Articles | Volume 385
https://doi.org/10.5194/piahs-385-399-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/piahs-385-399-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Bayesian inference of synthetic daily rating curves by coupling Chebyshev Polynomials and the GR4J model
Rafael Navas
CORRESPONDING AUTHOR
Hidrología e Hidráulica, Departamento del Agua, CENUR – Litoral Norte, Universidad de la República, Salto 50000, Uruguay
Programa Nacional de Investigación en Producción y Sustentabilidad Ambiental, Instituto Nacional de Investigación Agropecuaria, La Estanzuela 70000, Uruguay
Pablo Gamazo
Hidrología e Hidráulica, Departamento del Agua, CENUR – Litoral Norte, Universidad de la República, Salto 50000, Uruguay
R. Willem Vervoort
ARC ITTC in Data Analytics for Resources and Environments & School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW 2006, Australia
Related authors
Andrés Saracho, Rafael Navas, Pablo Gamazo, and Elena Alvareda
Proc. IAHS, 385, 423–427, https://doi.org/10.5194/piahs-385-423-2024, https://doi.org/10.5194/piahs-385-423-2024, 2024
Short summary
Short summary
This work evaluated the impact of irrigation downstream of reservoirs in agricultural basins It was found that the impact of irrigation due to return flows is not homogeneous across the stream and varies between seasons Results indicates that although the effect of the dam construction is the reduction of the flow in the channel, this can be partially reversed under certain conditions: particularly during the dry season and in sections with significant accumulation of irrigation return flows
Andrés Saracho, Rafael Navas, Pablo Gamazo, and Elena Alvareda
Proc. IAHS, 385, 423–427, https://doi.org/10.5194/piahs-385-423-2024, https://doi.org/10.5194/piahs-385-423-2024, 2024
Short summary
Short summary
This work evaluated the impact of irrigation downstream of reservoirs in agricultural basins It was found that the impact of irrigation due to return flows is not homogeneous across the stream and varies between seasons Results indicates that although the effect of the dam construction is the reduction of the flow in the channel, this can be partially reversed under certain conditions: particularly during the dry season and in sections with significant accumulation of irrigation return flows
Keirnan Fowler, Murray Peel, Margarita Saft, Tim J. Peterson, Andrew Western, Lawrence Band, Cuan Petheram, Sandra Dharmadi, Kim Seong Tan, Lu Zhang, Patrick Lane, Anthony Kiem, Lucy Marshall, Anne Griebel, Belinda E. Medlyn, Dongryeol Ryu, Giancarlo Bonotto, Conrad Wasko, Anna Ukkola, Clare Stephens, Andrew Frost, Hansini Gardiya Weligamage, Patricia Saco, Hongxing Zheng, Francis Chiew, Edoardo Daly, Glen Walker, R. Willem Vervoort, Justin Hughes, Luca Trotter, Brad Neal, Ian Cartwright, and Rory Nathan
Hydrol. Earth Syst. Sci., 26, 6073–6120, https://doi.org/10.5194/hess-26-6073-2022, https://doi.org/10.5194/hess-26-6073-2022, 2022
Short summary
Short summary
Recently, we have seen multi-year droughts tending to cause shifts in the relationship between rainfall and streamflow. In shifted catchments that have not recovered, an average rainfall year produces less streamflow today than it did pre-drought. We take a multi-disciplinary approach to understand why these shifts occur, focusing on Australia's over-10-year Millennium Drought. We evaluate multiple hypotheses against evidence, with particular focus on the key role of groundwater processes.
Gonzalo Sapriza-Azuri, Pablo Gamazo, Saman Razavi, and Howard S. Wheater
Hydrol. Earth Syst. Sci., 22, 3295–3309, https://doi.org/10.5194/hess-22-3295-2018, https://doi.org/10.5194/hess-22-3295-2018, 2018
Short summary
Short summary
Arctic and subarctic regions are amongst the most susceptible regions on Earth to climate change. There, models require a proper representation of the interactions between climate and hydrology. Typically these model represent the soil with shallow depths, whereas for cold regions, deep soil is needed. To address this, we run model experiments to characterize the effect of soil depth and temperature soil initialization. Our results demonstrate that 20 m of soil profile is essential.
Cited articles
Andrews, F. T., Croke, B. F. W., and Jakeman, A. J.: An open software environment for hydrological model assessment and development, Environ. Modell. Softw., 26, 1171–1185, https://doi.org/10.1016/j.envsoft.2011.04.006, 2011.
Arsenault, R. and Brissette, F. P.: Continuous streamflow prediction in ungauged basins: The effects of equifinality and parameter set selection on uncertainty in regionalization approaches, Water Resour. Res., 50, 6135–6153, https://doi.org/10.1002/2013WR014898, 2014.
Bhandari, B., Markert, K., Mishra, V., Markert, A., and Griffin, R.: Investigation of Data-Driven Rating Curve (DDRC) Approach, Water, 15, 604, https://doi.org/10.3390/w15030604, 2023.
