Can the Responses of Photosynthesis and Stomatal Conductance to Water and Nitrogen Stress Combinations Be Modeled Using a Single Set of Parameters?

Science.gov (United States)

Zhang, Ningyi; Li, Gang; Yu, Shanxiang; An, Dongsheng; Sun, Qian; Luo, Weihong; Yin, Xinyou

2017-01-01

Accurately predicting photosynthesis in response to water and nitrogen stress is the first step toward predicting crop growth, yield and many quality traits under fluctuating environmental conditions. While mechanistic models are capable of predicting photosynthesis under fluctuating environmental conditions, simplifying the parameterization procedure is important toward a wide range of model applications. In this study, the biochemical photosynthesis model of Farquhar, von Caemmerer and Berry (the FvCB model) and the stomatal conductance model of Ball, Woodrow and Berry which was revised by Leuning and Yin (the BWB-Leuning-Yin model) were parameterized for Lilium (L. auratum × speciosum “Sorbonne”) grown under different water and nitrogen conditions. Linear relationships were found between biochemical parameters of the FvCB model and leaf nitrogen content per unit leaf area (Na), and between mesophyll conductance and Na under different water and nitrogen conditions. By incorporating these Na-dependent linear relationships, the FvCB model was able to predict the net photosynthetic rate (An) in response to all water and nitrogen conditions. In contrast, stomatal conductance (gs) can be accurately predicted if parameters in the BWB-Leuning-Yin model were adjusted specifically to water conditions; otherwise gs was underestimated by 9% under well-watered conditions and was overestimated by 13% under water-deficit conditions. However, the 13% overestimation of gs under water-deficit conditions led to only 9% overestimation of An by the coupled FvCB and BWB-Leuning-Yin model whereas the 9% underestimation of gs under well-watered conditions affected little the prediction of An. Our results indicate that to accurately predict An and gs under different water and nitrogen conditions, only a few parameters in the BWB-Leuning-Yin model need to be adjusted according to water conditions whereas all other parameters are either conservative or can be adjusted according to

Recommended Parameter Values for GENII Modeling of Radionuclides in Routine Air and Water Releases

Energy Technology Data Exchange (ETDEWEB)

Snyder, Sandra F. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Arimescu, Carmen [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Napier, Bruce A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hay, Tristan R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2012-11-01

The GENII v2 code is used to estimate dose to individuals or populations from the release of radioactive materials into air or water. Numerous parameter values are required for input into this code. User-defined parameters cover the spectrum from chemical data, meteorological data, agricultural data, and behavioral data. This document is a summary of parameter values that reflect conditions in the United States. Reasonable regional and age-dependent data is summarized. Data availability and quality varies. The set of parameters described address scenarios for chronic air emissions or chronic releases to public waterways. Considerations for the special tritium and carbon-14 models are briefly addressed. GENIIv2.10.0 is the current software version that this document supports.

Seasonal and spatial variation in broadleaf forest model parameters

Science.gov (United States)

Groenendijk, M.; van der Molen, M. K.; Dolman, A. J.

2009-04-01

Process based, coupled ecosystem carbon, energy and water cycle models are used with the ultimate goal to project the effect of future climate change on the terrestrial carbon cycle. A typical dilemma in such exercises is how much detail the model must be given to describe the observations reasonably realistic while also be general. We use a simple vegetation model (5PM) with five model parameters to study the variability of the parameters. These parameters are derived from the observed carbon and water fluxes from the FLUXNET database. For 15 broadleaf forests the model parameters were derived for different time resolutions. It appears that in general for all forests, the correlation coefficient between observed and simulated carbon and water fluxes improves with a higher parameter time resolution. The quality of the simulations is thus always better when a higher time resolution is used. These results show that annual parameters are not capable of properly describing weather effects on ecosystem fluxes, and that two day time resolution yields the best results. A first indication of the climate constraints can be found by the seasonal variation of the covariance between Jm, which describes the maximum electron transport for photosynthesis, and climate variables. A general seasonality we found is that during winter the covariance with all climate variables is zero. Jm increases rapidly after initial spring warming, resulting in a large covariance with air temperature and global radiation. During summer Jm is less variable, but co-varies negatively with air temperature and vapour pressure deficit and positively with soil water content. A temperature response appears during spring and autumn for broadleaf forests. This shows that an annual model parameter cannot be representative for the entire year. And relations with mean annual temperature are not possible. During summer the photosynthesis parameters are constrained by water availability, soil water content and

Determining extreme parameter correlation in ground water models

DEFF Research Database (Denmark)

Hill, Mary Cole; Østerby, Ole

2003-01-01

can go undetected even by experienced modelers. Extreme parameter correlation can be detected using parameter correlation coefficients, but their utility depends on the presence of sufficient, but not excessive, numerical imprecision of the sensitivities, such as round-off error. This work...... investigates the information that can be obtained from parameter correlation coefficients in the presence of different levels of numerical imprecision, and compares it to the information provided by an alternative method called the singular value decomposition (SVD). Results suggest that (1) calculated...... correlation coefficients with absolute values that round to 1.00 were good indicators of extreme parameter correlation, but smaller values were not necessarily good indicators of lack of correlation and resulting unique parameter estimates; (2) the SVD may be more difficult to interpret than parameter...

Hexagonal boron nitride and water interaction parameters

Energy Technology Data Exchange (ETDEWEB)

Wu, Yanbin; Aluru, Narayana R., E-mail: aluru@illinois.edu [Department of Mechanical Science and Engineering, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States); Wagner, Lucas K. [Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801-3080 (United States)

2016-04-28

The study of hexagonal boron nitride (hBN) in microfluidic and nanofluidic applications at the atomic level requires accurate force field parameters to describe the water-hBN interaction. In this work, we begin with benchmark quality first principles quantum Monte Carlo calculations on the interaction energy between water and hBN, which are used to validate random phase approximation (RPA) calculations. We then proceed with RPA to derive force field parameters, which are used to simulate water contact angle on bulk hBN, attaining a value within the experimental uncertainties. This paper demonstrates that end-to-end multiscale modeling, starting at detailed many-body quantum mechanics and ending with macroscopic properties, with the approximations controlled along the way, is feasible for these systems.

Correlation and prediction of osmotic coefficient and water activity of aqueous electrolyte solutions by a two-ionic parameter model

International Nuclear Information System (INIS)

Pazuki, G.R.

2005-01-01

In this study, osmotic coefficients and water activities in aqueous solutions have been modeled using a new approach based on the Pitzer model. This model contains two physically significant ionic parameters regarding ionic solvation and the closest distance of approach between ions in a solution. The proposed model was evaluated by estimating the osmotic coefficients of nine electrolytes in aqueous solutions. The obtained results showed that the model is suitable for predicting the osmotic coefficients in aqueous electrolyte solutions. Using adjustable parameters, which have been calculated from regression between the experimental osmotic coefficient and the results of this model, the water activity coefficients of aqueous solutions were calculated. The average absolute relative deviations of the osmotic coefficients between the experimental data and the calculated results were in agreement

Modelling of intermittent microwave convective drying: parameter sensitivity

Directory of Open Access Journals (Sweden)

Zhang Zhijun

2017-06-01

Full Text Available The reliability of the predictions of a mathematical model is a prerequisite to its utilization. A multiphase porous media model of intermittent microwave convective drying is developed based on the literature. The model considers the liquid water, gas and solid matrix inside of food. The model is simulated by COMSOL software. Its sensitivity parameter is analysed by changing the parameter values by ±20%, with the exception of several parameters. The sensitivity analysis of the process of the microwave power level shows that each parameter: ambient temperature, effective gas diffusivity, and evaporation rate constant, has significant effects on the process. However, the surface mass, heat transfer coefficient, relative and intrinsic permeability of the gas, and capillary diffusivity of water do not have a considerable effect. The evaporation rate constant has minimal parameter sensitivity with a ±20% value change, until it is changed 10-fold. In all results, the temperature and vapour pressure curves show the same trends as the moisture content curve. However, the water saturation at the medium surface and in the centre show different results. Vapour transfer is the major mass transfer phenomenon that affects the drying process.

DETERMINATION OF ACTIVATED SLUDGE MODEL ASDM PARAMETERS FOR WASTE WATER TREATMENT PLANT OPERATING IN THE SEQUENTIAL–FLOW TECHNOLOGY

Directory of Open Access Journals (Sweden)

Dariusz Zdebik

2015-01-01

Full Text Available This paper presents a method for calibration of activated sludge model with the use of computer program BioWin. Computer scheme has been developed on the basis of waste water treatment plant operating in the sequential – flow technology. For calibration of the activated sludge model data of influent and treated effluent from the existing object were used. As a result of conducted analysis was a change in biokinetic model and kinetic parameters parameters of wastewater treatment facilities. The presented method of study of the selected parameters impact on the activated sludge biokinetic model (including autotrophs maximum growth rate, the share of organic slurry in suspension general operational, efficiency secondary settling tanks can be used for conducting simulation studies of other treatment plants.

Application of isotopic information for estimating parameters in Philip infiltration model

Directory of Open Access Journals (Sweden)

Tao Wang

2016-10-01

Full Text Available Minimizing parameter uncertainty is crucial in the application of hydrologic models. Isotopic information in various hydrologic components of the water cycle can expand our knowledge of the dynamics of water flow in the system, provide additional information for parameter estimation, and improve parameter identifiability. This study combined the Philip infiltration model with an isotopic mixing model using an isotopic mass balance approach for estimating parameters in the Philip infiltration model. Two approaches to parameter estimation were compared: (a using isotopic information to determine the soil water transmission and then hydrologic information to estimate the soil sorptivity, and (b using hydrologic information to determine the soil water transmission and the soil sorptivity. Results of parameter estimation were verified through a rainfall infiltration experiment in a laboratory under rainfall with constant isotopic compositions and uniform initial soil water content conditions. Experimental results showed that approach (a, using isotopic and hydrologic information, estimated the soil water transmission in the Philip infiltration model in a manner that matched measured values well. The results of parameter estimation of approach (a were better than those of approach (b. It was also found that the analytical precision of hydrogen and oxygen stable isotopes had a significant effect on parameter estimation using isotopic information.

Estimation of Key Parameters of the Coupled Energy and Water Model by Assimilating Land Surface Data

Science.gov (United States)

Abdolghafoorian, A.; Farhadi, L.

2017-12-01

Accurate estimation of land surface heat and moisture fluxes, as well as root zone soil moisture, is crucial in various hydrological, meteorological, and agricultural applications. Field measurements of these fluxes are costly and cannot be readily scaled to large areas relevant to weather and climate studies. Therefore, there is a need for techniques to make quantitative estimates of heat and moisture fluxes using land surface state observations that are widely available from remote sensing across a range of scale. In this work, we applies the variational data assimilation approach to estimate land surface fluxes and soil moisture profile from the implicit information contained Land Surface Temperature (LST) and Soil Moisture (SM) (hereafter the VDA model). The VDA model is focused on the estimation of three key parameters: 1- neutral bulk heat transfer coefficient (CHN), 2- evaporative fraction from soil and canopy (EF), and 3- saturated hydraulic conductivity (Ksat). CHN and EF regulate the partitioning of available energy between sensible and latent heat fluxes. Ksat is one of the main parameters used in determining infiltration, runoff, groundwater recharge, and in simulating hydrological processes. In this study, a system of coupled parsimonious energy and water model will constrain the estimation of three unknown parameters in the VDA model. The profile of SM (LST) at multiple depths is estimated using moisture diffusion (heat diffusion) equation. In this study, the uncertainties of retrieved unknown parameters and fluxes are estimated from the inverse of Hesian matrix of cost function which is computed using the Lagrangian methodology. Analysis of uncertainty provides valuable information about the accuracy of estimated parameters and their correlation and guide the formulation of a well-posed estimation problem. The results of proposed algorithm are validated with a series of experiments using a synthetic data set generated by the simultaneous heat and

Parameter estimation of variable-parameter nonlinear Muskingum model using excel solver

Science.gov (United States)

Kang, Ling; Zhou, Liwei

2018-02-01

Abstract . The Muskingum model is an effective flood routing technology in hydrology and water resources Engineering. With the development of optimization technology, more and more variable-parameter Muskingum models were presented to improve effectiveness of the Muskingum model in recent decades. A variable-parameter nonlinear Muskingum model (NVPNLMM) was proposed in this paper. According to the results of two real and frequently-used case studies by various models, the NVPNLMM could obtain better values of evaluation criteria, which are used to describe the superiority of the estimated outflows and compare the accuracies of flood routing using various models, and the optimal estimated outflows by the NVPNLMM were closer to the observed outflows than the ones by other models.

Integrated water system simulation by considering hydrological and biogeochemical processes: model development, with parameter sensitivity and autocalibration

Science.gov (United States)

Zhang, Y. Y.; Shao, Q. X.; Ye, A. Z.; Xing, H. T.; Xia, J.

2016-02-01

Integrated water system modeling is a feasible approach to understanding severe water crises in the world and promoting the implementation of integrated river basin management. In this study, a classic hydrological model (the time variant gain model: TVGM) was extended to an integrated water system model by coupling multiple water-related processes in hydrology, biogeochemistry, water quality, and ecology, and considering the interference of human activities. A parameter analysis tool, which included sensitivity analysis, autocalibration and model performance evaluation, was developed to improve modeling efficiency. To demonstrate the model performances, the Shaying River catchment, which is the largest highly regulated and heavily polluted tributary of the Huai River basin in China, was selected as the case study area. The model performances were evaluated on the key water-related components including runoff, water quality, diffuse pollution load (or nonpoint sources) and crop yield. Results showed that our proposed model simulated most components reasonably well. The simulated daily runoff at most regulated and less-regulated stations matched well with the observations. The average correlation coefficient and Nash-Sutcliffe efficiency were 0.85 and 0.70, respectively. Both the simulated low and high flows at most stations were improved when the dam regulation was considered. The daily ammonium-nitrogen (NH4-N) concentration was also well captured with the average correlation coefficient of 0.67. Furthermore, the diffuse source load of NH4-N and the corn yield were reasonably simulated at the administrative region scale. This integrated water system model is expected to improve the simulation performances with extension to more model functionalities, and to provide a scientific basis for the implementation in integrated river basin managements.

[Sensitivity analysis of AnnAGNPS model's hydrology and water quality parameters based on the perturbation analysis method].

Science.gov (United States)

Xi, Qing; Li, Zhao-Fu; Luo, Chuan

2014-05-01

Sensitivity analysis of hydrology and water quality parameters has a great significance for integrated model's construction and application. Based on AnnAGNPS model's mechanism, terrain, hydrology and meteorology, field management, soil and other four major categories of 31 parameters were selected for the sensitivity analysis in Zhongtian river watershed which is a typical small watershed of hilly region in the Taihu Lake, and then used the perturbation method to evaluate the sensitivity of the parameters to the model's simulation results. The results showed that: in the 11 terrain parameters, LS was sensitive to all the model results, RMN, RS and RVC were generally sensitive and less sensitive to the output of sediment but insensitive to the remaining results. For hydrometeorological parameters, CN was more sensitive to runoff and sediment and relatively sensitive for the rest results. In field management, fertilizer and vegetation parameters, CCC, CRM and RR were less sensitive to sediment and particulate pollutants, the six fertilizer parameters (FR, FD, FID, FOD, FIP, FOP) were particularly sensitive for nitrogen and phosphorus nutrients. For soil parameters, K is quite sensitive to all the results except the runoff, the four parameters of the soil's nitrogen and phosphorus ratio (SONR, SINR, SOPR, SIPR) were less sensitive to the corresponding results. The simulation and verification results of runoff in Zhongtian watershed show a good accuracy with the deviation less than 10% during 2005- 2010. Research results have a direct reference value on AnnAGNPS model's parameter selection and calibration adjustment. The runoff simulation results of the study area also proved that the sensitivity analysis was practicable to the parameter's adjustment and showed the adaptability to the hydrology simulation in the Taihu Lake basin's hilly region and provide reference for the model's promotion in China.

Comparing the Performance of Artificial Intelligence Models in Estimating Water Quality Parameters in Periods of Low and High Water Flow

Directory of Open Access Journals (Sweden)

majid montaseri

2017-03-01

Full Text Available Introduction: A total dissolved solid (TDS is an important indicator for water quality assesment. Since the composition of mineral salts and discharge affects the TDS of water, it is important to understand the relationships of mineral salts composition with TDS. Materials and Methods: In this study, methods of artificial neural networks with five different training algorithm,Levenberg-Marquardt (LM, Scaled Conjugate Gradient (SCG, Fletcher Conjugate Gradient (CGF, One Step Secant (OSS and Gradient descent with adaptive learning rate backpropagation(GDAalgorithm and adaptive Neurofuzzy inference system based on Subtractive Clustering were used to model water quality properties of Zarrineh River Basin, to be developed in total dissolved solids prediction. ANN and ANFIS program code were written in MATLAB language. Here, the ANN with one hidden layer was used and the hidden nodes’ number was determined using trial and error. Different activation functions (logarithm sigmoid, tangent sigmoid and linear were tried for the hidden and output nodes. Therefore, water quality data from seven hydrometer stationswere used during the statistical period of 18years (1993-2010.In this research, the study period was divided into two periods of dry and wet flow, and then in a preliminary statistical analysis, the main parameters affecting the estimation of the TDS are determined and isused for modeling. 75% of data are used for remaining and 25% of the data are used for evaluation of the model, randomly. In this paper, three statistical evaluation criteria, correlation coefficient (R, the root mean square error (RMSE and mean absolute error (MAE were used to assess models’ performances. Results and Discussion: By applying correlation coefficients method between the parameters of water quality and discharge with total dissolved solid in two periods, wet and dry periods, the significant (at 95% level variables entered into the model were Q, HCO3., Cl, So4, Ca

The influence of model parameters on catchment-response

International Nuclear Information System (INIS)

Shah, S.M.S.; Gabriel, H.F.; Khan, A.A.

2002-01-01

This paper deals with the study of influence of influence of conceptual rainfall-runoff model parameters on catchment response (runoff). A conceptual modified watershed yield model is employed to study the effects of model-parameters on catchment-response, i.e. runoff. The model is calibrated, using manual parameter-fitting approach, also known as trial and error parameter-fitting. In all, there are twenty one (21) parameters that control the functioning of the model. A lumped parametric approach is used. The detailed analysis was performed on Ling River near Kahuta, having catchment area of 56 sq. miles. The model includes physical parameters like GWSM, PETS, PGWRO, etc. fitting coefficients like CINF, CGWS, etc. and initial estimates of the surface-water and groundwater storages i.e. srosp and gwsp. Sensitivity analysis offers a good way, without repetititious computations, the proper weight and consideration that must be taken when each of the influencing factor is evaluated. Sensitivity-analysis was performed to evaluate the influence of model-parameters on runoff. The sensitivity and relative contributions of model parameters influencing catchment-response are studied. (author)

Analysis of sensitivity of simulated recharge to selected parameters for seven watersheds modeled using the precipitation-runoff modeling system

Science.gov (United States)

Ely, D. Matthew

2006-01-01

Recharge is a vital component of the ground-water budget and methods for estimating it range from extremely complex to relatively simple. The most commonly used techniques, however, are limited by the scale of application. One method that can be used to estimate ground-water recharge includes process-based models that compute distributed water budgets on a watershed scale. These models should be evaluated to determine which model parameters are the dominant controls in determining ground-water recharge. Seven existing watershed models from different humid regions of the United States were chosen to analyze the sensitivity of simulated recharge to model parameters. Parameter sensitivities were determined using a nonlinear regression computer program to generate a suite of diagnostic statistics. The statistics identify model parameters that have the greatest effect on simulated ground-water recharge and that compare and contrast the hydrologic system responses to those parameters. Simulated recharge in the Lost River and Big Creek watersheds in Washington State was sensitive to small changes in air temperature. The Hamden watershed model in west-central Minnesota was developed to investigate the relations that wetlands and other landscape features have with runoff processes. Excess soil moisture in the Hamden watershed simulation was preferentially routed to wetlands, instead of to the ground-water system, resulting in little sensitivity of any parameters to recharge. Simulated recharge in the North Fork Pheasant Branch watershed, Wisconsin, demonstrated the greatest sensitivity to parameters related to evapotranspiration. Three watersheds were simulated as part of the Model Parameter Estimation Experiment (MOPEX). Parameter sensitivities for the MOPEX watersheds, Amite River, Louisiana and Mississippi, English River, Iowa, and South Branch Potomac River, West Virginia, were similar and most sensitive to small changes in air temperature and a user-defined flow

Directional spread parameter at intermediate water depth

Digital Repository Service at National Institute of Oceanography (India)

SanilKumar, V.; Deo, M.C.; Anand, N.M.; AshokKumar, K.

’ involves only the significant wave height, zero crossing wave period and water depth, the spreading function based on ‘s 3 ’ can be used for practical appli- cation. In the model based on ‘s 3 ’ the mean wave direction is an input and this has...-linearity parameter can be recommended for practical use as it provides an averaged distribution. Acknowledgements The authors would like to thank the Department of Science and Technology, New Delhi, for funding the project titled “Directional wave modelling...

Parameters-related uncertainty in modeling sugar cane yield with an agro-Land Surface Model

Science.gov (United States)

Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Ruget, F.; Gabrielle, B.

2012-12-01

Agro-Land Surface Models (agro-LSM) have been developed from the coupling of specific crop models and large-scale generic vegetation models. They aim at accounting for the spatial distribution and variability of energy, water and carbon fluxes within soil-vegetation-atmosphere continuum with a particular emphasis on how crop phenology and agricultural management practice influence the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty in these models is related to the many parameters included in the models' equations. In this study, we quantify the parameter-based uncertainty in the simulation of sugar cane biomass production with the agro-LSM ORCHIDEE-STICS on a multi-regional approach with data from sites in Australia, La Reunion and Brazil. First, the main source of uncertainty for the output variables NPP, GPP, and sensible heat flux (SH) is determined through a screening of the main parameters of the model on a multi-site basis leading to the selection of a subset of most sensitive parameters causing most of the uncertainty. In a second step, a sensitivity analysis is carried out on the parameters selected from the screening analysis at a regional scale. For this, a Monte-Carlo sampling method associated with the calculation of Partial Ranked Correlation Coefficients is used. First, we quantify the sensitivity of the output variables to individual input parameters on a regional scale for two regions of intensive sugar cane cultivation in Australia and Brazil. Then, we quantify the overall uncertainty in the simulation's outputs propagated from the uncertainty in the input parameters. Seven parameters are identified by the screening procedure as driving most of the uncertainty in the agro-LSM ORCHIDEE-STICS model output at all sites. These parameters control photosynthesis (optimal temperature of photosynthesis, optimal carboxylation rate), radiation interception (extinction coefficient), root

Subsurface water parameters: optimization approach to their determination from remotely sensed water color data.

Science.gov (United States)

Jain, S C; Miller, J R

1976-04-01

A method, using an optimization scheme, has been developed for the interpretation of spectral albedo (or spectral reflectance) curves obtained from remotely sensed water color data. This method used a two-flow model of the radiation flow and solves for the albedo. Optimization fitting of predicted to observed reflectance data is performed by a quadratic interpolation method for the variables chlorophyll concentration and scattering coefficient. The technique is applied to airborne water color data obtained from Kawartha Lakes, Sargasso Sea, and Nova Scotia coast. The modeled spectral albedo curves are compared to those obtained experimentally, and the computed optimum water parameters are compared to ground truth values. It is shown that the backscattered spectral signal contains information that can be interpreted to give quantitative estimates of the chlorophyll concentration and turbidity in the waters studied.

Temporal variation and scaling of parameters for a monthly hydrologic model

Science.gov (United States)

Deng, Chao; Liu, Pan; Wang, Dingbao; Wang, Weiguang

2018-03-01

The temporal variation of model parameters is affected by the catchment conditions and has a significant impact on hydrological simulation. This study aims to evaluate the seasonality and downscaling of model parameter across time scales based on monthly and mean annual water balance models with a common model framework. Two parameters of the monthly model, i.e., k and m, are assumed to be time-variant at different months. Based on the hydrological data set from 121 MOPEX catchments in the United States, we firstly analyzed the correlation between parameters (k and m) and catchment properties (NDVI and frequency of rainfall events, α). The results show that parameter k is positively correlated with NDVI or α, while the correlation is opposite for parameter m, indicating that precipitation and vegetation affect monthly water balance by controlling temporal variation of parameters k and m. The multiple linear regression is then used to fit the relationship between ε and the means and coefficient of variations of parameters k and m. Based on the empirical equation and the correlations between the time-variant parameters and NDVI, the mean annual parameter ε is downscaled to monthly k and m. The results show that it has lower NSEs than these from model with time-variant k and m being calibrated through SCE-UA, while for several study catchments, it has higher NSEs than that of the model with constant parameters. The proposed method is feasible and provides a useful tool for temporal scaling of model parameter.

Lumped-parameter models

Energy Technology Data Exchange (ETDEWEB)

Ibsen, Lars Bo; Liingaard, M.

2006-12-15

A lumped-parameter model represents the frequency dependent soil-structure interaction of a massless foundation placed on or embedded into an unbounded soil domain. In this technical report the steps of establishing a lumped-parameter model are presented. Following sections are included in this report: Static and dynamic formulation, Simple lumped-parameter models and Advanced lumped-parameter models. (au)

Seasonal variability of the parameters of the Ball-Berry model of stomatal conductance in maize (Zea mays L.) and sunflower (Helianthus annuus L.) under well-watered and water-stressed conditions.

Science.gov (United States)

Miner, Grace L; Bauerle, William L

2017-09-01

The Ball-Berry (BB) model of stomatal conductance (g s ) is frequently coupled with a model of assimilation to estimate water and carbon exchanges in plant canopies. The empirical slope (m) and 'residual' g s (g 0 ) parameters of the BB model influence transpiration estimates, but the time-intensive nature of measurement limits species-specific data on seasonal and stress responses. We measured m and g 0 seasonally and under different water availability for maize and sunflower. The statistical method used to estimate parameters impacted values nominally when inter-plant variability was low, but had substantial impact with larger inter-plant variability. Values for maize (m = 4.53 ± 0.65; g 0  = 0.017 ± 0.016 mol m -2 s -1 ) were 40% higher than other published values. In maize, we found no seasonal changes in m or g 0 , supporting the use of constant seasonal values, but water stress reduced both parameters. In sunflower, inter-plant variability of m and g 0 was large (m = 8.84 ± 3.77; g 0  = 0.354 ± 0.226 mol m -2 s -1 ), presenting a challenge to clear interpretation of seasonal and water stress responses - m values were stable seasonally, even as g 0 values trended downward, and m values trended downward with water stress while g 0 values declined substantially. © 2017 John Wiley & Sons Ltd.

MODEL-ASSISTED ESTIMATION OF THE GENETIC VARIABILITY IN PHYSIOLOGICAL PARAMETERS RELATED TO TOMATO FRUIT GROWTH UNDER CONTRASTED WATER CONDITIONS

Directory of Open Access Journals (Sweden)

Dario Constantinescu

2016-12-01

Full Text Available Drought stress is a major abiotic stres threatening plant and crop productivity. In case of fleshy fruits, understanding Drought stress is a major abiotic stress threatening plant and crop productivity. In case of fleshy fruits, understanding mechanisms governing water and carbon accumulations and identifying genes, QTLs and phenotypes, that will enable trade-offs between fruit growth and quality under Water Deficit (WD condition is a crucial challenge for breeders and growers. In the present work, 117 recombinant inbred lines of a population of Solanum lycopersicum were phenotyped under control and WD conditions. Plant water status, fruit growth and composition were measured and data were used to calibrate a process-based model describing water and carbon fluxes in a growing fruit as a function of plant and environment. Eight genotype-dependent model parameters were estimated using a multiobjective evolutionary algorithm in order to minimize the prediction errors of fruit dry and fresh mass throughout fruit development. WD increased the fruit dry matter content (up to 85 % and decreased its fresh weight (up to 60 %, big fruit size genotypes being the most sensitive. The mean normalized root mean squared errors of the predictions ranged between 16-18 % in the population. Variability in model genotypic parameters allowed us to explore diverse genetic strategies in response to WD. An interesting group of genotypes could be discriminated in which i the low loss of fresh mass under WD was associated with high active uptake of sugars and low value of the maximum cell wall extensibility, and ii the high dry matter content in control treatment (C was associated with a slow decrease of mass flow. Using 501 SNP markers genotyped across the genome, a QTL analysis of model parameters allowed to detect three main QTLs related to xylem and phloem conductivities, on chromosomes 2, 4 and 8. The model was then applied to design ideotypes with high dry matter

Improved gravitational search algorithm for parameter identification of water turbine regulation system

International Nuclear Information System (INIS)

Chen, Zhihuan; Yuan, Xiaohui; Tian, Hao; Ji, Bin

2014-01-01

Highlights: • We propose an improved gravitational search algorithm (IGSA). • IGSA is applied to parameter identification of water turbine regulation system (WTRS). • WTRS is modeled by considering the impact of turbine speed on torque and water flow. • Weighted objective function strategy is applied to parameter identification of WTRS. - Abstract: Parameter identification of water turbine regulation system (WTRS) is crucial in precise modeling hydropower generating unit (HGU) and provides support for the adaptive control and stability analysis of power system. In this paper, an improved gravitational search algorithm (IGSA) is proposed and applied to solve the identification problem for WTRS system under load and no-load running conditions. This newly algorithm which is based on standard gravitational search algorithm (GSA) accelerates convergence speed with combination of the search strategy of particle swarm optimization and elastic-ball method. Chaotic mutation which is devised to stepping out the local optimal with a certain probability is also added into the algorithm to avoid premature. Furthermore, a new kind of model associated to the engineering practices is built and analyzed in the simulation tests. An illustrative example for parameter identification of WTRS is used to verify the feasibility and effectiveness of the proposed IGSA, as compared with standard GSA and particle swarm optimization in terms of parameter identification accuracy and convergence speed. The simulation results show that IGSA performs best for all identification indicators

Application of Least-Squares Support Vector Machines for Quantitative Evaluation of Known Contaminant in Water Distribution System Using Online Water Quality Parameters

Directory of Open Access Journals (Sweden)

Kexin Wang

2018-03-01

Full Text Available In water-quality, early warning systems and qualitative detection of contaminants are always challenging. There are a number of parameters that need to be measured which are not entirely linearly related to pollutant concentrations. Besides the complex correlations between variable water parameters that need to be analyzed also impairs the accuracy of quantitative detection. In aspects of these problems, the application of least-squares support vector machines (LS-SVM is used to evaluate the water contamination and various conventional water quality sensors quantitatively. The various contaminations may cause different correlative responses of sensors, and also the degree of response is related to the concentration of the injected contaminant. Therefore to enhance the reliability and accuracy of water contamination detection a new method is proposed. In this method, a new relative response parameter is introduced to calculate the differences between water quality parameters and their baselines. A variety of regression models has been examined, as result of its high performance, the regression model based on genetic algorithm (GA is combined with LS-SVM. In this paper, the practical application of the proposed method is considered, controlled experiments are designed, and data is collected from the experimental setup. The measured data is applied to analyze the water contamination concentration. The evaluation of results validated that the LS-SVM model can adapt to the local nonlinear variations between water quality parameters and contamination concentration with the excellent generalization ability and accuracy. The validity of the proposed approach in concentration evaluation for potassium ferricyanide is proven to be more than 0.5 mg/L in water distribution systems.

Geostatistical Characteristic of Space -Time Variation in Underground Water Selected Quality Parameters in Klodzko Water Intake Area (SW Part of Poland)

Science.gov (United States)

Namysłowska-Wilczyńska, Barbara

2016-04-01

This paper presents selected results of research connected with the development of a (3D) geostatistical hydrogeochemical model of the Klodzko Drainage Basin, dedicated to the spatial and time variation in the selected quality parameters of underground water in the Klodzko water intake area (SW part of Poland). The research covers the period 2011÷2012. Spatial analyses of the variation in various quality parameters, i.e, contents of: ammonium ion [gNH4+/m3], NO3- (nitrate ion) [gNO3/m3], PO4-3 (phosphate ion) [gPO4-3/m3], total organic carbon C (TOC) [gC/m3], pH redox potential and temperature C [degrees], were carried out on the basis of the chemical determinations of the quality parameters of underground water samples taken from the wells in the water intake area. Spatial and time variation in the quality parameters was analyzed on the basis of archival data (period 1977÷1999) for 22 (pump and siphon) wells with a depth ranging from 9.5 to 38.0 m b.g.l., later data obtained (November 2011) from tests of water taken from 14 existing wells. The wells were built in the years 1954÷1998. The water abstraction depth (difference between the terrain elevation and the dynamic water table level) is ranged from 276÷286 m a.s.l., with an average of 282.05 m a.s.l. Dynamic water table level is contained between 6.22 m÷16.44 m b.g.l., with a mean value of 9.64 m b.g.l. The latest data (January 2012) acquired from 3 new piezometers, with a depth of 9÷10m, which were made in other locations in the relevant area. Thematic databases, containing original data on coordinates X, Y (latitude, longitude) and Z (terrain elevation and time - years) and on regionalized variables, i.e. the underground water quality parameters in the Klodzko water intake area determined for different analytical configurations (22 wells, 14 wells, 14 wells + 3 piezometers), were created. Both archival data (acquired in the years 1977÷1999) and the latest data (collected in 2011÷2012) were analyzed

Mass balance model parameter transferability on a tropical glacier

Science.gov (United States)

Gurgiser, Wolfgang; Mölg, Thomas; Nicholson, Lindsey; Kaser, Georg

2013-04-01

The mass balance and melt water production of glaciers is of particular interest in the Peruvian Andes where glacier melt water has markedly increased water supply during the pronounced dry seasons in recent decades. However, the melt water contribution from glaciers is projected to decrease with appreciable negative impacts on the local society within the coming decades. Understanding mass balance processes on tropical glaciers is a prerequisite for modeling present and future glacier runoff. As a first step towards this aim we applied a process-based surface mass balance model in order to calculate observed ablation at two stakes in the ablation zone of Shallap Glacier (4800 m a.s.l., 9°S) in the Cordillera Blanca, Peru. Under the tropical climate, the snow line migrates very frequently across most of the ablation zone all year round causing large temporal and spatial variations of glacier surface conditions and related ablation. Consequently, pronounced differences between the two chosen stakes and the two years were observed. Hourly records of temperature, humidity, wind speed, short wave incoming radiation, and precipitation are available from an automatic weather station (AWS) on the moraine near the glacier for the hydrological years 2006/07 and 2007/08 while stake readings are available at intervals of between 14 to 64 days. To optimize model parameters, we used 1000 model simulations in which the most sensitive model parameters were varied randomly within their physically meaningful ranges. The modeled surface height change was evaluated against the two stake locations in the lower ablation zone (SH11, 4760m) and in the upper ablation zone (SH22, 4816m), respectively. The optimal parameter set for each point achieved good model skill but if we transfer the best parameter combination from one stake site to the other stake site model errors increases significantly. The same happens if we optimize the model parameters for each year individually and transfer

Sensitivity of a carbon and productivity model to climatic, water, terrain, and biophysical parameters in a Rocky Mountain watershed

Energy Technology Data Exchange (ETDEWEB)

Xu, S.; Peddle, D.R.; Coburn, C.A.; Kienzle, S. [Univ. of Lethbridge, Dept. of Geography, Lethbridge, Alberta (Canada)

2008-06-15

Net primary productivity (NPP) is a key component of the terrestrial carbon cycle and is important in ecological, watershed, and forest management studies, and more broadly in global climate change research. Determining the relative importance and magnitude of uncertainty of NPP model inputs is important for proper carbon reporting over larger areas and time periods. This paper presents a systematic evaluation of the boreal ecosystem productivity simulator (BEPS) model in mountainous terrain using an established montane forest test site in Kananaskis, Alberta, in the Canadian Rocky Mountains. Model runs were based on forest (land cover, leaf area index (LAI), biomass) and climate-water inputs (solar radiation, temperature, precipitation, humidity, soil water holding capacity) derived from digital elevation model (DEM) derivatives, climate data, geographical information system (GIS) functions, and topographically corrected satellite imagery. Four sensitivity analyses were conducted as a controlled series of experiments involving (i) NPP individual parameter sensitivity for a full growing season, (ii) NPP independent variation tests (parameter {mu} {+-} 1{sigma}), (iii) factorial analyses to assess more complex multiple-factor interactions, and (iv) topographic correction. The results, validated against field measurements, showed that modeled NPP was sensitive to most inputs measured in the study area, with LAI and forest type the most important forest input, and solar radiation the most important climate input. Soil available water holding capacity expressed as a function of wetness index was only significant in conjunction with precipitation when both parameters represented a moisture-deficit situation. NPP uncertainty resulting from topographic influence was equivalent to 140 kg C ha{sup -1}{center_dot}year{sup -1}. This suggested that topographic correction of model inputs is important for accurate NPP estimation. The BEPS model, designed originally for flat

Sensitivity of a carbon and productivity model to climatic, water, terrain, and biophysical parameters in a Rocky Mountain watershed

International Nuclear Information System (INIS)

Xu, S.; Peddle, D.R.; Coburn, C.A.; Kienzle, S.

2008-01-01

Net primary productivity (NPP) is a key component of the terrestrial carbon cycle and is important in ecological, watershed, and forest management studies, and more broadly in global climate change research. Determining the relative importance and magnitude of uncertainty of NPP model inputs is important for proper carbon reporting over larger areas and time periods. This paper presents a systematic evaluation of the boreal ecosystem productivity simulator (BEPS) model in mountainous terrain using an established montane forest test site in Kananaskis, Alberta, in the Canadian Rocky Mountains. Model runs were based on forest (land cover, leaf area index (LAI), biomass) and climate-water inputs (solar radiation, temperature, precipitation, humidity, soil water holding capacity) derived from digital elevation model (DEM) derivatives, climate data, geographical information system (GIS) functions, and topographically corrected satellite imagery. Four sensitivity analyses were conducted as a controlled series of experiments involving (i) NPP individual parameter sensitivity for a full growing season, (ii) NPP independent variation tests (parameter μ ± 1σ), (iii) factorial analyses to assess more complex multiple-factor interactions, and (iv) topographic correction. The results, validated against field measurements, showed that modeled NPP was sensitive to most inputs measured in the study area, with LAI and forest type the most important forest input, and solar radiation the most important climate input. Soil available water holding capacity expressed as a function of wetness index was only significant in conjunction with precipitation when both parameters represented a moisture-deficit situation. NPP uncertainty resulting from topographic influence was equivalent to 140 kg C ha -1 ·year -1 . This suggested that topographic correction of model inputs is important for accurate NPP estimation. The BEPS model, designed originally for flat boreal forests, was shown to be

Quality assessment of water cycle parameters in REMO by radar-lidar synergy

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B. Hennemuth

2008-01-01

Full Text Available A comparison study of water cycle parameters derived from ground-based remote-sensing instruments and from the regional model REMO is presented. Observational data sets were collected during three measuring campaigns in summer/autumn 2003 and 2004 at Richard Aßmann Observatory, Lindenberg, Germany. The remote sensing instruments which were used are differential absorption lidar, Doppler lidar, ceilometer, cloud radar, and micro rain radar for the derivation of humidity profiles, ABL height, water vapour flux profiles, cloud parameters, and rain rate. Additionally, surface latent and sensible heat flux and soil moisture were measured. Error ranges and representativity of the data are discussed. For comparisons the regional model REMO was run for all measuring periods with a horizontal resolution of 18 km and 33 vertical levels. Parameter output was every hour. The measured data were transformed to the vertical model grid and averaged in time in order to better match with gridbox model values. The comparisons show that the atmospheric boundary layer is not adequately simulated, on most days it is too shallow and too moist. This is found to be caused by a wrong partitioning of energy at the surface, particularly a too large latent heat flux. The reason is obviously an overestimation of soil moisture during drying periods by the one-layer scheme in the model. The profiles of water vapour transport within the ABL appear to be realistically simulated. The comparison of cloud cover reveals an underestimation of low-level and mid-level clouds by the model, whereas the comparison of high-level clouds is hampered by the inability of the cloud radar to see cirrus clouds above 10 km. Simulated ABL clouds apparently have a too low cloud base, and the vertical extent is underestimated. The ice water content of clouds agree in model and observation whereas the liquid water content is unsufficiently derived from cloud radar reflectivity in the present study

Root zone water quality model (RZWQM2): Model use, calibration and validation

Science.gov (United States)

Ma, Liwang; Ahuja, Lajpat; Nolan, B.T.; Malone, Robert; Trout, Thomas; Qi, Z.

2012-01-01

The Root Zone Water Quality Model (RZWQM2) has been used widely for simulating agricultural management effects on crop production and soil and water quality. Although it is a one-dimensional model, it has many desirable features for the modeling community. This article outlines the principles of calibrating the model component by component with one or more datasets and validating the model with independent datasets. Users should consult the RZWQM2 user manual distributed along with the model and a more detailed protocol on how to calibrate RZWQM2 provided in a book chapter. Two case studies (or examples) are included in this article. One is from an irrigated maize study in Colorado to illustrate the use of field and laboratory measured soil hydraulic properties on simulated soil water and crop production. It also demonstrates the interaction between soil and plant parameters in simulated plant responses to water stresses. The other is from a maize-soybean rotation study in Iowa to show a manual calibration of the model for crop yield, soil water, and N leaching in tile-drained soils. Although the commonly used trial-and-error calibration method works well for experienced users, as shown in the second example, an automated calibration procedure is more objective, as shown in the first example. Furthermore, the incorporation of the Parameter Estimation Software (PEST) into RZWQM2 made the calibration of the model more efficient than a grid (ordered) search of model parameters. In addition, PEST provides sensitivity and uncertainty analyses that should help users in selecting the right parameters to calibrate.

A "total parameter estimation" method in the varification of distributed hydrological models

Science.gov (United States)

Wang, M.; Qin, D.; Wang, H.

