A joined multi-metric calibration of river discharge and nitrate loads with different performance measures

Journal of Hydrology

Volumn 536, Issue , 2016, Pages 534-545

  Haas, Marcelo B ^a   Guse, Björn ^a   Pfannerstill, Matthias ^a   Fohrer, Nicola ^a  

^a UNIVERSITY OF KIEL   (Germany)

Author keywords

Ecohydrological modelling; Flow and nitrate duration curve; Multi metric and multi variable calibration; Signature measures; Water quality

Indexed keywords

CATCHMENTS; ELECTRIC NETWORK TOPOLOGY; HYDROLOGY; MULTIVARIABLE SYSTEMS; RUNOFF; WATER QUALITY;

DURATION CURVE; ECO-HYDROLOGICAL MODELS; ENVIRONMENTAL PROCESS; HYDROLOGICAL CONDITION; MULTI VARIABLES; PERFORMANCE APPROACH; SIGNATURE MEASURES; STATISTICAL PERFORMANCE;

NITRATES;

CALIBRATION; CATCHMENT; ECOHYDROLOGY; HYDROGRAPH; HYDROLOGICAL MODELING; MAGNITUDE; NITRATE; RIVER DISCHARGE; STATISTICAL ANALYSIS; WATER QUALITY;

EID: 84962288739     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2016.03.001     Document Type: Article

References (69)

