Water Resources Systems Planning and Management: An Introduction to Methods, Models and Applications

This 2005 version has been superseded by the 2017 edition, available in full here: http://hdl.handle.net/1813/48159Throughout history much of the world has witnessed ever-greater demands for reliable, high-quality and inexpensive water supplies for domestic consumption, agriculture and industry. In recent decades there have also been increasing demands for hydrological regimes that support healthy and diverse ecosystems, provide for water-based recreational activities, reduce if not prevent floods and droughts, and in some cases, provide for the production of hydropower and ensure water levels adequate for ship navigation. Water managers are challenged to meet these multiple and often conflicting demands. At the same time, public stakeholder interest groups have shown an increasing desire to take part in the water resources development and management decision making process. Added to all these management challenges are the uncertainties of natural water supplies and demands due to changes in our climate, changes in people's standards of living, changes in watershed land uses and changes in technology. How can managers develop, or redevelop and restore, and then manage water resources systems - systems ranging from small watersheds to those encompassing large river basins and coastal zones - in a way that meets society's changing objectives and goals? In other words, how can water resources systems become more integrated and sustainable

A surrogate model for simulation–optimization of aquifer systems subjected to seawater intrusion

This study presents the application of Evolutionary Polynomial Regression (EPR) as a pattern recognition system to predicate the behavior of nonlinear and computationally complex aquifer systems subjected to seawater intrusion (SWI). The developed EPR models are integrated with a multi objective genetic algorithm to examine the efficiency of different arrangements of hydraulic barriers in controlling SWI. The objective of the optimization is to minimize the economic and environmental costs. The developed EPR model is trained and tested for different control scenarios, on sets of data including different pumping patterns as inputs and the corresponding set of numerically calculated outputs. The results are compared with those obtained by direct linking of the numerical simulation model with the optimization tool. The results of the two above-mentioned simulation–optimization (S/O) strategies are in excellent agreement. Three management scenarios are considered involving simultaneous use of abstraction and recharge to control SWI. Minimization of cost of the management process and the salinity levels in the aquifer are the two objective functions used for evaluating the efficiency of each management scenario. By considering the effects of the unsaturated zone, a subsurface pond is used to collect the water and artificially recharge the aquifer. The distinguished feature of EPR emerges in its application as the metamodel in the S/O process where it significantly reduces the overall computational complexity and time. The results also suggest that the application of other sources of water such as treated waste water (TWW) and/or storm water, coupled with continuous abstraction of brackish water and its desalination and use is the most cost effective method to control SWI. A sensitivity analysis is conducted to investigate the effects of different external sources of recharge water and different recovery ratios of desalination plant on the optimal results

Advances in Modeling and Management of Urban Water Networks

The Special Issue on Advances in Modeling and Management of Urban Water Networks (UWNs) explores four important topics of research in the context of UWNs: asset management, modeling of demand and hydraulics, energy recovery, and pipe burst identification and leakage reduction. In the first topic, the multi-objective optimization of interventions on the network is presented to find trade-off solutions between costs and efficiency. In the second topic, methodologies are presented to simulate and predict demand and to simulate network behavior in emergency scenarios. In the third topic, a methodology is presented for the multi-objective optimization of pump-as-turbine (PAT) installation sites in transmission mains. In the fourth topic, methodologies for pipe burst identification and leakage reduction are presented. As for the urban drainage systems (UDSs), the two explored topics are asset management, with a system upgrade to reduce flooding, and modeling of flow and water quality, with analyses on the transition from surface to pressurized flow, impact of water use reduction on the operation of UDSs, and sediment transport in pressurized pipes. The Special Issue also includes one paper dealing with the hydraulic modeling of an urban river with a complex cross-section

Kentucky Water Resources Research Institute Annual Technical Report FY 2008

The 2008 Annual Technical Report for Kentucky consolidates reporting requirements of the Section 104(b) base grant award into a single document that includes: 1) a synopsis of each research project conducted with grant funds during the period, 2) citations for related publications, reports, and presentations, 3) a description of information transfer activities, 4) a summary of student support during the reporting period, and 5) notable awards and achievements during the year

Modeling water resources management at the basin level: review and future directions

Water quality / Water resources development / Agricultural production / River basin development / Mathematical models / Simulation models / Water allocation / Policy / Economic aspects / Hydrology / Reservoir operation / Groundwater management / Drainage / Conjunctive use / Surface water / GIS / Decision support systems / Optimization methods / Water supply

