Long-Term Assessment of Climate Change Impacts on Tennessee Valley Authority Reservoir Operations: Norris Dam

Norris Reservoir is the oldest and largest reservoir maintained and operated by the Tennessee Valley Authority (TVA). Norris Dam received a new operating guide in 2004; however, this new guide did not consider projected climate change. In an aging infrastructure, the necessity to assess the potential impacts of climate change on water resources planning and management is increasing. This study used a combined monthly hydrologic model and a general circulation model’s (GCM) outcome to project inflows for three future time spans: 2030s, 2050s, and 2070s. The current operating guide was then assessed and optimized using penalty-function-driven genetic algorithms to gain insight for how the current guide will respond to climate change, and if it can be further optimized. The results showed that the current operating guide could sufficiently handle the increased projected runoff without major risk of dam failure or inundation, but the optimized operating guides decreased operational penalties ranging from 22 to 37 percent. These findings show that the framework used here provides water resources planning and management a methodology for assessing and optimizing current systems, and emphasizes the need to consider projected climate change as an assessment tool for reservoir operations

Long-Term Assessment of Climate Change Impacts on Tennessee Valley Authority Reservoir Operations: Norris Dam

Norris Reservoir is the oldest and largest reservoir maintained and operated by the Tennessee Valley Authority (TVA). Norris Dam received a new operating guide in 2004; however, this new guide did not consider projected climate change. In an aging infrastructure, the necessity to assess the potential impacts of climate change on water resources planning and management is increasing. This study used a combined monthly hydrologic model and a general circulation model’s (GCM) outcome to project inflows for three future time spans: 2030s, 2050s, and 2070s. The current operating guide was then assessed and optimized using penalty-function-driven genetic algorithms to gain insight for how the current guide will respond to climate change, and if it can be further optimized. The results showed that the current operating guide could sufficiently handle the increased projected runoff without major risk of dam failure or inundation, but the optimized operating guides decreased operational penalties ranging from 22 to 37 percent. These findings show that the framework used here provides water resources planning and management a methodology for assessing and optimizing current systems, and emphasizes the need to consider projected climate change as an assessment tool for reservoir operations

An Upscaled Approach for Transport in Media with Extended Tailing Due to Back-Diffusion Using Analytical and Numerical Solutions of the Advection Dispersion Equation

The mono-continuum advection-dispersion equation (mADE) is commonly regarded as unsuitable for application to media that exhibit rapid breakthrough and extended tailing associated with diffusion between high and low permeability regions. This paper demonstrates that the mADE can be successfully used to model such conditions if certain issues are addressed. First, since hydrodynamic dispersion, unlike molecular diffusion, cannot occur upstream of the contaminant source, models must be formulated to prevent “back-dispersion.” Second, large variations in aquifer permeability will result in differences between volume-weighted average concentration (resident concentration) and flow-weighted average concentration (flux concentration). Water samples taken from wells may be regarded as flux concentrations, while soil samples may be analyzed to determine resident concentrations. While the mADE is usually derived in terms of resident concentration, it is known that a mADE of the same mathematical form may be written in terms of flux concentration. However, when solving the latter, the mathematical transformation of a flux boundary condition applied to the resident mADE becomes a concentration type boundary condition for the flux mADE. Initial conditions must also be consistent with the form of the mADE that is to be solved. Thus, careful attention must be given to the type of concentration data that is available, whether resident or flux concentrations are to be simulated, and to boundary and initial conditions. We present 3-D analytical solutions for resident and flux concentrations, discuss methods of solving numerical models to obtain resident and flux concentrations, and compare results for hypothetical problems. We also present an upscaling method for computing “effective” dispersivities and other mADE model parameters in terms of physically meaningful parameters in a diffusion-limited mobile–immobile model. Application of the latter to previously published studies of systems that exhibit early breakthrough and extended tailing shows that the upscaled mADE model is able to describe the observed behavior with reasonable accuracy given only known physical parameters for the systems without any model calibration

Optimal Cultivation Pattern to Increase Revenue and Reduce Water Use: Application of Linear Programming to Arjan Plain in Fars Province

Because the available water resources of the Arjan plain region in Iran do not fully meet the watering requirements for plants in farmlands, the crops suffer from water stress, a situation that causes them to wilt. The aim of this study is to develop a water resources planning model that helps decision-makers determine an appropriate cultivation pattern, optimize the exploitation from surface water resources, and specify the method of allocating water across different farm crops to minimize the detrimental effects of water shortage. Through investigating various models of water resources planning and properties along with the governing conditions for each of these models, the linear programming model was selected as a suitable option due to its simplicity and practical applicability to water resource allocation planning. The model was run for a five-year period by considering gradual variations through the determination of the most appropriate exploitation pattern from the available water resources (surface and groundwater). Results reveal that the negative water balance can be improved gradually as positive, where it will reach +20 million m3 per year in 2040 from the current deficit of 236 million m3 with an 8% increased net profit

An Upscaled Approach for Transport in Media with Extended Tailing Due to Back-Diffusion Using Analytical and Numerical Solutions of the Advection Dispersion Equation

