Hilary McMillan: Hydrology Information and Downloads
I am a hydrological scientist. For the last 9 years I worked at NIWA: the National Institute of Water and Atmospheric Research, in Christchurch, New Zealand. I am now Associate Professor of Water Resources at San Diego State University, USA.
My research interests include hydrological process studies, human impacts on hydrology, hydrological model structure, uncertainty estimation, flood prediction and risk assessment, climate change impacts on hydrology, water resource management.
I led the NZ-government funded 'Waterscape' project, a collaboration between NIWA, Aqualinc and GNS. The project aims to provide a scientific basis for the integrated understanding, modelling and management of surface water and groundwater in New Zealand. It includes development of new field instrument networks to measure evapo-transpiration, land surface recharge and surfacewater-groundwater interactions, and develops new quantitative models of vadose zone, catchment and groundwater processes. It works with end-users and stakeholders to develop water resource management tools.
I led NIWA's research into hydrological model development for operational flow and flood forecasting.
Internationally, I am currently Chair of the IAHS hydrological decade 2013-2022 with the theme `Panta Rhei: Change in Hydrology and Society'. The decade recognises the urgency of hydrological research to understand and predict the interactions of society and water, to support sustainable water resource use under changing climatic and environmental conditions.
Some current projects:
Westerberg, I., McMillan, H. (in press) Uncertainty in hydrological signatures, Hydrol. Earth Syst. Sci., 12, 4233-4270, doi.org/doi:10.5194/hess-19-3951-2015, 2015.
Pechlivanidis, I., Jackson, B., McMillan, H., Gupta, H. (in press). Robust informational entropy-based descriptors of flow in catchment hydrology. Hydrological Sciences Journal. http://dx.doi.org/DOI:10.1080/02626667.2014.983516
McMillan, H., Srinivasan MS. (2015) Characteristics and controls of variability in surface and groundwaters in a headwater catchment. Hydrology and Earth System Sciences 19, p 1767-1786. http://doi.org/doi:10.5194/hess-19-1767-2015
McMillan, H., Westerberg, I. (2015) Rating curve estimation under epistemic uncertainty. Hydrological Processes 29: 1873-1882. http://doi.org/DOI:10.1002/hyp.10419
McMillan, H. , M. Gueguen, E. Grimon, R. Woods, M. Clark, D. Rupp. (2014). Spatial variability of hydrological processes and model structure diagnostics in a 50 km2 catchment. Hydrological Processes 28(18): 4896-4913. Pre-print Article
Pechlivanidis, I. G., B. Jackson, H. McMillan, H. Gupta. (2014). Use of an entropy based metric in multi-objective calibration to improve model performance. Water Resources Research. 50: 8066-8083. Article
Montanari, A.; Young, G.; Savenije, H. H. G.; Hughes, D.; Wagener, T.; Ren, L. L.; Koutsoyiannis, D.; Cudennec, C.; Toth, E.; Grimaldi, S.; Bloeschl, G.; Sivapalan, M.; Beven, K.; Gupta, H.; Hipsey, M.; Schaefli, B.; Arheimer, B.; Boegh, E.; Schymanski, S. J.; Di Baldassarre, G.; Yu, B.; Hubert, P.; Huang, Y.; Schumann, A.; Post, D. A.; Srinivasan, V.; Harman, C.; Thompson, S.; Rogger, M.; Viglione, A.; McMillan, H.; Characklis, G.; Pang, Z.; Belyaev, V. (2013). "Panta Rhei-Everything Flows" : Change in hydrology and society-The IAHS Scientific Decade 2013-2022. Hydrological Sciences Journal: 58(6): 1256-1275. Article
McMillan, H. , E.O. Hreinsson, M. Clark, S. Singh, C. Zammit, M. Uddstrom (2013). Operational hydrological data assimilation with the recursive ensemble Kalman filter. Hydrol. Earth Syst. Sci. : 17, 21-38, doi:10.5194/hess-17-21-2013. Article
Singh, S., H. McMillan, A. Bardossy, (2013). Use of the data depth function to differentiate between case of interpolation and extrapolation in hydrological model prediction. Journal of Hydrology 477: 213-228. Article
Ackerley, D., R. G. Bell, A. B. Mullan, H. McMillan (2013). Estimation of regional departures from global-average sea-level rise around New Zealand from AOGCM simulations. Weather and Climate. 33: 2-22.
