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Temporal variability in stage-discharge relationships
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL.
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL.
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL.
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL.
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2012 (English)In: Journal of Hydrology, ISSN 0022-1694, E-ISSN 1879-2707, Vol. 446, 90-102 p.Article in journal (Refereed) Published
Abstract [en]

Although discharge estimations are central for water management and hydropower, there are few studies on the variability and uncertainty of their basis; deriving discharge from stage heights through the use of a rating curve that depends on riverbed geometry. A large fraction of the world's river-discharge stations are presumably located in alluvial channels where riverbed characteristics may change over time because of erosion and sedimentation. This study was conducted to analyse and quantify the dynamic relationship between stage and discharge and to determine to what degree currently used methods are able to account for such variability. The study was carried out for six hydrometric stations in the upper Choluteca River basin, Honduras, where a set of unusually frequent stage-discharge data are available. The temporal variability and the uncertainty of the rating curve and its parameters were analysed through a Monte Carlo (MC) analysis on a moving window of data using the Generalised Likelihood Uncertainty Estimation (GLUE) methodology. Acceptable ranges for the values of the rating-curve parameters were determined from riverbed surveys at the six stations, and the sampling space was constrained according to those ranges, using three-dimensional alpha shapes. Temporal variability was analysed in three ways: (i) with annually updated rating curves (simulating Honduran practices), (ii) a rating curve for each time window, and (iii) a smoothed, continuous dynamic rating curve derived from the MC analysis. The temporal variability of the rating parameters translated into a high rating-curve variability. The variability could turn out as increasing or decreasing trends and/or cyclic behaviour. There was a tendency at all stations to a seasonal variability. The discharge at a given stage could vary by a factor of two or more. The quotient in discharge volumes estimated from dynamic and static rating curves varied between 0.5 and 1.5. The difference between discharge volumes derived from static and dynamic curves was largest for sub-daily ratings but stayed large also for monthly and yearly totals. The relative uncertainty was largest for low flows but it was considerable also for intermediate and large flows. The standard procedure of adjusting rating curves when calculated and observed discharge differ by more than 5% would have required continuously updated rating curves at the studied locations. We believe that these findings can be applicable to many other discharge stations around the globe.

Place, publisher, year, edition, pages
2012. Vol. 446, 90-102 p.
Keyword [en]
Rating curve, Discharge, Uncertainty, Temporal variability, Alluvial river
National Category
Oceanography, Hydrology, Water Resources
Identifiers
URN: urn:nbn:se:uu:diva-177587DOI: 10.1016/j.jhydrol.2012.04.031ISI: 000305365300009OAI: oai:DiVA.org:uu-177587DiVA: diva2:541226
Available from: 2012-07-16 Created: 2012-07-16 Last updated: 2017-12-07Bibliographically approved
In thesis
1. Robust Water Balance Modeling with Uncertain Discharge and Precipitation Data: Computational Geometry as a New Tool
Open this publication in new window or tab >>Robust Water Balance Modeling with Uncertain Discharge and Precipitation Data: Computational Geometry as a New Tool
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Robust vattenbalansmodellering med osäkra vattenförings- och nederbördsdata : beräkningsgeometri som ett nytt verktyg
Abstract [en]

Models are important tools for understanding the hydrological processes that govern water transport in the landscape and for prediction at times and places where no observations are available. The degree of trust placed on models, however, should not exceed the quality of the data they are fed with. The overall aim of this thesis was to tune the modeling process to account for the uncertainty in the data, by identifying robust parameter values using methods from computational geometry. The methods were developed and tested on data from the Choluteca River basin in Honduras.

Quality control of precipitation and discharge data resulted in a rejection of 22% percent of daily raingage data and the complete removal of one out of the seven discharge stations analyzed. The raingage network was not found sufficient to capture the spatial and temporal variability of precipitation in the Choluteca River basin. The temporal variability of discharge was evaluated through a Monte Carlo assessment of the rating-equation parameter values over a moving time window of stage-discharge measurements. Al hydrometric stations showed considerable temporal variability in the stage-discharge relationship, which was largest for low flows, albeit with no common trend. The problem with limited data quality was addressed by identifying robust model parameter values within the set of well-performing (behavioral) parameter-value vectors with computational-geometry methods. The hypothesis that geometrically deep parameter-value vectors within the behavioral set were hydrologically robust was tested, and verified, using two depth functions. Deep parameter-value vectors tended to perform better than shallow ones, were less sensitive to small changes in their values, and were better suited to temporal transfer. Depth functions rank multidimensional data. Methods to visualize the multivariate distribution of behavioral parameters based on the ranked values were developed. It was shown that, by projecting along a common dimension, the multivariate distribution of behavioral parameters for models of varying complexity could be compared using the proposed visualization tools. This has a potential to aid in the selection of an adequate model structure considering the uncertainty in the data.