2011-12-01

Conventionally hydrological models are used for runoff or flood forecasting, hence the determination of model parameters are common estimated based on discharge measurements at the catchment outlets. With the advancement in hydrological sciences and computer technology, distributed hydrological models based on the physical mechanism such as SWAT, MIKESHE, and WEP, have gradually become the mainstream models in hydrology sciences. However, the assessments of distributed hydrological models and model parameter determination still rely on runoff and occasionally, groundwater level measurements. It is essential in many countries, including China, to understand the local and regional water cycle: not only do we need to simulate the runoff generation process and for flood forecasting in wet areas, we also need to grasp the water cycle pathways and consumption process of transformation in arid and semi-arid regions for the conservation and integrated water resources management. As distributed hydrological model can simulate physical processes within a catchment, we can get a more realistic representation of the actual water cycle within the simulation model. Runoff is the combined result of various hydrological processes, using runoff for parameter estimation alone is inherits problematic and difficult to assess the accuracy. In particular, in the arid areas, such as the Haihe River Basin in China, runoff accounted for only 17% of the rainfall, and very concentrated during the rainy season from June to August each year. During other months, many of the perennial rivers within the river basin dry up. Thus using single runoff simulation does not fully utilize the distributed hydrological model in arid and semi-arid regions. This paper proposed a "total parameter estimation" method to verify the distributed hydrological models within various water cycle processes, including runoff, evapotranspiration, groundwater, and soil water; and apply it to the Haihe river basin in

Importance of hydrological parameters in contaminant transport modeling in a terrestrial environment

International Nuclear Information System (INIS)

Tsuduki, Katsunori; Matsunaga, Takeshi

2007-01-01

A grid type multi-layered distributed parameter model for calculating discharge in a watershed was described. Model verification with our field observation resulted in different sets of hydrological parameter values, all of which reproduced the observed discharge. The effect of those varied hydrological parameters on contaminant transport calculation was examined and discussed by simulation of event water transfer. (author)

Application of ann for predicting water quality parameters in the mediterranean sea along gaza-palestine

International Nuclear Information System (INIS)

Zaqoot, H.A.; Unar, M.A.

2008-01-01

Seawater pollution problems are gaining interest world wide because of their health impacts and other environmental issues. Intense human activities in areas surrounding enclosed and semi-enclosed seas such as the Mediterranean Sea always produce in the long term a strong environmental impact in the form of coastal and marine degradation. This paper is concerned with the use of ANNs (Artificial Neural Networks) MLP ( Multilayer Perceptron) model for the prediction of pH and EC (Electrical Conductivity) in water quality parameters along Gaza city coast. MLP neural networks are trained and developed with reference to three major oceanographic parameters (water temperature, wind speed and turbidity) to predict the values of pH and EC; these parameters are considered as inputs of the neural network. The data collected comprised of four years and collected from nine locations along Gaza coastline. Results show that the model has high capability and accuracy in predicting both parameters. The network performance has been validated with different data sets and the results show satisfactory performance. Results of the developed model have been compared with multiple regression statistical models and found that MLP predictions are slightly better than the conventional methods. Prediction results prove that the proposed approach is suitable for modeling the water quality in the Mediterranean Sea along Gaza. (author)

[Weight parameters of water quality impact and risk grade determination of water environmental sensitive spots in Jiashan].

Science.gov (United States)

Xie, Rong-Rong; Pang, Yong; Zhang, Qian; Chen, Ke; Sun, Ming-Yuan

2012-07-01

For the safety of the water environment in Jiashan county in Zhejiang Province, one-dimensional hydrodynamic and water quality models are established based on three large-scale monitoring of hydrology and water quality in Jiashan county, three water environmental sensitive spots including Hongqitang dam Chijia hydrological station and Luxie pond are selected to investigate weight parameters of water quality impact and risk grade determination. Results indicate as follows (1) Internal pollution impact in Jiashan areas was greater than the external, the average weight parameters of internal chemical oxygen demand (COD) pollution is 55.3%, internal ammonia nitrogen (NH(4+)-N) is 67.4%, internal total phosphor (TP) is 63.1%. Non-point pollution impact in Jiashan areas was greater than point pollution impact, the average weight parameters of non-point COD pollutions is 53.7%, non-point NH(4+)-N is 65.9%, non-point TP is 57.8%. (2) The risk of Hongqitang dam and Chijia hydrological station are in the middle risk. The risk of Luxie pond is also in the middle risk in August, and in April and December the risk of Luxie pond is low. The strategic decision will be suggested to guarantee water environment security and social and economic security in the study.

Modeling the impact of drought on canopy carbon and water fluxes for a subtropical evergreen coniferous plantation in southern China through parameter optimization using an ensemble Kalman filter

Directory of Open Access Journals (Sweden)

W. Ju

2010-03-01

Full Text Available Soil and atmospheric water deficits have significant influences on CO₂ and energy exchanges between the atmosphere and terrestrial ecosystems. Model parameterization significantly affects the ability of a model to simulate carbon, water, and energy fluxes. In this study, an ensemble Kalman filter (EnKF and observations of gross primary productivity (GPP and latent heat (LE fluxes were used to optimize model parameters significantly affecting the calculation of these fluxes for a subtropical coniferous plantation in southeastern China. The optimized parameters include the maximum carboxylation rate (Vc_max, the slope in the modified Ball-Berry model (M and the coefficient determining the sensitivity of stomatal conductance to atmospheric water vapor deficit (D₀. Optimized Vc_max and M showed larger variations than D₀. Seasonal variations of Vc_max and M were more pronounced than the variations between the two years. Vc_max and M were associated with soil water content (SWC. During dry periods, SWC at the 20 cm depth explained 61% and 64% of variations of Vc_max and M, respectively. EnKF parameter optimization improved the simulations of GPP, LE and SH, mainly during dry periods. After parameter optimization using EnKF, the variations of GPP, LE and SH explained by the model increased by 1% to 4% at half-hourly steps and by 3% to 5% at daily time steps. Further efforts are needed to differentiate the real causes of parameter variations and improve the ability of models to describe the change of stomatal conductance with net photosynthesis rate and the sensitivity of photosynthesis capacity to soil water stress under different environmental conditions.

Development Smart Water Aquaponics Model

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Gheorghe Adrian ZUGRAVU

2017-06-01

Full Text Available The present paper contributes to the modeling aquaculture. The paper main objectives are to identify an analysis smart water aquaponics. The purpose is to add more value to end aquaponics products. Aquaculture production depends on physical, chemical and biological qualities of pond water to a greater extent. The successful pond management requires an understanding of water quality. Intensification of pond makes the water quality undesirable with a number of water quality parameters. The objective of this model is to test and predicts plant and fish growth and net ammonium and nitrate concentrations in water in an aquaponic system. This is done by comparing the model outputs with measurements under controlled conditions in order to assess the accuracy of the tool to simulate nutrient concentrations in water and fish and plant biomass production of the system.

Centrifuge modeling of one-step outflow tests for unsaturated parameter estimations

Directory of Open Access Journals (Sweden)

H. Nakajima

2006-01-01

Full Text Available Centrifuge modeling of one-step outflow tests were carried out using a 2-m radius geotechnical centrifuge, and the cumulative outflow and transient pore water pressure were measured during the tests at multiple gravity levels. Based on the scaling laws of centrifuge modeling, the measurements generally showed reasonable agreement with prototype data calculated from forward simulations with input parameters determined from standard laboratory tests. The parameter optimizations were examined for three different combinations of input data sets using the test measurements. Within the gravity level examined in this study up to 40g, the optimized unsaturated parameters compared well when accurate pore water pressure measurements were included along with cumulative outflow as input data. With its capability to implement variety of instrumentations under well controlled initial and boundary conditions and to shorten testing time, the centrifuge modeling technique is attractive as an alternative experimental method that provides more freedom to set inverse problem conditions for the parameter estimation.

Centrifuge modeling of one-step outflow tests for unsaturated parameter estimations

Science.gov (United States)

Nakajima, H.; Stadler, A. T.

2006-10-01

Centrifuge modeling of one-step outflow tests were carried out using a 2-m radius geotechnical centrifuge, and the cumulative outflow and transient pore water pressure were measured during the tests at multiple gravity levels. Based on the scaling laws of centrifuge modeling, the measurements generally showed reasonable agreement with prototype data calculated from forward simulations with input parameters determined from standard laboratory tests. The parameter optimizations were examined for three different combinations of input data sets using the test measurements. Within the gravity level examined in this study up to 40g, the optimized unsaturated parameters compared well when accurate pore water pressure measurements were included along with cumulative outflow as input data. With its capability to implement variety of instrumentations under well controlled initial and boundary conditions and to shorten testing time, the centrifuge modeling technique is attractive as an alternative experimental method that provides more freedom to set inverse problem conditions for the parameter estimation.

CIEMAT model results for Esthwaite Water

International Nuclear Information System (INIS)

Aguero, A.; Garcia-Olivares, A.

2000-01-01

This study used the transfer model PRYMA-LO, developed by CIEMAT-IMA, Madrid, Spain, to simulate the transfer of Cs-137 in watershed scenarios. The main processes considered by the model include: transfer of the fallout to the ground, incorporation of the fallout radioisotopes into the water flow, and their removal from the system. The model was tested against observation data obtained in water and sediments of Esthwaite Water, Lake District, UK. This comparison made it possible to calibrate the parameters of the model to the specific scenario

Steel corrosion products solubility under conditions simulating various water chemistry parameters in power plants

International Nuclear Information System (INIS)

Slobodov, A.A.; Kritskij, V.G.; Zarembo, V.I.; Puchkov, L.V.

1988-01-01

To simulate construction material corrosion product mass transfer model in power plant circuits calculation of iron oxide and hydroxide solubility, depending on water chemistry parameters: temperature, pH-value, content of dissolved in water hydrogen and oxygen, is carried out

Modelling water fluxes in a pine wood soil-vegetation-atmosphere system. Comparison of a water budget and water flow model using different parameter data sources

International Nuclear Information System (INIS)

Schneider, S.; Jacques, D.; Mallants, D.

2010-01-01

For modelling complex hydrological problems, realistic models and accurate hydraulic properties are needed. A mechanistic model (HYDRUS-1D) and a compartment model are evaluated for simulating the water balance in a soil-vegetation-atmosphere system using time series of measured water content at several depths in two lysimeters in a podzol soil with Scots Pine vegetation. 10 calibration scenarios are used to investigate the impact of the model type and the number of horizons in the profile on the calibration accuracy. Main results are: (i) with a large number of soil layers, both models describe accurately the water contents at all depths, (II) the number of soil layers is the major factor that controls the quality of the calibration. The compartment model is as an abstracted model and the mechanistic model is our reference model. Drainage values are the considered output. Drainage values simulated by the abstracted model were close to those of the reference model when averaged over a sufficiently long period (about 9 months). This result suggests that drainage values obtained with an abstracted model are reliably when averaged over sufficiently long periods; the abstracted model needs less computational time without an important loss of accuracy.

Modelling water fluxes in a pine wood soil-vegetation-atmosphere system. Comparison of a water budget and water flow model using different parameter data sources

Energy Technology Data Exchange (ETDEWEB)

Schneider, S.; Jacques, D.; Mallants, D.

2010-02-15

For modelling complex hydrological problems, realistic models and accurate hydraulic properties are needed. A mechanistic model (HYDRUS-1D) and a compartment model are evaluated for simulating the water balance in a soil-vegetation-atmosphere system using time series of measured water content at several depths in two lysimeters in a podzol soil with Scots Pine vegetation. 10 calibration scenarios are used to investigate the impact of the model type and the number of horizons in the profile on the calibration accuracy. Main results are: (i) with a large number of soil layers, both models describe accurately the water contents at all depths, (II) the number of soil layers is the major factor that controls the quality of the calibration. The compartment model is as an abstracted model and the mechanistic model is our reference model. Drainage values are the considered output. Drainage values simulated by the abstracted model were close to those of the reference model when averaged over a sufficiently long period (about 9 months). This result suggests that drainage values obtained with an abstracted model are reliably when averaged over sufficiently long periods; the abstracted model needs less computational time without an important loss of accuracy.

Sensitivity analysis of specific activity model parameters for environmental transport of 3H and dose assessment

International Nuclear Information System (INIS)

Rout, S.; Mishra, D.G.; Ravi, P.M.; Tripathi, R.M.

2016-01-01

Tritium is one of the radionuclides likely to get released to the environment from Pressurized Heavy Water Reactors. Environmental models are extensively used to quantify the complex environmental transport processes of radionuclides and also to assess the impact to the environment. Model parameters exerting the significant influence on model results are identified through a sensitivity analysis (SA). SA is the study of how the variation (uncertainty) in the output of a mathematical model can be apportioned, qualitatively or quantitatively, to different sources of variation in the input parameters. This study was designed to identify the sensitive model parameters of specific activity model (TRS 1616, IAEA) for environmental transfer of 3 H following release to air and then to vegetation and animal products. Model includes parameters such as air to soil transfer factor (CRs), Tissue Free Water 3 H to Organically Bound 3 H ratio (Rp), Relative humidity (RH), WCP (fractional water content) and WEQp (water equivalent factor) any change in these parameters leads to change in 3 H level in vegetation and animal products consequently change in dose due to ingestion. All these parameters are function of climate and/or plant which change with time, space and species. Estimation of these parameters at every time is a time consuming and also required sophisticated instrumentation. Therefore it is necessary to identify the sensitive parameters and freeze the values of least sensitive parameters at constant values for more accurate estimation of 3 H dose in short time for routine assessment

A parameter optimization tool for evaluating the physical consistency of the plot-scale water budget of the integrated eco-hydrological model GEOtop in complex terrain

Science.gov (United States)

Bertoldi, Giacomo; Cordano, Emanuele; Brenner, Johannes; Senoner, Samuel; Della Chiesa, Stefano; Niedrist, Georg

2017-04-01

In mountain regions, the plot- and catchment-scale water and energy budgets are controlled by a complex interplay of different abiotic (i.e. topography, geology, climate) and biotic (i.e. vegetation, land management) controlling factors. When integrated, physically-based eco-hydrological models are used in mountain areas, there are a large number of parameters, topographic and boundary conditions that need to be chosen. However, data on soil and land-cover properties are relatively scarce and do not reflect the strong variability at the local scale. For this reason, tools for uncertainty quantification and optimal parameters identification are essential not only to improve model performances, but also to identify most relevant parameters to be measured in the field and to evaluate the impact of different assumptions for topographic and boundary conditions (surface, lateral and subsurface water and energy fluxes), which are usually unknown. In this contribution, we present the results of a sensitivity analysis exercise for a set of 20 experimental stations located in the Italian Alps, representative of different conditions in terms of topography (elevation, slope, aspect), land use (pastures, meadows, and apple orchards), soil type and groundwater influence. Besides micrometeorological parameters, each station provides soil water content at different depths, and in three stations (one for each land cover) eddy covariance fluxes. The aims of this work are: (I) To present an approach for improving calibration of plot-scale soil moisture and evapotranspiration (ET). (II) To identify the most sensitive parameters and relevant factors controlling temporal and spatial differences among sites. (III) Identify possible model structural deficiencies or uncertainties in boundary conditions. Simulations have been performed with the GEOtop 2.0 model, which is a physically-based, fully distributed integrated eco-hydrological model that has been specifically designed for mountain

Geostatistical analysis of space variation in underground water various quality parameters in Kłodzko water intake area (SW part of Poland

Directory of Open Access Journals (Sweden)

Namysłowska-Wilczyńska Barbara

2016-09-01

Full Text Available This paper presents selected results of research connected with the development of a (3D geostatistical hydrogeochemical model of the Kłodzko Drainage Basin, dedicated to the spatial variation in the different quality parameters of underground water in the water intake area (SW part of Poland. The research covers the period 2011-2012. Spatial analyses of the variation in various quality parameters, i.e., contents of: iron, manganese, ammonium ion, nitrate ion, phosphate ion, total organic carbon, pH redox potential and temperature, were carried out on the basis of the chemical determinations of the quality parameters of underground water samples taken from the wells in the water intake area. Spatial variation in the parameters was analyzed on the basis of data obtained (November 2011 from tests of water taken from 14 existing wells with a depth ranging from 9.5 to 38.0 m b.g.l. The latest data (January 2012 were obtained (gained from 3 new piezometers, made in other locations in the relevant area. A depth of these piezometers amounts to 9-10 m.

Mathematical models in the analysis of quality parameters to the Almendares river

International Nuclear Information System (INIS)

Dominguez, J.; Borroto, J.; Hernandez, A.; Santiago, J.F.; CU)

2003-01-01

The river Almendares, one of the most important water bodies of the Havana City, is very polluted. The analysis of parameters as dissolved oxygen and biochemical oxygen demand is very helpful for the studies aimed to the recovery of the river. There is a growing recognition around the word that the water quality models are very useful tools to plan sanitary strategies for the handling of the contamination. In the present work, the advective, steady- state Streeter and Phelps model was validated to simulate the effect of the multiple-point and distributed sources on the carbonaceous oxygen demand, NH4 and dissolved oxygen. For modeling purposes the section of the river located between the point where the waste water treatment station Maria del Carmen discharges to the river and the Bridge El Bosque, was divided in 11 segments. The use of the 99mTc and the Rodamine WT as tracers allowed determining the hydrodynamic parameters necessary for modeling purposes. The validated model allows to predict the effect of the sanitary strategies on the water quality of the river

Automatic estimation of aquifer parameters using long-term water supply pumping and injection records

Science.gov (United States)

Luo, Ning; Illman, Walter A.

2016-09-01

Analyses are presented of long-term hydrographs perturbed by variable pumping/injection events in a confined aquifer at a municipal water-supply well field in the Region of Waterloo, Ontario (Canada). Such records are typically not considered for aquifer test analysis. Here, the water-level variations are fingerprinted to pumping/injection rate changes using the Theis model implemented in the WELLS code coupled with PEST. Analyses of these records yield a set of transmissivity ( T) and storativity ( S) estimates between each monitoring and production borehole. These individual estimates are found to poorly predict water-level variations at nearby monitoring boreholes not used in the calibration effort. On the other hand, the geometric means of the individual T and S estimates are similar to those obtained from previous pumping tests conducted at the same site and adequately predict water-level variations in other boreholes. The analyses reveal that long-term municipal water-level records are amenable to analyses using a simple analytical solution to estimate aquifer parameters. However, uniform parameters estimated with analytical solutions should be considered as first rough estimates. More accurate hydraulic parameters should be obtained by calibrating a three-dimensional numerical model that rigorously captures the complexities of the site with these data.

Development of non-bonded interaction parameters between graphene and water using particle swarm optimization.

Science.gov (United States)

Bejagam, Karteek K; Singh, Samrendra; Deshmukh, Sanket A

2018-05-05

New Lennard-Jones parameters have been developed to describe the interactions between atomistic model of graphene, represented by REBO potential, and five commonly used all-atom water models, namely SPC, SPC/E, SPC/Fw, SPC/Fd, and TIP3P/Fs by employing particle swarm optimization (PSO) method. These new parameters were optimized to reproduce the macroscopic contact angle of water on a graphene sheet. The calculated line tension was in the order of 10 -11 J/m for the droplets of all water models. Our molecular dynamics simulations indicate the preferential orientation of water molecules near graphene-water interface with one OH bond pointing toward the graphene surface. Detailed analysis of simulation trajectories reveals the presence of water molecules with ≤∼1, ∼2, and ∼4 hydrogen bonds at the surface of air-water interface, graphene-water interface, and bulk region of the water droplet, respectively. Presence of water molecules with ≤∼1 and ∼2 hydrogen bonds suggest the existence of water clusters of different sizes at these interfaces. The trends observed in the libration, bending, and stretching bands of the vibrational spectra are closely associated with these structural features of water. The inhomogeneity in hydrogen bond network of water at the air-water and graphene-water interface is manifested by broadening of the peaks in the libration band for water present at these interfaces. The stretching band for the molecules in water droplet shows a blue shift as compared to the pure bulk water, which conjecture the presence of weaker hydrogen bond network in a droplet. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Modeling phytoremediation of nitrogen-polluted water using water hyacinth (Eichhornia crassipes)

Science.gov (United States)

Mayo, Aloyce W.; Hanai, Emmanuel E.

2017-08-01

Water hyacinth (Eichhornia crassipes) has a great potential for purification of wastewater through physical, chemical and biological mechanisms. In an attempt to improve the quality of effluents discharged from waste stabilization ponds at the University of Dar es Salaam, a pilot plant was constructed to experiment the effectiveness of this plants for transformation and removal of nitrogen. Samples of wastewater were collected and examined for water quality parameters, including pH, temperature, dissolved oxygen, and various forms of nitrogen, which were used as input parameters in a kinetic mathematical model. A conceptual model was then developed to model various processes in the system using STELLA 6.0.1 software. The results show that total nitrogen was removed by 63.9%. Denitrification contributed 73.8% of the removed nitrogen. Other dominant nitrogen removal mechanisms are net sedimentation and uptake by water hyacinth, which contributed 16.7% and 9.5% of the removed nitrogen, respectively. The model indicated that in presence of water hyacinth biofilm about 1.26 g Nm-2day-1 of nitrogen was removed. However, in the absence of biofilm in water hyacinth pond, the permanent nitrogen removal was only 0.89 g Nm-2day-1. This suggests that in absence of water hyacinth, the efficiency of nitrogen removal would decrease by 29.4%.

Mathematical modelization of surface waters for drinking water; Modelizacion matematica de la potabilizacion de aguas superficiales

Energy Technology Data Exchange (ETDEWEB)

Marin Llanes, L.A.; Alvarez Rosell, S.

1995-06-01

The application of the general strategy of deterministic modelling to the water treatment for human consumption process for surface waters is treated in this paper. Deterministic models that describe the behaviour of clarification processes: coagulation-flocculation an filtration with respect to the principal parameters that define the water principal parameters that define the water quality: turbidity, color, pH, organic matter an presence of iron, manganese and aluminium cations were obtained. The models have been checked in actual operation conditions of water treatment plant for human consumption located in Campo Florido, Havana, cuba, named Planta Norte Habana. This plant receives water from three dams. The obtained results were good. The models are valid to describe the process, to corroborate the main theories related to water clarification and to know more about this process. The complexity of the models permits their rapid and efficient solution even without the aid of a digital computer. (Author) 5 refs.

Application of Time-series Model to Predict Groundwater Quality Parameters for Agriculture: (Plain Mehran Case Study)

Science.gov (United States)

Mehrdad Mirsanjari, Mir; Mohammadyari, Fatemeh

2018-03-01

Underground water is regarded as considerable water source which is mainly available in arid and semi arid with deficient surface water source. Forecasting of hydrological variables are suitable tools in water resources management. On the other hand, time series concepts is considered efficient means in forecasting process of water management. In this study the data including qualitative parameters (electrical conductivity and sodium adsorption ratio) of 17 underground water wells in Mehran Plain has been used to model the trend of parameters change over time. Using determined model, the qualitative parameters of groundwater is predicted for the next seven years. Data from 2003 to 2016 has been collected and were fitted by AR, MA, ARMA, ARIMA and SARIMA models. Afterward, the best model is determined using information criterion or Akaike (AIC) and correlation coefficient. After modeling parameters, the map of agricultural land use in 2016 and 2023 were generated and the changes between these years were studied. Based on the results, the average of predicted SAR (Sodium Adsorption Rate) in all wells in the year 2023 will increase compared to 2016. EC (Electrical Conductivity) average in the ninth and fifteenth holes and decreases in other wells will be increased. The results indicate that the quality of groundwater for Agriculture Plain Mehran will decline in seven years.

Coupled 1D-2D hydrodynamic inundation model for sewer overflow: Influence of modeling parameters

Directory of Open Access Journals (Sweden)

Adeniyi Ganiyu Adeogun

2015-10-01

Full Text Available This paper presents outcome of our investigation on the influence of modeling parameters on 1D-2D hydrodynamic inundation model for sewer overflow, developed through coupling of an existing 1D sewer network model (SWMM and 2D inundation model (BREZO. The 1D-2D hydrodynamic model was developed for the purpose of examining flood incidence due to surcharged water on overland surface. The investigation was carried out by performing sensitivity analysis on the developed model. For the sensitivity analysis, modeling parameters, such as mesh resolution Digital Elevation Model (DEM resolution and roughness were considered. The outcome of the study shows the model is sensitive to changes in these parameters. The performance of the model is significantly influenced, by the Manning's friction value, the DEM resolution and the area of the triangular mesh. Also, changes in the aforementioned modeling parameters influence the Flood characteristics, such as the inundation extent, the flow depth and the velocity across the model domain. Keywords: Inundation, DEM, Sensitivity analysis, Model coupling, Flooding

Assimilation of Earth rotation parameters into a global ocean model (FESOM)

Science.gov (United States)

Androsov, A.; Schröter, J.; Brunnabend, S.; Saynisch, J.

2012-04-01

Earth Rotation Parameters (ERP) are used to improve estimates of the ocean circulation and mass budget. GRACE data can be used for verification or for further improvements. The Finite Element Sea-ice Ocean Model (FESOM) is used to simulate weekly ocean circulation and mass variations. The FESOM model is a hydrostatic ocean circulation model with a fully non-linear free surface. It solves the hydrostatic primitive equations with volume (Boussinesq approximation) and mass (Greatbatch correction) conservation. Fresh water exchange with the atmosphere and land is modelled as mass flux. This flux is the weakest part of the mass budget as it is the difference of large and uncertain quantities: evaporation, precipitation and river runoff. All uncertainties included in these parameters are directly reflected in the model results. ERP help in closing the budget in a realistic manner. Our strategy is designed for testing parametric estimation on a weekly basis. First, Oceanographic Earth rotation parameters (OERP) are calculated by subtracting atmospheric and hydrologic estimates from observed ERP. They are compared to OERP derived from a global ocean circulation model. The difference can be inverted to diagnose a correction of the oceanic mass budget. Additionally mass variations measured by GRACE are used for verification. In a second step, the global mass correction parameter, derived by the inversion, is used to improve the fresh water budget of FESOM.

Accuracy limit of rigid 3-point water models

Science.gov (United States)

Izadi, Saeed; Onufriev, Alexey V.

2016-08-01

Classical 3-point rigid water models are most widely used due to their computational efficiency. Recently, we introduced a new approach to constructing classical rigid water models [S. Izadi et al., J. Phys. Chem. Lett. 5, 3863 (2014)], which permits a virtually exhaustive search for globally optimal model parameters in the sub-space that is most relevant to the electrostatic properties of the water molecule in liquid phase. Here we apply the approach to develop a 3-point Optimal Point Charge (OPC3) water model. OPC3 is significantly more accurate than the commonly used water models of same class (TIP3P and SPCE) in reproducing a comprehensive set of liquid bulk properties, over a wide range of temperatures. Beyond bulk properties, we show that OPC3 predicts the intrinsic charge hydration asymmetry (CHA) of water — a characteristic dependence of hydration free energy on the sign of the solute charge — in very close agreement with experiment. Two other recent 3-point rigid water models, TIP3PFB and H2ODC, each developed by its own, completely different optimization method, approach the global accuracy optimum represented by OPC3 in both the parameter space and accuracy of bulk properties. Thus, we argue that an accuracy limit of practical 3-point rigid non-polarizable models has effectively been reached; remaining accuracy issues are discussed.

Impact of the calibration period on the conceptual rainfall-runoff model parameter estimates

Science.gov (United States)

Todorovic, Andrijana; Plavsic, Jasna

2015-04-01

A conceptual rainfall-runoff model is defined by its structure and parameters, which are commonly inferred through model calibration. Parameter estimates depend on objective function(s), optimisation method, and calibration period. Model calibration over different periods may result in dissimilar parameter estimates, while model efficiency decreases outside calibration period. Problem of model (parameter) transferability, which conditions reliability of hydrologic simulations, has been investigated for decades. In this paper, dependence of the parameter estimates and model performance on calibration period is analysed. The main question that is addressed is: are there any changes in optimised parameters and model efficiency that can be linked to the changes in hydrologic or meteorological variables (flow, precipitation and temperature)? Conceptual, semi-distributed HBV-light model is calibrated over five-year periods shifted by a year (sliding time windows). Length of the calibration periods is selected to enable identification of all parameters. One water year of model warm-up precedes every simulation, which starts with the beginning of a water year. The model is calibrated using the built-in GAP optimisation algorithm. The objective function used for calibration is composed of Nash-Sutcliffe coefficient for flows and logarithms of flows, and volumetric error, all of which participate in the composite objective function with approximately equal weights. Same prior parameter ranges are used in all simulations. The model is calibrated against flows observed at the Slovac stream gauge on the Kolubara River in Serbia (records from 1954 to 2013). There are no trends in precipitation nor in flows, however, there is a statistically significant increasing trend in temperatures at this catchment. Parameter variability across the calibration periods is quantified in terms of standard deviations of normalised parameters, enabling detection of the most variable parameters

Inverse modeling with RZWQM2 to predict water quality

Science.gov (United States)

Nolan, Bernard T.; Malone, Robert W.; Ma, Liwang; Green, Christopher T.; Fienen, Michael N.; Jaynes, Dan B.

2011-01-01

This chapter presents guidelines for autocalibration of the Root Zone Water Quality Model (RZWQM2) by inverse modeling using PEST parameter estimation software (Doherty, 2010). Two sites with diverse climate and management were considered for simulation of N losses by leaching and in drain flow: an almond [Prunus dulcis (Mill.) D.A. Webb] orchard in the San Joaquin Valley, California and the Walnut Creek watershed in central Iowa, which is predominantly in corn (Zea mays L.)–soybean [Glycine max (L.) Merr.] rotation. Inverse modeling provides an objective statistical basis for calibration that involves simultaneous adjustment of model parameters and yields parameter confidence intervals and sensitivities. We describe operation of PEST in both parameter estimation and predictive analysis modes. The goal of parameter estimation is to identify a unique set of parameters that minimize a weighted least squares objective function, and the goal of predictive analysis is to construct a nonlinear confidence interval for a prediction of interest by finding a set of parameters that maximizes or minimizes the prediction while maintaining the model in a calibrated state. We also describe PEST utilities (PAR2PAR, TSPROC) for maintaining ordered relations among model parameters (e.g., soil root growth factor) and for post-processing of RZWQM2 outputs representing different cropping practices at the Iowa site. Inverse modeling provided reasonable fits to observed water and N fluxes and directly benefitted the modeling through: (i) simultaneous adjustment of multiple parameters versus one-at-a-time adjustment in manual approaches; (ii) clear indication by convergence criteria of when calibration is complete; (iii) straightforward detection of nonunique and insensitive parameters, which can affect the stability of PEST and RZWQM2; and (iv) generation of confidence intervals for uncertainty analysis of parameters and model predictions. Composite scaled sensitivities, which

Parameter Identification with the Random Perturbation Particle Swarm Optimization Method and Sensitivity Analysis of an Advanced Pressurized Water Reactor Nuclear Power Plant Model for Power Systems

Directory of Open Access Journals (Sweden)

Li Wang

2017-02-01

Full Text Available The ability to obtain appropriate parameters for an advanced pressurized water reactor (PWR unit model is of great significance for power system analysis. The attributes of that ability include the following: nonlinear relationships, long transition time, intercoupled parameters and difficult obtainment from practical test, posed complexity and difficult parameter identification. In this paper, a model and a parameter identification method for the PWR primary loop system were investigated. A parameter identification process was proposed, using a particle swarm optimization (PSO algorithm that is based on random perturbation (RP-PSO. The identification process included model variable initialization based on the differential equations of each sub-module and program setting method, parameter obtainment through sub-module identification in the Matlab/Simulink Software (Math Works Inc., Natick, MA, USA as well as adaptation analysis for an integrated model. A lot of parameter identification work was carried out, the results of which verified the effectiveness of the method. It was found that the change of some parameters, like the fuel temperature and coolant temperature feedback coefficients, changed the model gain, of which the trajectory sensitivities were not zero. Thus, obtaining their appropriate values had significant effects on the simulation results. The trajectory sensitivities of some parameters in the core neutron dynamic module were interrelated, causing the parameters to be difficult to identify. The model parameter sensitivity could be different, which would be influenced by the model input conditions, reflecting the parameter identifiability difficulty degree for various input conditions.

Assessment of the water quality parameters in relation to fish ...

African Journals Online (AJOL)

Physicochemical indices of water body changed seasonally and this necessitated an investigation to assess the water quality parameters of Osinmo reservoir in relation to its fish species. The water quality parameters were measured using standard methods. Results obtained show that the reservoir is alkaline in nature with ...

Modeling sugarcane yield with a process-based model from site to continental scale: uncertainties arising from model structure and parameter values

Science.gov (United States)

Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Caubel, A.; Huth, N.; Marin, F.; Martiné, J.-F.

2014-06-01

Agro-land surface models (agro-LSM) have been developed from the integration of specific crop processes into large-scale generic land surface models that allow calculating the spatial distribution and variability of energy, water and carbon fluxes within the soil-vegetation-atmosphere continuum. When developing agro-LSM models, particular attention must be given to the effects of crop phenology and management on the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty of agro-LSM models is related to their usually large number of parameters. In this study, we quantify the parameter-values uncertainty in the simulation of sugarcane biomass production with the agro-LSM ORCHIDEE-STICS, using a multi-regional approach with data from sites in Australia, La Réunion and Brazil. In ORCHIDEE-STICS, two models are chained: STICS, an agronomy model that calculates phenology and management, and ORCHIDEE, a land surface model that calculates biomass and other ecosystem variables forced by STICS phenology. First, the parameters that dominate the uncertainty of simulated biomass at harvest date are determined through a screening of 67 different parameters of both STICS and ORCHIDEE on a multi-site basis. Secondly, the uncertainty of harvested biomass attributable to those most sensitive parameters is quantified and specifically attributed to either STICS (phenology, management) or to ORCHIDEE (other ecosystem variables including biomass) through distinct Monte Carlo runs. The uncertainty on parameter values is constrained using observations by calibrating the model independently at seven sites. In a third step, a sensitivity analysis is carried out by varying the most sensitive parameters to investigate their effects at continental scale. A Monte Carlo sampling method associated with the calculation of partial ranked correlation coefficients is used to quantify the sensitivity of harvested biomass to input

Error propagation of partial least squares for parameters optimization in NIR modeling

Science.gov (United States)

Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng

2018-03-01

A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models.

Error propagation of partial least squares for parameters optimization in NIR modeling.

Science.gov (United States)

Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng

2018-03-05

A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models. Copyright © 2017. Published by Elsevier B.V.

A Review of Distributed Parameter Groundwater Management Modeling Methods

Science.gov (United States)

Gorelick, Steven M.

1983-04-01

Models which solve the governing groundwater flow or solute transport equations in conjunction with optimization techniques, such as linear and quadratic programing, are powerful aquifer management tools. Groundwater management models fall in two general categories: hydraulics or policy evaluation and water allocation. Groundwater hydraulic management models enable the determination of optimal locations and pumping rates of numerous wells under a variety of restrictions placed upon local drawdown, hydraulic gradients, and water production targets. Groundwater policy evaluation and allocation models can be used to study the influence upon regional groundwater use of institutional policies such as taxes and quotas. Furthermore, fairly complex groundwater-surface water allocation problems can be handled using system decomposition and multilevel optimization. Experience from the few real world applications of groundwater optimization-management techniques is summarized. Classified separately are methods for groundwater quality management aimed at optimal waste disposal in the subsurface. This classification is composed of steady state and transient management models that determine disposal patterns in such a way that water quality is protected at supply locations. Classes of research missing from the literature are groundwater quality management models involving nonlinear constraints, models which join groundwater hydraulic and quality simulations with political-economic management considerations, and management models that include parameter uncertainty.

Quantifying the Effect of Soil Water Repellency on Infiltration Parameters Using a Dry Sand

Science.gov (United States)

Shillito, R.; Berli, M.; Ghezzehei, T. A.; Kaminski, E.

2017-12-01

Water infiltration into less than perfectly wettable soils has usually been considered an exceptional case—in fact, it may be the rule. Infiltration into soils exhibiting some degree of water repellency has important implications in agricultural irrigation, post-fire runoff, golf course and landscape management, and spill and contaminant mitigation. Beginning from fundamental principles, we developed a physically-based model to quantify the effect of water repellency on infiltration parameters. Experimentally, we used a dry silica sand and treated it to achieve various known degrees of water repellency. The model was verified using data gathered from multiple upward infiltration (wicking) experiments using the treated sand. The model also allowed us to explore the effect of initial soil moisture conditions on infiltration into water-repellent soils, and the physical interpretation of the simple water drop penetration time test. These results provide a fundamental step in the physically-based understanding of how water infiltrates into a less than perfectly wettable porous media.

A Simple Beta-Function Model for Soil-Water Repellency as a Function of Water and Organic Carbon Contents

DEFF Research Database (Denmark)

Karunarathna, Anurudda Kumara; Kawamoto, Ken; Møldrup, Per

2010-01-01

Soil-water content (θ) and soil organic carbon (SOC) are key factors controlling the occurrence and magnitude of soil-water repellency (WR). Although expressions have recently been proposed to describe the nonlinear variation of WR with θ, the inclusion of easily measurable parameters in predictive...... conditions for 19 soils were used to test the model. The beta function successfully reproduced all the measured soil-water repellency characteristic, α(θ), curves. Significant correlations were found between model parameters and SOC content (1%-14%). The model was independently tested against data...

Validation of a spatial–temporal soil water movement and plant water uptake model

KAUST Repository

HEPPELL, J.

2014-06-01

© 2014, (publisher). All rights reserved. Management and irrigation of plants increasingly relies on accurate mathematical models for the movement of water within unsaturated soils. Current models often use values for water content and soil parameters that are averaged over the soil profile. However, many applications require models to more accurately represent the soil–plant–atmosphere continuum, in particular, water movement and saturation within specific parts of the soil profile. In this paper a mathematical model for water uptake by a plant root system from unsaturated soil is presented. The model provides an estimate of the water content level within the soil at different depths, and the uptake of water by the root system. The model was validated using field data, which include hourly water content values at five different soil depths under a grass/herb cover over 1 year, to obtain a fully calibrated system for plant water uptake with respect to climate conditions. When compared quantitatively to a simple water balance model, the proposed model achieves a better fit to the experimental data due to its ability to vary water content with depth. To accurately model the water content in the soil profile, the soil water retention curve and saturated hydraulic conductivity needed to vary with depth.

Quantitative Determination of Spring Water Quality Parameters via Electronic Tongue

Directory of Open Access Journals (Sweden)

Noèlia Carbó

2017-12-01

Full Text Available The use of a voltammetric electronic tongue for the quantitative analysis of quality parameters in spring water is proposed here. The electronic voltammetric tongue consisted of a set of four noble electrodes (iridium, rhodium, platinum, and gold housed inside a stainless steel cylinder. These noble metals have a high durability and are not demanding for maintenance, features required for the development of future automated equipment. A pulse voltammetry study was conducted in 83 spring water samples to determine concentrations of nitrate (range: 6.9–115 mg/L, sulfate (32–472 mg/L, fluoride (0.08–0.26 mg/L, chloride (17–190 mg/L, and sodium (11–94 mg/L as well as pH (7.3–7.8. These parameters were also determined by routine analytical methods in spring water samples. A partial least squares (PLS analysis was run to obtain a model to predict these parameter. Orthogonal signal correction (OSC was applied in the preprocessing step. Calibration (67% and validation (33% sets were selected randomly. The electronic tongue showed good predictive power to determine the concentrations of nitrate, sulfate, chloride, and sodium as well as pH and displayed a lower R2 and slope in the validation set for fluoride. Nitrate and fluoride concentrations were estimated with errors lower than 15%, whereas chloride, sulfate, and sodium concentrations as well as pH were estimated with errors below 10%.

Solubility of Methane, Ethane, and Propane in Pure Water Using New Binary Interaction Parameters

Directory of Open Access Journals (Sweden)

Masoud Behrouz

2015-07-01

Full Text Available Solubility of hydrocarbons in water is important due to ecological concerns and new restrictions on the existence of organic pollutants in water streams. Also, the creation of a thermodynamic model has required an advanced study of the phase equilibrium between water (as a basis for the widest spread muds and amines and gas hydrocarbon phases in wide temperature and pressure ranges. Therefore, it is of great interest to develop semi-empirical correlations, charts, or thermodynamic models for estimating the solubility of hydrocarbons in liquid water. In this work, a thermodynamic model based on Mathias modification of Sova-Redlich-Kwong (SRK equation of state is suggested using classical mixing rules with new binary interaction parameters which were used for two-component systems of hydrocarbons and water. Finally, the model results and their deviations in comparison with the experimental data are presented; these deviations were equal to 5.27, 6.06, and 4.1% for methane, ethane, and propane respectively.

Modelling anisotropic water transport in polymer composite

Indian Academy of Sciences (India)

This work reports anisotropic water transport in a polymer composite consisting of an epoxy matrix reinforced with aligned triangular bars made of vinyl ester. By gravimetric experiments, water diffusion in resin and polymer composites were characterized. Parameters for Fickian diffusion and polymer relaxation models were ...

Modeling the outflow of liquid with initial supercritical parameters using the relaxation model for condensation

Directory of Open Access Journals (Sweden)

Lezhnin Sergey

2017-01-01

Full Text Available The two-temperature model of the outflow from a vessel with initial supercritical parameters of medium has been realized. The model uses thermodynamic non-equilibrium relaxation approach to describe phase transitions. Based on a new asymptotic model for computing the relaxation time, the outflow of water with supercritical initial pressure and super- and subcritical temperatures has been calculated.

Control-volume-based model of the steam-water injector flow

Science.gov (United States)

Kwidziński, Roman

2010-03-01

The paper presents equations of a mathematical model to calculate flow parameters in characteristic cross-sections in the steam-water injector. In the model, component parts of the injector (steam nozzle, water nozzle, mixing chamber, condensation wave region, diffuser) are treated as a series of connected control volumes. At first, equations for the steam nozzle and water nozzle are written and solved for known flow parameters at the injector inlet. Next, the flow properties in two-phase flow comprising mixing chamber and condensation wave region are determined from mass, momentum and energy balance equations. Then, water compression in diffuser is taken into account to evaluate the flow parameters at the injector outlet. Irreversible losses due to friction, condensation and shock wave formation are taken into account for the flow in the steam nozzle. In two-phase flow domain, thermal and mechanical nonequilibrium between vapour and liquid is modelled. For diffuser, frictional pressure loss is considered. Comparison of the model predictions with experimental data shows good agreement, with an error not exceeding 15% for discharge (outlet) pressure and 1 K for outlet temperature.

Modeling the historical water cycle of the Copenhagen Area 1850-2003

DEFF Research Database (Denmark)

Jeppesen, Jan; Christensen, Steen; Ladekarl, Ulla Lyngs

2011-01-01

The paper describes a set of modelling utilities (a root-zone model, a grid-distribution tool, and a modified Modflow-2000 model) that can be used to simulate the water cycle of a city in terms of root-zone water balance, water supply, wastewater, storm runoff, groundwater flow, streamflow......-wise calibration strategy, using different parts of the data in the various steps, to calibrate hydrogeological parameters, storm runoff parameters, and parameters governing the interactions between groundwater and leaky pipe systems, respectively. Simulations indicate that present rates of groundwater leakage...... into streams, lakes, and wetlands constitute 60% of pre-urbanization levels due to massive groundwater extraction. However, the current problems of groundwater shortages and streamflow depletion would have been far worse, if precipitation had not increased by 20% since 1850. Model simulations indicate...

Site-specific parameter values for the Nuclear Regulatory Commission's food pathway dose model

International Nuclear Information System (INIS)

Hamby, D.M.

