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Model Calibration (model + calibration)
Selected AbstractsUse of Observations below Detection Limit for Model CalibrationGROUND WATER, Issue 2 2009Michael LeFrancois Censored (nondetect) values occur when chemical concentrations in water samples are near or below the level that can be measured by an analysis method. It is common to either delete or substitute values for nondetect observations for use in model calibration, but this practice can bias the estimated parameter values and the model predictions. A more realistic representation of the system is obtained from the calibration if we include such observations in a manner reflecting that we know only the value is below the detection limit. Consequently, we propose use of the censored-residual approach to including nondetect values as observations for calibration. In this approach, residuals are calculated as the detection limit minus the simulated value when the simulated value exceeds the detection limit, and the residual is assigned a value of zero when the simulated value is below the detection limit. The new censored-residual approach is particularly advantageous when calibrating transport models to low concentration data. [source] The Value of Subsidence Data in Ground Water Model CalibrationGROUND WATER, Issue 4 2008Tingting Yan The accurate estimation of aquifer parameters such as transmissivity and specific storage is often an important objective during a ground water modeling investigation or aquifer resource evaluation. Parameter estimation is often accomplished with changes in hydraulic head data as the key and most abundant type of observation. The availability and accessibility of global positioning system and interferometric synthetic aperture radar data in heavily pumped alluvial basins can provide important subsidence observations that can greatly aid parameter estimation. The aim of this investigation is to evaluate the value of spatial and temporal subsidence data for automatically estimating parameters with and without observation error using UCODE-2005 and MODFLOW-2000. A synthetic conceptual model (24 separate cases) containing seven transmissivity zones and three zones each for elastic and inelastic skeletal specific storage was used to simulate subsidence and drawdown in an aquifer with variably thick interbeds with delayed drainage. Five pumping wells of variable rates were used to stress the system for up to 15 years. Calibration results indicate that (1) the inverse of the square of the observation values is a reasonable way to weight the observations, (2) spatially abundant subsidence data typically produce superior parameter estimates under constant pumping even with observation error, (3) only a small number of subsidence observations are required to achieve accurate parameter estimates, and (4) for seasonal pumping, accurate parameter estimates for elastic skeletal specific storage values are largely dependent on the quantity of temporal observational data and less on the quantity of available spatial data. [source] Hydrologic comparison between a forested and a wetland/lake dominated watershed using SWATHYDROLOGICAL PROCESSES, Issue 10 2008Kangsheng Wu Abstract The Soil and Water Assessment Tool (SWAT) is a physically-based hydrologic model developed for agricultural watersheds, which has been infrequently validated for forested watersheds, particularly those with deep overwinter snow accumulation and abundant lakes and wetlands. The goal of this study was to determine the applicability of SWAT for modelling streamflow in two watersheds of the Ontonagon River basin of northern Michigan which differ in proportion of wetland and lake area. The forest-dominated East Branch watershed contains 17% wetland and lake area, whereas the wetland/lake-dominated Middle Branch watershed contains 26% wetland and lake area. The specific objectives were to: (1) calibrate and validate SWAT models for the East Branch and Middle Branch watersheds to simulate monthly stream flow, and (2) compare the effects of wetland and lake abundance on the magnitude and timing of streamflow. Model calibration and validation was satisfactory, as determined by deviation of discharge D and Nash and Sutcliffe coefficient values E that compared simulated monthly mean discharge versus measured monthly mean discharge. Streamflow simulation discrepancies occurred during summer and fall months and dry years. Several snow melting parameters were found to be critical for the SWAT simulation: TIMP (snow temperature lag factor) and SMFMX and SMFMN (melting factors). Snow melting parameters were not transferable between adjacent watersheds. Differences in seasonal pattern of long-term monthly streamflow were found, with the forest-dominated watershed having a higher peak flow during April but a lower flow during the remainder of the year in comparison to the wetland and lake-dominated watershed. The results suggested that a greater proportion of wetland and lake area increases the capacity of a watershed to impound surface runoff and to delay storm and snow melting events. Representation of wetlands and lakes in a watershed model is required to simulate monthly stream flow in a wetland/lake-dominated watershed. Copyright © 2007 John Wiley & Sons, Ltd. [source] On the Segregation of Genetically Modified, Conventional and Organic Products in European Agriculture: A Multi-market Equilibrium AnalysisJOURNAL OF AGRICULTURAL ECONOMICS, Issue 3 2005GianCarlo Moschini Q1; O3 Abstract Evaluating the possible benefits of the introduction of genetically modified (GM) crops must address the issue of consumer resistance as well as the complex regulation that has ensued. In the European Union (EU), this regulation envisions the co-existence of GM food with conventional and quality-enhanced products, mandates the labelling and traceability of GM products and allows only a stringent adventitious presence of GM content in other products. All these elements are brought together within a partial equilibrium model of the EU agricultural food sector. The model comprises conventional, GM and organic food. Demand is modelled in a novel fashion, whereby organic and conventional products are treated as horizontally differentiated but GM products are vertically differentiated (weakly inferior) relative to conventional ones. Supply accounts explicitly for the land constraint at the sector level and for the need for additional resources to produce organic food. Model calibration and simulation allow insights into the qualitative and quantitative effects of the large-scale introduction of GM products in the EU market. We find that the introduction of GM food reduces overall EU welfare, mostly because of the associated need for costly segregation of non-GM products, but the producers of quality-enhanced