Hydrograph separation through multi objective optimization: Revealing the importance of a temporally and spatially constrained baseflow solute source

Adam, 2009, Implications of global climate change for snowmelt hydrology in the twenty-first century, Hydrol. Process., 23, 962, 10.1002/hyp.7201 Arnold, 1999, Automated methods for estimating baseflow and ground water recharge from streamflow records, JAWRA J. Am. Water Resour. Assoc., 35, 411, 10.1111/j.1752-1688.1999.tb03599.x Arnold, 1995, Automated base flow separation and recession analysis techniques, Groundwater, 33, 1010, 10.1111/j.1745-6584.1995.tb00046.x Arnold, 2000, Regional estimation of base flow and groundwater recharge in the Upper Mississippi river basin, J. Hydrol., 227, 21, 10.1016/S0022-1694(99)00139-0 Avery, 2018, Quantification of groundwater discharge in a subalpine stream using radon-222, Water, 10, 100, 10.3390/w10020100 Becerra, R.L., Coello, C.A.C., 2006. Solving hard multiobjective optimization problems using ε-constraint with cultured differential evolution. In: Runarsson, T.P., Beyer, H.-G., Burke, E., Merelo-Guervós, J.J., Whitley, L.D., Yao, X. (Eds.), Parallel Problem Solving from Nature - PPSN IX, Lecture Notes in Computer Science. Springer, Berlin, Heidelberg, pp. 543–552. https://doi.org/10.1007/11844297_55. Blum, C., 2005. Ant colony optimization: Introduction and recent trends. Phys. Life Reviews 2, 353–373. Phys. Life Rev. 2, 353–373. https://doi.org/10.1016/j.plrev.2005.10.001. Boughton, W.C., 1993. A hydrograph-based model for estimating the water yield of ungauged catchments. In: Hydrology and Water Resources Symposium. Institution of Engineers Australia, Newcastle, NSW, pp. 317–324. Branke, J., Deb, K., Dierolf, H., Osswald, M., 2004. Finding knees in multi-objective optimization. In: Yao, X., Burke, E.K., Lozano, J.A., Smith, J., Merelo-Guervós, J.J., Bullinaria, J.A., Rowe, J.E., Tiňo, P., Kabán, A., Schwefel, H.-P. (Eds.), Parallel Problem Solving from Nature – PPSN VIII, Lecture Notes in Computer Science. Springer, Berlin, Heidelberg, pp. 722–731. https://doi.org/10.1007/978-3-540-30217-9_73. Buttle, 2018, Mediating stream baseflow response to climate change: the role of basin storage, Hydrol. Process., 32, 363, 10.1002/hyp.11418 Cartwright, 2014, Contrasts between estimates of baseflow help discern multiple sources of water contributing to rivers, Hydrol. Earth Syst. Sci., 18, 15, 10.5194/hess-18-15-2014 Chapman, T., Maxwell, A., 1996. Baseflow separation-comparison of numerical methods with tracer experiments. In: Hydrology and Water Resources Symposium 1996: Water and the Environment; Preprints of Papers. Institution of Engineers, Australia. Coats, 2010, Climate change in the Tahoe basin: regional trends, impacts and drivers, Clim. Change, 102, 435, 10.1007/s10584-010-9828-3 Coello, 2018, Multi-objective optimization, Handbook Heuristics, 177, 10.1007/978-3-319-07124-4_17 Collischonn, 2013, Defining parameters for Eckhardt’s digital baseflow filter, Hydrol. Process., 27, 2614, 10.1002/hyp.9391 Combalicer, E., Lee, S.-K., Ahn, S., Kim, D., im, S., 2008. Comparing groundwater recharge and base flow in the Bukmoongol small-forested watershed, Korea. J. Earth Syst. Sci. 117, 553–566. https://doi.org/10.1007/s12040-008-0052-8. Danielescu, 2018, SEPHYDRO: a customizable online tool for hydrograph separation, Groundwater, 56, 589, 10.1111/gwat.12792 Das, 1999, On characterizing the “knee” of the Pareto curve based on Normal-Boundary Intersection, Struct. Optim., 18, 107, 10.1007/BF01195985 Deb, K., 2001. Multi-Objective Optimization using Evolutionary Algorithms. John Wiley & Sons. Deb, 2011, Understanding knee points in bicriteria problems and their implications as preferred solution principles, Eng. Optim., 43, 1175, 10.1080/0305215X.2010.548863 Deb, 2002, A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Trans. Evol. Comput., 6, 182, 10.1109/4235.996017 Deirmendjian, 2018, Carbon dioxide degassing at the groundwater-stream-atmosphere interface: isotopic equilibration and hydrological mass balance in a sandy watershed, J. Hydrol., 558, 129, 10.1016/j.jhydrol.2018.01.003 Dettinger, 2004, Simulated hydrologic responses to climate variations and change in the Merced, Carson, and