1992-01-01

Routine operations at the Savannah River Site (SRS) in Western South Carolina result in radionuclide releases to the atmosphere and to the Savannah River. The resulting radiation doses to the off-site maximum individual and the off-site population within 80 km of the SRS are estimated on a yearly basis. These estimates are currently generated using dose models prescribed for the commercial nuclear power industry by the Nuclear Regulatory Commission (NRC). The NRC provides default values for dose-model parameters for facilities without resources to develop site-specific values. A survey of land- and water-use characteristics for the Savannah River area has been conducted to determine site-specific values for water recreation, consumption, and agricultural parameters used in the NRC Regulatory Guide 1.109 (1977) dosimetric models. These site parameters include local characteristics of meat, milk, and vegetable production; recreational and commercial activities on the Savannah River; and meat, milk, vegetable, and seafood consumption rates. This paper describes how parameter data were obtained at the Savannah River Site and the impacts of such data on off-site dose. Dose estimates using site-specific parameter values are compared to estimates using the NRC default values

A Probabilistic Model for Propagating Ungauged Basin Runoff Prediction Variability and Uncertainty Into Estuarine Water Quality Dynamics and Water Quality-Based Management Decisions

Science.gov (United States)

Anderson, R.; Gronewold, A.; Alameddine, I.; Reckhow, K.

2008-12-01

The latest official assessment of United States (US) surface water quality indicates that pathogens are a leading cause of coastal shoreline water quality standard violations. Rainfall-runoff and hydrodynamic water quality models are commonly used to predict fecal indicator bacteria (FIB) concentrations in these waters and to subsequently identify climate change, land use, and pollutant mitigation scenarios which might improve water quality and lead to reinstatement of a designated use. While decay, settling, and other loss kinetics dominate FIB fate and transport in freshwater systems, previous authors identify tidal advection as a dominant fate and transport process in coastal estuaries. As a result, acknowledging hydrodynamic model input (e.g. watershed runoff) variability and parameter (e.g tidal dynamics parameter) uncertainty is critical to building a robust coastal water quality model. Despite the widespread application of watershed models (and associated model calibration procedures), we find model inputs and parameters are commonly encoded as deterministic point estimates (as opposed to random variables), an approach which effectively ignores potential sources of variability and uncertainty. Here, we present an innovative approach to building, calibrating, and propagating uncertainty and variability through a coupled data-based mechanistic (DBM) rainfall-runoff and tidal prism water quality model. While we apply the model to an ungauged tributary of the Newport River Estuary (one of many currently impaired shellfish harvesting waters in Eastern North Carolina), our model can be used to evaluate water quality restoration scenarios for coastal waters with a wide range of designated uses. We begin by calibrating the DBM rainfall-runoff model, as implemented in the IHACRES software package, using a regionalized calibration approach. We then encode parameter estimates as random variables (in the rainfall-runoff component of our comprehensive model) via the

Identification of Important Parameter from Leachate Solid Waste Landfill on Water Quality, Case Study of Pesanggrahan River

Science.gov (United States)

Yanidar, R.; Hartono, D. M.; Moersidik, S. S.

2018-03-01

Cipayung Landfill takes waste generation from Depok City approximately ± 750 tons/day of solid waste. The south and west boundaries of the landfill is Pesanggarahan River which 200m faraway. The objectives of this study are to indicate an important parameter which greatly affects the water quality of Pesanggrahan River and purpose the dynamic model for improving our understanding of the dynamic behavior that captures the interactions and feedbacks important parameter in river in order to identify and assess the effects of the treated leachate from final solid waste disposal activity as it responds to changes over time in the river. The high concentrations of BOD and COD are not the only cause significantly affect the quality of the pesanggrahan water, it also because the river has been contaminated in the upstream area. It need the water quality model to support the effectiveness calculation of activities for preventing a selected the pollutant sources the model should be developed for simulating and predicting the trend of water quality performance in Pesanggrahan River which can potentially be used by policy makers in strategic management to sustain river water quality as raw drinking water.

A review of hydrological/water-quality models

Directory of Open Access Journals (Sweden)

Liangliang GAO,Daoliang LI

2014-12-01

Full Text Available Water quality models are important in predicting the changes in surface water quality for environmental management. A range of water quality models are wildly used, but every model has its advantages and limitations for specific situations. The aim of this review is to provide a guide to researcher for selecting a suitable water quality model. Eight well known water quality models were selected for this review: SWAT, WASP, QUALs, MIKE 11, HSPF, CE-QUAL-W2, ELCOM-CAEDYM and EFDC. Each model is described according to its intended use, development, simulation elements, basic principles and applicability (e.g., for rivers, lakes, and reservoirs and estuaries. Currently, the most important trends for future model development are: (1 combination models─individual models cannot completely solve the complex situations so combined models are needed to obtain the most appropriate results, (2 application of artificial intelligence and mechanistic models combined with non-mechanistic models will provide more accurate results because of the realistic parameters derived from non-mechanistic models, and (3 integration with remote sensing, geographical information and global position systems (3S ─3S can solve problems requiring large amounts of data.

Using an inverse modelling approach to evaluate the water retention in a simple water harvesting technique

Directory of Open Access Journals (Sweden)

K. Verbist

2009-10-01

Full Text Available In arid and semi-arid zones, runoff harvesting techniques are often applied to increase the water retention and infiltration on steep slopes. Additionally, they act as an erosion control measure to reduce land degradation hazards. Nevertheless, few efforts were observed to quantify the water harvesting processes of these techniques and to evaluate their efficiency. In this study, a combination of detailed field measurements and modelling with the HYDRUS-2D software package was used to visualize the effect of an infiltration trench on the soil water content of a bare slope in northern Chile. Rainfall simulations were combined with high spatial and temporal resolution water content monitoring in order to construct a useful dataset for inverse modelling purposes. Initial estimates of model parameters were provided by detailed infiltration and soil water retention measurements. Four different measurement techniques were used to determine the saturated hydraulic conductivity (K_sat independently. The tension infiltrometer measurements proved a good estimator of the K_sat value and a proxy for those measured under simulated rainfall, whereas the pressure and constant head well infiltrometer measurements showed larger variability. Six different parameter optimization functions were tested as a combination of soil-water content, water retention and cumulative infiltration data. Infiltration data alone proved insufficient to obtain high model accuracy, due to large scatter on the data set, and water content data were needed to obtain optimized effective parameter sets with small confidence intervals. Correlation between the observed soil water content and the simulated values was as high as R²=0.93 for ten selected observation points used in the model calibration phase, with overall correlation for the 22 observation points equal to 0.85. The model results indicate that the infiltration trench has a

Water quality assessment and meta model development in Melen watershed - Turkey.

Science.gov (United States)

Erturk, Ali; Gurel, Melike; Ekdal, Alpaslan; Tavsan, Cigdem; Ugurluoglu, Aysegul; Seker, Dursun Zafer; Tanik, Aysegul; Ozturk, Izzet

2010-07-01

Istanbul, being one of the highly populated metropolitan areas of the world, has been facing water scarcity since the past decade. Water transfer from Melen Watershed was considered as the most feasible option to supply water to Istanbul due to its high water potential and relatively less degraded water quality. This study consists of two parts. In the first part, water quality data covering 26 parameters from 5 monitoring stations were analyzed and assessed due to the requirements of the "Quality Required of Surface Water Intended for the Abstraction of Drinking Water" regulation. In the second part, a one-dimensional stream water quality model with simple water quality kinetics was developed. It formed a basic design for more advanced water quality models for the watershed. The reason for assessing the water quality data and developing a model was to provide information for decision making on preliminary actions to prevent any further deterioration of existing water quality. According to the water quality assessment at the water abstraction point, Melen River has relatively poor water quality with regard to NH(4)(+), BOD(5), faecal streptococcus, manganese and phenol parameters, and is unsuitable for drinking water abstraction in terms of COD, PO(4)(3-), total coliform, total suspended solids, mercury and total chromium parameters. The results derived from the model were found to be consistent with the water quality assessment. It also showed that relatively high inorganic nitrogen and phosphorus concentrations along the streams are related to diffuse nutrient loads that should be managed together with municipal and industrial wastewaters. Copyright 2010 Elsevier Ltd. All rights reserved.

Parameter values for the long-term nuclear waste management food chain model LIMCAL

International Nuclear Information System (INIS)

Zach, Reto.

1982-09-01

Eighteen parameters of LIMCAL, a comprehensive food chain model for predicting ICRP 26 50-year committed effective dose equivalents to man due to long-term nuclear waste management are reviewed. The parameters are: soil bulk density, plowlayer depth, soil surface layer depth, resusupension factor, atmospheric dust load, deposition velocity, plant interception fraction, plant environmental half-time, translocation factor, time of above-ground exposure, plant yield, holdup time, animals' feed consumption rate, animals' water consumption rate, man's water consumption rate, food type calorie conversion factors, man's total caloric intake rate and food type calorie fractions. LIMCAL has both traditional and unique parameters. The former occur in most of the currently used assessment models for nuclear installations, whereas the latter do not. For each of the parameters of LIMCAL, a suitable generic value for long-term nuclear waste management was determined. Thus, the general literature and the values currently used or recommended by various agencies were reviewed

The modelling influence of water content to mechanical parameter of soil in analysis of slope stability

Science.gov (United States)

Gusman, M.; Nazki, A.; Putra, R. R.

2018-04-01

One of the parameters in slope stability analysis is the shear strength of the soil. Changes in soil shear strength characteristics lead to a decrease in safety factors on the slopes. This study aims to see the effect of increased moisture content on soil mechanical parameters. The case study study was conducted on the slopes of Sitinjau Lauik Kota Padang. The research method was done by laboratory analysis and simple liniear regression analysis and multiple. Based on the test soil results show that the increase in soil water content causes a decrease in cohesion values and internal shear angle. The relationship of moisture content to cohesion is described in equation Y = 55.713-0,6X with R2 = 0.842. While the relationship of water content to shear angle in soil is described in the equation Y = 38.878-0.258X with R2 = 0.915. From several simulations of soil water level improvement, calculation of safety factor (SF) of slope. The calculation results show that the increase of groundwater content is very significant affect the safety factor (SF) slope. SF slope values are in safe condition when moisture content is 50% and when it reaches maximum water content 73.74% slope safety factor value potentially for landslide.

Water quality modeling in the dead end sections of drinking water distribution networks.

Science.gov (United States)

Abokifa, Ahmed A; Yang, Y Jeffrey; Lo, Cynthia S; Biswas, Pratim

2016-02-01

Dead-end sections of drinking water distribution networks are known to be problematic zones in terms of water quality degradation. Extended residence time due to water stagnation leads to rapid reduction of disinfectant residuals allowing the regrowth of microbial pathogens. Water quality models developed so far apply spatial aggregation and temporal averaging techniques for hydraulic parameters by assigning hourly averaged water demands to the main nodes of the network. Although this practice has generally resulted in minimal loss of accuracy for the predicted disinfectant concentrations in main water transmission lines, this is not the case for the peripheries of the distribution network. This study proposes a new approach for simulating disinfectant residuals in dead end pipes while accounting for both spatial and temporal variability in hydraulic and transport parameters. A stochastic demand generator was developed to represent residential water pulses based on a non-homogenous Poisson process. Dispersive solute transport was considered using highly dynamic dispersion rates. A genetic algorithm was used to calibrate the axial hydraulic profile of the dead-end pipe based on the different demand shares of the withdrawal nodes. A parametric sensitivity analysis was done to assess the model performance under variation of different simulation parameters. A group of Monte-Carlo ensembles was carried out to investigate the influence of spatial and temporal variations in flow demands on the simulation accuracy. A set of three correction factors were analytically derived to adjust residence time, dispersion rate and wall demand to overcome simulation error caused by spatial aggregation approximation. The current model results show better agreement with field-measured concentrations of conservative fluoride tracer and free chlorine disinfectant than the simulations of recent advection dispersion reaction models published in the literature. Accuracy of the simulated

Modeling Surface Water Flow in the Atchafalaya Basin

Science.gov (United States)

Liu, K.; Simard, M.

2017-12-01

While most of the Mississippi River Delta is sinking due to insufficient sediment supply and subsidence, the stable wetlands and the prograding delta systems in the Atchafalaya Basin provide a unique opportunity to study the constructive interactions between riverine and marine forcings and their impacts upon coastal morphology. To better understand the hydrodynamics in this region, we developed a numerical modeling system for the water flow through the river channel - deltas - wetlands networks in the Atchafalaya Basin. Determining spatially varying model parameters for a large area composed of such diverse land cover types poses a challenge to developing an accurate numerical model. For example, the bottom friction coefficient can not be measured directly and the available elevation maps for the wetlands in the basin are inaccurate. To overcome these obstacles, we developed the modeling system in three steps. Firstly, we modeled river bathymetry based on in situ sonar transects and developed a simplified 1D model for the Wax Lake Outlet using HEC-RAS. Secondly, we used a Bayesian approach to calibrate the model automatically and infer important unknown parameters such as riverbank elevation and bottom friction coefficient through Markov Chain Monte Carlo (MCMC) simulations. We also estimated the wetland elevation based on the distribution of different vegetation species in the basin. Thirdly, with the lessons learnt from the 1D model, we developed a depth-averaged 2D model for the whole Atchafalaya Basin using Delft3D. After calibrations, the model successfully reproduced the water levels measured at five gauges in the Wax Lake Outlet and the modeled water surface profile along the channel agreed reasonably well with our LIDAR measurements. In addition, the model predicted a one-hour delay in tidal phase from the Wax Lake Delta to the upstream gauge. In summary, this project presents a procedure to initialize hydrology model parameters that integrates field

Modeling water quality in the middle segment of the Luyano River

International Nuclear Information System (INIS)

Valcarcel Rojas, Lino; Alberro Macias, Nancy; Rodriguez GonzalesZahilys; Herrero, Maydel; Borroto Portela, Jorge; Rodrigues Garcez, Anel; Dominguez Catases, Judith; Griffith Martinez, Jose; Derivet Zarzabal, Milagros; Flores Juan, Pedro; Cuesta Borges, Jaime

2010-01-01

The methodology for the modelling of three parameters that characterize the quality of water: Biochemical Oxygen Demand, Dissolved Oxygen and ammonium in a stretch of Luyano river using the software RIOSep v.2.0. The procedure combined the use of radiotracer techniques for estimating the hydrodynamic parameters of the current with physicochemical techniques for the determination of its basic parameters. The lifting of the hydrodynamic parameters in the current was conducted with the use of 99mTc as a radiotracer. Simultaneously with flow determination, water was sampled at five stations in the main channel and two tributaries, in order to determine the physicochemical parameters of interest. The result was a model that describes accurately the Biochemical Oxygen Demand and Dissolved Oxygen behaviour (more than 90%), and showed good result for ammonium, so it adequately characterizes the processes of purification and oxygen balance in the water. (Author)

Uncertainty Assessment in Urban Storm Water Drainage Modelling

DEFF Research Database (Denmark)

Thorndahl, Søren

The object of this paper is to make an overall description of the author's PhD study, concerning uncertainties in numerical urban storm water drainage models. Initially an uncertainty localization and assessment of model inputs and parameters as well as uncertainties caused by different model...

Developing a particle tracking surrogate model to improve inversion of ground water - Surface water models

Science.gov (United States)

Cousquer, Yohann; Pryet, Alexandre; Atteia, Olivier; Ferré, Ty P. A.; Delbart, Célestine; Valois, Rémi; Dupuy, Alain

2018-03-01

The inverse problem of groundwater models is often ill-posed and model parameters are likely to be poorly constrained. Identifiability is improved if diverse data types are used for parameter estimation. However, some models, including detailed solute transport models, are further limited by prohibitive computation times. This often precludes the use of concentration data for parameter estimation, even if those data are available. In the case of surface water-groundwater (SW-GW) models, concentration data can provide SW-GW mixing ratios, which efficiently constrain the estimate of exchange flow, but are rarely used. We propose to reduce computational limits by simulating SW-GW exchange at a sink (well or drain) based on particle tracking under steady state flow conditions. Particle tracking is used to simulate advective transport. A comparison between the particle tracking surrogate model and an advective-dispersive model shows that dispersion can often be neglected when the mixing ratio is computed for a sink, allowing for use of the particle tracking surrogate model. The surrogate model was implemented to solve the inverse problem for a real SW-GW transport problem with heads and concentrations combined in a weighted hybrid objective function. The resulting inversion showed markedly reduced uncertainty in the transmissivity field compared to calibration on head data alone.

Hydraulic modeling of clay ceramic water filters for point-of-use water treatment.

Science.gov (United States)

Schweitzer, Ryan W; Cunningham, Jeffrey A; Mihelcic, James R

2013-01-02

The acceptability of ceramic filters for point-of-use water treatment depends not only on the quality of the filtered water, but also on the quantity of water the filters can produce. This paper presents two mathematical models for the hydraulic performance of ceramic water filters under typical usage. A model is developed for two common filter geometries: paraboloid- and frustum-shaped. Both models are calibrated and evaluated by comparison to experimental data. The hydraulic models are able to predict the following parameters as functions of time: water level in the filter (h), instantaneous volumetric flow rate of filtrate (Q), and cumulative volume of water produced (V). The models' utility is demonstrated by applying them to estimate how the volume of water produced depends on factors such as the filter shape and the frequency of filling. Both models predict that the volume of water produced can be increased by about 45% if users refill the filter three times per day versus only once per day. Also, the models predict that filter geometry affects the volume of water produced: for two filters with equal volume, equal wall thickness, and equal hydraulic conductivity, a filter that is tall and thin will produce as much as 25% more water than one which is shallow and wide. We suggest that the models can be used as tools to help optimize filter performance.

Thermodynamic Modeling of Natural Gas Systems Containing Water

DEFF Research Database (Denmark)

Karakatsani, Eirini K.; Kontogeorgis, Georgios M.

2013-01-01

As the need for dew point specifications remains very urgent in the natural gas industry, the development of accurate thermodynamic models, which will match experimental data and will allow reliable extrapolations, is needed. Accurate predictions of the gas phase water content in equilibrium...... with a heavy phase were previously obtained using cubic plus association (CPA) coupled with a solid phase model in the case of hydrates, for the binary systems of water–methane and water–nitrogen and a few natural gas mixtures. In this work, CPA is being validated against new experimental data, both water...... content and phase equilibrium data, and solid model parameters are being estimated for four natural gas main components (methane, ethane, propane, and carbon dioxide). Different tests for the solid model parameters are reported, including vapor-hydrate-equilibria (VHE) and liquid-hydrate-equilibria (LHE...

Temporal variability in water quality parameters--a case study of drinking water reservoir in Florida, USA.

Science.gov (United States)

Toor, Gurpal S; Han, Lu; Stanley, Craig D

2013-05-01

Our objective was to evaluate changes in water quality parameters during 1983-2007 in a subtropical drinking water reservoir (area: 7 km(2)) located in Lake Manatee Watershed (area: 338 km(2)) in Florida, USA. Most water quality parameters (color, turbidity, Secchi depth, pH, EC, dissolved oxygen, total alkalinity, cations, anions, and lead) were below the Florida potable water standards. Concentrations of copper exceeded the potable water standard of water quality threshold of 20 μg l(-1). Concentrations of total N showed significant increase from 1983 to 1994 and a decrease from 1997 to 2007. Total P showed significant increase during 1983-2007. Mean concentrations of total N (n = 215; 1.24 mg l(-1)) were lower, and total P (n = 286; 0.26 mg l(-1)) was much higher than the EPA numeric criteria of 1.27 mg total N l(-1) and 0.05 mg total P l(-1) for Florida's colored lakes, respectively. Seasonal trends were observed for many water quality parameters where concentrations were typically elevated during wet months (June-September). Results suggest that reducing transport of organic N may be one potential option to protect water quality in this drinking water reservoir.

Soil-related Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

A. J. Smith

2003-01-01

This analysis is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the geologic repository at Yucca Mountain. The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A graphical representation of the documentation hierarchy for the ERMYN biosphere model is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003 [163602]). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. ''The Biosphere Model Report'' (BSC 2003 [160699]) describes in detail the conceptual model as well as the mathematical model and its input parameters. The purpose of this analysis was to develop the biosphere model parameters needed to evaluate doses from pathways associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation and ash

Mechanism Underlying Bonding Water Film Effect on Rheological Parameters

Directory of Open Access Journals (Sweden)

Yiyan Lv

2016-01-01

Full Text Available From experiments on bonding water of different slurries and the analysis of flow curves, the bilinear fluid model has been improved. The results showed that the rheological parameters correspond to physical processes at different stages of shear strain. As shear rate increases, slurries evolve from high-viscosity Bingham fluids to low-viscosity Bingham fluids. Specific surface area determines the number of edge-to-face arrangements; mineral composition influences the binding strength of each edge-to-face arrangement; and the volume fraction of particles regulates the distance between clay particles and number of edge-to-face arrangements.

Modelling anisotropic water transport in polymer composite ...

Indian Academy of Sciences (India)

Parameters for Fickian diffusion and polymer relaxation models were determined by .... Water transport process of resin and polymer composite specimens at ..... simulation. ... Kwon Y W and Bang H 1997 Finite element method using matlab.

The surface water model for assessing Canada's nuclear fuel waste disposal concept

International Nuclear Information System (INIS)

Bird, G.A.; Stephenson, M.; Cornett, R.J.

1993-01-01

Canada's Nuclear Fuel Waste Management Program (NFWMP) is investigating the concept of disposal of nuclear fuel waste in a vault excavated deep in crystalline rock on the Canadian Shield. Probabilistic vault, geosphere, and biosphere models are implemented using Monte Carlo simulation techniques to trace nuclides transported in groundwater to the surface environment and humans far into the future. This paper describes the surface water submodel and its parameter values, sensitivity analysis, and validation. The surface water model is a simple, time-dependent, mass balance model of a lake that calculates radioactive and stable isotope contaminant concentrations in lake water and sediment. These concentrations are input to the other submodels and used to predict the radiological dose to humans and other biota. Parameter values in the model are based on the literature and the author's own data, and are generic to Canadian Shield lakes. Most parameters are represented by log normally distributed probability density functions. Sensitivity analysis indicates that nuclide concentrations in lake water and sediment are governed primarily by hydrological flushing with catchment area being the most important parameter. When catchment area is held constant lake area and nuclide transfer rate from water to sediment strongly influence concentrations in both water and sediment. For volatile nuclides, gaseous evasion also has a marked influence on concentrations in both water and sediment, whereas sedimentation rate strongly influences sediment nuclide concentrations. Validation tests demonstrate that the models predictions for 60 Co, 134 Cs, 3 H, P, Cd and Ca are consistent with empirical data when uncertainties are taken into account

Estimation of octanol/water partition coefficients using LSER parameters

Science.gov (United States)

Luehrs, Dean C.; Hickey, James P.; Godbole, Kalpana A.; Rogers, Tony N.

1998-01-01

The logarithms of octanol/water partition coefficients, logKow, were regressed against the linear solvation energy relationship (LSER) parameters for a training set of 981 diverse organic chemicals. The standard deviation for logKow was 0.49. The regression equation was then used to estimate logKow for a test of 146 chemicals which included pesticides and other diverse polyfunctional compounds. Thus the octanol/water partition coefficient may be estimated by LSER parameters without elaborate software but only moderate accuracy should be expected.

Inverse modeling of hydrologic parameters using surface flux and runoff observations in the Community Land Model

Science.gov (United States)

Sun, Y.; Hou, Z.; Huang, M.; Tian, F.; Leung, L. Ruby

2013-12-01

This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4). Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Both deterministic least-square fitting and stochastic Markov-chain Monte Carlo (MCMC)-Bayesian inversion approaches are evaluated by applying them to CLM4 at selected sites with different climate and soil conditions. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find that using model parameters calibrated by the sampling-based stochastic inversion approaches provides significant improvements in the model simulations compared to using default CLM4 parameter values, and that as more information comes in, the predictive intervals (ranges of posterior distributions) of the calibrated parameters become narrower. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty bounds.

Modeling of Water Quality 'Almendares River'

International Nuclear Information System (INIS)

Domínguez Catasús, Judith

2005-01-01

The river Almendares, one of the most important water bodies of the Havana City, is very polluted. The analysis of parameters as dissolved oxygen and biochemical oxygen demand is very helpful for the studies aimed to the recovery of the river. There is a growing recognition around the word that the water quality models are very useful tools to plan sanitary strategies for the handling of the contamination. In the present work, the advective, steady- state Streeter and Phelps model was validated to simulate the effect of the multiple-point and distributed sources on the carbonaceous oxygen demand, NH4 and dissolved oxygen. For modeling purposes the section of the river located between the point where the waste water treatment station Maria del Carmen discharges to the river and the Bridge El Bosque, was divided in 11 segments. The use of the 99mTc and the Rodamine WT as tracers allowed determining the hydrodynamic parameters necessary for modeling purposes. The validated model allows to predict the effect of the sanitary strategies on the water quality of the river. The main conclusions are: 1. The model Streeter and Phelps calibrated and validated in the Almendares between the confluence of the channel 'María del Carmen' and bridge the Forest of Havana, described in more than 90% The behavior of the dissolved oxygen and BODn (in terms of ammonia), and more than 85%, the carbonaceous demand oxygen, which characterizes the process of purification. 2. Model validation Streeter and Phelps, indicates that implicit conceptual model is appropriate. This refers primarily to the considerations relating to the calculation of the kinetic constants and the DOS, the segmentation used, to the location of the discharges and the Standing been about them, to the river morphology and hydrodynamic parameters . 3. The calibration procedure Streeter and Phelps model that determines the least-squares Kr-Kd pair that best fits the OD and uses this Kr to model BOD gets four% increase in

Model parameter updating using Bayesian networks

International Nuclear Information System (INIS)

Treml, C.A.; Ross, Timothy J.

2004-01-01

This paper outlines a model parameter updating technique for a new method of model validation using a modified model reference adaptive control (MRAC) framework with Bayesian Networks (BNs). The model parameter updating within this method is generic in the sense that the model/simulation to be validated is treated as a black box. It must have updateable parameters to which its outputs are sensitive, and those outputs must have metrics that can be compared to that of the model reference, i.e., experimental data. Furthermore, no assumptions are made about the statistics of the model parameter uncertainty, only upper and lower bounds need to be specified. This method is designed for situations where a model is not intended to predict a complete point-by-point time domain description of the item/system behavior; rather, there are specific points, features, or events of interest that need to be predicted. These specific points are compared to the model reference derived from actual experimental data. The logic for updating the model parameters to match the model reference is formed via a BN. The nodes of this BN consist of updateable model input parameters and the specific output values or features of interest. Each time the model is executed, the input/output pairs are used to adapt the conditional probabilities of the BN. Each iteration further refines the inferred model parameters to produce the desired model output. After parameter updating is complete and model inputs are inferred, reliabilities for the model output are supplied. Finally, this method is applied to a simulation of a resonance control cooling system for a prototype coupled cavity linac. The results are compared to experimental data.

Low-field NMR logging sensor for measuring hydraulic parameters of model soils

Science.gov (United States)

Sucre, Oscar; Pohlmeier, Andreas; Minière, Adrien; Blümich, Bernhard

2011-08-01

SummaryKnowing the exact hydraulic parameters of soils is very important for improving water management in agriculture and for the refinement of climate models. Up to now, however, the investigation of such parameters has required applying two techniques simultaneously which is time-consuming and invasive. Thus, the objective of this current study is to present only one technique, i.e., a new non-invasive method to measure hydraulic parameters of model soils by using low-field nuclear magnetic resonance (NMR). Hereby, two model clay or sandy soils were respectively filled in a 2 m-long acetate column having an integrated PVC tube. After the soils were completely saturated with water, a low-field NMR sensor was moved up and down in the PVC tube to quantitatively measure along the whole column the initial water content of each soil sample. Thereafter, both columns were allowed to drain. Meanwhile, the NMR sensor was set at a certain depth to measure the water content of that soil slice. Once the hydraulic equilibrium was reached in each of the two columns, a final moisture profile was taken along the whole column. Three curves were subsequently generated accordingly: (1) the initial moisture profile, (2) the evolution curve of the moisture depletion at that particular depth, and (3) the final moisture profile. All three curves were then inverse analyzed using a MATLAB code over numerical data produced with the van Genuchten-Mualem model. Hereby, a set of values ( α, n, θr and θs) was found for the hydraulic parameters for the soils under research. Additionally, the complete decaying NMR signal could be analyzed through Inverse Laplace Transformation and averaged on the 1/ T2 space. Through measurement of the decay in pure water, the effect on the relaxation caused by the sample could be estimated from the obtained spectra. The migration of the sample-related average with decreasing saturation speaks for a enhancement of the surface relaxation as the soil dries, in

Parametric sensitivity analysis of an agro-economic model of management of irrigation water

Science.gov (United States)

El Ouadi, Ihssan; Ouazar, Driss; El Menyari, Younesse

2015-04-01

The current work aims to build an analysis and decision support tool for policy options concerning the optimal allocation of water resources, while allowing a better reflection on the issue of valuation of water by the agricultural sector in particular. Thus, a model disaggregated by farm type was developed for the rural town of Ait Ben Yacoub located in the east Morocco. This model integrates economic, agronomic and hydraulic data and simulates agricultural gross margin across in this area taking into consideration changes in public policy and climatic conditions, taking into account the competition for collective resources. To identify the model input parameters that influence over the results of the model, a parametric sensitivity analysis is performed by the "One-Factor-At-A-Time" approach within the "Screening Designs" method. Preliminary results of this analysis show that among the 10 parameters analyzed, 6 parameters affect significantly the objective function of the model, it is in order of influence: i) Coefficient of crop yield response to water, ii) Average daily gain in weight of livestock, iii) Exchange of livestock reproduction, iv) maximum yield of crops, v) Supply of irrigation water and vi) precipitation. These 6 parameters register sensitivity indexes ranging between 0.22 and 1.28. Those results show high uncertainties on these parameters that can dramatically skew the results of the model or the need to pay particular attention to their estimates. Keywords: water, agriculture, modeling, optimal allocation, parametric sensitivity analysis, Screening Designs, One-Factor-At-A-Time, agricultural policy, climate change.

40 CFR 141.87 - Monitoring requirements for water quality parameters.

Science.gov (United States)

2010-07-01

... § 141.87 Monitoring requirements for water quality parameters. All large water systems, and all small- and medium-size systems that exceed the lead or copper action level shall monitor water quality... methods. (i) Tap samples shall be representative of water quality throughout the distribution system...

Comparison of anthropometric parameters among Iranian and Spanish water polo players

Directory of Open Access Journals (Sweden)

Pooya Nekooei

2016-06-01

Full Text Available The purpose of this study was to compare the anthropometric parameters between Iranian and Spanish water polo national team players. Material and Methods ― The research was conducted in the physiological laboratory of Isfahan Azad University. Participants who participate in this study were 44 male national water polo players (22 Iranian and 22 Spanish, age 22±2 years old (Mean±SD. For the aim of this study twenty anthropometric parameters that was more important for water polo was measured and analysis. All the parameters were measured base on the international standard of anthropometric parameters (International Society for the Advancement of Kinanthropometry – ISAK. For analysis data, normal distribution of the data was proved by Kolmogorov-Smirnov test and then comparison between two groups was done by t-test. Results ― The results showed a significant difference in seven anthropometric parameters contain body fat percentage (P=0.031, biliocristal breadth (P<0.001, wrist breadth (P<0.001, chest girth (P=0.021, mid-thigh girth (P=0.019, palm length (P<0.001 and height (P=0.032. Conclusion ― Spanish players with relatively higher underlying levels of anthropometric parameters compare to Iranian water polo players had stronger ability to control the ball with the bigger palm and bigger wrist breadth, also they had stronger ability to do water vertical jump, cause of higher value of biliocristal breadth and mid-thigh girth and also stronger throwing the ball because of bigger muscle on their chest part of their body. However, Base on this study, having longer hands, more muscular body than fat and taller stature is an advantage for the players because it is considered to be a useful parameter in water polo.

PARAMETER ESTIMATION IN BREAD BAKING MODEL

Directory of Open Access Journals (Sweden)

Hadiyanto Hadiyanto

2012-05-01

Full Text Available Bread product quality is highly dependent to the baking process. A model for the development of product quality, which was obtained by using quantitative and qualitative relationships, was calibrated by experiments at a fixed baking temperature of 200°C alone and in combination with 100 W microwave powers. The model parameters were estimated in a stepwise procedure i.e. first, heat and mass transfer related parameters, then the parameters related to product transformations and finally product quality parameters. There was a fair agreement between the calibrated model results and the experimental data. The results showed that the applied simple qualitative relationships for quality performed above expectation. Furthermore, it was confirmed that the microwave input is most meaningful for the internal product properties and not for the surface properties as crispness and color. The model with adjusted parameters was applied in a quality driven food process design procedure to derive a dynamic operation pattern, which was subsequently tested experimentally to calibrate the model. Despite the limited calibration with fixed operation settings, the model predicted well on the behavior under dynamic convective operation and on combined convective and microwave operation. It was expected that the suitability between model and baking system could be improved further by performing calibration experiments at higher temperature and various microwave power levels.  Abstrak  PERKIRAAN PARAMETER DALAM MODEL UNTUK PROSES BAKING ROTI. Kualitas produk roti sangat tergantung pada proses baking yang digunakan. Suatu model yang telah dikembangkan dengan metode kualitatif dan kuantitaif telah dikalibrasi dengan percobaan pada temperatur 200oC dan dengan kombinasi dengan mikrowave pada 100 Watt. Parameter-parameter model diestimasi dengan prosedur bertahap yaitu pertama, parameter pada model perpindahan masa dan panas, parameter pada model transformasi, dan

Temporal variability and climatology of hydrodynamic, water property and water quality parameters in the West Johor Strait of Singapore.

Science.gov (United States)

Behera, Manasa Ranjan; Chun, Cui; Palani, Sundarambal; Tkalich, Pavel

2013-12-15

The study presents a baseline variability and climatology study of measured hydrodynamic, water properties and some water quality parameters of West Johor Strait, Singapore at hourly-to-seasonal scales to uncover their dependency and correlation to one or more drivers. The considered parameters include, but not limited by sea surface elevation, current magnitude and direction, solar radiation and air temperature, water temperature, salinity, chlorophyll-a and turbidity. FFT (Fast Fourier Transform) analysis is carried out for the parameters to delineate relative effect of tidal and weather drivers. The group and individual correlations between the parameters are obtained by principal component analysis (PCA) and cross-correlation (CC) technique, respectively. The CC technique also identifies the dependency and time lag between driving natural forces and dependent water property and water quality parameters. The temporal variability and climatology of the driving forces and the dependent parameters are established at the hourly, daily, fortnightly and seasonal scales. Copyright © 2013 Elsevier Ltd. All rights reserved.

Modeling of water erosion by seagis model. Case Watershed Dam Siliana

International Nuclear Information System (INIS)

Chabaan, Chayma

2016-01-01

water erosion is a complicated phenomenon, largely obvious in north Africa, especially in the watershed of Siliana, where natural factors and the aggressiveness of the environment do affect the loss of soil there, which characterized by a form so uneven with attitudes that vary from 700 to 1350 m rigid going from 5 to 10 pour cent and sometimes more. Moreover, it has drained with a thick hydrographic network. Generally, water erosion depends of the importance and the frequent agent factor of this erosion ( rain and streaming), soil type, the topography and the occupation of soil. The usage of mathematic models has to take on consideration of these parameters. The main objective of this work consist in developing put into affect a geomatic approach of stimulation which aims at estimate in time and space, the impact of the climate, and the soil occupation on the water erosion and the transportation of the sediments diversions into sliding of a small watershed. Locally, this approach allows evaluating the parameters of water erosion of SEAGIS model (USLE/RUSLE) to an extent that is identifies and drowing the emergency areas of intervention in the watershed of Siliana.

Stochastic Still Water Response Model

DEFF Research Database (Denmark)

Friis-Hansen, Peter; Ditlevsen, Ove Dalager

2002-01-01

In this study a stochastic field model for the still water loading is formulated where the statistics (mean value, standard deviation, and correlation) of the sectional forces are obtained by integration of the load field over the relevant part of the ship structure. The objective of the model is...... out that an important parameter of the stochastic cargo field model is the mean number of containers delivered by each customer.......In this study a stochastic field model for the still water loading is formulated where the statistics (mean value, standard deviation, and correlation) of the sectional forces are obtained by integration of the load field over the relevant part of the ship structure. The objective of the model...... is to establish the stochastic load field conditional on a given draft and trim of the vessel. The model contributes to a realistic modelling of the stochastic load processes to be used in a reliability evaluation of the ship hull. Emphasis is given to container vessels. The formulation of the model for obtaining...

Dealing with uncertainty in modeling intermittent water supply

Science.gov (United States)

Lieb, A. M.; Rycroft, C.; Wilkening, J.

2015-12-01

Intermittency in urban water supply affects hundreds of millions of people in cities around the world, impacting water quality and infrastructure. Building on previous work to dynamically model the transient flows in water distribution networks undergoing frequent filling and emptying, we now consider the hydraulic implications of uncertain input data. Water distribution networks undergoing intermittent supply are often poorly mapped, and household metering frequently ranges from patchy to nonexistent. In the face of uncertain pipe material, pipe slope, network connectivity, and outflow, we investigate how uncertainty affects dynamical modeling results. We furthermore identify which parameters exert the greatest influence on uncertainty, helping to prioritize data collection.

Modelling surface-water depression storage in a Prairie Pothole Region

Science.gov (United States)

Hay, Lauren E.; Norton, Parker A.; Viger, Roland; Markstrom, Steven; Regan, R. Steven; Vanderhoof, Melanie

2018-01-01

In this study, the Precipitation-Runoff Modelling System (PRMS) was used to simulate changes in surface-water depression storage in the 1,126-km2 Upper Pipestem Creek basin located within the Prairie Pothole Region of North Dakota, USA. The Prairie Pothole Region is characterized by millions of small water bodies (or surface-water depressions) that provide numerous ecosystem services and are considered an important contribution to the hydrologic cycle. The Upper Pipestem PRMS model was extracted from the U.S. Geological Survey's (USGS) National Hydrologic Model (NHM), developed to support consistent hydrologic modelling across the conterminous United States. The Geospatial Fabric database, created for the USGS NHM, contains hydrologic model parameter values derived from datasets that characterize the physical features of the entire conterminous United States for 109,951 hydrologic response units. Each hydrologic response unit in the Geospatial Fabric was parameterized using aggregated surface-water depression area derived from the National Hydrography Dataset Plus, an integrated suite of application-ready geospatial datasets. This paper presents a calibration strategy for the Upper Pipestem PRMS model that uses normalized lake elevation measurements to calibrate the parameters influencing simulated fractional surface-water depression storage. Results indicate that inclusion of measurements that give an indication of the change in surface-water depression storage in the calibration procedure resulted in accurate changes in surface-water depression storage in the water balance. Regionalized parameterization of the USGS NHM will require a proxy for change in surface-storage to accurately parameterize surface-water depression storage within the USGS NHM.

Hysteresis and uncertainty in soil water-retention curve parameters

Science.gov (United States)

Likos, William J.; Lu, Ning; Godt, Jonathan W.

2014-01-01

Accurate estimates of soil hydraulic parameters representing wetting and drying paths are required for predicting hydraulic and mechanical responses in a large number of applications. A comprehensive suite of laboratory experiments was conducted to measure hysteretic soil-water characteristic curves (SWCCs) representing a wide range of soil types. Results were used to quantitatively assess differences and uncertainty in three simplifications frequently adopted to estimate wetting-path SWCC parameters from more easily measured drying curves. They are the following: (1) αw=2αd, (2) nw=nd, and (3) θws=θds, where α, n, and θs are fitting parameters entering van Genuchten’s commonly adopted SWCC model, and the superscripts w and d indicate wetting and drying paths, respectively. The average ratio αw/αd for the data set was 2.24±1.25. Nominally cohesive soils had a lower αw/αd ratio (1.73±0.94) than nominally cohesionless soils (3.14±1.27). The average nw/nd ratio was 1.01±0.11 with no significant dependency on soil type, thus confirming the nw=nd simplification for a wider range of soil types than previously available. Water content at zero suction during wetting (θws) was consistently less than during drying (θds) owing to air entrapment. The θws/θds ratio averaged 0.85±0.10 and was comparable for nominally cohesive (0.87±0.11) and cohesionless (0.81±0.08) soils. Regression statistics are provided to quantitatively account for uncertainty in estimating hysteretic retention curves. Practical consequences are demonstrated for two case studies.

Robust estimation of hydrological model parameters

Directory of Open Access Journals (Sweden)

A. Bárdossy

2008-11-01

Full Text Available The estimation of hydrological model parameters is a challenging task. With increasing capacity of computational power several complex optimization algorithms have emerged, but none of the algorithms gives a unique and very best parameter vector. The parameters of fitted hydrological models depend upon the input data. The quality of input data cannot be assured as there may be measurement errors for both input and state variables. In this study a methodology has been developed to find a set of robust parameter vectors for a hydrological model. To see the effect of observational error on parameters, stochastically generated synthetic measurement errors were applied to observed discharge and temperature data. With this modified data, the model was calibrated and the effect of measurement errors on parameters was analysed. It was found that the measurement errors have a significant effect on the best performing parameter vector. The erroneous data led to very different optimal parameter vectors. To overcome this problem and to find a set of robust parameter vectors, a geometrical approach based on Tukey's half space depth was used. The depth of the set of N randomly generated parameters was calculated with respect to the set with the best model performance (Nash-Sutclife efficiency was used for this study for each parameter vector. Based on the depth of parameter vectors, one can find a set of robust parameter vectors. The results show that the parameters chosen according to the above criteria have low sensitivity and perform well when transfered to a different time period. The method is demonstrated on the upper Neckar catchment in Germany. The conceptual HBV model was used for this study.

Photovoltaic module parameters acquisition model

Energy Technology Data Exchange (ETDEWEB)

Cibira, Gabriel, E-mail: cibira@lm.uniza.sk; Koščová, Marcela, E-mail: mkoscova@lm.uniza.sk

2014-09-01

Highlights: • Photovoltaic five-parameter model is proposed using Matlab{sup ®} and Simulink. • The model acquisits input sparse data matrix from stigmatic measurement. • Computer simulations lead to continuous I–V and P–V characteristics. • Extrapolated I–V and P–V characteristics are in hand. • The model allows us to predict photovoltaics exploitation in different conditions. - Abstract: This paper presents basic procedures for photovoltaic (PV) module parameters acquisition using MATLAB and Simulink modelling. In first step, MATLAB and Simulink theoretical model are set to calculate I–V and P–V characteristics for PV module based on equivalent electrical circuit. Then, limited I–V data string is obtained from examined PV module using standard measurement equipment at standard irradiation and temperature conditions and stated into MATLAB data matrix as a reference model. Next, the theoretical model is optimized to keep-up with the reference model and to learn its basic parameters relations, over sparse data matrix. Finally, PV module parameters are deliverable for acquisition at different realistic irradiation, temperature conditions as well as series resistance. Besides of output power characteristics and efficiency calculation for PV module or system, proposed model validates computing statistical deviation compared to reference model.

