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1.
River discharge values, estimated using a rating curve, are subject to both random and epistemic errors. We present a new likelihood function, the ‘Voting Point’ likelihood that accounts for both error types and enables generation of multiple possible multisegment power‐law rating curve samples that aim to represent the total uncertainty. The rating curve samples can be used for subsequent discharge analysis that needs total uncertainty estimation, e.g. regionalisation studies or calculation of hydrological signatures. We demonstrate the method using four catchments with diverse rating curve error characteristics, where epistemic uncertainty sources include weed growth, scour and redeposition of the bed gravels in a braided river, and unconfined high flows. The results show that typically, the posterior rating curve distributions include all of the gauging points and succeed in representing the spread of discharge values caused by epistemic rating errors. We aim to provide a useful method for hydrology practitioners to assess rating curve, and hence discharge, uncertainty that is easily applicable to a wide range of catchments and does not require prior specification of the particular types and causes of epistemic error at the gauged location. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
2.
Grey S. Nearing Yudong Tian Hoshin V. Gupta Martyn P. Clark Kenneth W. Harrison Steven V. Weijs 《水文科学杂志》2016,61(9):1666-1678
ABSTRACTUncertainty is an epistemological concept in the sense that any meaningful understanding of uncertainty requires a theory of knowledge. Therefore, uncertainty resulting from scientific endeavors can only be properly understood in the context of a well-defined philosophy of science. Our main message here is that much of the discussion about uncertainty in hydrology has lacked grounding in these foundational concepts, and has resulted in a controversy that is largely the product of logical errors rather than true (axiomatic) disagreement. As an example, we explore the current debate about the appropriate role of probability theory for hydrological uncertainty quantification. Our main messages are: (1) apparent (and/or claimed) limitations of probability theory are not actually consequences of that theory, but rather of deeper underlying epistemological (and ontological) issues; (2) questions about the appropriateness of probability theory are only meaningful if posed as questions about our preferred philosophy of science; and (3) questions about uncertainty may often be better posed as questions about available information and information use efficiency. Our purpose here is to discuss how hydrologists might ask more meaningful questions about uncertainty. 相似文献
3.
Facets of uncertainty: epistemic uncertainty,non-stationarity,likelihood, hypothesis testing,and communication 总被引：1，自引：1，他引：0
Keith Beven 《水文科学杂志》2016,61(9):1652-1665
ABSTRACTThis paper presents a discussion of some of the issues associated with the multiple sources of uncertainty and non-stationarity in the analysis and modelling of hydrological systems. Different forms of aleatory, epistemic, semantic, and ontological uncertainty are defined. The potential for epistemic uncertainties to induce disinformation in calibration data and arbitrary non-stationarities in model error characteristics, and surprises in predicting the future, are discussed in the context of other forms of non-stationarity. It is suggested that a condition tree is used to be explicit about the assumptions that underlie any assessment of uncertainty. This also provides an audit trail for providing evidence to decision makers.
Editor D. Koutsoyiannis; Associate editor S. Weijs 相似文献
4.
Uncertainty in discharge data must be critically assessed before data can be used in, e.g. water resources estimation or hydrological modelling. In the alluvial Choluteca River in Honduras, the river‐bed characteristics change over time as fill, scour and other processes occur in the channel, leading to a non‐stationary stage‐discharge relationship and difficulties in deriving consistent rating curves. Few studies have investigated the uncertainties related to non‐stationarity in the stage‐discharge relationship. We calculated discharge and the associated uncertainty with a weighted fuzzy regression of rating curves applied within a moving time window, based on estimated uncertainties in the observed rating data. An 18‐year‐long dataset with unusually frequent ratings (1268 in total) was the basis of this study. A large temporal variability in the stage‐discharge relationship was found especially for low flows. The time‐variable rating curve resulted in discharge estimate differences of ? 60 to + 90% for low flows and ± 20% for medium to high flows when compared to a constant rating curve. The final estimated uncertainty in discharge was substantial and the uncertainty limits varied between ? 43 to + 73% of the best discharge estimate. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
5.
