scholarly journals Incorporating experimentally derived streamflow contributions into model parameterization to improve discharge prediction

2021 ◽  
Author(s):  
Andreas Hartmann ◽  
Jean-Lionel Payeur-Poirier ◽  
Luisa Hopp
Keyword(s):  
Parameter Estimation ◽  
Riparian Zone ◽  
Monsoon Season ◽  
Experimental Information ◽  
Model Parameters ◽  
Environmental Tracers ◽  
Hydrograph Separation ◽  
Flow Conditions ◽  
Catchment Scale ◽  
Additional Information

Abstract. Environmental tracers have been used to separate streamflow components for many years. They allow to quantify the contribution of water originating from different sources such as direct runoff from precipitation, subsurface stormflow or groundwater to total streamflow at variable flow conditions. Although previous studies have explored the value of incorporating experimentally derived fractions of event and pre-event water into hydrological models, a thorough analysis of the value of incorporating hydrograph separation derived information on multiple streamflow components at varying flow conditions into model parameter estimation has not yet been performed. This study explores the value of such information to achieve more realistic simulations of catchment discharge. We use a modified version of the process-oriented HBV model that simulates catchment discharge through the interplay of hillslope, riparian zone discharge and groundwater discharge at a small forested catchment which is located in the mountainous north of South Korea subject to a monsoon season between June and August. Applying a Monte Carlo based parameter estimation scheme and the Kling Gupta efficiency (KGE) to compare discharge observations and simulations across two seasons (2013 & 2014), we show that the model is able to provide accurate simulations of catchment discharge (KGE ≥ 0.8) but fails to provide robust predictions and realistic estimates of the contribution of the different streamflow components. Using a simple framework to incorporate experimental information on the contributions of hillslope, riparian zone and groundwater to total discharge during four sub-periods, we show that the precision of simulated streamflow components can be increased while remaining with accurate discharge simulations. We further show that the additional information increases the identifiability of all model parameters and results in more robust predictions. Our study shows how tracer derived information on streamflow contributions can be used to improve the simulation and predictions of streamflow at the catchment scale without adding additional complexity to the model. The complementary use of temporally resolved observations of streamflow components and modelling provides a promising direction to improve discharge prediction by representing model internal dynamics more realistically.

scholarly journals Assessment of surface water resources availability using catchment modelling and the results of tracer studies in the mesoscale Migina Catchment, Rwanda

2014 ◽  
Vol 18 (12) ◽  
pp. 5289-5301 ◽  
Author(s):  
O. Munyaneza ◽  
A. Mukubwa ◽  
S. Maskey ◽  
S. Uhlenbrook ◽  
J. Wenninger
Keyword(s):  
Decision Making ◽  
Water Resources ◽  
Hydrological Model ◽  
Model Parameters ◽  
Water Resources Planning ◽  
Distributed Hydrological Model ◽  
Hydrograph Separation ◽  
Catchment Scale ◽  
Streamflow Data ◽  
Resources Planning

Abstract. In the present study, we developed a catchment hydrological model which can be used to inform water resources planning and decision making for better management of the Migina Catchment (257.4 km2). The semi-distributed hydrological model HEC-HMS (Hydrologic Engineering Center – the Hydrologic Modelling System) (version 3.5) was used with its soil moisture accounting, unit hydrograph, liner reservoir (for baseflow) and Muskingum–Cunge (river routing) methods. We used rainfall data from 12 stations and streamflow data from 5 stations, which were collected as part of this study over a period of 2 years (May 2009 and June 2011). The catchment was divided into five sub-catchments. The model parameters were calibrated separately for each sub-catchment using the observed streamflow data. Calibration results obtained were found acceptable at four stations with a Nash–Sutcliffe model efficiency index (NS) of 0.65 on daily runoff at the catchment outlet. Due to the lack of sufficient and reliable data for longer periods, a model validation was not undertaken. However, we used results from tracer-based hydrograph separation from a previous study to compare our model results in terms of the runoff components. The model performed reasonably well in simulating the total flow volume, peak flow and timing as well as the portion of direct runoff and baseflow. We observed considerable disparities in the parameters (e.g. groundwater storage) and runoff components across the five sub-catchments, which provided insights into the different hydrological processes on a sub-catchment scale. We conclude that such disparities justify the need to consider catchment subdivisions if such parameters and components of the water cycle are to form the base for decision making in water resources planning in the catchment.

scholarly journals Data assimilation in integrated hydrological modelling in the presence of observation bias

2016 ◽  
Vol 20 (5) ◽  
pp. 2103-2118 ◽  
Author(s):  
Jørn Rasmussen ◽  
Henrik Madsen ◽  
Karsten Høgh Jensen ◽  
Jens Christian Refsgaard
Keyword(s):  
Parameter Estimation ◽  
Kalman Filter ◽  
Optimal Parameter ◽  
Estimation Methods ◽  
Model Parameters ◽  
Bias Estimation ◽  
Catchment Scale ◽  
Stream Discharge ◽  
Groundwater Head ◽  
Observation Bias