Photovoltaic module parameters acquisition model

International Nuclear Information System (INIS)

Cibira, Gabriel; Koščová, Marcela

2014-01-01

Highlights: • Photovoltaic five-parameter model is proposed using Matlab ® and Simulink. • The model acquisits input sparse data matrix from stigmatic measurement. • Computer simulations lead to continuous I–V and P–V characteristics. • Extrapolated I–V and P–V characteristics are in hand. • The model allows us to predict photovoltaics exploitation in different conditions. - Abstract: This paper presents basic procedures for photovoltaic (PV) module parameters acquisition using MATLAB and Simulink modelling. In first step, MATLAB and Simulink theoretical model are set to calculate I–V and P–V characteristics for PV module based on equivalent electrical circuit. Then, limited I–V data string is obtained from examined PV module using standard measurement equipment at standard irradiation and temperature conditions and stated into MATLAB data matrix as a reference model. Next, the theoretical model is optimized to keep-up with the reference model and to learn its basic parameters relations, over sparse data matrix. Finally, PV module parameters are deliverable for acquisition at different realistic irradiation, temperature conditions as well as series resistance. Besides of output power characteristics and efficiency calculation for PV module or system, proposed model validates computing statistical deviation compared to reference model

Inverse modeling for the determination of hydrogeological parameters of a two-phase system

International Nuclear Information System (INIS)

Finsterle, S.

1993-02-01

Investigations related to the disposal of radioactive wastes in Switzerland consider formations containing natural gas as potential rocks for a repository. Moreover, gas generation in the repository itself may lead to an unsaturated zone of significant extent and impact on the system's performance. The site characterization procedure requires the estimation of hydraulic properties being used as input parameters for a two-phase two-component numerical simulator. In this study, estimates of gas-related formation parameters are obtained by inverse modeling. Based on discrete observations of the system's state, model parameters can be estimated within the framework of a given conceptual model by means of optimization techniques. This study presents the theoretical background that related field data to the model parameters. A parameter estimation procedure is proposed and implemented in a computer code for automatic model calibration. This tool allows identification of key parameters affecting flow of water and gas in porous media. The inverse modeling approach is verified using data from a synthetic laboratory experiment. In addition, the Gas test performed at the Grimsel Test Site is analyzed in order to demonstrate the applicability of the proposed procedure when used with data from a real geologic environment. Estimation of hydrogeologic parameters by automatic model calibration improves the understanding of the two-phase flow processes and therefore increases the reliability of the subsequent simulation runs. (author) figs., tabs., refs

Inverse modeling for the determination of hydrogeological parameters of a two-phase system

International Nuclear Information System (INIS)

Finsterle, S.

1993-01-01

Investigations related to the disposal of radioactive wastes in Switzerland are dealing with formations containing natural gas as potential host rock for a repository. Moreover, gas generation in the repository itself may lead to an unsaturated zone of significant extent and impact on the system's performance. The site characterization procedure requires the estimation of hydraulic properties being used as input parameters for a two-phase two-component numerical simulator. In this study, estimates of gas related formation parameters are obtained by inverse modeling. Based on discrete observations of the system's state, model parameters can be estimated within the framework of a given conceptual model by means of optimization techniques. This study presents the theoretical background that relates field data to the model parameters. A parameter estimation procedure is proposed and implemented in a computer code for automatic model calibration. This tool allows to identify key parameters affecting flow of water and gas in porous media. The inverse modeling approach is verified using data from a synthetic laboratory experiment. In addition, the Gastest performed at the Grimsel Test Site is analyzed in order to demonstrate the applicability of the proposed procedure when used with data from a real geologic environment. Estimation of hydrogeologic parameters by automatic model calibration improves the understanding of the two-phase flow processes and therefore increases the reliability of the subsequent simulation runs. (author) figs., tabs., 100 refs

The use of tritiated water in evaluating animal production parameters

International Nuclear Information System (INIS)

Robertshaw, D.

1988-01-01

Tritiated water (TOH) provides a means of measuring a number of parameters of importance not only to the applied animal physiologist but to those involved in assessing animal productivity. For the examination of animal-environment interactions, TOH is an invaluable tool for assessing total body water, water turnover rate and hence water requirements of different types of animals kept under a variety of climatic and other conditions. It can also be useful for measuring water losses, e.g. through evaporation, and hence is a tool for assessing thermal stress. For animal productivity studies, TOH is useful for assessing such parameters as carcass composition, the intake of forages, supplements and milk. Each of these aspects is described as are the assumptions which have to be made when using TOH for the measurements concerned. (author). 11 refs, 1 tab

Estimating water retention curves and strength properties of unsaturated sandy soils from basic soil gradation parameters

Science.gov (United States)

Wang, Ji-Peng; Hu, Nian; François, Bertrand; Lambert, Pierre

2017-07-01

This study proposed two pedotransfer functions (PTFs) to estimate sandy soil water retention curves. It is based on the van Genuchten's water retention model and from a semiphysical and semistatistical approach. Basic gradation parameters of d60 as particle size at 60% passing and the coefficient of uniformity Cu are employed in the PTFs with two idealized conditions, the monosized scenario and the extremely polydisperse condition, satisfied. Water retention tests are carried out on eight granular materials with narrow particle size distributions as supplementary data of the UNSODA database. The air entry value is expressed as inversely proportional to d60 and the parameter n, which is related to slope of water retention curve, is a function of Cu. The proposed PTFs, although have fewer parameters, have better fitness than previous PTFs for sandy soils. Furthermore, by incorporating with the suction stress definition, the proposed pedotransfer functions are imbedded in shear strength equations which provide a way to estimate capillary induced tensile strength or cohesion at a certain suction or degree of saturation from basic soil gradation parameters. The estimation shows quantitative agreement with experimental data in literature, and it also explains that the capillary-induced cohesion is generally higher for materials with finer mean particle size or higher polydispersity.

Physicochemical parameters and seasonal variation of coastal water from Balochistan coast, Pakistan

Directory of Open Access Journals (Sweden)

Naeema Elahi

2015-03-01

Full Text Available Objective: To determine common physico-chemical parameters of coastal water. Methods: Physicochemical properties of water were determined according to the standards of the American Public Health Association. Generally, all those parameters were recorded a small variation between stations. The variation in physico-chemical parameters like salinity, temperature, dissolved oxygen and pH at Gwadar (Coastal water of Balochistan were recorded. Results: The range of air temperature of coastal water of Balochistan during 2004 and 2006 varies from 25 ºC to 37 ºC, water temperature ranged from 15.00 ºC to 33.00 ºC, pH ranged from 7.08 to 8.95, salinity ranged from 37.4‰ to 41.3‰ and dissolved oxygen ranged from 5.32 to 8.67 mg/L. Conclusions: Results showed that these parameters of Balochistan coast of Pakistan is not dangerous for marine habitat and the use of these parameters in monitoring programs to assess ecosystem health has the potential to inform the general public and decision-makers about the state of the coastal ecosystems. To save this vital important habitat, the government agencies and scientists should work with proper attention.

Hedging Rules for Water Supply Reservoir Based on the Model of Simulation and Optimization

Directory of Open Access Journals (Sweden)

Yi Ji

2016-06-01

Full Text Available This study proposes a hedging rule model which is composed of a two-period reservior operation model considering the damage depth and hedging rule parameter optimization model. The former solves hedging rules based on a given poriod’s water supply weighting factor and carryover storage target, while the latter optimization model is used to optimize the weighting factor and carryover storage target based on the hedging rules. The coupling model gives the optimal poriod’s water supply weighting factor and carryover storage target to guide release. The conclusions achieved from this study as follows: (1 the water supply weighting factor and carryover storage target have a direct impact on the three elements of the hedging rule; (2 parameters can guide reservoirs to supply water reasonably after optimization of the simulation and optimization model; and (3 in order to verify the utility of the hedging rule, the Heiquan reservoir is used as a case study and particle swarm optimization algorithm with a simulation model is adopted for optimizing the parameter. The results show that the proposed hedging rule can improve the operation performances of the water supply reservoir.

Temporal variability and climatology of hydrodynamic, water property and water quality parameters in the West Johor Strait of Singapore

International Nuclear Information System (INIS)

Behera, Manasa Ranjan; Chun, Cui; Palani, Sundarambal; Tkalich, Pavel

2013-01-01

Highlights: • Water temperature is driven by solar radiation and air temperature in the West Johor Strait (WJS). • Salinity in WJS is driven by flood-ebb tide and seasonal variability due to monsoon. • Turbidity is mainly dependent on tidal current and river discharge in WJS. • Chl-a concentration increases with increase in air and water temperature in WJS. • Near-bottom Chl-a concentration in the WJS is high during SW monsoon. -- Abstract: The study presents a baseline variability and climatology study of measured hydrodynamic, water properties and some water quality parameters of West Johor Strait, Singapore at hourly-to-seasonal scales to uncover their dependency and correlation to one or more drivers. The considered parameters include, but not limited by sea surface elevation, current magnitude and direction, solar radiation and air temperature, water temperature, salinity, chlorophyll-a and turbidity. FFT (Fast Fourier Transform) analysis is carried out for the parameters to delineate relative effect of tidal and weather drivers. The group and individual correlations between the parameters are obtained by principal component analysis (PCA) and cross-correlation (CC) technique, respectively. The CC technique also identifies the dependency and time lag between driving natural forces and dependent water property and water quality parameters. The temporal variability and climatology of the driving forces and the dependent parameters are established at the hourly, daily, fortnightly and seasonal scales

Validation of AquaCrop Model for Simulation of Winter Wheat Yield and Water Use Efficiency under Simultaneous Salinity and Water Stress

OpenAIRE

M. Mohammadi; B. Ghahraman; K. Davary; H. Ansari; A. Shahidi

2016-01-01

Introduction: FAO AquaCrop model (Raes et al., 2009a; Steduto et al., 2009) is a user-friendly and practitioner oriented type of model, because it maintains an optimal balance between accuracy, robustness, and simplicity; and it requires a relatively small number of model input parameters. The FAO AquaCrop model predicts crop productivity, water requirement, and water use efficiency under water-limiting and saline water conditions. This model has been tested and validated for different crops ...

Effects of ring-porous and diffuse-porous stem wood anatomy on the hydraulic parameters used in a water flow and storage model.

Science.gov (United States)

Steppe, Kathy; Lemeur, Raoul

2007-01-01

Calibration of a recently developed water flow and storage model based on experimental data for a young diffuse-porous beech tree (Fagus sylvatica L.) and a young ring-porous oak tree (Quercus robur L.) revealed that differences in stem wood anatomy between species strongly affect the calibrated values of the hydraulic model parameters. The hydraulic capacitance (C) of the stem storage tissue was higher in oak than in beech (939.8 versus 212.3 mg MPa(-1)). Model simulation of the elastic modulus (epsilon) revealed that this difference was linked to the higher elasticity of the stem storage tissue of oak compared with beech. Furthermore, the hydraulic resistance (R (x)) of beech was about twice that of oak (0.1829 versus 0.1072 MPa s mg(-1)). To determine the physiological meaning of the R (x) parameter identified by model calibration, we analyzed the stem wood anatomy of the beech and oak trees. Calculation of stem specific hydraulic conductivity (k (s)) of beech and oak with the Hagen-Poiseuille equation confirmed the differences in R (x) predicted by the model. The contributions of different vessel diameter classes to the total hydraulic conductivity of the xylem were calculated. As expected, the few big vessels contributed much more to total conductivity than the many small vessels. Compared with beech, the larger vessels of oak resulted in a higher k (s) (10.66 versus 4.90 kg m(-1) s(-1) MPa(-1)). The calculated ratio of k (s) of oak to beech was 2, confirming the R (x) ratio obtained by model calibration. Thus, validation of the R (x) parameter of the model led to identification of its physiological meaning.

An efficient soil water balance model based on hybrid numerical and statistical methods

Science.gov (United States)

Mao, Wei; Yang, Jinzhong; Zhu, Yan; Ye, Ming; Liu, Zhao; Wu, Jingwei

2018-04-01

Most soil water balance models only consider downward soil water movement driven by gravitational potential, and thus cannot simulate upward soil water movement driven by evapotranspiration especially in agricultural areas. In addition, the models cannot be used for simulating soil water movement in heterogeneous soils, and usually require many empirical parameters. To resolve these problems, this study derives a new one-dimensional water balance model for simulating both downward and upward soil water movement in heterogeneous unsaturated zones. The new model is based on a hybrid of numerical and statistical methods, and only requires four physical parameters. The model uses three governing equations to consider three terms that impact soil water movement, including the advective term driven by gravitational potential, the source/sink term driven by external forces (e.g., evapotranspiration), and the diffusive term driven by matric potential. The three governing equations are solved separately by using the hybrid numerical and statistical methods (e.g., linear regression method) that consider soil heterogeneity. The four soil hydraulic parameters required by the new models are as follows: saturated hydraulic conductivity, saturated water content, field capacity, and residual water content. The strength and weakness of the new model are evaluated by using two published studies, three hypothetical examples and a real-world application. The evaluation is performed by comparing the simulation results of the new model with corresponding results presented in the published studies, obtained using HYDRUS-1D and observation data. The evaluation indicates that the new model is accurate and efficient for simulating upward soil water flow in heterogeneous soils with complex boundary conditions. The new model is used for evaluating different drainage functions, and the square drainage function and the power drainage function are recommended. Computational efficiency of the new

Quasi 3D modelling of water flow in the sandy soil

Science.gov (United States)

Rezaei, Meisam; Seuntjens, Piet; Joris, Ingeborg; Boënne, Wesley; De Pue, Jan; Cornelis, Wim

2016-04-01

Monitoring and modeling tools may improve irrigation strategies in precision agriculture. Spatial interpolation is required for analyzing the effects of soil hydraulic parameters, soil layer thickness and groundwater level on irrigation management using hydrological models at field scale. We used non-invasive soil sensor, a crop growth (LINGRA-N) and a soil hydrological model (Hydrus-1D) to predict soil-water content fluctuations and crop yield in a heterogeneous sandy grassland soil under supplementary irrigation. In the first step, the sensitivity of the soil hydrological model to hydraulic parameters, water stress, crop yield and lower boundary conditions was assessed after integrating models at one soil column. Free drainage and incremental constant head conditions were implemented in a lower boundary sensitivity analysis. In the second step, to predict Ks over the whole field, the spatial distributions of Ks and its relationship between co-located soil ECa measured by a DUALEM-21S sensor were investigated. Measured groundwater levels and soil layer thickness were interpolated using ordinary point kriging (OK) to a 0.5 by 0.5 m in aim of digital elevation maps. In the third step, a quasi 3D modelling approach was conducted using interpolated data as input hydraulic parameter, geometric information and boundary conditions in the integrated model. In addition, three different irrigation scenarios namely current, no irrigation and optimized irrigations were carried out to find out the most efficient irrigation regime. In this approach, detailed field scale maps of soil water stress, water storage and crop yield were produced at each specific time interval to evaluate the best and most efficient distribution of water using standard gun sprinkler irrigation. The results show that the effect of the position of the groundwater level was dominant in soil-water content prediction and associated water stress. A time-dependent sensitivity analysis of the hydraulic

Evaluation of Empirical and Machine Learning Algorithms for Estimation of Coastal Water Quality Parameters

Directory of Open Access Journals (Sweden)

Majid Nazeer

2017-11-01

Full Text Available Coastal waters are one of the most vulnerable resources that require effective monitoring programs. One of the key factors for effective coastal monitoring is the use of remote sensing technologies that significantly capture the spatiotemporal variability of coastal waters. Optical properties of coastal waters are strongly linked to components, such as colored dissolved organic matter (CDOM, chlorophyll-a (Chl-a, and suspended solids (SS concentrations, which are essential for the survival of a coastal ecosystem and usually independent of each other. Thus, developing effective remote sensing models to estimate these important water components based on optical properties of coastal waters is mandatory for a successful coastal monitoring program. This study attempted to evaluate the performance of empirical predictive models (EPM and neural networks (NN-based algorithms to estimate Chl-a and SS concentrations, in the coastal area of Hong Kong. Remotely-sensed data over a 13-year period was used to develop regional and local models to estimate Chl-a and SS over the entire Hong Kong waters and for each water class within the study area, respectively. The accuracy of regional models derived from EPM and NN in estimating Chl-a and SS was 83%, 93%, 78%, and 97%, respectively, whereas the accuracy of local models in estimating Chl-a and SS ranged from 60–94% and 81–94%, respectively. Both the regional and local NN models exhibited a higher performance than those models derived from empirical analysis. Thus, this study suggests using machine learning methods (i.e., NN for the more accurate and efficient routine monitoring of coastal water quality parameters (i.e., Chl-a and SS concentrations over the complex coastal area of Hong Kong and other similar coastal environments.

A System Dynamics Modeling of Water Supply and Demand in Las Vegas Valley

Science.gov (United States)

Parajuli, R.; Kalra, A.; Mastino, L.; Velotta, M.; Ahmad, S.

2017-12-01

The rise in population and change in climate have posed the uncertainties in the balance between supply and demand of water. The current study deals with the water management issues in Las Vegas Valley (LVV) using Stella, a system dynamics modeling software, to model the feedback based relationship between supply and demand parameters. Population parameters were obtained from Center for Business and Economic Research while historical water demand and conservation practices were modeled as per the information provided by local authorities. The water surface elevation of Lake Mead, which is the prime source of water supply to the region, was modeled as the supply side whereas the water demand in LVV was modeled as the demand side. The study was done from the period of 1989 to 2049 with 1989 to 2012 as the historical one and the period from 2013 to 2049 as the future period. This study utilizes Coupled Model Intercomparison Project data sets (2013-2049) (CMIP3&5) to model different future climatic scenarios. The model simulates the past dynamics of supply and demand, and then forecasts the future water budget for the forecasted future population and future climatic conditions. The results can be utilized by the water authorities in understanding the future water status and hence plan suitable conservation policies to allocate future water budget and achieve sustainable water management.

Soil-Related Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

Smith, A. J.

2004-01-01

analysis revises the previous version with the same name (BSC 2003 [DIRS 161239]), which was itself a revision of one titled ''Evaluate Soil/Radionuclide Removal by Erosion and Leaching'' (CRWMS M and O 2001 [DIRS 152517]). In Revision 00 of this report, the data generated were fixed values (i.e., taking no account of uncertainty and variability). Revision 01 (BSC 2003 [DIRS 161239]) incorporated uncertainty and variability into the values for the bulk density, elemental partition coefficients, average annual loss of soil from erosion, resuspension enhancement factor, and field capacity water content. The current revision of this document improves the transparency and traceability of the products without changing the details of the analysis. This analysis report supports the treatment of six of the features, events, and processes (FEPs) applicable to the Yucca Mountain reference biosphere (DTN: MO0407SEPFEPLA.000 [DIRS 170760]). The use of the more recent FEP list in DTN: MO0407SEPFEPLA.000 [DIRS 170760] represents a deviation from the detail provided in the TWP (BSC 2004 [DIRS 169573]), which referenced a previous version of the FEP list. The parameters developed in this report support treatment of these six FEPs addressed in the biosphere model that are listed in Table 1-1. Inclusion and treatment of FEPs in the biosphere model is described in the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460], Section 6.2)

Prediction ofWater Quality Parameters (NO3, CL in Karaj Riverby Usinga Combinationof Wavelet Neural Network, ANN and MLRModels

Directory of Open Access Journals (Sweden)

T. Rajaee

2016-10-01

Full Text Available IntroductionThe water quality is an issue of ongoing concern. Evaluation of the quantity and quality of running waters is considerable in hydro-environmental management.The prediction and control of the quality of Karaj river water, as one of the important needed water supply sources of Tehran, possesses great importance. In this study, Performance of Artificial Neural Network (ANN, Wavelet Neural Network combination (WANN and multi linear regression (MLR models, to predict next month the Nitrate (NO3 and Chloride (CL ions of "gate ofBylaqan sluice" station located in Karaj River has been evaluated. Materials and MethodsIn this research two separate ANN models for prediction of NO3 and CL has been expanded. Each one of the parameters for prediction (NO3 / CL has been put related to the past amounts of the same time series (NO3 / CL and its amounts of Q in past months.From astatisticalperiod of10yearswas usedforthe input of the models. Hence 80% of entire data from (96 initial months of data as training set, next 10% of data (12 months and 10% of the end of time series (terminal 12 months were considered as for validation and test of the models, respectively. In WANNcombination model, the real monthly observed time series of river discharge (Q and mentioned qualityparameters(NO3 / CL were decomposed to some sub-time series at different levels by wavelet analysis.Then the decomposed quality parameters to predict and Q time series were used at different levels as inputs to the ANN technique for predicting one-step-ahead Nitrate and Chloride. These time series play various roles in the original time series and the behavior of each is distinct, so the contribution to the original time series varies from each other. In addition, prediction of high NO3 and CL values greater than mean of data that have great importancewere investigated by the models. The capability of the models was evaluated by Coefficient of Efficiency (E and the Root Mean Square

Water and salt balance modelling to predict the effects of land-use changes in forested catchments. 1. Small catchment water balance model

Science.gov (United States)

Sivapalan, Murugesu; Ruprecht, John K.; Viney, Neil R.

1996-03-01

A long-term water balance model has been developed to predict the hydrological effects of land-use change (especially forest clearing) in small experimental catchments in the south-west of Western Australia. This small catchment model has been used as the building block for the development of a large catchment-scale model, and has also formed the basis for a coupled water and salt balance model, developed to predict the changes in stream salinity resulting from land-use and climate change. The application of the coupled salt and water balance model to predict stream salinities in two small experimental catchments, and the application of the large catchment-scale model to predict changes in water yield in a medium-sized catchment that is being mined for bauxite, are presented in Parts 2 and 3, respectively, of this series of papers.The small catchment model has been designed as a simple, robust, conceptually based model of the basic daily water balance fluxes in forested catchments. The responses of the catchment to rainfall and pan evaporation are conceptualized in terms of three interdependent subsurface stores A, B and F. Store A depicts a near-stream perched aquifer system; B represents a deeper, permanent groundwater system; and F is an intermediate, unsaturated infiltration store. The responses of these stores are characterized by a set of constitutive relations which involves a number of conceptual parameters. These parameters are estimated by calibration by comparing observed and predicted runoff. The model has performed very well in simulations carried out on Salmon and Wights, two small experimental catchments in the Collie River basin in south-west Western Australia. The results from the application of the model to these small catchments are presented in this paper.

On the estimation of water pure compound parameters in association theories

DEFF Research Database (Denmark)

Grenner, Andreas; Kontogeorgis, Georgios; Michelsen, Michael Locht

2007-01-01

Determination of the appropriate number of association sites and estimation of parameters for association (SAFT-type) theories is not a trivial matter. Building further on a recently published manuscript by Clark et al., this work investigates aspects of the parameter estimation for water using t...... different association theories. Their performance for various properties as well as against the results presented earlier is demonstrated.......Determination of the appropriate number of association sites and estimation of parameters for association (SAFT-type) theories is not a trivial matter. Building further on a recently published manuscript by Clark et al., this work investigates aspects of the parameter estimation for water using two...

A sensitivity analysis of a radiological assessment model for Arctic waters

DEFF Research Database (Denmark)

Nielsen, S.P.

1998-01-01

A model based on compartment analysis has been developed to simulate the dispersion of radionuclides in Arctic waters for an assessment of doses to man. The model predicts concentrations of radionuclides in the marine environment and doses to man from a range of exposure pathways. A parameter sen...... scavenging, water-sediment interaction, biological uptake, ice transport and fish migration. Two independent evaluations of the release of radioactivity from dumped nuclear waste in the Kara Sea have been used as source terms for the dose calculations.......A model based on compartment analysis has been developed to simulate the dispersion of radionuclides in Arctic waters for an assessment of doses to man. The model predicts concentrations of radionuclides in the marine environment and doses to man from a range of exposure pathways. A parameter...... sensitivity analysis has identified components of the model that are potentially important contributors to the predictive accuracy of doses to individuals of critical groups as well as to the world population. The components investigated include features associated with water transport and mixing, particle...

Parameter sensitivity and identifiability for a biogeochemical model of hypoxia in the northern Gulf of Mexico

Science.gov (United States)

Local sensitivity analyses and identifiable parameter subsets were used to describe numerical constraints of a hypoxia model for bottom waters of the northern Gulf of Mexico. The sensitivity of state variables differed considerably with parameter changes, although most variables ...

Influence of parameters and light e vironment under the canopy on the fuel moisture estimation model

International Nuclear Information System (INIS)

Tamai, K.; Goto, Y.

2006-01-01

Model parameterization was performed for estimation of the fuel moisture in adjacent plots with different tree species aiming at the mapping of forest fire hazard. One plot was covered with only deciduous species and the other with deciduous and evergreen trees. This model has our constant parameters. Three of them are for the relationship between evaporation and solar radiation. Another parameter is the maximum water content ratio of the litter. All of these parameters depend on the intrinsic drying properties of the litter. The water content ratio of the litter and solar radiation on the forest floor were measured in ach plot for one year. Parameters were fixed with the measured data. Though the parameter values were very different between the two plots, estimated moisture ratios were not so different. It was concluded that litter moisture depends on the microclimate, such as solar radiation, rather than on the intrinsic drying properties of the litter and litter layer

Parameter Identification of the 2-Chlorophenol Oxidation Model Using Improved Differential Search Algorithm

Directory of Open Access Journals (Sweden)

Guang-zhou Chen

2015-01-01

Full Text Available Parameter identification plays a crucial role for simulating and using model. This paper firstly carried out the sensitivity analysis of the 2-chlorophenol oxidation model in supercritical water using the Monte Carlo method. Then, to address the nonlinearity of the model, two improved differential search (DS algorithms were proposed to carry out the parameter identification of the model. One strategy is to adopt the Latin hypercube sampling method to replace the uniform distribution of initial population; the other is to combine DS with simplex method. The results of sensitivity analysis reveal the sensitivity and the degree of difficulty identified for every model parameter. Furthermore, the posteriori probability distribution of parameters and the collaborative relationship between any two parameters can be obtained. To verify the effectiveness of the improved algorithms, the optimization performance of improved DS in kinetic parameter estimation is studied and compared with that of the basic DS algorithm, differential evolution, artificial bee colony optimization, and quantum-behaved particle swarm optimization. And the experimental results demonstrate that the DS with the Latin hypercube sampling method does not present better performance, while the hybrid methods have the advantages of strong global search ability and local search ability and are more effective than the other algorithms.

STUDY OF POND WATER QUALITY BY THE ASSESSMENT OF PHYSICOCHEMICAL PARAMETERS AND WATER QUALITY INDEX

OpenAIRE

Vinod Jena; Satish Dixit; Ravi ShrivastavaSapana Gupta; Sapana Gupta

2013-01-01

Water quality index (WQI) is a dimensionless number that combines multiple water quality factors into a single number by normalizing values to subjective rating curves. Conventionally it has been used for evaluating the quality of water for water resources suchas rivers, streams and lakes, etc. The present work is aimed at assessing the Water Quality Index (W.Q.I) ofpond water and the impact of human activities on it. Physicochemical parameters were monitored for the calculation of W.Q.I for ...

Calibration parameters used to simulate streamflow from application of the Hydrologic Simulation Program-FORTRAN Model (HSPF) to mountainous basins containing coal mines in West Virginia

Science.gov (United States)

Atkins, John T.; Wiley, Jeffrey B.; Paybins, Katherine S.

2005-01-01

This report presents the Hydrologic Simulation Program-FORTRAN Model (HSPF) parameters for eight basins in the coal-mining region of West Virginia. The magnitude and characteristics of model parameters from this study will assist users of HSPF in simulating streamflow at other basins in the coal-mining region of West Virginia. The parameter for nominal capacity of the upper-zone storage, UZSN, increased from south to north. The increase in UZSN with the increase in basin latitude could be due to decreasing slopes, decreasing rockiness of the soils, and increasing soil depths from south to north. A special action was given to the parameter for fraction of ground-water inflow that flows to inactive ground water, DEEPFR. The basis for this special action was related to the seasonal movement of the water table and transpiration from trees. The models were most sensitive to DEEPFR and the parameter for interception storage capacity, CEPSC. The models were also fairly sensitive to the parameter for an index representing the infiltration capacity of the soil, INFILT; the parameter for indicating the behavior of the ground-water recession flow, KVARY; the parameter for the basic ground-water recession rate, AGWRC; the parameter for nominal capacity of the upper zone storage, UZSN; the parameter for the interflow inflow, INTFW; the parameter for the interflow recession constant, IRC; and the parameter for lower zone evapotranspiration, LZETP.

Stochastic model and method of zoning water networks

OpenAIRE

Тевяшев, Андрей Дмитриевич; Матвиенко, Ольга Ивановна

2014-01-01

Water consumption at different time of the day is uneven. The model of steady flow distribution in water-supply networks is calculated for maximum consumption and effectively used in the network design and reconstruction. Quasi-stationary modes, in which the parameters are random variables and vary relative to their mean values are more suitable for operational management and planning of rational network operation modes.Leaks, which sometimes exceed 50 % of the volume of water supplied, are o...

Modeling and Optimization for Management of Intermittent Water Supply

Science.gov (United States)

Lieb, A. M.; Wilkening, J.; Rycroft, C.

2014-12-01

In many urban areas, piped water is supplied only intermittently, as valves direct water to different parts of the water distribution system at different times. The flow is transient, and may transition between free-surface and pressurized, resulting in complex dynamical features with important consequences for water suppliers and users. These consequences include degradation of distribution system components, compromised water quality, and inequitable water availability. The goal of this work is to model the important dynamics and identify operating conditions that mitigate certain negative effects of intermittent water supply. Specifically, we will look at controlling valve parameters occurring as boundary conditions in a network model of transient, transition flow through closed pipes. Gradient-based optimization will be used to find boundary values to minimize pressure gradients and ensure equitable water availability at system endpoints.

Optimizing a Water Simulation based on Wavefront Parameter Optimization

OpenAIRE

Lundgren, Martin

2017-01-01

DICE, a Swedish game company, wanted a more realistic water simulation. Currently, most large scale water simulations used in games are based upon ocean simulation technology. These techniques falter when used in other scenarios, such as coastlines. In order to produce a more realistic simulation, a new one was created based upon the water simulation technique "Wavefront Parameter Interpolation". This technique involves a rather extensive preprocess that enables ocean simulations to have inte...

Zinc Nanoparticles Effect on the Parameters of Water

OpenAIRE

Trumsiņa, E; Kukle, S; Zommere, G

2011-01-01

The article is associated with the detection of metal nanoparticles concentration in water. The main risks associated with the metal covered textile use are metal nanoparticle separation from material in use and maintenance processes, resulting in a threat to living organisms. This article aims to look at options to recognize the presence of zinc oxide nanoparticles in water, applying the GDV electrography method and by analyzing parameters of electrogrammes, distinguish those who respond to ...

Modelling spatial and temporal variations in the water quality of an artificial water reservoir in the semiarid Midwest of Argentina

Energy Technology Data Exchange (ETDEWEB)

Cid, Fabricio D., E-mail: fabricio.cid@gmail.com [Laboratory of Biology ' Prof. E. Caviedes Codelia' , Facultad de Ciencias Humanas, Universidad Nacional de San Luis, San Luis (Argentina); Laboratory of Integrative Biology, Institute for Multidisciplinary Research in Biology (IMIBIO-SL), Consejo Nacional de Investigaciones Cientificas y Tecnicas, San Luis (Argentina); Department of Biochemistry and Biological Sciences, Facultad de Quimica, Bioquimica y Farmacia, Universidad Nacional de San Luis, San Luis (Argentina); Anton, Rosa I. [Department of Analytical Chemistry, Facultad de Quimica, Bioquimica y Farmacia, Universidad Nacional de San Luis, San Luis (Argentina); Pardo, Rafael; Vega, Marisol [Department of Analytical Chemistry, Facultad de Ciencias, Universidad de Valladolid, Valladolid (Spain); Caviedes-Vidal, Enrique [Laboratory of Biology ' Prof. E. Caviedes Codelia' , Facultad de Ciencias Humanas, Universidad Nacional de San Luis, San Luis (Argentina); Laboratory of Integrative Biology, Institute for Multidisciplinary Research in Biology (IMIBIO-SL), Consejo Nacional de Investigaciones Cientificas y Tecnicas, San Luis (Argentina); Department of Biochemistry and Biological Sciences, Facultad de Quimica, Bioquimica y Farmacia, Universidad Nacional de San Luis, San Luis (Argentina)

2011-10-31

Highlights: {yields} Water quality of an Argentinean reservoir has been investigated by N-way PCA. {yields} PARAFAC mode modelled spatial and seasonal variations of water composition. {yields} Two factors related with organic and lead pollution have been identified. {yields} The most polluted areas of the reservoir were located, and polluting sources identified. - Abstract: Temporal and spatial patterns of water quality of an important artificial water reservoir located in the semiarid Midwest of Argentina were investigated using chemometric techniques. Surface water samples were collected at 38 points of the water reservoir during eleven sampling campaigns between October 1998 and June 2000, covering the warm wet season and the cold dry season, and analyzed for dissolved oxygen (DO), conductivity, pH, ammonium, nitrate, nitrite, total dissolved solids (TDS), alkalinity, hardness, bicarbonate, chloride, sulfate, calcium, magnesium, fluoride, sodium, potassium, iron, aluminum, silica, phosphate, sulfide, arsenic, chromium, lead, cadmium, chemical oxygen demand (COD), biochemical oxygen demand (BOD), viable aerobic bacteria (VAB) and total coliform bacteria (TC). Concentrations of lead, ammonium, nitrite and coliforms were higher than the maximum allowable limits for drinking water in a large proportion of the water samples. To obtain a general representation of the spatial and temporal trends of the water quality parameters at the reservoir, the three-dimensional dataset (sampling sites x parameters x sampling campaigns) has been analyzed by matrix augmentation principal component analysis (MA-PCA) and N-way principal component analysis (N-PCA) using Tucker3 and PARAFAC (Parallel Factor Analysis) models. MA-PCA produced a component accounting for the general behavior of parameters associated with organic pollution. The Tucker3 models were not appropriate for modelling the water quality dataset. The two-factor PARAFAC model provided the best picture to understand the

Modelling spatial and temporal variations in the water quality of an artificial water reservoir in the semiarid Midwest of Argentina

International Nuclear Information System (INIS)

Cid, Fabricio D.; Anton, Rosa I.; Pardo, Rafael; Vega, Marisol; Caviedes-Vidal, Enrique

2011-01-01

Highlights: → Water quality of an Argentinean reservoir has been investigated by N-way PCA. → PARAFAC mode modelled spatial and seasonal variations of water composition. → Two factors related with organic and lead pollution have been identified. → The most polluted areas of the reservoir were located, and polluting sources identified. - Abstract: Temporal and spatial patterns of water quality of an important artificial water reservoir located in the semiarid Midwest of Argentina were investigated using chemometric techniques. Surface water samples were collected at 38 points of the water reservoir during eleven sampling campaigns between October 1998 and June 2000, covering the warm wet season and the cold dry season, and analyzed for dissolved oxygen (DO), conductivity, pH, ammonium, nitrate, nitrite, total dissolved solids (TDS), alkalinity, hardness, bicarbonate, chloride, sulfate, calcium, magnesium, fluoride, sodium, potassium, iron, aluminum, silica, phosphate, sulfide, arsenic, chromium, lead, cadmium, chemical oxygen demand (COD), biochemical oxygen demand (BOD), viable aerobic bacteria (VAB) and total coliform bacteria (TC). Concentrations of lead, ammonium, nitrite and coliforms were higher than the maximum allowable limits for drinking water in a large proportion of the water samples. To obtain a general representation of the spatial and temporal trends of the water quality parameters at the reservoir, the three-dimensional dataset (sampling sites x parameters x sampling campaigns) has been analyzed by matrix augmentation principal component analysis (MA-PCA) and N-way principal component analysis (N-PCA) using Tucker3 and PARAFAC (Parallel Factor Analysis) models. MA-PCA produced a component accounting for the general behavior of parameters associated with organic pollution. The Tucker3 models were not appropriate for modelling the water quality dataset. The two-factor PARAFAC model provided the best picture to understand the spatial and

Parameter Estimation of Partial Differential Equation Models.

Science.gov (United States)

Xun, Xiaolei; Cao, Jiguo; Mallick, Bani; Carroll, Raymond J; Maity, Arnab

2013-01-01

Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown, and need to be estimated from the measurements of the dynamic system in the present of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE, and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from LIDAR data.

Contaminant transport in aquifers: improving the determination of model parameters

International Nuclear Information System (INIS)

Sabino, C.V.S.; Moreira, R.M.; Lula, Z.L.; Chausson, Y.; Magalhaes, W.F.; Vianna, M.N.

1998-01-01

Parameters conditioning the migration behavior of cesium and mercury are measured with their tracers 137 Cs and 203 Hg in the laboratory, using both batch and column experiments. Batch tests were used to define the sorption isotherm characteristics. Also investigated were the influences of some test parameters, in particular those due to the volume of water to mass of soil ratio (V/m). A provisional relationship between V/m and the distribution coefficient, K d , has been advanced, and a procedure to estimate K d 's valid for environmental values of the ratio V/m has been suggested. Column tests provided the parameters for a transport model. A major problem to be dealt with in such tests is the collimation of the radioactivity probe. Besides mechanically optimizing the collimator, a deconvolution procedure has been suggested and tested, with statistical criteria, to filter off both noise and spurious tracer signals. Correction procedures for the integrating effect introduced by sampling at the exit of columns have also been developed. These techniques may be helpful in increasing the accuracy required in the measurement of parameters conditioning contaminant migration in soils, thus allowing more reliable predictions based on mathematical model applications. (author)

Physically based model for extracting dual permeability parameters using non-Newtonian fluids

Science.gov (United States)

Abou Najm, M. R.; Basset, C.; Stewart, R. D.; Hauswirth, S.

2017-12-01

Dual permeability models are effective for the assessment of flow and transport in structured soils with two dominant structures. The major challenge to those models remains in the ability to determine appropriate and unique parameters through affordable, simple, and non-destructive methods. This study investigates the use of water and a non-Newtonian fluid in saturated flow experiments to derive physically-based parameters required for improved flow predictions using dual permeability models. We assess the ability of these two fluids to accurately estimate the representative pore sizes in dual-domain soils, by determining the effective pore sizes of macropores and micropores. We developed two sub-models that solve for the effective macropore size assuming either cylindrical (e.g., biological pores) or planar (e.g., shrinkage cracks and fissures) pore geometries, with the micropores assumed to be represented by a single effective radius. Furthermore, the model solves for the percent contribution to flow (wi) corresponding to the representative macro and micro pores. A user-friendly solver was developed to numerically solve the system of equations, given that relevant non-Newtonian viscosity models lack forms conducive to analytical integration. The proposed dual-permeability model is a unique attempt to derive physically based parameters capable of measuring dual hydraulic conductivities, and therefore may be useful in reducing parameter uncertainty and improving hydrologic model predictions.

Pedotransfer functions to estimate water retention parameters of soils in northeastern Brazil

Directory of Open Access Journals (Sweden)

Alexandre Hugo Cezar Barros

2013-04-01

Full Text Available Pedotransfer functions (PTF were developed to estimate the parameters (α, n, θr and θs of the van Genuchten model (1980 to describe soil water retention curves. The data came from various sources, mainly from studies conducted by universities in Northeast Brazil, by the Brazilian Agricultural Research Corporation (Embrapa and by a corporation for the development of the São Francisco and Parnaíba river basins (Codevasf, totaling 786 retention curves, which were divided into two data sets: 85 % for the development of PTFs, and 15 % for testing and validation, considered independent data. Aside from the development of general PTFs for all soils together, specific PTFs were developed for the soil classes Ultisols, Oxisols, Entisols, and Alfisols by multiple regression techniques, using a stepwise procedure (forward and backward to select the best predictors. Two types of PTFs were developed: the first included all predictors (soil density, proportions of sand, silt, clay, and organic matter, and the second only the proportions of sand, silt and clay. The evaluation of adequacy of the PTFs was based on the correlation coefficient (R and Willmott index (d. To evaluate the PTF for the moisture content at specific pressure heads, we used the root mean square error (RMSE. The PTF-predicted retention curve is relatively poor, except for the residual water content. The inclusion of organic matter as a PTF predictor improved the prediction of parameter a of van Genuchten. The performance of soil-class-specific PTFs was not better than of the general PTF. Except for the water content of saturated soil estimated by particle size distribution, the tested models for water content prediction at specific pressure heads proved satisfactory. Predictions of water content at pressure heads more negative than -0.6 m, using a PTF considering particle size distribution, are only slightly lower than those obtained by PTFs including bulk density and organic matter

Soil-Related Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

A. J. Smith

2004-09-09

was defined as AP-SIII.9Q, ''Scientific Analyses''. This analysis revises the previous version with the same name (BSC 2003 [DIRS 161239]), which was itself a revision of one titled ''Evaluate Soil/Radionuclide Removal by Erosion and Leaching'' (CRWMS M&O 2001 [DIRS 152517]). In Revision 00 of this report, the data generated were fixed values (i.e., taking no account of uncertainty and variability). Revision 01 (BSC 2003 [DIRS 161239]) incorporated uncertainty and variability into the values for the bulk density, elemental partition coefficients, average annual loss of soil from erosion, resuspension enhancement factor, and field capacity water content. The current revision of this document improves the transparency and traceability of the products without changing the details of the analysis. This analysis report supports the treatment of six of the features, events, and processes (FEPs) applicable to the Yucca Mountain reference biosphere (DTN: MO0407SEPFEPLA.000 [DIRS 170760]). The use of the more recent FEP list in DTN: MO0407SEPFEPLA.000 [DIRS 170760] represents a deviation from the detail provided in the TWP (BSC 2004 [DIRS 169573]), which referenced a previous version of the FEP list. The parameters developed in this report support treatment of these six FEPs addressed in the biosphere model that are listed in Table 1-1. Inclusion and treatment of FEPs in the biosphere model is described in the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460], Section 6.2).

Electrodialytic desalination of brackish water: determination of optimal experimental parameters using full factorial design

Science.gov (United States)

Gmar, Soumaya; Helali, Nawel; Boubakri, Ali; Sayadi, Ilhem Ben Salah; Tlili, Mohamed; Amor, Mohamed Ben

2017-12-01

The aim of this work is to study the desalination of brackish water by electrodialysis (ED). A two level-three factor (23) full factorial design methodology was used to investigate the influence of different physicochemical parameters on the demineralization rate (DR) and the specific power consumption (SPC). Statistical design determines factors which have the important effects on ED performance and studies all interactions between the considered parameters. Three significant factors were used including applied potential, salt concentration and flow rate. The experimental results and statistical analysis show that applied potential and salt concentration are the main effect for DR as well as for SPC. The effect of interaction between applied potential and salt concentration was observed for SPC. A maximum value of 82.24% was obtained for DR under optimum conditions and the best value of SPC obtained was 5.64 Wh L-1. Empirical regression models were also obtained and used to predict the DR and the SPC profiles with satisfactory results. The process was applied for the treatment of real brackish water using the optimal parameters.