products actually benefit. [source] FORECASTING DRY SEASON STREAMFLOW ON THE PEACE RIVER AT ARCADIA, FLORIDA, USA,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 4 2006David M. Coley ABSTRACT: The Peace River at Arcadia, Florida, is a municipal water supply supplement for southwestern Florida. Consequently, probabilities of encountering low flows during the dry season are of critical importance. Since the association between Pacific Ocean sea surface temperatures (SSTs) and seasonal streamflow variability in the southeastern United States is well documented, it is reasonable to generate forecasts based on this information. Here, employing historic records of minimum, mean, and maximum flows during winter (JFM) and spring (AMJ), upper and lower terciles define "above normal,""normal," and "below normal" levels of each variable. A probability distribution model describes the likelihood of these seasonal variables conditioned upon Pacific SSTs from the previous summer (JAS). Model calibration is based upon 40 (of 50) years of record employing stratified random sampling to ensure equal representation from each decade. The model is validated against the remaining 10 samples and the process repeated 100 times. Each conditional probability distribution yields varying probabilities of observing flow variables within defined categories. Generally, a warm (cold) Pacific is associated with higher (lower) flows. To test model skill, the forecast is constrained to be the most probable category in each calibration year, with significance tested by chi-square frequency tables. For all variables, the tables indicate high levels of association between forecast and observed terciles and forecast skill, particularly during winter. During spring the pattern is less clear, possibly due to the variable starting date of the summer rainy season. This simple technique suggests that Pacific SSTs provide a good forecast of low flows. [source] CT15 RISK STRATIFICATION MODELS FOR HEART VALVE SURGERYANZ JOURNAL OF SURGERY, Issue 2007C. H. Yap Purpose Risk stratification models may be useful in aiding surgical decision-making, preoperative informed consent, quality assurance and healthcare management. While several overseas models exist, no model has been well-validated for use in Australia. We aimed to assess the performance of two valve surgery risk stratification models in an Australian patient cohort. Method The Society of Cardiothoracic Surgeons of Great Britain and Ireland (SCTS) and Northern New England (NNE) models were applied to all patients undergoing valvular heart surgery at St Vincent's Hospital Melbourne and The Geelong Hospital between June 2001 and November 2006. Observed and predicted early mortalities were compared using the chi-square test. Model discrimination was assessed by the area under the receiver operating characteristic (ROC) curve. Model calibration was tested by applying the chi-square test to risk tertiles. Results SCTS model (n = 1095) performed well. Observed mortality was 4.84%, expected mortality 6.64% (chi-square p = 0.20). Model discrimination (area under ROC curve 0.835) and calibration was good (chi-square p = 0.9). the NNE model (n = 1015) over-predicted mortality. Observed mortality 4.83% and expected 7.54% (chi-square p < 0.02). Model discrimination (area under ROC curve 0.835) and calibration was good (chi-square p = 0.9). Conclusion Both models showed good model discrimination and calibration. The NNE model over-predicted early mortality whilst the SCTS model performed well in our cohort of patients. The SCTS model may be useful for use in Australia for risk stratification. [source] Respirometric evaluation and modeling of glucose utilization by Escherichia coli under aerobic and mesophilic cultivation conditionsBIOTECHNOLOGY & BIOENGINEERING, Issue 1 2007G. Insel Abstract The study presents a mechanistic model for the evaluation of glucose utilization by Escherichia coli under aerobic and mesophilic growth conditions. In the first step, the experimental data was derived from batch respirometric experiments conducted at 37°C, using two different initial substrate to microorganism (S0/X0) ratios of 15.0 and 1.3 mgCOD/mgSS. Acetate generation, glycogen formation and oxygen uptake rate profile were monitored together with glucose uptake and biomass increase throughout the experiments. The oxygen uptake rate (OUR) exhibited a typical profile accounting for growth on glucose, acetate and glycogen. No acetate formation (overflow) was detected at low initial S0/X0 ratio. In the second step, the effect of culture history developed under long-term growth limiting conditions on the kinetics of glucose utilization by the same culture was evaluated in a sequencing batch reactor (SBR). The system was operated at cyclic steady state with a constant mean cell residence time of 5 days. The kinetic response of E.coli culture was followed by similar measurements within a complete cycle. Model calibration for the SBR system showed that E. coli culture regulated its growth metabolism by decreasing the maximum growth rate (lower ) together with an increase of substrate affinity (lower KS) as compared to uncontrolled growth conditions. The continuous low rate operation of SBR system induced a significant biochemical substrate storage capability as glycogen in parallel to growth, which persisted throughout the operation. The acetate overflow was observed again as an important mechanism to be accounted for in the evaluation of process kinetics. Biotechnol. Bioeng. 2007;96: 94,105. © 2006 Wiley Periodicals, Inc. [source] Development of a dedicated risk-adjustment scoring system for colorectal surgery (colorectal POSSUM),,BRITISH JOURNAL OF SURGERY (NOW INCLUDES EUROPEAN JOURNAL OF SURGERY), Issue 9 2004P. P. Tekkis Background: The aim of the study was to develop a dedicated colorectal Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity (CR-POSSUM) equation for predicting operative mortality, and to compare its performance with the Portsmouth (P)-POSSUM model. Methods: Data were collected prospectively from 6883 patients undergoing colorectal surgery in 15 UK hospitals between 1993 and 2001. After excluding missing data and 93 patients who did not satisfy the inclusion criteria, 4632 patients (68·2 per cent) underwent elective surgery and 2107 had an emergency operation (31·0 per cent); 2437 operations (35·9 per cent) for malignant and 4267 (62·8 per cent) for non-malignant diseases were scored. Stepwise logistic regression analysis was used to develop an age-adjusted POSSUM model and a dedicated CR-POSSUM model. A 60 : 40 per cent split-sample validation technique was adopted for model development and testing. Observed and expected mortality rates were compared. Results: The operative mortality rate for the series was 5·7 per cent (387 of 6790 patients) (elective operations 