The mono-continuum advection-dispersion equation (mADE) is commonly regarded as unsuitable for application to media that exhibit rapid breakthrough and extended tailing associated with diffusion between high and low permeability regions. This paper demonstrates that the mADE can be successfully used to model such conditions if certain issues are addressed. First, since hydrodynamic dispersion, unlike molecular diffusion, cannot occur upstream of the contaminant source, models must be formulated to prevent “back-dispersion.” Second, large variations in aquifer permeability will result in differences between volume-weighted average concentration (resident concentration) and flow-weighted average concentration (flux concentration). Water samples taken from wells may be regarded as flux concentrations, while soil samples may be analyzed to determine resident concentrations. While the mADE is usually derived in terms of resident concentration, it is known that a mADE of the same mathematical form may be written in terms of flux concentration. However, when solving the latter, the mathematical transformation of a flux boundary condition applied to the resident mADE becomes a concentration type boundary condition for the flux mADE. Initial conditions must also be consistent with the form of the mADE that is to be solved. Thus, careful attention must be given to the type of concentration data that is available, whether resident or flux concentrations are to be simulated, and to boundary and initial conditions. We present 3-D analytical solutions for resident and flux concentrations, discuss methods of solving numerical models to obtain resident and flux concentrations, and compare results for hypothetical problems. We also present an upscaling method for computing “effective” dispersivities and other mADE model parameters in terms of physically meaningful parameters in a diffusion-limited mobile–immobile model. Application of the latter to previously published studies of systems that exhibit early breakthrough and extended tailing shows that the upscaled mADE model is able to describe the observed behavior with reasonable accuracy given only known physical parameters for the systems without any model calibration

Optimal Cultivation Pattern to Increase Revenue and Reduce Water Use: Application of Linear Programming to Arjan Plain in Fars Province

Because the available water resources of the Arjan plain region in Iran do not fully meet the watering requirements for plants in farmlands, the crops suffer from water stress, a situation that causes them to wilt. The aim of this study is to develop a water resources planning model that helps decision-makers determine an appropriate cultivation pattern, optimize the exploitation from surface water resources, and specify the method of allocating water across different farm crops to minimize the detrimental effects of water shortage. Through investigating various models of water resources planning and properties along with the governing conditions for each of these models, the linear programming model was selected as a suitable option due to its simplicity and practical applicability to water resource allocation planning. The model was run for a five-year period by considering gradual variations through the determination of the most appropriate exploitation pattern from the available water resources (surface and groundwater). Results reveal that the negative water balance can be improved gradually as positive, where it will reach +20 million m3 per year in 2040 from the current deficit of 236 million m3 with an 8% increased net profit

Stochastic Cost-Optimization and Risk Assessment of in situ Chemical Oxidation for Dense Non-Aqueous Phase Liquid (DNAPL) Source Remediation

This study involved development of a computer program to determine optimal design variables for in situ chemical oxidation (ISCO) of dense nonaqueous phase liquid (DNAPL) sites to meet site-wide remediation objectives with minimum life-cycle remediation cost while taking uncertainty in site characterization data and model predictions into consideration. A physically-based ISCO performance model computes field-scale DNAPL dissolution, instantaneous reaction of oxidant with contaminant and with readily oxidizable natural oxidant demand (NOD), second-order kinetic reactions for slowly oxidizable NOD, and time to reach ISCO termination criteria. Remediation cost is computed by coupling the performance model with a cost module. ISCO termination protocols are implemented that allow different treatment subregions (e.g., zones with different estimated contaminant concentrations) to be terminated independently based on statistical criteria related to confidence limits of contaminant concentrations estimated from soil and/or groundwater sampling data. The ISCO model was implemented in the program called Stochastic Cost Optimization Toolkit, which includes modules for additional remediation technologies that can be implemented serially or in parallel coupled with a dissolved plume model to enable design optimization to meet plume-scale cleanup objectives. This study focuses on optimization of ISCO design to meet specified source zone remediation objectives. ISCO design parameters considered for optimization include oxidant concentration and injection rate, frequency and number of soil or groundwater samples, and cleanup criteria for termination of subregion injection. Sensitivity studies and example applications are presented to demonstrate the benefits of proposed stochastic optimization methodology

Development and Application of Urban Landslide Vulnerability Assessment Methodology Reflecting Social and Economic Variables

An urban landslide vulnerability assessment methodology is proposed with major focus on considering urban social and economic aspects. The proposed methodology was developed based on the landslide susceptibility maps that Korean Forest Service utilizes to identify landslide source areas. Frist, debris flows are propagated to urban areas from such source areas by Flow-R (flow path assessment of gravitational hazards at a regional scale), and then urban vulnerability is assessed by two categories: physical and socioeconomic aspect. The physical vulnerability is related to buildings that can be impacted by a landslide event. This study considered two popular building structure types, reinforced-concrete frame and nonreinforced-concrete frame, to assess the physical vulnerability. The socioeconomic vulnerability is considered a function of the resistant levels of the vulnerable people, trigger factor of secondary damage, and preparedness level of the local government. An index-based model is developed to evaluate the life and indirect damage under landslide as well as the resilience ability against disasters. To illustrate the validity of the proposed methodology, physical and socioeconomic vulnerability levels are analyzed for Seoul, Korea, using the suggested approach. The general trend found in this study indicates that the higher population density areas under a weaker fiscal condition that are located at the downstream of mountainous areas are more vulnerable than the areas in opposite conditions

Application of Copula-Based Markov Model to Generate Monthly Precipitation

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv