Modelling Waikato Farm Nitrogen Discharges for Policy Analysis

This study describes the development of bio economic models examining the economic and water quality impact of various proposed policy options in the Upper Waikato catchment. In the first phase nitrogen emissions are determined for representative farming systems using the Overseer nutrient budget model. These model components are integrated into an economic model, which predicts producer responses to various policy options. The second phase determines catchment wide costs and water quality impacts of riparian buffers by combining geographic information system, bio economic modelling and experimental data. The results of the study signals directions for policy initiatives and further analysis exploring policy design and all costs associated with production adjustment.Riparian margins, Non point pollution, Nitrogen, Linear programming, and Environmental policy, Community/Rural/Urban Development, Crop Production/Industries, Environmental Economics and Policy, Farm Management, Health Economics and Policy, Industrial Organization, Land Economics/Use, Livestock Production/Industries, Research Methods/ Statistical Methods, Resource /Energy Economics and Policy,

Water Quality Management of the Nitra River Basin (Slovakia): Evaluation of Various Control Strategies

The Nitra is one of the most polluted rivers in Slovakia due to numerous municipal and industrial discharges, and the low level of waste water treatment. The ongoing economic transition and lack of financial resources for environmental management calls for the development of short-run least-cost policies on the basis of ambient standards (or a combination of ambient and effluent ones). A water quality control policy model was developed which incorporates dissolved oxygen simulation models, municipal wastewater treatment alternatives, an optimization model based on dynamic programming, a data base, and a graphical user interface. Least-cost policies to achieve various water quality goals were developed and compared to effluent standard based strategies (including that deriving from the application of the "best available technology"). The role of industrial emissions was demonstrated in a sensitivity fashion, while the influence of parameter uncertainty on the developed policies was analyzed in a multiobjective framework. The study shows that significant cost savings are possible in comparison to uniform, effluent standard policies. They also suggest that a long-term strategy should be realized on the basis of a sequence of properly phased least-cost policies corresponding to ambient standards to be tightened gradually

Sensitivity analysis and parameter estimation for distributed hydrological modeling: potential of variational methods

Variational methods are widely used for the analysis and control of computationally intensive spatially distributed systems. In particular, the adjoint state method enables a very efficient calculation of the derivatives of an objective function (response function to be analysed or cost function to be optimised) with respect to model inputs. In this contribution, it is shown that the potential of variational methods for distributed catchment scale hydrology should be considered. A distributed flash flood model, coupling kinematic wave overland flow and Green Ampt infiltration, is applied to a small catchment of the Thoré basin and used as a relatively simple (synthetic observations) but didactic application case. It is shown that forward and adjoint sensitivity analysis provide a local but extensive insight on the relation between the assigned model parameters and the simulated hydrological response. Spatially distributed parameter sensitivities can be obtained for a very modest calculation effort (~6 times the computing time of a single model run) and the singular value decomposition (SVD) of the Jacobian matrix provides an interesting perspective for the analysis of the rainfall-runoff relation. For the estimation of model parameters, adjoint-based derivatives were found exceedingly efficient in driving a bound-constrained quasi-Newton algorithm. The reference parameter set is retrieved independently from the optimization initial condition when the very common dimension reduction strategy (i.e. scalar multipliers) is adopted. Furthermore, the sensitivity analysis results suggest that most of the variability in this high-dimensional parameter space can be captured with a few orthogonal directions. A parametrization based on the SVD leading singular vectors was found very promising but should be combined with another regularization strategy in order to prevent overfitting

Decentralized fault-tolerant control of inland navigation networks: a challenge

Inland waterways are large-scale networks used principally for navigation. Even if the transport planning is an important issue, the water resource management is a crucial point. Indeed, navigation is not possible when there is too little or too much water inside the waterways. Hence, the water resource management of waterways has to be particularly efficient in a context of climate change and increase of water demand. This management has to be done by considering different time and space scales and still requires the development of new methodologies and tools in the topics of the Control and Informatics communities. This work addresses the problem of waterways management in terms of modeling, control, diagnosis and fault-tolerant control by focusing in the inland waterways of the north of France. A review of proposed tools and the ongoing research topics are provided in this paper.Peer ReviewedPostprint (published version