Abstract. The use of bias-aware Kalman filters for estimating and correcting observation bias in groundwater head observations is evaluated using both synthetic and real observations. In the synthetic test, groundwater head observations with a constant bias and unbiased stream discharge observations are assimilated in a catchment-scale integrated hydrological model with the aim of updating stream discharge and groundwater head, as well as several model parameters relating to both streamflow and groundwater modelling. The coloured noise Kalman filter (ColKF) and the separate-bias Kalman filter (SepKF) are tested and evaluated for correcting the observation biases. The study found that both methods were able to estimate most of the biases and that using any of the two bias estimation methods resulted in significant improvements over using a bias-unaware Kalman filter. While the convergence of the ColKF was significantly faster than the convergence of the SepKF, a much larger ensemble size was required as the estimation of biases would otherwise fail. Real observations of groundwater head and stream discharge were also assimilated, resulting in improved streamflow modelling in terms of an increased Nash–Sutcliffe coefficient while no clear improvement in groundwater head modelling was observed. Both the ColKF and the SepKF tended to underestimate the biases, which resulted in drifting model behaviour and sub-optimal parameter estimation, but both methods provided better state updating and parameter estimation than using a bias-unaware filter.

scholarly journals Constrained Parameter Estimation for a Mechanistic Kinetic Model of Cobalt–Hydrogen Electrochemical Competition during a Cobalt Removal Process

Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 387
Author(s):  
Yiting Liang ◽  
Yuanhua Zhang ◽  
Yonggang Li
Keyword(s):  
Parameter Estimation ◽  
Kinetic Model ◽  
Model Parameters ◽  
Hydrogen Ions ◽  
Removal Process ◽  
Cobalt Removal ◽  
Estimation Scheme ◽  
Zinc Hydrometallurgy ◽  
The Impact ◽  
Parameter Estimation Scheme

A mechanistic kinetic model of cobalt–hydrogen electrochemical competition for the cobalt removal process in zinc hydrometallurgical was proposed. In addition, to overcome the parameter estimation difficulties arising from the model nonlinearities and the lack of information on the possible value ranges of parameters to be estimated, a constrained guided parameter estimation scheme was derived based on model equations and experimental data. The proposed model and the parameter estimation scheme have two advantages: (i) The model reflected for the first time the mechanism of the electrochemical competition between cobalt and hydrogen ions in the process of cobalt removal in zinc hydrometallurgy; (ii) The proposed constrained parameter estimation scheme did not depend on the information of the possible value ranges of parameters to be estimated; (iii) the constraint conditions provided in that scheme directly linked the experimental phenomenon metrics to the model parameters thereby providing deeper insights into the model parameters for model users. Numerical experiments showed that the proposed constrained parameter estimation algorithm significantly improved the estimation efficiency. Meanwhile, the proposed cobalt–hydrogen electrochemical competition model allowed for accurate simulation of the impact of hydrogen ions on cobalt removal rate as well as simulation of the trend of hydrogen ion concentration, which would be helpful for the actual cobalt removal process in zinc hydrometallurgy.

scholarly journals Determination of synchronous generator nonlinear model parameters based on power rejection tests using a gradient optimization algorithm

2017 ◽  
Vol 65 (4) ◽  
pp. 479-488 ◽  
Author(s):  
A. Boboń ◽  
A. Nocoń ◽  
S. Paszek ◽  
P. Pruski
Keyword(s):  
Parameter Estimation ◽  
Objective Function ◽  
Optimization Algorithm ◽  
Least Squares Method ◽  
Synchronous Generator ◽  
Operating Conditions ◽  
Model Parameters ◽  
State Variables ◽  
Starting Point ◽  
Gradient Optimization

AbstractThe paper presents a method for determining electromagnetic parameters of different synchronous generator models based on dynamic waveforms measured at power rejection. Such a test can be performed safely under normal operating conditions of a generator working in a power plant. A generator model was investigated, expressed by reactances and time constants of steady, transient, and subtransient state in the d and q axes, as well as the circuit models (type (3,3) and (2,2)) expressed by resistances and inductances of stator, excitation, and equivalent rotor damping circuits windings. All these models approximately take into account the influence of magnetic core saturation. The least squares method was used for parameter estimation. There was minimized the objective function defined as the mean square error between the measured waveforms and the waveforms calculated based on the mathematical models. A method of determining the initial values of those state variables which also depend on the searched parameters is presented. To minimize the objective function, a gradient optimization algorithm finding local minima for a selected starting point was used. To get closer to the global minimum, calculations were repeated many times, taking into account the inequality constraints for the searched parameters. The paper presents the parameter estimation results and a comparison of the waveforms measured and calculated based on the final parameters for 200 MW and 50 MW turbogenerators.

