Integrated Carbonate Field Management Using Forward Stratigraphic Modelling Approach. Case Study of a Field in Central Luconia

2017 ◽  
Author(s):  
D. A. Uli ◽  
A. H. Mithani ◽  
Kartina Ali ◽  
Roslan B Abu Mansur ◽  
Rahim Masoudi ◽  
...  
Keyword(s):  
Field Management ◽  
Central Luconia ◽  
Modelling Approach

Investigation of a New Approach to Predict Water Quality Extremes with a Case Study of Chemical Determinands in Stream Water

1991 ◽  
Vol 24 (6) ◽  
pp. 25-33
Author(s):  
A. J. Jakeman ◽  
P. G. Whitehead ◽  
A. Robson ◽  
J. A. Taylor ◽  
J. Bai
Keyword(s):  
Water Quality ◽  
Stream Water ◽  
Probability Distributions ◽  
Management Strategies ◽  
Hybrid Modelling ◽  
Trend Model ◽  
Environmental Extremes ◽  
Modelling Approach

The paper illustrates analysis of the assumptions of the statistical component of a hybrid modelling approach for predicting environmental extremes. This shows how to assess the applicability of the approach to water quality problems. The analysis involves data on stream acidity from the Birkenes catchment in Norway. The modelling approach is hybrid in that it uses: (1) a deterministic or process-based description to simulate (non-stationary) long term trend values of environmental variables, and (2) probability distributions which are superimposed on the trend values to characterise the frequency of shorter term concentrations. This permits assessment of management strategies and of sensitivity to climate variables by adjusting the values of major forcing variables in the trend model. Knowledge of the variability about the trend is provided by: (a) identification of an appropriate parametric form of the probability density function (pdf) of the environmental attribute (e.g. stream acidity variables) whose extremes are of interest, and (b) estimation of pdf parameters using the output of the trend model.

scholarly journals Comparing an insurer's perspective on building damages with modelled damages from pan-European winter windstorm event sets: a case study from Zurich, Switzerland

2021 ◽  
Vol 21 (1) ◽  
pp. 279-299
Author(s):  
Christoph Welker ◽  
Thomas Röösli ◽  
David N. Bresch
Keyword(s):  
Open Source ◽  
Return Period ◽  
Model Building ◽  
Information Service ◽  
Source Model ◽  
Insurance Companies ◽  
Risk Models ◽  
Risk Modelling ◽  
Modelling Approach

Abstract. With access to claims, insurers have a long tradition of being knowledge leaders on damages caused by windstorms. However, new opportunities have arisen to better assess the risks of winter windstorms in Europe through the availability of historic footprints provided by the Windstorm Information Service (Copernicus WISC). In this study, we compare how modelling of building damages complements claims-based risk assessment. We describe and use two windstorm risk models: an insurer's proprietary model and the open source CLIMADA platform. Both use the historic WISC dataset and a purposefully built, probabilistic hazard event set of winter windstorms across Europe to model building damages in the canton of Zurich, Switzerland. These approaches project a considerably lower estimate for the annual average damage (CHF 1.4 million), compared to claims (CHF 2.3 million), which originates mainly from a different assessment of the return period of the most damaging historic event Lothar–Martin. Additionally, the probabilistic modelling approach allows assessment of rare events, such as a 250-year-return-period windstorm causing CHF 75 million in damages, including an evaluation of the uncertainties. Our study emphasizes the importance of complementing a claims-based perspective with a probabilistic risk modelling approach to better understand windstorm risks. The presented open-source model provides a straightforward entry point for small insurance companies.

scholarly journals Application of data-based mechanistic modelling for flood forecasting at multiple locations in the Eden catchment in the National Flood Forecasting System (England and Wales)

2013 ◽  
Vol 17 (1) ◽  
pp. 177-185 ◽  
Author(s):  
D. Leedal ◽  
A. H. Weerts ◽  
P. J. Smith ◽  
K. J. Beven
Keyword(s):  
Warning System ◽  
Open Shell ◽  
Flood Forecasting ◽  
Mechanistic Modelling ◽  
Forecasting Models ◽  
Forecasting System ◽  
Environment Agency ◽  
The Uk ◽  
Modelling Approach

Abstract. The Delft Flood Early Warning System provides a versatile framework for real-time flood forecasting. The UK Environment Agency has adopted the Delft framework to deliver its National Flood Forecasting System. The Delft system incorporates new flood forecasting models very easily using an "open shell" framework. This paper describes how we added the data-based mechanistic modelling approach to the model inventory and presents a case study for the Eden catchment (Cumbria, UK).