Blöschl, G. and Sivapalan, M.: Scale issues in hydrological modelling: A review, Hydrol. Process., 9, 251–290, https://doi.org/10.1002/hyp.3360090305, 1995.
Bureau of Meteorology: Water Data Online, Water Information, Bureau of Meteorology [data set], http://www.bom.gov.au/waterdata/, last access: 14 September 2023.
Coron, L., Thirel, G., Delaigue, O., Perrin, C., and Andréassian, V.: The suite of lumped GR hydrological models in an R package, Environ. Modell. Softw., 94, 166–171, https://doi.org/10.1016/j.envsoft.2017.05.002, 2017.
Di Baldassarre, G. and Claps, P.: A hydraulic study on the applicability of flood rating curves, Hydrol. Res., 42, 10–19, https://doi.org/10.2166/nh.2010.098, 2011.
Dottori, F., Martina, M. L. V., and Todini, E.: A dynamic rating curve approach to indirect discharge measurement, Hydrol. Earth Syst. Sci., 13, 847–863, https://doi.org/10.5194/hess-13-847-2009, 2009.
Fenton, J. D.: On the generation of stream rating curves, J. Hydrol., 564, 748–757, https://doi.org/10.1016/j.jhydrol.2018.07.025, 2018.
Flores, N., Rodríguez, R., Yépez, S., Osores, V., Rau, P., Rivera, D., and Balocchi, F.: Comparison of Three Daily Rainfall-Runoff Hydrological Models Using Four Evapotranspiration Models in Four Small Forested Watersheds with Different Land Cover in South-Central Chile, Water, 13, 3191, https://doi.org/10.3390/w13223191, 2021.
Hidayat, H., Vermeulen, B., Sassi, M. G., Torfs, P. J. J. F., and Hoitink, A. J. F.: Discharge estimation in a backwater affected meandering river, Hydrol. Earth Syst. Sci., 15, 2717–2728, https://doi.org/10.5194/hess-15-2717-2011, 2011.
Jalbert, J., Mathevet, T., and Favre, A.-C.: Temporal uncertainty estimation of discharges from rating curves using a variographic analysis, J. Hydrol., 397, 83–92, https://doi.org/10.1016/j.jhydrol.2010.11.031, 2011.
Jeffrey, S. J., Carter, J. O., Moodie, K. B., Beswick, A. R.: Using Spatial Interpolation to Construct a Comprehensive Archive of Australian Climate Data, Environ. Modell. Softw., 16, 309–330, https://doi.org/10.1016/S1364-8152(01)00008-1, 2001.
Jian, J., Ryu, D., Costelloe, J. F., and Su, C.-H.: Towards hydrological model calibration using river level measurements, J. Hydrol. Reg. Stud., 10, 95–109, https://doi.org/10.1016/j.ejrh.2016.12.085, 2017.
Kiang, J. E., Gazoorian, C., McMillan, H., Coxon, G., Le Coz, J., Westerberg, I. K., Belleville, A., Sevrez, D., Sikorska, A. E., Petersen-Øverleir, A., Reitan, T., Freer, J., Renard, B., Mansanarez, V., and Mason, R.: A Comparison of Methods for Streamflow Uncertainty Estimation, Water Resour. Res., 54, 7149–7176, https://doi.org/10.1029/2018WR022708, 2018.
Kim, Y., Oh, S., Lee, S., Byun, J., and An, H.: Application of Stage-Fall-Discharge Rating Curves to a Reservoir Based on Acoustic Doppler Velocity Meter Measurement Data, Water, 13, 2443, https://doi.org/10.3390/w13172443, 2021.
Kittel, C. M. M., Jiang, L., Tøttrup, C., and Bauer-Gottwein, P.: Sentinel-3 radar altimetry for river monitoring – a catchment-scale evaluation of satellite water surface elevation from Sentinel-3A and Sentinel-3B, Hydrol. Earth Syst. Sci., 25, 333–357, https://doi.org/10.5194/hess-25-333-2021, 2021.
Lang, M., Pobanz, K., Renard, B., Renouf, E., and Sauquet, E.: Extrapolation of rating curves by hydraulic modelling, with application to flood frequency analysis, Hydrolog. Sci. J., 55, 883–898, https://doi.org/10.1080/02626667.2010.504186, 2010.
Le Coz, J.: A literature review of methods for estimating the uncertainty associated with stage-discharge relations, WMO, Rep. PO6a, 21, https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.400.8656&rep=rep1&type=pdf (last access: 14 September 2023), 2012.
Lee, W. S., Lee, K. S., Kim, S. U., and Chung, E.-S.: The Development of Rating Curve Considering Variance Function Using Pseudo-likelihood Estimation Method, Water Resour. Manage., 24, 321–348, https://doi.org/10.1007/s11269-009-9448-8, 2010.