American River Basins, Sierra Nevada, California, 1900–2099, Clim. Change, 62, 283, 10.1023/B:CLIM.0000013683.13346.4f Eckhardt, 2008, A comparison of baseflow indices, which were calculated with seven different baseflow separation methods, J. Hydrol., 352, 168, 10.1016/j.jhydrol.2008.01.005 Eckhardt, 2005, How to construct recursive digital filters for baseflow separation, Hydrol. Process., 19, 507, 10.1002/hyp.5675 Eichfelder, J., 2009. A Constraint method in nonlinear multi-objective optimization. In: Lecture Notes in Economics and Mathematical Systems, vol. 618. Multiobjective Programming and Goal Programming. Springer, pp. 3–12. Ficklin, 2016, Impacts of recent climate change on trends in baseflow and stormflow in United States watersheds, Geophys. Res. Lett., 43, 5079, 10.1002/2016GL069121 Gebert, W.A., Walker, J.F., Kennedy, J.L., 2011. Estimating 1970-99 average annual groundwater recharge in Wisconsin using streamflow data. https://doi.org/10.3133/ofr20091210. Hagedorn, 2015, Solute sources and water mixing in a flashy mountainous stream (Pahsimeroi River, U.S. Rocky Mountains): Implications on chemical weathering rate and groundwater–surface water interaction, Chem. Geol., 391, 123, 10.1016/j.chemgeo.2014.10.031 Haimes, 1971, On a bicriterion formation of the problems of integrated system identification and system optimization, IEEE Trans. Syst. Man Cybern., SMC-1, 296, 10.1109/TSMC.1971.4308298 Herzceg, 1993, Transport of soluble salts in a large semiarid basin: River Murray, Australia, J. Hydrol., 144, 59, 10.1016/0022-1694(93)90165-6 Hotchkiss, 2015, Sources of and processes controlling CO2 emissions change with the size of streams and rivers, Nat. Geosci., 8, 696, 10.1038/ngeo2507 Huntington, 2012, Role of surface-water and groundwater interactions on projected summertime streamflow in snow dominated regions: An integrated modeling approach, Water Resour. Res., 48, 10.1029/2012WR012319 Kennedy, J., Eberhart, R., 1995. Particle swarm optimization. In: Proceedings of ICNN’95 – International Conference on Neural Networks. Presented at the Proceedings of ICNN’95 – International Conference on Neural Networks, vol. 4, pp. 1942–194. https://doi.org/10.1109/ICNN.1995.488968. Kronholm, 2015, A comparison of high-resolution specific conductance-based end-member mixing analysis and a graphical method for baseflow separation of four streams in hydrologically challenging agricultural watersheds, Hydrol. Process., 29, 2521, 10.1002/hyp.10378 Ladson, 2013, A standard approach to baseflow separation using the Lyne and Hollick filter, Aust. J. Water Resour., 17, 25 Lenz, 2019, Identification of load dependent cell voltage model parameters from sparse input data using the mixed integer distributed ant colony optimization solver, J. Power Sources, 437, 10.1016/j.jpowsour.2019.226880 Li, 2013, Framework for assessing and improving the performance of recursive digital filters for baseflow estimation with application to the Lyne and Hollick filter, Environ. Model. Softw., 41, 163, 10.1016/j.envsoft.2012.11.009 Li, 2014, Performance assessment and improvement of recursive digital baseflow filters for catchments with different physical characteristics and hydrological inputs, Environ. Model. Softw., 54, 39, 10.1016/j.envsoft.2013.12.011 Liu, 2004, Source waters and flowpaths in a seasonally snow-covered catchment, Colorado Front Range, USA, Water Resour. Res., 40, W09401 Longobardi, 2016, Hydro-geo-chemical streamflow analysis as a support for digital hydrograph filtering in a small, rainfall dominated, sandstone watershed, J. Hydrol., 539, 177, 10.1016/j.jhydrol.2016.05.028 Lyne, V., Hollick, M., 1979. Stochastic time-variable rainfall-runoff modelling. Hydrology and Water Resources Symposium, Perth, Institution of Engineers, Australia. Maier, 2014, Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions, Environ. Model. Softw., 62, 271, 10.1016/j.envsoft.2014.09.013 Maier, 2019, Introductory overview: Optimization using evolutionary algorithms and other metaheuristics, Environ. Model. Softw., 114, 195, 10.1016/j.envsoft.2018.11.018 Marler, 2010, The weighted sum method for multi-objective optimization: New insights, Struct. Multidiscip. Optim., 41, 853, 10.1007/s00158-009-0460-7 