Quality assessment for radiological model parameters

International Nuclear Information System (INIS)

Funtowicz, S.O.

1989-01-01

A prototype framework for representing uncertainties in radiological model parameters is introduced. This follows earlier development in this journal of a corresponding framework for representing uncertainties in radiological data. Refinements and extensions to the earlier framework are needed in order to take account of the additional contextual factors consequent on using data entries to quantify model parameters. The parameter coding can in turn feed in to methods for evaluating uncertainties in calculated model outputs. (author)

Predicted infiltration for sodic/saline soils from reclaimed coastal areas: sensitivity to model parameters.

Science.gov (United States)

Liu, Dongdong; She, Dongli; Yu, Shuang'en; Shao, Guangcheng; Chen, Dan

2014-01-01

This study was conducted to assess the influences of soil surface conditions and initial soil water content on water movement in unsaturated sodic soils of reclaimed coastal areas. Data was collected from column experiments in which two soils from a Chinese coastal area reclaimed in 2007 (Soil A, saline) and 1960 (Soil B, nonsaline) were used, with bulk densities of 1.4 or 1.5 g/cm(3). A 1D-infiltration model was created using a finite difference method and its sensitivity to hydraulic related parameters was tested. The model well simulated the measured data. The results revealed that soil compaction notably affected the water retention of both soils. Model simulations showed that increasing the ponded water depth had little effect on the infiltration process, since the increases in cumulative infiltration and wetting front advancement rate were small. However, the wetting front advancement rate increased and the cumulative infiltration decreased to a greater extent when θ₀ was increased. Soil physical quality was described better by the S parameter than by the saturated hydraulic conductivity since the latter was also affected by the physical chemical effects on clay swelling occurring in the presence of different levels of electrolytes in the soil solutions of the two soils.

Predicted Infiltration for Sodic/Saline Soils from Reclaimed Coastal Areas: Sensitivity to Model Parameters

Directory of Open Access Journals (Sweden)

Dongdong Liu

2014-01-01

Full Text Available This study was conducted to assess the influences of soil surface conditions and initial soil water content on water movement in unsaturated sodic soils of reclaimed coastal areas. Data was collected from column experiments in which two soils from a Chinese coastal area reclaimed in 2007 (Soil A, saline and 1960 (Soil B, nonsaline were used, with bulk densities of 1.4 or 1.5 g/cm3. A 1D-infiltration model was created using a finite difference method and its sensitivity to hydraulic related parameters was tested. The model well simulated the measured data. The results revealed that soil compaction notably affected the water retention of both soils. Model simulations showed that increasing the ponded water depth had little effect on the infiltration process, since the increases in cumulative infiltration and wetting front advancement rate were small. However, the wetting front advancement rate increased and the cumulative infiltration decreased to a greater extent when θ0 was increased. Soil physical quality was described better by the S parameter than by the saturated hydraulic conductivity since the latter was also affected by the physical chemical effects on clay swelling occurring in the presence of different levels of electrolytes in the soil solutions of the two soils.

Accounting for and predicting the influence of spatial autocorrelation in water quality modeling

Science.gov (United States)

Miralha, L.; Kim, D.

2017-12-01

Although many studies have attempted to investigate the spatial trends of water quality, more attention is yet to be paid to the consequences of considering and ignoring the spatial autocorrelation (SAC) that exists in water quality parameters. Several studies have mentioned the importance of accounting for SAC in water quality modeling, as well as the differences in outcomes between models that account for and ignore SAC. However, the capacity to predict the magnitude of such differences is still ambiguous. In this study, we hypothesized that SAC inherently possessed by a response variable (i.e., water quality parameter) influences the outcomes of spatial modeling. We evaluated whether the level of inherent SAC is associated with changes in R-Squared, Akaike Information Criterion (AIC), and residual SAC (rSAC), after accounting for SAC during modeling procedure. The main objective was to analyze if water quality parameters with higher Moran's I values (inherent SAC measure) undergo a greater increase in R² and a greater reduction in both AIC and rSAC. We compared a non-spatial model (OLS) to two spatial regression approaches (spatial lag and error models). Predictor variables were the principal components of topographic (elevation and slope), land cover, and hydrological soil group variables. We acquired these data from federal online sources (e.g. USGS). Ten watersheds were selected, each in a different state of the USA. Results revealed that water quality parameters with higher inherent SAC showed substantial increase in R² and decrease in rSAC after performing spatial regressions. However, AIC values did not show significant changes. Overall, the higher the level of inherent SAC in water quality variables, the greater improvement of model performance. This indicates a linear and direct relationship between the spatial model outcomes (R² and rSAC) and the degree of SAC in each water quality variable. Therefore, our study suggests that the inherent level of

Modeling of radiocesium transport kinetics in system water-aquatic plants

International Nuclear Information System (INIS)

Svadlenkova, M.

1988-01-01

Compartment models were used to describe the kinetics of the transport of radionuclides in the system water-biomass of aquatic plants. Briefly described are linear models and models with time variable parameters. The model was tested using data from a locality in the environs of the Bohunice nuclear power plant. Cladophora glomerata algae were the monitored plants, 137 Cs the monitored radionuclide. The models may be used when aquatic plants serve as bioindicators of the radioactive contamination of surface waters, for monitoring the transport of radionuclides in food chains. (M.D.). 10 refs

Assessing the relative importance of parameter and forcing uncertainty and their interactions in conceptual hydrological model simulations

Science.gov (United States)

Mockler, E. M.; Chun, K. P.; Sapriza-Azuri, G.; Bruen, M.; Wheater, H. S.

2016-11-01

Predictions of river flow dynamics provide vital information for many aspects of water management including water resource planning, climate adaptation, and flood and drought assessments. Many of the subjective choices that modellers make including model and criteria selection can have a significant impact on the magnitude and distribution of the output uncertainty. Hydrological modellers are tasked with understanding and minimising the uncertainty surrounding streamflow predictions before communicating the overall uncertainty to decision makers. Parameter uncertainty in conceptual rainfall-runoff models has been widely investigated, and model structural uncertainty and forcing data have been receiving increasing attention. This study aimed to assess uncertainties in streamflow predictions due to forcing data and the identification of behavioural parameter sets in 31 Irish catchments. By combining stochastic rainfall ensembles and multiple parameter sets for three conceptual rainfall-runoff models, an analysis of variance model was used to decompose the total uncertainty in streamflow simulations into contributions from (i) forcing data, (ii) identification of model parameters and (iii) interactions between the two. The analysis illustrates that, for our subjective choices, hydrological model selection had a greater contribution to overall uncertainty, while performance criteria selection influenced the relative intra-annual uncertainties in streamflow predictions. Uncertainties in streamflow predictions due to the method of determining parameters were relatively lower for wetter catchments, and more evenly distributed throughout the year when the Nash-Sutcliffe Efficiency of logarithmic values of flow (lnNSE) was the evaluation criterion.

Assessment of parameter regionalization methods for modeling flash floods in China

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Ragettli, Silvan; Zhou, Jian; Wang, Haijing

2017-04-01

Rainstorm flash floods are a common and serious phenomenon during the summer months in many hilly and mountainous regions of China. For this study, we develop a modeling strategy for simulating flood events in small river basins of four Chinese provinces (Shanxi, Henan, Beijing, Fujian). The presented research is part of preliminary investigations for the development of a national operational model for predicting and forecasting hydrological extremes in basins of size 10 - 2000 km2, whereas most of these basins are ungauged or poorly gauged. The project is supported by the China Institute of Water Resources and Hydropower Research within the framework of the national initiative for flood prediction and early warning system for mountainous regions in China (research project SHZH-IWHR-73). We use the USGS Precipitation-Runoff Modeling System (PRMS) as implemented in the Java modeling framework Object Modeling System (OMS). PRMS can operate at both daily and storm timescales, switching between the two using a precipitation threshold. This functionality allows the model to perform continuous simulations over several years and to switch to the storm mode to simulate storm response in greater detail. The model was set up for fifteen watersheds for which hourly precipitation and runoff data were available. First, automatic calibration based on the Shuffled Complex Evolution method was applied to different hydrological response unit (HRU) configurations. The Nash-Sutcliffe efficiency (NSE) was used as assessment criteria, whereas only runoff data from storm events were considered. HRU configurations reflect the drainage-basin characteristics and depend on assumptions regarding drainage density and minimum HRU size. We then assessed the sensitivity of optimal parameters to different HRU configurations. Finally, the transferability to other watersheds of optimal model parameters that were not sensitive to HRU configurations was evaluated. Model calibration for the 15

SSDA code to apply data assimilation in soil water flow modeling: Documentation and user manual

Science.gov (United States)

Soil water flow models are based on simplified assumptions about the mechanisms, processes, and parameters of water retention and flow. That causes errors in soil water flow model predictions. Data assimilation (DA) with the ensemble Kalman filter (EnKF) corrects modeling results based on measured s...

Performance assessment model development and parameter acquisition for analysis of the transport of natural radionuclides in a Mediterranean watershed

International Nuclear Information System (INIS)

Agueero, Almudena

2005-01-01

This paper describes the methodology developed to construct a model for predicting the behaviour of the natural radioisotopes of U, Th and Ra in a Mediterranean watershed. The methodology includes the development of the performance assessment model, obtaining water flow and radiological parameters based on experimental data and analysis of results. The model, which accounts for both water flows and mass balances of the radionuclides in a semi-natural environment, provides assessments of radionuclide behaviour in grassland and agricultural soils, rivers and reservoirs, including the processes of radionuclide migration through land and water and interactions between both. From field and laboratory data, it has been possible to obtain parameters for the driving processes considered in the model, water fluxes, source term definition, soil to plant transfer factors and distribution coefficient values. Ranges of parameter values obtained have shown good agreement with published literature data. This general methodological approach was developed to be extended to other radionuclides for the modelling of a biosphere watershed in the context of performance assessment of a High Level Waste (HLW) repository under Mediterranean climate conditions, as well as for forecasting radionuclide transport under similar Mediterranean conditions that will occur in the future in other areas. The application of sensitivity and uncertainty analysis was intended to identify key uncertainties with the aim of setting priorities for future research. The model results for the activity concentration in the reservoir indicate that for 238 U and 230 Th the most relevant parameter is the initial concentrations of the radionuclides in the reservoir sediments. However, for 226 Ra the most important parameter is the precipitation rate over the whole watershed

Real-Time System for Water Modeling and Management

Science.gov (United States)

Lee, J.; Zhao, T.; David, C. H.; Minsker, B.

2012-12-01

Working closely with the Texas Commission on Environmental Quality (TCEQ) and the University of Texas at Austin (UT-Austin), we are developing a real-time system for water modeling and management using advanced cyberinfrastructure, data integration and geospatial visualization, and numerical modeling. The state of Texas suffered a severe drought in 2011 that cost the state $7.62 billion in agricultural losses (crops and livestock). Devastating situations such as this could potentially be avoided with better water modeling and management strategies that incorporate state of the art simulation and digital data integration. The goal of the project is to prototype a near-real-time decision support system for river modeling and management in Texas that can serve as a national and international model to promote more sustainable and resilient water systems. The system uses National Weather Service current and predicted precipitation data as input to the Noah-MP Land Surface model, which forecasts runoff, soil moisture, evapotranspiration, and water table levels given land surface features. These results are then used by a river model called RAPID, along with an error model currently under development at UT-Austin, to forecast stream flows in the rivers. Model forecasts are visualized as a Web application for TCEQ decision makers, who issue water diversion (withdrawal) permits and any needed drought restrictions; permit holders; and reservoir operation managers. Users will be able to adjust model parameters to predict the impacts of alternative curtailment scenarios or weather forecasts. A real-time optimization system under development will help TCEQ to identify optimal curtailment strategies to minimize impacts on permit holders and protect health and safety. To develop the system we have implemented RAPID as a remotely-executed modeling service using the Cyberintegrator workflow system with input data downloaded from the North American Land Data Assimilation System. The

Sensitivity of Calibrated Parameters and Water Resource Estimates on Different Objective Functions and Optimization Algorithms

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Delaram Houshmand Kouchi

2017-05-01

Full Text Available The successful application of hydrological models relies on careful calibration and uncertainty analysis. However, there are many different calibration/uncertainty analysis algorithms, and each could be run with different objective functions. In this paper, we highlight the fact that each combination of optimization algorithm-objective functions may lead to a different set of optimum parameters, while having the same performance; this makes the interpretation of dominant hydrological processes in a watershed highly uncertain. We used three different optimization algorithms (SUFI-2, GLUE, and PSO, and eight different objective functions (R2, bR2, NSE, MNS, RSR, SSQR, KGE, and PBIAS in a SWAT model to calibrate the monthly discharges in two watersheds in Iran. The results show that all three algorithms, using the same objective function, produced acceptable calibration results; however, with significantly different parameter ranges. Similarly, an algorithm using different objective functions also produced acceptable calibration results, but with different parameter ranges. The different calibrated parameter ranges consequently resulted in significantly different water resource estimates. Hence, the parameters and the outputs that they produce in a calibrated model are “conditioned” on the choices of the optimization algorithm and objective function. This adds another level of non-negligible uncertainty to watershed models, calling for more attention and investigation in this area.

Parameter Estimation of Partial Differential Equation Models

KAUST Repository

Xun, Xiaolei

2013-09-01

Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown and need to be estimated from the measurements of the dynamic system in the presence of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from long-range infrared light detection and ranging data. Supplementary materials for this article are available online. © 2013 American Statistical Association.

Parameter Estimation for Thurstone Choice Models

Energy Technology Data Exchange (ETDEWEB)

Vojnovic, Milan [London School of Economics (United Kingdom); Yun, Seyoung [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-04-24

We consider the estimation accuracy of individual strength parameters of a Thurstone choice model when each input observation consists of a choice of one item from a set of two or more items (so called top-1 lists). This model accommodates the well-known choice models such as the Luce choice model for comparison sets of two or more items and the Bradley-Terry model for pair comparisons. We provide a tight characterization of the mean squared error of the maximum likelihood parameter estimator. We also provide similar characterizations for parameter estimators defined by a rank-breaking method, which amounts to deducing one or more pair comparisons from a comparison of two or more items, assuming independence of these pair comparisons, and maximizing a likelihood function derived under these assumptions. We also consider a related binary classification problem where each individual parameter takes value from a set of two possible values and the goal is to correctly classify all items within a prescribed classification error. The results of this paper shed light on how the parameter estimation accuracy depends on given Thurstone choice model and the structure of comparison sets. In particular, we found that for unbiased input comparison sets of a given cardinality, when in expectation each comparison set of given cardinality occurs the same number of times, for a broad class of Thurstone choice models, the mean squared error decreases with the cardinality of comparison sets, but only marginally according to a diminishing returns relation. On the other hand, we found that there exist Thurstone choice models for which the mean squared error of the maximum likelihood parameter estimator can decrease much faster with the cardinality of comparison sets. We report empirical evaluation of some claims and key parameters revealed by theory using both synthetic and real-world input data from some popular sport competitions and online labor platforms.

Chaboche-based cyclic material hardening models for 316 SS–316 SS weld under in-air and pressurized water reactor water conditions

Energy Technology Data Exchange (ETDEWEB)

Mohanty, Subhasish, E-mail: smohanty@anl.gov; Soppet, William K.; Majumdar, Saurindranath; Natesan, Krishnamurti

2016-08-15

Highlights: • 316 SS–316 SS weld cyclically harden/soften while undergoing fatigue loading. • Cyclic hardening/softening creates cycle dependent stress-strain curves. • This necessitate to estimate the cycle dependence of material properties. • Cyclic evolution of Chaboche parameters are estimated under different conditions. - Abstract: This paper discusses a material hardening models for welds made from 316 stainless steel (SS) to 316 SS. The model parameters were estimated from the strain-versus-stress curves obtained from tensile and fatigue tests conducted under different conditions (air at room temperature, air at 300 °C, and primary loop water conditions for a pressurized water reactor). These data were used to check the fatigue cycle dependency of the material hardening parameters (yield stress, parameters related to Chaboche-based linear and nonlinear kinematic hardening models, etc.). The details of the experimental results, material hardening models, and associated calculated results are published in an Argonne report (ANL/LWRS-15/2). This paper summarizes the reported material parameters for 316 SS–316 SS welds and their dependency on fatigue cycles and other test conditions.

A large scale GIS geodatabase of soil parameters supporting the modeling of conservation practice alternatives in the United States

Science.gov (United States)

Water quality modeling requires across-scale support of combined digital soil elements and simulation parameters. This paper presents the unprecedented development of a large spatial scale (1:250,000) ArcGIS geodatabase coverage designed as a functional repository of soil-parameters for modeling an...

Fuzzy logic applied to the modeling of water dynamics in an Oxisol in northeastern Brazil

Directory of Open Access Journals (Sweden)

Antônio Cláudio Marques Afonso

2014-04-01

Full Text Available Modeling of water movement in non-saturated soil usually requires a large number of parameters and variables, such as initial soil water content, saturated water content and saturated hydraulic conductivity, which can be assessed relatively easily. Dimensional flow of water in the soil is usually modeled by a nonlinear partial differential equation, known as the Richards equation. Since this equation cannot be solved analytically in certain cases, one way to approach its solution is by numerical algorithms. The success of numerical models in describing the dynamics of water in the soil is closely related to the accuracy with which the water-physical parameters are determined. That has been a big challenge in the use of numerical models because these parameters are generally difficult to determine since they present great spatial variability in the soil. Therefore, it is necessary to develop and use methods that properly incorporate the uncertainties inherent to water displacement in soils. In this paper, a model based on fuzzy logic is used as an alternative to describe water flow in the vadose zone. This fuzzy model was developed to simulate the displacement of water in a non-vegetated crop soil during the period called the emergency phase. The principle of this model consists of a Mamdani fuzzy rule-based system in which the rules are based on the moisture content of adjacent soil layers. The performances of the results modeled by the fuzzy system were evaluated by the evolution of moisture profiles over time as compared to those obtained in the field. The results obtained through use of the fuzzy model provided satisfactory reproduction of soil moisture profiles.

Geochemical modelling of worst-case leakage scenarios at potential CO2-storage sites - CO2 and saline water contamination of drinking water aquifers

Science.gov (United States)

Szabó, Zsuzsanna; Edit Gál, Nóra; Kun, Éva; Szőcs, Teodóra; Falus, György

2017-04-01

Carbon Capture and Storage is a transitional technology to reduce greenhouse gas emissions and to mitigate climate change. Following the implementation and enforcement of the 2009/31/EC Directive in the Hungarian legislation, the Geological and Geophysical Institute of Hungary is required to evaluate the potential CO2 geological storage structures of the country. Basic assessment of these saline water formations has been already performed and the present goal is to extend the studies to the whole of the storage complex and consider the protection of fresh water aquifers of the neighbouring area even in unlikely scenarios when CO2 injection has a much more regional effect than planned. In this work, worst-case scenarios are modelled to understand the effects of CO2 or saline water leaks into drinking water aquifers. The dissolution of CO2 may significantly change the pH of fresh water which induces mineral dissolution and precipitation in the aquifer and therefore, changes in solution composition and even rock porosity. Mobilization of heavy metals may also be of concern. Brine migration from CO2 reservoir and replacement of fresh water in the shallower aquifer may happen due to pressure increase as a consequence of CO2 injection. The saline water causes changes in solution composition which may also induce mineral reactions. The modelling of the above scenarios has happened at several methodological levels such as equilibrium batch, kinetic batch and kinetic reactive transport simulations. All of these have been performed by PHREEQC using the PHREEQC.DAT thermodynamic database. Kinetic models use equations and kinetic rate parameters from the USGS report of Palandri and Kharaka (2004). Reactive transport modelling also considers estimated fluid flow and dispersivity of the studied formation. Further input parameters are the rock and the original ground water compositions of the aquifers and a range of gas-phase CO2 or brine replacement ratios. Worst-case scenarios

Global modelling of river water quality under climate change

Science.gov (United States)

van Vliet, Michelle T. H.; Franssen, Wietse H. P.; Yearsley, John R.

2017-04-01

Climate change will pose challenges on the quality of freshwater resources for human use and ecosystems for instance by changing the dilution capacity and by affecting the rate of chemical processes in rivers. Here we assess the impacts of climate change and induced streamflow changes on a selection of water quality parameters for river basins globally. We used the Variable Infiltration Capacity (VIC) model and a newly developed global water quality module for salinity, temperature, dissolved oxygen and biochemical oxygen demand. The modelling framework was validated using observed records of streamflow, water temperature, chloride, electrical conductivity, dissolved oxygen and biochemical oxygen demand for 1981-2010. VIC and the water quality module were then forced with an ensemble of bias-corrected General Circulation Model (GCM) output for the representative concentration pathways RCP2.6 and RCP8.5 to study water quality trends and identify critical regions (hotspots) of water quality deterioration for the 21st century.

Measurement of Water Quality Parameters for Before and After Maintenance Service in Water Filter System

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Shaharudin Nuraida

2017-01-01

Full Text Available An adequate supply of safe drinking water is one of major ways to obtain healthy life. Water filter system is one way to improve the water quality. However, to maintain the performance of the system, it need to undergo the maintenance service. This study evaluate the requirement of maintenance service in water filter system. Water quality was measured before and after maintenance service. Parameters measured were pH, turbidity, residual chlorine, nitrate and heavy metals and these parameters were compared with National Drinking Water Quality Standards. Collection of data were involved three housing areas in Johor. The quality of drinking water from water filter system were analysed using pH meter, turbidity meter, DR6000 and Inductively Coupled Plasma-Mass Spectrometer. pH value was increased from 16.4% for before maintenance services to 30.7% for after maintenance service. Increment of removal percentage for turbidity, residual chlorine and nitrate after maintenance were 21.5, 13.6 and 26.7, respectively. This result shows that maintenance service enhance the performance of the system. However, less significant of maintenance service for enhance the removal of heavy metals which the increment of removal percentage in range 0.3 to 9.8. Only aluminium shows percentage removal for after maintenance with 92.8% lower compared to before maintenance service with 95.5%.

A model to predict stream water temperature across the conterminous USA

Science.gov (United States)

Catalina Segura; Peter Caldwell; Ge Sun; Steve McNulty; Yang Zhang

2014-01-01

Stream water temperature (ts) is a critical water quality parameter for aquatic ecosystems. However, ts records are sparse or nonexistent in many river systems. In this work, we present an empirical model to predict ts at the site scale across the USA. The model, derived using data from 171 reference sites selected from the Geospatial Attributes of Gages for Evaluating...

A Budyko-type Model for Human Water Consumption

Science.gov (United States)

Lei, X.; Zhao, J.; Wang, D.; Sivapalan, M.

2017-12-01

With the expansion of human water footprint, water crisis is no longer only a conflict or competition for water between different economic sectors, but also increasingly between human and the environment. In order to describe the emergent dynamics and patterns of the interaction, a theoretical framework that encapsulates the physical and societal controls impacting human water consumption is needed. In traditional hydrology, Budyko-type models are simple but efficient descriptions of vegetation-mediated hydrologic cycle in catchments, i.e., the partitioning of mean annual precipitation into runoff and evapotranspiration. Plant water consumption plays a crucial role in the process. Hypothesized similarities between human-water and vegetation-water interactions, including water demand, constraints and system functioning, give the idea of corresponding Budyko-type framework for human water consumption at the catchment scale. Analogous to variables of Budyko-type models for hydrologic cycle, water demand, water consumption, environmental water use and available water are corresponding to potential evaporation, actual evaporation, runoff and precipitation respectively. Human water consumption data, economic and hydro-meteorological data for 51 human-impacted catchments and 10 major river basins in China are assembled to look for the existence of a Budyko-type relationship for human water consumption, and to seek explanations for the spread in the observed relationship. Guided by this, a Budyko-type analytical model is derived based on application of an optimality principle, that of maximum water benefit. The model derived has the same functional form and mathematical features as those that apply for the original Budyko model. Parameters of the new Budyko-type model for human consumption are linked to economic and social factors. The results of this paper suggest that the functioning of both social and hydrologic subsystems within catchment systems can be explored within

Effects of temporal and spatial resolution of calibration data on integrated hydrologic water quality model identification

Science.gov (United States)

Jiang, Sanyuan; Jomaa, Seifeddine; Büttner, Olaf; Rode, Michael

2014-05-01

Hydrological water quality modeling is increasingly used for investigating runoff and nutrient transport processes as well as watershed management but it is mostly unclear how data availablity determins model identification. In this study, the HYPE (HYdrological Predictions for the Environment) model, which is a process-based, semi-distributed hydrological water quality model, was applied in two different mesoscale catchments (Selke (463 km2) and Weida (99 km2)) located in central Germany to simulate discharge and inorganic nitrogen (IN) transport. PEST and DREAM(ZS) were combined with the HYPE model to conduct parameter calibration and uncertainty analysis. Split-sample test was used for model calibration (1994-1999) and validation (1999-2004). IN concentration and daily IN load were found to be highly correlated with discharge, indicating that IN leaching is mainly controlled by runoff. Both dynamics and balances of water and IN load were well captured with NSE greater than 0.83 during validation period. Multi-objective calibration (calibrating hydrological and water quality parameters simultaneously) was found to outperform step-wise calibration in terms of model robustness. Multi-site calibration was able to improve model performance at internal sites, decrease parameter posterior uncertainty and prediction uncertainty. Nitrogen-process parameters calibrated using continuous daily averages of nitrate-N concentration observations produced better and more robust simulations of IN concentration and load, lower posterior parameter uncertainty and IN concentration prediction uncertainty compared to the calibration against uncontinuous biweekly nitrate-N concentration measurements. Both PEST and DREAM(ZS) are efficient in parameter calibration. However, DREAM(ZS) is more sound in terms of parameter identification and uncertainty analysis than PEST because of its capability to evolve parameter posterior distributions and estimate prediction uncertainty based on global

Automated parameter estimation for biological models using Bayesian statistical model checking.

Science.gov (United States)

Hussain, Faraz; Langmead, Christopher J; Mi, Qi; Dutta-Moscato, Joyeeta; Vodovotz, Yoram; Jha, Sumit K

2015-01-01

Probabilistic models have gained widespread acceptance in the systems biology community as a useful way to represent complex biological systems. Such models are developed using existing knowledge of the structure and dynamics of the system, experimental observations, and inferences drawn from statistical analysis of empirical data. A key bottleneck in building such models is that some system variables cannot be measured experimentally. These variables are incorporated into the model as numerical parameters. Determining values of these parameters that justify existing experiments and provide reliable predictions when model simulations are performed is a key research problem. Using an agent-based model of the dynamics of acute inflammation, we demonstrate a novel parameter estimation algorithm by discovering the amount and schedule of doses of bacterial lipopolysaccharide that guarantee a set of observed clinical outcomes with high probability. We synthesized values of twenty-eight unknown parameters such that the parameterized model instantiated with these parameter values satisfies four specifications describing the dynamic behavior of the model. We have developed a new algorithmic technique for discovering parameters in complex stochastic models of biological systems given behavioral specifications written in a formal mathematical logic. Our algorithm uses Bayesian model checking, sequential hypothesis testing, and stochastic optimization to automatically synthesize parameters of probabilistic biological models.

Integrated Modeling of Groundwater and Surface Water Interactions in a Manmade Wetland

Directory of Open Access Journals (Sweden)

Guobiao Huang Gour-Tsyh Yeh

2012-01-01

Full Text Available A manmade pilot wetland in south Florida, the Everglades Nutrient Removal (ENR project, was modeled with a physics-based integrated approach using WASH123D (Yeh et al. 2006. Storm water is routed into the treatment wetland for phosphorus removal by plant and sediment uptake. It overlies a highly permeable surficial groundwater aquifer. Strong surface water and groundwater interactions are a key component of the hydrologic processes. The site has extensive field measurement and monitoring tools that provide point scale and distributed data on surface water levels, groundwater levels, and the physical range of hydraulic parameters and hydrologic fluxes. Previous hydrologic and hydrodynamic modeling studies have treated seepage losses empirically by some simple regression equations and, only surface water flows are modeled in detail. Several years of operational data are available and were used in model historical matching and validation. The validity of a diffusion wave approximation for two-dimensional overland flow (in the region with very flat topography was also tested. The uniqueness of this modeling study is notable for (1 the point scale and distributed comparison of model results with observed data; (2 model parameters based on available field test data; and (3 water flows in the study area include two-dimensional overland flow, hydraulic structures/levees, three-dimensional subsurface flow and one-dimensional canal flow and their interactions. This study demonstrates the need and the utility of a physics-based modeling approach for strong surface water and groundwater interactions.

Modeling phosphorus in the Lake Allatoona watershed using SWAT: I. Developing phosphorus parameter values.

Science.gov (United States)

Radcliffe, D E; Lin, Z; Risse, L M; Romeis, J J; Jackson, C R

2009-01-01

Lake Allatoona is a large reservoir north of Atlanta, GA, that drains an area of about 2870 km2 scheduled for a phosphorus (P) total maximum daily load (TMDL). The Soil and Water Assessment Tool (SWAT) model has been widely used for watershed-scale modeling of P, but there is little guidance on how to estimate P-related parameters, especially those related to in-stream P processes. In this paper, methods are demonstrated to individually estimate SWAT soil-related P parameters and to collectively estimate P parameters related to stream processes. Stream related parameters were obtained using the nutrient uptake length concept. In a manner similar to experiments conducted by stream ecologists, a small point source is simulated in a headwater sub-basin of the SWAT models, then the in-stream parameter values are adjusted collectively to get an uptake length of P similar to the values measured in the streams in the region. After adjusting the in-stream parameters, the P uptake length estimated in the simulations ranged from 53 to 149 km compared to uptake lengths measured by ecologists in the region of 11 to 85 km. Once the a priori P-related parameter set was developed, the SWAT models of main tributaries to Lake Allatoona were calibrated for daily transport. Models using SWAT P parameters derived from the methods in this paper outperformed models using default parameter values when predicting total P (TP) concentrations in streams during storm events and TP annual loads to Lake Allatoona.

Impact of water temperature and structural parameters on the hydraulic labyrinth-channel emitter performance

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Ahmed I. Al-Amoud

2014-06-01

Full Text Available The effects of water temperature and structural parameters of a labyrinth emitter on drip irrigation hydraulic performance were investigated. The inside structural parameters of the trapezoidal labyrinth emitter include path width (W and length (L, trapezoidal unit numbers (N, height (H, and spacing (S. Laboratory experiments were conducted using five different types of labyrinth-channel emitters (three non-pressure compensating and two pressure-compensating emitters commonly used for subsurface drip irrigation systems. The water temperature effect on the hydraulic characteristics at various operating pressures was recorded and a comparison was made to identify the most effective structural parameter on emitter performance. The pressure compensating emitter flow exponent (x average was 0.014, while non-pressure compensating emitter’s values average was 0.456, indicating that the sensitivity of non-pressure compensating emitters to pressure variation is an obvious characteristic (p<0.001 of this type of emitters. The effects of water temperature on emitter flow rate were insignificant (p>0.05 at various operating pressures, where the flow rate index values for emitters were around one. The effects of water temperature on manufacturer’s coefficient of variation (CV values for all emitters were insignificant (p>0.05. The CV values of the non-pressure compensating emitters were lower than those of pressure compensating emitters. This is typical for most compensating models because they are manufactured with more elements than non-compensating emitters are. The results of regression analysis indicate that N and H are the essential factors (p<0.001 to affect the hydraulic performance.

Parameter and input data uncertainty estimation for the assessment of water resources in two sub-basins of the Limpopo River Basin

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N. Oosthuizen

2018-05-01

Full Text Available The demand for water resources is rapidly growing, placing more strain on access to water and its management. In order to appropriately manage water resources, there is a need to accurately quantify available water resources. Unfortunately, the data required for such assessment are frequently far from sufficient in terms of availability and quality, especially in southern Africa. In this study, the uncertainty related to the estimation of water resources of two sub-basins of the Limpopo River Basin – the Mogalakwena in South Africa and the Shashe shared between Botswana and Zimbabwe – is assessed. Input data (and model parameters are significant sources of uncertainty that should be quantified. In southern Africa water use data are among the most unreliable sources of model input data because available databases generally consist of only licensed information and actual use is generally unknown. The study assesses how these uncertainties impact the estimation of surface water resources of the sub-basins. Data on farm reservoirs and irrigated areas from various sources were collected and used to run the model. Many farm dams and large irrigation areas are located in the upper parts of the Mogalakwena sub-basin. Results indicate that water use uncertainty is small. Nevertheless, the medium to low flows are clearly impacted. The simulated mean monthly flows at the outlet of the Mogalakwena sub-basin were between 22.62 and 24.68 Mm3 per month when incorporating only the uncertainty related to the main physical runoff generating parameters. The range of total predictive uncertainty of the model increased to between 22.15 and 24.99 Mm3 when water use data such as small farm and large reservoirs and irrigation were included. For the Shashe sub-basin incorporating only uncertainty related to the main runoff parameters resulted in mean monthly flows between 11.66 and 14.54 Mm3. The range of predictive uncertainty changed to between 11.66 and 17

Developing the remote sensing-based water environmental model for monitoring alpine river water environment over Plateau cold zone

Science.gov (United States)

You, Y.; Wang, S.; Yang, Q.; Shen, M.; Chen, G.

2017-12-01

Alpine river water environment on the Plateau (such as Tibetan Plateau, China) is a key indicator for water security and environmental security in China. Due to the complex terrain and various surface eco-environment, it is a very difficult to monitor the water environment over the complex land surface of the plateau. The increasing availability of remote sensing techniques with appropriate spatiotemporal resolutions, broad coverage and low costs allows for effective monitoring river water environment on the Plateau, particularly in remote and inaccessible areas where are lack of in situ observations. In this study, we propose a remote sense-based monitoring model by using multi-platform remote sensing data for monitoring alpine river environment. In this study some parameterization methodologies based on satellite remote sensing data and field observations have been proposed for monitoring the water environmental parameters (including chlorophyll-a concentration (Chl-a), water turbidity (WT) or water clarity (SD), total nitrogen (TN), total phosphorus (TP), and total organic carbon (TOC)) over the china's southwest highland rivers, such as the Brahmaputra. First, because most sensors do not collect multiple observations of a target in a single pass, data from multiple orbits or acquisition times may be used, and varying atmospheric and irradiance effects must be reconciled. So based on various types of satellite data, at first we developed the techniques of multi-sensor data correction, atmospheric correction. Second, we also built the inversion spectral database derived from long-term remote sensing data and field sampling data. Then we have studied and developed a high-precision inversion model over the southwest highland river backed by inversion spectral database through using the techniques of multi-sensor remote sensing information optimization and collaboration. Third, take the middle reaches of the Brahmaputra river as the study area, we validated the key

Towards modelling of water inflow into the mantle

Science.gov (United States)

Thielmann, M.; Eichheimer, P.; Golabek, G.

2017-12-01

The transport and storage of water in the mantle significantly affects various material properties of mantle rocks and thus water plays a key role in a variety of geodynamical processes (tectonics, magmatism etc.) Geological and seismological observations suggest different inflow mechanisms of water via the subducting slab like slab bending, thermal cracking and serpentinization (Faccenda et al., 2009; Korenaga, 2017). Most of the previous numerical models do not take different dip angles of the subduction slab and subduction velocities into account, while nature provides two different types of subduction regimes i.e. shallow and deep subduction (Li et al., 2011). To which extent both parameters influence the inflow and outflow of water in the mantle still remains unclear. For the investigation of the inflow and outflow of fluids e.g. water in the mantle, we use high resolution 2D finite element simulations, which allow us to resolve subducted sediments and crustal layers. For this purpose the finite element code MVEP2 (Kaus, 2010), is tested against benchmark results (van Keken et al., 2008). In a first step we reproduced the analytical cornerflow model (Batchelor, 1967) used in the benchmark of van Keken et al.(2008) as well as the steady state temperature field. Further steps consist of successively increasing model complexity, such as the incorporation of hydrogen diffusion, water transport and dehydration reactions. ReferencesBatchelor, G. K. An Introduction to Fluid Dynamics. Cambridge University Press, Cambridge, UK (1967) van Keken, P. E., et al. A community benchmark for subduction zone modeling. Phys. Earth Planet. Int. 171, 187-197 (2008). Faccenda, M., T.V. Gerya, and L. Burlini. Deep slab hydration induced by bending-related variations in tectonic pressure. Nat. Geosci. 2, 790-793 (2009). Korenaga, J. On the extent of mantle hydration caused by plate bending. Earth Planet. Sci. Lett. 457, 1-9 (2017). Li, Z. H., Xu, Z. Q., and T.V. Gerya. Flat versus

Understanding the operational parameters affecting NDMA formation at Advanced Water Treatment Plants.

Science.gov (United States)

Farré, Maria José; Döderer, Katrin; Hearn, Laurence; Poussade, Yvan; Keller, Jurg; Gernjak, Wolfgang

2011-01-30

N-nitrosodimethylamine (NDMA) can be formed when secondary effluents are disinfected by chloramines. By means of bench scale experiments this paper investigates operational parameters than can help Advanced Water Treatment Plants (AWTPs) to reduce the formation of NDMA during the production of high quality recycled water. The formation of NDMA was monitored during a contact time of 24h using dimethylamine as NDMA model precursor and secondary effluent from wastewater treatment plants. The three chloramine disinfection strategies tested were pre-formed and in-line formed monochloramine, and pre-formed dichloramine. Although the latter is not employed on purpose in full-scale applications, it has been suggested as the main contributing chemical generating NDMA during chloramination. After 24h, the NDMA formation decreased in both matrices tested in the order: pre-formed dichloramine>in-line formed monochloramine≫pre-formed monochloramine. The most important parameter to consider for the inhibition of NDMA formation was the length of contact time between disinfectant and wastewater. Formation of NDMA was initially inhibited for up to 6h with concentrations consistently NDMA concentrations were reduced by a factor of 20 by optimizing the disinfection strategy. Copyright © 2010 Elsevier B.V. All rights reserved.

On parameter estimation in deformable models

DEFF Research Database (Denmark)

Fisker, Rune; Carstensen, Jens Michael

1998-01-01

Deformable templates have been intensively studied in image analysis through the last decade, but despite its significance the estimation of model parameters has received little attention. We present a method for supervised and unsupervised model parameter estimation using a general Bayesian form...

Hydraulic modelling of drinking water treatment plant operations

Directory of Open Access Journals (Sweden)

L. C. Rietveld

2009-06-01

Full Text Available The flow through a unit of a drinking water treatment plant is one of the most important parameters in terms of a unit's effectiveness. In the present paper, a new EPAnet library is presented with the typical hydraulic elements for drinking water treatment processes well abstraction, rapid sand filtration and cascade and tower aeration. Using this treatment step library, a hydraulic model was set up, calibrated and validated for the drinking water treatment plant Harderbroek. With the actual valve position and pump speeds, the flows were calculated through the several treatment steps. A case shows the use of the model to calculate the new setpoints for the current frequency converters of the effluent pumps during a filter backwash.

Use of tracer to calibrate water quality models in the river Almendares

International Nuclear Information System (INIS)

Dominguez Catasus, Judith; Borroto Portela, Jorge; Perez Machado, Esperanza; Hernandez Garces, Anel

2003-01-01

The Almendares river, one of the most important water bodies of the Havana City, is very polluted. The analysis of parameters as dissolved oxygen and biochemical oxygen demand is very helpful for the studies aimed to the recovery of the river. There is a growing recognition around the word that the water quality models are very useful tools to plan sanitary strategies for the management of wastewater contamination to predict the effectiveness of control options to improve water quality to desired levels. In the present work, the advective, steady- state Streeter and Phelps model was calibrated and validated to simulate the effect of multiple-point and distributed sources on the carbonaceous oxygen demand and dissolved oxygen. The use of the 99mTc and the Rodamine WT as tracers allowed determining the hydrodynamic parameters necessary for modeling purposes

Estimation of ground water hydraulic parameters

Energy Technology Data Exchange (ETDEWEB)

Hvilshoej, Soeren

1998-11-01

The main objective was to assess field methods to determine ground water hydraulic parameters and to develop and apply new analysis methods to selected field techniques. A field site in Vejen, Denmark, which previously has been intensively investigated on the basis of a large amount of mini slug tests and tracer tests, was chosen for experimental application and evaluation. Particular interest was in analysing partially penetrating pumping tests and a recently proposed single-well dipole test. Three wells were constructed in which partially penetrating pumping tests and multi-level single-well dipole tests were performed. In addition, multi-level slug tests, flow meter tests, gamma-logs, and geologic characterisation of soil samples were carried out. In addition to the three Vejen analyses, data from previously published partially penetrating pumping tests were analysed assuming homogeneous anisotropic aquifer conditions. In the present study methods were developed to analyse partially penetrating pumping tests and multi-level single-well dipole tests based on an inverse numerical model. The obtained horizontal hydraulic conductivities from the partially penetrating pumping tests were in accordance with measurements obtained from multi-level slug tests and mini slug tests. Accordance was also achieved between the anisotropy ratios determined from partially penetrating pumping tests and multi-level single-well dipole tests. It was demonstrated that the partially penetrating pumping test analysed by and inverse numerical model is a very valuable technique that may provide hydraulic information on the storage terms and the vertical distribution of the horizontal and vertical hydraulic conductivity under both confined and unconfined aquifer conditions. (EG) 138 refs.

Parameterization of water vapor using high-resolution GPS data and empirical models

Science.gov (United States)

Ningombam, Shantikumar S.; Jade, Sridevi; Shrungeshwara, T. S.

2018-03-01

The present work evaluates eleven existing empirical models to estimate Precipitable Water Vapor (PWV) over a high-altitude (4500 m amsl), cold-desert environment. These models are tested extensively and used globally to estimate PWV for low altitude sites (below 1000 m amsl). The moist parameters used in the model are: water vapor scale height (Hc), dew point temperature (Td) and water vapor pressure (Es 0). These moist parameters are derived from surface air temperature and relative humidity measured at high temporal resolution from automated weather station. The performance of these models are examined statistically with observed high-resolution GPS (GPSPWV) data over the region (2005-2012). The correlation coefficient (R) between the observed GPSPWV and Model PWV is 0.98 at daily data and varies diurnally from 0.93 to 0.97. Parameterization of moisture parameters were studied in-depth (i.e., 2 h to monthly time scales) using GPSPWV , Td , and Es 0 . The slope of the linear relationships between GPSPWV and Td varies from 0.073°C-1 to 0.106°C-1 (R: 0.83 to 0.97) while GPSPWV and Es 0 varied from 1.688 to 2.209 (R: 0.95 to 0.99) at daily, monthly and diurnal time scales. In addition, the moist parameters for the cold desert, high-altitude environment are examined in-depth at various time scales during 2005-2012.

Complexity, parameter sensitivity and parameter transferability in the modelling of floodplain inundation

Science.gov (United States)

Bates, P. D.; Neal, J. C.; Fewtrell, T. J.

2012-12-01

In this we paper we consider two related questions. First, we address the issue of how much physical complexity is necessary in a model in order to simulate floodplain inundation to within validation data error. This is achieved through development of a single code/multiple physics hydraulic model (LISFLOOD-FP) where different degrees of complexity can be switched on or off. Different configurations of this code are applied to four benchmark test cases, and compared to the results of a number of industry standard models. Second we address the issue of how parameter sensitivity and transferability change with increasing complexity using numerical experiments with models of different physical and geometric intricacy. Hydraulic models are a good example system with which to address such generic modelling questions as: (1) they have a strong physical basis; (2) there is only one set of equations to solve; (3) they require only topography and boundary conditions as input data; and (4) they typically require only a single free parameter, namely boundary friction. In terms of complexity required we show that for the problem of sub-critical floodplain inundation a number of codes of different dimensionality and resolution can be found to fit uncertain model validation data equally well, and that in this situation Occam's razor emerges as a useful logic to guide model selection. We find also find that model skill usually improves more rapidly with increases in model spatial resolution than increases in physical complexity, and that standard approaches to testing hydraulic models against laboratory data or analytical solutions may fail to identify this important fact. Lastly, we find that in benchmark testing studies significant differences can exist between codes with identical numerical solution techniques as a result of auxiliary choices regarding the specifics of model implementation that are frequently unreported by code developers. As a consequence, making sound

Studies on water quality parameters due to operation of PHWR at KAPS

International Nuclear Information System (INIS)

Jha, Mukesh; John, Jaison T.; Joshi, C.P.; Vyas, P.V.; Hegde, A.G.

2005-01-01

The paper elucidates the effect of water quality due to operation of Pressurised Heavy Water Reactor located at Kakrapar as water is the essential commodity for all living beings. It is the main concern in recent times for environmental protection, there is a pressure on all type of industries including nuclear power stations to discharge various types of effluents in such a manner that pollution in surrounding environment is kept to the minimum. Owing the wastewater discharge modes of Kakrapar atomic power station behavior of effluents resulting impact on environment and general public will be guided by the water quality of the aquatic system. To ensure the quality of water, the study of water quality parameters are taken up and the investigated parameters showed no degradation in ecosystem due to the operation of PHWR at KAPS. (author)

Constraining model parameters on remotely sensed evaporation: justification for distribution in ungauged basins?

Directory of Open Access Journals (Sweden)

H. C. Winsemius

2008-12-01

Full Text Available In this study, land surface related parameter distributions of a conceptual semi-distributed hydrological model are constrained by employing time series of satellite-based evaporation estimates during the dry season as explanatory information. The approach has been applied to the ungauged Luangwa river basin (150 000 (km² in Zambia. The information contained in these evaporation estimates imposes compliance of the model with the largest outgoing water balance term, evaporation, and a spatially and temporally realistic depletion of soil moisture within the dry season. The model results in turn provide a better understanding of the information density of remotely sensed evaporation. Model parameters to which evaporation is sensitive, have been spatially distributed on the basis of dominant land cover characteristics. Consequently, their values were conditioned by means of Monte-Carlo sampling and evaluation on satellite evaporation estimates. The results show that behavioural parameter sets for model units with similar land cover are indeed clustered. The clustering reveals hydrologically meaningful signatures in the parameter response surface: wetland-dominated areas (also called dambos show optimal parameter ranges that reflect vegetation with a relatively small unsaturated zone (due to the shallow rooting depth of the vegetation which is easily moisture stressed. The forested areas and highlands show parameter ranges that indicate a much deeper root zone which is more drought resistent. Clustering was consequently used to formulate fuzzy membership functions that can be used to constrain parameter realizations in further calibration. Unrealistic parameter ranges, found for instance in the high unsaturated soil zone values in the highlands may indicate either overestimation of satellite-based evaporation or model structural deficiencies. We believe that in these areas, groundwater uptake into the root zone and lateral movement of

Linear correlation of interfacial tension at water-solvent interface, solubility of water in organic solvents, and SE* scale parameters

International Nuclear Information System (INIS)

Mezhov, E.A.; Khananashvili, N.L.; Shmidt, V.S.

1988-01-01

A linear correlation has been established between the solubility of water in water-immiscible organic solvents and the interfacial tension at the water-solvent interface on the one hand and the parameters of the SE* and π* scales for these solvents on the other hand. This allows us, using the known tabulated SE* or π* parameters for each solvent, to predict the values of the interfacial tension and the solubility of water for the corresponding systems. We have shown that the SE* scale allows us to predict these values more accurately than other known solvent scales, since in contrast to other scales it characterizes solvents found in equilibrium with water

A water quality index model using stepwise regression and neural networks models for the Piabanha River basin in Rio de Janeiro, Brazil

Science.gov (United States)

Villas Boas, M. D.; Olivera, F.; Azevedo, J. S.

2013-12-01

The evaluation of water quality through 'indexes' is widely used in environmental sciences. There are a number of methods available for calculating water quality indexes (WQI), usually based on site-specific parameters. In Brazil, WQI were initially used in the 1970s and were adapted from the methodology developed in association with the National Science Foundation (Brown et al, 1970). Specifically, the WQI 'IQA/SCQA', developed by the Institute of Water Management of Minas Gerais (IGAM), is estimated based on nine parameters: Temperature Range, Biochemical Oxygen Demand, Fecal Coliforms, Nitrate, Phosphate, Turbidity, Dissolved Oxygen, pH and Electrical Conductivity. The goal of this study was to develop a model for calculating the IQA/SCQA, for the Piabanha River basin in the State of Rio de Janeiro (Brazil), using only the parameters measurable by a Multiparameter Water Quality Sonde (MWQS) available in the study area. These parameters are: Dissolved Oxygen, pH and Electrical Conductivity. The use of this model will allow to further the water quality monitoring network in the basin, without requiring significant increases of resources. The water quality measurement with MWQS is less expensive than the laboratory analysis required for the other parameters. The water quality data used in the study were obtained by the Geological Survey of Brazil in partnership with other public institutions (i.e. universities and environmental institutes) as part of the project "Integrated Studies in Experimental and Representative Watersheds". Two models were developed to correlate the values of the three measured parameters and the IQA/SCQA values calculated based on all nine parameters. The results were evaluated according to the following validation statistics: coefficient of determination (R2), Root Mean Square Error (RMSE), Akaike information criterion (AIC) and Final Prediction Error (FPE). The first model was a linear stepwise regression between three independent variables

A linked hydrodynamic and water quality model for the Salton Sea

Science.gov (United States)

Chung, E.G.; Schladow, S.G.; Perez-Losada, J.; Robertson, Dale M.

2008-01-01

A linked hydrodynamic and water quality model was developed and applied to the Salton Sea. The hydrodynamic component is based on the one-dimensional numerical model, DLM. The water quality model is based on a new conceptual model for nutrient cycling in the Sea, and simulates temperature, total suspended sediment concentration, nutrient concentrations, including PO4-3, NO3-1 and NH4+1, DO concentration and chlorophyll a concentration as functions of depth and time. Existing water temperature data from 1997 were used to verify that the model could accurately represent the onset and breakup of thermal stratification. 1999 is the only year with a near-complete dataset for water quality variables for the Salton Sea. The linked hydrodynamic and water quality model was run for 1999, and by adjustment of rate coefficients and other water quality parameters, a good match with the data was obtained. In this article, the model is fully described and the model results for reductions in external phosphorus load on chlorophyll a distribution are presented. ?? 2008 Springer Science+Business Media B.V.

Modeling Water Containing Systems with the Simplified PC-SAFT and CPA Equations of State

DEFF Research Database (Denmark)

Liang, Xiaodong; Tsivintzelis, Ioannis; Kontogeorgis, Georgios M.

2014-01-01

of them fail to describe second-order derivative properties of water, i.e., residual isochoric heat capacity and speed of sound. The ability of the models to predict the monomer (free site) fractions of saturated pure water is investigated and discussed from various aspects. The results suggest that more......Numerous studies have been presented for modeling of water containing systems with the perturbed-chain statistical associating fluid theory (PC-SAFT) equation of state (EOS), and more than 20 water parameter sets have been published with emphasis on different applications. In this work, eight...... of these sets and new estimated parameters with different association schemes are systematically compared on describing properties of pure water, the liquid-liquid equilibria (LLE) of water with hydrocarbons, and the vapor-liquid (VLE) and/or vapor-liquid-liquid equilibria (VLLE) of water with 1-alcohols...

Using genetic algorithms to calibrate a water quality model.

Science.gov (United States)

Liu, Shuming; Butler, David; Brazier, Richard; Heathwaite, Louise; Khu, Soon-Thiam

2007-03-15

With the increasing concern over the impact of diffuse pollution on water bodies, many diffuse pollution models have been developed in the last two decades. A common obstacle in using such models is how to determine the values of the model parameters. This is especially true when a model has a large number of parameters, which makes a full range of calibration expensive in terms of computing time. Compared with conventional optimisation approaches, soft computing techniques often have a faster convergence speed and are more efficient for global optimum searches. This paper presents an attempt to calibrate a diffuse pollution model using a genetic algorithm (GA). Designed to simulate the export of phosphorus from diffuse sources (agricultural land) and point sources (human), the Phosphorus Indicators Tool (PIT) version 1.1, on which this paper is based, consisted of 78 parameters. Previous studies have indicated the difficulty of full range model calibration due to the number of parameters involved. In this paper, a GA was employed to carry out the model calibration in which all parameters were involved. A sensitivity analysis was also performed to investigate the impact of operators in the GA on its effectiveness in optimum searching. The calibration yielded satisfactory results and required reasonable computing time. The application of the PIT model to the Windrush catchment with optimum parameter values was demonstrated. The annual P loss was predicted as 4.4 kg P/ha/yr, which showed a good fitness to the observed value.

Stochastic estimation approach for the evaluation of thermal-hydraulic parameters in pressurized water reactors

International Nuclear Information System (INIS)

Shieh, D.J.; Upadhyaya, M.G.

1986-01-01

A method based on the extended Kalman filter is developed for the estimation of the core coolant mass flow rate in pressurized water reactors. The need for flow calibration can be avoided by a direct estimation of this parameter. A reduced-order neutronic and thermal-hydraulic model is developed for the Loss-of-Fluid Test (LOFT) reactor. The neutron detector and core-exit coolant temperature signals from the LOFT reactor are used as measurements in the parameter estimation algorithm. The estimation sensitivity to model uncertainties was evaluated using the ambiguity function analysis. This also provides a lower bound on the measurement sample size necessary to achieve a certain estimation accuracy. A sequential technique was developed to minimize the computational effort needed to discretize the continuous time equations, and thus achieve faster convergence to the true parameter value. The performance of the stochastic approximation method was first evaluated using simulated random data, and then applied to the estimation of coolant flow rate using the operational data from the LOFT reactor at 100 and 65% flow rate conditions

Publishing and sharing of hydrologic models through WaterHUB

Science.gov (United States)

Merwade, V.; Ruddell, B. L.; Song, C.; Zhao, L.; Kim, J.; Assi, A.

2011-12-01

Most hydrologists use hydrologic models to simulate the hydrologic processes to understand hydrologic pathways and fluxes for research, decision making and engineering design. Once these tasks are complete including publication of results, the models generally are not published or made available to the public for further use and improvement. Although publication or sharing of models is not required for journal publications, sharing of models may open doors for new collaborations, and avoids duplication of efforts if other researchers are interested in simulating a particular watershed for which a model already exists. For researchers, who are interested in sharing models, there are limited avenues to publishing their models to the wider community. Towards filling this gap, a prototype cyberinfrastructure (CI), called WaterHUB, is developed for sharing hydrologic data and modeling tools in an interactive environment. To test the utility of WaterHUB for sharing hydrologic models, a system to publish and share SWAT (Soil Water Assessment Tool) is developed. Users can utilize WaterHUB to search and download existing SWAT models, and also upload new SWAT models. Metadata such as the name of the watershed, name of the person or agency who developed the model, simulation period, time step, and list of calibrated parameters also published with individual model.

A scale model to evaluate water evaporation from indoor swimming pools

Energy Technology Data Exchange (ETDEWEB)

Asdrubali, F. [Department of Industrial Engineering, University of Perugia, Via G. Duranti 67, 06125 Perugia (Italy)

2009-03-15

The evaluation of water evaporation from indoor swimming pools is a topic of considerable practical interest, since evaporation may cause the highest energy consumption of the pool plant. A purposely designed experimental apparatus was used to measure the water evaporation rate from a pool scale model inserted into a climatic chamber to control environmental conditions. The experimental data were obtained varying various parameters such as water temperature, air temperature, relative humidity and air velocity. The results were used to propose a prediction model for water evaporation which was compared to other methods found in the literature, showing a good agreement. (author)

Inorganic chemical quality of European tap-water: 1. Distribution of parameters and regulatory compliance

International Nuclear Information System (INIS)

Banks, David; Birke, Manfred; Flem, Belinda; Reimann, Clemens

2015-01-01

Highlights: • A pan-European survey comprises >60 inorganic parameters in 579 tap water samples. • Compliance with standards for inorganic parameters is good (>99% in EU states). • Around 1% non-compliance is observed for arsenic and 0.2% for uranium. • No sample of water contained nitrate in excess of 45 mg/L. • A weak co-variation in Cu and Pb could indicate derivation from plumbing. - Abstract: 579 tap water samples were collected at the European scale and analysed in a single laboratory for more than 60 parameters. This dataset is evaluated here in terms of the statistical distribution of the analysed parameters and compliance with EU and international drinking water regulations. For most parameters a 99% (or better) degree of compliance was achieved. Among the parameters with the higher rates of non-compliance are: arsenic (1% non-compliance in EU member states, 1.6% when samples from non-EU states are also considered) and sodium (0.6%/1.0%). The decision by the WHO to raise its provisional guideline from 15 μg/L (WHO, 2004) to 30 μg/L (WHO, 2011) has reduced non-compliance for uranium from 1.0% to 0.2%. Despite the fact that tap water (i.e. presumed treated water) was collected, many observations can still be interpreted in terms of hydrogeochemical processes. The dataset demonstrates the potential value of very cost-effective, low-density sampling approaches at a continental (European) scale

A survey of indicator parameters to monitor regrowth in unchlorinated drinking water

NARCIS (Netherlands)

Wielen, P.W.J.J. van der; Bakker, G.; Atsma, A.; Lut, M.; Roeselers, G.; Graaf, B. de

2016-01-01

The objective of our study was to explore microbiological parameters that are suitable as indicators for regrowth in distribution systems that receive unchlorinated drinking water in the Netherlands. Treated water and distributed water at two locations in the distribution system of 28 treatment

Application of a Linear Input/Output Model to Tankless Water Heaters

Energy Technology Data Exchange (ETDEWEB)

Butcher T.; Schoenbauer, B.

2011-12-31

In this study, the applicability of a linear input/output model to gas-fired, tankless water heaters has been evaluated. This simple model assumes that the relationship between input and output, averaged over both active draw and idle periods, is linear. This approach is being applied to boilers in other studies and offers the potential to make a small number of simple measurements to obtain the model parameters. These parameters can then be used to predict performance under complex load patterns. Both condensing and non-condensing water heaters have been tested under a very wide range of load conditions. It is shown that this approach can be used to reproduce performance metrics, such as the energy factor, and can be used to evaluate the impacts of alternative draw patterns and conditions.

Isotope effects in the evaporation of water: a status report of the Craig-Gordon model.

Science.gov (United States)

Horita, Juske; Rozanski, Kazimierz; Cohen, Shabtai

2008-03-01

The Craig-Gordon model (C-G model) [H. Craig, L.I. Gordon. Deuterium and oxygen 18 variations in the ocean and the marine atmosphere. In Stable Isotopes in Oceanographic Studies and Paleotemperatures, E. Tongiorgi (Ed.), pp. 9-130, Laboratorio di Geologia Nucleare, Pisa (1965).] has been synonymous with the isotope effects associated with the evaporation of water from surface waters, soils, and vegetations, which in turn constitutes a critical component of the global water cycle. On the occasion of the four decades of its successful applications to isotope geochemistry and hydrology, an attempt is made to: (a) examine its physical background within the framework of modern evaporation models, (b) evaluate our current knowledge of the environmental parameters of the C-G model, and (c) comment on a general strategy for the use of these parameters in field applications. Despite its simplistic representation of evaporation processes at the water-air interface, the C-G model appears to be adequate to provide the isotopic composition of the evaporation flux. This is largely due to its nature for representing isotopic compositions (a ratio of two fluxes of different isotopic water molecules) under the same environmental conditions. Among many environmental parameters that are included in the C-G model, accurate description and calculations are still problematic of the kinetic isotope effects that occur in a diffusion-dominated thin layer of air next to the water-air interface. In field applications, it is of importance to accurately evaluate several environmental parameters, particularly the relative humidity and isotopic compositions of the 'free-atmosphere', for a system under investigation over a given time-scale of interest (e.g., hourly to daily to seasonally). With a growing interest in the studies of water cycles of different spatial and temporal scales, including paleoclimate and water resource studies, the importance and utility of the C-G model is also likely to

Universally sloppy parameter sensitivities in systems biology models.

Directory of Open Access Journals (Sweden)

Ryan N Gutenkunst

2007-10-01

Full Text Available Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

Universally sloppy parameter sensitivities in systems biology models.

Science.gov (United States)

Gutenkunst, Ryan N; Waterfall, Joshua J; Casey, Fergal P; Brown, Kevin S; Myers, Christopher R; Sethna, James P

2007-10-01

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models.

Directory of Open Access Journals (Sweden)

Jonathan R Karr

2015-05-01

Full Text Available Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model's structure and in silico "experimental" data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation.

Parameter optimization, sensitivity, and uncertainty analysis of an ecosystem model at a forest flux tower site in the United States

Science.gov (United States)

Wu, Yiping; Liu, Shuguang; Huang, Zhihong; Yan, Wende

2014-01-01

Ecosystem models are useful tools for understanding ecological processes and for sustainable management of resources. In biogeochemical field, numerical models have been widely used for investigating carbon dynamics under global changes from site to regional and global scales. However, it is still challenging to optimize parameters and estimate parameterization uncertainty for complex process-based models such as the Erosion Deposition Carbon Model (EDCM), a modified version of CENTURY, that consider carbon, water, and nutrient cycles of ecosystems. This study was designed to conduct the parameter identifiability, optimization, sensitivity, and uncertainty analysis of EDCM using our developed EDCM-Auto, which incorporated a comprehensive R package—Flexible Modeling Framework (FME) and the Shuffled Complex Evolution (SCE) algorithm. Using a forest flux tower site as a case study, we implemented a comprehensive modeling analysis involving nine parameters and four target variables (carbon and water fluxes) with their corresponding measurements based on the eddy covariance technique. The local sensitivity analysis shows that the plant production-related parameters (e.g., PPDF1 and PRDX) are most sensitive to the model cost function. Both SCE and FME are comparable and performed well in deriving the optimal parameter set with satisfactory simulations of target variables. Global sensitivity and uncertainty analysis indicate that the parameter uncertainty and the resulting output uncertainty can be quantified, and that the magnitude of parameter-uncertainty effects depends on variables and seasons. This study also demonstrates that using the cutting-edge R functions such as FME can be feasible and attractive for conducting comprehensive parameter analysis for ecosystem modeling.

Research on physical and chemical parameters of coolant in Light-Water Reactors

Energy Technology Data Exchange (ETDEWEB)

Reis, Isabela C.; Mesquita, Amir Z., E-mail: icr@cdtn.br, E-mail: amir@cdtn.br [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN/CNEM-MG), Belo Horizonte, MG (Brazil)

2015-07-01

The coolant radiochemical monitoring of light-water reactors, both power reactor as research reactors is one most important tasks of the system safe operation. The last years have increased the interest in the coolant chemical studying to optimize the process, to minimize the corrosion, to ensure the primary system materials integrity, and to reduce the workers exposure radiation. This paper has the objective to present the development project in Nuclear Technology Development Center (CDTN), which aims to simulate the primary water physical-chemical parameters of light-water-reactors (LWR). Among these parameters may be cited: the temperature, the pressure, the pH, the electric conductivity, and the boron concentration. It is also being studied the adverse effects that these parameters can result in the reactor integrity. The project also aims the mounting of a system to control and monitoring of temperature, electric conductivity, and pH of water in the Installation of Test in Accident Conditions (ITCA), located in the Thermal-Hydraulic Laboratory at CDTN. This facility was widely used in the years 80/90 for commissioning of several components that were installed in Angra 2 containment. In the test, the coolant must reproduce the physical and chemical conditions of the primary. It is therefore fundamental knowledge of the main control parameters of the primary cooling water from PWR reactors. Therefore, this work is contributing, with the knowledge and the reproduction with larger faithfulness of the reactors coolant in the experimental circuits. (author)

Scaling up watershed model parameters--Flow and load simulations of the Edisto River Basin

Science.gov (United States)

Feaster, Toby D.; Benedict, Stephen T.; Clark, Jimmy M.; Bradley, Paul M.; Conrads, Paul

2014-01-01

The Edisto River is the longest and largest river system completely contained in South Carolina and is one of the longest free flowing blackwater rivers in the United States. The Edisto River basin also has fish-tissue mercury concentrations that are some of the highest recorded in the United States. As part of an effort by the U.S. Geological Survey to expand the understanding of relations among hydrologic, geochemical, and ecological processes that affect fish-tissue mercury concentrations within the Edisto River basin, analyses and simulations of the hydrology of the Edisto River basin were made with the topography-based hydrological model (TOPMODEL). The potential for scaling up a previous application of TOPMODEL for the McTier Creek watershed, which is a small headwater catchment to the Edisto River basin, was assessed. Scaling up was done in a step-wise process beginning with applying the calibration parameters, meteorological data, and topographic wetness index data from the McTier Creek TOPMODEL to the Edisto River TOPMODEL. Additional changes were made with subsequent simulations culminating in the best simulation, which included meteorological and topographic wetness index data from the Edisto River basin and updated calibration parameters for some of the TOPMODEL calibration parameters. Comparison of goodness-of-fit statistics between measured and simulated daily mean streamflow for the two models showed that with calibration, the Edisto River TOPMODEL produced slightly better results than the McTier Creek model, despite the significant difference in the drainage-area size at the outlet locations for the two models (30.7 and 2,725 square miles, respectively). Along with the TOPMODEL hydrologic simulations, a visualization tool (the Edisto River Data Viewer) was developed to help assess trends and influencing variables in the stream ecosystem. Incorporated into the visualization tool were the water-quality load models TOPLOAD, TOPLOAD-H, and LOADEST

A parsimonious dynamic model for river water quality assessment.

Science.gov (United States)

Mannina, Giorgio; Viviani, Gaspare

2010-01-01

Water quality modelling is of crucial importance for the assessment of physical, chemical, and biological changes in water bodies. Mathematical approaches to water modelling have become more prevalent over recent years. Different model types ranging from detailed physical models to simplified conceptual models are available. Actually, a possible middle ground between detailed and simplified models may be parsimonious models that represent the simplest approach that fits the application. The appropriate modelling approach depends on the research goal as well as on data available for correct model application. When there is inadequate data, it is mandatory to focus on a simple river water quality model rather than detailed ones. The study presents a parsimonious river water quality model to evaluate the propagation of pollutants in natural rivers. The model is made up of two sub-models: a quantity one and a quality one. The model employs a river schematisation that considers different stretches according to the geometric characteristics and to the gradient of the river bed. Each stretch is represented with a conceptual model of a series of linear channels and reservoirs. The channels determine the delay in the pollution wave and the reservoirs cause its dispersion. To assess the river water quality, the model employs four state variables: DO, BOD, NH(4), and NO. The model was applied to the Savena River (Italy), which is the focus of a European-financed project in which quantity and quality data were gathered. A sensitivity analysis of the model output to the model input or parameters was done based on the Generalised Likelihood Uncertainty Estimation methodology. The results demonstrate the suitability of such a model as a tool for river water quality management.

Analysis of ex-vessel melt jet breakup and coolability. Part 1: Sensitivity on model parameters and accident conditions

Energy Technology Data Exchange (ETDEWEB)

Moriyama, Kiyofumi; Park, Hyun Sun, E-mail: hejsunny@postech.ac.kr; Hwang, Byoungcheol; Jung, Woo Hyun

2016-06-15

Highlights: • Application of JASMINE code to melt jet breakup and coolability in APR1400 condition. • Coolability indexes for quasi steady state breakup and cooling process. • Typical case in complete breakup/solidification, film boiling quench not reached. • Significant impact of water depth and melt jet size; weak impact of model parameters. - Abstract: The breakup of a melt jet falling in a water pool and the coolability of the melt particles produced by such jet breakup are important phenomena in terms of the mitigation of severe accident consequences in light water reactors, because the molten and relocated core material is the primary heat source that governs the accident progression. We applied a modified version of the fuel–coolant interaction simulation code, JASMINE, developed at Japan Atomic Energy Agency (JAEA) to a plant scale simulation of melt jet breakup and cooling assuming an ex-vessel condition in the APR1400, a Korean advanced pressurized water reactor. Also, we examined the sensitivity on seven model parameters and five initial/boundary condition variables. The results showed that the melt cooling performance of a 6 m deep water pool in the reactor cavity is enough for removing the initial melt enthalpy for solidification, for a melt jet of 0.2 m initial diameter. The impacts of the model parameters were relatively weak and that of some of the initial/boundary condition variables, namely the water depth and melt jet diameter, were very strong. The present model indicated that a significant fraction of the melt jet is not broken up and forms a continuous melt pool on the containment floor in cases with a large melt jet diameter, 0.5 m, or a shallow water pool depth, ≤3 m.

Systematic parameter inference in stochastic mesoscopic modeling

Energy Technology Data Exchange (ETDEWEB)

Lei, Huan; Yang, Xiu [Pacific Northwest National Laboratory, Richland, WA 99352 (United States); Li, Zhen [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States); Karniadakis, George Em, E-mail: george_karniadakis@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States)

2017-02-01

We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the prior knowledge that the coefficients are “sparse”. The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space. Fully access to the response surfaces within the confidence range enables us to infer the optimal force parameters given the desirable values of target properties at the macroscopic scale. Moreover, it enables us to investigate the intrinsic relationship between the model parameters, identify possible degeneracies in the parameter space, and optimize the model by eliminating model redundancies. The proposed method provides an efficient alternative approach for constructing mesoscopic models by inferring model parameters to recover target properties of the physics systems (e.g., from experimental measurements), where those force field parameters and formulation cannot be derived from the microscopic level in a straight forward way.

Integrating retention soil filters into urban hydrologic models - Relevant processes and important parameters

Science.gov (United States)

Bachmann-Machnik, Anna; Meyer, Daniel; Waldhoff, Axel; Fuchs, Stephan; Dittmer, Ulrich

2018-04-01

Retention Soil Filters (RSFs), a form of vertical flow constructed wetlands specifically designed for combined sewer overflow (CSO) treatment, have proven to be an effective tool to mitigate negative impacts of CSOs on receiving water bodies. Long-term hydrologic simulations are used to predict the emissions from urban drainage systems during planning of stormwater management measures. So far no universally accepted model for RSF simulation exists. When simulating hydraulics and water quality in RSFs, an appropriate level of detail must be chosen for reasonable balancing between model complexity and model handling, considering the model input's level of uncertainty. The most crucial parameters determining the resultant uncertainties of the integrated sewer system and filter bed model were identified by evaluating a virtual drainage system with a Retention Soil Filter for CSO treatment. To determine reasonable parameter ranges for RSF simulations, data of 207 events from six full-scale RSF plants in Germany were analyzed. Data evaluation shows that even though different plants with varying loading and operation modes were examined, a simple model is sufficient to assess relevant suspended solids (SS), chemical oxygen demand (COD) and NH4 emissions from RSFs. Two conceptual RSF models with different degrees of complexity were assessed. These models were developed based on evaluation of data from full scale RSF plants and column experiments. Incorporated model processes are ammonium adsorption in the filter layer and degradation during subsequent dry weather period, filtration of SS and particulate COD (XCOD) to a constant background concentration and removal of solute COD (SCOD) by a constant removal rate during filter passage as well as sedimentation of SS and XCOD in the filter overflow. XCOD, SS and ammonium loads as well as ammonium concentration peaks are discharged primarily via RSF overflow not passing through the filter bed. Uncertainties of the integrated

Criticality parameters for uranyl nitrate or plutonium nitrate systems in tributyl phosphate/kerosine and water

International Nuclear Information System (INIS)

Weber, W.

1985-01-01

This report presents the calculated values of smallest critical masses and volumina and neutron physical parameters for uranyl nitrate (3, 4, 5% U-235) or plutonium nitrate (5% Pu-240), each in a 30 per cent solution of tributyl phosphate (TBP)/kerosine. For the corresponding nitrate-water solutions, newly calculated results are presented together with a revised solution density model. A comparison of the data shows to what extent the criticality of nitrate-TBP/kerosine systems can be assessed on the basis of nitrate-water parameters, revealing that such data can be applied to uranyl nitrate/water systems, taking into account that the smallest critical mass of uranyl nitrate-TBP/kerosine systems, up to a 5 p.c. U-235 enrichment, is by 4.5 p.c. at the most smaller than that of UNH-water solutions. Plutonium nitrate (5% Pu-240) in the TBP/kerosine solution will have a smallest critical mass of up to 7 p.c. smaller, as compared with the water data. The suitability of the computing methods and cross-sections used is verified by recalculating experiments carried out to determine the lowest critical enrichment of uranyl nitrate. The calculated results are well in agreement with experimental data. The lowest critical enrichment is calculated to be 2.10 p.c. in the isotope U-235. (orig.) [de

Quantifying the economic importance of irrigation water reuse in a Chilean watershed using an integrated agent-based model

Science.gov (United States)

Arnold, R. T.; Troost, Christian; Berger, Thomas

2015-01-01

Irrigation with surface water enables Chilean agricultural producers to generate one of the country's most important economic exports. The Chilean water code established tradable water rights as a mechanism to allocate water amongst farmers and other water-use sectors. It remains contested whether this mechanism is effective and many authors have raised equity concerns regarding its impact on water users. For example, speculative hoarding of water rights in expectations of their increasing value has been described. This paper demonstrates how farmers can hoard water rights as a risk management strategy for variable water supply, for example, due to the cycles of El Niño or as consequence of climate change. While farmers with insufficient water rights can rely on unclaimed water during conditions of normal water availability, drought years overproportionally impact on their supply of irrigation water and thereby farm profitability. This study uses a simulation model that consists of a hydrological balance model component and a multiagent farm decision and production component. Both model components are parameterized with empirical data, while uncertain parameters are calibrated. The study demonstrates a thorough quantification of parameter uncertainty, using global sensitivity analysis and multiple behavioral parameter scenarios.

Parameter sensitivity and uncertainty of the forest carbon flux model FORUG : a Monte Carlo analysis

Energy Technology Data Exchange (ETDEWEB)

Verbeeck, H.; Samson, R.; Lemeur, R. [Ghent Univ., Ghent (Belgium). Laboratory of Plant Ecology; Verdonck, F. [Ghent Univ., Ghent (Belgium). Dept. of Applied Mathematics, Biometrics and Process Control

2006-06-15

The FORUG model is a multi-layer process-based model that simulates carbon dioxide (CO{sub 2}) and water exchange between forest stands and the atmosphere. The main model outputs are net ecosystem exchange (NEE), total ecosystem respiration (TER), gross primary production (GPP) and evapotranspiration. This study used a sensitivity analysis to identify the parameters contributing to NEE uncertainty in the FORUG model. The aim was to determine if it is necessary to estimate the uncertainty of all parameters of a model to determine overall output uncertainty. Data used in the study were the meteorological and flux data of beech trees in Hesse. The Monte Carlo method was used to rank sensitivity and uncertainty parameters in combination with a multiple linear regression. Simulations were run in which parameters were assigned probability distributions and the effect of variance in the parameters on the output distribution was assessed. The uncertainty of the output for NEE was estimated. Based on the arbitrary uncertainty of 10 key parameters, a standard deviation of 0.88 Mg C per year per NEE was found, which was equal to 24 per cent of the mean value of NEE. The sensitivity analysis showed that the overall output uncertainty of the FORUG model could be determined by accounting for only a few key parameters, which were identified as corresponding to critical parameters in the literature. It was concluded that the 10 most important parameters determined more than 90 per cent of the output uncertainty. High ranking parameters included soil respiration; photosynthesis; and crown architecture. It was concluded that the Monte Carlo technique is a useful tool for ranking the uncertainty of parameters of process-based forest flux models. 48 refs., 2 tabs., 2 figs.

Test models for improving filtering with model errors through stochastic parameter estimation

International Nuclear Information System (INIS)

Gershgorin, B.; Harlim, J.; Majda, A.J.

2010-01-01

The filtering skill for turbulent signals from nature is often limited by model errors created by utilizing an imperfect model for filtering. Updating the parameters in the imperfect model through stochastic parameter estimation is one way to increase filtering skill and model performance. Here a suite of stringent test models for filtering with stochastic parameter estimation is developed based on the Stochastic Parameterization Extended Kalman Filter (SPEKF). These new SPEKF-algorithms systematically correct both multiplicative and additive biases and involve exact formulas for propagating the mean and covariance including the parameters in the test model. A comprehensive study is presented of robust parameter regimes for increasing filtering skill through stochastic parameter estimation for turbulent signals as the observation time and observation noise are varied and even when the forcing is incorrectly specified. The results here provide useful guidelines for filtering turbulent signals in more complex systems with significant model errors.

Multiscale modeling of a rectifying bipolar nanopore: explicit-water versus implicit-water simulations.

Science.gov (United States)

Ható, Zoltán; Valiskó, Mónika; Kristóf, Tamás; Gillespie, Dirk; Boda, Dezsö

2017-07-21

In a multiscale modeling approach, we present computer simulation results for a rectifying bipolar nanopore at two modeling levels. In an all-atom model, we use explicit water to simulate ion transport directly with the molecular dynamics technique. In a reduced model, we use implicit water and apply the Local Equilibrium Monte Carlo method together with the Nernst-Planck transport equation. This hybrid method makes the fast calculation of ion transport possible at the price of lost details. We show that the implicit-water model is an appropriate representation of the explicit-water model when we look at the system at the device (i.e., input vs. output) level. The two models produce qualitatively similar behavior of the electrical current for different voltages and model parameters. Looking at the details of concentration and potential profiles, we find profound differences between the two models. These differences, however, do not influence the basic behavior of the model as a device because they do not influence the z-dependence of the concentration profiles which are the main determinants of current. These results then address an old paradox: how do reduced models, whose assumptions should break down in a nanoscale device, predict experimental data? Our simulations show that reduced models can still capture the overall device physics correctly, even though they get some important aspects of the molecular-scale physics quite wrong; reduced models work because they include the physics that is necessary from the point of view of device function. Therefore, reduced models can suffice for general device understanding and device design, but more detailed models might be needed for molecular level understanding.

Revisiting a many-body model for water based on a single polarizable site: from gas phase clusters to liquid and air/liquid water systems.

Science.gov (United States)

Réal, Florent; Vallet, Valérie; Flament, Jean-Pierre; Masella, Michel

2013-09-21

We present a revised version of the water many-body model TCPE [M. Masella and J.-P. Flament, J. Chem. Phys. 107, 9105 (1997)], which is based on a static three charge sites and a single polarizable site to model the molecular electrostatic properties of water, and on an anisotropic short range many-body energy term specially designed to accurately model hydrogen bonding in water. The parameters of the revised model, denoted TCPE/2013, are here developed to reproduce the ab initio energetic and geometrical properties of small water clusters (up to hexamers) and the repulsive water interactions occurring in cation first hydration shells. The model parameters have also been refined to reproduce two liquid water properties at ambient conditions, the density and the vaporization enthalpy. Thanks to its computational efficiency, the new model range of applicability was validated by performing simulations of liquid water over a wide range of temperatures and pressures, as well as by investigating water liquid/vapor interfaces over a large range of temperatures. It is shown to reproduce several important water properties at an accurate enough level of precision, such as the existence liquid water density maxima up to a pressure of 1000 atm, the water boiling temperature, the properties of the water critical point (temperature, pressure, and density), and the existence of a "singularity" temperature at about 225 K in the supercooled regime. This model appears thus to be particularly well-suited for characterizing ion hydration properties under different temperature and pressure conditions, as well as in different phases and interfaces.

Estimation of lake water - groundwater interactions in meromictic mining lakes by modelling isotope signatures of lake water.

Science.gov (United States)

Seebach, Anne; Dietz, Severine; Lessmann, Dieter; Knoeller, Kay

2008-03-01

A method is presented to assess lake water-groundwater interactions by modelling isotope signatures of lake water using meteorological parameters and field data. The modelling of delta(18)O and deltaD variations offers information about the groundwater influx into a meromictic Lusatian mining lake. Therefore, a water balance model is combined with an isotope water balance model to estimate analogies between simulated and measured isotope signatures within the lake water body. The model is operated with different evaporation rates to predict delta(18)O and deltaD values in a lake that is only controlled by weather conditions with neither groundwater inflow nor outflow. Comparisons between modelled and measured isotope values show whether the lake is fed by the groundwater or not. Furthermore, our investigations show that an adaptation of the Craig and Gordon model [H. Craig, L.I. Gordon. Deuterium and oxygen-18 variations in the ocean and the marine atmosphere. In Stable Isotopes in Oceanographic Studies and Paleotemperature, Spoleto, E. Tongiorgi (Ed.), pp. 9-130, Consiglio Nazionale delle Ricerche, Laboratorio di Geologia Nucleare, Pisa (1965).] to specific conditions in temperate regions seems necessary.

A holistic water depth simulation model for small ponds

Science.gov (United States)

Ali, Shakir; Ghosh, Narayan C.; Mishra, P. K.; Singh, R. K.

2015-10-01

Estimation of time varying water depth and time to empty of a pond is prerequisite for comprehensive and coordinated planning of water resource for its effective utilization. A holistic water depth simulation (HWDS) and time to empty (TE) model for small, shallow ephemeral ponds have been derived by employing the generalized model based on the Green-Ampt equation in the basic water balance equation. The HWDS model includes time varying rainfall, runoff, surface water evaporation, outflow and advancement of wetting front length as external inputs. The TE model includes two external inputs; surface water evaporation and advancement of wetting front length. Both the models also consider saturated hydraulic conductivity and fillable porosity of the pond's bed material as their parameters. The solution of the HWDS model involved numerical iteration in successive time intervals. The HWDS model has successfully evaluated with 3 years of field data from two small ponds located within a watershed in a semi-arid region in western India. The HWDS model simulated time varying water depth in the ponds with high accuracy as shown by correlation coefficient (R2 ⩾ 0.9765), index of agreement (d ⩾ 0.9878), root mean square errors (RMSE ⩽ 0.20 m) and percent bias (PB ⩽ 6.23%) for the pooled data sets of the measured and simulated water depth. The statistical F and t-tests also confirmed the reliability of the HWDS model at probability level, p ⩽ 0.0001. The response of the TE model showed its ability to estimate the time to empty the ponds. An additional field calibration and validation of the HWDS and TE models with observed field data in varied hydro-climatic conditions could be conducted to increase the applicability and credibility of the models.

Mutagenicity of drinking water sampled from the Yangtze River and Hanshui River (Wuhan section) and correlations with water quality parameters.

Science.gov (United States)

Lv, Xuemin; Lu, Yi; Yang, Xiaoming; Dong, Xiaorong; Ma, Kunpeng; Xiao, Sanhua; Wang, Yazhou; Tang, Fei

2015-03-31

A total of 54 water samples were collected during three different hydrologic periods (level period, wet period, and dry period) from Plant A and Plant B (a source for Yangtze River and Hanshui River water, respectively), and several water parameters, such as chemical oxygen demand (COD), turbidity, and total organic carbon (TOC), were simultaneously analyzed. The mutagenicity of the water samples was evaluated using the Ames test with Salmonella typhimurium strains TA98 and TA100. According to the results, the organic compounds in the water were largely frame-shift mutagens, as positive results were found for most of the tests using TA98. All of the finished water samples exhibited stronger mutagenicity than the relative raw and distribution water samples, with water samples collected from Plant B presenting stronger mutagenic strength than those from Plant A. The finished water samples from Plant A displayed a seasonal-dependent variation. Water parameters including COD (r = 0.599, P = 0.009), TOC (r = 0.681, P = 0.02), UV254 (r = 0.711, P = 0.001), and total nitrogen (r = 0.570, P = 0.014) exhibited good correlations with mutagenicity (TA98), at 2.0 L/plate, which bolsters the argument of the importance of using mutagenicity as a new parameter to assess the quality of drinking water.

[Temporal and spatial heterogeneity analysis of optimal value of sensitive parameters in ecological process model: The BIOME-BGC model as an example.

Science.gov (United States)

Li, Yi Zhe; Zhang, Ting Long; Liu, Qiu Yu; Li, Ying

2018-01-01

The ecological process models are powerful tools for studying terrestrial ecosystem water and carbon cycle at present. However, there are many parameters for these models, and weather the reasonable values of these parameters were taken, have important impact on the models simulation results. In the past, the sensitivity and the optimization of model parameters were analyzed and discussed in many researches. But the temporal and spatial heterogeneity of the optimal parameters is less concerned. In this paper, the BIOME-BGC model was used as an example. In the evergreen broad-leaved forest, deciduous broad-leaved forest and C3 grassland, the sensitive parameters of the model were selected by constructing the sensitivity judgment index with two experimental sites selected under each vegetation type. The objective function was constructed by using the simulated annealing algorithm combined with the flux data to obtain the monthly optimal values of the sensitive parameters at each site. Then we constructed the temporal heterogeneity judgment index, the spatial heterogeneity judgment index and the temporal and spatial heterogeneity judgment index to quantitatively analyze the temporal and spatial heterogeneity of the optimal values of the model sensitive parameters. The results showed that the sensitivity of BIOME-BGC model parameters was different under different vegetation types, but the selected sensitive parameters were mostly consistent. The optimal values of the sensitive parameters of BIOME-BGC model mostly presented time-space heterogeneity to different degrees which varied with vegetation types. The sensitive parameters related to vegetation physiology and ecology had relatively little temporal and spatial heterogeneity while those related to environment and phenology had generally larger temporal and spatial heterogeneity. In addition, the temporal heterogeneity of the optimal values of the model sensitive parameters showed a significant linear correlation

Accuracy of spatio-temporal RARX model predictions of water table depths

NARCIS (Netherlands)

Knotters, M.; Bierkens, M.F.P.

