Journal articles on the topic 'End use water models'
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1
White, S., G. Milne, and C. Riedy. "End use analysis: issues and lessons." Water Supply 4, no. 3 (June 1, 2004): 57–66. http://dx.doi.org/10.2166/ws.2004.0043.
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Methodologies for end use analysis have been developed by different researchers in the energy and water fields and in different areas in the world over the last 20 years. While there are core features associated with the methodologies and models used, the differences can provide insight into the ways that they might be improved, as well as the differences that may be required in different regions and when models are used for different purposes. In addition to reviewing the field of end use analysis and appliance stock models, this paper will focus on two case studies. The first is the Sydney Water End Use Model, developed as part of the Sydney Water Least Cost Planning Study. This model has been developed and used to project the demand for water in Sydney over the next 20 years under business as usual scenario, as well as allow the projection of a number of scenarios which include major investment in water efficiency and effluent reuse programs as well as regulatory options to improve the efficiency of water using appliances in stalled in new buildings. Key features of the Sydney Water End Use Model include the fact that it takes into account the fact that the efficiency of toilets in Australia has a much larger range than (say) the US, in that the dual flush toilet was introduced in (to date) three stages. The model also accounts for projections of demographic and land use change which has been particularly dramatic in Sydney, particularly the movement to smaller occupancy rates in dwellings, and towards multi-family residential dwellings. The second case study will demonstrate the linkages between end use modeling of energy using and water using appliances. A model of residential energy use in Australia has been developed as part of a research project to develop greenhouse abatement scenarios for Australia, and many of the appliances modeled overlap with the water end use model, including clothes washing machines, dishwashers, showerheads and taps. This more recent modeling exercise has revealed the importance of key assumptions in standard stock modeling techniques, and highlighted the need for earlier starting dates for stock modeling. The process and results of these two case studies will be presented, and conclusions drawn about further improvements in end use analysis for both water and energy use. The linkage between the use of backcasting as a planning tool, and the use of end use analysis as a pre-requisite for the development of a demand management program is highlighted.
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Cahill, R., J. R. Lund, B. DeOreo, and J. Medellín-Azuara. "Household water use and conservation models using Monte Carlo techniques." Hydrology and Earth System Sciences 17, no. 10 (October 15, 2013): 3957–67. http://dx.doi.org/10.5194/hess-17-3957-2013.
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Abstract. The increased availability of end use measurement studies allows for mechanistic and detailed approaches to estimating household water demand and conservation potential. This study simulates water use in a single-family residential neighborhood using end-water-use parameter probability distributions generated from Monte Carlo sampling. This model represents existing water use conditions in 2010 and is calibrated to 2006–2011 metered data. A two-stage mixed integer optimization model is then developed to estimate the least-cost combination of long- and short-term conservation actions for each household. This least-cost conservation model provides an estimate of the upper bound of reasonable conservation potential for varying pricing and rebate conditions. The models were adapted from previous work in Jordan and are applied to a neighborhood in San Ramon, California in the eastern San Francisco Bay Area. The existing conditions model produces seasonal use results very close to the metered data. The least-cost conservation model suggests clothes washer rebates are among most cost-effective rebate programs for indoor uses. Retrofit of faucets and toilets is also cost-effective and holds the highest potential for water savings from indoor uses. This mechanistic modeling approach can improve understanding of water demand and estimate cost-effectiveness of water conservation programs.
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Cahill, R., J. R. Lund, B. DeOreo, and J. Medellín-Azuara. "Household water use and conservation models using Monte Carlo techniques." Hydrology and Earth System Sciences Discussions 10, no. 4 (April 17, 2013): 4869–900. http://dx.doi.org/10.5194/hessd-10-4869-2013.
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Abstract. The increased availability of water end use measurement studies allows for more mechanistic and detailed approaches to estimating household water demand and conservation potential. This study uses, probability distributions for parameters affecting water use estimated from end use studies and randomly sampled in Monte Carlo iterations to simulate water use in a single-family residential neighborhood. This model represents existing conditions and is calibrated to metered data. A two-stage mixed integer optimization model is then developed to estimate the least-cost combination of long- and short-term conservation actions for each household. This least-cost conservation model provides an estimate of the upper bound of reasonable conservation potential for varying pricing and rebate conditions. The models were adapted from previous work in Jordan and are applied to a neighborhood in San Ramon, California in eastern San Francisco Bay Area. The existing conditions model produces seasonal use results very close to the metered data. The least-cost conservation model suggests clothes washer rebates are among most cost-effective rebate programs for indoor uses. Retrofit of faucets and toilets is also cost effective and holds the highest potential for water savings from indoor uses. This mechanistic modeling approach can improve understanding of water demand and estimate cost-effectiveness of water conservation programs.
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Sebri, Maamar. "ANN versus SARIMA models in forecasting residential water consumption in Tunisia." Journal of Water, Sanitation and Hygiene for Development 3, no. 3 (February 15, 2013): 330–40. http://dx.doi.org/10.2166/washdev.2013.031.
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Water scarcity and increasing water demand, especially for residential end-use, are major challenges facing Tunisia. The need to accurately forecast water consumption is useful for the planning and management of this natural resource. In the current study, quarterly time series of household water consumption in Tunisia was forecast using a comparative analysis between the traditional Box–Jenkins method and an artificial neural networks approach. In particular, an attempt was made to test the effectiveness of data preprocessing, such as detrending and deseasonalization, on the accuracy of neural networks forecasting. Results indicate that the traditional Box–Jenkins method outperforms neural networks estimated on raw, detrended, or deseasonalized data in terms of forecasting accuracy. However, forecasts provided by the neural network model estimated on combined detrended and deseasonalized data are significantly more accurate and much closer to the actual data. This model is therefore selected to forecast future household water consumption in Tunisia. Projection results suggest that by 2025, water demand for residential end-use will represent around 18% of the total water demand of the country.
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Rummukainen, M., J. Räisänen, D. Bjørge, J. H. Christensen, O. B. Christensen, T. Iversen, K. Jylhä, H. Ólafsson, and H. Tuomenvirta. "Regional Climate Scenarios for use in Nordic Water Resources Studies." Hydrology Research 34, no. 5 (October 1, 2003): 399–412. http://dx.doi.org/10.2166/nh.2003.0014.
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According to global climate projections, a substantial global climate change will occur during the next decades, under the assumption of continuous anthropogenic climate forcing. Global models, although fundamental in simulating the response of the climate system to anthropogenic forcing are typically geographically too coarse to well represent many regional or local features. In the Nordic region, climate studies are conducted in each of the Nordic countries to prepare regional climate projections with more detail than in global ones. Results so far indicate larger temperature changes in the Nordic region than in the global mean, regional increases and decreases in net precipitation, longer growing season, shorter snow season etc. These in turn affect runoff, snowpack, groundwater, soil frost and moisture, and thus hydropower production potential, flooding risks etc. Regional climate models do not yet fully incorporate hydrology. Water resources studies are carried out off-line using hydrological models. This requires archived meteorological output from climate models. This paper discusses Nordic regional climate scenarios for use in regional water resources studies. Potential end-users of water resources scenarios are the hydropower industry, dam safety instances and planners of other lasting infrastructure exposed to precipitation, river flows and flooding.
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Lee, Soo-Jin, You-Jeong Kim, Hye-Sun Jin, Sung-Im Kim, Soo-Yeon Ha, and Seung-Yeong Song. "Residential End-Use Energy Estimation Models in Korean Apartment Units through Multiple Regression Analysis." Energies 12, no. 12 (June 18, 2019): 2327. http://dx.doi.org/10.3390/en12122327.
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The aim of this study was to develop a mathematical regression model for predicting end-use energy consumption in the residential sector. To this end, housing characteristics were collected through a field survey and in-depth interviews with residents of 71 households (15 apartment complexes) in Seoul, South Korea, and annual data on end-use energy consumption were collected from measurement systems installed within each apartment unit. Based on the data collected, correlativity between the field-survey data and end-use energy consumption was analyzed, and effective independent variables from the field-survey data were selected. Regression models were developed and validated for estimating six end uses of energy consumption: heating, cooling, domestic hot water (DHW), lighting, electric appliances, and cooking. Regression analysis for ventilation was not applied, and instead a calculation formula was derived, because the energy-consumption proportion was too low. The adj-R2 of the estimation model ranged from 0.406 to 0.703, and the maximum error between measured and estimated values was around ±30%, depending on the end use.
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Mateus, Marcos, Ricardo Vieira, Carina Almeida, Miguel Silva, and Filipa Reis. "ScoRE—A Simple Approach to Select a Water Quality Model." Water 10, no. 12 (December 9, 2018): 1811. http://dx.doi.org/10.3390/w10121811.
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Over the past decades, water quality models have become unique tools in the management of aquatic resources. A consequence of their widespread application is the significant number of models now available. Available methodologies to compare models provide limited support for their choice in the first place, especially to end-users or modelers with limited experience. Here we propose a method to assist in the selection of a particular model from a set of apparently similar models. The method is termed ScoRE, as it grades models according to three main aspects: Scope (aim, simulated processes, constituents, etc.), Record (reference to the model in publications, its range of applications, etc.), and the Experience of using the model from the user perspective (support material, graphical user interface, etc.). End-users define the criteria to be evaluated and their relative importance, as well as the conditions for model exclusion. The evaluation of models is still performed by the modelers, in open discussion with end-users. ScoRE is a complete approach, as it provides guidance not only to exclude models but also to select the most appropriate model for a particular situation. An application of this method is provided to illustrate its use in the choice of a model. The application resulted in the definition of 18 criteria, where 6 of these were defined exclusively by the end-users. Based on these and the relative importance of each criterion, ScoRE produced a ranking of models, facilitating model selection. The results illustrate how the contributions from modelers and end-users are integrated to select a model for a particular task.