Matthews, 1966, Geologic map of California Fresno sheet: California Division of Mines and Geology, scale, 1, 250,000 McCallum, 2010, Solute dynamics during bank storage flows and implications for chemical base flow separation, Water Resour. Res., 46, W07541, 10.1029/2009WR008539 Meixner, 2016, Implications of projected climate change for groundwater recharge in the western United States, J. Hydrol., 534, 124, 10.1016/j.jhydrol.2015.12.027 Meredith, 2016, Coal aquifer contribution to streams in the Powder River Basin, Montana, J. Hydrol., 537, 130, 10.1016/j.jhydrol.2016.03.042 Miller, 2015, A new approach for continuous estimation of baseflow using discrete water quality data: method description and comparison with baseflow estimates from two existing approaches, J. Hydrol., 522, 203, 10.1016/j.jhydrol.2014.12.039 Miller, 2014, Continuous estimation of baseflow in snowmelt-dominated streams and rivers in the Upper Colorado River Basin: A chemical hydrograph separation approach, Water Resour. Res., 50, 6986, 10.1002/2013WR014939 Mostafaie, 2018, Comparing multi-objective optimization techniques to calibrate a conceptual hydrological model using in situ runoff and daily GRACE data, Comput. Geosci., 22, 789, 10.1007/s10596-018-9726-8 Nathan, 1990, Evaluation of automated techniques for base flow and recession analyses, Water Resour. Res., 26, 1465, 10.1029/WR026i007p01465 Neff, B.P., Day, S.M., Piggott, A.R., Fuller, L.M., 2005. Base flow in the Great Lakes Basin. https://doi.org/10.3133/sir20055217. Nielsen, M.G., Westenbroek, S.M., 2019. Groundwater recharge estimates for Maine using a Soil-Water-Balance model—25-year average, range, and uncertainty, 1991 to 2015 (USGS Numbered Series No. 2019–5125), Groundwater recharge estimates for Maine using a Soil-Water-Balance model—25-year average, range, and uncertainty, 1991 to 2015, Scientific Investigations Report. U.S. Geological Survey, Reston, VA. https://doi.org/10.3133/sir20195125. Okello, 2018, Hydrograph separation using tracers and digital filters to quantify runoff components in a semi-arid mesoscale catchment, Hydrol. Process., 32, 1334, 10.1002/hyp.11491 Partington, 2012, Evaluation of outputs from automated baseflow separation methods against simulated baseflow from a physically based, surface water-groundwater flow model, J. Hydrol., 458–459, 28, 10.1016/j.jhydrol.2012.06.029 Polsenaere, 2013, Export and degassing of terrestrial carbon through watercourses draining a temperate podzolized catchment, Aquat. Sci., 75, 299, 10.1007/s00027-012-0275-2 Price, 2011, Effects of watershed topography, soils, land use, and climate on baseflow hydrology in humid regions: a review, Prog. Phys. Geogr. Earth Environ., 35, 465, 10.1177/0309133311402714 PRISM, 2010. Parameter-elevation Relationships on Independent Slopes Model – Precipitation Maps. Northwest Alliance for Computational Science and Engineering (http://www.prism.oregonstate.edu/). Raffensperger, J.P., Baker, A.C., Blomquist, J.D., Hopple, J.A., 2017. Optimal hydrograph separation using a recursive digital filter constrained by chemical mass balance, with application to selected Chesapeake Bay watersheds (USGS Numbered Series No. 2017–5034), Scientific Investigations Report. U.S. Geological Survey, Reston, VA. Rammal, 2018, Technical note: an operational implementation of recursive digital filter for base flow separation, Water Resour. Res., 54, 8528, 10.1029/2018WR023351 Reddy, 2007, Multi-objective particle swarm optimization for generating optimal trade-offs in reservoir operation, Hydrol. Process., 21, 10.1002/hyp.6507 Rimmer, 2014, Optimal hydrograph separation filter to evaluate transport routines of hydrological models, J. Hydrol., 514, 249, 10.1016/j.jhydrol.2014.04.033 Ritter, 2013, Performance evaluation of hydrological models: Statistical significance for reducing subjectivity in goodness-of-fit assessments, J. Hydrol., 480, 33, 10.1016/j.jhydrol.2012.12.004 Rumsey, 2015, Regional scale estimates of baseflow and factors influencing baseflow in the Upper Colorado River Basin, J. Hydrol. Reg. Stud., 4, 91, 10.1016/j.ejrh.2015.04.008 Rutledge, A.T., 1998. Computer programs for describing the recession of ground-water discharge and for estimating mean ground-water