2·8 per cent; emergency surgery 12·0 per cent). The CR-POSSUM, age-adjusted POSSUM and P-POSSUM models had similar areas under the receiver,operator characteristic curves. Model calibration was similar for CR-POSSUM and age-adjusted POSSUM models, and superior to that for the P-POSSUM model. The CR-POSSUM model offered the best overall accuracy, with an observed : expected ratio of 1·000, 0·998 and 0·911 respectively (test population). Conclusion: The CR-POSSUM model provided an accurate predictor of operative mortality. External validation is required in hospitals different from those in which the model was developed. Copyright © 2004 British Journal of Surgery Society Ltd. Published by John Wiley & Sons, Ltd. [source] Lignin turnover in an agricultural field: from plant residues to soil-protected fractionsEUROPEAN JOURNAL OF SOIL SCIENCE, Issue 4 2006D. P. Rasse Summary Lignin has long been suspected to be a major source of stable carbon in soils, notably because of the recalcitrant nature of its polyphenolic structure relative to other families of plant molecules. However, lignin turnover studies have produced conflicting results, most of them suggesting that large proportions of plant-residue lignin decompose within a year of incorporation into soils. Here, we propose a two-reservoir model where lignin in undecomposed plant residue (Lp) can either reach soil fractions where it is somewhat protected from further decomposition (Ls) or is transformed to non-lignin products. Model calibration data were obtained through compound-specific 13C isotopic analyses conducted in a zero- to 9-year chronosequence of maize monoculture after wheat in a temperate loam soil of the Paris basin. Lignin was quantified by CuO oxidation as VSC-lignin, i.e. the sum of vanillil- (V), syringyl- (S) and coumaryl-type (C) phenols. Model calibrations indicate that Lp has a turnover rate faster than 1 year and that 92% is mineralized as CO2 or transformed into other non-lignin products, while only 8% reaches the Ls fraction. Estimated turnover rate of the Ls fraction was 0.05 years,1. The model also suggested that about half of Lp was not measured because it had been excluded from the samples in the process of sieving at 5 mm. In conclusion, the model indicates that chemical recalcitrance alone is not sufficient to explain VSC-lignin turnover in soils, and that, functionally, the most relevant mechanism appears to be the transfer of VSC-lignin molecules and fragments from decomposing plant tissues to soil-protected fractions. [source] Parameter estimation in semi-distributed hydrological catchment modelling using a multi-criteria objective functionHYDROLOGICAL PROCESSES, Issue 22 2007Hamed Rouhani Abstract Output generated by hydrologic simulation models is traditionally calibrated and validated using split-samples of observed time series of total water flow, measured at the drainage outlet of the river basin. Although this approach might yield an optimal set of model parameters, capable of reproducing the total flow, it has been observed that the flow components making up the total flow are often poorly reproduced. Previous research suggests that notwithstanding the underlying physical processes are often poorly mimicked through calibration of a set of parameters hydrologic models most of the time acceptably estimates the total flow. The objective of this study was to calibrate and validate a computer-based hydrologic model with respect to the total and slow flow. The quick flow component used in this study was taken as the difference between the total and slow flow. Model calibrations were pursued on the basis of comparing the simulated output with the observed total and slow flow using qualitative (graphical) assessments and quantitative (statistical) indicators. The study was conducted using the Soil and Water Assessment Tool (SWAT) model and a 10-year historical record (1986,1995) of the daily flow components of the Grote Nete River basin (Belgium). The data of the period 1986,1989 were used for model calibration and data of the period 1990,1995 for model validation. The predicted daily average total flow matched the observed values with a Nash,Sutcliff coefficient of 0·67 during calibration and 0·66 during validation. The Nash,Sutcliff coefficient for slow flow was 0·72 during calibration and 0·61 during validation. Analysis of high and low flows indicated that the model is unbiased. A sensitivity analysis revealed that for the modelling of the daily total flow, accurate estimation of all 10 calibration parameters in the SWAT model is justified, while for the slow flow processes only 4 out of the set of 10 parameters were identified as most sensitive. Copyright © 2007 John Wiley & Sons, Ltd. [source] The implications of data selection for regional erosion and sediment yield modellingEARTH SURFACE PROCESSES AND LANDFORMS, Issue 15 2009Joris de Vente Abstract Regional environmental models often require detailed data on topography, land cover, soil, and climate. Remote sensing derived data form an increasingly important source of information for these models. Yet, it is often not easy to decide what the most feasible source of information is and how different input data affect model outcomes. This paper compares the quality and performance of remote sensing derived data for regional soil erosion and sediment yield modelling with the WATEM-SEDEM model in south-east Spain. An ASTER-derived digital elevation model (DEM) was compared with the DEM obtained from the Shuttle Radar Topography Mission (SRTM), and land cover information from the CORINE database (CLC2000) was compared with classified ASTER satellite images. The SRTM DEM provided more accurate estimates of slope gradient and upslope drainage area than the ASTER DEM. The classified ASTER images provided a high accuracy (90%) land cover map, and due to its higher resolution, it showed a more fragmented landscape than the CORINE land cover data. Notwithstanding the differences in quality and level of detail, CORINE and ASTER land cover data in combination with the SRTM DEM or ASTER DEM allowed accurate predictions of sediment yield at the catchment scale. Although the absolute values of erosion and sediment deposition were different, the qualitative spatial pattern of the major sources and sinks of sediments was comparable, irrespective of the DEM and land cover data used. However, due to its lower accuracy, the quantitative spatial pattern of predictions with the ASTER DEM will be worse than with the SRTM DEM. Therefore, the SRTM DEM in combination with ASTER-derived land cover data presumably provide most accurate spatially distributed estimates of soil erosion and sediment yield. Nevertheless, model calibration is required for each data set and resolution and validation of the spatial pattern of predictions is urgently needed. Copyright © 2009 John Wiley & Sons, Ltd. [source] The contributions of topoclimate and land cover to species distributions and abundance: fine-resolution tests for a mountain butterfly faunaGLOBAL ECOLOGY, Issue 2 2010Javier Gutiérrez Illán ABSTRACT Aim, Models relating species distributions to climate or habitat are widely used to predict the effects of global change on biodiversity. Most such approaches assume that climate governs coarse-scale species ranges, whereas habitat limits fine-scale distributions. We tested the influence of topoclimate and land cover on butterfly distributions and abundance in a mountain range, where climate may vary as markedly at a fine scale as land cover. Location, Sierra de Guadarrama (Spain, southern Europe) Methods, We sampled the butterfly fauna of 180 locations (89 in 2004, 91 in 2005) in a 10,800 km2 region, and derived generalized linear models (GLMs) for species occurrence and abundance based on topoclimatic (elevation and insolation) or habitat (land cover, geology and hydrology) variables sampled at 100-m resolution using GIS. Models for each year were tested against independent data from the alternate year, using the area under the receiver operating characteristic curve (AUC) (distribution) or Spearman's rank correlation coefficient (rs) (abundance). Results, In independent model tests, 74% of occurrence models achieved AUCs of > 0.7, and 85% of abundance models were significantly related to observed abundance. Topoclimatic models outperformed models based purely on land cover in 72% of occurrence models and 66% of abundance models. Including both types of variables often explained most variation in model calibration, but did not significantly improve model cross-validation relative to topoclimatic models. Hierarchical partitioning analysis confirmed the overriding effect of topoclimatic factors on species distributions, with the exception of several species for which the importance of land cover was confirmed. Main conclusions, Topoclimatic factors may dominate fine-resolution species distributions in mountain ranges where climate conditions vary markedly over short distances and large areas of natural habitat remain. Climate change is likely to be a key driver of species distributions in such systems and could have important effects on biodiversity. However, continued habitat protection may be vital to facilitate range shifts in response to climate change. [source] On Constraining Pilot Point Calibration with Regularization in PESTGROUND WATER, Issue 6 2009Michael N. Fienen Ground water model calibration has made great advances in recent years with practical tools such as PEST being instrumental for making the latest techniques available to practitioners. As models and calibration tools get more sophisticated, however, the power of these tools can be misapplied, resulting in poor parameter estimates and/or nonoptimally calibrated models that do not suit their intended purpose. Here, we focus on an increasingly common technique for calibrating highly parameterized numerical models,pilot point parameterization with Tikhonov regularization. Pilot points are a popular method for spatially parameterizing complex hydrogeologic systems; however, additional flexibility offered by pilot points can become problematic if not constrained by Tikhonov regularization. The objective of this work is to explain and illustrate the specific roles played by control variables in the PEST software for Tikhonov regularization applied to pilot points. A recent study encountered difficulties implementing this approach, but through examination of that analysis, insight into underlying sources of potential misapplication can be gained and some guidelines for overcoming them developed. [source] A Stable and Efficient Numerical Algorithm for Unconfined Aquifer AnalysisGROUND WATER, Issue 4 2009Elizabeth Keating The nonlinearity of equations governing flow in unconfined aquifers poses challenges for numerical models, particularly in field-scale applications. Existing methods are often unstable, do not converge, or require extremely fine grids and small time steps. Standard modeling procedures such as automated model calibration and Monte Carlo uncertainty analysis typically require thousands of model runs. Stable and efficient model performance is essential to these analyses. We propose a new method that offers improvements in stability and efficiency and is relatively tolerant of coarse grids. It applies a strategy similar to that in the MODFLOW code to the solution of Richard's equation with a grid-dependent pressure/saturation relationship. The method imposes a contrast between horizontal and vertical permeability in gridblocks containing the water table, does not require "dry" cells to convert to inactive cells, and allows recharge to flow through relatively dry cells to the water table. We establish the accuracy of the method by comparison to an analytical solution for radial flow to a well in an unconfined aquifer with delayed yield. Using a suite of test problems, we demonstrate the efficiencies gained in speed and accuracy over two-phase simulations, and improved stability when compared to MODFLOW. The advantages for applications to transient unconfined aquifer analysis are clearly demonstrated by our examples. We also demonstrate applicability to mixed vadose zone/saturated zone applications, including transport, and find that the method shows great promise for these types of problem as well. [source] Use of Observations below Detection Limit for Model CalibrationGROUND WATER, Issue 2 2009Michael LeFrancois Censored (nondetect) values occur when chemical concentrations in water samples are near or below the level that can be measured by an analysis method. It is common to either delete or substitute values for nondetect observations for use in model calibration, but this practice can bias the estimated parameter values and the model predictions. A more realistic representation of the system is obtained from the calibration if we include such observations in a manner reflecting that we know only the value is below the detection limit. Consequently, we propose use of the censored-residual approach to including nondetect values as observations for calibration. In this approach, residuals are calculated as the detection limit minus the simulated value when the simulated value exceeds the detection limit, and the residual is assigned a value of zero when the simulated value is below the detection limit. The new censored-residual approach is particularly advantageous when calibrating transport models to low concentration data. [source] Ground Water Flow Analysis of a Mid-Atlantic Outer Coastal Plain Watershed, Virginia, U.S.A.GROUND WATER, Issue 2 2002Michael A. Robinson Models for ground water flow (MODFLOW) and particle tracking (MODPATH) were used to