Related Research Articles
Hydrology is the scientific study of the movement, distribution, and management of water on Earth and other planets, including the water cycle, water resources, and drainage basin sustainability. A practitioner of hydrology is called a hydrologist. Hydrologists are scientists studying earth or environmental science, civil or environmental engineering, and physical geography. Using various analytical methods and scientific techniques, they collect and analyze data to help solve water related problems such as environmental preservation, natural disasters, and water management.
Mathematical optimization or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems arise in all quantitative disciplines from computer science and engineering to operations research and economics, and the development of solution methods has been of interest in mathematics for centuries.
Hydrogeology is the area of geology that deals with the distribution and movement of groundwater in the soil and rocks of the Earth's crust. The terms groundwater hydrology, geohydrology, and hydrogeology are often used interchangeably.
A water supply network or water supply system is a system of engineered hydrologic and hydraulic components that provide water supply. A water supply system typically includes the following:
- A drainage basin
- A raw water collection point where the water accumulates, such as a lake, a river, or groundwater from an underground aquifer. Raw water may be transferred using uncovered ground-level aqueducts, covered tunnels, or underground water pipes to water purification facilities.
- Water purification facilities. Treated water is transferred using water pipes.
- Water storage facilities such as reservoirs, water tanks, or water towers. Smaller water systems may store the water in cisterns or pressure vessels. Tall buildings may also need to store water locally in pressure vessels in order for the water to reach the upper floors.
- Additional water pressurizing components such as pumping stations may need to be situated at the outlet of underground or aboveground reservoirs or cisterns.
- A pipe network for distribution of water to consumers and other usage points
- Connections to the sewers are generally found downstream of the water consumers, but the sewer system is considered to be a separate system, rather than part of the water supply system.
The analytic element method (AEM) is a numerical method used for the solution of partial differential equations. It was initially developed by O.D.L. Strack at the University of Minnesota. It is similar in nature to the boundary element method (BEM), as it does not rely upon the discretization of volumes or areas in the modeled system; only internal and external boundaries are discretized. One of the primary distinctions between AEM and BEMs is that the boundary integrals are calculated analytically. Although originally developed to model groundwater flow, AEM has subsequently been applied to other fields of study including studies of heat flow and conduction, periodic waves, and deformation by force.
The hyporheic zone is the region of sediment and porous space beneath and alongside a stream bed, where there is mixing of shallow groundwater and surface water. The flow dynamics and behavior in this zone is recognized to be important for surface water/groundwater interactions, as well as fish spawning, among other processes. As an innovative urban water management practice, the hyporheic zone can be designed by engineers and actively managed for improvements in both water quality and riparian habitat.
An hydrological transport model is a mathematical model used to simulate the flow of rivers, streams, groundwater movement or drainage front displacement, and calculate water quality parameters. These models generally came into use in the 1960s and 1970s when demand for numerical forecasting of water quality and drainage was driven by environmental legislation, and at a similar time widespread access to significant computer power became available. Much of the original model development took place in the United States and United Kingdom, but today these models are refined and used worldwide.
Groundwater recharge or deep drainage or deep percolation is a hydrologic process, where water moves downward from surface water to groundwater. Recharge is the primary method through which water enters an aquifer. This process usually occurs in the vadose zone below plant roots and is often expressed as a flux to the water table surface. Groundwater recharge also encompasses water moving away from the water table farther into the saturated zone. Recharge occurs both naturally and through anthropogenic processes, where rainwater and/or reclaimed water is routed to the subsurface.
In fluid dynamics, pipe network analysis is the analysis of the fluid flow through a hydraulics network, containing several or many interconnected branches. The aim is to determine the flow rates and pressure drops in the individual sections of the network. This is a common problem in hydraulic design.
A runoff models or rainfall-runoff model describes how rainfall is converted into runoff in a drainage basin. More precisely, it produces a surface runoff hydrograph in response to a rainfall event, represented by and input as a hyetograph. Rainfall-runoff models need to be calibrated before they can be used.
A hydrologic model is a simplification of a real-world system that aids in understanding, predicting, and managing water resources. Both the flow and quality of water are commonly studied using hydrologic models.
GSSHA is a two-dimensional, physically based watershed model developed by the Engineer Research and Development Center of the United States Army Corps of Engineers. It simulates surface water and groundwater hydrology, erosion and sediment transport. The GSSHA model is used for hydraulic engineering and research, and is on the Federal Emergency Management Agency (FEMA) list of hydrologic models accepted for use in the national flood insurance program for flood hydrograph estimation. Input is best prepared by the Watershed Modeling System interface, which effectively links the model with geographic information systems (GIS).
FEHM is a groundwater model that has been developed in the Earth and Environmental Sciences Division at Los Alamos National Laboratory over the past 30 years. The executable is available free at the FEHM Website. The capabilities of the code have expanded over the years to include multiphase flow of heat and mass with air, water, and CO2, methane hydrate, plus multi-component reactive chemistry and both thermal and mechanical stress. Applications of this code include simulations of: flow and transport in basin scale groundwater systems , migration of environmental isotopes in the vadose zone, geologic carbon sequestration, oil shale extraction, geothermal energy, migration of both nuclear and chemical contaminants, methane hydrate formation, seafloor hydrothermal circulation, and formation of karst. The simulator has been used to generate results for more than 100 peer reviewed publications which can be found at FEHM Publications.