Addressing Uncertainty in TMDLS: Short Course at Arkansas Water Resources Center 2001 Annual Conference

Management of a critical natural resource like water requires information on the status of that resource. The US Environmental Protection Agency (EPA) reported in the 1998 National Water Quality Inventory that more than 291,000 miles of assessed rivers and streams and 5 million acres of lakes do not meet State water quality standards. This inventory represents a compilation of State assessments of 840,000 miles of rivers and 17.4 million acres of lakes; a 22 percent increase in river miles and 4 percent increase in lake acres over their 1996 reports. Siltation, bacteria, nutrients and metals were the leading pollutants of impaired waters, according to EPA. The sources of these pollutants were presumed to be runoff from agricultural lands and urban areas. EPA suggests that the majority of Americans-over 218 million-live within ten miles of a polluted waterbody. This seems to contradict the recent proclamations of the success of the Clean Water Act, the Nation\u27s water pollution control law. EPA also claims that, while water quality is still threatened in the US, the amount of water safe for fishing and swimming has doubled since 1972, and that the number of people served by sewage treatment plants has more than doubled

Frequency analysis of river water quality using integrated urban wastewater models

Copyright © IWA Publishing 2012.The definitive peer-reviewed and edited version of this article is published in Water Science and Technology Volume 65 Issue 12, pp. 2112–2117 (2012), DOI: 10.2166/wst.2012.127 and is available at www.iwapublishing.com.In recent years integrated models have been developed to simulate the entire urban wastewater system, including urban drainage systems, wastewater treatment plants, and receiving waterbodies. This paper uses such an integrated urban wastewater model to analyze the frequency of receiving water quality in an urban wastewater system with the aim of assessing the overall system performance during rainfall events. The receiving water quality is represented by two indicators: event mean dissolved oxygen (DO) concentration and event mean ammonium concentration. The compliance probability of the water quality indicators satisfying a specific threshold is used to represent the system performance, and is derived using the rainfall events from a series of 10 years' rainfall data. A strong correlation between the depth of each rainfall event and the associated volume of combined sewer overflow (CSO) discharges is revealed for the case study catchment, while there is a low correlation between the intensity/duration of the rainfall event and the volume of the CSO discharges. The frequency analysis results obtained suggest that the event mean DO and ammonium concentrations have very different characteristics in terms of compliance probabilities at two discharging points for CSO and wastewater treatment plant effluent, respectively. In general, the simulation results provide an understanding of the performance of the integrated urban wastewater system and can provide useful information to support water quality management

Use of surrogate modelling for multiobjective optimisation of urban wastewater systems

Copyright © IWA Publishing 2009. The definitive peer-reviewed and edited version of this article is published in Water Science and Technology Volume 60 Issue 6, pp. 1641–1647 (2009), DOI: 10.2166/wst.2009.508 and is available at www.iwapublishing.comSimulation models are now available to represent the sewer network, wastewater treatment plant and receiving water as an integrated system. These models can be combined with optimisation methods to improve overall system performance through optimal control. Evolutionary algorithms (EAs) have been proven to be a powerful method in developing optimal control strategies; however, the intensive computational requirement of these methods imposes a limit on their application. This paper explores the potential of surrogate modelling in multiobjective optimisation of urban wastewater systems with a limited number of model simulations. A surrogate based method, ParEGO, is combined with an integrated urban wastewater model to solve real time control problems. This method is compared with the popular NSGA II, by using performance indicators: the hypervolume indicator, additive binary epsilon-indicator and attainment surface. Comparative results show that ParEGO is an efficient and effective method in deriving optimal control strategies for multiple objective control problems with a small number of simulations. It is suggested that ParEGO can greatly improve computational efficiency in the multiobjective optimisation process, particularly for complex urban wastewater systems