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Mundi, Gurvinder, Richard G. Zytner, Keith Warriner, Hossein Bonakdari, and Bahram Gharabaghi. "Machine Learning Models for Predicting Water Quality of Treated Fruit and Vegetable Wastewater." Water 13, no. 18 (September 10, 2021): 2485. http://dx.doi.org/10.3390/w13182485.
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Wash-waters and wastewaters from the fruit and vegetable processing industry are characterized in terms of solids and organic content that requires treatment to meet regulatory standards for purpose-of-use. In the following, the efficacy of 13 different water remediation methods (coagulation, filtration, bioreactors, and ultraviolet-based methods) to treat fourteen types of wastewater derived from fruit and vegetable processing (fruit, root vegetables, leafy greens) were examined. Each treatment was assessed in terms of reducing suspended solids, total phosphorus, nitrogen, biochemical and chemical oxygen demand. From the data generated, it was possible to develop predictive modeling for each of the water treatments tested. Models to predict post-treatment water quality were studied and developed using multiple linear regression (coefficient of determination (R2) of 30 to 83%), which were improved by the generalized structure of group method of data handling models (R2 of 73–99%). The selection of multiple linear regression and the generalized structure of group method of data handling models was due to the ability of the models to produce robust equations for ease of use and practicality. The large variability and complex nature of wastewater quality parameters were challenging to represent in linear models; however, they were better suited for group method of data handling technique as shown in the study. The model provides an important tool to end users in selecting the appropriate treatment based on the original wastewater characteristics and required standards for the treated water.
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Lee, Sanghoon, Dugin Kaown, Eun‐Hee Koh, Kyung‐Seok Ko, and Kang‐Kun Lee. "Delineation of groundwater quality locations suitable for target end‐use purposes through deep neural network models." Journal of Environmental Quality 50, no. 2 (March 2021): 416–28. http://dx.doi.org/10.1002/jeq2.20206.
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Kotowski, Jerzy, Jacek Oko, and Monika Żygadło. "Simulation of water supply networks using modern means of information technology." E3S Web of Conferences 44 (2018): 00076. http://dx.doi.org/10.1051/e3sconf/20184400076.
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We present in turn the development of computer technology from the beginning of its creation on our planet. Then we discuss the development of information technology at our university. At the end, we present a selected technical problem which is the task of simulation of the water supply network. We present mathematical models of these issues and algorithms for their solutions requiring the use of a computer.
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Toth, Lorand, George Artur Găman, Daniel Pupăzan, Cristian Nicolescu, and and Marius Kovacs. "Use of Performance Criteria in Calibrating Methods for Modeling and Simulating the Pollution Phenomena of Surface Waters." E3S Web of Conferences 241 (2021): 01003. http://dx.doi.org/10.1051/e3sconf/202124101003.
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The release of certain substances into surface waters (lakes, rivers, estuaries and oceans) to the point where they interfere with beneficial use of water or with natural functioning of ecosystems defines the phenomenon of pollution. When stating aspects of pollution modelling, we refer to constitutive equations of the model, which may involve different values, so that the shape of equation is flexible while maintaining its structure. Quantifying the phenomenon of water pollution through simulation and spatial-temporal modelling requires the use of hydrological models that use characteristic parameters such as: bathymetry, hydrodynamic roughness, speed, Model Boundary Conditions, etc. The current paper is driven by lack of clear performance guidelines for pollution models for software users trying to demonstrate to customers and/or end users that a model is fit for purpose. Thus, common problems associated with data availability, errors and uncertainty as well as model examination will be addressed, including its calibration and validation on a case study materialized on a watercourse located in the Jiu Valley, Romania. The scientific article is intended to be a point of reference both for software users (numerical modelers) and for specialists in charge of interpreting the accuracy and validity of results from hydrodynamic models.
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Telteu, Camelia-Eliza, Hannes Müller Schmied, Wim Thiery, Guoyong Leng, Peter Burek, Xingcai Liu, Julien Eric Stanislas Boulange, et al. "Understanding each other's models: an introduction and a standard representation of 16 global water models to support intercomparison, improvement, and communication." Geoscientific Model Development 14, no. 6 (June 24, 2021): 3843–78. http://dx.doi.org/10.5194/gmd-14-3843-2021.
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Abstract. Global water models (GWMs) simulate the terrestrial water cycle on the global scale and are used to assess the impacts of climate change on freshwater systems. GWMs are developed within different modelling frameworks and consider different underlying hydrological processes, leading to varied model structures. Furthermore, the equations used to describe various processes take different forms and are generally accessible only from within the individual model codes. These factors have hindered a holistic and detailed understanding of how different models operate, yet such an understanding is crucial for explaining the results of model evaluation studies, understanding inter-model differences in their simulations, and identifying areas for future model development. This study provides a comprehensive overview of how 16 state-of-the-art GWMs are designed. We analyse water storage compartments, water flows, and human water use sectors included in models that provide simulations for the Inter-Sectoral Impact Model Intercomparison Project phase 2b (ISIMIP2b). We develop a standard writing style for the model equations to enhance model intercomparison, improvement, and communication. In this study, WaterGAP2 used the highest number of water storage compartments, 11, and CWatM used 10 compartments. Six models used six compartments, while four models (DBH, JULES-W1, Mac-PDM.20, and VIC) used the lowest number, three compartments. WaterGAP2 simulates five human water use sectors, while four models (CLM4.5, CLM5.0, LPJmL, and MPI-HM) simulate only water for the irrigation sector. We conclude that, even though hydrological processes are often based on similar equations for various processes, in the end these equations have been adjusted or models have used different values for specific parameters or specific variables. The similarities and differences found among the models analysed in this study are expected to enable us to reduce the uncertainty in multi-model ensembles, improve existing hydrological processes, and integrate new processes.
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Otkin, Jason A., Derek J. Posselt, Erik R. Olson, Hung-Lung Huang, James E. Davies, Jun Li, and Christopher S. Velden. "Mesoscale Numerical Weather Prediction Models Used in Support of Infrared Hyperspectral Measurement Simulation and Product Algorithm Development." Journal of Atmospheric and Oceanic Technology 24, no. 4 (April 1, 2007): 585–601. http://dx.doi.org/10.1175/jtech1994.1.
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Abstract A novel application of numerical weather prediction (NWP) models within an end-to-end processing system used to demonstrate advanced hyperspectral satellite technologies and instrument concepts is presented. As part of this system, sophisticated NWP models are used to generate simulated atmospheric profile datasets with fine horizontal and vertical resolution. The simulated datasets, which are treated as the “truth” atmosphere, are subsequently passed through a sophisticated forward radiative transfer model to generate simulated top-of-atmosphere (TOA) radiances across a broad spectral region. Atmospheric motion vectors and temperature and water vapor retrievals generated from the TOA radiances are then compared with the original model-simulated atmosphere to demonstrate the potential utility of future hyperspectral wind and retrieval algorithms. Representative examples of TOA radiances, atmospheric motion vectors, and temperature and water vapor retrievals are shown to illustrate the use of the simulated datasets. Case study results demonstrate that the numerical models are able to realistically simulate mesoscale cloud, temperature, and water vapor structures present in the real atmosphere. Because real hyperspectral radiance measurements with high spatial and temporal resolution are not available for large geographical domains, the simulated TOA radiance datasets are the only viable alternative that can be used to demonstrate the new hyperspectral technologies and capabilities. As such, sophisticated mesoscale models are critically important for the demonstration of the future end-to-end processing system.
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Chen, Zhuo, Huu Hao Ngo, Wenshan Guo, Xiaochang C. Wang, Clayton Miechel, Nigel Corby, Andrzej Listowski, and Kelly O'Halloran. "Analysis of social attitude to the new end use of recycled water for household laundry in Australia by the regression models." Journal of Environmental Management 126 (September 2013): 79–84. http://dx.doi.org/10.1016/j.jenvman.2013.04.012.
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Hublart, Paul, Denis Ruelland, Inaki García de Cortázar-Atauri, Simon Gascoin, Stef Lhermitte, and Antonio Ibacache. "Reliability of lumped hydrological modeling in a semi-arid mountainous catchment facing water-use changes." Hydrology and Earth System Sciences 20, no. 9 (September 8, 2016): 3691–717. http://dx.doi.org/10.5194/hess-20-3691-2016.
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Abstract. This paper explores the reliability of a hydrological modeling framework in a mesoscale (1515 km2) catchment of the dry Andes (30° S) where irrigation water use and snow sublimation represent a significant part of the annual water balance. To this end, a 20-year simulation period encompassing a wide range of climate and water-use conditions was selected to evaluate three types of integrated models referred to as A, B and C. These models share the same runoff generation and routing module but differ in their approach to snowmelt modeling and irrigation water use. Model A relies on a simple degree-day approach to estimate snowmelt rates and assumes that irrigation impacts can be neglected at the catchment scale. Model B ignores irrigation impacts just as Model A but uses an enhanced degree-day approach to account for the effects of net radiation and sublimation on melt rates. Model C relies on the same snowmelt routine as Model B but incorporates irrigation impacts on natural streamflow using a conceptual irrigation module. Overall, the reliability of probabilistic streamflow predictions was greatly improved with Model C, resulting in narrow uncertainty bands and reduced structural errors, notably during dry years. This model-based analysis also stressed the importance of considering sublimation in empirical snowmelt models used in the subtropics, and provided evidence that water abstractions from the unregulated river are impacting on the hydrological response of the system. This work also highlighted areas requiring additional research, including the need for a better conceptualization of runoff generation processes in the dry Andes.