Rating curve uncertainty and change detection in discharge time series: case study with 44‐year historic data from the Nyangores River,Kenya 
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下载免费PDF全文 The intersection of the developing topic of rating curve and discharge series uncertainty with the topic of hydrological change detection (e.g., in response to land cover or climatic change) has not yet been well studied. The work herein explores this intersection, with consideration of a long‐term discharge response (1964–2007) for a ~650‐km2 headwater basin of the Mara River in west Kenya, starting with stream rating and daily gauge height data. A rating model was calibrated using Bayesian methods to quantify uncertainty intervals in model parameters and predictions. There was an unknown balance of random and systemic error in rating data scatter (a scenario not likely unique to this basin), which led to an unknown balance of noise and information in the calibrated statistical error model. This had implications on testing for hydrological change. Overall, indications were that shifts in basin's discharge response were rather subtle over the 44‐year period. A null hypothesis for change using flow duration curves (FDCs) from four different 8‐year data intervals could be either accepted or rejected over much of the net flow domain depending on different applications of the statistical error model (each with precedence in the literature). The only unambiguous indication of change in FDC comparisons appeared to be a reduction in lowest baseflow in recent years (flows with >98% exceedance probability). We defined a subjective uncertainty interval based on an intermediate balance of random and systematic error in the rating model that suggested a possibility of more prevalent impacts. These results have relevance to management in the Mara basin and to future studies that might establish linkages to historic land use and climatic factors. The concern about uncertain uncertainty intervals (uncertainty2) extends beyond the Mara and is relevant to testing change where non‐random rating errors may be important and subtle responses are investigated. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
6.
Logic-tree Approach for Probabilistic Tsunami Hazard Analysis and its Applications to the Japanese Coasts 总被引：2，自引：0，他引：2
Tadashi Annaka Kenji Satake Tsutomu Sakakiyama Ken Yanagisawa Nobuo Shuto 《Pure and Applied Geophysics》2007,164(2-3):577-592
For Probabilistic Tsunami Hazard Analysis (PTHA), we propose a logic-tree approach to construct tsunami hazard curves (relationship
between tsunami height and probability of exceedance) and present some examples for Japan for the purpose of quantitative
assessments of tsunami risk for important coastal facilities. A hazard curve is obtained by integration over the aleatory
uncertainties, and numerous hazard curves are obtained for different branches of logic-tree representing epistemic uncertainty.
A PTHA consists of a tsunami source model and coastal tsunami height estimation. We developed the logic-tree models for local
tsunami sources around Japan and for distant tsunami sources along the South American subduction zones. Logic-trees were made
for tsunami source zones, size and frequency of tsunamigenic earthquakes, fault models, and standard error of estimated tsunami
heights. Numerical simulation rather than empirical relation was used for estimating the median tsunami heights. Weights of
discrete branches that represent alternative hypotheses and interpretations were determined by the questionnaire survey for
tsunami and earthquake experts, whereas those representing the error of estimated value were determined on the basis of historical
data. Examples of tsunami hazard curves were illustrated for the coastal sites, and uncertainty in the tsunami hazard was
displayed by 5-, 16-, 50-, 84- and 95-percentile and mean hazard curves. 相似文献
7.
Multiple segmented rating curves have been proposed to better capture the variability of the physical and hydraulic characteristics of river–floodplain systems. We evaluate the accuracy of one- and two-segmented rating curves by exploiting a large and unique database of direct measurements of stage and discharge data in more than 200 Swedish catchments. Such a comparison is made by explicitly accounting for the potential impact of measurement uncertainty. This study shows that two-segmented rating curves did not fit the data significantly better, nor did they generate fewer errors than one-segmented rating curves. Two-segmented rating curves were found to be slightly beneficial for low flow when there were strong indications of segmentation, but predicted the rating relationship worse in cases of weak indication of segmentation. Other factors were found to have a larger impact on rating curve errors, such as the uncertainty of the discharge measurements and the type of regression method. 相似文献
8.
Francisco José da Silva Dias Luiz Drude Lacerda Rozane Valente Marins Francisco Carlos Fernandes de Paula 《水文研究》2011,25(14):2188-2201
This work quantifies, using ADP and rating curve techniques, the instantaneous outflows at estuarine interfaces: higher to middle estuary and middle to lower estuary, in two medium‐sized watersheds (72 000 and 66 000 km2 of area, respectively), the Jaguaribe and Contas Rivers located in the northeastern (semi‐arid) and eastern (tropical humid) Brazilian coasts, respectively. Results from ADP showed that the net water balances show the Contas River as a net water exporter, whereas the Jaguaribe River Estuary is a net water importer. At the Jaguaribe Estuary, water retention during flood tide contributes to 58% of the total volume transferred during the ebb tide from the middle to lower estuary. However, 42% of the total water volume (452 m3 s?1) that entered during flood tide is retained in the middle estuary. In the Contas River, 90% of the total water is retained during the flood tide contributing to the volume transported in the ebb tide from the middle to the lower estuary. Outflows obtained with the rating curve method for the Contas and Jaguaribe Rivers were uniform through time due to river flow normalization by dams in both basins. Estimated outflows with this method are about 65% (Contas) and 95% (Jaguaribe) lower compared to outflows obtained with ADP. This suggests that the outflows obtained with the rating curve method underestimate the net water balance in both systems, particularly in the Jaguaribe River under a semi‐arid climate. This underestimation is somewhat decreased due to wetter conditions in the Contas River basin. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
9.