recharge and discharge from streamflow records-update (USGS Numbered Series No. 98-4148), Water-Resources Investigations Report. U.S. Dept. of the Interior, U.S. Geological Survey ; Information Services,. Sanford, W.E., Nelms, D.L., Pope, J.P., Selnick, D.L., 2012. Quantifying components of the hydrologic cycle in Virginia using chemical hydrograph separation and multiple regression analysis (USGS Numbered Series No. 2011-5198), Scientific Investigations Report. U.S. Geological Survey, Reston, VA. Schlueter, 2014, MIDACO software performance on interplanetary trajectory benchmarks, Adv. Space Res., 54, 744, 10.1016/j.asr.2014.05.002 Schlueter, 2013, MIDACO on MINLP space applications, Adv. Space Res., 51, 1116, 10.1016/j.asr.2012.11.006 Schlueter, M., Yam, C.H., Watanabe, T., Oyama, A., 2016. Parallelization impact on many-objective optimization for space trajectory design. Int. J. Mach. Learn. Comput. 6. Schlüter, M., 2018. Mixed Integer Distributed Ant Colony Optimization (MIDACO) -Solver. User Manual. Simpson, 1991, Salinity and evaporation in the River Murray Basin, Australia, J. Hydrol., 124, 1, 10.1016/0022-1694(91)90003-Z Sloto, R.A., Crouse, M.Y., 1996. HYSEP: a computer program for streamflow hydrograph separation and analysis: U.S. Geological Survey Water-Resources Investigations Report 96-4040. Socha, K., Dorigo, M., 2008. Ant colony optimization for continuous domains. Eur. J. Oper. Res. https://doi.org/10.1016/j.ejor.2006.06.046. Spongberg, 2000, Spectral analysis of base flow separation with digital filters, Water Resour. Res., 36, 745, 10.1029/1999WR900303 Srinivas, 1994, Muiltiobjective optimization using nondominated sorting in genetic algorithms, Evol. Comput., 2, 221, 10.1162/evco.1994.2.3.221 Stewart, 2007, Calibration of base flow separation methods with streamflow conductivity, Ground Water, 45, 17, 10.1111/j.1745-6584.2006.00263.x Tortajada, 2017, The California drought: coping responses and resilience building, Environ. Sci. Policy, 78, 97, 10.1016/j.envsci.2017.09.012 Tranter, Martyn, 1991. Controls on the Composition of Snowmelt, in: Davies, T.D., Tranter, M., Jones, H.G. (Eds.), Seasonal Snowpacks, NATO ASI Series. Springer, Berlin, Heidelberg, pp. 241–271. https://doi.org/10.1007/978-3-642-75112-7_11. Uhlenbrook, 2003, Quantifying uncertainties in tracer based hydrograph separations: a case study for two-, three- and five component hydrograph separations in a mountainous catchment, Hydrol. Process., 17, 431, 10.1002/hyp.1134 USGS, 2019. Water Data for the Nation – http://waterdata.usgs.gov/nwis [WWW Document]. Vrugt, 2003, Effective and efficient algorithm for multiobjective optimization of hydrologic models, Water Resour. Res., 39, 1214, 10.1029/2002WR001746 Wahl, K.L., Wahl, T.L., 1995. Determining the Flow of Comal Springs at New Braunfels, Texas; Texas Water ’95; American Society of Civil Engineers: San Antonio, TX, USA. Wang, 2017, Application and analysis of methods for selecting an optimal solution from the pareto-optimal front obtained by multiobjective optimization, Ind. Eng. Chem. Res., 56, 560, 10.1021/acs.iecr.6b03453 Williams, 1991, Solute chemistry of snowmelt and runoff in an Alpine Basin, Sierra Nevada, Water Resour. Res., 27, 1575, 10.1029/90WR02774 Yang, 2017, Lags in hydrologic recovery following an extreme drought: Assessing the roles of climate and catchment characteristics, Water Resour. Res., 53, 4821, 10.1002/2017WR020683 Yihdego, Y., 2017. Drought and Groundwater Quality in Coastal Areas [WWW Document]. Handb. Drought Water Scarcity. https://doi.org/10.1201/9781315226781-15. Zhang, 2017, Evaluating relative merits of four baseflow separation methods in Eastern Australia, J. Hydrol., 549, 252, 10.1016/j.jhydrol.2017.04.004 Zitzler, E., 1999. Evolutionary Algorithms for Multiobjective Optimization: Methods and Applications (PhD Dissertation). Eidgenössische Technische Hochschule Zürich. Zobaa, 2019, Mixed-integer distributed ant colony multi-objective optimization of single-tuned passive harmonic filter parameters, IEEE Access, 7, 44862, 10.1109/ACCESS.2019.2903910 Zomlot, 2015, Spatial distribution of groundwater recharge and base flow: assessment of controlling factors, J. Hydrol. Reg. Stud., 4, 349, 10.1016/j.ejrh.2015.07.005