2015. Calibrating a hydrologic model by step-wise method using GRACE TWS and discharge data. Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), 71, 4, I_85-I_90.10.2208/jscejhe.71.I_85
  34. Parajka, J., Merz, R., Blöschl, G., 2003. Estimation of daily potential evapotranspiration for regional water balance modeling in Austria. In: 11th International Poster Day and Institute of Hydrology Open Day “Transport of Water, Chemicals and Energy in the Soil - Crop Canopy - Atmosphere System”, Slovak Academy of Sciences, Bratislava, pp. 299–306.
  35. Parajka, J., Merz, R., Blöschl, G., 2007. Uncertainty and multiple objective calibration in regional water balance modelling: case study in 320 Austrian catchments. Hydrological Processes, 21, 435–446.10.1002/hyp.6253
  36. Parajka, J., Viglione, A., Rogger, M., Salinas, J.L., Sivapalan, M., Blöschl, G., 2013. Comparative assessment of predictions in ungauged basins - Part 1: Runoff hydrograph studies. Hydrology and Earth System Sciences, 17, 1783–1795.10.5194/hess-17-1783-2013
  37. Rogger, M., Kohl, B., Pirkl, H., Viglione, A., Komma, J., Kirn-bauer, R., Merz, R., Blöschl, G., 2012. Runoff models and flood frequency statistics for design flood estimation in Austria - Do they tell a consistent story? Journal of Hydrology, 456–457, 30–43.10.1016/j.jhydrol.2012.05.068
  38. Savenije, H.H.G., 2001. Equifinality, a blessing in disguise? Hydrological Processes, 15, 2835–2838.10.1002/hyp.494
  39. Schrödter, H., 1985. Verdunstung - Anwendungsorientierte Messverfahren und Bestimmungsmethoden. Springer, 186 p. ISBN: 978-3-642-70434-5.
  40. Seibert, J., 2000. Multi-criteria calibration of a conceptual runoff model using a genetic algorithm. Hydrology and Earth System Sciences, 4, 215–224.10.5194/hess-4-215-2000
  41. Silasari, R., Parajka, J., Ressl, C., Strauss, P., Blöschl, G., 2017. Potential of time - lapse photography for identifying saturation area dynamics on agricultural hillslopes. Hydrological Processes, 31, 3610–3627.10.1002/hyp.11272
  42. Silvestro, F., Gabellani, S., Rudari, R., Delogu, F., Laiolo, P., Boni, G., 2015. Uncertainty reduction and parameter estimation of a distributed hydrological model with ground and remote-sensing data. Hydrology and Earth System Sciences, 19, 1727–1751.10.5194/hess-19-1727-2015
  43. Sleziak, P., Szolgay, J., Hlavcova, K., Danko, M., Parajka, J., 2020. The effect of the snow weighting on the temporal stability of hydrologic model efficiency and parameters. Journal of Hydrology, 583, 124639.10.1016/j.jhydrol.2020.124639
  44. Széles, B., Broer, M., Parajka, J., Hogan, P., Eder, A., Strauss, P., Blöschl, G., 2018. Separation of scales in transpiration effects on low flows – A spatial analysis in the Hydrological Open Air Laboratory. Water Resources Research, 54, 9, 6168–6188.10.1029/2017WR022037622101530449909
  45. Széles, B., Parajka, J., Hogan, P., Silasari, R., Pavlin, L., Strauss, P., Blöschl, G., 2020. The added value of different data types for calibrating and testing a hydrologic model in a small catchment. Submitted to Water Resources Research.10.1029/2019WR026153759444733149373
  46. Thyer, M., Beckers, J., Spittlehouse, D., Alila, Y., Winkler, R., 2004. Diagnosing a distributed hydrologic model for two high-elevation forested catchments based on detailed stand-and basin-scale data. Water Resources Research, 40, W01103.10.1029/2003WR002414
  47. Viglione, A., Parajka, J., Rogger, M., Salinas, J.L., Laaha, G., Sivapalan, M., Blöschl, G., 2013. Comparative assessment of predictions in ungauged basins – Part 3: Runoff signatures in Austria. Hydrology and Earth System Sciences, 17, 2263–2279.10.5194/hess-17-2263-2013
  48. Viglione, A., Rogger, M., Pirkl, H., Parajka, J., Blöschl, G., 2018. Conceptual model building inspired by field-mapped runoff generation mechanisms. Journal of Hydrology and Hydromechanics, 66, 3, 303–315.10.2478/johh-2018-0010
DOI: https://doi.org/10.2478/johh-2020-0029 | Journal eISSN: 1338-4333 | Journal ISSN: 0042-790X
Language: English
Page range: 65 - 75
Submitted on: Apr 1, 2020
Accepted on: Jul 20, 2020
Published on: Jan 26, 2021
Published by: Slovak Academy of Sciences
In partnership with: Paradigm Publishing Services
Publication frequency: 4 times per year

© 2021 Borbála Széles, Juraj Parajka, Patrick Hogan, Rasmiaditya Silasari, Lovrenc Pavlin, Peter Strauss, Günter Blöschl, published by Slovak Academy of Sciences
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.