The instantaneous salt dilution method for water discharge measurements in open channels has been improved by the development of a new instrument measuring conductivity. The salt method consists of two parts: the calibration and the actual measurement in the stream. The calibration aims to calculate the linear relationship between electrical conductivity and salt concentration at various degrees of dilution in a salt solution. The original undiluted solution is injected into the water of a stream and the conductivity is measured downstream from the injection site. When measuring, the new instrument integrates the conductivity over time. From the value obtained on the instrument's display, the water discharge can easily be calculated on a hand-PC in the field. The instrument has eliminated the subsequent calculation work formerly necessary. It has increased the accuracy of the method and also reduced the need for field personnel during measurements. 相似文献
10.
Haykel Sellami Isabelle La Jeunesse Sihem Benabdallah Marnik Vanclooster 《水文科学杂志》2013,58(8):1635-1657
AbstractThe SWAT model was tested to simulate the streamflow of two small Mediterranean catchments (the Vène and the Pallas) in southern France. Model calibration and prediction uncertainty were assessed simultaneously by using three different techniques (SUFI-2, GLUE and ParaSol). Initially, a sensitivity analysis was conducted using the LH-OAT method. Subsequent sensitive parameter calibration and SWAT prediction uncertainty were analysed by considering, firstly, deterministic discharge data (assuming no uncertainty in discharge data) and secondly, uncertainty in discharge data through the development of a methodology that accounts explicitly for error in the rating curve (the stage?discharge relationship). To efficiently compare the different uncertainty methods and the effect of the uncertainty of the rating curve on model prediction uncertainty, common criteria were set for the likelihood function, the threshold value and the number of simulations. The results show that model prediction uncertainty is not only case-study specific, but also depends on the selected uncertainty analysis technique. It was also found that the 95% model prediction uncertainty interval is wider and more successful at encompassing the observations when uncertainty in the discharge data is considered explicitly. The latter source of uncertainty adds additional uncertainty to the total model prediction uncertainty.
Editor D. Koutsoyiannis; Associate editor D. GertenCitation Sellami, H., La Jeunesse, I., Benabdallah, S., and Vanclooster, M., 2013. Parameter and rating curve uncertainty propagation analysis of the SWAT model for two small Mediterranean watersheds. Hydrological Sciences Journal, 58 (8), 1635?1657. 相似文献
11.
This paper presents an analytical method for establishing a stage–fall–discharge rating using hydraulic performance graphs (HPG). The rating curves derived from the HPG are used as the basis to establish the functional relation of stage, fall and discharge through regression analysis following the USGS procedure. In doing so, the conventional trial‐and‐error process can be avoided and the associated uncertainties involved may be reduced. For illustration, the proposed analytical method is applied to establish stage–fall–discharge relations for the Keelung River in northern Taiwan to examine its accuracy and applicability in an actual river. Based on the data extracted from the HPG for the Keelung River, one can establish a stage–fall–discharge relation that is more accurate than the one obtained by the conventionally used relation. Furthermore, the discharges obtained from the proposed rating method are verified through backwater analysis for measured high water level events. The results indicate that the analytical stage–fall–discharge rating method is capable of circumventing the shortcomings of those based on single‐station data and, consequently, enhancing the reliability of flood estimation and forecasting. Copyright © 2008 John Wiley & Sons, Ltd. 相似文献
12.
Trond Reitan Asgeir Petersen-Øverleir 《Stochastic Environmental Research and Risk Assessment (SERRA)》2009,23(5):627-642
This study explores Bayesian methods for handling compound stage–discharge relationships, a problem which arises in many natural
rivers. It is assumed: (1) the stage–discharge relationship in each rating curve segment is a power-law with a location parameter,
or zero-plane displacement; (2) the segment transitions are abrupt and continuous; and (3) multiplicative measurement errors
are of equal variance. The rating curve fitting procedure is then formulated as a piecewise regression problem where the number
of segments and the associated changepoints are assumed unknown. Procedures are developed for describing both global and site-specific
prior distributions for all rating curve parameters, including the changepoints. Estimation and uncertainty analysis is evaluated
using Markov chain Monte Carlo simulation (MCMC) techniques. The first model explored accounts for parameter and model uncertainties
in the interpolated area, i.e. within the range of available stage–discharge measurements. A second model is constructed in
an attempt to include the uncertainty in extrapolation, which is necessary when the rating curve is used to estimate discharges
beyond the highest or lowest measurement. This is done by assuming that the rate of changepoints both inside and outside the
measured area follows a Poisson process. The theory is applied to actual data from Norwegian gauging stations. The MCMC solutions
give results that appear sensible and useful for inferential purposes, though the latter model needs further efforts in order
to obtain a more efficient simulation scheme. 相似文献
13.