Modeling and real-time control of urban drainage systems: A review

Urban drainage systems (UDS) may be considered large-scale systems given their large number of associated states and decision actions, making challenging their real-time control (RTC) design. Moreover, the complexity of the dynamics of the UDS makes necessary the development of strategies for the control design. This paper reviews and discusses several techniques and strategies commonly used for the control of UDS. Moreover, the models to describe, simulate, and control the transport of wastewater in UDS are also reviewed.This work has been partially supported by Mexichem, Colombia through the project “Drenaje Urbano y Cambio Climático: Hacia los Sistemas de Alcantarillado del Futuro.” Fase II, with reference No. 548-2012, the scholarships of Colciencias No. 567-2012 and 647-2013, and the project ECOCIS (Ref. DPI2013-48243-C2-1-R).Peer Reviewe

Municipal wastewater treatment with pond technology : historical review and future outlook

Facing an unprecedented population growth, it is difficult to overstress the assets for wastewater treatment of waste stabilization ponds (WSPs), i.e. high removal efficiency, simplicity, and low cost, which have been recognized by numerous scientists and operators. However, stricter discharge standards, changes in wastewater compounds, high emissions of greenhouse gases, and elevated land prices have led to their replacements in many places. This review aims at delivering a comprehensive overview of the historical development and current state of WSPs, and providing further insights to deal with their limitations in the future. The 21st century is witnessing changes in the way of approaching conventional problems in pond technology, in which WSPs should no longer be considered as a low treatment technology. Advanced models and technologies have been integrated for better design, control, and management. The roles of algae, which have been crucial as solar-powered aeration, will continue being a key solution. Yet, the separation of suspended algae to avoid deterioration of the effluent remains a major challenge in WSPs while in the case of high algal rate pond, further research is needed to maximize algal growth yield, select proper strains, and optimize harvesting methods to put algal biomass production in practice. Significant gaps need to be filled in understanding mechanisms of greenhouse gas emission, climate change mitigation, pond ecosystem services, and the fate and toxicity of emerging contaminants. From these insights, adaptation strategies are developed to deal with new opportunities and future challenges

River Basin Water Quality Management Models: A State-of-the-Art Review

With the increasing human activities within river basins, the problem of water quality management is becoming increasingly important. Quality management can be achieved through control/prevention measures that have various economic and water quality implications. To facilitate the analysis of available management options, decision models are needed which represent the many facets of the problem. Such models must be capable of adequately depicting the hydrological, chemical and biological processes occurring in the river; while incorporating social, economic and political considerations within the decision framework. Management analyses can be performed using simulation, optimization, or both, depending on the management goal and the size and type of the problem. The critical issues in a management model are the nonlinearities, uncertainties, multiple pollutant nature of waste discharges, multiple objectives, and the spatial and temporal distribution of management actions. Literature on various management models were reviewed under the headings of linear, nonlinear and dynamic programming approaches; their stochastic counterparts, and combined or miscellaneous approaches. Dynamic programming was found to be an attractive methodology which can exploit the sequential decision problem pertaining to river basin water quality problems (downstream control actions do not influence water quality upstream). DP handles discrete decision variables which represent discrete management alternatives, and it is generic in the sense that both linear and non-linear water quality models expressing the relation between emissions and ambient quality levels can be incorporated. An example problem is presented which demonstrates the application of a DP-based management model to formulate least-cost strategies for the Nitra River basin in Slovakia. However, it is hardly possible for a single model to represent all the aspects of a complex decision problem. Different types of management models (e.g. deterministic vs stochastic models) have different capabilities and limitations. The only way to compensate for the deficiencies is to perform the analysis in a sensitivity style. The necessity for sensitivity analyses is further implied due to the fact that water quality problems are rather loosely formulated with respect to the quality and economic goals