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Hublart, P., D. Ruelland, I. García de Cortázar-Atauri, S. Gascoin, S. Lhermitte, and A. Ibacache. "Reliability of lumped hydrological modeling in a semi-arid mountainous catchment facing water-use changes." Hydrology and Earth System Sciences Discussions 12, no. 11 (November 3, 2015): 11485–548. http://dx.doi.org/10.5194/hessd-12-11485-2015.
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Abstract. This paper explores the reliability of a hydrological modeling framework in a mesoscale (1515 km2) catchment of the dry Andes (30° S) where irrigation water-use and snow sublimation represent a significant part of the annual water balance. To this end, a 20 year simulation period encompassing a wide range of climate and water-use conditions was selected to evaluate three types of integrated Models referred to as A, B and C. These Models share the same runoff generation and routing module but differ in their approach to snowmelt modeling and irrigation water-use. Model A relies on a simple degree-day approach to estimate snowmelt rates and assumes that irrigation impacts can be neglected at the catchment scale. Model B ignores irrigation impacts just as Model A but uses an enhanced degree-day approach to account for the effects of net radiation and sublimation on melt rates. Model C relies on the same snowmelt routine as Model B but incorporates irrigation impacts on natural streamflow using a conceptual irrigation module. Overall, the reliability of probabilistic streamflow predictions was greatly improved with Model C, resulting in narrow uncertainty bands and reduced structural errors, notably during dry years. This model-based analysis also stressed the importance of considering sublimation in empirical snowmelt models used in the subtropics, and provided evidence that water abstractions from the unregulated river is impacting on the hydrological response of the system. This work also highlighted areas requiring additional research, including the need for a better conceptualization of runoff generation processes in the dry Andes.
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Gonçalves, Filipe, and Miguel Cavique. "F-Gas regulation-Possible solutions for the retrofit dead end." MATEC Web of Conferences 178 (2018): 09023. http://dx.doi.org/10.1051/matecconf/201817809023.
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The EU F-gas regulation of 2006 and the recast of 2014 are forcing the market to reduce the use of refrigerants with high global warming potential (GWP). As a result, the production of hydrofluorocarbon (HFC) refrigerants with higher GWP decreased, making the prices of all HFC gases to increase. Any maintenance problem in a refrigeration system asks to evaluate the retrofitting of the gas making necessary to know the expected behaviour of the system. This paper aims to discuss the gases that can substitute the now-a-days HFCs, and the impact the retrofit will cause in a real air-conditioning systems. Many studies on retrofit address the behaviour of the refrigeration cycle, but usually, do not take into account the behaviour of the system as a whole. This paper models a water-to-water air-conditioning system taking into consideration the evaporator and condenser heat exchangers, the refrigeration cycle, the air-conditioning loop and the heat exchanger to the acclimatized area. Moreover, the paper studies the performance of the system when subjected to high condensing temperatures. The paper concludes that all possible retrofit solutions need to use flammable gases that make the refrigeration power of the equipment to reduce.
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Rípodas, P., A. Gassmann, J. Förstner, D. Majewski, M. Giorgetta, P. Korn, L. Kornblueh, et al. "Icosahedral Shallow Water Model (ICOSWM): results of shallow water test cases and sensitivity to model parameters." Geoscientific Model Development 2, no. 2 (December 7, 2009): 231–51. http://dx.doi.org/10.5194/gmd-2-231-2009.
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Abstract. The Icosahedral Shallow Water Model (ICOSWM) has been a first step in the development of the ICON (acronym for ICOsahedral Nonhydrostatic) models. ICON is a joint project of the Max Planck Institute for Meteorology in Hamburg (MPI-M) and Deutscher Wetterdienst (DWD) for the development of new unified general circulation models for climate modeling and numerical weather forecasting on global or regional domains. A short description of ICOSWM is given. Standard test cases are used to test the performance of ICOSWM. The National Center for Atmospheric Research (NCAR) Spectral Transform Shallow Water Model (STSWM) has been used as reference for test cases without an analytical solution. The sensitivity of the model results to different model parameters is studied. The kinetic energy spectra are calculated and compared to the STSWM spectra. A comparison to the shallow water version of the current operational model GME at DWD is presented. The results presented in this paper use the ICOSWM version at the end of 2008 and are a benchmark for the new options implemented in the development of the ICON project.
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Rípodas, P., A. Gassmann, J. Förstner, D. Majewski, M. Giorgetta, P. Korn, L. Kornblueh, et al. "Icosahedral Shallow Water Model (ICOSWM): results of shallow water test cases and sensitivity to model parameters." Geoscientific Model Development Discussions 2, no. 1 (June 16, 2009): 581–638. http://dx.doi.org/10.5194/gmdd-2-581-2009.
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Abstract. The Icosahedral Shallow Water Model (ICOSWM) has been a first step in the development of the ICON (acronym for ICOsahedral Nonhydrostatic) models. ICON is a joint project of the Max Planck Institute for Meteorology in Hamburg (MPI-M) and Deutscher Wetterdienst (DWD) for the development of new unified general circulation models for climate modeling and numerical weather forecasting on global or regional domains. A short description of ICOSWM is given. Standard test cases are used to test the performance of ICOSWM. The National Center for Atmospheric Research (NCAR) Spectral Transform Shallow Water Model (STSWM) has been used as reference for test cases without an analytical solution. The sensitivity of the model results to different model parameters is studied. The kinetic energy spectra are calculated and compared to the STSWM spectra. A comparison to the shallow water version of the current operational model GME at DWD is presented. In the framework of the ICON project an hydrostatic dynamical core has been developed, and a local grid refinement option and a non-hydrostatic dynamical core are under development. The results presented in this paper use the ICOSWM version at the end of 2008 and are a benchmark for the new options implemented in the development of these models.
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Ibrahim A, Salmatta, Fayyaz Memon, and David Butler. "Seasonal Variation of Rainy and Dry Season Per Capita Water Consumption in Freetown City Sierra Leone." Water 13, no. 4 (February 15, 2021): 499. http://dx.doi.org/10.3390/w13040499.
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Ensuring a sustainable urban water supply for developing/low-income countries requires an understanding of the factors affecting water consumption and technical evidence of individual consumption which can be used to design an improved water demand projection. This paper compared dry and rainy season water sources available for consumption and the end-use volume by each person in the different income groups. The study used a questionnaire survey to gather household data for a total of 398 households, which was analysed to develop the relationship between per capita water consumption characteristics: Socio-economic status, demographics, water use behaviour around indoor and outdoor water use activities. In the per capita water consumption patterns of Freetown, a seasonal variation was found: In the rainy season, per capita water consumption was found to be about 7% higher than the consumption for the full sample, whilst in the dry season, per capita water consumption was almost 14% lower than the full survey. The statistical analysis of the data shows that the average per capita water consumption for both households increases with income for informal slum-, low-, middle- and high-income households without piped connection (73, 78, 94 and 112 L/capita/day) and with connection (91, 97, 113 and 133 L/capita/day), respectively. The collected data have been used to develop 20 statistical models using the multiple linear stepwise regression method for selecting the best predictor variable from the data set. It can be seen from the values that the strongest significant relationships of per capita consumption are with the number of occupants (R = −0.728) in the household and time spent to fetch water for use (R = −0.711). Furthermore, the results reveal that the highest fraction of end use is showering (18%), then bathing (16%), followed by toilet use (14%). This is not in agreement with many developing countries where toilet use represents the largest component of indoor end use.
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Batista, Lucas dos Santos, Raimundo Rodrigues Gomes Filho, Clayton Moura de Carvalho, Alceu Pedrotti, Igor Leonardo Nascimento Santos, Gregorio Guirado Faccioli, Sara Julliane Ribeiro Assunção, and Douglas Romeu da Costa. "Water infiltration rate in the soil under different uses and covers in the Poxim River basin, Sergipe, Brazil." International Journal for Innovation Education and Research 8, no. 11 (November 1, 2020): 321–39. http://dx.doi.org/10.31686/ijier.vol8.iss11.2756.
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Watersheds are units of planning and environmental management having a great importance in the management of water resources and their use. To this end, knowledge about the soil's physical and water attributes is of paramount importance in the context of water dynamics in aquifer recharge areas. Water infiltration rate into the soil is considered an important variable in the hydrological cycle, as the increase in this process can lead to a reduction in erosion and consequently greater groundwater recharge. Thus, the present work aimed to evaluate the soil water infiltration rate in the phytophysiognomy of the Poxim River basin in the State of Sergipe, in the agriculture, eucalyptus and forest areas, and to observe the effect of the infiltration water rate in areas of no-till, minimum and conventional cultivation. The soil water infiltration rate was obtained through the use of double cylinder infiltrometer and estimated through the mathematical models of Kostiakov, Kostiakov-Lewis, Horton and Philip. When making comparisons between the models for estimating of soil water infiltration rates, the Horton model showed a better fit compared to the other models used, and the type of soil cover that obtained the highest infiltration rate was the forest. No-till areas provided higher water infiltration rates in the soil, contributing to greater groundwater recharge.
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Sin, Gürkan, Dirk J. W. De Pauw, Stefan Weijers, and Peter A. Vanrolleghem. "Developing a framework for continuous use of models in daily management and operation of WWTPs: a life cycle approach." Water Science and Technology 57, no. 9 (May 1, 2008): 1301–7. http://dx.doi.org/10.2166/wst.2008.225.
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We developed and evaluated a framework for the continuous use of dynamic models in daily management and operation of WWTPs. The overall aim is to generate knowledge and build in-house capacity for the reliable use of dynamic models in practice (within a regional water authority in The Netherlands). To this end, we have adopted a life cycle approach, where the plant model follows the different stages that make up the typical lifespan of a plant. Since this approach creates a framework in which models are continuously reused, it is more efficient in terms of resources and investment than the traditional approach where one always makes a new model for the plant whenever it is needed. The methodology was evaluated successfully at a 50,000 PE domestic EBPR plant (Haaren, The Netherlands). It is shown that the continuous use and update of models in a cyclic manner creates a learning cycle, which results in experience and knowledge generation about the plant's modelling that accumulates and translates into improvements into the modelling quality and efficiency. Moreover, a model is now always on-the-shelf for process optimization.