Lima, F. N., Fernandes, W., and Nascimento, N.: Joint calibration of a hydrological model and rating curve parameters for simulation of flash flood in urban areas, Rev. Bras. de Recur. Hidr., 24, https://doi.org/10.1590/2318-0331.241920180066, 2019.
McMahon, T. A. and Peel, M. C.: Uncertainty in stage–discharge rating curves: application to Australian Hydrologic Reference Stations data, Hydrolog. Sci. J., 64, 255–275, https://doi.org/10.1080/02626667.2019.1577555, 2019.
McMillan, H., Freer, J., Pappenberger, F., Krueger, T., and Clark, M.: Impacts of uncertain river flow data on rainfall-runoff model calibration and discharge predictions, Hydrol. Process., 24, 1270–1284, https://doi.org/10.1002/hyp.7587, 2010.
Morlot, T., Perret, C., Favre, A.-C., and Jalbert, J.: Dynamic rating curve assessment for hydrometric stations and computation of the associated uncertainties: Quality and station management indicators, J. Hydrol., 517, 173–186, https://doi.org/10.1016/j.jhydrol.2014.05.007, 2014.
Narbondo, S., Gorgoglione, A., Crisci, M., and Chreties, C.: Enhancing Physical Similarity Approach to Predict Runoff in Ungauged Watersheds in Sub-Tropical Regions, Water, 12, 528, https://doi.org/10.3390/w12020528, 2020.
Petersen-Øverleir, A.: Modelling stage – discharge relationships affected by hysteresis using the Jones formula and nonlinear regression, Hydrolog. Sci. J., 51, 365–388, https://doi.org/10.1623/hysj.51.3.365, 2006.
Pedersen, Ø., Aberle, J., and Rüther, N.: Hydraulic scale modelling of the rating curve for a gauging station with challenging geometry, Hydrol. Res., 50, 825–836, https://doi.org/10.2166/nh.2019.044, 2019.
Perret, E., Renard, B., and Le Coz, J.: A Rating Curve Model Accounting for Cyclic Stage-Discharge Shifts due to Seasonal Aquatic Vegetation, Water Resour. Res., 57, e2020WR027745, https://doi.org/10.1029/2020WR027745, 2021.
Perrin, C., Michel, C., and Andréassian, V.: Improvement of a parsimonious model for streamflow simulation, J. Hydrol., 279, 275–289, https://doi.org/10.1016/S0022-1694(03)00225-7, 2003.
Qi, W., Chen, J., Li, L., Xu, C., Li, J., Xiang, Y., and Zhang, S.: A framework to regionalize conceptual model parameters for global hydrological modeling, Hydrol. Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/hess-2020-127, 2020.
Queensland Government: SILO – Australian climate data from 1889 to yesterday, Queensland Government [data set], https://www.longpaddock.qld.gov.au/silo/, last access: 14 September 2023.
Reistad, K., Petersen-Øverleir, A., and Bogetveit, L.: Setting up rating curves using HEC-RAS, VANN, Journal of the Norwegian Water Association, 3, 20–30, 2007.
Reitan, T. and Petersen-Øverleir, A.: Bayesian methods for estimating multi-segment discharge rating curves, Stoch. Environ. Res. Risk Assess., 23, 627–642, https://doi.org/10.1007/s00477-008-0248-0, 2009.
Sellami, H., La Jeunesse, I., Benabdallah, S., and Vanclooster, M.: Parameter and rating curve uncertainty propagation analysis of the SWAT model for two small Mediterranean catchments, Hydrolog. Sci. J., 58, 1635–1657, https://doi.org/10.1080/02626667.2013.837222, 2013.
Sikorska, A. E. and Renard, B.: Calibrating a hydrological model in stage space to account for rating curve uncertainties: general framework and key challenges, Adv. Water Resour., 105, 51–66, https://doi.org/10.1016/j.advwatres.2017.04.011, 2017.
Soetaert, K. and Petzoldt, T.: Inverse Modelling, Sensitivity and Monte Carlo Analysis in R Using Package FME, J. Stat. Soft. [software], 33, 1–28, https://doi.org/10.18637/jss.v033.i03, 2010.
WMO: Manual on stream gauging, World Meteorological Organization, Geneva, 2 pp., https://library.wmo.int/viewer/35848?medianame=1044_Vol_I_en_#page=1&viewer=picture&o=&n=0&q=, 2010.
Yang, X., Magnusson, J., Rizzi, J., and Xu, C.-Y.: Runoff prediction in ungauged catchments in Norway: comparison of regionalization approaches, Hydrol. Res., 49, 487–505, https://doi.org/10.2166/nh.2017.071, 2018.
Short summary
It’s difficult to estimate the daily discharge of a river when only one instantaneous level record is available per day. This work proposes to estimate synthetic daily rating curves from nearby gauged locations using a rainfall-runoff model and bayesian inference. The results can help provide a more comprehensive understanding of the hydrological functioning of systems where only one instantaneous stage level per day is available.
It’s difficult to estimate the daily discharge of a river when only one instantaneous level...