The Geochemist's Workbench (GWB) is an integrated set of interactive software tools for solving a range of problems in aqueous chemistry. The graphical user interface simplifies the use of the geochemical code.
The global freshwater model WaterGAP calculates flows and storages of water on all continents of the globe, taking into account the human influence on the natural freshwater system by water abstractions and dams. It supports understanding the freshwater situation across the world's river basins during the 20th and the 21st centuries, and is applied to assess water scarcity, droughts and floods and to quantify the impact of human actions on e.g. groundwater, wetlands, streamflow and sea-level rise. Modelling results of WaterGAP have contributed to international assessment of the global environmental situation including the UN World Water Development Reports, the Millennium Ecosystem Assessment, the UN Global Environmental Outlooks as well as to reports of the Intergovernmental Panel on Climate Change. WaterGAP contributes to the Intersectoral Impact Model Intercomparison Project ISIMIP, where consistent ensembles of model runs by a number of global hydrological models are generated to assess the impact of climate change and other anthropogenic stressors on freshwater resources world-wide.
Integrated Water Flow Model (IWFM) is a computer program for simulating water flow through the integrated land surface, surface water and groundwater flow systems. It is a rewrite of the abandoned software IGSM, which was found to have several programing errors. The IWFM programs and source code are freely available. IWFM is written in Fortran, and can be compiled and run on Microsoft Windows, Linux and Unix operating systems. The IWFM source code is released under the GNU General Public License.
Christine A. Shoemaker joined the Department of Industrial Systems Engineering & Management and the Department of Civil and Environmental Engineering as NUS Distinguished Professor on 31 August 2015. Prof Shoemaker obtained her Ph.D. in mathematics from the University of Southern California supervised by Richard Bellman in Dynamic Programming. Upon her graduation, she joined the School of Civil and Environmental Engineering and later the School of Operations Research and Information Engineering at Cornell University, Ithaca, NY, USA. She was promoted to full Professor in 1985. From 1985 to 1988, Professor Shoemaker was the Chair of the Department of Environmental Engineering at Cornell University. In 2002 Prof. Shoemaker was appointed the Joseph P. Ripley Professor of Engineering at Cornell University, USA. In 2015, Prof. Shoemaker became Distinguished Professor at National University of Singapore, in both Industrial Systems Engineering and Management Department and Civil and Environmental Engineering Department. While in Singapore she has worked with Singapore water agency to apply her global optimization algorithms to improve the selection of parameters for computationally expensive partial differential equation models for lake hydrodynamics and complex multi-species water quality elements. These results used her group's new parallel algorithms.
Bioclogging or biological clogging refers to the blockage of pore space in soil by microbial biomass, including active cells and their byproducts such as extracellular polymeric substance (EPS). The microbial biomass obstructs pore spaces, creating an impermeable layer in the soil and significantly reducing water infiltration rates.
Ezio Todini is an Italian academic, hydrologist and civil engineer.
References
- ↑ Ahlfeld, David P.; Mulvey, John M.; Pinder, George F.; Wood, Eric F. (1988). "Contaminated groundwater remediation design using simulation, optimization, and sensitivity theory: 1. Model development". Water Resources Research. 24 (3): 431–441. Bibcode:1988WRR....24..431A. doi:10.1029/WR024i003p00431. ISSN 1944-7973.
- ↑ Alminagorta, Omar (2016). "Systems modeling to improve the hydro-ecological performance of diked wetlands". Water Resources Research. 52 (9): 7070–7085. Bibcode:2016WRR....52.7070A. doi:10.1002/2015WR018105. S2CID 31097159.
- ↑ Feyen, Luc; Gorelick, Steven M. (2005). "Framework to evaluate the worth of hydraulic conductivity data for optimal groundwater resources management in ecologically sensitive areas". Water Resources Research. 41 (3): 03019. Bibcode:2005WRR....41.3019F. doi:10.1029/2003WR002901. S2CID 108490062.
- ↑ Alminagorta, Omar; Tesfatsion, Bereket; Rosenberg, David E.; Neilson, Bethany (2013). "Simple Optimization Method to Determine Best Management Practices to Reduce Phosphorus Loading in Echo Reservoir, Utah". Journal of Water Resources Planning and Management. 139: 122–125. doi:10.1061/(ASCE)WR.1943-5452.0000224.
- ↑ Santhosh, Apoorva; Farid, Amro M.; Youcef-Toumi, Kamal (2014). "Real-time economic dispatch for the supply side of the energy-water nexus" (PDF). Applied Energy. 122: 42–52. Bibcode:2014ApEn..122...42S. doi:10.1016/j.apenergy.2014.01.062.
- ↑ Dandy, Graeme C.; Simpson, Angus R.; Murphy, Laurence J. (1996). "An improved genetic algorithm for pipe network optimization" (PDF). Water Resources Research. 32 (2): 449–458. Bibcode:1996WRR....32..449D. doi:10.1029/95WR02917. hdl: 2440/1073 . S2CID 16097463. Archived from the original (PDF) on 2019-08-10.