New, general methods to define the depth separating surface water from deep water, outflow and internal loading for mass-balance models for lakes

2004 ◽  
Vol 175 (4) ◽  
pp. 339-352 ◽  
Author(s):  
Lars Håkanson ◽  
Thorsten Blenckner ◽  
J.Mikael Malmaeus
Keyword(s):  
Surface Water ◽  
Mass Balance ◽  
Deep Water ◽  
Internal Loading ◽  
Mass Balance Models ◽  
Water Outflow

Role of Internal Phosphorus Loading in Two Shallow, Productive Lakes in Alberta, Canada

1984 ◽  
Vol 41 (6) ◽  
pp. 845-855 ◽  
Author(s):  
E. T. Riley ◽  
E. E. Prepas
Keyword(s):  
Surface Water ◽  
Deep Water ◽  
Laboratory Experiments ◽  
Water Exchange ◽  
Sediment Cores ◽  
Internal Loading ◽  
Phosphorus Loading ◽  
Quantitative Estimates ◽  
Internal Phosphorus Loading

The contribution of internal loading from the sediments to the total phosphorus (TP) budget and to the [TP] in the surface water was investigated from May to November in Nakamun and Halfmoon lakes, Alberta. During the summer, Nakamun Lake was intermittently stratified and Halfmoon Lake was weakly, thermally stratified. During the stratified periods, water overlying the sediments was anoxic, TP levels increased in the deep water, and sediments were the main source of TP, contributing 1468 and 147 kg of TP to Nakamun and Halfmoon lakes, respectively. During these same periods, internal loading to Nakamun and Halfmoon lakes (12.7 and 15.6 mg∙m−2∙d−1, respectively) were slightly higher than the rates predicted from laboratory experiments on sediment cores (9.7 and 7.2 mg∙m−2∙d−1, respectively). Quantitative estimates of vertical water exchange in Nakamun Lake and in-lake TP budgets for both lakes indicated that phosphorus released from the sediments was transported to the surface water during mixing. After eight of the nine mixing events that immediatley followed stratified periods, [TP] increased 3–43% and 31–52% in the surf ace water of Nakamun and Halfmoon lakes, respectively.

The role of multimedia mass balance models for assessing the effects of volatile organic compound emissions on urban air quality

2006 ◽  
Vol 40 (16) ◽  
pp. 2986-2994 ◽  
Author(s):  
Karen L. Foster ◽  
Steven Sharpe ◽  
Eva Webster ◽  
Donald Mackay ◽  
Randy Maddalena
Keyword(s):  
Air Quality ◽  
Organic Compound ◽  
Mass Balance ◽  
Volatile Organic Compound ◽  
Urban Air Quality ◽  
Urban Air ◽  
Mass Balance Models ◽  
Volatile Organic ◽  
Volatile Organic Compound Emissions

Comparison between energy balance and mass balance models for actual evapotranspiration assessment

2009 ◽  
Author(s):  
A. Gentile ◽  
L. Pierce ◽  
G. Ciraolo ◽  
G. Zhang ◽  
G. La Loggia ◽  
...  
Keyword(s):  
Energy Balance ◽  
Mass Balance ◽  
Actual Evapotranspiration ◽  
Mass Balance Models

Investigating Fast- and Slow-settling Phosphorus Fractions in Lakes using Steady-state Modeling

2021 ◽  
Author(s):  
Hamed Khorasani ◽  
Zhenduo Zhu
Keyword(s):  
Steady State ◽  
Mass Balance ◽  
Large Scale ◽  
Hydraulic Residence Time ◽  
Simple Method ◽  
Retention Models ◽  
Mass Balance Models ◽  
Limiting Nutrient ◽  
Fast Settling ◽  
P Retention

<p>Phosphorus (P) is the key and limiting nutrient in the eutrophication of freshwater resources. Modeling P retention in lakes using steady-state mass balance models (i.e. Vollenweider-type models) provides insights into the lake P management and a simple method for large-scale assessments of P in lakes. One of the basic problems in the mass balance modeling of P in lakes is the removal of P from the lake water column by settling. A fraction of the incoming P into the lake from the watershed is associated with fast-settling particles (e.g. sediment particles) that result in the removal of that fraction of P quickly at the lake entrance. However, existing models considering a constant fraction of fast-settling TP for all lakes are shown to result in overestimation of the retention of P in lakes with short hydraulic residence time. In this study, we combine a hypothesis of the fast- and slow-settling P fractions into the steady-state mass balance models of P retention in lakes. We use a large database of lakes to calibrate the model and evaluate the hypothesis. The results of this work can be used for the improvement of the prediction power of P retention models in lakes and help to better understand the processes of P cycling in lakes.</p>

scholarly journals Inorganic carbon time series at Ocean Weather Station M in the Norwegian Sea

2007 ◽  
Vol 4 (4) ◽  
pp. 2929-2958 ◽  
Author(s):  
I. Skjelvan ◽  
E. Falck ◽  
F. Rey ◽  
S. B. Kringstad
Keyword(s):  
Surface Water ◽  
Deep Water ◽  
Inorganic Carbon ◽  
Dissolved Inorganic Carbon ◽  
Sea Surface ◽  
Linear Regression Method ◽  
Weather Station ◽  
Arctic Water ◽  
Annual Increase ◽  
Norwegian Sea