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Price, René M., Grzegorz Skrzypek, Pauline F. Grierson, Peter K. Swart, and James W. Fourqurean. "The use of stable isotopes of oxygen and hydrogen to identify water sources in two hypersaline estuaries with different hydrologic regimes." Marine and Freshwater Research 63, no. 11 (2012): 952. http://dx.doi.org/10.1071/mf12042.
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Stable isotopes of oxygen and hydrogen are used here with salinity data in geochemical and mass-balance models to decipher the proportion of different sources of water in two hypersaline estuaries that vary in size and hydrologic condition. Shark Bay, located on the mid-western coast of Australia, is hypersaline year round and has an arid climate. Florida Bay, located in the south-eastern United States, is seasonally hypersaline and has a subtropical climate. The water budget in both bays can be explained by evaporation of seawater, with seasonal inputs of surface-water runoff and precipitation. In Shark Bay, discharge from the Wooramel River associated with a recent major flood was detected in the relationship between the stable isotopic composition and salinity of surface waters near the mouth of the river, despite the persistence of hypersalinity. The volume of water equal to one pool volume replenished Hamelin Pool (a hypersaline water body located at the southern end of eastern Shark Bay that supports living stromatolites) once every 6–12 months. The eastern portion of Florida Bay received a greater proportion of freshwater from overland flow (70–80%) than did the western portion where rainfall was the dominant source of freshwater.
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Mangalekar, R. D., and K. S. Gumaste. "Residential water demand modelling and hydraulic reliability in design of building water supply systems: a review." Water Supply 21, no. 4 (January 21, 2021): 1385–97. http://dx.doi.org/10.2166/ws.2021.021.
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Abstract The building water supply system is a fundamental unit in water supply systems as it is directly associated with end users. However, the studies available on its efficient design are limited. Water demand estimation continues to be an important issue in water supply systems' design because of its multifaceted nature. Hunter's curve, or Fixture Unit method, is widely used for estimating the load on plumbing. Regardless of its popularity, it has a few drawbacks and is arbitrarily modified in some plumbing codes. Fixture-use probability, a basic entity in the Fixture Unit and some other methods, is a difficult parameter to estimate. Commonly, high-resolution field data is used for stochastic modelling of residential water demand which may not be always available. The paper reviews important residential water demand models in view of their applicability in building water supply system design. The irregular nature of water demand in buildings is due to uncertainty in water-use behaviour of users at fixture level. Use of soft-computing techniques can provide an advantage over the other methods in modelling such behaviour. The paper also discusses reliability of building water supply systems and applicability of some common indices for estimating reliability of building water supply systems.
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Liu, Ronghua, Jiahua Wei, Yan Ren, Qi Liu, Guangqian Wang, Songdong Shao, and Shuang Tang. "HydroMP – a computing platform for hydrodynamic simulation based on cloud computing." Journal of Hydroinformatics 19, no. 6 (September 12, 2017): 953–72. http://dx.doi.org/10.2166/hydro.2017.140.
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Abstract Modern water management decisions are increasingly dependent on efficient numerical simulations of multiple scenarios with multi-models. In this paper, a service mode for the hydrodynamic simulation based on cloud computing is proposed, and the relevant frameworks of the Hydrologic/Hydraulic Modeling Platform (HydroMP) are designed and implemented. Various hydro-models can be integrated into HydroMP dynamically without the need of program recompiling, since it achieves the scheduling of computing resources to provide end users with the rapid computing capacity of concurrent scenario simulations in the form of a Web service. The present study focuses on the dynamic model integration, resource scheduling, system communication and data structure design. To use the present one-dimensional hydrodynamic cloud computing as a prototype, two integration methods (including the EXE integration and PIIM integration) are applied to construct the CE-QUAL-RIV1 and JPWSPC (Joint Point Water Stage Prediction and Correction) models, thereby to investigate real-time scheduling of the water transfer channels in the South-to-North Water Diversion (SNWD) project. The results showed that massive modeling scenarios by use of different hydrodynamic models, if submitted concurrently, can be processed simultaneously in the HydroMP. The data structure of the proposed framework can also be extended to two-dimensional and three-dimensional hydrodynamic situations.
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Shannon, Sarah, Robin Smith, Andy Wiltshire, Tony Payne, Matthias Huss, Richard Betts, John Caesar, Aris Koutroulis, Darren Jones, and Stephan Harrison. "Global glacier volume projections under high-end climate change scenarios." Cryosphere 13, no. 1 (February 1, 2019): 325–50. http://dx.doi.org/10.5194/tc-13-325-2019.
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Abstract. The Paris agreement aims to hold global warming to well below 2 ∘C and to pursue efforts to limit it to 1.5 ∘C relative to the pre-industrial period. Recent estimates based on population growth and intended carbon emissions from participant countries suggest global warming may exceed this ambitious target. Here we present glacier volume projections for the end of this century, under a range of high-end climate change scenarios, defined as exceeding +2 ∘C global average warming relative to the pre-industrial period. Glacier volume is modelled by developing an elevation-dependent mass balance model for the Joint UK Land Environment Simulator (JULES). To do this, we modify JULES to include glaciated and unglaciated surfaces that can exist at multiple heights within a single grid box. Present-day mass balance is calibrated by tuning albedo, wind speed, precipitation, and temperature lapse rates to obtain the best agreement with observed mass balance profiles. JULES is forced with an ensemble of six Coupled Model Intercomparison Project Phase 5 (CMIP5) models, which were downscaled using the high-resolution HadGEM3-A atmosphere-only global climate model. The CMIP5 models use the RCP8.5 climate change scenario and were selected on the criteria of passing 2 ∘C global average warming during this century. The ensemble mean volume loss at the end of the century plus or minus 1 standard deviation is -64±5 % for all glaciers excluding those on the peripheral of the Antarctic ice sheet. The uncertainty in the multi-model mean is rather small and caused by the sensitivity of HadGEM3-A to the boundary conditions supplied by the CMIP5 models. The regions which lose more than 75 % of their initial volume by the end of the century are Alaska, western Canada and the US, Iceland, Scandinavia, the Russian Arctic, central Europe, Caucasus, high-mountain Asia, low latitudes, southern Andes, and New Zealand. The ensemble mean ice loss expressed in sea level equivalent contribution is 215.2±21.3 mm. The largest contributors to sea level rise are Alaska (44.6±1.1 mm), Arctic Canada north and south (34.9±3.0 mm), the Russian Arctic (33.3±4.8 mm), Greenland (20.1±4.4), high-mountain Asia (combined central Asia, South Asia east and west), (18.0±0.8 mm), southern Andes (14.4±0.1 mm), and Svalbard (17.0±4.6 mm). Including parametric uncertainty in the calibrated mass balance parameters gives an upper bound global volume loss of 281.1 mm of sea level equivalent by the end of the century. Such large ice losses will have inevitable consequences for sea level rise and for water supply in glacier-fed river systems.
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Ockenden, M. C., N. A. Chappell, and C. Neal. "Quantifying the differential contributions of deep groundwater to streamflow in nested basins, using both water quality characteristics and water balance." Hydrology Research 45, no. 2 (August 22, 2013): 200–212. http://dx.doi.org/10.2166/nh.2013.035.
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This paper describes use of a hydro-chemical mixing model and a water budget to investigate the presence of deep runoff pathways in two small, nested sub-catchments of the Eden basin, UK (8.8 km2 Blind Beck and 1.0 km2 Low Hall stream). A linear relationship between bicarbonate concentration and electrical conductivity was used in a two-component mixing model. End-members were identified as a high-solute, deep groundwater and a low-solute, soil-water. The mixing model indicated 69% ± 10% deep groundwater in Low Hall for September–December 2008 and 46% ± 8% in Blind Beck for the same period. The water budget also indicated more deep groundwater in Low Hall stream. These results were consistent with the findings of rainfall–runoff models which also indicated the presence of high storage, deeper pathways.
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Bennetsen, Elina, Sacha Gobeyn, Gert Everaert, and Peter Goethals. "Setting Priorities in River Management Using Habitat Suitability Models." Water 13, no. 7 (March 24, 2021): 886. http://dx.doi.org/10.3390/w13070886.
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Worldwide river systems are under pressure from human development. River managers need to identify the most important stressors in a stream basin, to propose effective management interventions for river restoration. In the European Union, the Water Framework Directive proposes the ecological status as the management endpoint for these interventions. Many decision support tools exist that use predictive water quality models to evaluate different river management scenarios, but only a few consider a river’s ecological status in this analysis explicitly. This paper presents a novel method, which combines abiotic monitoring data and biological monitoring data, to provide information and insight on why the ecological status does not reach the good status. We use habitat suitability models as a decision support tool, which can identify the most important stressors in river systems to define management scenarios. To this end, we disassemble the ecological status into its individual building blocks, i.e., the community composition, and we use habitat suitability models to perform an ecological gap analysis. In this paper, we present our method and its underlying ecological concepts, and we illustrate its benefits by applying the method on a regional level for Flanders using a biotic index, the Multimetric Macroinvertebrate Index Flanders (MMIF). To evaluate our method, we calculated the number of correctly classified instances (CCI = 47.7%) and the root-mean-square error (RMSE = 0.18) on the MMIF class and the MMIF value. Furthermore, there is a monotonic decreasing relationship between the results of the priority classification and the ecological status expressed by the MMIF, which is strengthened by the inclusion of ecological concepts in our method (Pearson’s R2 −0.92 vs. −0.87). In addition, the results of our method are complementary to information derived from the legal targets set for abiotic variables. Thus, our proposed method can further optimize the inclusion of monitoring data for the sake of sustainable decisions in river management.
