In this chapter, you will see how the simplex method simplifies when it is applied to a class of optimization problems that are known as “network flow models.” You will also see that if a network flow model has “integer-valued data,” the simplex method finds an optimal solution that is integer-valued.

Flows in Networks

The design and implementation of effective environmental policies need to be informed by a holistic understanding of the system processes (biophysical, social and economic), their complex interactions, and how they respond to various changes. Models, integrating different system processes into a unified framework, are seen as useful tools to help analyse alternatives with stakeholders, assess their outcomes, and communicate results in a transparent way. This paper reviews five common approaches or model types that have the capacity to integrate knowledge by developing models that can accommodate multiple issues, values, scales and uncertainty considerations, as well as facilitate stakeholder engagement. The approaches considered are: systems dynamics, Bayesian networks, coupled component models, agent-based models and knowledge-based models (also referred to as expert systems). We start by discussing several considerations in model development, such as the purpose of model building, the availability of qualitative versus quantitative data for model specification, the level of spatio-temporal detail required, and treatment of uncertainty. These considerations and a review of applications are then used to develop a framework that aims to assist modellers and model users in the choice of an appropriate modelling approach for their integrated assessment applications and that enables more effective learning in interdisciplinary settings. We review five common integrated modelling approaches.Model choice considers purpose, data type, scale and uncertainty treatment.We present a guiding framework for selecting the most appropriate approach.

Selecting among five common modelling approaches for integrated environmental assessment and management

There is increasing interest in long-term plans that can adapt to changing situations under conditions of deep uncertainty. We argue that a sustainable plan should not only achieve economic, environmental, and social objectives, but should be robust and able to be adapted over time to (unforeseen) future conditions. Large numbers of papers dealing with robustness and adaptive plans have begun to appear, but the literature is fragmented. The papers appear in disparate journals, and deal with a wide variety of policy domains. This paper (1) describes and compares a family of related conceptual approaches to designing a sustainable plan, and (2) describes several computational tools supporting these approaches. The conceptual approaches all have their roots in an approach to longterm planning called Assumption-Based Planning. Guiding principles for the design of a sustainable adaptive plan are: explore a wide variety of relevant uncertainties, connect short-term targets to long-term goals over time, commit to short-term actions while keeping options open, and continuously monitor the world and take actions if necessary. A key computational tool across the conceptual approaches is a fast, simple (policy analysis) model that is used to make large numbers of runs, in order to explore the full range of uncertainties and to identify situations in which the plan would fail.

/pdf/adapt-or-perish-a-review-of-planning-approaches-for-1cwqqvaw6a.pdf

Adapt or Perish: A Review of Planning Approaches for Adaptation under Deep Uncertainty

. Interactions between humans and the environment are occurring on a scale that has never previously been seen; the scale of human interaction with the water cycle, along with the coupling present between social and hydrological systems, means that decisions that impact water also impact people. Models are often used to assist in decision-making regarding hydrological systems, and so in order for effective decisions to be made regarding water resource management, these interactions and feedbacks should be accounted for in models used to analyse systems in which water and humans interact. This paper reviews literature surrounding aspects of socio-hydrological modelling. It begins with background information regarding the current state of socio-hydrology as a discipline, before covering reasons for modelling and potential applications. Some important concepts that underlie socio-hydrological modelling efforts are then discussed, including ways of viewing socio-hydrological systems, space and time in modelling, complexity, data and model conceptualisation. Several modelling approaches are described, the stages in their development detailed and their applicability to socio-hydrological cases discussed. Gaps in research are then highlighted to guide directions for future research. The review of literature suggests that the nature of socio-hydrological study, being interdisciplinary, focusing on complex interactions between human and natural systems, and dealing with long horizons, is such that modelling will always present a challenge; it is, however, the task of the modeller to use the wide range of tools afforded to them to overcome these challenges as much as possible. The focus in socio-hydrology is on understanding the human–water system in a holistic sense, which differs from the problem solving focus of other water management fields, and as such models in socio-hydrology should be developed with a view to gaining new insight into these dynamics. There is an essential choice that socio-hydrological modellers face in deciding between representing individual system processes or viewing the system from a more abstracted level and modelling it as such; using these different approaches has implications for model development, applicability and the insight that they are capable of giving, and so the decision regarding how to model the system requires thorough consideration of, among other things, the nature of understanding that is sought.

/pdf/socio-hydrological-modelling-a-review-asking-why-what-and-7wf07k20fi.pdf

Socio-hydrological modelling: a review asking "why, what and how?"

Soil moisture forecasting by a hybrid machine learning technique: ELM integrated with ensemble empirical mode decomposition

Management of regulated water systems has become increasingly complex due to rapid socio-economic growth and environmental changes in river basins over recent decades. This paper introduces the Source Integrated Modelling System (IMS), and describes the individual modelling components and how they are integrated within it. It also describes the methods employed for tracking and assessment of uncertainties, as well as presenting outcomes of two case study applications. Traditionally, the mathematical tools for water resources planning and management were generally designed for sectoral applications with, for example, groundwater being modelled separately from surface water. With the increasing complexity of water resources management in the 21st century those tools are becoming outmoded. Water management organisations are increasingly looking for new generation tools that allow integration across domains to assist their decision making processes for short-term operations and long-term planning; not only to meet current needs, but those of the future as well. In response to the need for an integrated tool in the water industry in Australia, the eWater Cooperative Research Centre (CRC) has developed a new generation software package called the Source IMS. The Source IMS is an integrated modelling environment containing algorithms and approaches that allow defensible predictions of water flow and constituents from catchment sources to river outlets at the sea. It is designed and developed to provide a transparent, robust and repeatable approach to underpin a wide range of water planning and management purposes. It can be used to develop water sharing plans and underpin daily river operations, as well as be used for assessments on water quantity and quality due to changes in: i) land-use and climate; ii) demands (irrigation, urban, ecological); iii) infrastructure, such as weirs and reservoirs; iv) management rules that might be associated with these; and v) the impacts of all of the above on various ecological indices. The Source IMS integrates the existing knowledge and modelling capabilities used by different state and federal water agencies across Australia and has additional functionality required for the river system models that will underpin the next round of water sharing plans in the country. It is built in a flexible modelling environment to allow stakeholders to incorporate new scientific knowledge and modelling methods as they evolve, and is designed as a generic tool suitable for use across different jurisdictions. Due to its structure, the platform can be extended/customised for use in other countries and basins, particularly where there are boundary issues.

