Abstract Predicting change of water quality in complex aquatic ecosystems is always challenged by... more Abstract Predicting change of water quality in complex aquatic ecosystems is always challenged by accurate prediction of changes in hydrological, hydraulic and hydrodynamic behaviours at catchment scales. Therefore, developing a fully integrated catchment-wide modelling and monitoring framework is particularly important. In this paper, we introduce a comprehensive and integrated catchment-scale monitoring and modelling approach that consists of: 1) input datasets either from real-time sensors or sampling measurements or modelling; 2) a coupled catchment-scale modelling system including 1D-hydrological/hydraulic models, 1D-emission and transport models as well as 3D-hydrodynamic and water quality models; 3) data assimilation techniques; and 4) an operational management system (OMS). Results from various case studies demonstrate that this integrative system can be used not only for long-term predictions of water quality levels and scenario tests, but also for event predictions and real-time forecasting of water quality. This approach produces synergistic effects in modelling capability for facilitating research and management applications.
International Journal of System of Systems Engineering, 2013
Managing CO2 emission control policy is a complex problem because of uncertainties in CO2 emissio... more Managing CO2 emission control policy is a complex problem because of uncertainties in CO2 emission process and CO2 uptake, and irreversibility in investment decisions. Traditional method using benefit cost analysis for evaluation of CO2 reduction policy is not effective in presence of deep uncertainties. Real options analysis approach is an alternative methodology which incorporates uncertainties and flexible timing in decision making. It allows the policymaker to learn and then act when the more information is available to resolve the uncertainties. This paper proposes a methodology with real options analysis for analysing the timing and conditions of adoption of CO2 reduction policies. CO2 emission is modelled as a stochastic process and CO2 observation data are used to statistically estimate the parameters of the stochastic CO2 emission model. A perpetual time model is developed to investigate CO2 emission cutback policy and CO2 concentration abatement policy and closed form analytical solutions are pr...
International Journal for Numerical Methods in Fluids, 2008
... An example of error correction in a non-measurement station is given in Figure 5 where the CM... more ... An example of error correction in a non-measurement station is given in Figure 5 where the CMBmodel output at grid point 2 was corrected using the proposed error correction scheme. For a forecast horizon of 12 h, the phase error was greatly removed and only small ...
Models of water resources systems are conceived to capture the underlying environmental dynamics ... more Models of water resources systems are conceived to capture the underlying environmental dynamics occurring within watersheds. All such models can be regarded as working hypotheses, differing in the aspects of process representation and conceptualization. Most of the associated efforts in the water resources research community is dedicated to development of new models that perform well under specific atmospheric conditions and catchment properties. In this context, flexible modeling frameworks are gaining importance as they facilitate the model building process by providing the model building blocks, whereby the hydrologist is free to assemble the model for task at hand. Such flexible models have high degree of transferability, which in turn aid in progressing toward a unified hydrological theory at catchment scale. However, in cases without sufficient insights regarding a catchment characteristics and/or lack of expert's knowledge, one may have to try a large number of model configurations based on available model building blocks to construct an appropriate model for the catchment of interest. Undoubtedly, this may be time consuming and computationally intensive. This paper proposes a novel model building algorithm, which uses the full potential of flexible modeling frameworks by searching the model space and inferring suitable model configurations relying on machine learning. Proposed machine learning algorithm is based on evolutionary computation approach using genetic programming (GP). State‐of‐art GP applications in rainfall‐runoff modeling so far used the algorithm as a short‐term forecasting tool that generates an expected future time series very similar to neural networks application. In this case, the proposed algorithm develops a physically meaningful rainfall‐runoff model. Although at the moment we learn models using two flexible modeling frameworks (SUPERFLEX and FUSE), the model induction toolkit can be armed with any internal coherence building blocks. The model induction capabilities of the proposed framework have been evaluated on the Blackwater River basin, Alabama, United States. The model configurations evolved through the model induction toolkit are consistent with the fieldwork investigations and previously reported research findings.