determine ground water flow patterns, principal ground water discharge and recharge zones, and estimates of ground water travel times in an unconfined ground water system of an outer coastal plain watershed on the Delmarva Peninsula, Virginia. By coupling recharge and discharge zones within the watershed, flowpath analysis can provide a method to locate and implement specific management strategies within a watershed to reduce ground water nitrogen loading to surface water. A monitoring well network was installed in Eyreville Creek watershed, a first-order creek, to determine hydraulic conductivities and spatial and temporal variations in hydraulic heads for use in model calibration. Ground water flow patterns indicated the convergence of flow along the four surface water features of the watershed; primary discharge areas were in the noontide portions of the watershed. Ground water recharge zones corresponded to the surface water features with minimal development of a regional ground water system. Predicted ground water velocities varied between < 0.01 to 0.24 m/day, with elevated values associated with discharge areas and areas of convergence along surface water features. Some ground water residence times exceeded 100 years, although average residence times ranged between 16 and 21 years; approximately 95% of the ground water resource would reflect land use activities within the last 50 years. [source] Simulating soil-water movement under a hedgerow surrounding a bottomland reveals the importance of transpiration in water balanceHYDROLOGICAL PROCESSES, Issue 5 2008Z. Thomas Abstract The objective of this study was to quantify components of the water balance related to root-water uptake in the soil below a hedgerow. At this local scale, a two-dimensional (2D) flow domain in the x,z plane 6 m long and 1·55 m deep was considered. An attempt was made to estimate transpiration using a simulation model. The SWMS-2D model was modified and used to simulate temporally and spatially heterogeneous boundary conditions. A function with a variable spatial distribution of root-water uptake was considered, and model calibration was performed by adjusting this root-water uptake distribution. Observed data from a previous field study were compared against model predictions. During the validation step, satisfactory agreement was obtained, as the difference between observed and modelled pressure head values was less than 50 cm for 80% of the study data. Hedge transpiration capacity is a significant component of soil-water balance in the summer, when predicted transpiration reaches about 5·6 mm day,1. One of the most important findings is that hedge transpiration is nearly twice that of a forest canopy. In addition, soil-water content is significantly different whether downslope or upslope depending on the root-water uptake. The high transpiration rate was mainly due to the presence of a shallow water table below the hedgerow trees. Soil-water content was not a limiting factor for transpiration in this context, as it could be in one with a much deeper water table. Hedgerow tree transpiration exerts a strong impact not only on water content within the vadose zone but also on the water-table profile along the transect. Results obtained at the local scale reveal that the global impact of hedges at the catchment scale has been underestimated in the past. Transpiration rate exerts a major influence on water balance at both the seasonal and annual scales for watersheds with a dense network of hedgerows. Copyright © 2007 John Wiley & Sons, Ltd. [source] Parameter estimation in semi-distributed hydrological catchment modelling using a multi-criteria objective functionHYDROLOGICAL PROCESSES, Issue 22 2007Hamed Rouhani Abstract Output generated by hydrologic simulation models is traditionally calibrated and validated using split-samples of observed time series of total water flow, measured at the drainage outlet of the river basin. Although this approach might yield an optimal set of model parameters, capable of reproducing the total flow, it has been observed that the flow components making up the total flow are often poorly reproduced. Previous research suggests that notwithstanding the underlying physical processes are often poorly mimicked through calibration of a set of parameters hydrologic models most of the time acceptably estimates the total flow. The objective of this study was to calibrate and validate a computer-based hydrologic model with respect to the total and slow flow. The quick flow component used in this study was taken as the difference between the total and slow flow. Model calibrations were pursued on the basis of comparing the simulated output with the observed total and slow flow using qualitative (graphical) assessments and quantitative (statistical) indicators. The study was conducted using the Soil and Water Assessment Tool (SWAT) model and a 10-year historical record (1986,1995) of the daily flow components of the Grote Nete River basin (Belgium). The data of the period 1986,1989 were used for model calibration and data of the period 1990,1995 for model validation. The predicted daily average total flow matched the observed values with a Nash,Sutcliff coefficient of 0·67 during calibration and 0·66 during validation. The Nash,Sutcliff coefficient for slow flow was 0·72 during calibration and 0·61 during validation. Analysis of high and low flows indicated that the model is unbiased. A sensitivity analysis revealed that for the modelling of the daily total flow, accurate estimation of all 10 calibration parameters in the SWAT model is justified, while for the slow flow processes only 4 out of the set of 10 parameters were identified as most sensitive. Copyright © 2007 John Wiley & Sons, Ltd. [source] Multi-variable and multi-site calibration and validation of SWAT in a large mountainous catchment with high spatial variabilityHYDROLOGICAL PROCESSES, Issue 5 2006Wenzhi Cao Abstract Many methods developed for calibration and validation of physically based distributed hydrological models are time consuming and computationally intensive. Only a small set of input parameters can be optimized, and the optimization often results in unrealistic values. In this study we adopted a multi-variable and multi-site approach to calibration and validation of the Soil Water Assessment Tool (SWAT) model for the Motueka catchment, making use of extensive field measurements. Not only were a number of hydrological processes (model components) in a catchment evaluated, but also a number of subcatchments were used in the calibration. The internal variables used were PET, annual water yield, daily streamflow, baseflow, and soil moisture. The study was conducted using an 11-year historical flow record (1990,2000); 1990,94 was used for calibration and 1995,2000 for validation. SWAT generally predicted