A Disaggregation‐Emulation Approach for Optimization of Large Urban Drainage Systems

none3Multi-objective optimization can help identify efficient and appealing designs of urban drainage systems. However, their application to large-scale problems is hindered by the computational cost of urban drainage simulation. We propose a novel disaggregation approach that allows simulating a portion of a drainage network while the remaining part is represented by a surrogate model that maps changes in the region of interest to hydraulic head time-series at synthetic nodes shared with the remaining part of the network. The proposed approach is demonstrated with an application to the many-objective optimization of sustainable urban drainage systems in two urban areas. The design problem's decision variables include the types of sustainable drainage systems, their combination within a subcatchment, their surface areas and spatial distribution, whereas the objectives include the minimization of capital cost, flood volume, flood duration, and total suspended solids or average peak runoff. The results show that the proposed disaggregation-emulation approach can provide an accurate representation of the system dynamics while significantly reducing the computational time compared to a model that simulates the whole network dynamics. Two alternative surrogate models are considered based on multilayer perceptron (MLP) and generalized regression neural networks (GRNN). MLP is found to be more accurate compared to GRNN at the cost of a larger computational time for the training process.noneSeyedashraf O.; Bottacin-Busolin Andrea; Harou J.J.Seyedashraf, O.; Bottacin-Busolin, Andrea; Harou, J. J

Tracking trade transactions in water resource systems: A node- arc optimization formulation

[1] We formulate and apply a multicommodity network flow node-arc optimization model capable of tracking trade transactions in complex water resource systems. The model uses a simple node to node network connectivity matrix and does not require preprocessing of all possible flow paths in the network. We compare the proposed node-arc formulation with an existing arc-path (flow path) formulation and explain the advantages and difficulties of both approaches. We verify the proposed formulation model on a hypothetical water distribution network. Results indicate the arc-path model solves the problem with fewer constraints, but the proposed formulation allows using a simple network connectivity matrix which simplifies modeling large or complex networks. The proposed algorithm allows converting existing node-arc hydroeconomic models that broadly represent water trading to ones that also track individual supplier-receiver relationships (trade transactions)

Many-Objective Optimization of Sustainable Drainage Systems in Urban Areas with Different Surface Slopes

From Springer Nature via Jisc Publications RouterHistory: received 2020-10-21, accepted 2021-04-12, registration 2021-04-13, pub-print 2021-06, pub-electronic 2021-06-09, online 2021-06-09Publication status: PublishedAbstract: Sustainable urban drainage systems are multi-functional nature-based solutions that can facilitate flood management in urban catchments while improving stormwater runoff quality. Traditionally, the evaluation of the performance of sustainable drainage infrastructure has been limited to a narrow set of design objectives to simplify their implementation and decision-making process. In this study, the spatial design of sustainable urban drainage systems is optimized considering five objective functions, including minimization of flood volume, flood duration, average peak runoff, total suspended solids, and capital cost. This allows selecting an ensemble of admissible portfolios that best trade-off capital costs and the other important urban drainage services. The impact of the average surface slope of the urban catchment on the optimal design solutions is discussed in terms of spatial distribution of sustainable drainage types. Results show that different subcatchment slopes result in non-uniform distributional designs of sustainable urban drainage systems, with higher capital costs and larger surface areas of green assets associated with steeper slopes. This has two implications. First, urban areas with different surface slopes should not have a one-size-fits-all design policy. Second, spatial equality must be taken into account when applying optimization models to urban subcatchments with different surface slopes to avoid unequal distribution of environmental and human health co-benefits associated with green drainage infrastructure

An Open-Source Data Manager for Network Models

Developing simulation and optimisation models for resource networks like water or energy systems increasingly involves integrating multiple data sources and software. Connecting multiple models and managing data accessed by different groups of analysts is a software challenge. Many resource systems are represented in computer models as networks of nodes and links, driven by a range of objectives and rules. We present a data storage platform, written in Python, which exploits the commonality of network representations to store data for multiple model types within a single deployment. This open-source platform provides a common source of data to multiple models using consistent data formats, reducing likelihood of error compared to file based data management. When deployed as a web service, it allows data to be shared securely among authorised users over the internet, facilitating collaboration. A case study describes the hosting of a water utility planning model, with an accompanying worked example

Balancing renewable energy and river resources by moving from individual assessments of hydropower projects to energy system planning

