Revealing Dynamics: A Graphical Approach to Sensitivity Analysis in Complex Systems, Demonstrated with Compartmental Models | Chapter 9 | Research Updates in Mathematics and Computer Science Vol. 9

 

Understanding the dynamics of model behavior in response to changes in input parameters is pivotal, especially within complex models featuring an array of input factors. Sensitivity Analysis (SA) serves as a fundamental methodology for elucidating and quantifying the uctuations in model behavior corresponding to variations in model input factors. In situations where models incorporate a wide range of input factors, identifying the most in uential variables is of utmost importance. Although the employment of graphical tools to encapsulate SA findings is gaining traction, it remains a relatively new and evolving approach. The advancement of graphical representations significantly enhances the understanding of SA outcomes. Within this work, an exploration into the efficacy of two modern graphical techniques, specifically star plots and dot charts, as tools for SA is undertaken. These visual aids provide a clear representation of key input factors, thereby accelerating the comprehension process. To showcase their utility in SA,these techniques are applied to two distinct compartmental models elucidating the dynamics of the global carbon cycle.

 

Author(s) Details

 

Suzan Gazioglu

Department of Mathematical Sciences, Montana Technological University, 1300 W. Park Street, Butte, MT 59701 USA.

 

Please see the link:- https://doi.org/10.9734/bpi/rumcs/v9/650

Analysis of Runoff Simulation under Changes in Climate Variability: A Case Study of the Upper Awash Sab-basin, Ethiopia | Chapter 1 | Geography, Earth Science and Environment: Research Highlights Vol.4

The impact of precipitation and temperature on runoff over land surfaces is examined through runoff simulation analysis. The Soil and Water Assessment Tool (SWAT) hydrology model is used in this study to predict the sensitivity of runoff to changes in temperature and precipitation. To investigate the sensitivity of runoff to temperature and rainfall, these variables were changed. Rainfall and temperature have a major impact on runoff accessibility by affecting the timing and contribution of water sources. For the entire upper Awash Sab-basin (1980–2010), monthly station-based temperature and rainfall data were used to run the SWAT model. The hydrological model was calibrated during an eight-year period (1993-2000), and the simulation findings were validated using historical stream-flow data at the Hombole gauging station's outlet for four years (2001-2005). The calibrated and validated SWAT hydrological model was used to perform a sensitivity analysis in order to evaluate the effect of changes in temperature and rainfall on the sub-basin's runoff. Utilizing the SWAT model, the effects of several theoretical rainfall and temperature scenarios on the yearly runoff of the Upper Awash sub-basin have been examined. This was accomplished by using temperature increases (up to 5°C) and variations in rainfall (+/-20%) separately and in combination. The findings demonstrated that in the studied area, runoff was responsive to variations in temperature and rainfall.  It has been found that a yearly temperature increase of 1, 2, 3, 4, and 50C results in annual runoff reductions of 0.085, 0.88, 1.75, 2.55, and 3.30%, respectively. There is a negative link between temperature changes and runoff, but a positive correlation with changes in rainfall. The findings show that rainfall has a greater effect on runoff than temperature rise. A 10% increase or decrease in rainfall will cause a 22% or 21% increase or decrease in annual runoff. The findings demonstrated that the availability of water was significantly impacted by changes in the climatic variables.

 

Author (s) Details

 

Mekonnen H. Daba (PhD)
Oromia Agricultural Research Institute, Bako Agricultural Research Center, Bako, Ethiopia.

 

Please see the book here:- https://doi.org/10.9734/bpi/geserh/v4/2245 

Revealing Dynamics: A Graphical Approach to Sensitivity Analysis in Complex Systems, Demonstrated with Compartmental Models | Chapter 9 | Research Updates in Mathematics and Computer Science Vol. 9

Understanding the dynamics of model behavior in response to changes in input parameters is pivotal, especially within complex models featuring an array of input factors. Sensitivity Analysis (SA) serves as a fundamental methodology for elucidating and quantifying the fluctuations in model behavior corresponding to variations in model input factors. In situations where models incorporate a wide range of input factors, identifying the most influential variables is of utmost importance. Although the employment of graphical tools to encapsulate SA findings is gaining traction, it remains a relatively new and evolving approach. The advancement of graphical representations significantly enhances the understanding of SA outcomes. Within this work, an exploration into the efficacy of two modern graphical techniques, specically star plots and dot charts, as tools for SA is undertaken. These visual aids provide a clear representation of key input factors, thereby accelerating the comprehension process. To showcase their utility in SA, these techniques are applied to two distinct compartmental models elucidating the dynamics of the global carbon cycle.

 

Author (s) Details

 

Suzan Gazioglu
Department of Mathematical Sciences, Montana Technological University, 1300 W. Park Street, Butte, MT 59701 USA.

 

Please see the book here:-  https://doi.org/10.9734/bpi/rumcs/v9/65

Comparative & Sensitivity Analysis of Seasonal Variation of Borehole Water Quality in Selected Communities in River State | Chapter 12 | Emerging Issues in Science and Technology Vol. 4

This study was aimed at comparing groundwater quality of three communities namely Choba, Ekini and Ozuoba, all in Obio/Akpor Local Government Area in River State, Nigeria. Water samples from the functioning boreholes in these communities were collected and then analyzed physiochemically. Analysis of variance and weighted water quality index approach and multiple regression analyses were the methodologies employed for analyses of the collected data. Microsoft excel 2016 and an add-in (XLSTAT 2016) were the statistical tools used as aids for data analyses. Additionally, manual calculation on one-way analysis of variance was carried out to cross-check the output on XLSTAT software results for Choba Ph values between wet and dry seasons. At 5% level of significance, the computed results indicated significance for both manual and XLSTAT outputs. The result from the analyses revealed poor water quality for Choba and Ozuoba communities with water quality indexes of 55.14 and 63.34, respectively. Ekini community has a good water quality rating with water quality index of 29.79. The developed model for prediction of water quality index for the communities revealed mean square errors, 0.000 and goodness of fits, 1.000. However, sensitivity analyses on the developed model parameters revealed that for Choba and Ekini communities, the major parameters with significant influence on the water quality index were pH, Turbidity and Al. While for Ozuoba community, pH, and Al had significant influence on the resultant water quality index based on the sensitivity analyses on the developed water quality index model.

Author(s) Details

Ify L. Nwaogazie
Department of Civil and Environmental Engineering, University of Port Harcourt, Rivers State, Nigeria.

O. P. Osamudiamen
Department of Civil and Environmental Engineering, University of Port Harcourt, Rivers State, Nigeria.

View Book :- http://bp.bookpi.org/index.php/bpi/catalog/book/184