McMillan, H. (2012) Effect of spatial variability and seasonality in soil moisture on drainage thresholds and fluxes in a conceptual hydrological model. Hydrological Processes 26(18): 2838-2844 Pre-print Article
McMillan, H., D. Tetzlaff, M. Clark, C. Soulsby (2012) Do time variant tracers aid the evaluation of hydrological model structure? A multi-model approach. Water Resources Research. 48: W05501 Pre-print Article
McMillan, H., T. Krueger, J. Freer (2012). Benchmarking observational uncertainties for hydrology: rainfall, river discharge and water quality. Hydrological Processes 26(26): 4078-4111 Pre-print Article
Pechlivanidis I.G., Jackson B., McMillan H. (2012) Using an informational Entropy-Based Metric as a Diagnostic of Flow Duration to Drive Model Parameter Identification. Global NEST Journal Article
McMillan, H., M. Duncan, G. Smart, J. Sturman, S. Poyck, S. Reese, A. Tait, E. Hreinsson, J. Walsh (2012). The Urban Impacts Toolbox: An example of modelling the effect of climate change and sea level rise on future flooding. Weather and Climate 32(2): 21-39. Article
Gawith, D., D.G. Kingston, H. McMillan (2012). The effects of climate change on runoff in the Lindis and Matukituki catchments, Otago, New Zealand. Journal of Hydrology (NZ) 51(2):121-136. Article
McMillan, H., M. Clark, W. Bowden, M. Duncan, R.Woods (2011). Hydrological field data from a modeller's perspective: Part 1. Diagnostic tests for model structure. Hydrological Processes: 25(4): 511-522 Article Pre-print
Clark, M., McMillan, H. , Collins, D., Kavetski, D., Woods, R. (2011). Hydrological field data from a modeller's perspective: Part 2. Process-based evaluation of model hypotheses. Hydrological Processes: 25(4): 523-543 Article Pre-print
Poyck, S., J. Hendrikx, H. McMillan. E.O. Hreinsson, R. Woods (2011) Combined snow- and streamflow modelling to estimate impacts of climate change on water resources in the Clutha, New Zealand. Journal of Hydrology (NZ) Article
McMillan, H., B. Jackson, M. Clark, D. Kavetski, R. Woods (2010). Input Uncertainty in Hydrological Models: An Evaluation of Error Models for Rainfall . Journal of Hydrology 400(1-2): 83-94 Article Pre-print
McMillan, H., J. Freer, F. Pappenberger, T. Krueger, M. Clark (2010). Impacts of Uncertain River Flow Data on Rainfall-Runoff Model Calibration and Discharge Predictions . Hydrological Processes DOI: 10.1002/hyp.7587 Article Pre-print
2009), Rainfall-runoff model calibration using informal likelihood measures within a Markov chain Monte Carlo sampling scheme, Water Resour. Res., 45, W04418, doi:10.1029/2008WR007288. Article Pre-print(
McMillan H., J. Brasington (2008), End-to-end flood risk assessment: A coupled model cascade with uncertainty estimation, Water Resour. Res., 44, W03419, doi:10.1029/2007WR005995. Article Pre-print
McMillan H., J. Brasington (2007). Reduced complexity strategies for modelling urban floodplain inundation. Geomorphology, Volume 90, Issues 3-4, Pages 226-243. Article Pre-print
Freer, J.E., McMillan, H., McDonnell, J.J., Beven, K.J. (2004).Constraining dynamic TOPMODEL responses for imprecise water table information using fuzzy rule based performance measures. Journal of Hydrology, Volume 291, Issues 3-4, Pages 254-277 Article Pre-print
Pechlivanidis, I.G., B. Jackson, H. McMillan, H. Gupta (2011). Driving model parameter identification using informational entropy-based metrics. Proceedings of the 12th International Conference on Environmental Science and Technology (CEST2011), 8 - 10 September 2011, Rhodes island, Greece Article
Clark, M.P., D. Kavetski, F. Fenicia, H. McMillan (2011). The quest for physically realistic streamflow forecasting models. Proceedings of the Water Information Research and Development Alliance (WIRADA) Conference, CSIRO, 2011 Pre-print
Pechlivanidis I.G., Jackson B., McMillan H. (2010) The Use of Entropy as a Model Diagnostic in Rainfall-Runoff Modelling . Proceedings of the 2010 International Congress on Environmental Modelling and Software, Ottawa, Canada Article
McMillan, H., M. Clark, R. Woods, M. Duncan, MS. Srinivasan, A. Western, D. Goodrich (2010). Improving Perceptual and Conceptual Hydrological Models using Data from Small Basins. Status and Perspectives of Hydrology in Small Basins (Proceedings of the Workshop held at Goslar-Hahnenklee, Germany, 30 March-2 April 2009). IAHS Publ. 336-08, 2010. Article Pre-print
McMillan, H.K., Tetzlaff, D., Clark, M., Soulsby, C.
Evaluating hydrological model structure using tracer data within a multi-model framework
Presented at American Geophysical Union Fall Meeting, San Francisco, 2011.
McMillan, H.K., Clark, M.P., Martinez, G., Goodrich, D., Srinivasan, M.S., Duncan, M., Woods, R., Western, A.
Diagnostics for Model Structure: Improving Hydrological Models using Data from Experimental Basins.
Presented at European Geophysical Union Conference, Vienna, 2009.
McMillan, H.K., Freer, J., Pappenberger, F., Krueger, T., Clark, M.P.
Impacts of Uncertain Flow Data on Rainfall-Runoff Model Calibration and Discharge Predictions in a Mobile-Bed River
Presented at American Geophysical Union Fall Meeting, San Francisco, 2008.
McMillan, H.K., Clark, M.P., Ibbitt, R.P.
Calibration strategies for distributed hydrological models using qualitative knowledge of spatially variable process characteristics.
Presented at European Geophysical Union Conference, Vienna, 2008.
Freer, J.E., McMillan, H. K., McDonnell, J.J., Beven, K.J.
Constraining dynamic TOPMODEL responses for imprecise water table information using fuzzy rule based performance measures.
Presented at European Geophysical Union Conference, Nice, 2003.
Download my thesis here: 'End-to-End Flood Risk Assessment: A Model Cascade with Uncertainty Estimation'.