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Blokker, Mirjam, Claudia Agudelo-Vera, Andreas Moerman, Peter van Thienen, and Ilse Pieterse-Quirijns. "Review of applications for SIMDEUM, a stochastic drinking water demand model with a small temporal and spatial scale." Drinking Water Engineering and Science 10, no. 1 (April 26, 2017): 1–12. http://dx.doi.org/10.5194/dwes-10-1-2017.
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Abstract. Many researchers have developed drinking water demand models with various temporal and spatial scales. A limited number of models is available at a temporal scale of 1 s and a spatial scale of a single home. The reasons for building these models were described in the papers in which the models were introduced, along with a discussion on their potential applications. However, the predicted applications are seldom re-examined. SIMDEUM, a stochastic end-use model for drinking water demand, has often been applied in research and practice since it was developed. We are therefore re-examining its applications in this paper. SIMDEUM's original purpose was to calculate maximum demands in order to design self-cleaning networks. Yet, the model has been useful in many more applications. This paper gives an overview of the many fields of application for SIMDEUM and shows where this type of demand model is indispensable and where it has limited practical value. This overview also leads to an understanding of the requirements for demand models in various applications.
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Grayson, Richard, Paul Kay, and Miles Foulger. "The use of GIS and multi-criteria evaluation (MCE) to identify agricultural land management practices which cause surface water pollution in drinking water supply catchments." Water Science and Technology 58, no. 9 (November 1, 2008): 1797–802. http://dx.doi.org/10.2166/wst.2008.569.
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Diffuse pollution poses a threat to water quality and results in the need for treatment for potable water supplies which can prove costly. Within the Yorkshire region, UK, nitrates, pesticides and water colour present particular treatment problems. Catchment management techniques offer an alternative to ‘end of pipe’ solutions and allow resources to be targeted to the most polluting areas. This project has attempted to identify such areas using GIS based modelling approaches in catchments where water quality data were available. As no model exists to predict water colour a model was created using an MCE method which is capable of predicting colour concentrations at the catchment scale. CatchIS was used to predict pesticide and nitrate N concentrations and was found to be generally capable of reliably predicting nitrate N loads at the catchment scale. The pesticides results did not match the historic data possibly due to problems with the historic pesticide data and temporal and spatially variability in pesticide usage. The use of these models can be extended to predict water quality problems in catchments where water quality data are unavailable and highlight areas of concern.
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Saiyed, I. M., P. R. Bullock, H. D. Sapirstein, G. J. Finlay, and C. K. Jarvis. "Thermal time models for estimating wheat phenological development and weather-based relationships to wheat quality." Canadian Journal of Plant Science 89, no. 3 (May 1, 2009): 429–39. http://dx.doi.org/10.4141/cjps07114.
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Accurate prediction of crop phenology is a key requirement for crop development models. The prediction of spring wheat yield and quality from meteorological data can be improved by quantifying heat and moisture conditions during specified phenological phases; therefore, accurate prediction of phenological development is important for estimating weather impacts on wheat quality. The objective of this study was to test the accuracy of biometeorological time (BMT), growing degree days (GDD), and physiological days (Pdays) for prediction of wheat phenological stages and impacts of growing season weather during those stages on wheat bread-making quality. Observed crop phenological stages and detailed weather data across 17 site-years in western Canada for six hard spring wheat varieties were collected to assess BMT, GDD and Pdays. Biometeorological time was most consistent for predicting the length of the seeding to jointing and seeding to anthesis growth stages and second most consistent behind GDD for predicting seeding to soft dough and seeding to maturity. The ability of the BMT and GDD models to predict calendar days to anthesis and maturity were further tested using field data from 166 farms across western Canada. Both GDD and BMT models were effective for predicting time from seeding to anthesis (R2 = 0.84 and 0.90, respectively) and seeding to maturity (R2 = 0.62 and 0.66, respectively). BMT- and GDD-predicted wheat growth phases were used to calculate modeled crop water use by growth period for producer fields. Crop water use is significantly correlated to key bread-making quality parameters of flour protein, farinograph dough development time and farinograph stability. Biometeorological time predicted water use was more highly correlated to these quality parameters than GDD predictions. Accordingly, the BMT scale is recommended for estimation of wheat phenological development especially for modeling weather impacts on wheat end-use quality.Key words: Spring wheat, phenological development, biometeorological time, growing degree day, physiological day, wheat quality
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Keeble, James, Birgit Hassler, Antara Banerjee, Ramiro Checa-Garcia, Gabriel Chiodo, Sean Davis, Veronika Eyring, et al. "Evaluating stratospheric ozone and water vapour changes in CMIP6 models from 1850 to 2100." Atmospheric Chemistry and Physics 21, no. 6 (March 31, 2021): 5015–61. http://dx.doi.org/10.5194/acp-21-5015-2021.
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Abstract. Stratospheric ozone and water vapour are key components of the Earth system, and past and future changes to both have important impacts on global and regional climate. Here, we evaluate long-term changes in these species from the pre-industrial period (1850) to the end of the 21st century in Coupled Model Intercomparison Project phase 6 (CMIP6) models under a range of future emissions scenarios. There is good agreement between the CMIP multi-model mean and observations for total column ozone (TCO), although there is substantial variation between the individual CMIP6 models. For the CMIP6 multi-model mean, global mean TCO has increased from ∼ 300 DU in 1850 to ∼ 305 DU in 1960, before rapidly declining in the 1970s and 1980s following the use and emission of halogenated ozone-depleting substances (ODSs). TCO is projected to return to 1960s values by the middle of the 21st century under the SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5 scenarios, and under the SSP3-7.0 and SSP5-8.5 scenarios TCO values are projected to be ∼ 10 DU higher than the 1960s values by 2100. However, under the SSP1-1.9 and SSP1-1.6 scenarios, TCO is not projected to return to the 1960s values despite reductions in halogenated ODSs due to decreases in tropospheric ozone mixing ratios. This global pattern is similar to regional patterns, except in the tropics where TCO under most scenarios is not projected to return to 1960s values, either through reductions in tropospheric ozone under SSP1-1.9 and SSP1-2.6, or through reductions in lower stratospheric ozone resulting from an acceleration of the Brewer–Dobson circulation under other Shared Socioeconomic Pathways (SSPs). In contrast to TCO, there is poorer agreement between the CMIP6 multi-model mean and observed lower stratospheric water vapour mixing ratios, with the CMIP6 multi-model mean underestimating observed water vapour mixing ratios by ∼ 0.5 ppmv at 70 hPa. CMIP6 multi-model mean stratospheric water vapour mixing ratios in the tropical lower stratosphere have increased by ∼ 0.5 ppmv from the pre-industrial to the present-day period and are projected to increase further by the end of the 21st century. The largest increases (∼ 2 ppmv) are simulated under the future scenarios with the highest assumed forcing pathway (e.g. SSP5-8.5). Tropical lower stratospheric water vapour, and to a lesser extent TCO, shows large variations following explosive volcanic eruptions.
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Su, Benyu, Zhixiong Li, Rongyao Li, Rongfu Rao, and Jingcun Yu. "Exploration Disaster Source of Mine Water by Electromagnetic Radiation." Elektronika ir Elektrotechnika 26, no. 5 (October 27, 2020): 16–21. http://dx.doi.org/10.5755/j01.eie.26.5.25960.
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geological hazard in deep underground mining. Before the rock mass explosion, electromagnetic energy will radiate outward during the deformation and rupture of the coal rocks. Hence, it is possible to use the electromagnetic radiation to predict geological disasters in coal mines. A challenging task using the active source electromagnetic survey technique is to detect geological anomalies, such as disaster water sources and geological structures. To this end, this paper proposes a new electromagnetic radiation solution based on the forward and inversion theory to detect geological anomalies in the coal seam. Based on typical coal mine geological models, the forward modelling and inversion modelling have been performed, respectively. The forward modelling explained the geological anomalies inside the coal seam, which were very sensitive to the response of the radiated electromagnetic field; especially, for the water-bearing geological anomalies. The inversion modelling discovered that the inversion geo-electric parameter distribution agreed well with the actual model. As a result, the proposed method is feasible for geological anomalies detection.
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Wijngaard, René Reijer, Hester Biemans, Arthur Friedrich Lutz, Arun Bhakta Shrestha, Philippus Wester, and Walter Willem Immerzeel. "Climate change vs. socio-economic development: understanding the future South Asian water gap." Hydrology and Earth System Sciences 22, no. 12 (December 6, 2018): 6297–321. http://dx.doi.org/10.5194/hess-22-6297-2018.
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Abstract. The Indus, Ganges, and Brahmaputra (IGB) river basins provide about 900 million people with water resources used for agricultural, domestic, and industrial purposes. These river basins are marked as “climate change hotspots”, where climate change is expected to affect monsoon dynamics and the amount of meltwater from snow and ice, and thus the amount of water available. Simultaneously, rapid and continuous population growth as well as strong economic development will likely result in a rapid increase in water demand. Since quantification of these future trends is missing, it is rather uncertain how the future South Asian water gap will develop. To this end, we assess the combined impacts of climate change and socio-economic development on the future “blue” water gap in the IGB until the end of the 21st century. We apply a coupled modelling approach consisting of the distributed cryospheric–hydrological model SPHY, which simulates current and future upstream water supply, and the hydrology and crop production model LPJmL, which simulates current and future downstream water supply and demand. We force the coupled models with an ensemble of eight representative downscaled general circulation models (GCMs) that are selected from the RCP4.5 and RCP8.5 scenarios, and a set of land use and socio-economic scenarios that are consistent with the shared socio-economic pathway (SSP) marker scenarios 1 and 3. The simulation outputs are used to analyse changes in the water availability, supply, demand, and gap. The outcomes show an increase in surface water availability towards the end of the 21st century, which can mainly be attributed to increases in monsoon precipitation. However, despite the increase in surface water availability, the strong socio-economic development and associated increase in water demand will likely lead to an increase in the water gap during the 21st century. This indicates that socio-economic development is the key driver in the evolution of the future South Asian water gap. The transgression of future environmental flows will likely be limited, with sustained environmental flow requirements during the monsoon season and unmet environmental flow requirements during the low-flow season in the Indus and Ganges river basins.