well the PET, water yield and daily streamflow. The predicted daily streamflow matched the observed values, with a Nash,Sutcliffe coefficient of 0·78 during calibration and 0·72 during validation. However, values for subcatchments ranged from 0·31 to 0·67 during calibration, and 0·36 to 0·52 during validation. The predicted soil moisture remained wet compared with the measurement. About 50% of the extra soil water storage predicted by the model can be ascribed to overprediction of precipitation; the remaining 50% discrepancy was likely to be a result of poor representation of soil properties. Hydrological compensations in the modelling results are derived from water balances in the various pathways and storage (evaporation, streamflow, surface runoff, soil moisture and groundwater) and the contributions to streamflow from different geographic areas (hill slopes, variable source areas, sub-basins, and subcatchments). The use of an integrated multi-variable and multi-site method improved the model calibration and validation and highlighted the areas and hydrological processes requiring greater calibration effort. Copyright © 2005 John Wiley & Sons, Ltd. [source] Predicting river water temperatures using the equilibrium temperature concept with application on Miramichi River catchments (New Brunswick, Canada)HYDROLOGICAL PROCESSES, Issue 11 2005Daniel Caissie Abstract Water temperature influences most of the physical, chemical and biological properties of rivers. It plays an important role in the distribution of fish and the growth rates of many aquatic organisms. Therefore, a better understanding of the thermal regime of rivers is essential for the management of important fisheries resources. This study deals with the modelling of river water temperature using a new and simplified model based on the equilibrium temperature concept. The equilibrium temperature concept is an approach where the net heat flux at the water surface can be expressed by a simple equation with fewer meteorological parameters than required with traditional models. This new water temperature model was applied on two watercourses of different size and thermal characteristics, but within a similar meteorological region, i.e., the Little Southwest Miramichi River and Catamaran Brook (New Brunswick, Canada). A study of the long-term thermal characteristics of these two rivers revealed that the greatest differences in water temperatures occurred during mid-summer peak temperatures. Data from 1992 to 1994 were used for the model calibration, while data from 1995 to 1999 were used for the model validation. Results showed a slightly better agreement between observed and predicted water temperatures for Catamaran Brook during the calibration period, with a root-mean-square error (RMSE) of 1·10 °C (Nash coefficient, NTD = 0·95) compared to 1·45 °C for the Little Southwest Miramichi River (NTD = 0·94). During the validation period, RMSEs were calculated at 1·31 °C for Catamaran Brook and 1·55 °C for the Little Southwest Miramichi River. Poorer model performances were generally observed early in the season (e.g., spring) for both rivers due to the influence of snowmelt conditions, while late summer to autumn modelling performances showed better results. Copyright © 2005 John Wiley & Sons, Ltd. [source] Further testing of the Integrated Hydrology Model (InHM): event-based simulations for a small rangeland catchment located near Chickasha, OklahomaHYDROLOGICAL PROCESSES, Issue 7 2005Keith Loague In the paper that is the foundation for this study, VanderKwaak and Loague (2001. Water Resources Research37: 999,1013) reported a demonstration of a fully coupled comprehensive physics-based hydrologic-response model, InHM (Integrated Hydrology Model), for two rainfall-runoff events from the small rangeland catchment known as R-5. The InHM simulations reported herein address (in three phases) limitations in the VanderKwaak and Loague (2001. Water Resources Research37: 999,1013) simulations. In Phase I, a new finite-element mesh was selected to represent R-5. In Phase II, with the new mesh in place, evaporation was considered for the R-5 events. In Phase III, with the new mesh in place and evaporation considered, the geology of R-5 was approximated. Each phase, compared with the results reported by VanderKwaak and Loague (2001. Water Resources Research37: 999,1013), shows a change in the simulated near-surface response. The performance of InHM for 15 R-5 events is also reported herein. The results from two stages of model calibration are presented. The uncertainty in initial soil-water content estimates for event-based simulation is shown to be a major limitation for physics-based models. The performance of InHM, relative to past event-based simulation efforts with a quasi-physically based rainfall-runoff model, is better for both peak stormflow and the time to peak stormflow, but worse for stormflow depth. The InHM simulations reported here set the stage for continuous simulation of near-surface response for the R-5 catchment with InHM. Copyright © 2004 John Wiley & Sons, Ltd. [source] Erosion models: quality of spatial predictionsHYDROLOGICAL PROCESSES, Issue 5 2003Victor Jetten Abstract An Erratum has been published for this article in Hydrological Processes 18(3) 2004, 595. An overview is given on the predictive quality of spatially distributed runoff and erosion models. A summary is given of the results of model comparison workshops organized by the Global Change and Terrestrial Ecosystems Focus 3 programme, as well as other results obtained by individual researchers. The results concur with the generally held viewpoint in the literature that the predictive quality of distributed models is moderately good for total discharge at the outlet, and not very good for net soil loss. This is only true if extensive calibration is done: uncalibrated results are generally bad. The more simple lumped models seem to perform equally well as the more complex distributed models, although the latter produce more detailed spatially distributed results that can aid the researcher. All these results are outlet based: models are tested on lumped discharge and soil loss or on hydrographs and sedigraphs. Surprisingly few tests have been done on the comparison of simulated and modelled erosion patterns, although this may arguably be just as important in the sense of designing anti-erosion measures and determining source and sink areas. Two studies are shown in which the spatial performance of the erosion model LISEM (Limburg soil erosion model) is analysed. It seems that: (i) the model is very sensitive to the resolution (grid cell size); (ii) the spatial pattern prediction is not very good; (iii) the performance becomes better when the results are resampled to a lower resolution and (iv) the results are improved when certain processes