Changes in precipitation extremes in the tropical urban context is complex, where the precipitati... more Changes in precipitation extremes in the tropical urban context is complex, where the precipitation activities are influenced by the combined effects of El Niño–Southern Oscillation (ENSO), global warming and local effects. This study presents a comprehensive framework to investigate the variability and trends in precipitation extremes in a tropical urban city‐state, Singapore, based on a set of extreme indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI). The long‐term trends in the precipitation extremes over the period from 1980 until 2013 are examined using an iterative‐based Mann–Kendall trend test. Besides, the relative importance of precipitation frequency and intensity in inter‐annual variability of wet‐day precipitation totals is investigated. Finally, the correlations between precipitation extremes and three potential large‐scale and local factors, i.e. ENSO, global mean temperature and local temperature are analysed based on linear regression method. Results reveal that annual wet‐day precipitation totals, as well as average wet‐day precipitation intensity, have increased significantly, accompanied by a significant increase in the frequency and intensity of precipitation extremes in Singapore. The inter‐annual variability of wet‐day precipitation totals is mainly dominated by precipitation intensity. Significant correlations are found between precipitation extremes and all the three factors, and the signature of local effects is more evident than global warming. These findings have implications for adaption planning and disaster risk reduction in Singapore in the context of global warming.
Page 1. An Evolutionary Approach to Knowledge Induction: Genetic Programming in Hydraulic Enginee... more Page 1. An Evolutionary Approach to Knowledge Induction: Genetic Programming in Hydraulic Engineering Vladan Babovic*, Maarten Keijzer*, David Rodríguez Aguilera** and Joe Harrington *** * DHI Water & Environment ...
... A landmark in the chaos signal processing was made with the origin of embedding ... of chaoti... more ... A landmark in the chaos signal processing was made with the origin of embedding ... of chaotictime series because these share many fundamental ideas with the time-delay embedding ... was undertaken using the historical data set available at Horsburgh lighthouse and Hong ...
Governments face the daunting task of developing policies and making investment decisions for cli... more Governments face the daunting task of developing policies and making investment decisions for climate change adaptation in an environment that consist of complex, interlinked systems with manifold uncertainties. Instead of responding to surprises and making decisions on ad hoc basis, a structured approach to deal with complex systems and uncertainties can provide indispensable support for policy making. This contribution proposes a structured approach for designing climate adaptation policies based on the concepts of Adaptation Pathways, Adaptive Policy Making, and Real Options Analysis. Such an approach results in incorporation of flexibility that allows change over time in response to how the future unfolds, what is learned about the system, and changes in societal preferences. The approach is illustrated by looking at drainage policies and measures to address flooding in Singapore.
Inducing equations based on theory and data is a timehonoured technique in science. This is usual... more Inducing equations based on theory and data is a timehonoured technique in science. This is usually done manually, based on theoretical understanding and previously established equations. In this work, for a particular problem in hydraulics, human induction of equations is compared with the use of genetic programming. It will be shown that even with the use of synthetic data for training, genetic programming was capable of identifying a relationship that was more concise and more accurate than the relationship uncovered by scientists. As such this is a human-competitive result. Furthermore it will be shown that the genetic programming induced expression could be embedded in a line of theoretical work, filling in a few gaps in an already established line of reasoning. The resulting equation is the most accurate and elegant formulation of vegetation induced resistance to date.
The computer-controlled operating environments of such facilities as automated factories, nuclear... more The computer-controlled operating environments of such facilities as automated factories, nuclear power plants, telecommunication centres and space stations are continually becoming more complex.The situation is similar, if not even more apparent and urgent, in the case of water. Water is not only mankind's most valuable natural resource, but one which is in increasingly limited supply. The fresh water is the vita! natural resource which supports all environmental activities, that is, natura! economy, and all human socio-economic activities, that is, the artificial economy. The pressure for a sustainable control and exploration of water and thus for the peaceful co-existence of human- and hydro-economies, is not only a human, socio-economic pressure, but it is the question of life and death! Hydroinformatics - the nascent technology concerned with the flow of information related to the flow of fluids and all that they convey - is probably the best possible answer yet proposed to...