1. Arnold J.G., Srinivasan R., Muttiah R.S., Williams J.R. Large area hydrologic modeling and assessment. Part I: Model development. J. Am. Water Resour. Assoc. 1998, 34(1):73-89. 10.1111/j.1752-1688.1998.tb05961.x.
2. Bailey R.T., Ahmadi M. Spatial and temporal variability of in-stream water quality parameter influence on dissolved oxygen and nitrate within a regional stream network. Ecol. Model. 2014, 277:87-96. 10.1016/j.ecolmodel.2014.01.015.
3. Bekele E.G., Nicklow J.W. Multi-objective automatic calibration of SWAT using NSGA-II. J. Hydrol. 2007, 341(3):165-176. 10.1016/j.jhydrol.2007.05.014.
4. Beven K. A manifesto for the equifinality thesis. J. Hydrol. 2006, 320:18-36. 10.1016/j.jhydrol.2005.07.007.
5. BGR Bundesanstalt fuer Geowisschenschaften und Rohstoffe - Bodenuebersichtskarte im Maßstab 1:200.000 1999, Verbreitung der Bodengesellschaften.
6. Bouraoui F., Grizzetti B. Modelling mitigation options to reduce diffuse nitrogen water pollution from agriculture. Sci. Total Environ. 2014, 468-469:1267-1277.
7. Boyle D.P., Gupta H.V., Sorooshian S. Toward improved calibration of hydrologic models: combining the strengths of manual and automatic methods. Water Resour. Res. 2000, 36(12):3663-3674. 10.1029/2000WR900207.
8. Cerro I., Antiguedad I., Srinavasan R., Sauvage S., Volk M., Sanchez-Perez J.M. Simulating land management options to reduce nitrate pollution in an agricultural watershed dominated by an alluvial aquifer. J. Environ. Qual. 2014, 43:67-74. 10.2134/jeq2011.0393.
9. Cheng L., Yaeger M., Viglione A., Coopersmith E., Ye S., Sivapalan M. Exploring the physical controls of regional patterns of flow duration curves - Part 1: Insights from statistical analyses. Hydrol. Earth Syst. Sci. 2012, 16:4435-4446. 10.5194/hess-16-4435-2012.
10. Choi H.T., Beven K. Multi-period and multi-criteria model conditioning to reduce prediction uncertainty in an application of TOPMODEL within the GLUE framework. J. Hydrol. 2007, 332:316-336. 10.1016/j.jhydrol.2006.07.012.
11. Dietrich, A., 2010. Untersuchungen zum Herbizidaustrag mit dem Oberflächenabfluss im Regensimulationsversuch. Christian-Albrechts-Universität zu Kiel. Master thesis.
12. Doherty J., Johnston J.M. Methodologies for calibration and predictive analysis of a watershed model. J. Am. Water Resour. Assoc. 2003, 39(2):251-265.
13. Du J., Rui H., Zuo T., Li Q., Zheng D., Chen A., Xu Y., Xu C.-Y. Hydrological simulation by SWAT model with fixed and varied parameterization approaches under land use change. Water Resour. Manage 2013, 27(8):2823-2838. 10.1007/s11269-013-0317-0.
14. Dunn S.M. Imposing constraints on parameter values of a conceptual hydrological model using baseflow response. Hydrol. Earth Syst. Sci. 1999, 3(2):271-284.
15. EPA - United States Environmental Protection Agency, 2007. An Approach for Using Load Duration Curves in the Development of TMDLs. EPA 841-B-07-006, Washington, D.C.
16. EPA - United States Environmental Protection Agency, 2008. Development of Duration-Curve Based Methods for Quantifying Variability and Change in Watershed Hydrology and Water Quality. EPA/600/R-08/065, Cincinnati, Ohio.
17. Fohrer N., Schmalz B., Tavares F., Golon J. Modelling the landscape water balance of mesoscale lowland catchments considering agricultural drainage systems. Hydrol. Wasserbewirt./Hydrol. Water Resour. Manage. Germany 2007, 51(4):164-169.
18. Glavan M., White S., Holman I.P. Evaluation of river water quality simulations at a daily time step - experience with SWAT in the Axe Catchment, UK. Clean Soil Air Water 2011, 39(1):43-54. 10.1002/clen.200900298.
19. Gupta H.V., Kling H., Yilmaz K.K., Martinez Z.F. Decomposition of the mean squared error and NSE performance criteria: implications for improving hydrological modeling. J. Hydrol. 2009, 377:80-91.
20. Gupta H.V., Sorooshian S., Yapo P.O. Toward improved calibration of hydrologic models: multiple and noncommensurable measures of information. Water Resour. Res. 1998, 34(4):751-763. 10.1029/97WR03495.
21. Gupta H.V., Sorooshian S., Yapo P.O. Status of automatic calibration for hydrologic models: comparison with multilevel expert calibration. J. Hydrol. Eng. 1999, 4(2):135-143. 10.1061/(ASCE)1084-0699(1999) 4:2(135).
22. Guse B., Bronstert A., Rode M., Tetzlaff B., Wendland F. Application of two phosphorus models with different complexities in a mesoscale river catchment. Adv. Geosci. 2007, 11:77-84.
23. Guse B., Kail J., Radinger J., Schröder M., Kiesel J., Hering D., Wolter C., Fohrer N. Eco-hydrologic model cascades: simulating land use and climate change impacts on hydrology, hydraulics and habitats for fish and macroinvertebrates. Sci. Tot. Environ. 2015, 533:542-556. 10.1016/j.scitotenv.2015.05.078.