Developing a Linearization Method to Determine Optimum Blending for Surimi with Varied Moisture Contents Using Linear Programming

2019 ◽  
Vol 0 (0) ◽  
Author(s):  
Hyeon W. Park ◽  
Jae W. Park ◽  
Won B. Yoon
Keyword(s):  
Linear Programming ◽  
Moisture Content ◽  
Standard Procedure ◽  
Unit Cost ◽  
Linearization Method ◽  
Model Parameters ◽  
Additional Information ◽  
Moisture Contents ◽  
Design Variables ◽  
Critical Moisture

AbstractNovel algorithm to determine the least cost formulation of a surimi blend was developed using linear programming (LP). Texture properties and the unit cost of surimi blend at the target moisture content were used as constraint functions and the objective function, respectively. The mathematical models to describe the moisture content dependence of the ring tensile properties were developed using critical moisture content, and the model parameters were used for the least cost LP (LCLP) model. The LCLP model successfully predicted the quality of surimi blend. Sensitivity analysis was used to obtain an additional information when the perturbations of design variables are provided. A standard procedure to determine the least cost formulation for blending surimi with varied moisture contents was systematically developed.

scholarly journals Are streamflow recession characteristics really characteristic?

2013 ◽  
Vol 17 (2) ◽  
pp. 817-828 ◽  
Author(s):  
M. Stoelzle ◽  
K. Stahl ◽  
M. Weiler
Keyword(s):  
Extraction Method ◽  
Storage Capacity ◽  
Extraction Methods ◽  
Model Parameters ◽  
Catchment Scale ◽  
Model Parameterization ◽  
Recession Curves ◽  
Recession Analysis ◽  
Meso Scale

Abstract. Streamflow recession has been investigated by a variety of methods, often involving the fit of a model to empirical recession plots to parameterize a non-linear storage–outflow relationship based on the dQ/dt−Q method. Such recession analysis methods (RAMs) are used to estimate hydraulic conductivity, storage capacity, or aquifer thickness and to model streamflow recession curves for regionalization and prediction at the catchment scale. Numerous RAMs have been published, but little is known about how comparably the resulting recession models distinguish characteristic catchment behavior. In this study we combined three established recession extraction methods with three different parameter-fitting methods to the power-law storage–outflow model to compare the range of recession characteristics that result from the application of these different RAMs. Resulting recession characteristics including recession time and corresponding storage depletion were evaluated for 20 meso-scale catchments in Germany. We found plausible ranges for model parameterization; however, calculated recession characteristics varied over two orders of magnitude. While recession characteristics of the 20 catchments derived with the different methods correlate strongly, particularly for the RAMs that use the same extraction method, not all rank the catchments consistently, and the differences among some of the methods are larger than among the catchments. To elucidate this variability we discuss the ambiguous roles of recession extraction procedures and the parameterization of the storage–outflow model and the limitations of the presented recession plots. The results suggest strong limitations to the comparability of recession characteristics derived with different methods, not only in the model parameters but also in the relative characterization of different catchments. A multiple-methods approach to investigating streamflow recession characteristics should be considered for applications whenever possible.

Stacking-velocity tomography for tilted orthorhombic media

Geophysics ◽  
2019 ◽  
Vol 84 (3) ◽  
pp. C171-C180 ◽  
Author(s):  
Qifan Liu ◽  
Ilya Tsvankin
Keyword(s):  
Parameter Estimation ◽  
Subsurface Layer ◽  
Synthetic Data ◽  
Transversely Isotropic ◽  
P Waves ◽  
Additional Information ◽  
Reflection Data ◽  
Anisotropic Layers ◽  
Zero Offset ◽  
Velocity Tomography

Tilted orthorhombic (TOR) models are typical for dipping anisotropic layers, such as fractured shales, and can also be due to nonhydrostatic stress fields. Velocity analysis for TOR media, however, is complicated by the large number of independent parameters. Using multicomponent wide-azimuth reflection data, we develop stacking-velocity tomography to estimate the interval parameters of TOR media composed of homogeneous layers separated by plane dipping interfaces. The normal-moveout (NMO) ellipses, zero-offset traveltimes, and reflection time slopes of P-waves and split S-waves ([Formula: see text] and [Formula: see text]) are used to invert for the interval TOR parameters including the orientation of the symmetry planes. We show that the inversion can be facilitated by assuming that the reflector coincides with one of the symmetry planes, which is a common geologic constraint often employed for tilted transversely isotropic media. This constraint makes the inversion for a single TOR layer feasible even when the initial model is purely isotropic. If the dip plane is also aligned with one of the symmetry planes, we show that the inverse problem for [Formula: see text]-, [Formula: see text]-, and [Formula: see text]-waves can be solved analytically. When only [Formula: see text]-wave data are available, parameter estimation requires combining NMO ellipses from a horizontal and dipping interface. Because of the increase in the number of independent measurements for layered TOR media, constraining the reflector orientation is required only for the subsurface layer. However, the inversion results generally deteriorate with depth because of error accumulation. Using tests on synthetic data, we demonstrate that additional information such as knowledge of the vertical velocities (which may be available from check shots or well logs) and the constraint on the reflector orientation can significantly improve the accuracy and stability of interval parameter estimation.