Case Study: Drilling Performance in a Thin Oil Rim Carbonate Pinnacle: Central Luconia, Sarawak

2020 ◽  
Author(s):  
Keng Hung Kok ◽  
Michael Ajang ◽  
Jeremiah Michael ◽  
Runtuwene Michael ◽  
Chien Hock Jong ◽  
...  
Keyword(s):  
Drilling Performance ◽  
Central Luconia ◽  
Oil Rim

scholarly journals Using a modified DNDC biogeochemical model to optimize field management of a multi-crop (cotton, wheat, and maize) system: a site-scale case study in northern China

2019 ◽  
Vol 16 (14) ◽  
pp. 2905-2922 ◽  
Author(s):  
Wei Zhang ◽  
Chunyan Liu ◽  
Xunhua Zheng ◽  
Kai Wang ◽  
Feng Cui ◽  
...  
Keyword(s):  
Best Management Practices ◽  
Process Model ◽  
Management Practices ◽  
Gross Primary Production ◽  
Northern China ◽  
Biogeochemical Model ◽  
No Production ◽  
Field Management ◽  
Crop System

Abstract. It is still a severe challenge to optimize the field management practices for a multi-crop system when simultaneously aiming at yield sustainability and minimum negative impacts on climate as well as atmosphere and water quality. This site-scale case study was devoted to developing a biogeochemical process model-based approach as a solution to this challenge. The best management practices (BMPs) of a three-crop system growing cotton and winter wheat–summer maize (W–M) in rotation, which is widely adopted in northern China, were identified. The BMPs referred to the management alternatives with the lowest negative impact potentials (NIPs) among the scenarios satisfying all given constraints. The independent variables used to determine the NIPs and those utilized as constrained criteria were simulated by the DeNitrification-DeComposition model, which was modified in this study. Due to the unsatisfactory performance of the model in daily simulations of nitric oxide (NO) emission and net ecosystem exchange of carbon dioxide (NEE), the model was modified to (i) newly parameterize the soil moisture effects on NO production during nitrification, and (ii) replace the original NEE calculation approach with an algorithm based on gross primary production. Validation of the modified model showed statistically meaningful agreements between the simulations and observations in the cotton and W–M fields. Three BMP alternatives with overlapping uncertainties of simulated NIPs were screened from 6000 management scenarios randomly generated by Latin hypercube sampling. All of these BMP alternatives adopted the baseline (currently applied) practices of crop rotation (3 consecutive years of cotton rotating with 3 years of W–M in each 6-year cycle), the fraction of crop residue incorporation (100 %), and deep tillage (30 cm) for cotton. At the same time, these BMP alternatives would use 18 % less fertilizer nitrogen and sprinkle or flood-irrigate ∼23 % less water than the baseline while adopting reduced tillage (5 cm) for W–M. Compared with the baseline practices, these BMP alternatives could simultaneously sustain crop yields, annually enlarge the soil organic carbon stock by 4 ‰ or more, mitigate the aggregate emission of greenhouse gases, NO release, ammonia volatilization, and nitrate leaching by ∼7 %, ∼25 %, ∼2 %, and ∼43 %, respectively, despite a ∼5 % increase in N2O emission. However, further study is still necessary for field confirmation of these BMP alternatives. Nevertheless, this case study proposed a practical approach to optimize multi-crop system management to simultaneously achieve multiple United Nations Sustainable Development Goals.

Enterprise Modelling in Support of Organisation Design and Change

2010 ◽  
pp. 352-378
Author(s):  
Joseph Ajaefobi ◽  
Aysin Rahimifard ◽  
Richard Weston
Keyword(s):  
Simulation Modelling ◽  
Integrated Modelling ◽  
Market Place ◽  
Manufacturing Enterprises ◽  
Enterprise Modelling ◽  
Requirements Change ◽  
Study Application ◽  
Modelling Approach

Enterprises (business organisations) are increasingly operating under uncertain conditions arising from: governments that introduce new regulations; a market place which is shaped by ongoing change in customer requirements; change in capital markets that orient overall market directions; an advancing base of technology; and increasing competition which can arise from a growing number of sources (Monfared, 2000). Consequently, organisations are expected to change rapidly in response to emerging requirements. Classical theories and more recently ‘method-based’ organisation (re)design and change approaches have been proposed and tried with varying degrees of successes. This chapter contribution discusses the role of enterprise and simulation modelling in support of organisation (re)design and change. The capabilities and constraints of some widely acknowledged public domain enterprise modelling frameworks and methods are reviewed. A modelling approach which integrates the use of enterprise modelling (EM), causal loop modelling (CLM), and simulation modelling (SM) is described. The approach enables the generation of coherent and semantically rich models of organisations. The integrated modelling approach has been applied and tested in a number of manufacturing enterprises (MEs) and one case study application is described.

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