As governments and non-state actors strive to minimize global warming, a primary strategy is the decarbonization of power systems which will require a massive increase in renewable electricity generation. Leading energy agencies forecast a doubling of global hydropower capacity as part of that necessary expansion of renewables. While hydropower provides generally low-carbon generation and can integrate variable renewables, such as wind and solar, into electrical grids, hydropower dams are one of the primary reasons that only one-third of the world’s major rivers remain free-flowing. This loss of free-flowing rivers has contributed to dramatic declines of migratory fish and sediment delivery to agriculturally productive deltas. Further, the reservoirs behind dams have displaced tens of millions of people. Thus, hydropower challenges the world’s efforts to meet climate targets while simultaneously achieving other Sustainable Development Goals. In this paper, we explore strategies to achieve the needed renewable energy expansion while sustaining the diverse social and environmental benefits of rivers. These strategies can be implemented at scales ranging from the individual project (environmental flows, fish passage and other site-level mitigation) to hydropower cascades to river basins and regional electrical power systems. While we review evidence that project-level management and mitigation can reduce environmental and social costs, we posit that the most effective scale for finding balanced solutions occurs at the scale of power systems. We further hypothesize that the pursuit of solutions at the system scale can also provide benefits for investors, developers and governments; evidence of benefits to these actors will be necessary for achieving broad uptake of the approaches described in this paper. We test this hypothesis through cases from Chile and Uganda that demonstrate the potential for system-scale power planning to allow countries to meet low-carbon energy targets with power systems that avoid damming high priority rivers (e.g., those that would cause conflicts with other social and environmental benefits) for a similar system cost as status quo approaches. We also show that, through reduction of risk and potential conflict, strategic planning of hydropower site selection can improve financial performance for investors and developers, with a case study from Colombia

Collaborative management of the Grand Ethiopian Renaissance Dam increases economic benefits and resilience

From Springer Nature via Jisc Publications RouterHistory: received 2020-07-29, accepted 2021-08-13, registration 2021-09-07, pub-electronic 2021-09-23, online 2021-09-23, collection 2021-12Publication status: PublishedFunder: UK Research and Innovation: ES/P011373/1Abstract: The landscape of water infrastructure in the Nile Basin is changing with the construction of the Grand Ethiopian Renaissance Dam. Although this dam could improve electricity supply in Ethiopia and its neighbors, there is a lack of consensus between Ethiopia, Sudan, and Egypt on the dam operation. We introduce a new modeling framework that simulates the Nile River System and Egypt’s macroeconomy, with dynamic feedbacks between the river system and the macroeconomy. Because the two systems “coevolve” throughout multi-year simulations, we term this a “coevolutionary” modeling framework. The framework is used to demonstrate that a coordinated operating strategy could allow the Grand Ethiopian Renaissance Dam to help meet water demands in Egypt during periods of water scarcity and increase hydropower generation and storage in Ethiopia during high flows. Here we show the hydrological and macroeconomic performance of this coordinated strategy compared to a strategy that resembles a recent draft proposal for the operation of the dam discussed in Washington DC

Sensitivity of projected climate impacts to climate model weighting: multi-sector analysis in eastern Africa

Uncertainty in long-term projections of future climate can be substantial and presents a major challenge to climate change adaptation planning. This is especially so for projections of future precipitation in most tropical regions, at the spatial scale of many adaptation decisions in water-related sectors. Attempts have been made to constrain the uncertainty in climate projections, based on the recognised premise that not all of the climate models openly available perform equally well. However, there is no agreed ‘good practice’ on how to weight climate models. Nor is it clear to what extent model weighting can constrain uncertainty in decision-relevant climate quantities. We address this challenge, for climate projection information relevant to ‘high stakes’ investment decisions across the ‘water-energy-food’ sectors, using two case-study river basins in Tanzania and Malawi. We compare future climate risk profiles of simple decision-relevant indicators for water-related sectors, derived using hydrological and water resources models, which are driven by an ensemble of future climate model projections. In generating these ensembles, we implement a range of climate model weighting approaches, based on context-relevant climate model performance metrics and assessment. Our case-specific results show the various model weighting approaches have limited systematic effect on the spread of risk profiles. Sensitivity to climate model weighting is lower than overall uncertainty and is considerably less than the uncertainty resulting from bias correction methodologies. However, some of the more subtle effects on sectoral risk profiles from the more ‘aggressive’ model weighting approaches could be important to investment decisions depending on the decision context. For application, model weighting is justified in principle, but a credible approach should be very carefully designed and rooted in robust understanding of relevant physical processes to formulate appropriate metrics

Climate variability affects water-energy-food infrastructure performance in East Africa

The need to assess major infrastructure performance under a changing climate is widely recognized yet rarely practiced, particularly in rapidly growing African economies. Here, we consider high-stakes investments across the water, energy, and food sectors for two major river basins in a climate transition zone in Africa. We integrate detailed interpretation of observed and modeled climate-system behavior with hydrological modeling and decision-relevant performance metrics. For the Rufiji River in Tanzania, projected risks for the mid-21st century are similar to those of the present day, but for the Lake Malawi-Shire River, future risk exceeds that experienced during the 20th century. In both basins a repeat of an early-20th century multi-year drought would challenge the viability of proposed infrastructure. A long view, which emphasizes past and future changes in variability, set within a broader context of climate-information interpretation and decision making, is crucial for screening the risk to infrastructure