Simulation-Optimization for Conjunctive Water Resources Management and Optimal Crop Planning in Kushabhadra-Bhargavi River Delta of Eastern India

Water resources sustainability is a worldwide concern because of climate variability, growing population, and excessive groundwater exploitation in order to meet freshwater demand. Addressing these conflicting challenges sometimes can be aided by using both simulation and mathematical optimization tools. This study combines a groundwater-flow simulation model and two optimization models to develop optimal reconnaissance-level water management strategies. For a given set of hydrologic and management constraints, both of the optimization models are applied to part of the Mahanadi River basin groundwater system, which is an important source of water supply in Odisha State, India. The first optimization model employs a calibrated groundwater simulation model (MODFLOW-2005, the U.S. Geological Survey modular ground-water model) within the Simulation-Optimization MOdeling System (SOMOS) module number 1 (SOMO1) to estimate maximum permissible groundwater extraction, subject to suitable constraints that protect the aquifer from seawater intrusion. The second optimization model uses linear programming optimization to: (a) optimize conjunctive allocation of surface water and groundwater and (b) to determine a cropping pattern that maximizes net annual returns from crop yields, without causing seawater intrusion. Together, the optimization models consider the weather seasons, and the suitability and variability of existing cultivable land, crops, and the hydrogeologic system better than the models that do not employ the distributed maximum groundwater pumping rates that will not induce seawater intrusion. The optimization outcomes suggest that minimizing agricultural rice cultivation (especially during the non-monsoon season) and increasing crop diversification would improve farmers’ livelihoods and aid sustainable use of water resources

Kentucky Water Resources Research Institute Annual Technical Report FY 2008

The 2008 Annual Technical Report for Kentucky consolidates reporting requirements of the Section 104(b) base grant award into a single document that includes: 1) a synopsis of each research project conducted with grant funds during the period, 2) citations for related publications, reports, and presentations, 3) a description of information transfer activities, 4) a summary of student support during the reporting period, and 5) notable awards and achievements during the year

Nonpoint Source Pollution Control Using a Multi-Objective Optimization Tool for Best Management Practices Selection and Spatial Placement in the Lower Bear River Watershed, Utah

This dissertation presents a set of approaches to help address water quality problems related to total phosphorus loads in water bodies. Water quality degradation is caused by many nonpoint sources such as agricultural runoff, fertilizers applications, and bank erosion. Three studies present methodologies for water quality protection from degradation in watersheds. The first study demonstrates the application of a watershed simulation tool that can quantify flows in the watershed, the amount of released pollutants and identify the areas contributing to the pollutants’ release in the watershed. The second study presents a simple combination tool that can pair potential management practices with the identified nonpoint sources areas to generate cost-effective combinations of management practices for reducing excess phosphorus loading to water bodies. The last study develops an optimization framework that recommends the area optimum sizes that are available for implementing management practices. These studies were applied to real-case problems to reduce excess nutrients within the Lower Bear River Watershed in northern Utah and expected to improve the management of nutrient control plans under the allocated funds

Modeling of Suspended Sediment Concentration Using Conventional and Machine Learning Approaches, in Thames River, Canada

Water resource management, planning, hydraulic design, environmental conservation, reservoir management and operation all require reliable information and data about Suspended Sediment Concentration (SSC). To predict such data, direct sampling and Sediment Rating Curves (SRC) are commonly utilized. Since direct sampling can be risky during extreme weather events and SRC cannot provide satisfactorily dependable results, engineers are trying to propose new precise fore-casting approaches. Various soft computing techniques have been applied to model different hydrological and environmental problems and have showed promising results in this regard. Although many studies have been performed to simulate the phenomena of SSC at numerous rivers and creeks in the literature, the SSC is a site-specific problem. In this study, Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) models were proposed and compared with the conventional SRC and linear regression methods. Using different combination of measured data from 1993 to 2016 of SSC and simultaneous Stream dis-charge, Water Temperature, and Electric Conductivity for Thames River at Byron Station, London, Canada, several models were trained. Goodness of each model was evaluated using Mean Absolute Error, Root-Mean Square Error and Nash-Sutcliffe Efficiency Coefficient. Results show that ANN models are of a superior accuracy if compared with other approaches in predicting SSC for this river