Abstract Predicting change of water quality in complex aquatic ecosystems is always challenged by... more Abstract Predicting change of water quality in complex aquatic ecosystems is always challenged by accurate prediction of changes in hydrological, hydraulic and hydrodynamic behaviours at catchment scales. Therefore, developing a fully integrated catchment-wide modelling and monitoring framework is particularly important. In this paper, we introduce a comprehensive and integrated catchment-scale monitoring and modelling approach that consists of: 1) input datasets either from real-time sensors or sampling measurements or modelling; 2) a coupled catchment-scale modelling system including 1D-hydrological/hydraulic models, 1D-emission and transport models as well as 3D-hydrodynamic and water quality models; 3) data assimilation techniques; and 4) an operational management system (OMS). Results from various case studies demonstrate that this integrative system can be used not only for long-term predictions of water quality levels and scenario tests, but also for event predictions and real-time forecasting of water quality. This approach produces synergistic effects in modelling capability for facilitating research and management applications.
International Journal of System of Systems Engineering, 2013
Managing CO2 emission control policy is a complex problem because of uncertainties in CO2 emissio... more Managing CO2 emission control policy is a complex problem because of uncertainties in CO2 emission process and CO2 uptake, and irreversibility in investment decisions. Traditional method using benefit cost analysis for evaluation of CO2 reduction policy is not effective in presence of deep uncertainties. Real options analysis approach is an alternative methodology which incorporates uncertainties and flexible timing in decision making. It allows the policymaker to learn and then act when the more information is available to resolve the uncertainties. This paper proposes a methodology with real options analysis for analysing the timing and conditions of adoption of CO2 reduction policies. CO2 emission is modelled as a stochastic process and CO2 observation data are used to statistically estimate the parameters of the stochastic CO2 emission model. A perpetual time model is developed to investigate CO2 emission cutback policy and CO2 concentration abatement policy and closed form analytical solutions are pr...
International Journal for Numerical Methods in Fluids, 2008
... An example of error correction in a non-measurement station is given in Figure 5 where the CM... more ... An example of error correction in a non-measurement station is given in Figure 5 where the CMBmodel output at grid point 2 was corrected using the proposed error correction scheme. For a forecast horizon of 12 h, the phase error was greatly removed and only small ...
Models of water resources systems are conceived to capture the underlying environmental dynamics ... more Models of water resources systems are conceived to capture the underlying environmental dynamics occurring within watersheds. All such models can be regarded as working hypotheses, differing in the aspects of process representation and conceptualization. Most of the associated efforts in the water resources research community is dedicated to development of new models that perform well under specific atmospheric conditions and catchment properties. In this context, flexible modeling frameworks are gaining importance as they facilitate the model building process by providing the model building blocks, whereby the hydrologist is free to assemble the model for task at hand. Such flexible models have high degree of transferability, which in turn aid in progressing toward a unified hydrological theory at catchment scale. However, in cases without sufficient insights regarding a catchment characteristics and/or lack of expert's knowledge, one may have to try a large number of model configurations based on available model building blocks to construct an appropriate model for the catchment of interest. Undoubtedly, this may be time consuming and computationally intensive. This paper proposes a novel model building algorithm, which uses the full potential of flexible modeling frameworks by searching the model space and inferring suitable model configurations relying on machine learning. Proposed machine learning algorithm is based on evolutionary computation approach using genetic programming (GP). State‐of‐art GP applications in rainfall‐runoff modeling so far used the algorithm as a short‐term forecasting tool that generates an expected future time series very similar to neural networks application. In this case, the proposed algorithm develops a physically meaningful rainfall‐runoff model. Although at the moment we learn models using two flexible modeling frameworks (SUPERFLEX and FUSE), the model induction toolkit can be armed with any internal coherence building blocks. The model induction capabilities of the proposed framework have been evaluated on the Blackwater River basin, Alabama, United States. The model configurations evolved through the model induction toolkit are consistent with the fieldwork investigations and previously reported research findings.