2002-01-01

Time series of water table depths (Ht) are predicted in space using a regionalised autoregressive exogenous variable (RARX) model with precipitation surplus (Pt) as input variable. Because of their physical basis, RARX model parameters can be guessed from auxiliary information such as a digital

The study of interrelationship between raw water quality parameters, chlorine demand and the formation of disinfection by-products

Science.gov (United States)

Abdullah, Md. Pauzi; Yee, Lim Fang; Ata, Sadia; Abdullah, Abass; Ishak, Basar; Abidin, Khairul Nidzham Zainal

Disinfection is the most crucial process in the treatment of drinking water supply and is the final barrier against bacteriological impurities in drinking water. Chlorine is the primary disinfectant used in the drinking water treatment process throughout Malaysia. However, the occurrence of various disinfection by-products such as trihalomethanes (THM) and haloacetic acids created a major issue on the potential health hazards which may pose adverse health effects in both human and animals. To simulate real water treatment conditions and to represent the conditions inherent in a tropical country, this study was performed at an urbanized water treatment plant with a daily production of about 549,000 m 3 of treated water. The purpose of this work is to examine the relationship between the water quality parameters in the raw water with chlorine demand and the formation of disinfection by-products. This study also investigated the possibility of the statistical model applications for the prediction of chlorine demand and the THM formation. Two models were developed to estimate the chlorine demand and the THM formation. For the statistical evaluation, correlation and simple linear regression analysis were conducted using SPSS. The results of Kolmogorov-Smirnov test for the estimation of goodness-of-fit of the dependent variables of the models to the normal distribution showed that all the dependent variables followed the normal distribution at significance level of 0.05. Good linear correlations were observed between the independent parameters and formation of THM and the chlorine demand. This study also revealed that ammonia and the specific ultraviolet absorbent (SUVA) were the function of chlorine consumption in the treatment process. Chlorine dosage and SUVA increase the yield of THM. Chlorine demand and THM formation was moderately sensitive, but significant to the pH. The level of significance ( α) for the statistical tests and the inclusion of a variable in the

Bottom friction models for shallow water equations: Manning’s roughness coefficient and small-scale bottom heterogeneity

Science.gov (United States)

Dyakonova, Tatyana; Khoperskov, Alexander

2018-03-01

The correct description of the surface water dynamics in the model of shallow water requires accounting for friction. To simulate a channel flow in the Chezy model the constant Manning roughness coefficient is frequently used. The Manning coefficient nM is an integral parameter which accounts for a large number of physical factors determining the flow braking. We used computational simulations in a shallow water model to determine the relationship between the Manning coefficient and the parameters of small-scale perturbations of a bottom in a long channel. Comparing the transverse water velocity profiles in the channel obtained in the models with a perturbed bottom without bottom friction and with bottom friction on a smooth bottom, we constructed the dependence of nM on the amplitude and spatial scale of perturbation of the bottom relief.

Integrating water data, models and forecasts - the Australian Water Resources Information System (Invited)

Science.gov (United States)

Argent, R.; Sheahan, P.; Plummer, N.

2010-12-01

Under the Commonwealth Water Act 2007 the Bureau of Meteorology was given a new national role in water information, encompassing standards, water accounts and assessments, hydrological forecasting, and collecting, enhancing and making freely available Australia’s water information. The Australian Water Resources Information System (AWRIS) is being developed to fulfil part of this role, by providing foundational data, information and model structures and services. Over 250 organisations across Australia are required to provide water data and metadata to the Bureau, including federal, state and local governments, water storage management and hydroelectricity companies, rural and urban water utilities, and catchment management bodies. The data coverage includes the categories needed to assess and account for water resources at a range of scales. These categories are surface, groundwater and meteorological observations, water in storages, water restrictions, urban and irrigation water use and flows, information on rights, allocations and trades, and a limited suite of water quality parameters. These data are currently supplied to the Bureau via a file-based delivery system at various frequencies from annual to daily or finer, and contain observations taken at periods from minutes to monthly or coarser. One of the primary keys to better data access and utilisation is better data organisation, including content and markup standards. As a significant step on the path to standards for water data description, the Bureau has developed a Water Data Transfer Format (WDTF) for transmission of a variety of water data categories, including site metadata. WDTF is adapted from the OGC’s observation and sampling-features standard. The WDTF XML schema is compatible with the OGC's Web Feature Service (WFS) interchange standard, and conforms to GML Simple Features profile (GML-SF) level 1, emphasising the importance of standards in data exchange. In the longer term we are also

Inexact nonlinear improved fuzzy chance-constrained programming model for irrigation water management under uncertainty

Science.gov (United States)

Zhang, Chenglong; Zhang, Fan; Guo, Shanshan; Liu, Xiao; Guo, Ping

2018-01-01

An inexact nonlinear mλ-measure fuzzy chance-constrained programming (INMFCCP) model is developed for irrigation water allocation under uncertainty. Techniques of inexact quadratic programming (IQP), mλ-measure, and fuzzy chance-constrained programming (FCCP) are integrated into a general optimization framework. The INMFCCP model can deal with not only nonlinearities in the objective function, but also uncertainties presented as discrete intervals in the objective function, variables and left-hand side constraints and fuzziness in the right-hand side constraints. Moreover, this model improves upon the conventional fuzzy chance-constrained programming by introducing a linear combination of possibility measure and necessity measure with varying preference parameters. To demonstrate its applicability, the model is then applied to a case study in the middle reaches of Heihe River Basin, northwest China. An interval regression analysis method is used to obtain interval crop water production functions in the whole growth period under uncertainty. Therefore, more flexible solutions can be generated for optimal irrigation water allocation. The variation of results can be examined by giving different confidence levels and preference parameters. Besides, it can reflect interrelationships among system benefits, preference parameters, confidence levels and the corresponding risk levels. Comparison between interval crop water production functions and deterministic ones based on the developed INMFCCP model indicates that the former is capable of reflecting more complexities and uncertainties in practical application. These results can provide more reliable scientific basis for supporting irrigation water management in arid areas.

Model parameters for representative wetland plant functional groups

Science.gov (United States)

Williams, Amber S.; Kiniry, James R.; Mushet, David M.; Smith, Loren M.; McMurry, Scott T.; Attebury, Kelly; Lang, Megan; McCarty, Gregory W.; Shaffer, Jill A.; Effland, William R.; Johnson, Mari-Vaughn V.

2017-01-01

Wetlands provide a wide variety of ecosystem services including water quality remediation, biodiversity refugia, groundwater recharge, and floodwater storage. Realistic estimation of ecosystem service benefits associated with wetlands requires reasonable simulation of the hydrology of each site and realistic simulation of the upland and wetland plant growth cycles. Objectives of this study were to quantify leaf area index (LAI), light extinction coefficient (k), and plant nitrogen (N), phosphorus (P), and potassium (K) concentrations in natural stands of representative plant species for some major plant functional groups in the United States. Functional groups in this study were based on these parameters and plant growth types to enable process-based modeling. We collected data at four locations representing some of the main wetland regions of the United States. At each site, we collected on-the-ground measurements of fraction of light intercepted, LAI, and dry matter within the 2013–2015 growing seasons. Maximum LAI and k variables showed noticeable variations among sites and years, while overall averages and functional group averages give useful estimates for multisite simulation modeling. Variation within each species gives an indication of what can be expected in such natural ecosystems. For P and K, the concentrations from highest to lowest were spikerush (Eleocharis macrostachya), reed canary grass (Phalaris arundinacea), smartweed (Polygonum spp.), cattail (Typha spp.), and hardstem bulrush (Schoenoplectus acutus). Spikerush had the highest N concentration, followed by smartweed, bulrush, reed canary grass, and then cattail. These parameters will be useful for the actual wetland species measured and for the wetland plant functional groups they represent. These parameters and the associated process-based models offer promise as valuable tools for evaluating environmental benefits of wetlands and for evaluating impacts of various agronomic practices in

Microbial Communities Model Parameter Calculation for TSPA/SR

International Nuclear Information System (INIS)

D. Jolley

2001-01-01

This calculation has several purposes. First the calculation reduces the information contained in ''Committed Materials in Repository Drifts'' (BSC 2001a) to useable parameters required as input to MING V1.O (CRWMS M and O 1998, CSCI 30018 V1.O) for calculation of the effects of potential in-drift microbial communities as part of the microbial communities model. The calculation is intended to replace the parameters found in Attachment II of the current In-Drift Microbial Communities Model revision (CRWMS M and O 2000c) with the exception of Section 11-5.3. Second, this calculation provides the information necessary to supercede the following DTN: M09909SPAMING1.003 and replace it with a new qualified dataset (see Table 6.2-1). The purpose of this calculation is to create the revised qualified parameter input for MING that will allow ΔG (Gibbs Free Energy) to be corrected for long-term changes to the temperature of the near-field environment. Calculated herein are the quadratic or second order regression relationships that are used in the energy limiting calculations to potential growth of microbial communities in the in-drift geochemical environment. Third, the calculation performs an impact review of a new DTN: M00012MAJIONIS.000 that is intended to replace the currently cited DTN: GS9809083 12322.008 for water chemistry data used in the current ''In-Drift Microbial Communities Model'' revision (CRWMS M and O 2000c). Finally, the calculation updates the material lifetimes reported on Table 32 in section 6.5.2.3 of the ''In-Drift Microbial Communities'' AMR (CRWMS M and O 2000c) based on the inputs reported in BSC (2001a). Changes include adding new specified materials and updating old materials information that has changed

Energy deposition model for I-125 photon radiation in water

International Nuclear Information System (INIS)

Fuss, M.C.; Garcia, G.; Munoz, A.; Oller, J.C.; Blanco, F.; Limao-Vieira, P.; Williart, A.; Garcia, G.; Huerga, C.; Tellez, M.

2010-01-01

In this study, an electron-tracking Monte Carlo algorithm developed by us is combined with established photon transport models in order to simulate all primary and secondary particle interactions in water for incident photon radiation. As input parameters for secondary electron interactions, electron scattering cross sections by water molecules and experimental energy loss spectra are used. With this simulation, the resulting energy deposition can be modelled at the molecular level, yielding detailed information about localization and type of single collision events. The experimental emission spectrum of I-125 seeds, as used for radiotherapy of different tumours, was used for studying the energy deposition in water when irradiating with this radionuclide. (authors)

Energy deposition model for I-125 photon radiation in water

Energy Technology Data Exchange (ETDEWEB)

Fuss, M.C.; Garcia, G. [Instituto de Fisica Fundamental, Consejo Superior de Investigaciones Cientificas (CSIC), Madrid (Spain); Munoz, A.; Oller, J.C. [Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas (CIEMAT), Madrid (Spain); Blanco, F. [Departamento de Fisica Atomica, Molecular y Nuclear, Universidad Complutense de Madrid (Spain); Limao-Vieira, P. [Laboratorio de Colisoes Atomicas e Moleculares, Departamento de Fisica, CEFITEC, FCT-Universidade Nova de Lisboa, Caparica (Portugal); Williart, A.; Garcia, G. [Departamento de Fisica de los Materiales, Universidad Nacional de Educacion a Distancia, Madrid (Spain); Huerga, C.; Tellez, M. [Hospital Universitario La Paz, Madrid (Spain)

2010-10-15

In this study, an electron-tracking Monte Carlo algorithm developed by us is combined with established photon transport models in order to simulate all primary and secondary particle interactions in water for incident photon radiation. As input parameters for secondary electron interactions, electron scattering cross sections by water molecules and experimental energy loss spectra are used. With this simulation, the resulting energy deposition can be modelled at the molecular level, yielding detailed information about localization and type of single collision events. The experimental emission spectrum of I-125 seeds, as used for radiotherapy of different tumours, was used for studying the energy deposition in water when irradiating with this radionuclide. (authors)

Modeling of primary water stress corrosion cracking at control rod drive mechanism nozzles of pressurized water reactors

International Nuclear Information System (INIS)

Aly, Omar Fernandes

2006-01-01

One of the main failure mechanisms that cause risks to pressurized water reactors is the primary water stress corrosion cracking (PWSCC) occurring in alloys. It can occurs, besides another places, at the control reactor displacement mechanism nozzles. It is caused by the joint effect of tensile stress, temperature, susceptible metallurgical microstructure and environmental conditions of the primary water. These cracks can cause accidents that reduce nuclear safety by blocking the rod's displacement and may cause leakage of primary water, reducing the reactor's life. In this work it is proposed a study of the existing models and a modeling proposal to primary water stress corrosion cracking in these nozzles in a nickel based Alloy 600. It is been superposed electrochemical and fracture mechanics models, and validated using experimental and literature data. The experimental data were obtained at CDTN-Brazilian Nuclear Technology Development Center, in a recent installed slow strain rate testing equipment. In the literature it is found a diagram that indicates a thermodynamic condition for the occurrence of some PWSCC sub modes in Alloy 600: it was used potential x pH diagrams (Pourbaix diagrams), for Alloy 600 in high temperature primary water (300 deg C till 350 deg C). Over it, were located the PWSCC sub modes, using experimental data. It was added a third parameter called 'stress corrosion strength fraction'. However, it is possible to superpose to this diagram, other parameters expressing PWSCC initiation or growth kinetics from other models. Here is the proposition of the original contribution of this work: from an original experimental condition of potential versus pH, it was superposed, an empiric-comparative, a semi-empiric-probabilistic, an initiation time, and a strain rate damage models, to quantify respectively the PWSCC susceptibility, the failure time, and in the two lasts, the initiation time of stress corrosion cracking. It was modeling from our

Constraining Parameter Uncertainty in Simulations of Water and Heat Dynamics in Seasonally Frozen Soil Using Limited Observed Data

Directory of Open Access Journals (Sweden)

Mousong Wu

2016-02-01

Full Text Available Water and energy processes in frozen soils are important for better understanding hydrologic processes and water resources management in cold regions. To investigate the water and energy balance in seasonally frozen soils, CoupModel combined with the generalized likelihood uncertainty estimation (GLUE method was used. Simulation work on water and heat processes in frozen soil in northern China during the 2012/2013 winter was conducted. Ensemble simulations through the Monte Carlo sampling method were generated for uncertainty analysis. Behavioral simulations were selected based on combinations of multiple model performance index criteria with respect to simulated soil water and temperature at four depths (5 cm, 15 cm, 25 cm, and 35 cm. Posterior distributions for parameters related to soil hydraulic, radiation processes, and heat transport indicated that uncertainties in both input and model structures could influence model performance in modeling water and heat processes in seasonally frozen soils. Seasonal courses in water and energy partitioning were obvious during the winter. Within the day-cycle, soil evaporation/condensation and energy distributions were well captured and clarified as an important phenomenon in the dynamics of the energy balance system. The combination of the CoupModel simulations with the uncertainty-based calibration method provides a way of understanding the seasonal courses of hydrology and energy processes in cold regions with limited data. Additional measurements may be used to further reduce the uncertainty of regulating factors during the different stages of freezing–thawing.

Exploiting intrinsic fluctuations to identify model parameters.

Science.gov (United States)

Zimmer, Christoph; Sahle, Sven; Pahle, Jürgen

2015-04-01

Parameterisation of kinetic models plays a central role in computational systems biology. Besides the lack of experimental data of high enough quality, some of the biggest challenges here are identification issues. Model parameters can be structurally non-identifiable because of functional relationships. Noise in measured data is usually considered to be a nuisance for parameter estimation. However, it turns out that intrinsic fluctuations in particle numbers can make parameters identifiable that were previously non-identifiable. The authors present a method to identify model parameters that are structurally non-identifiable in a deterministic framework. The method takes time course recordings of biochemical systems in steady state or transient state as input. Often a functional relationship between parameters presents itself by a one-dimensional manifold in parameter space containing parameter sets of optimal goodness. Although the system's behaviour cannot be distinguished on this manifold in a deterministic framework it might be distinguishable in a stochastic modelling framework. Their method exploits this by using an objective function that includes a measure for fluctuations in particle numbers. They show on three example models, immigration-death, gene expression and Epo-EpoReceptor interaction, that this resolves the non-identifiability even in the case of measurement noise with known amplitude. The method is applied to partially observed recordings of biochemical systems with measurement noise. It is simple to implement and it is usually very fast to compute. This optimisation can be realised in a classical or Bayesian fashion.

Two-Dimensional Modeling of Heat and Moisture Dynamics in Swedish Roads: Model Set up and Parameter Sensitivity

Science.gov (United States)

Rasul, H.; Wu, M.; Olofsson, B.

2017-12-01

Modelling moisture and heat changes in road layers is very important to understand road hydrology and for better construction and maintenance of roads in a sustainable manner. In cold regions due to the freezing/thawing process in the partially saturated material of roads, the modeling task will become more complicated than simple model of flow through porous media without freezing/thawing pores considerations. This study is presenting a 2-D model simulation for a section of highway with considering freezing/thawing and vapor changes. Partial deferential equations (PDEs) are used in formulation of the model. Parameters are optimized from modelling results based on the measured data from test station on E18 highway near Stockholm. Impacts of phase change considerations in the modelling are assessed by comparing the modeled soil moisture with TDR-measured data. The results show that the model can be used for prediction of water and ice content in different layers of the road and at different seasons. Parameter sensitivities are analyzed by implementing a calibration strategy. In addition, the phase change consideration is evaluated in the modeling process, by comparing the PDE model with another model without considerations of freezing/thawing in roads. The PDE model shows high potential in understanding the moisture dynamics in the road system.

Extending a Consensus-based Fuzzy Ordered Weighting Average (FOWA Model in New Water Quality Indices

Directory of Open Access Journals (Sweden)

Mohammad Ali Baghapour

2017-07-01

Full Text Available In developing a specific WQI (Water Quality Index, many water quality parameters are involved with different levels of importance. The impact of experts’ different opinions and viewpoints, current risks affecting their opinions, and plurality of the involved parameters double the significance of the issue. Hence, the current study tries to apply a consensus-based FOWA (Fuzzy Ordered Weighting Average model as one of the most powerful and well-known Multi Criteria Decision Making (MCDM techniques to determine the importance of the used parameters in the development of such WQIs which is shown with an example. This operator has provided the capability of modeling the risks in decision-making through applying the optimistic degree of stakeholders and their power coupled with the use of fuzzy numbers. Totally, 22 water quality parameters for drinking purposes are considered in this study. To determine the weight of each parameter, the viewpoints of 4 decision-making groups of experts are taken into account. After determining the final weights, to validate the use of each parameter in a potential WQI, consensus degrees of both the decision makers and the parameters are calculated. All calculations are carried out by using the expertise software called Group Fuzzy Decision Making (GFDM. The highest and the lowest weight values, 0.999 and 0.073 respectively, are related to Hg and temperature. Regarding the type of consumption that is drinking, the parameters’ weights and ranks are consistent with their health impacts. Moreover, the decision makers’ highest and lowest consensus degrees were 0.9905 and 0.9669, respectively. Among the water quality parameters, temperature (with consensus degree of 0.9972 and Pb (with consensus degree of 0.9665, received the highest and lowest agreement from the decision making group. This study indicates that the weight of parameters in determining water quality largely depends on the experts’ opinions and

Inverse Modeling of Soil Hydraulic Parameters Based on a Hybrid of Vector-Evaluated Genetic Algorithm and Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Yi-Bo Li

2018-01-01

Full Text Available The accurate estimation of soil hydraulic parameters (θs, α, n, and Ks of the van Genuchten–Mualem model has attracted considerable attention. In this study, we proposed a new two-step inversion method, which first estimated the hydraulic parameter θs using objective function by the final water content, and subsequently estimated the soil hydraulic parameters α, n, and Ks, using a vector-evaluated genetic algorithm and particle swarm optimization (VEGA-PSO method based on objective functions by cumulative infiltration and infiltration rate. The parameters were inversely estimated for four types of soils (sand, loam, silt, and clay under an in silico experiment simulating the tension disc infiltration at three initial water content levels. The results indicated that the method is excellent and robust. Because the objective function had multilocal minima in a tiny range near the true values, inverse estimation of the hydraulic parameters was difficult; however, the estimated soil water retention curves and hydraulic conductivity curves were nearly identical to the true curves. In addition, the proposed method was able to estimate the hydraulic parameters accurately despite substantial measurement errors in initial water content, final water content, and cumulative infiltration, proving that the method was feasible and practical for field application.

Performance of chromatographic systems to model soil-water sorption.

Science.gov (United States)

Hidalgo-Rodríguez, Marta; Fuguet, Elisabet; Ràfols, Clara; Rosés, Martí

2012-08-24

A systematic approach for evaluating the goodness of chromatographic systems to model the sorption of neutral organic compounds by soil from water is presented in this work. It is based on the examination of the three sources of error that determine the overall variance obtained when soil-water partition coefficients are correlated against chromatographic retention factors: the variance of the soil-water sorption data, the variance of the chromatographic data, and the variance attributed to the dissimilarity between the two systems. These contributions of variance are easily predicted through the characterization of the systems by the solvation parameter model. According to this method, several chromatographic systems besides the reference octanol-water partition system have been selected to test their performance in the emulation of soil-water sorption. The results from the experimental correlations agree with the predicted variances. The high-performance liquid chromatography system based on an immobilized artificial membrane and the micellar electrokinetic chromatography systems of sodium dodecylsulfate and sodium taurocholate provide the most precise correlation models. They have shown to predict well soil-water sorption coefficients of several tested herbicides. Octanol-water partitions and high-performance liquid chromatography measurements using C18 columns are less suited for the estimation of soil-water partition coefficients. Copyright © 2012 Elsevier B.V. All rights reserved.

Incorporating model parameter uncertainty into inverse treatment planning

International Nuclear Information System (INIS)

Lian Jun; Xing Lei

2004-01-01

Radiobiological treatment planning depends not only on the accuracy of the models describing the dose-response relation of different tumors and normal tissues but also on the accuracy of tissue specific radiobiological parameters in these models. Whereas the general formalism remains the same, different sets of model parameters lead to different solutions and thus critically determine the final plan. Here we describe an inverse planning formalism with inclusion of model parameter uncertainties. This is made possible by using a statistical analysis-based frameset developed by our group. In this formalism, the uncertainties of model parameters, such as the parameter a that describes tissue-specific effect in the equivalent uniform dose (EUD) model, are expressed by probability density function and are included in the dose optimization process. We found that the final solution strongly depends on distribution functions of the model parameters. Considering that currently available models for computing biological effects of radiation are simplistic, and the clinical data used to derive the models are sparse and of questionable quality, the proposed technique provides us with an effective tool to minimize the effect caused by the uncertainties in a statistical sense. With the incorporation of the uncertainties, the technique has potential for us to maximally utilize the available radiobiology knowledge for better IMRT treatment

Modeling the electrochemistry of the primary circuits of light water reactors

International Nuclear Information System (INIS)

Bertuch, A.; Macdonald, D.D.; Pang, J.; Kriksunov, L.; Arioka, K.

1994-01-01

To model the corrosion behaviors of the heat transport circuits of light water reactors, a mixed potential model (NTM) has been developed and applied to both boiling water reactors (BWRs) and pressurized water reactors (PWRs). Using the data generated by the GE/UKEA-Harwell radiolysis model, electrochemical potentials (ECPs) have been calculated for the heat transport circuits of eight BWRs operating under hydrogen water chemistry (HWC). By modeling the corrosion behaviors of these reactors, the effectiveness of HWC at limiting IGSCC and IASCC can be determined. For simulating PWR primary circuits, a chemical-radiolysis model (developed by the authors) was used to generate input parameters for the MPM. Corrosion potentials of Type 304 and 316 SSs in PWR primary environments were calculated using the NTM and were found to be in good agreement with the corrosion potentials measured in the laboratory for simulated PWR primary environments

Simplified distributed parameters BWR dynamic model for transient and stability analysis

International Nuclear Information System (INIS)

Espinosa-Paredes, Gilberto; Nunez-Carrera, Alejandro; Vazquez-Rodriguez, Alejandro

2006-01-01

This paper describes a simplified model to perform transient and linear stability analysis for a typical boiling water reactor (BWR). The simplified transient model was based in lumped and distributed parameters approximations, which includes vessel dome and the downcomer, recirculation loops, neutron process, fuel pin temperature distribution, lower and upper plenums reactor core and pressure and level controls. The stability was determined by studying the linearized versions of the equations representing the BWR system in the frequency domain. Numerical examples are used to illustrate the wide application of the simplified BWR model. We concluded that this simplified model describes properly the dynamic of a BWR and can be used for safety analysis or as a first approach in the design of an advanced BWR

Identification of Water Quality Significant Parameter with Two Transformation/Standardization Methods on Principal Component Analysis and Scilab Software

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Jovan Putranda

2016-09-01

Full Text Available Water quality monitoring is prone to encounter error on its recording or measuring process. The monitoring on river water quality not only aims to recognize the water quality dynamic, but also to evaluate the data to create river management policy and water pollution in order to maintain the continuity of human health or sanitation requirement, and biodiversity preservation. Evaluation on water quality monitoring needs to be started by identifying the important water quality parameter. This research objected to identify the significant parameters by using two transformation or standardization methods on water quality data, which are the river Water Quality Index, WQI (Indeks Kualitas Air, Sungai, IKAs transformation or standardization method and transformation or standardization method with mean 0 and variance 1; so that the variability of water quality parameters could be aggregated with one another. Both of the methods were applied on the water quality monitoring data which its validity and reliability have been tested. The PCA, Principal Component Analysis (Analisa Komponen Utama, AKU, with the help of Scilab software, has been used to process the secondary data on water quality parameters of Gadjah Wong river in 2004-2013, with its validity and reliability has been tested. The Scilab result was cross examined with the result from the Excel-based Biplot Add In software. The research result showed that only 18 from total 35 water quality parameters that have passable data quality. The two transformation or standardization data methods gave different significant parameter type and amount result. On the transformation or standardization mean 0 variances 1, there were water quality significant parameter dynamic to mean concentration of each water quality parameters, which are TDS, SO4, EC, TSS, NO3N, COD, BOD5, Grease Oil and NH3N. On the river WQI transformation or standardization, the water quality significant parameter showed the level of

Development and application of the Qausi Distributed Water Balance model (QDWB in the Neishaboor-Rokh watershed

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sajjad razavi

2017-03-01

Full Text Available Limitation of water resources in Iran motivates sustaining and preserving of the resources in order to supply future water needs. Fulfilling these objectives will not be possible unless having accurate water balance of watersheds. The purpose of this study is to estimate the water balance parameters using a distributed method. The large number of distributed models and methods was studied and “Quasi Distributed Water Balance model” (QDWB was written in the MATLAB programming environment. To conduct this model, it is needed that each data layer (precipitation, potential evapotranspiration, land use, soil data,.. to be converted into grid format. In this research the 500m * 500m cell size was used and water balance parameters for each cell was estimated. Runoff and deep percolation obtained from surface balance equation and irrigation needs were estimated based on soil moisture deficit. The study area of 9157 square kilometers is Neyshabour- Rokh watershed. The results showed there is a good correlation between water balance parameters such as precipitation-runoff, precipitation-evapotranspiration, and precipitation- deep percoulation and demonstrate that QDWB model is consistent with the basin hydrological process.Change in soil moisture at basin wide is 1 MCM in 1388-89 and 40 MCM in 1380-81. The evapotranspiration results from a distributed model” SWAT” and QDWB model were in good agreement.

WATER DIVERSION MODEL

International Nuclear Information System (INIS)

J.B. Case

1999-01-01

The distribution of seepage in the proposed repository will be highly variable due in part to variations in the spatial distribution of percolations. The performance of the drip shield and the backfill system may divert the water flux around the waste packages to the invert. Diversion will occur along the drift surface, within the backfill, at the drip shield, and at the Waste Package (WP) surface, even after the drip shield and WP have been breached by corrosion. The purpose and objective of this Analysis and Modeling Report (AMR) are to develop a conceptual model and constitutive properties for bounding the volume and rate of seepage water that flows around the drip shield (CRWMS MandO 1999c). This analysis model is to be compatible with the selected repository conceptual design (Wilkins and Heath, 1999) and will be used to evaluate the performance of the Engineered Barrier System (EBS), and to provide input to the EBS Water Distribution and Removal Model. This model supports the Engineered Barrier System (EBS) postclosure performance assessment for the Site Recommendation (SR). This document characterizes the hydrological constitutive properties of the backfill and invert materials (Section 6.2) and a third material that represents a mixture of the two. These include the Overton Sand which is selected as a backfill (Section 5.2), crushed tuff which is selected as the invert (Section 5.1), and a combined material (Sections 5.9 and 5.10) which has retention and hydraulic conductivity properties intermediate to the selected materials for the backfill and the invert. The properties include the grain size distribution, the dry bulk density and porosity, the moisture retention, the intrinsic permeability, the relative permeability, and the material thermal properties. The van Genuchten relationships with curve fit parameters are used to define the basic retention relationship of moisture potential to volumetric moisture content, and the basic relationship of

WATER DIVERSION MODEL

Energy Technology Data Exchange (ETDEWEB)

J.B. Case

1999-12-21

The distribution of seepage in the proposed repository will be highly variable due in part to variations in the spatial distribution of percolations. The performance of the drip shield and the backfill system may divert the water flux around the waste packages to the invert. Diversion will occur along the drift surface, within the backfill, at the drip shield, and at the Waste Package (WP) surface, even after the drip shield and WP have been breached by corrosion. The purpose and objective of this Analysis and Modeling Report (AMR) are to develop a conceptual model and constitutive properties for bounding the volume and rate of seepage water that flows around the drip shield (CRWMS M&O 1999c). This analysis model is to be compatible with the selected repository conceptual design (Wilkins and Heath, 1999) and will be used to evaluate the performance of the Engineered Barrier System (EBS), and to provide input to the EBS Water Distribution and Removal Model. This model supports the Engineered Barrier System (EBS) postclosure performance assessment for the Site Recommendation (SR). This document characterizes the hydrological constitutive properties of the backfill and invert materials (Section 6.2) and a third material that represents a mixture of the two. These include the Overton Sand which is selected as a backfill (Section 5.2), crushed tuff which is selected as the invert (Section 5.1), and a combined material (Sections 5.9 and 5.10) which has retention and hydraulic conductivity properties intermediate to the selected materials for the backfill and the invert. The properties include the grain size distribution, the dry bulk density and porosity, the moisture retention, the intrinsic permeability, the relative permeability, and the material thermal properties. The van Genuchten relationships with curve fit parameters are used to define the basic retention relationship of moisture potential to volumetric moisture content, and the basic relationship of unsaturated

Dynamic modelling of water demand, water availability and adaptation strategies for power plants to global change

International Nuclear Information System (INIS)

Koch, Hagen; Voegele, Stefan

2009-01-01

According to the latest IPCC reports, the frequency of hot and dry periods will increase in many regions of the world in the future. For power plant operators, the increasing possibility of water shortages is an important challenge that they have to face. Shortages of electricity due to water shortages could have an influence on industries as well as on private households. Climate change impact analyses must analyse the climate effects on power plants and possible adaptation strategies for the power generation sector. Power plants have lifetimes of several decades. Their water demand changes with climate parameters in the short- and medium-term. In the long-term, the water demand will change as old units are phased out and new generating units appear in their place. In this paper, we describe the integration of functions for the calculation of the water demand of power plants into a water resources management model. Also included are both short-term reactive and long-term planned adaptation. This integration allows us to simulate the interconnection between the water demand of power plants and water resources management, i.e. water availability. Economic evaluation functions for water shortages are also integrated into the water resources management model. This coupled model enables us to analyse scenarios of socio-economic and climate change, as well as the effects of water management actions. (author)

Hydrologic parameters and land use reflection on water quality at Mun river, Thailand

International Nuclear Information System (INIS)

Akter, A.; Babel, M.S.

2005-01-01

The 'River Basin' is the land area surrounding one river from its headwaters to its mouth whereas the area drained by a river and its tributaries. So that the land use changes and excessive application of nutrients (Nitrogen and Phosphorus) in predominant agricultural river basins may have a great influence on water quality. Here the study area Mun River Basin is approximately of 69,701 km/sup 2/ and in 1994, out of the total basin area 'about 80 percent was covered by agricultural purposes. Also one of the driest parts of Thailand as well as one of the industrialized provinces in Thailand, Nakhon Ratchasima is situated at the upstream of the river. Accordingly the downstream part Ubon Ratchathani seems totally agricultural based area. To get the water quality changing trends due to land use, there are around forty water quality parameters has considered for the last ten years along with the basins hydrological parameters. For this study based on the fifteen years rainfall data, the whole year divided into two seasons namely wet season (May to October) and dry season (November to April). The result shows: (1) most of the physicochemical parameters are high in wet season; (2) heavy metals moreover appear higher at wet season and (3) although the presences of pesticides are very nominal, the higher values are detected at wet season. The conclusion draws for the water quality by having wet season water sampling and then the testing of water samples for selected seven parameters whereas the water samples are collected at a duration of one-week to three-week from April to October 2004. And this short duration analysis shows that the mean value of the nutrient shows not only higher at wet season (May to October) than April's data also exceed the existing Thailand's surface water quality standard. (author)

Death Valley regional ground-water flow system, Nevada and California -- hydrogeologic framework and transient ground-water flow model

Science.gov (United States)

Belcher, Wayne R.

2004-01-01

provided by acquiring additional data, by reevaluating existing data using current technology and concepts, and by refining earlier interpretations to reflect the current understanding of the regional ground-water flow system. Ground-water flow in the Death Valley region is composed of several interconnected, complex ground-water flow systems. Ground-water flow occurs in three subregions in relatively shallow and localized flow paths that are superimposed on deeper, regional flow paths. Regional ground-water flow is predominantly through a thick Paleozoic carbonate rock sequence affected by complex geologic structures from regional faulting and fracturing that can enhance or impede flow. Spring flow and evapotranspiration (ET) are the dominant natural ground-water discharge processes. Ground water also is withdrawn for agricultural, commercial, and domestic uses. Ground-water flow in the DVRFS was simulated using MODFLOW-2000, a 3D finite-difference modular ground-water flow modeling code that incorporates a nonlinear least-squares regression technique to estimate aquifer parameters. The DVRFS model has 16 layers of defined thickness, a finite-difference grid consisting of 194 rows and 160 columns, and uniform cells 1,500 m on each side. Prepumping conditions (before 1913) were used as the initial conditions for the transient-state calibration. The model uses annual stress periods with discrete recharge and discharge components. Recharge occurs mostly from infiltration of precipitation and runoff on high mountain ranges and from a small amount of underflow from adjacent basins. Discharge occurs primarily through ET and spring discharge (both simulated as drains) and water withdrawal by pumping and, to a lesser amount, by underflow to adjacent basins, also simulated by drains. All parameter values estimated by the regression are reasonable and within the range of expected values. The simulated hydraulic heads of the final calibrated transient model gener

Calibration by Hydrological Response Unit of a National Hydrologic Model to Improve Spatial Representation and Distribution of Parameters

Science.gov (United States)

Norton, P. A., II

2015-12-01

The U. S. Geological Survey is developing a National Hydrologic Model (NHM) to support consistent hydrologic modeling across the conterminous United States (CONUS). The Precipitation-Runoff Modeling System (PRMS) simulates daily hydrologic and energy processes in watersheds, and is used for the NHM application. For PRMS each watershed is divided into hydrologic response units (HRUs); by default each HRU is assumed to have a uniform hydrologic response. The Geospatial Fabric (GF) is a database containing initial parameter values for input to PRMS and was created for the NHM. The parameter values in the GF were derived from datasets that characterize the physical features of the entire CONUS. The NHM application is composed of more than 100,000 HRUs from the GF. Selected parameter values commonly are adjusted by basin in PRMS using an automated calibration process based on calibration targets, such as streamflow. Providing each HRU with distinct values that captures variability within the CONUS may improve simulation performance of the NHM. During calibration of the NHM by HRU, selected parameter values are adjusted for PRMS based on calibration targets, such as streamflow, snow water equivalent (SWE) and actual evapotranspiration (AET). Simulated SWE, AET, and runoff were compared to value ranges derived from multiple sources (e.g. the Snow Data Assimilation System, the Moderate Resolution Imaging Spectroradiometer (i.e. MODIS) Global Evapotranspiration Project, the Simplified Surface Energy Balance model, and the Monthly Water Balance Model). This provides each HRU with a distinct set of parameter values that captures the variability within the CONUS, leading to improved model performance. We present simulation results from the NHM after preliminary calibration, including the results of basin-level calibration for the NHM using: 1) default initial GF parameter values, and 2) parameter values calibrated by HRU.

Parameter discovery in stochastic biological models using simulated annealing and statistical model checking.

Science.gov (United States)

Hussain, Faraz; Jha, Sumit K; Jha, Susmit; Langmead, Christopher J

2014-01-01

Stochastic models are increasingly used to study the behaviour of biochemical systems. While the structure of such models is often readily available from first principles, unknown quantitative features of the model are incorporated into the model as parameters. Algorithmic discovery of parameter values from experimentally observed facts remains a challenge for the computational systems biology community. We present a new parameter discovery algorithm that uses simulated annealing, sequential hypothesis testing, and statistical model checking to learn the parameters in a stochastic model. We apply our technique to a model of glucose and insulin metabolism used for in-silico validation of artificial pancreata and demonstrate its effectiveness by developing parallel CUDA-based implementation for parameter synthesis in this model.

Establishing statistical models of manufacturing parameters

International Nuclear Information System (INIS)

Senevat, J.; Pape, J.L.; Deshayes, J.F.

1991-01-01

This paper reports on the effect of pilgering and cold-work parameters on contractile strain ratio and mechanical properties that were investigated using a large population of Zircaloy tubes. Statistical models were established between: contractile strain ratio and tooling parameters, mechanical properties (tensile test, creep test) and cold-work parameters, and mechanical properties and stress-relieving temperature

Modeling Jambo wastewater treatment system to predict water re ...

African Journals Online (AJOL)

The main objective of this study was twofold: (i) to investigate how processes can be efficiently improved and optimized for environmental safety, and (ii) to develop Dev C++ programme to implement Brown's model for determining water quality usage of the effluent of the factory. Specifically, wastewater parameters ...

Simultaneous state-parameter estimation supports the evaluation of data assimilation performance and measurement design for soil-water-atmosphere-plant system

Science.gov (United States)

Hu, Shun; Shi, Liangsheng; Zha, Yuanyuan; Williams, Mathew; Lin, Lin

2017-12-01

Improvements to agricultural water and crop managements require detailed information on crop and soil states, and their evolution. Data assimilation provides an attractive way of obtaining these information by integrating measurements with model in a sequential manner. However, data assimilation for soil-water-atmosphere-plant (SWAP) system is still lack of comprehensive exploration due to a large number of variables and parameters in the system. In this study, simultaneous state-parameter estimation using ensemble Kalman filter (EnKF) was employed to evaluate the data assimilation performance and provide advice on measurement design for SWAP system. The results demonstrated that a proper selection of state vector is critical to effective data assimilation. Especially, updating the development stage was able to avoid the negative effect of ;phenological shift;, which was caused by the contrasted phenological stage in different ensemble members. Simultaneous state-parameter estimation (SSPE) assimilation strategy outperformed updating-state-only (USO) assimilation strategy because of its ability to alleviate the inconsistency between model variables and parameters. However, the performance of SSPE assimilation strategy could deteriorate with an increasing number of uncertain parameters as a result of soil stratification and limited knowledge on crop parameters. In addition to the most easily available surface soil moisture (SSM) and leaf area index (LAI) measurements, deep soil moisture, grain yield or other auxiliary data were required to provide sufficient constraints on parameter estimation and to assure the data assimilation performance. This study provides an insight into the response of soil moisture and grain yield to data assimilation in SWAP system and is helpful for soil moisture movement and crop growth modeling and measurement design in practice.

Modelling and interpreting the isotopic composition of water vapour in convective updrafts

Directory of Open Access Journals (Sweden)

M. Bolot

2013-08-01

Full Text Available The isotopic compositions of water vapour and its condensates have long been used as tracers of the global hydrological cycle, but may also be useful for understanding processes within individual convective clouds. We review here the representation of processes that alter water isotopic compositions during processing of air in convective updrafts and present a unified model for water vapour isotopic evolution within undiluted deep convective cores, with a special focus on the out-of-equilibrium conditions of mixed-phase zones where metastable liquid water and ice coexist. We use our model to show that a combination of water isotopologue measurements can constrain critical convective parameters, including degree of supersaturation, supercooled water content and glaciation temperature. Important isotopic processes in updrafts include kinetic effects that are a consequence of diffusive growth or decay of cloud particles within a supersaturated or subsaturated environment; isotopic re-equilibration between vapour and supercooled droplets, which buffers isotopic distillation; and differing mechanisms of glaciation (droplet freezing vs. the Wegener–Bergeron–Findeisen process. As all of these processes are related to updraft strength, particle size distribution and the retention of supercooled water, isotopic measurements can serve as a probe of in-cloud conditions of importance to convective processes. We study the sensitivity of the profile of water vapour isotopic composition to differing model assumptions and show how measurements of isotopic composition at cloud base and cloud top alone may be sufficient to retrieve key cloud parameters.

Modelling and interpreting the isotopic composition of water vapour in convective updrafts

Science.gov (United States)

Bolot, M.; Legras, B.; Moyer, E. J.

2013-08-01

The isotopic compositions of water vapour and its condensates have long been used as tracers of the global hydrological cycle, but may also be useful for understanding processes within individual convective clouds. We review here the representation of processes that alter water isotopic compositions during processing of air in convective updrafts and present a unified model for water vapour isotopic evolution within undiluted deep convective cores, with a special focus on the out-of-equilibrium conditions of mixed-phase zones where metastable liquid water and ice coexist. We use our model to show that a combination of water isotopologue measurements can constrain critical convective parameters, including degree of supersaturation, supercooled water content and glaciation temperature. Important isotopic processes in updrafts include kinetic effects that are a consequence of diffusive growth or decay of cloud particles within a supersaturated or subsaturated environment; isotopic re-equilibration between vapour and supercooled droplets, which buffers isotopic distillation; and differing mechanisms of glaciation (droplet freezing vs. the Wegener-Bergeron-Findeisen process). As all of these processes are related to updraft strength, particle size distribution and the retention of supercooled water, isotopic measurements can serve as a probe of in-cloud conditions of importance to convective processes. We study the sensitivity of the profile of water vapour isotopic composition to differing model assumptions and show how measurements of isotopic composition at cloud base and cloud top alone may be sufficient to retrieve key cloud parameters.

Modelling and intepreting the isotopic composition of water vapour in convective updrafts

Science.gov (United States)

Bolot, M.; Legras, B.; Moyer, E. J.