in the model (in this case gully incision) are restricted to so called ,critical areas', selected from the digital elevation model with simple rules. The difficulties associated with calibrating and validating spatially distributed soil erosion models are, to a large extent, due to the large spatial and temporal variability of soil erosion phenomena and the uncertainty associated with the input parameter values used in models to predict these processes. They will, therefore, not be solved by constructing even more complete, and therefore more complex, models. However, the situation may be improved by using more spatial information for model calibration and validation rather than output data only and by using ,optimal' models, describing only the dominant processes operating in a given landscape. Copyright © 2003 John Wiley & Sons, Ltd. [source] Erosion prediction on unpaved mountain roads in northern Thailand: validation of dynamic erodibility modelling using KINEROS2HYDROLOGICAL PROCESSES, Issue 3 2001Alan D. Ziegler Abstract The event- and physics-based KINEROS2 runoff/erosion model for predicting overland flow generation and sediment production was applied to unpaved mountain roads. Field rainfall simulations conducted in northern Thailand provided independent data for model calibration and validation. Validation shows that KINEROS2 can be parameterized to simulate total discharge, sediment transport and sediment concentration on small-scale road plots, for a range of slopes, during simulated rainfall events. The KINEROS2 model, however, did not accurately predict time-dependent changes in sediment output and concentration. In particular, early flush peaks and the temporal decay in sediment output were not predicted, owing to the inability of KINEROS2 to model removal of a surface sediment layer of finite depth. After 15,20 min, sediment transport declines as the supply of loose superficial material becomes depleted. Modelled erosion response was improved by allowing road erodibility to vary during an event. Changing the model values of erosion detachment parameters in response to changes in surface sediment availability improved model accuracy of predicted sediment transport by 30,40%. A predictive relationship between road erodibility ,states' and road surface sediment depth is presented. This relationship allows implementation of the dynamic erodibility (DE) method to events where pre-storm sediment depth can be estimated (e.g., from traffic usage variables). Copyright © 2001 John Wiley & Sons, Ltd. [source] A random field model for generating synthetic microstructures of functionally graded materialsINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 7 2008Sharif Rahman Abstract This article presents a new level-cut, inhomogeneous, filtered Poisson random field model for representing two-phase microstructures of statistically inhomogeneous, functionally graded materials with fully penetrable embedded particles. The model involves an inhomogeneous, filtered Poisson random field comprising a sum of deterministic kernel functions that are scaled by random variables and a cut of the filtered Poisson field above a specified level. The resulting level-cut field depends on the Poisson intensity, level, kernel functions, random scaling variables, and random rotation matrices. A reconstruction algorithm including model calibration and Monte Carlo simulation is presented for generating samples of two-phase microstructures of statistically inhomogeneous media. Numerical examples demonstrate that the model developed is capable of producing a wide variety of two- and three-dimensional microstructures of functionally graded composites containing particles of various sizes, shapes, densities, gradations, and orientations. An example involving finite element analyses of random microstructures, leading to statistics of effective properties of functionally graded composites, illustrates the usefulness of the proposed model. Copyright © 2008 John Wiley & Sons, Ltd. [source] Robust methods for partial least squares regressionJOURNAL OF CHEMOMETRICS, Issue 10 2003M. Hubert Abstract Partial least squares regression (PLSR) is a linear regression technique developed to deal with high-dimensional regressors and one or several response variables. In this paper we introduce robustified versions of the SIMPLS algorithm, this being the leading PLSR algorithm because of its speed and efficiency. Because SIMPLS is based on the empirical cross-covariance matrix between the response variables and the regressors and on linear least squares regression, the results are affected by abnormal observations in the data set. Two robust methods, RSIMCD and RSIMPLS, are constructed from a robust covariance matrix for high-dimensional data and robust linear regression. We introduce robust RMSECV and RMSEP values for model calibration and model validation. Diagnostic plots are constructed to visualize and classify the outliers. Several simulation results and the analysis of real data sets show the effectiveness and robustness of the new approaches. Because RSIMPLS is roughly twice as fast as RSIMCD, it stands out as the overall best method. Copyright © 2003 John Wiley & Sons, Ltd. [source] Modeling and simulation of the sequencing batch reactor at a full-scale municipal wastewater treatment plantAICHE JOURNAL, Issue 8 2009Bing-Jie Ni Abstract In this work, we attempted to modify the Activated Sludge Model No.3 and to simulate the performance of a full-scale sequencing batch reactor (SBR) plant for municipal wastewater treatment. The long-term dynamic data from the continuous operation of this SBR plant were simulated. The influent wastewater composition was characterized using batch measurements. After incorporating all the relevant processes, the sensitivity of the stoichiometric and kinetic coefficients for the model was thoroughly analyzed prior to the model calibration. The modified model was calibrated and validated with the data from both batch- and full-scale experiments. Model predictions were compared with routine data in terms of chemical oxygen demand, NH4+ -N and mixed liquid volatile suspended solids in the SBR, combined with batch experimental data under different conditions. The model predictions match the experimental results well, demonstrating that the model is appropriate to simulate the performance of a full-scale wastewater treatment plant even operated under perturbation conditions. © 2009 American Institute of Chemical Engineers AIChE J, 2009 [source] DOC leaching from a coniferous forest floor: modeling a manipulation experiment,JOURNAL OF PLANT NUTRITION AND SOIL SCIENCE, Issue 3 2005Edward Tipping Abstract The DyDOC model simulates the C dynamics of forest soils, including the production and transport of dissolved organic matter (DOM), on the basis of soil hydrology, metabolic