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Endres, Anthony L., and Edward A. Bertrand. "A pore-size scale model for the dielectric properties of water-saturated clean rocks and soils." GEOPHYSICS 71, no. 6 (November 2006): F185—F193. http://dx.doi.org/10.1190/1.2360192.
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The dielectric properties of water-saturated rock and soils are strongly dependent on the amount and nature of their porosity; interpretation of these geophysical data requires petrophysical models that incorporate both of these elements. The differential effective medium approximation (DEMA) is used to develop a dielectric permittivity model for clean (i.e., clay free) media that divides the pore spaces into elements corresponding to three categories of relative size scale: microscopic porosity (e.g., intergranular cracks), mesoscopic porosity (e.g., main pore volumes), and macroscopic porosity (e.g., vugs and fractures). The hierarchical size-scale structure imposed by the DEMA iterative embedding process is used to assign each pore space category its role in model construction. Use of this model demonstrates that the relationship between dielectric permittivity and porosity is significantly affected by the size scales of pores present in the rock models. A region of realizable permittivity-porosity values is obtained by varying the pore structure in the scaled-porosity model. The bounds of this region correspond to end-member porosity models. Analysis of experimental permittivity data for water-saturated sandstones and carbonates that cover a substantial range of porosity values found that the scaled-porosity models account for a significant part of the variability in experimental data.
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Wu, Yuqiang, Qinhui Wang, Ge Li, and Jidong Li. "Data-driven runoff forecasting for Minjiang River: a case study." Water Supply 20, no. 6 (June 26, 2020): 2284–95. http://dx.doi.org/10.2166/ws.2020.134.
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Abstract Long-term runoff forecasting has the characteristics of a long forecast period, which can be widely applied in environmental protection, hydropower operation, flood prevention and waterlogging management, water transport management, and optimal allocation of water resources. Many models and methods are currently used for runoff prediction, and data-driven models for runoff prediction are now mainstream methods, but their prediction accuracy cannot meet the needs of production departments. To this end, the present research starts with this method and, based on a support vector machine (SVM), it introduces ant colony optimization (ACO) to optimize its penalty coefficient C, Kernel function parameter g, and insensitivity coefficient p, to construct a data-driven ACO-SVM model. The validity of the method is confirmed by taking the Minjiang River Basin as an example. The results show that the runoff predicted by use of ACO-SVM is more accurate than that of the default parameter SVM and the Bayesian method.
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Koeve, W., H. Wagner, P. Kähler, and A. Oschlies. "<sup>14</sup>C-age tracers in global ocean circulation models." Geoscientific Model Development 8, no. 7 (July 16, 2015): 2079–94. http://dx.doi.org/10.5194/gmd-8-2079-2015.
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Abstract. The natural abundance of 14C in total CO2 dissolved in seawater (DIC) is a property applied to evaluate the water age structure and circulation in the ocean and in ocean models. In this study we use three different representations of the global ocean circulation augmented with a suite of idealised tracers to study the potential and limitations of using natural 14C to determine water age, which is the time elapsed since a body of water has been in contact with the atmosphere. We find that, globally, bulk 14C-age is dominated by two equally important components, one associated with ageing, i.e. the time component of circulation, and one associated with a "preformed 14C-age". The latter quantity exists because of the slow and incomplete atmosphere–ocean equilibration of 14C particularly in high latitudes where many water masses form. In the ocean's interior, preformed 14C-age behaves like a passive tracer. The relative contribution of the preformed component to bulk 14C-age varies regionally within a given model, but also between models. Regional variability in the Atlantic Ocean is associated with the mixing of waters with very different end members of preformed 14C-age. Here, variations in the preformed component over space and time mask the circulation component to an extent that its patterns are not detectable from bulk 14C-age. Between models, the variability of preformed 14C-age can also be considerable (factor of 2), related to the combination of physical model parameters, which influence circulation dynamics or gas exchange. The preformed component was found to be very sensitive to gas exchange and moderately sensitive to ice cover. In our model evaluation, the choice of the gas-exchange constant from within the currently accepted range of uncertainty had such a strong influence on preformed and bulk 14C-age that if model evaluation would be based on bulk 14C-age, it could easily impair the evaluation and tuning of a model's circulation on global and regional scales. Based on the results of this study, we propose that considering preformed 14C-age is critical for a correct assessment of circulation in ocean models.
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Alibabaei, Khadijeh, Pedro D. Gaspar, and Tânia M. Lima. "Crop Yield Estimation Using Deep Learning Based on Climate Big Data and Irrigation Scheduling." Energies 14, no. 11 (May 22, 2021): 3004. http://dx.doi.org/10.3390/en14113004.
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Deep learning has already been successfully used in the development of decision support systems in various domains. Therefore, there is an incentive to apply it in other important domains such as agriculture. Fertilizers, electricity, chemicals, human labor, and water are the components of total energy consumption in agriculture. Yield estimates are critical for food security, crop management, irrigation scheduling, and estimating labor requirements for harvesting and storage. Therefore, estimating product yield can reduce energy consumption. Two deep learning models, Long Short-Term Memory and Gated Recurrent Units, have been developed for the analysis of time-series data such as agricultural datasets. In this paper, the capabilities of these models and their extensions, called Bidirectional Long Short-Term Memory and Bidirectional Gated Recurrent Units, to predict end-of-season yields are investigated. The models use historical data, including climate data, irrigation scheduling, and soil water content, to estimate end-of-season yield. The application of this technique was tested for tomato and potato yields at a site in Portugal. The Bidirectional Long Short-Term memory outperformed the Gated Recurrent Units network, the Long Short-Term Memory, and the Bidirectional Gated Recurrent Units network on the validation dataset. The model was able to capture the nonlinear relationship between irrigation amount, climate data, and soil water content and predict yield with an MSE of 0.017 to 0.039. The performance of the Bidirectional Long Short-Term Memory in the test was compared with the most commonly used deep learning method, the Convolutional Neural Network, and machine learning methods including a Multi-Layer Perceptrons model and Random Forest Regression. The Bidirectional Long Short-Term Memory outperformed the other models with an R2 score between 0.97 and 0.99. The results show that analyzing agricultural data with the Long Short-Term Memory model improves the performance of the model in terms of accuracy. The Convolutional Neural Network model achieved the second-best performance. Therefore, the deep learning model has a remarkable ability to predict the yield at the end of the season.
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López-Moreno, J. I., S. M. Vicente-Serrano, E. Moran-Tejeda, J. Zabalza, J. Lorenzo-Lacruz, and J. M. García-Ruiz. "Impact of climate evolution and land use changes on water yield in the ebro basin." Hydrology and Earth System Sciences 15, no. 1 (January 25, 2011): 311–22. http://dx.doi.org/10.5194/hess-15-311-2011.
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Abstract. In this study the climatic and hydrological trends across 88 sub-basins of the Ebro River basin were analyzed for the period 1950–2006. A new database of climate information and river flows for the entire basin facilitated a spatially distributed assessment of climate-runoff relationships. It constitutes the first assessment of water yield evolution across the whole Ebro basin, a very representative example of large Mediterranean rivers. The results revealed a marked decrease in river discharges in most of the sub-basins. Moreover, a number of changes in the seasonality of the river regime was found, resulting from dam regulation and a decrease in snowpack in the headwaters. Significant and positive trends in temperature were observed across most of the basin, whereas most of the precipitation series showed negative coefficients, although the decrease in magnitude was low. The time evolution of the residuals from empirical models that relate climate and runoff in each sub-basin provided evidence that climate alone does not explain the observed decrease in river discharge. Thus, changes in water yield are associated with an increase in evapotranspiration rates in natural vegetation, growth of which has expanded as a consequence of land abandonment in areas where agricultural activities and livestock pressure have decreased. In the lowlands of the basin the decrease in water yield has been exacerbated by increased water consumption for domestic, industrial and agricultural uses. Climate projections for the end of the 21st century suggest a reduced capacity for runoff generation because of increasing temperature and less precipitation. Thus, the maintenance of water supply under conditions of increasing demand presents a challenging issue requiring appropriate coordination amongst politicians and managers.
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López-Moreno, J. I., S. M. Vicente-Serrano, E. Moran-Tejeda, J. Zabalza, J. Lorenzo-Lacruz, and J. M. García-Ruiz. "Impact of climate evolution and land use changes on water yield in the Ebro basin." Hydrology and Earth System Sciences Discussions 7, no. 2 (April 29, 2010): 2651–81. http://dx.doi.org/10.5194/hessd-7-2651-2010.
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Abstract. In this study the climatic and hydrological trends across 88 sub-basins of the Ebro River basin were analyzed for the period 1950–2006. A new database of climate information and river flows for the entire basin facilitated a spatially distributed assessment of climate-runoff relationships. It constitutes the first assessment of water yield evolution across the whole Ebro basin, a very representative example of large Mediterranean rivers. The results revealed a marked decrease in river discharges in most of the sub-basins. Moreover, a number of changes in the seasonality of the river regime was found, resulting from dam regulation and a decrease in snowpack in the headwaters. Significant and positive trends in temperature were observed across most of the basin, whereas most of the precipitation series showed negative coefficients, although the decrease in magnitude was low. The time evolution of the residuals from empirical models that relate climate and runoff in each sub-basin provided evidence that climate alone does not explain the observed decrease in river discharge. Thus, changes in water yield are associated with an increase in evapotranspiration rates in natural vegetation, growth of which has expanded as a consequence of land abandonment in areas where agricultural activities and livestock pressure have decreased. In the lowlands of the basin the decrease in water yield has been exacerbated by increased water consumption for domestic, industrial and agricultural uses. Climate projections for the end of the 21st century suggest a reduced capacity for runoff generation because of increasing temperature and less precipitation. Thus, the maintenance of water supply under conditions of increasing demand presents a challenging issue requiring appropriate coordination amongst politicians and managers.