2012-08-01

The isotopic compositions of water vapour and its condensates have long been used as tracers of the global hydrological cycle, but may also be useful for understanding processes within individual convective clouds. We review here the representation of processes that alter water isotopic compositions during processing of air in convective updrafts and present a unified model for water vapour isotopic evolution within undiluted deep convective cores, with a special focus on the out-of-equilibrium conditions of mixed phase zones where metastable liquid water and ice coexist. We use our model to show that a combination of water isotopologue measurements can constrain critical convective parameters including degree of supersaturation, supercooled water content and glaciation temperature. Important isotopic processes in updrafts include kinetic effects that are a consequence of diffusive growth or decay of cloud particles within a supersaturated or subsaturated environment; isotopic re-equilibration between vapour and supercooled droplets, which buffers isotopic distillation; and differing mechanisms of glaciation (droplet freezing vs. the Wegener-Bergeron-Findeisen process). As all of these processes are related to updraft strength, droplet size distribution and the retention of supercooled water, isotopic measurements can serve as a probe of in-cloud conditions of importance to convective processes. We study the sensitivity of the profile of water vapour isotopic composition to differing model assumptions and show how measurements of isotopic composition at cloud base and cloud top alone may be sufficient to retrieve key cloud parameters.

Modified Feddes type stress reduction function for modeling root water uptake: Accounting for limited aeration and low water potential

Science.gov (United States)

Peters, Andre; Durner, Wolfgang; Iden, Sascha C.

2017-04-01

Modeling water flow in the soil-plant-atmosphere continuum with the Richards equation requires a model for the sink term describing water uptake by plant roots. Despite recent progress in developing process-based models of water uptake by plant roots and water flow in aboveground parts of vegetation, effective models of root water uptake are widely applied and necessary for large-scale applications. Modeling root water uptake consists of three steps, (i) specification of the spatial distribution of potential uptake, (ii) reduction of uptake due to various stress sources, and (iii) enhancement of uptake in part of the simulation domain to describe compensation. We discuss the conceptual shortcomings of the frequently used root water uptake model of Feddes and suggest a simple but effective improvement of the model. The improved model parametrizes water stress in wet soil by a reduction scheme which is formulated as function of air content where water stress due to low soil water potential is described by the original approach of Feddes. The improved model is physically more consistent than Feddes' model because water uptake in wet soil is limited by aeration which is a function of water content. The suggested modification is particularly relevant for simulations in heterogeneous soils, because stress parameters are uniquely defined for the entire simulation domain, irrespective of soil texture. Numerical simulations of water flow and root water uptake in homogeneous and stochastic heterogeneous soils illustrate the effect of the new model on root water uptake and actual transpiration. For homogeneous fine-textured soils, root water uptake never achieves its potential rate. In stochastic heterogeneous soil, water uptake is more pronounced at the interfaces between fine and coarse regions which has potential implications for plant growth, nutrient uptake and depletion.

Some tests for parameter constancy in cointegrated VAR-models

DEFF Research Database (Denmark)

Hansen, Henrik; Johansen, Søren

1999-01-01

Some methods for the evaluation of parameter constancy in vector autoregressive (VAR) models are discussed. Two different ways of re-estimating the VAR model are proposed; one in which all parameters are estimated recursively based upon the likelihood function for the first observations, and anot...... be applied to test the constancy of the long-run parameters in the cointegrated VAR-model. All results are illustrated using a model for the term structure of interest rates on US Treasury securities. ......Some methods for the evaluation of parameter constancy in vector autoregressive (VAR) models are discussed. Two different ways of re-estimating the VAR model are proposed; one in which all parameters are estimated recursively based upon the likelihood function for the first observations......, and another in which the cointegrating relations are estimated recursively from a likelihood function, where the short-run parameters have been concentrated out. We suggest graphical procedures based on recursively estimated eigenvalues to evaluate the constancy of the long-run parameters in the model...

Edge Modeling by Two Blur Parameters in Varying Contrasts.

Science.gov (United States)

Seo, Suyoung

2018-06-01

This paper presents a method of modeling edge profiles with two blur parameters, and estimating and predicting those edge parameters with varying brightness combinations and camera-to-object distances (COD). First, the validity of the edge model is proven mathematically. Then, it is proven experimentally with edges from a set of images captured for specifically designed target sheets and with edges from natural images. Estimation of the two blur parameters for each observed edge profile is performed with a brute-force method to find parameters that produce global minimum errors. Then, using the estimated blur parameters, actual blur parameters of edges with arbitrary brightness combinations are predicted using a surface interpolation method (i.e., kriging). The predicted surfaces show that the two blur parameters of the proposed edge model depend on both dark-side edge brightness and light-side edge brightness following a certain global trend. This is similar across varying CODs. The proposed edge model is compared with a one-blur parameter edge model using experiments of the root mean squared error for fitting the edge models to each observed edge profile. The comparison results suggest that the proposed edge model has superiority over the one-blur parameter edge model in most cases where edges have varying brightness combinations.

Definition and solution of a stochastic inverse problem for the Manning's n parameter field in hydrodynamic models

Science.gov (United States)

Butler, T.; Graham, L.; Estep, D.; Dawson, C.; Westerink, J. J.

2015-04-01

The uncertainty in spatially heterogeneous Manning's n fields is quantified using a novel formulation and numerical solution of stochastic inverse problems for physics-based models. The uncertainty is quantified in terms of a probability measure and the physics-based model considered here is the state-of-the-art ADCIRC model although the presented methodology applies to other hydrodynamic models. An accessible overview of the formulation and solution of the stochastic inverse problem in a mathematically rigorous framework based on measure theory is presented. Technical details that arise in practice by applying the framework to determine the Manning's n parameter field in a shallow water equation model used for coastal hydrodynamics are presented and an efficient computational algorithm and open source software package are developed. A new notion of "condition" for the stochastic inverse problem is defined and analyzed as it relates to the computation of probabilities. This notion of condition is investigated to determine effective output quantities of interest of maximum water elevations to use for the inverse problem for the Manning's n parameter and the effect on model predictions is analyzed.

Identifiability of altimetry-based rating curve parameters in function of river morphological parameters

Science.gov (United States)

Paris, Adrien; André Garambois, Pierre; Calmant, Stéphane; Paiva, Rodrigo; Walter, Collischonn; Santos da Silva, Joecila; Medeiros Moreira, Daniel; Bonnet, Marie-Paule; Seyler, Frédérique; Monnier, Jérôme

2016-04-01

Estimating river discharge for ungauged river reaches from satellite measurements is not straightforward given the nonlinearity of flow behavior with respect to measurable and non measurable hydraulic parameters. As a matter of facts, current satellite datasets do not give access to key parameters such as river bed topography and roughness. A unique set of almost one thousand altimetry-based rating curves was built by fit of ENVISAT and Jason-2 water stages with discharges obtained from the MGB-IPH rainfall-runoff model in the Amazon basin. These rated discharges were successfully validated towards simulated discharges (Ens = 0.70) and in-situ discharges (Ens = 0.71) and are not mission-dependent. The rating curve writes Q = a(Z-Z0)b*sqrt(S), with Z the water surface elevation and S its slope gained from satellite altimetry, a and b power law coefficient and exponent and Z0 the river bed elevation such as Q(Z0) = 0. For several river reaches in the Amazon basin where ADCP measurements are available, the Z0 values are fairly well validated with a relative error lower than 10%. The present contribution aims at relating the identifiability and the physical meaning of a, b and Z0given various hydraulic and geomorphologic conditions. Synthetic river bathymetries sampling a wide range of rivers and inflow discharges are used to perform twin experiments. A shallow water model is run for generating synthetic satellite observations, and then rating curve parameters are determined for each river section thanks to a MCMC algorithm. Thanks to twin experiments, it is shown that rating curve formulation with water surface slope, i.e. closer from Manning equation form, improves parameter identifiability. The compensation between parameters is limited, especially for reaches with little water surface variability. Rating curve parameters are analyzed for riffle and pools for small to large rivers, different river slopes and cross section shapes. It is shown that the river bed

Fuzzy rule-based modelling for human health risk from naturally occurring radioactive materials in produced water

International Nuclear Information System (INIS)

Shakhawat, Chowdhury; Tahir, Husain; Neil, Bose

2006-01-01

Produced water, discharged from offshore oil and gas operations, contains chemicals from formation water, condensed water, and any chemical added down hole or during the oil/water separation process. Although, most of the contaminants fall below the detection limits within a short distance from the discharge port, a few of the remaining contaminants including naturally occurring radioactive materials (NORM) are of concern due to their bioavailability in the media and bioaccumulation characteristics in finfish and shellfish species used for human consumption. In the past, several initiatives have been taken to model human health risk from NORM in produced water. The parameters of the available risk assessment models are imprecise and sparse in nature. In this study, a fuzzy possibilistic evaluation using fuzzy rule based modeling has been presented. Being conservative in nature, the possibilistic approach considers possible input parameter values; thus provides better environmental prediction than the Monte Carlo (MC) calculation. The uncertainties of the input parameters were captured with fuzzy triangular membership functions (TFNs). Fuzzy if-then rules were applied for input concentrations of two isotopes of radium, namely 226 Ra, and 228 Ra, available in produced water and bulk dilution to evaluate the radium concentration in fish tissue used for human consumption. The bulk dilution was predicted using four input parameters: produced water discharge rate, ambient seawater velocity, depth of discharge port and density gradient. The evaluated cancer risk shows compliance with the regulatory guidelines; thus minimum risk to human health is expected from NORM components in produced water

Multiobjective constraints for climate model parameter choices: Pragmatic Pareto fronts in CESM1

Science.gov (United States)

Langenbrunner, B.; Neelin, J. D.

2017-09-01

Global climate models (GCMs) are examples of high-dimensional input-output systems, where model output is a function of many variables, and an update in model physics commonly improves performance in one objective function (i.e., measure of model performance) at the expense of degrading another. Here concepts from multiobjective optimization in the engineering literature are used to investigate parameter sensitivity and optimization in the face of such trade-offs. A metamodeling technique called cut high-dimensional model representation (cut-HDMR) is leveraged in the context of multiobjective optimization to improve GCM simulation of the tropical Pacific climate, focusing on seasonal precipitation, column water vapor, and skin temperature. An evolutionary algorithm is used to solve for Pareto fronts, which are surfaces in objective function space along which trade-offs in GCM performance occur. This approach allows the modeler to visualize trade-offs quickly and identify the physics at play. In some cases, Pareto fronts are small, implying that trade-offs are minimal, optimal parameter value choices are more straightforward, and the GCM is well-functioning. In all cases considered here, the control run was found not to be Pareto-optimal (i.e., not on the front), highlighting an opportunity for model improvement through objectively informed parameter selection. Taylor diagrams illustrate that these improvements occur primarily in field magnitude, not spatial correlation, and they show that specific parameter updates can improve fields fundamental to tropical moist processes—namely precipitation and skin temperature—without significantly impacting others. These results provide an example of how basic elements of multiobjective optimization can facilitate pragmatic GCM tuning processes.

Some analytic diagnostic models for transport processes in estuarine and coastal waters

International Nuclear Information System (INIS)

Suarez Antola, R.

2001-03-01

Advection and dispersion processes in estuarine and coastal waters are briefly reviewed. Beginning from the basic macroscopic equations of transport for a substance diluted or suspended in the considered body of water,several levels of filtering in time and space are described and applied to obtain suitable diagnostic mathematical models both with scale effects and gaussian.The solutions of the aforementioned models,for initial distributions and boundary conditions with enough symmetry,are discussed, as well as their applications to a parameter characterization of the transport properties of the receiving body of water

Identifyability measures to select the parameters to be estimated in a solid-state fermentation distributed parameter model.

Science.gov (United States)

da Silveira, Christian L; Mazutti, Marcio A; Salau, Nina P G

2016-07-08

Process modeling can lead to of advantages such as helping in process control, reducing process costs and product quality improvement. This work proposes a solid-state fermentation distributed parameter model composed by seven differential equations with seventeen parameters to represent the process. Also, parameters estimation with a parameters identifyability analysis (PIA) is performed to build an accurate model with optimum parameters. Statistical tests were made to verify the model accuracy with the estimated parameters considering different assumptions. The results have shown that the model assuming substrate inhibition better represents the process. It was also shown that eight from the seventeen original model parameters were nonidentifiable and better results were obtained with the removal of these parameters from the estimation procedure. Therefore, PIA can be useful to estimation procedure, since it may reduce the number of parameters that can be evaluated. Further, PIA improved the model results, showing to be an important procedure to be taken. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:905-917, 2016. © 2016 American Institute of Chemical Engineers.

State and parameter estimation of two land surface models using the ensemble Kalman filter and the particle filter

Directory of Open Access Journals (Sweden)

H. Zhang

2017-09-01

Full Text Available Land surface models (LSMs use a large cohort of parameters and state variables to simulate the water and energy balance at the soil–atmosphere interface. Many of these model parameters cannot be measured directly in the field, and require calibration against measured fluxes of carbon dioxide, sensible and/or latent heat, and/or observations of the thermal and/or moisture state of the soil. Here, we evaluate the usefulness and applicability of four different data assimilation methods for joint parameter and state estimation of the Variable Infiltration Capacity Model (VIC-3L and the Community Land Model (CLM using a 5-month calibration (assimilation period (March–July 2012 of areal-averaged SPADE soil moisture measurements at 5, 20, and 50 cm depths in the Rollesbroich experimental test site in the Eifel mountain range in western Germany. We used the EnKF with state augmentation or dual estimation, respectively, and the residual resampling PF with a simple, statistically deficient, or more sophisticated, MCMC-based parameter resampling method. The performance of the calibrated LSM models was investigated using SPADE water content measurements of a 5-month evaluation period (August–December 2012. As expected, all DA methods enhance the ability of the VIC and CLM models to describe spatiotemporal patterns of moisture storage within the vadose zone of the Rollesbroich site, particularly if the maximum baseflow velocity (VIC or fractions of sand, clay, and organic matter of each layer (CLM are estimated jointly with the model states of each soil layer. The differences between the soil moisture simulations of VIC-3L and CLM are much larger than the discrepancies among the four data assimilation methods. The EnKF with state augmentation or dual estimation yields the best performance of VIC-3L and CLM during the calibration and evaluation period, yet results are in close agreement with the PF using MCMC resampling. Overall, CLM demonstrated the

Environmental Transport Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

M. A. Wasiolek

2003-06-27

This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (TWP) (BSC 2003 [163602]). Some documents in Figure 1-1 may be under development and not available when this report is issued. This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA), but access to the listed documents is not required to understand the contents of this report. This report is one of the reports that develops input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2003 [160699]) describes the conceptual model, the mathematical model, and the input parameters. The purpose of this analysis is to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or volcanic ash). The analysis was performed in accordance with the TWP (BSC 2003 [163602]). This analysis develops values of parameters associated with many features, events, and processes (FEPs) applicable to the reference biosphere (DTN: M00303SEPFEPS2.000 [162452]), which are addressed in the biosphere model (BSC 2003 [160699]). The treatment of these FEPs is described in BSC (2003 [160699

Environmental Transport Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

Wasiolek, M. A.

2003-01-01

This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (TWP) (BSC 2003 [163602]). Some documents in Figure 1-1 may be under development and not available when this report is issued. This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA), but access to the listed documents is not required to understand the contents of this report. This report is one of the reports that develops input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2003 [160699]) describes the conceptual model, the mathematical model, and the input parameters. The purpose of this analysis is to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or volcanic ash). The analysis was performed in accordance with the TWP (BSC 2003 [163602]). This analysis develops values of parameters associated with many features, events, and processes (FEPs) applicable to the reference biosphere (DTN: M00303SEPFEPS2.000 [162452]), which are addressed in the biosphere model (BSC 2003 [160699]). The treatment of these FEPs is described in BSC (2003 [160699], Section 6.2). Parameter values

Parameter estimation in stochastic rainfall-runoff models

DEFF Research Database (Denmark)

Jonsdottir, Harpa; Madsen, Henrik; Palsson, Olafur Petur

2006-01-01

A parameter estimation method for stochastic rainfall-runoff models is presented. The model considered in the paper is a conceptual stochastic model, formulated in continuous-discrete state space form. The model is small and a fully automatic optimization is, therefore, possible for estimating all...... the parameter values are optimal for simulation or prediction. The data originates from Iceland and the model is designed for Icelandic conditions, including a snow routine for mountainous areas. The model demands only two input data series, precipitation and temperature and one output data series...

Water adsorption on goethite: Application of multilayer adsorption models

Science.gov (United States)

Hatch, C. D.; Tumminello, R.; Meredith, R.

2016-12-01

Adsorbed water on the surface of atmospheric mineral dust has recently been shown to significantly affect the ability of mineral dust aerosol to act as cloud condensation nuclei. We have studied water adsorption as a function of relative humidity (RH) on goethite (α-FeO(OH)), a common component of atmospheric mineral dust. The goethite surface area and particle size was determined using BET analysis and with N2 as an adsorbate and scanning electron microscopy, respectively. Water adsorption on the sample was monitored using horizontal attenuated total reflectance Fourier transform infrared (HATR-FTIR) spectroscopy equipped with a flow cell. Water content was determined using Beer's law and the optical constants for bulk water. The results were analyzed using Type II adsorption isotherms to model multilayer adsorption, including BET (Brunauer, Emmet and Teller), FHH (Frenkel, Halsey and Hill) and Freundlich. BET fits to experimental data provide parameters of monolayer coverage, while the FHH and Freundlich isotherms provide insights into multilayer adsorption mechanisms. Results indicate that goethite contains 5% H2O by mass at 50% RH, which increases to 12% by mass at 90% RH. Adsorption parameters and experimental results will be presented.

Evaluating Outdoor Water Use Demand under Changing Climatic and Demographic Conditions: An Agent-based Modeling Approach

Science.gov (United States)

Kanta, L.; Berglund, E. Z.; Soh, M. H.

2017-12-01

Outdoor water-use for landscape and irrigation constitutes a significant end-use in total residential water demand. In periods of water shortages, utilities may reduce garden demands by implementing irrigation system audits, rebate programs, local ordinances, and voluntary or mandatory water-use restrictions. Because utilities do not typically record outdoor and indoor water-uses separately, the effects of policies for reducing garden demands cannot be readily calculated. The volume of water required to meet garden demands depends on the housing density, lawn size, type of vegetation, climatic conditions, efficiency of garden irrigation systems, and consumer water-use behaviors. Many existing outdoor demand estimation methods are deterministic and do not include consumer responses to conservation campaigns. In addition, mandatory restrictions may have a substantial impact on reducing outdoor demands, but the effectiveness of mandatory restrictions depends on the timing and the frequency of restrictions, in addition to the distribution of housing density and consumer types within a community. This research investigates a garden end-use model by coupling an agent-based modeling approach and a mechanistic-stochastic water demand model to create a methodology for estimating garden demand and evaluating demand reduction policies. The garden demand model is developed for two water utilities, using a diverse data sets, including residential customer billing records, outdoor conservation programs, frequency and type of mandatory water-use restrictions, lot size distribution, population growth, and climatic data. A set of garden irrigation parameter values, which are based on the efficiency of irrigation systems and irrigation habits of consumers, are determined for a set of conservation ordinances and restrictions. The model parameters are then validated using customer water usage data from the participating water utilities. A sensitivity analysis is conducted for garden

A method for model identification and parameter estimation

International Nuclear Information System (INIS)

Bambach, M; Heinkenschloss, M; Herty, M

2013-01-01

We propose and analyze a new method for the identification of a parameter-dependent model that best describes a given system. This problem arises, for example, in the mathematical modeling of material behavior where several competing constitutive equations are available to describe a given material. In this case, the models are differential equations that arise from the different constitutive equations, and the unknown parameters are coefficients in the constitutive equations. One has to determine the best-suited constitutive equations for a given material and application from experiments. We assume that the true model is one of the N possible parameter-dependent models. To identify the correct model and the corresponding parameters, we can perform experiments, where for each experiment we prescribe an input to the system and observe a part of the system state. Our approach consists of two stages. In the first stage, for each pair of models we determine the experiment, i.e. system input and observation, that best differentiates between the two models, and measure the distance between the two models. Then we conduct N(N − 1) or, depending on the approach taken, N(N − 1)/2 experiments and use the result of the experiments as well as the previously computed model distances to determine the true model. We provide sufficient conditions on the model distances and measurement errors which guarantee that our approach identifies the correct model. Given the model, we identify the corresponding model parameters in the second stage. The problem in the second stage is a standard parameter estimation problem and we use a method suitable for the given application. We illustrate our approach on three examples, including one where the models are elliptic partial differential equations with different parameterized right-hand sides and an example where we identify the constitutive equation in a problem from computational viscoplasticity. (paper)

Integrated hydrologic and hydrodynamic modeling to assess water exchange in a data-scarce reservoir

Science.gov (United States)

Wu, Binbin; Wang, Guoqiang; Wang, Zhonggen; Liu, Changming; Ma, Jianming

2017-12-01

Integrated hydrologic and hydrodynamic modeling is useful in evaluating hydrodynamic characteristics (e.g. water exchange processes) in data-scarce water bodies, however, most studies lack verification of the hydrologic model. Here, water exchange (represented by water age) was investigated through integrated hydrologic and hydrodynamic modeling of the Hongfeng Reservoir, a poorly gauged reservoir in southwest China. The performance of the hydrologic model and parameter replacement among sub-basins with hydrological similarity was verified by historical data. Results showed that hydrological similarity based on the hierarchical cluster analysis and topographic index probability density distribution was reliable with satisfactory performance of parameter replacement. The hydrodynamic model was verified using daily water levels and water temperatures from 2009 and 2010. The water exchange processes in the Hongfeng Reservoir are very complex with temporal, vertical, and spatial variations. The temporal water age was primarily controlled by the variable inflow and outflow, and the maximum and minimum ages for the site near the dam were 406.10 d (15th June) and 90.74 d (3rd August), respectively, in 2010. Distinct vertical differences in water age showed that surface flow, interflow, and underflow appeared alternately, depending on the season and water depth. The worst water exchange situation was found in the central areas of the North Lake with the highest water ages in the bottom on both 15th June and 3rd August, in 2010. Comparison of the spatial water ages revealed that the more favorable hydraulic conditions on 3rd August mainly improved the water exchange in the dam areas and most areas of the South Lake, but had little effect on the bottom layers of the other deepest areas in the South and North Lakes. The presented framework can be applied in other data-scarce waterbodies worldwide to provide better understanding of water exchange processes.

Post-mining water treatment. Nanofiltration of uranium-contaminated drainage. Experiments and modeling

Energy Technology Data Exchange (ETDEWEB)

Hoyer, Michael

2017-07-01

Nanofiltration of real uranium-contaminated mine drainage was successfully discussed in experiments and modeling. For the simulation a renowned model was adapted that is capable of describing multi-component solutions. Although the description of synthetic multi-component solutions with a limited number of components was performed before ([Garcia-Aleman2004], [Geraldes2006], [Bandini2003]) the results of this work show that the adapted model is capable of describing the very complex solution. The model developed here is based on: The Donnan-Steric Partitioning Pore Model incorporating Dielectric Exclusion - DSPM and DE ref. [Bowen1997], [Bandini2003], [Bowen2002], [Vezzani2002]. The steric, electric, and dielectric exclusion model - SEDE ref. [Szymczyk2005]. The developed modeling approach is capable of describing multi-component transport, and is based on the pore radius, membrane thickness, and volumetric membrane charge density as physically relevant membrane parameters instead of mere fitting parameters which allows conclusions concerning membrane modification or process design. The experiments involve typical commercially available membranes in combination with a water sample of industrial relevance in the mining sector. Furthermore, it has been shown experimentally that uranium speciation influences its retention. Hence, all experiments consider the speciation of uranium when assessing its charge and size. In the simulation 10 different ionic components have been taken into account. By freely fitting 4 parameters in parallel (pore radius, membrane thickness, membrane charge, relative permittivity of the oriented water layer at the pore wall) an excellent agreement between experiment and simulation was obtained. Moreover, the determined membrane thickness and pore radius is in close agreement with the values obtained by independent membrane characterization using pure water permeability and glucose retention. On the other hand, the fitted and the literature

Post-mining water treatment. Nanofiltration of uranium-contaminated drainage. Experiments and modeling

International Nuclear Information System (INIS)

Hoyer, Michael

2017-01-01

Nanofiltration of real uranium-contaminated mine drainage was successfully discussed in experiments and modeling. For the simulation a renowned model was adapted that is capable of describing multi-component solutions. Although the description of synthetic multi-component solutions with a limited number of components was performed before ([Garcia-Aleman2004], [Geraldes2006], [Bandini2003]) the results of this work show that the adapted model is capable of describing the very complex solution. The model developed here is based on: The Donnan-Steric Partitioning Pore Model incorporating Dielectric Exclusion - DSPM and DE ref. [Bowen1997], [Bandini2003], [Bowen2002], [Vezzani2002]. The steric, electric, and dielectric exclusion model - SEDE ref. [Szymczyk2005]. The developed modeling approach is capable of describing multi-component transport, and is based on the pore radius, membrane thickness, and volumetric membrane charge density as physically relevant membrane parameters instead of mere fitting parameters which allows conclusions concerning membrane modification or process design. The experiments involve typical commercially available membranes in combination with a water sample of industrial relevance in the mining sector. Furthermore, it has been shown experimentally that uranium speciation influences its retention. Hence, all experiments consider the speciation of uranium when assessing its charge and size. In the simulation 10 different ionic components have been taken into account. By freely fitting 4 parameters in parallel (pore radius, membrane thickness, membrane charge, relative permittivity of the oriented water layer at the pore wall) an excellent agreement between experiment and simulation was obtained. Moreover, the determined membrane thickness and pore radius is in close agreement with the values obtained by independent membrane characterization using pure water permeability and glucose retention. On the other hand, the fitted and the literature

Geochemical studies of fluoride and other water quality parameters of ground water in Dhule region Maharashtra, India.

Science.gov (United States)

Patil, Dilip A; Deshmukh, Prashant K; Fursule, Ravindra A; Patil, Pravin O

2010-07-01

This study has been carried out to find out the water pollutants and to test the suitability of water for drinking and irrigation purposes in Dhule and surrounding areas in Maharashtra State in India. The analysis was carried out for the parameters pH, DO (dissolved oxygen), BOD (biological oxygen demand), Cl-, NO3-, F-, S(2)-, total alkalinity, total solid, total dissolved solids (TDS), total suspended solids (TSS), total hardness, calcium, magnesium, carbonate and noncarbonate hardness, and concentrations of calcium and magnesium. These parameters were compared against the standards laid down by World Health Organization (WHO) and Indian Council of Medical Research (ICMR) for drinking water quality. High levels of NO(3)-, Cl-, F-, S(2)-, total solid, TDS, TSS, total hardness, magnesium and calcium have been found in the collected samples. From these observations, it has been found that fluoride is present as per the permissible limit (WHO 2003) in some of the villages studied, but both fluoride and nitrate levels are unacceptable in drinking water samples taken from several villages in Dhule. This is a serious problem and, therefore, requires immediate attention. Excess of theses impurities in water causes many diseases in plants and animals. This study has been carried out to find out the water pollutants and to test the suitability of water for drinking and irrigation purposes in Dhule and surrounding areas in Maharashtra.

Assessing the Impact of Model Parameter Uncertainty in Simulating Grass Biomass Using a Hybrid Carbon Allocation Strategy

Science.gov (United States)

Reyes, J. J.; Adam, J. C.; Tague, C.

2016-12-01

Grasslands play an important role in agricultural production as forage for livestock; they also provide a diverse set of ecosystem services including soil carbon (C) storage. The partitioning of C between above and belowground plant compartments (i.e. allocation) is influenced by both plant characteristics and environmental conditions. The objectives of this study are to 1) develop and evaluate a hybrid C allocation strategy suitable for grasslands, and 2) apply this strategy to examine the importance of various parameters related to biogeochemical cycling, photosynthesis, allocation, and soil water drainage on above and belowground biomass. We include allocation as an important process in quantifying the model parameter uncertainty, which identifies the most influential parameters and what processes may require further refinement. For this, we use the Regional Hydro-ecologic Simulation System, a mechanistic model that simulates coupled water and biogeochemical processes. A Latin hypercube sampling scheme was used to develop parameter sets for calibration and evaluation of allocation strategies, as well as parameter uncertainty analysis. We developed the hybrid allocation strategy to integrate both growth-based and resource-limited allocation mechanisms. When evaluating the new strategy simultaneously for above and belowground biomass, it produced a larger number of less biased parameter sets: 16% more compared to resource-limited and 9% more compared to growth-based. This also demonstrates its flexible application across diverse plant types and environmental conditions. We found that higher parameter importance corresponded to sub- or supra-optimal resource availability (i.e. water, nutrients) and temperature ranges (i.e. too hot or cold). For example, photosynthesis-related parameters were more important at sites warmer than the theoretical optimal growth temperature. Therefore, larger values of parameter importance indicate greater relative sensitivity in

A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques

Directory of Open Access Journals (Sweden)

Mohammad Haji Gholizadeh

2016-08-01

Full Text Available Remotely sensed data can reinforce the abilities of water resources researchers and decision makers to monitor waterbodies more effectively. Remote sensing techniques have been widely used to measure the qualitative parameters of waterbodies (i.e., suspended sediments, colored dissolved organic matter (CDOM, chlorophyll-a, and pollutants. A large number of different sensors on board various satellites and other platforms, such as airplanes, are currently used to measure the amount of radiation at different wavelengths reflected from the water’s surface. In this review paper, various properties (spectral, spatial and temporal, etc. of the more commonly employed spaceborne and airborne sensors are tabulated to be used as a sensor selection guide. Furthermore, this paper investigates the commonly used approaches and sensors employed in evaluating and quantifying the eleven water quality parameters. The parameters include: chlorophyll-a (chl-a, colored dissolved organic matters (CDOM, Secchi disk depth (SDD, turbidity, total suspended sediments (TSS, water temperature (WT, total phosphorus (TP, sea surface salinity (SSS, dissolved oxygen (DO, biochemical oxygen demand (BOD and chemical oxygen demand (COD.

Experimental research on dispersion parameters of ground water around the area of CIAE

International Nuclear Information System (INIS)

Yu Jun

1993-01-01

The dispersion are important parameters in modeling the migration of pollutant in the ground water. Due to the complexity of geological media, variant dispersion is expected according to the difference of the geological media. Three parts are included in physical simulation in the laboratory column, tracer experiment in the field and the prediction of dispersion using the stochastic model. Experimental results show that the dispersion obtained in the column are three orders of magnitude smaller than that obtained in the field. Using the field values of conductivity and stochastic theory, the calculated asymptotic longitudinal and lateral dispersion are 370 and 0.45 meters respectively and the correlation length is 400 meters approximately. Using the dispersion obtained from the formula in the paper can enhance the precision of the model prediction, the distance heeded to reach the Fick's dispersion is 6 km approximately

Application of lumped-parameter models

DEFF Research Database (Denmark)

Ibsen, Lars Bo; Liingaard, Morten

This technical report concerns the lumped-parameter models for a suction caisson with a ratio between skirt length and foundation diameter equal to 1/2, embedded into an viscoelastic soil. The models are presented for three different values of the shear modulus of the subsoil (section 1.1). Subse...

Extending a Consensus-based Fuzzy Ordered Weighting Average (FOWA Model in New Water Quality Indices

Directory of Open Access Journals (Sweden)

Mohammad Ali Baghapour

2017-07-01

Full Text Available In developing a specific WQI (Water Quality Index, many quality parameters are involved with different levels of importance. The impact of experts’ different opinions and viewpoints, current risks affecting their opinions, and plurality of the involved parameters double the significance of the issue. Hence, the current study tries to apply a consensus-based FOWA (Fuzzy Ordered Weighting Average model as one of the most powerful and well-known Multi-Criteria Decision- Making (MCDM techniques to determine the importance of the used parameters in the development of such WQIs which is shown with an example. This operator has provided the capability of modeling the risks in decision-making through applying the optimistic degree of stakeholders and their power coupled with the use of fuzzy numbers. Totally, 22 water quality parameters for drinking purposes were considered in this study. To determine the weight of each parameter, the viewpoints of 4 decision-making groups of experts were taken into account. After determining the final weights, to validate the use of each parameter in a potential WQI, consensus degrees of both the decision makers and the parameters are calculated. The highest and the lowest weight values, 0.999 and 0.073 respectively, were related to Hg and temperature. Regarding the type of consumption that was drinking, the parameters’ weights and ranks were consistent with their health impacts. Moreover, the decision makers’ highest and lowest consensus degrees were 0.9905 and 0.9669, respectively. Among the water quality parameters, temperature (with consensus degree of 0.9972 and Pb (with consensus degree of 0.9665, received the highest and lowest agreement with the decision-making group. This study indicated that the weight of parameters in determining water quality largely depends on the experts’ opinions and approaches. Moreover, using the FOWA model provides results accurate and closer- to-reality on the significance of

A simple three-dimensional macroscopic root water uptake model based on the hydraulic architecture approach

Directory of Open Access Journals (Sweden)

V. Couvreur

2012-08-01

Full Text Available Many hydrological models including root water uptake (RWU do not consider the dimension of root system hydraulic architecture (HA because explicitly solving water flow in such a complex system is too time consuming. However, they might lack process understanding when basing RWU and plant water stress predictions on functions of variables such as the root length density distribution. On the basis of analytical solutions of water flow in a simple HA, we developed an "implicit" model of the root system HA for simulation of RWU distribution (sink term of Richards' equation and plant water stress in three-dimensional soil water flow models. The new model has three macroscopic parameters defined at the soil element scale, or at the plant scale, rather than for each segment of the root system architecture: the standard sink fraction distribution SSF, the root system equivalent conductance K_rs and the compensatory RWU conductance K_comp. It clearly decouples the process of water stress from compensatory RWU, and its structure is appropriate for hydraulic lift simulation. As compared to a model explicitly solving water flow in a realistic maize root system HA, the implicit model showed to be accurate for predicting RWU distribution and plant collar water potential, with one single set of parameters, in dissimilar water dynamics scenarios. For these scenarios, the computing time of the implicit model was a factor 28 to 214 shorter than that of the explicit one. We also provide a new expression for the effective soil water potential sensed by plants in soils with a heterogeneous water potential distribution, which emerged from the implicit model equations. With the proposed implicit model of the root system HA, new concepts are brought which open avenues towards simple and mechanistic RWU models and water stress functions operational for field scale water dynamics simulation.

Are our dynamic water quality models too complex? A comparison of a new parsimonious phosphorus model, SimplyP, and INCA-P

Science.gov (United States)

Jackson-Blake, L. A.; Sample, J. E.; Wade, A. J.; Helliwell, R. C.; Skeffington, R. A.

2017-07-01

Catchment-scale water quality models are increasingly popular tools for exploring the potential effects of land management, land use change and climate change on water quality. However, the dynamic, catchment-scale nutrient models in common usage are complex, with many uncertain parameters requiring calibration, limiting their usability and robustness. A key question is whether this complexity is justified. To explore this, we developed a parsimonious phosphorus model, SimplyP, incorporating a rainfall-runoff model and a biogeochemical model able to simulate daily streamflow, suspended sediment, and particulate and dissolved phosphorus dynamics. The model's complexity was compared to one popular nutrient model, INCA-P, and the performance of the two models was compared in a small rural catchment in northeast Scotland. For three land use classes, less than six SimplyP parameters must be determined through calibration, the rest may be based on measurements, while INCA-P has around 40 unmeasurable parameters. Despite substantially simpler process-representation, SimplyP performed comparably to INCA-P in both calibration and validation and produced similar long-term projections in response to changes in land management. Results support the hypothesis that INCA-P is overly complex for the study catchment. We hope our findings will help prompt wider model comparison exercises, as well as debate among the water quality modeling community as to whether today's models are fit for purpose. Simpler models such as SimplyP have the potential to be useful management and research tools, building blocks for future model development (prototype code is freely available), or benchmarks against which more complex models could be evaluated.

Identification of ecosystem parameters by SDE-modelling

DEFF Research Database (Denmark)

Stochastic differential equations (SDEs) for ecosystem modelling have attracted increasing attention during recent years. The modelling has mostly been through simulation experiments in order to analyse how system noise propagates through the ordinary differential equation formulation of ecosystem...... models. Estimation of parameters in SDEs is, however, possible by combining Kalman filter techniques and likelihood estimation. By modelling parameters as random walks it is possible to identify linear as well as non-linear interactions between ecosystem components. By formulating a simple linear SDE...

Distributed parameter modeling and simulation for the evaporation system of a controlled circulation boiler based on 3-D combustion monitoring

International Nuclear Information System (INIS)

Chu Yuntao; Lou Chun; Cheng Qiang; Zhou Huaichun

2008-01-01

In this paper, a dynamic, distributed parameter model for the evaporation system of a controlled circulation boiler was developed. As an essential basis, the 3-D temperature distribution and the average emissivity of the particle phase inside its furnace can be got by a flame image processing technique from multiple, visible flame image detectors in a real-time combustion monitoring system. Then the transient, 2-D radiation flux can be obtained by solving a set of energy balance equations for the water wall elements, which serves as a distributed boundary condition for the dynamic, distributed parameter model proposed for the evaporation system. For large change of the boiler load, two important parameters, the correction factor of equivalent flame emissivity and the coefficient of the steam mass flow rate at the outlet of the drum, were determined using the operation data from a 300 MW boiler. The model was validated by comparing the simulation results for some main steam parameters of the system with those from measurements. Besides that, the transient distributions of the parameters, such as the steam quality and the mass velocity, were predicted by the model. This model can be used for on-line calculation or off-line prediction of the local abnormal phenomena occurring on the water walls, forming an important basis to effectively evaluate the security and the reliability of a power plant boiler

Spatio-temporal modeling of nonlinear distributed parameter systems

CERN Document Server

Li, Han-Xiong

2011-01-01

The purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches. In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein s

History of water quality parameters - a study on the Sinos River/Brazil.

Science.gov (United States)

Konzen, G B; Figueiredo, J A S; Quevedo, D M

2015-05-01

Water is increasingly becoming a valuable resource, constituting one of the central themes of environmental, economic and social discussions. The Sinos River, located in southern Brazil, is the main river from the Sinos River Basin, representing a source of drinking water supply for a highly populated region. Considering its size and importance, it becomes necessary to conduct a study to follow up the water quality of this river, which is considered by some experts as one of the most polluted rivers in Brazil. As for this study, its great importance lies in the historical analysis of indicators. In this sense, we sought to develop aspects related to the management of water resources by performing a historical analysis of the Water Quality Index (WQI) of the Sinos River, using statistical methods. With regard to the methodological procedures, it should be pointed out that this study performs a time analysis of monitoring data on parameters related to a punctual measurement that is variable in time, using statistical tools. The data used refer to analyses of the water quality of the Sinos River (WQI) from the State Environmental Protection Agency Henrique Luiz Roessler (Fundação Estadual de Proteção Ambiental Henrique Luiz Roessler, FEPAM) covering the period between 2000 and 2008, as well as to a theoretical analysis focusing on the management of water resources. The study of WQI and its parameters by statistical analysis has shown to be effective, ensuring its effectiveness as a tool for the management of water resources. The descriptive analysis of the WQI and its parameters showed that the water quality of the Sinos River is concerning low, which reaffirms that it is one of the most polluted rivers in Brazil. It should be highlighted that there was an overall difficulty in obtaining data with the appropriate periodicity, as well as a long complete series, which limited the conduction of statistical studies such as the present one.

Sensitivity of tidal sand wave characteristics to environmental parameters: A combined data analysis and modelling approach

NARCIS (Netherlands)

van Santen, R.B.; de Swart, H.E.; van Dijk, T.A.G.P.

2011-01-01

An integrated field data-modelling approach is employed to investigate relationships between the wavelength of tidal sand waves and four environmental parameters: tidal current amplitude, water depth, tidal ellipticity and median grain size. From echo sounder data at 23 locations on the Dutch

Models for estimating photosynthesis parameters from in situ production profiles

Science.gov (United States)

Kovač, Žarko; Platt, Trevor; Sathyendranath, Shubha; Antunović, Suzana

2017-12-01

The rate of carbon assimilation in phytoplankton primary production models is mathematically prescribed with photosynthesis irradiance functions, which convert a light flux (energy) into a material flux (carbon). Information on this rate is contained in photosynthesis parameters: the initial slope and the assimilation number. The exactness of parameter values is crucial for precise calculation of primary production. Here we use a model of the daily production profile based on a suite of photosynthesis irradiance functions and extract photosynthesis parameters from in situ measured daily production profiles at the Hawaii Ocean Time-series station Aloha. For each function we recover parameter values, establish parameter distributions and quantify model skill. We observe that the choice of the photosynthesis irradiance function to estimate the photosynthesis parameters affects the magnitudes of parameter values as recovered from in situ profiles. We also tackle the problem of parameter exchange amongst the models and the effect it has on model performance. All models displayed little or no bias prior to parameter exchange, but significant bias following parameter exchange. The best model performance resulted from using optimal parameter values. Model formulation was extended further by accounting for spectral effects and deriving a spectral analytical solution for the daily production profile. The daily production profile was also formulated with time dependent growing biomass governed by a growth equation. The work on parameter recovery was further extended by exploring how to extract photosynthesis parameters from information on watercolumn production. It was demonstrated how to estimate parameter values based on a linearization of the full analytical solution for normalized watercolumn production and from the solution itself, without linearization. The paper complements previous works on photosynthesis irradiance models by analysing the skill and consistency of

A coupled classification - evolutionary optimization model for contamination event detection in water distribution systems.

Science.gov (United States)

Oliker, Nurit; Ostfeld, Avi

2014-03-15

This study describes a decision support system, alerts for contamination events in water distribution systems. The developed model comprises a weighted support vector machine (SVM) for the detection of outliers, and a following sequence analysis for the classification of contamination events. The contribution of this study is an improvement of contamination events detection ability and a multi-dimensional analysis of the data, differing from the parallel one-dimensional analysis conducted so far. The multivariate analysis examines the relationships between water quality parameters and detects changes in their mutual patterns. The weights of the SVM model accomplish two goals: blurring the difference between sizes of the two classes' data sets (as there are much more normal/regular than event time measurements), and adhering the time factor attribute by a time decay coefficient, ascribing higher importance to recent observations when classifying a time step measurement. All model parameters were determined by data driven optimization so the calibration of the model was completely autonomic. The model was trained and tested on a real water distribution system (WDS) data set with randomly simulated events superimposed on the original measurements. The model is prominent in its ability to detect events that were only partly expressed in the data (i.e., affecting only some of the measured parameters). The model showed high accuracy and better detection ability as compared to previous modeling attempts of contamination event detection. Copyright © 2013 Elsevier Ltd. All rights reserved.