Abstract. Dissolved inorganic carbon (CT) has been collected at Ocean Weather Station M (OWSM) in the Norwegian Sea since 2001. Seasonal variations in CT are confined to the upper 50 m, where the biology is active, and below this layer no clear seasonal signal is seen. From winter to summer the surface CT concentration typical drops from 2140 to about 2040 μmol kg−1, while a deep water CT concentration of about 2163 μmol kg−1 is measured throughout the year. Observations show an annual increase in salinity normalized carbon concentration (nCT) of 1.3±0.7 μmol kg−1 in the surface layer, which is equivalent to a pCO2 increase of 2.6±1.2 μatm yr−1, i.e. larger than the atmospheric increase in this area. Observations also show an annual increase in the deep water nCT of 0.57± 0.24 μmol kg−1, of which about a tenth is due to inflow of old Arctic water with larger amounts of remineralised matter. The remaining part has an anthropogenic origin and sources for this might be Greenland Sea surface water, Iceland Sea surface water, and/or recirculated Atlantic Water. By using an extended multi linear regression method (eMLR) it is verified that anthropogenic carbon has entered the whole water column at OWSM.

Impact of the choice of surface mass balance models and their calibration on large-scale glacier change projections

2021 ◽  
Author(s):  
Lilian Schuster ◽  
David Rounce ◽  
Fabien Maussion
Keyword(s):  
Mass Balance ◽  
Large Scale ◽  
Model Complexity ◽  
Model Parameters ◽  
Glacier Change ◽  
Surface Mass Balance ◽  
Ice Dynamics ◽  
Surface Mass ◽  
Mass Balance Models ◽  
Intercomparison Study

<p>A recent large model intercomparison study (GlacierMIP) showed that differences between the glacier models is a dominant source of uncertainty for future glacier change projections, in particular in the first half of the century.  Each glacier model has their own unique set of process representations and climate forcing methodology, which makes it impossible to determine the model components that contribute most to the projection uncertainty. This study aims to improve our understanding of the sources of large scale glacier model uncertainty using the Open Global Glacier Model (OGGM), focussing on the surface mass balance (SMB) in a first step. We calibrate and run a set of interchangeable SMB model parameterizations (e.g. monthly vs. daily, constant vs. variable lapse rates, albedo, snowpack evolution and refreezing) under controlled boundary conditions. Based on ensemble approaches, we explore the influence of (i) the parameter calibration strategy and (ii) SMB model complexity on regional to global glacier change. These uncertainties are then put in relation to a qualitative selection of other model design choices, such as the forcing climate dataset and ice dynamics model parameters. </p>

Computational Techniques Application in Environmental Exposure Assessment

2015 ◽  
pp. 471-505
Author(s):  
Karolina Jagiello ◽  
Tomasz Puzyn
Keyword(s):  
Mass Balance ◽  
Exposure Assessment ◽  
Environmental Exposure ◽  
Chemical Properties ◽  
Computational Techniques ◽  
Structure Property ◽  
Mass Balance Models ◽  
Modelling Methodology ◽  
Environmental Exposure Assessment ◽  
Input Variables

In this chapter, the application of computational techniques in environmental exposure assessment was described. The most important groups of these techniques are Multimedia Mass-balance (MM) modelling and Quantitative Structure-Activity/Structure-Property Relationships (QSAR/QSPR) modelling. Multimedia Mass-balance models have been widely utilized for studying Long-Range Transport Potential (LRTP) and overall persistence (POV) of Persistent Organic Pollutants (POPs), regulated by many national and international acts, including the Stockholm Convention on POPs. Recently, a novel modelling methodology that links QSPR and MM has been implemented. According to this approach, the physical/chemical properties required as the input variables for multimedia modelling can be calculated directly from appropriate QSPR models. QSPR models must be previously developed based on the relationships between the chemical structure and the modelled properties (QSPR).

scholarly journals Mathematical Modeling of a Domestic Wastewater Treatment System Combining a Septic Tank, an Up Flow Anaerobic Filter, and a Constructed Wetland

Water ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3019
Author(s):  
Alberto Fernández del Castillo ◽  
Marycarmen Verduzco Garibay ◽  
Carolina Senés-Guerrero ◽  
Carlos Yebra-Montes ◽  
José de Anda ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Wastewater Treatment ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Mass Balance ◽  
Constructed Wetland ◽  
Oxygen Demand ◽  
Septic Tank ◽  
First Order ◽  
Mass Balance Models

Systems combining anaerobic bioreactors with constructed wetlands (CW) have proven to be adequate and efficient for wastewater treatment. Detailed knowledge of removal dynamics of contaminants can ensure positive results for engineering and design. Mathematical modeling is a useful approach to studying the dynamics of contaminant removal in wastewater. In this study, water quality monitoring was performed in a system composed of a septic tank (ST), an up flow anaerobic filter (UAF), and a horizontal flow constructed wetland (HFCW). Biological oxygen demand (BOD5), chemical oxygen demand (COD), total Kjeldahl nitrogen (TKN), NH3, organic nitrogen (ON), total suspended solids (TSS), NO2−, and NO3− were measured biweekly during a 3-month period. First-order kinetics, multiple linear regression, and mass balance models were applied for data adjustment. First-order models were useful to predict the outlet concentration of pollutants (R2 > 0.87). Relevant multiple linear regression models were found, which could be applied to facilitate the system’s monitoring and provide valuable information to control and improve biological and physical processes necessary for wastewater treatment. Finally, the values of important parameters (μmax, Ks,  and Yx/s) in mass-balance models were determined with the aid of a differential neural network (DNN) and an optimization algorithm. The estimated parameters indicated the high robustness of the treatment system since performance stability was found despite variations in wastewater composition.

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