Hilary McMillan Jim Freer Florian Pappenberger Tobias Krueger Martyn Clark 《水文研究》2010,24(10):1270-1284
In order to quantify total error affecting hydrological models and predictions, we must explicitly recognize errors in input data, model structure, model parameters and validation data. This paper tackles the last of these: errors in discharge measurements used to calibrate a rainfall‐runoff model, caused by stage–discharge rating‐curve uncertainty. This uncertainty may be due to several combined sources, including errors in stage and velocity measurements during individual gaugings, assumptions regarding a particular form of stage–discharge relationship, extrapolation of the stage–discharge relationship beyond the maximum gauging, and cross‐section change due to vegetation growth and/or bed movement. A methodology is presented to systematically assess and quantify the uncertainty in discharge measurements due to all of these sources. For a given stage measurement, a complete PDF of true discharge is estimated. Consequently, new model calibration techniques can be introduced to explicitly account for the discharge error distribution. The method is demonstrated for a gravel‐bed river in New Zealand, where all the above uncertainty sources can be identified, including significant uncertainty in cross‐section form due to scour and re‐deposition of sediment. Results show that rigorous consideration of uncertainty in flow data results in significant improvement of the model's ability to predict the observed flow. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
14.
Bayesian analysis of stage–fall–discharge models for gauging stations affected by variable backwater
Parsimonious stage–fall–discharge rating curve models for gauging stations subject to backwater complications are developed from simple hydraulic theory. The rating curve models are compounded in order to allow for possible shifts in the hydraulics when variable backwater becomes effective. The models provide a prior scientific understanding through the relationship between the rating curve parameters and the hydraulic properties of the channel section under study. This characteristic enables prior distributions for the rating curve parameters to be easily elicited according to site‐specific information and the magnitude of well‐known hydraulic quantities. Posterior results from three Norwegian and one American twin‐gauge stations affected by variable backwater are obtained using Markov chain Monte Carlo simulation techniques. The case studies demonstrate that the proposed Bayesian rating curve assessment is appropriate for developing rating procedures for gauging stations that are subject to variable backwater. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
15.
Brian S. Caruso 《水文研究》1999,13(2):169-190
This study evaluated the attributes and uncertainty of non‐point source pollution data derived from synoptic surveys in a catchment affected by inactive metal mines in order to help to identify and select appropriate methods for data analysis/reporting and information use. Dissolved zinc data from the Upper Animas River Basin, Colorado, USA, were the focus of the study. Zinc was evaluated because concentrations were highest relative to national water quality criteria for brown trout, and zinc had the greatest frequency of criteria exceedances compared with other metals. Data attributes evaluated included measurement and model error, sample size, non‐normality, seasonality and uncertainty. The average measurement errors for discharges, concentrations and loadings were 0·15, 0·1 and 0·18, respectively. The 90 and 95% coefficients of confidence intervals for mean concentrations based on a sample size of four were 0·48 and 0·65, respectively, and ranged between 0·15 and 0·23 for sample sizes greater than 40. Aggregation of data from multiple stations decreased the confidence intervals significantly, but additional aggregation of all data increased them as a result of increasing spatial variability. Unit area loading data were approximately log‐normal. Concentration data were right‐skewed but not log‐normal. Differences in median concentrations were appreciable between snowmelt and both storm flow and baseflow, but not between storm flow and baseflow. Differences in unit area loadings between all flow events were large. It was determined that the average concentration and unit area loading values should be estimated for each flow event because of significant seasonality. Time weighted values generally should be computed if annual information is required. The confidence in average concentrations and unit area loadings is dependent on the computation method used. Both concentrations and loadings can be significantly underestimated on an annual basis when using data from synoptic surveys if the first flush of contaminants during the initial snowmelt runoff period is not sampled. The ambient standard for dissolved zinc for all events was estimated as 1600 μg l−1 using the 85th percentile of observed concentration data, with a 90% confidence interval width of 200 μg l−1. Copyright © 1999 John Wiley & Sons, Ltd. 相似文献
16.