24. Guse B., Pfannerstill M., Fohrer N. Dynamic modelling of land use change impacts on nitrate loads in rivers. Environ. Process. 2015, 2(4):575-592. 10.1007/s40710-015-0099-x.
25. Guse B., Pfannerstill M., Strauch M., Reusser D., Lüdtke S., Volk M., Gupta H., Fohrer N. On characterizing the temporal dominance patterns of model parameters and processes. Hydrol. Process. 2016, 10.1002/hyp.10764.
26. Guse B., Reusser D.E., Fohrer N. How to improve the representation of hydrological processes in swat for a lowland catchment - temporal analysis of parameter sensitivity and model performance. Hydrol. Process. 2014, 28:2651-2670. 10.1002/hyp.9777.
27. Haas M., Guse B., Pfannerstill M., Fohrer N. Detection of dominant nitrate processes in ecohydrological modeling with temporal parameter sensitivity analysis. Ecol. Model. 2015, 314:62-72. 10.1016/j.ecolmodel.2015.07.009.
28. Hesse C., Krysanova V., Päzolt J., Hattermann F.F. Eco-hydrological modelling in a highly regulated lowland catchment to find measures for improving water quality. Ecol. Model. 2008, 218:135-148.
29. Jiang S., Jooma S., Büttner O., Meon G., Rode M. Multi-site identification of a distributed hydrological nitrogen model using Bayesian uncertainty analysis. J. Hydrol. 2015, 529:940-950. 10.1016/j.jhydrol.2015.09.009.
30. Kiesel J., Fohrer N., Schmalz B., White M. Incorporating landscape depressions and tile drainages of a northern german lowland catchment into a semi-distributed model. Hydrol. Process. 2010, 24(11):1472-1486. 10.1002/hyp.7607.
31. Kollat J.B., Reed P.M., Wagener T. When are multiobjective calibration trade-offs in hydrologic models meaningful?. Water Resour. Res. 2012, 48:W03520. 10.1029/2011WR011534.
32. Krause P., Boyle D.P., Bäse F. Comparison of different efficiency criteria for hydrological model assessment. Adv. Geosci. 2005, 5:89-97. 10.5194/adgeo-5-89-2005.
33. Kühling, I., 2011. Modellierung und räumliche Analyse der Phosphateintragspfade im Einzugsgebiet eines norddeutschen Tieflandbaches. Christian-Albrechts-Universität zu Kiel. Master thesis.
34. Laaha G., Blöschl G. A national low flow estimation procedure for Austria. Hydrol. Sci. J. 2007, 52(4):625-644. 10.1623/hysj.52.4.625.
35. Laurent F., Ruelland D. Assessing impacts of alternative land use and agricultural practices on nitrate pollution at the catchment scale. J. Hydrol. 2011, 409:440-450. 10.1016/j.jhydrol.2011.08.041.
36. LVermA, 1995. Digitales Geländemodell für Schleswig-Holstein. Landesvermessungsamt Schleswig-Holstein.
37. LVermA, 2004. Automatisierte Liegenschaftskarte (ALK). Landesvermessungsamt Schleswig-Holstein.
38. Madsen H. Automatic calibration of a conceptual rainfall-runoff model using multiple objectives. J. Hydrol. 2000, 235(3):276-288. 10.1016/S0022-1694(00)00279-1.
39. Moore C., Doherty J. The cost of uniqueness in groundwater model calibration. Adv. Water Resour. 2006, 29(4):605-623. 10.1016/j.advwatres.2005.07.003.
40. Moriasi D.N., Arnold J.G., Liew M.W.V., Bingner R.L., Harmel R.D., Veith T.L. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans. ASABE 2007, 50:885-900.
41. Moriasi D.N., Gowda P.H., Arnold J.G., Mulla D.J., Ale S., Steiner J.L. Modeling the impact of nitrogen fertilizer application and tile drain configuration on nitrate leaching using SWAT. Agric. Water Manage. 2013, 130:36-43.
42. Nash J.E., Sutcliffe J.V. River flow forecasting through conceptual models: Part 1. A discussion of principles. J. Hydrol. 1970, 10:282-290. 10.1016/0022-1694(70)90255-6.
43. Neitsch, S.L., Arnold, J.G., Kiniry, J.R., Williams, J.R., 2011. SWAT theoretical documentation version 2009, Grassland, Soil and Water Research Laboratory, Agricultural Research Service. Blackland Research Center, Texas Agricultural Experiment Station. Texas Water Resources Institute Technical Report No. 406.
44. Pechlivanidis I.G., Jackson B.M., McIntyre N.R., Wheater H.S. Catchment scale hydrological modelling: a review of model types, calibration approaches and uncertainty analysis methods in the context of recent developments in technology and applications. Glob. NEST J. 2011, 13(3):193-214.
45. Pfannerstill M., Guse B., Fohrer N. Smart low flow signature metrics for an improved overall performance evaluation of hydrological models. J. Hydrol. 2014, 510:447-458.
46. Pfannerstill M., Guse B., Fohrer N. A multi-storage groundwater concept for the SWAT model to emphasize nonlinear groundwater dynamics in lowland catchments. Hydrol. Process. 2014, 28:5599-5612. 10.1002/hyp.10062.
47. Pfannerstill M., Guse B., Reusser D., Fohrer N. Process verification of a hydrological model using a temporal parameter sensitivity analysis. Hydrol. Earth Syst. Sci. 2015, 19:4365-4376. 10.5194/hess-19-4365-2015.