These methods allowed to quantify observational uncertainties. Geometric methods have only recently begun to be used in hydrology. It was shown that they can be used to identify robust parameter values, and some of their potential uses were highlighted.

Abstract [sv]

Modeller är viktiga verktyg för att förstå de hydrologiska processer som bestämmer vattnets transport i landskapet och för prognoser för tider och platser där det saknas mätdata. Graden av tillit till modeller bör emellertid inte överstiga kvaliteten på de data som de matas med. Det övergripande syftet med denna avhandling var att anpassa modelleringsprocessen så att den tar hänsyn till osäkerheten i data och identifierar robusta parametervärden med hjälp av metoder från beräkningsgeometrin. Metoderna var utvecklade och testades på data från Cholutecaflodens avrinningsområde i Honduras.

Kvalitetskontrollen i nederbörds- och vattenföringsdata resulterade i att 22 % av de dagliga nederbördsobservationerna måste kasseras liksom alla data från en av sju analyserade vattenföringsstationer. Observationsnätet för nederbörd befanns otillräckligt för att fånga upp den rumsliga och tidsmässiga variabiliteten i den övre delen av Cholutecaflodens avrinningsområde. Vattenföringens tidsvariation utvärderades med en Monte Carlo-skattning av värdet på parametrarna i avbördningskurvan i ett rörligt tidsfönster av vattenföringsmätningar. Alla vattenföringsstationer uppvisade stor tidsvariation i avbördningskurvan som var störst för låga flöden, dock inte med någon gemensam trend. Problemet med den måttliga datakvaliteten bedömdes med hjälp av robusta modellparametervärden som identifierades med hjälp av beräkningsgeometriska metoder. Hypotesen att djupa parametervärdesuppsättningar var robusta testades och verifierades genom två djupfunktioner. Geometriskt djupa parametervärdesuppsättningar verkade ge bättre hydrologiska resultat än ytliga, var mindre känsliga för små ändringar i parametervärden och var bättre lämpade för förflyttning i tiden. Metoder utvecklades för att visualisera multivariata fördelningar av välpresterande parametrar baserade på de rangordnade värdena. Genom att projicera längs en gemensam dimension, kunde multivariata fördelningar av välpresterande parametrar hos modeller med varierande komplexitet jämföras med hjälp av det föreslagna visualiseringsverktyget. Det har alltså potentialen att bistå vid valet av en adekvat modellstruktur som tar hänsyn till osäkerheten i data.

Dessa metoder möjliggjorde kvantifiering av observationsosäkerheter. Geometriska metoder har helt nyligen börjat användas inom hydrologin. I studien demonstrerades att de kan användas för att identifiera robusta parametervärdesuppsättningar och några av metodernas potentiella användningsområden belystes.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2013. 95 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1010
Keyword
Alpha shape, Convex hull, Depth function, Discharge, Hydrological models, Honduras, Model calibration, Parameter-value estimation, Precipitation, Rating curve, Robust, Robustness, Uncertainty estimation, Water resources., Alfaform, avbördningskurva, djupfunktion, Honduras, hydrologiska modeller, konvext hölje, modellkalibrering, nederbörd, osäkerhetsskattning, parametervärdesskattning, robust, robusthet, vattenföring, vattenresurser
National Category
Oceanography, Hydrology, Water Resources
Research subject
Hydrology
Identifiers
urn:nbn:se:uu:diva-190686 (URN)978-91-554-8575-7 (ISBN)
Public defence
2013-02-22, Axel Hambergsalen, Earth Sciences Department, Villavägen 16, Uppsala, 13:00 (English)
Opponent
Supervisors
Funder
Sida - Swedish International Development Cooperation Agency, 75007349 and SWE-2005-296
Available from: 2013-02-01 Created: 2013-01-08 Last updated: 2013-02-18Bibliographically approved

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Guerrero, Jose-LuisWesterberg, Ida K.Halldin, SvenXu, Chong-YuLundin, Lars-Christer

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