processes, and sorption reactions. The model recognizes three main pools of soil C: litter, substrate (an intermediate transformation product), and humic substances. The model was used to simulate the behavior of C in the O horizon of soil under a Norway spruce stand at Asa, Sweden, that had been subjected to experimental manipulations (addition and removal) of above-ground litter inputs and to removal of the Oi and Oe layers. Initially, the model was calibrated using results for the control plots and was able to reproduce the observed total soil C pool and 14C content, DOC flux and DO14C content, and the pool of litter C, together with the assumed content of C in humic substances (20% of the total soil C), and the assumed distribution of DOC between hydrophilic and hydrophobic fractions. The constant describing DOC exchange between micro- and macropores was estimated from short-term variations in DOC concentration. When the calibrated model was used to predict the effects of litter and soil manipulations, it underestimated the additional DOC export (up to 33%) caused by litter addition, and underestimated the 22% reduction in DOC export caused by litter withdrawal. Therefore, an additional metabolic process, the direct conversion of litter to DOC, was added to the model. The addition of this process permitted reasonably accurate simulation of the results of the manipulation experiments, without affecting the goodness-of-fit in the model calibration. The results suggest that, under normal conditions, DOC exported from the Asa forest floor is a mixture of compounds derived from soil C pools with a range of residence times. Approximately equal amounts come from the litter pool (turnover time 4.6 yr), the substrate pool (26 yr), and the humic-substances pool (36 yr). [source] Practical identifiability of biokinetic parameters of a model describing two-step nitrification in biofilmsBIOTECHNOLOGY & BIOENGINEERING, Issue 3 2008D. Brockmann Abstract Parameter estimation and model calibration are key problems in the application of biofilm models in engineering practice, where a large number of model parameters need to be determined usually based on experimental data with only limited information content. In this article, identifiability of biokinetic parameters of a biofilm model describing two-step nitrification was evaluated based solely on bulk phase measurements of ammonium, nitrite, and nitrate. In addition to evaluating the impact of experimental conditions and available measurements, the influence of mass transport limitation within the biofilm and the initial parameter values on identifiability of biokinetic parameters was evaluated. Selection of parameters for identifiability analysis was based on global mean sensitivities while parameter identifiability was analyzed using local sensitivity functions. At most, four of the six most sensitive biokinetic parameters were identifiable from results of batch experiments at bulk phase dissolved oxygen concentrations of 0.8 or 5 mg O2/L. High linear dependences between the parameters of the subsets and resulted in reduced identifiability. Mass transport limitation within the biofilm did not influence the number of identifiable parameters but, in fact, decreased collinearity between parameters, especially for parameters that are otherwise correlated (e.g., µAOB and , or µNOB and ). The choice of the initial parameter values had a significant impact on the identifiability of two parameter subsets, both including the parameters µAOB and . Parameter subsets that did not include the subsets µAOB and or µNOB and were clearly identifiable independently of the choice of the initial parameter values. Biotechnol. Bioeng. 2008;101: 497,514. © 2008 Wiley Periodicals, Inc. [source] Storage and growth of denitrifiers in aerobic granules: Part II. model calibration and verificationBIOTECHNOLOGY & BIOENGINEERING, Issue 2 2008Bing-Jie Ni Abstract A mathematical model to describe the simultaneous storage and growth activities of denitrifiers in aerobic granules under anoxic conditions has been developed in an accompanying article. The sensitivity of the nitrate uptake rate (NUR) toward the stoichiometric and kinetic coefficients is analyzed in this article. The model parameter values are estimated by minimizing the sum of squares of the deviations between the measured and model-predicted values. The model is successfully calibrated and a set of stoichiometric and kinetic parameters for the anoxic storage and growth of the denitrifiers are obtained. Thereafter, the model established is verified with three set of experimental data. The comparison between the model established with the ASM1 model and ASM3 shows that the present model is appropriate to simulate and predict the performance of a granule-based denitrification system. Biotechnol. Bioeng. 2008;99: 324,332. © 2007 Wiley Periodicals, Inc. [source] In situ near infrared spectroscopy for analyte-specific monitoring of glucose and ammonium in streptomyces coelicolor fermentationsBIOTECHNOLOGY PROGRESS, Issue 1 2010Nanna Petersen Abstract There are many challenges associated with in situ collection of near infrared (NIR) spectra in a fermentation broth, particularly for highly aerated and agitated fermentations with filamentous organisms. In this study, antibiotic fermentation by the filamentous bacterium Streptomyces coelicolor was used as a model process. Partial least squares (PLS) regression models were calibrated for glucose and ammonium based on NIR spectra collected in situ. To ensure that the models were calibrated based on analyte-specific information, semisynthetic samples were used for model calibration in addition to data from standard batches. Thereby, part of the inherent correlation between the analytes could be eliminated. The set of semisynthetic samples were generated from fermentation broth from five separate fermentations to which different amounts of glucose, ammonium, and biomass were added. This method has previously been used off line but never before in situ. The use of semisynthetic samples along with validation on an independent batch provided a critical and realistic evaluation of analyte-specific models based on in situ NIR spectroscopy. The prediction of glucose was highly satisfactory resulting in a RMSEP of 1.1 g/L. The prediction of ammonium based on NIR spectra collected in situ was not satisfactory. A comparison with models calibrated based on NIR spectra collected off line suggested that this is caused by signal attenuation in the optical fibers in the region above 2,000 nm; a region which contains important absorption bands for ammonium. For improved predictions of ammonium in situ, it is suggested to focus efforts on enhancing the signal in that particular region. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2010 [source] | ||||||||||||||||||||||