48. Pokhrel P., Yilmaz K., Gupta H. Multiple-criteria calibration of a distributed watershed model using spatial regularization and response signatures. J. Hydrol. 2012, 418-419:49-60. 10.1016/j.jhydrol.2008.12.004.
49. R Core Team R: A Language and Environment for Statistical Computing 2013, R Foundation for Statistical Computing, Vienna, Austria.
50. Rode M., Arhonditsis G., Balin D., Kebede T., Krysanova V., van Griensven A., van der Zee S.E.A.T.M. New challenges in integrated water quality modeling. Hydrol. Process. 2010, 24:3447-3461. 10.1002/hyp.7766.
51. Santhi C., Arnold J.G., Williams J.R., Dugas W.A., Srinivasan R., Hauck L.M. Validation of the SWAT model on a large river basin with point and nonpoint sources. J. Am. Water Resour. Assoc. 2001, 37(5):1169-1188. 10.1111/j.1752-1688.2001.tb03630.x.
52. Schmalz B., Kuemmerlen M., Kiesel J., Cai Q., Jähnig S.C., Fohrer N. Impacts of land use changes on hydrological components and macroinvertebrate distributions in the Poyang lake area. Ecohydrology 2015, 8(6):1119-1136. 10.1002/eco.1569.
53. Schmalz B., Tavares F., Fohrer N. Modelling hydrological processes in mesoscale lowland river basins with SWAT - capabilities and challenges. Hydrol. Sci. J. 2008, 53(5):989-1000.
54. Sincock A.M., Wheater H.S., Whitehead P.G. Calibration and sensitivity analysis of a river water quality model under unsteady flow conditions. J. Hydrol. 2003, 277:214-229.
55. Smakhtin V. Low flow hydrology: a review. J. Hydrol. 2001, 240(3):147-186. 10.1016/S0022-1694(00)00340-1.
56. Soetaert K., Petzoldt T. Inverse modelling, sensitivity and Monte Carlo analysis in R using package FME. J. Stat. Softw. 2010, 33(3):1-28. doi:10.1.1.160.5179.
57. Strauch M., Lima J.E.F.W., Volk M., Lorz C., Makeschin F. The impact of Best Management Practices on simulated stream flow and sediment load in a Central Brazilian catchment. J. Environ. Manage. 2013, 127:S24-S36. 10.1016/j.jenvman.2013.01.014.
58. Tuppad P., Kannan N., Srinivasan R., Rossi C.G., Arnold J.G. Simulation of agricultural management alternatives for watershed protection. Water Resour. Manage 2010, 24:3115-3144.
59. van Griensven A., Bauwens W. Multiobjective autocalibration for semidistributed water quality models. Water Resour. Res. 2003, 39(12):1348. 10.1029/2003WR002284.
60. van Werkhoven K., Wagener T., Reed P., Tang Y. Sensitivity-guided reduction of parametric dimensionality for multi-objective calibration of watershed models. Adv. Water Resour. 2009, 32(8):1154-1169. 10.1016/j.advwatres.2009.03.002.
61. Vogel R.M., Fennessey N.M. Flow-duration curves. I: New interpretation and confidence intervals. J. Water Resour. Plan. Manage. 1994, 120(4):485-504. 10.1061/(ASCE)0733-9496(1994) 120:4(485).
62. Vrugt J.A., Gupta H.V., Bastidas L.A., Bouten W., Sorooshian S. Effective and efficient algorithm for multiobjective optimization of hydrologic models. Water Resour. Res. 2003, 39(8):1214. 10.1029/2002WR001746.
63. Williams M.R., King K.W., Macrae M.L., Ford W., Van Esbroeck C., Brunke R.I., English M.C., Schiff S.L. Uncertainty in nutrient loads from tile-drained landscapes: effect of sampling frequency, calculation algorithm, and compositing strategy. J. Hydrol. 2015, 530:306-316. 10.1016/j.jhydrol.2015.09.060.
64. Yadav M., Wagener T., Gupta H.V. Regionalization of constraints on expected watershed response behavior for improved predictions in ungauged basins. Adv. Water Resour. 2007, 30(8):1756-1774. 10.1016/j.advwatres.2007.01.005.
65. Yaeger M., Coopersmith E., Ye S., Cheng L., Viglione A., Sivapalan M. Exploring the physical controls of regional patterns of flow duration curves - Part 4: A synthesis of empirical analysis, process modeling and catchment classification. Hydrol. Earth Syst. Sci. 2012, 16:4483-4498.
66. Yeh T.-C.J., Mao D.-Q., Zha Y.-Y., Wen J.-C., Wan L., Hsu K.-C., Lee C.-H. Uniqueness, scale, and resolution issues in groundwater model parameter identification. Water Sci. Eng 2015, 8:175-194. 10.1016/j.wse.2015.08.002.
67. Yilmaz K.K., Gupta H.V., Wagener T. A process-based diagnostic approach to model evaluation: application to the NWS distributed hydrologic model. Water Resour. Res. 2008, 44(9). 10.1029/2007WR006716.
68. Yokoo Y., Sivapalan M. Towards reconstruction of the flow duration curve: development of a conceptual framework with a physical basis. Hydrol. Earth Syst. Sci. 2011, 15(9):2805-2819. 10.5194/hess-15-2805-2011.
69. Zhang H., Huang G.H., Wang D., Zhang X. Multi-period calibration of a semi-distributed hydrological model based on hydroclimatic clustering. Adv. Water Resour. 2011, 34(10):1292-1303. 10.1016/j.advwatres.2011.06.005.