ABSTRACT Ensemble machine learning models have been widely used in hydro-systems modeling as robust prediction tools that combine multiple decision trees. In this study, three newly developed ensemble machine learning models, namely gradient boost regression (GBR), AdaBoost regression (ABR) and random forest regression (RFR) are proposed for prediction of suspended sediment load (SSL), and their prediction performance and related uncertainty are assessed. The SSL of the Mississippi River, which is one of the major world rivers and is significantly affected by sedimentation, is predicted based on daily values of river discharge (Q) and suspended sediment concentration (SSC). Based on performance metrics and visualization, the RFR model shows a slight lead in prediction performance. The uncertainty analysis also indicates that the input variable combination has more impact on the obtained predictions than the model structure selection. 相似文献
17.
Sensitivity and uncertainty analysis of mesoscale model downscaled hydro‐meteorological variables for discharge prediction 下载免费PDF全文
下载免费PDF全文 Precipitation and Reference Evapotranspiration (ETo) are the most important variables for rainfall–runoff modelling. However, it is not always possible to get access to them from ground‐based measurements, particularly in ungauged catchments. This study explores the performance of rainfall and ETo data from the global European Centre for Medium Range Weather Forecasts (ECMWF) ERA interim reanalysis data for the discharge prediction. The Weather Research and Forecasting (WRF) mesoscale model coupled with the NOAH Land Surface Model is used for the retrieval of hydro‐meteorological variables by downscaling ECMWF datasets. The conceptual Probability Distribution Model (PDM) is chosen for this study for the discharge prediction. The input data and model parameter sensitivity analysis and uncertainty estimations are taken into account for the PDM calibration and prediction in the case study catchment in England following the Generalized Likelihood Uncertainty Estimation approach. The goodness of calibration and prediction uncertainty is judged on the basis of the p‐factor (observations bracketed by the prediction uncertainty) and the r‐factor (achievement of small uncertainty band). The overall analysis suggests that the uncertainty estimates using WRF downscaled ETo have slightly smaller p and r values (p= 0.65; r= 0.58) as compared to ground‐based observation datasets (p= 0.71; r= 0.65) during the validation and hence promising for discharge prediction. On the contrary, WRF precipitation has the worst performance, and further research is needed for its improvement (p= 0.04; r= 0.10). Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
18.
The measurement of discharge is fundamental in nutrient load estimation. Because of our ability to monitor discharge routinely, it is generally assumed that the associated uncertainty is low. This paper challenges this preconception, arguing that discharge uncertainty should be explicitly taken into account to produce robust statistical analyses. In many studies, paired discharge and chemical datasets are used to calculate ‘true’ loads and used as the benchmark to compare with other load estimates. This paper uses two years of high frequency (daily and sub‐hourly) discharge and nutrient concentration data (nitrate‐N and total phosphorus (TP)) collected at four field sites as part of the Hampshire Avon Demonstration Test Catchment (DTC) programme. A framework for estimating observational nutrient load uncertainty was used which combined a flexible non‐parametric approach to characterising discharge uncertainty, with error modelling that allowed the incorporation of errors which were heteroscedastic and temporally correlated. The results showed that the stage–discharge relationships were non‐stationary, and observational uncertainties from ±2 to 25% were recorded when the velocity–area method was used. The variability in nutrient load estimates ranged from 1.1 to 9.9% for nitrate‐N and from 3.3 to 10% for TP when daily laboratory data were used, rising to a maximum of 9% for nitrate‐N and 83% for TP when the sensor data were used. However, the sensor data provided a better representation of the ‘true’ load as storm events are better represented temporally, posing the question: is it more beneficial to have high frequency, lower precision data or lower frequency but higher precision data streams to estimate nutrient flux responses in headwater catchments? Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
19.
Trond Reitan Asgeir Petersen-Øverleir 《Stochastic Environmental Research and Risk Assessment (SERRA)》2006,20(6):445-453
Practical application of the power-law regression model with an unknown location parameter can be plagued by non-finite least squares parameter estimates. This presents a serious problem in hydrology, since stream flow data is mainly obtained using an estimated stage–discharge power-law rating curve. This study provides a set of sufficient requirements for the data to ensure the existence of finite least squares parameter estimates for a power-law regression with an unknown location parameter. It is shown that in practice, these requirements act as necessary for having a finite least squares solution, in most cases. Furthermore, it is proved that there is a finite probability for the model to produce data having non-finite least squares parameter estimates. The implications of this result are discussed in the context of asymptotic predictions, inference and experimental design. A Bayesian approach to the actual regression problem is recommended. 相似文献