An integrated modelling framework for regulated river systems

Different water agencies use different modeling tools for water resources planning and management. For example, different jurisdictions in Australia use a variety of river system models and these models vary considerably in approach and assumptions, including different time steps (monthly and daily), flow routing (different types of routing and no routing), ordering solution (optimization and heuristic) and representation of management and operational rules. These fundamental differences in approach make it difficult to integrate existing models of connected river systems at a basin scale. A collaborative joint venture (the eWater CRC) between research, industry and government partners has recently developed an integrated river system modelling tool called “eWater Source” to improve on the existing river system models in Australia. One of the major advances in Source is the implementation of two decision algorithms, heuristic and NetLP approaches, for water distribution modelling in the same modelling platform. This paper describes the implementation of heuristic and NetLP approaches for water delivery under management and operations rules in Source, and compares the performance of the two approaches through a case study in the Goulburn-Broken-Campaspe-Loddon (GBCL) river system in south-eastern Australia. The key performance measures used to compare the approaches include the efficiency and equity of water delivery to water users, impacts on the reliability of supply, agreement with storage operating targets, and model application run time. The results demonstrate that the heuristic approach implemented in Source can replicate the performance of the NetLP approach for a model of reasonable complexity. This is important because the run times of models with heuristic approaches are shorter than models with NetLP approaches, so this will allow more complexity to be represented than was previously practical in equivalent NetLP applications. Agreement between jurisdictions to move to the single river system modelling platform will contribute to overcoming the problems faced by river managers in Australia in transboundary river basins.

Examining Two Different Approaches to Modelling Management and Operation Rules in a Single River System Model

The literature is rich in discussion of methods, platforms and standards that hope to ease the process of integrating models in workflows or decision support systems. The reality for practitioners is that integrating models is still complex and time consuming in most cases. In addition, the literature contains few descriptions of the practicalities of integrating models in the hydrology domain. This paper presents two case studies to explore opportunities for reducing the complexity associated with model integration. Even though the case studies were different, significant commonalities exist in the linkage requirements for both case studies. The paper finds that meeting these requirements required significant change to the existing model architecture. The first case study involves linking the hydrological modeling system, Source IMS, with the Delft Flood Early Warning System (FEWS). The FEWS system is being trialed in the Australian Water Resources Assessment system (AWRA) that the Water Information Research and Development Alliance (WIRADA) is developing to support water assessment and water accounts products for the Bureau of Meteorology. The second case study involves linking the Source IMS with Parameter ESTimation (PEST) software for automated calibration of model parameters. These two case studies identified four key requirements that are considered common to how workflow tools would need to integrate with Source IMS. Specifically, 1. Run and retrieve results without a user's interaction. 2. Model independence - both FEWS and PEST remain independent of the model. 3. Manipulate parameters and boundary conditions; there was no need to modify the structure or configuration of the model. 4. Manage project load times and overall simulation times. The architecture of Source IMS changed significantly to support mechanisms for simulation stepping, distributed execution, stay-alive functionality and parameter passing. Adopting The Open Modelling Interface (OpenMI) would have addressed these requirements. However, the start up costs of implementing the OpenMI made this solution unachievable in the short term with the available resourcing. This paper discusses a pragmatic solution that addressed the key integration requirements while reducing the cost of moving to OpenMI in the future. The pragmatic solution involved changes such as:  Refactoring persistence functions (load and save), data model parameterisation and simulation methods so they were brokered through the application layer interfaces;  Decorating the application layer interfaces with Windows Communication Foundation (WCF) to enable inter-program, cross-process and cross-computer communication; and  Developing a command-line client and server application for providing application layer services to external programs. Practitioners and software developers solving model integration problems desire to leverage standards such as OpenMI. This paper contributes to our understanding of the precursor steps required to implement some of these standards. The precursor to integrating hydrological models in Source IMS was a reengineering of the software architecture. The reengineered architecture supported requirements of both case studies due to commonalities of PEST and FEWS. This paper encourages practitioners to consider major architectural decisions that might simplify or complicate the integration with other products.

Linking hydrological simulation models with workflow and optimisation software

eWater has developed and adopted a three pronged quality assurance approach for developing and applying water management models. The key elements of this approach are: (a) a structured process for model development, including user requirements, software testing, trial applications and supporting documentation; (b) provision of a peer reviewed family of guidelines outlining a best practice approach to model application, including generic guidelines representing the highest level in the hierarchy that provide the framework for a consistent set of more detailed, plus supporting guidelines for certain domains relevant to eWater Source; and (c) training and support, including online modules and a community of practice. This paper provides an overview of the main features, development and implementation of eWater's quality assurance approach.

eWater's quality assurance approach for developing and applying water management models

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Papers

An integrated modelling framework for regulated river systems

Examining Two Different Approaches to Modelling Management and Operation Rules in a Single River System Model

Linking hydrological simulation models with workflow and optimisation software

eWater's quality assurance approach for developing and applying water management models