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Koeve, W., H. Wagner, P. Kähler, and A. Oschlies. "<sup>14</sup>C-age tracers in global ocean circulation models." Geoscientific Model Development Discussions 7, no. 5 (October 24, 2014): 7033–74. http://dx.doi.org/10.5194/gmdd-7-7033-2014.
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Abstract. The natural abundance of 14C in total CO2 dissolved in seawater is a property applied to evaluate the water age structure and circulation in the ocean and in ocean models. In this study we use three different representations of the global ocean circulation augmented with a suite of idealised tracers to study the potential and limitations of using natural 14C to determine water age, the time elapsed since a body of water had contact with the atmosphere. We find that, globally, bulk 14C-age is dominated by two equally important components, one associated with aging, i.e. the time component of circulation and one associated with a "preformed 14C-age". This latter quantity exists because of the slow and incomplete atmosphere/ocean equilibration of 14C in particular in high latitudes where many water masses form. The relative contribution of the preformed component to bulk 14C-age varies regionally within a given model, but also between models. Regional variability, e.g. in the Atlantic Ocean is associated with the mixing of waters with very different end members of preformed 14C-age. In the Atlantic, variations in the preformed component over space and time mask the circulation component to an extent that its patterns are not detectable from bulk 14C-age alone. Between models the variability of age can also be considerable (factor of 2), related to the combinations of physical model parameters, which influence circulation dynamics, and gas exchange in the models. The preformed component was found to be very sensitive to gas exchange and moderately sensitive to ice cover. In our model evaluation exercise, the choice of the gas exchange constant from within the current range of uncertainty had such a strong influence on preformed and bulk 14C-age that if model evaluation would be based on bulk 14C-age it could easily impair the evaluation and tuning of a models circulation on global and regional scales. Based on the results of this study, we propose that considering preformed 14C-age is critical for a correct assessment of circulation in ocean models.
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Sakamoto, Shogo, Yu Nagai, Masahiro Sugiyama, Shinichiro Fujimori, Etsushi Kato, Ryoichi Komiyama, Yuhji Matsuo, Ken Oshiro, and Diego Silva Herran. "Demand-side decarbonization and electrification: EMF 35 JMIP study." Sustainability Science 16, no. 2 (March 2021): 395–410. http://dx.doi.org/10.1007/s11625-021-00935-w.
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AbstractJapan’s long-term strategy submitted to the United Nations Framework Convention on Climate Change emphasizes the importance of improving the electrification rates to reducing GHG emissions. Using the five models participating in Energy Modeling Forum 35 Japan Model Intercomparison project (JMIP), we focused on the demand-side decarbonization and analyzed the final energy composition required to achieve 80% reductions in GHGs by 2050 in Japan. The model results show that the electricity share in final energy use (electrification rate) needs to reach 37–66% in 2050 (26% in 2010) to achieve the emissions reduction of 80%. The electrification rate increases mainly due to switching from fossil fuel end-use technologies (i.e. oil water heater, oil stove and combustion-engine vehicles) to electricity end-use technologies (i.e. heat pump water heater and electric vehicles). The electricity consumption in 2050 other than AIM/Hub ranged between 840 and 1260 TWh (AIM/Hub: 1950TWh), which is comparable to the level seen in the last 10 years (950–1035 TWh). The pace at which electrification rate must be increased is a challenge. The model results suggest to increase the electrification pace to 0.46–1.58%/yr from 2030 to 2050. Neither the past electrification pace (0.30%/year from 1990 to 2010) nor the outlook of the Ministry of Economy, Trade and Industry (0.15%/year from 2010 to 2030) is enough to reach the suggested electrification rates in 2050. Therefore, more concrete measures to accelerate dissemination of electricity end-use technologies across all sectors need to be established.
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Tewari, Rachna, Jeff Johnson, Steven Mauget, Gary Leiker, Katharine Hayhoe, Annette Hernandez, Darren Hudson, Chenggang Wang, Dennis Patterson, and Ken Rainwater. "Using climate scenarios to evaluate future impacts on the groundwater resources and agricultural economy of the Texas High Plains." Journal of Water and Climate Change 6, no. 3 (December 16, 2014): 561–77. http://dx.doi.org/10.2166/wcc.2014.147.
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This study evaluated the impacts of future climate scenarios on the groundwater resources and agricultural economy of the Texas High Plains, using Hale county as a case study. Climate change impacts were incorporated into regional economic models using weather projections to develop crop response functions from crop models. These projections are based on quantitative projections of precipitation, potential evapotranspiration, and temperature trends driven by simulations from the latest IPCC AR4 climate models (Community Climate System Model (CCSM), Geophysical Fluid Dynamics Laboratory (GFDL), UK Met Office Hadley Model (HadCM3), and Parallel Climate Model (PCM)) under two specific emissions scenarios, A1B (mid-range) and A1FI (higher). Results indicated that for both the emission scenarios, saturated thickness, water use per cropland acre, and irrigated acreage declined under climatic predictions by all four models. At the end of the 90 year horizon, the A1B scenario resulted in a decline in average net income per acre as predicted by the CCSM and HadCM3 models, while the GFDL and PCM models predicted an increase in average net income per acre. Under the A1FI scenario, the CCSM, GFDL, and PCM model projections led to increased average net income per acre, while climate projections under the HadCM3 model indicated a decline in average net income per acre at the end of the 90 year horizon.
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Yemenu, F., and D. Chemeda. "Climate resources analysis for use of planning in crop production and rainfall water management in the central highlands of Ethiopia, the case of Bishoftu district, Oromia region." Hydrology and Earth System Sciences Discussions 7, no. 3 (June 23, 2010): 3733–63. http://dx.doi.org/10.5194/hessd-7-3733-2010.
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Abstract. Agricultural practices and water resources management in the central highlands of Ethiopia is highly dependant and associated with climatic resources and their pattern and hence wise use of those resources is a priority for the region. Accordingly, a study was conducted to asses and critically quantity the climate resources of the central high lands of Ethiop, Bishoftu district. Thirty three years of weather record data has been used for the work. The onset, duration and end of the growing seasons were defined and quantified based on FAO and Reddy models while the dry and wet spell distributions and the drought events were calculated using the Markov chain models and the standardized precipitation index (SPI) respectively. The results revealed that the mean onset of the main (Kiremt) growing season was found to occur during the second meteorological decade and ended during the end of September. Similarly, though unreliable and only few occurred during the entire study period, the mean onset of the shorter (Belg) season was found to occur during the beginning of the first decade of April. The length of the growing season during the main rainy season, (Kiremt,) ranged from 112 to 144 days with a standard deviation of 9.6 days and coefficient of variation of 7.5%. However, the mean growing length during the Belg season was found to be 22.4 days with a standard deviation of 27 days and coefficient of variation of 122%. The results of analysis obtained both from the Markov Chain and Reddy models indicated higher probabilities of dry spell occurrences during the shorter season (Belg) but the occurrences of the same in the main rainy season (Kiremt) was very minimal. Like wise, the SPI model detected some drought events ranging from mild to severe classes in both seasons based on one a month time scale analysis. A considerable attention of maximizing crop harvest during the main rainy season is practically important.
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Ozmen, Ozgur, James Nutaro, Michael Starke, Jeffrey Munk, Larry Roberts, Xiao Kou, Piljae Im, et al. "Power Grid Simulation Testbed for Transactive Energy Management Systems." Sustainability 12, no. 11 (May 28, 2020): 4402. http://dx.doi.org/10.3390/su12114402.
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To effectively engage demand-side and distributed energy resources (DERs) for dynamically maintaining the electric power balance, the challenges of controlling and coordinating building equipment and DERs on a large scale must be overcome. Although several control techniques have been proposed in the literature, a significant obstacle to applying these techniques in practice is having access to an effective testing platform. Performing tests at scale using real equipment is impractical, so simulation offers the only viable route to developmental testing at scales of practical interest. Existing power-grid testbeds are unable to model individual residential end-use devices for developing detailed control formulations for responsive loads and DERs. Furthermore, they cannot simulate the control and communications at subminute timescales. To address these issues, this paper presents a novel power-grid simulation testbed for transactive energy management systems. Detailed models of primary home appliances (e.g., heating and cooling systems, water heaters, photovoltaic panels, energy storage systems) are provided to simulate realistic load behaviors in response to environmental parameters and control commands. The proposed testbed incorporates software as it will be deployed, and enables deployable software to interact with various building equipment models for end-to-end performance evaluation at scale.
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Morales-Marín, Luis, Howard Wheater, and Karl-Erich Lindenschmidt. "Potential Changes of Annual-Averaged Nutrient Export in the South Saskatchewan River Basin under Climate and Land-Use Change Scenarios." Water 10, no. 10 (October 12, 2018): 1438. http://dx.doi.org/10.3390/w10101438.