Changes in precipitation extremes in the tropical urban context is complex, where the precipitati... more Changes in precipitation extremes in the tropical urban context is complex, where the precipitation activities are influenced by the combined effects of El Niño–Southern Oscillation (ENSO), global warming and local effects. This study presents a comprehensive framework to investigate the variability and trends in precipitation extremes in a tropical urban city‐state, Singapore, based on a set of extreme indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI). The long‐term trends in the precipitation extremes over the period from 1980 until 2013 are examined using an iterative‐based Mann–Kendall trend test. Besides, the relative importance of precipitation frequency and intensity in inter‐annual variability of wet‐day precipitation totals is investigated. Finally, the correlations between precipitation extremes and three potential large‐scale and local factors, i.e. ENSO, global mean temperature and local temperature are analysed based on linear regression method. Results reveal that annual wet‐day precipitation totals, as well as average wet‐day precipitation intensity, have increased significantly, accompanied by a significant increase in the frequency and intensity of precipitation extremes in Singapore. The inter‐annual variability of wet‐day precipitation totals is mainly dominated by precipitation intensity. Significant correlations are found between precipitation extremes and all the three factors, and the signature of local effects is more evident than global warming. These findings have implications for adaption planning and disaster risk reduction in Singapore in the context of global warming.
Page 1. An Evolutionary Approach to Knowledge Induction: Genetic Programming in Hydraulic Enginee... more Page 1. An Evolutionary Approach to Knowledge Induction: Genetic Programming in Hydraulic Engineering Vladan Babovic*, Maarten Keijzer*, David Rodríguez Aguilera** and Joe Harrington *** * DHI Water & Environment ...
... A landmark in the chaos signal processing was made with the origin of embedding ... of chaoti... more ... A landmark in the chaos signal processing was made with the origin of embedding ... of chaotictime series because these share many fundamental ideas with the time-delay embedding ... was undertaken using the historical data set available at Horsburgh lighthouse and Hong ...
Governments face the daunting task of developing policies and making investment decisions for cli... more Governments face the daunting task of developing policies and making investment decisions for climate change adaptation in an environment that consist of complex, interlinked systems with manifold uncertainties. Instead of responding to surprises and making decisions on ad hoc basis, a structured approach to deal with complex systems and uncertainties can provide indispensable support for policy making. This contribution proposes a structured approach for designing climate adaptation policies based on the concepts of Adaptation Pathways, Adaptive Policy Making, and Real Options Analysis. Such an approach results in incorporation of flexibility that allows change over time in response to how the future unfolds, what is learned about the system, and changes in societal preferences. The approach is illustrated by looking at drainage policies and measures to address flooding in Singapore.
Inducing equations based on theory and data is a timehonoured technique in science. This is usual... more Inducing equations based on theory and data is a timehonoured technique in science. This is usually done manually, based on theoretical understanding and previously established equations. In this work, for a particular problem in hydraulics, human induction of equations is compared with the use of genetic programming. It will be shown that even with the use of synthetic data for training, genetic programming was capable of identifying a relationship that was more concise and more accurate than the relationship uncovered by scientists. As such this is a human-competitive result. Furthermore it will be shown that the genetic programming induced expression could be embedded in a line of theoretical work, filling in a few gaps in an already established line of reasoning. The resulting equation is the most accurate and elegant formulation of vegetation induced resistance to date.
The computer-controlled operating environments of such facilities as automated factories, nuclear... more The computer-controlled operating environments of such facilities as automated factories, nuclear power plants, telecommunication centres and space stations are continually becoming more complex.The situation is similar, if not even more apparent and urgent, in the case of water. Water is not only mankind's most valuable natural resource, but one which is in increasingly limited supply. The fresh water is the vita! natural resource which supports all environmental activities, that is, natura! economy, and all human socio-economic activities, that is, the artificial economy. The pressure for a sustainable control and exploration of water and thus for the peaceful co-existence of human- and hydro-economies, is not only a human, socio-economic pressure, but it is the question of life and death! Hydroinformatics - the nascent technology concerned with the flow of information related to the flow of fluids and all that they convey - is probably the best possible answer yet proposed to...
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