scholarly journals An Optimized Snowmelt Lysimeter System for Monitoring Melt Rates and Collecting Samples for Stable Water Isotope Analysis

2019 ◽  
Vol 67 (1) ◽  
pp. 20-31 ◽  
Author(s):  
Andrea Rücker ◽  
Massimiliano Zappa ◽  
Stefan Boss ◽  
Jana von Freyberg
Keyword(s):  
Isotopic Composition ◽  
Isotope Analysis ◽  
Ground Level ◽  
Isotopic Signature ◽  
Small Scale ◽  
Spatial And Temporal Variability ◽  
Environmental Tracers ◽  
Hydrograph Separation ◽  
Stable Water Isotopes ◽  
Restricted Volume

Abstract The contribution of snow meltwater to catchment streamflow can be quantified through hydrograph separation analyses for which stable water isotopes (18O, 2H) are used as environmental tracers. For this, the spatial and temporal variability of the isotopic composition of meltwater needs to be captured by the sampling method. This study compares an optimized snowmelt lysimeter system and an unheated precipitation collector with focus on their ability to capture snowmelt rates and the isotopic composition of snowmelt. The snowmelt lysimeter system consists of three individual unenclosed lysimeters at ground level with a surface of 0.14 m2 each. The unheated precipitation collector consists of a 30 cm-long, extended funnel with its orifice at 2.3 m above ground. Daily snowmelt samples were collected with both systems during two snowfall-snowmelt periods in 2016. The snowmelt lysimeter system provided more accurate measurements of natural melt rates and allowed for capturing the small-scale variability of snowmelt process at the plot scale, such as lateral meltwater flow from the surrounding snowpack. Because of the restricted volume of the extended funnel, daily melt rates from the unheated precipitation collector were up to 43% smaller compared to the snowmelt lysimeter system. Overall, both snowmelt collection methods captured the general temporal evolution of the isotopic signature in snowmelt.

scholarly journals Deep search for hydrogen peroxide toward pre- and protostellar objects

2020 ◽  
Vol 636 ◽  
pp. A114
Author(s):  
G. W. Fuchs ◽  
D. Witsch ◽  
D. Herberth ◽  
M. Kempkes ◽  
B. Stanclik ◽  
...  
Keyword(s):  
Hydrogen Peroxide ◽  
Solid State ◽  
Water Reservoir ◽  
Reaction Network ◽  
Reaction Scheme ◽  
Young Stellar Objects ◽  
Model Parameters ◽  
Stellar Objects ◽  
Additional Information ◽  
Water Formation

Context. In the laboratory, hydrogen peroxide (HOOH) was proven to be an intermediate product in the solid-state reaction scheme that leads to the formation of water on icy dust grains. When HOOH desorbs from the icy grains, it can be detected in the gas phase. In combination with water detections, it may provide additional information on the water reaction network. Hydrogen peroxide has previously been found toward ρ Oph A. However, further searches for this molecule in other sources failed. Hydrogen peroxide plays a fundamental role in the understanding of solid-state water formation and the overall water reservoir in young stellar objects (YSOs). Without further HOOH detections, it is difficult to assess and develop suitable chemical models that properly take into account the formation of water on icy surfaces. Aims. The objective of this work is to identify HOOH in YSOs and thereby constrain the grain surface water formation hypothesis. Methods. Using an astrochemical model based on previous work in combination with a physical model of YSOs, the sources R CrA-IRS 5A, NGC C1333-IRAS 2A, L1551-IRS 5, and L1544 were identified as suitable candidates for an HOOH detection. Long integration times on the APEX 12 m and IRAM 30 m telescopes were applied to search for HOOH signatures in these sources. Results. None of the four sources under investigation showed convincing spectral signatures of HOOH. The upper limit for HOOH abundance based on the noise level at the frequency positions of this molecule for the source R CrA-IRS 5A was close to the predicted value. For NGC 1333-IRAS 2A, L1544, and L1551-IRS 5, the model overestimated the hydrogen peroxide abundances. Conclusions. HOOH remains an elusive molecule. With only one secure cosmic HOOH source detected so far, namely ρ Oph A, the chemical model parameters for this molecule cannot be sufficiently well determined or confirmed in existing models. Possible reasons for the nondetections of HOOH are discussed.

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