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Climate and land-use changes modify the physical functioning of river basins and, in particular, influence the transport of nutrients from land to water. In large-scale basins, where a variety of climates, topographies, soil types and land uses co-exist to form a highly heterogeneous environment, a more complex nutrient dynamic is imposed by climate and land-use changes. This is the case of the South Saskatchewan River (SSR) that, along with the North Saskatchewan River, forms one of the largest river systems in western Canada. The SPAtially Referenced Regression On Watershed (SPARROW) model is therefore implemented to assess water quality in the basin, in order to describe spatial and temporal patterns and identify those factors and processes that affect water quality. Forty-five climate and land-use change scenarios comprehended by five General Circulation Models (GCMs) and three Representative Concentration Pathways (RCPs) were incorporated into the model to explain how total nitrogen (TN) and total phosphorus (TP) export could vary across the basin in 30, 60 and 90 years from now. According to model results, annual averages of TN and TP export in the SSR are going to increase in the range 0.9–1.28 kg km − 2 year − 1 and 0.12–0.17 kg km − 2 year − 1 , respectively, by the end of the century, due to climate and land-use changes. Higher increases of TP compared to TN are expected since TP and TN are going to increase ∼36% and ∼21%, respectively, by the end of the century. This research will support management plans in order to mitigate nutrient export under future changes of climate and land use.
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Kajewska-Szkudlarek, Joanna, and Wojciech Łyczko. "Assessment of Hellwig Method for Predictors’ Selection in Groundwater Level Time Series Forecasting." Water 13, no. 6 (March 12, 2021): 778. http://dx.doi.org/10.3390/w13060778.
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Effective groundwater planning and management should be based on the prediction of available water volume. The complex nature of groundwater systems makes this complicated and requires the use of complex methods. Data-driven models using computational intelligence are becoming increasingly popular in that field. The key issue in predictive modelling is the selection of input variables. Wrocław-Osobowice irrigation fields were a wastewater treatment plant until 2013. The monitoring of groundwater levels is being continued to assess the water relations in that area after the end of their exploitation. The aim of the study was to assess the Hellwig method for predictors’ selection in groundwater level forecasting with support vector regression models. Data covered the daily time series of groundwater level in the period 2015–2019. Obtained models with a root mean squared error (RMSE) of 0.024–0.292 m and r2 of 0.7–0.9 were considered as high quality. Moreover, they showed good prediction ability for high as well as low groundwater values. Additionally, the proposed method is simple, and its implementation only requires access to groundwater level measurement data. It may be useful in groundwater management and planning in terms of actual climate change and threat of water deficits.
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Brinkman, F. P., T. V. Kane, R. R. McCullough, and J. W. Miertschin. "Use of Full-Field Simulation to Design a Miscible CO2 Flood." SPE Reservoir Evaluation & Engineering 2, no. 03 (June 1, 1999): 230–37. http://dx.doi.org/10.2118/56882-pa.
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Summary A study using full-field reservoir modeling optimized the design of a miscible CO2 flood project for the Sharon Ridge Canyon Unit. The study began with extensive data gathering in the field and building a full-field three-dimensional geologic model. A full-field simulation model with relatively coarse gridding was subsequently built and used to history match the waterflood. This waterflood model highlighted areas in the field with current high oil saturations as priority targets for CO2 flooding and generated a forecast of reserves from continued waterflooding. Predictions for the CO2 flood used an in-house four-component simulator (stock tank oil, solution gas, water, CO2. A full-field CO2 model with more finely gridded patterns was built using oil saturations and pressures at the end of history in the waterflood model. The CO2 model identified the best patterns for CO2 flooding and was instrumental in selecting a strategy for sizing the initial flood area and in determining the size, location, and timing of future expansions of the CO2 flood. Introduction The Sharon Ridge Canyon Unit (SRCU) is located in West Texas, about 70 miles northeast of the city of Midland. The Unit covers 13,712 acres. Fig. 1 shows the Horseshoe Atoll, a trend of more than 40 oil fields covering several West Texas counties. SRCU is geologically continuous with the Diamond M Unit and the giant Kelly-Snyder Field (SACROC Unit) to the northeast. Production is from the Canyon Reef formation, a thick carbonate buildup of late Pennsylvanian Canyon and Cisco age, and occurs at an average depth of 6600 feet. There are active CO2 floods in this formation at SACROC, Reinecke, and the Salt Creek field. Sharon Ridge was discovered in 1949 and developed on 40 acre spacing by 1953 with about 340 wells. The reservoir initially contained undersaturated oil at 3135 psi. Production was by expansion drive until 1952 when pressure fell below the bubble point of 1850 psi over most of the field. In 1955, the field was unitized and a peripheral waterflood was started to stabilize reservoir pressure. The waterflood is now at a mature stage with oil recovery approaching 50% of the original oil-in-place (OOIP). There has been limited infill drilling with 22 wells drilled at 20-acre spacing. Screening studies identified SRCU as a good candidate for a miscible CO2 flood project. These studies included core flood displacements, pattern element simulation models, and detailed evaluations of similar fields with CO2 floods. Laboratory core displacements showed a remaining oil to waterflood of over 40% with subsequent injection of CO2 reducing oil saturation to less than 10%. Simulations with small element models have also shown significant incremental oil recovery from injection of CO2 at SRCU. SRCU has reservoir properties similar to SACROC which has reported significant additional oil recovery from miscible CO2 flooding (Ref. 1). The goal of full-field modeling was to design a miscible CO2 flood with maximum economic potential. Key issues for project design include the amount and location of remaining oil, reservoir sweep efficiency, flood rate, gas injection volume, strategy for handling increased produced gas, and projection of continued secondary operations. To address these issues, we built three different full-field three-dimensional (3D) models: geologic model, coarse-grid waterflood model, and fine-grid CO2 flood model. Recent advances in computer technology made this approach possible as opposed to the prior approach of running type-element models and scaling up those results to field rates. The approach of using field-scale simulation models to study optimizations for another CO2 flood in West Texas has been reported in Ref. 2. Thus, advancing technology and prior experience led us to embark on this ambitious approach to use full-field modeling to design our CO2 flood. Geologic Modeling Geology. The reservoir is a thick carbonate buildup that is predominately limestone. Fig. 2 shows the structure on the top of the reservoir. Geographic areas of the field have been named: North End, South End, and Southeast Pinnacle. The topography is extremely variable, with the hydrocarbon column averaging 115 feet and ranging to a maximum of 450 feet in the South End area of the field. A large portion of the North End has over 90 feet of gross reservoir thickness above the original oil-water contact. Table 1 is a summary of reservoir rock and fluid properties. The reservoir has been subdivided into five depositional sequences or zones, four of which are shown in Fig. 3. The lower zones (4, 5) are found over almost the entire field while upper zones (1, 2, 3) are more areally restricted. Zones are usually separated by intervals of low porosity limestone with few shales in the reservoir. Most wells drilled during initial field development did not penetrate the entire reservoir, thus limiting description of the lower zones. A more detailed discussion of the geologic setting and depositional facies is available in Ref. 3. Model Design. Building a full-field 3D geologic model of SRCU presented several unique challenges, including having modern porosity logs on only a few wells and only 90 full penetrations of the reservoir. To address this problem of limited data, an extensive data acquisition program was implemented. This program included deepening 19 wells, coring 11 wells, and obtaining 49 miles of new two-dimensional (2D) seismic lines. After gathering these data, all new and old core, well log, and seismic data were integrated to develop a sequence stratigraphic reservoir framework.
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Alajmi, Turki, and Patrick Phelan. "Modeling and Forecasting End-Use Energy Consumption for Residential Buildings in Kuwait Using a Bottom-Up Approach." Energies 13, no. 8 (April 17, 2020): 1981. http://dx.doi.org/10.3390/en13081981.
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To meet the rapid-growing demand for electricity in Kuwait, utility planners need to be informed on the energy consumption to implement energy efficiency measures to manage sustainable load growth and avoid the high costs of increasing generation capacities. The first step of forecasting the future energy profile is to establish a baseline for Kuwait (i.e., a business-as-usual reference scenario where no energy efficiency incentives were given and the adoption of energy efficient equipment is purely market-driven). This paper presents an investigation of creating a baseline end-use energy profile until 2040 for the residential sector in Kuwait by using a bottom-up approach. The forecast consists of mainly two steps: (1) Forecasting the quantity of the residential energy-consuming equipment in the entire sector until 2040 where this paper used a stock-and-flow model that accounted for the income level, electrification, and urbanization rate to predict the quantify of the equipment over the years until 2040, and (2) calculate the unit energy consumption (UEC) for all equipment types using a variety of methods including EnergyPlus simulation models for cooling equipment. By combining the unit energy consumption and quantity of the equipment over the years, this paper established a baseline energy use profile for different end-use equipment for Kuwait until 2040. The results showed that the air conditioning loads accounted for 67% of residential electrical consumption and 72% of residential peak demand in Kuwait. The highest energy consuming appliances were refrigerators and freezers. Additionally, the air conditioning loads are expected to rise in the future, with an average annual growth rate of 2.9%, whereas the lighting and water heating loads are expected to rise at a much lower rate.
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Khanal, S. P., B. Poudel, R. P. Koirala, and N. P. Adhikari. "Solvation Free Energy of Protonated Lysine: Molecular Dynamics Study." Journal of Nepal Physical Society 7, no. 2 (August 6, 2021): 69–75. http://dx.doi.org/10.3126/jnphyssoc.v7i2.38625.
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In the present work, we have used an alchemical approach for calculating solvation free energy of protonated lysine in water from molecular dynamics simulations. These approaches use a non-physical pathway between two end states in order to compute free energy difference from the set of simulations. The solute is modeled using bonded and non-bonded interactions described by OPLS-AA potential, while four different water models: TIP3P, SPC, SPC/E and TIP4P are used. The free energy of solvation of protonated lysine in water has been estimated using thermodynamic integration, free energy perturbation, and Bennett acceptance ratio methods at 310 K temperature. The contributions to the free energy due to van der Waals and electrostatics parameters are also separately computed. The estimated values of free energy of solvation using different methods are in well agreement with previously reported experimental value within 14 %.