Improvement of simulating BMPs and LID practices in L-THIA-LID model

Best management practices (BMPs) and low impact development (LID) practices are popular approaches used to reduce the negative impacts of urbanization on hydrology and water quality. To assist planners and decision-makers in urban development projects, user-friendly tools are needed to assess the effectiveness of BMPs and LID practices on water quantity and quality. To address this need, the Long-Term Hydrologic Impact Assessment-LID (L-THIA-LID) model was enhanced with additional commonly used BMPs and LID practices represented in the model, improved approaches to estimate hydrology and water quality, and representation of practices in series. The tool was used to evaluate the performance of BMPs and LID practices individually and in series in four types of idealized land use units and watersheds (low density residential area, high density residential area, industrial area, and commercial area). Simulation results were comparable with the observed impacts of these practices in other published studies. Then, the model was enhanced further by creating L-THIA-LID 2.1 for modelling BMPs/LID practices at watershed scales and adding cost estimates of practices. The sensitivity and uncertainty of the enhanced model were analyzed using SobolOefs global sensitivity analysis method and the bootstrap method, respectively. CN (Curve Number) and Ratio_r (Practice outflow runoff volume/inflow runoff volume) were the most sensitive variables before and after BMPs/LID practices were implemented, respectively. The limited observed data in the same study area and results from other urban watersheds in scientific literature were either well within or close to the uncertainty ranges found in this study, indicating the model has good precision. Sixteen implementation scenarios of BMPs and LID practices were evaluated with the model at the watershed scale. The implementation of grass strips in 25% of the watershed where this practice could be applied was the most cost-efficient scenario. The scenario with very high levels of BMP and LID practice adoption provided the greatest reduction in runoff volume and pollutant loads among all scenarios. However, this scenario was not as cost-efficient as most other scenarios. The L-THIA-LID 2.1 model is a valid tool that can be applied to various locations to help identify cost effective BMP/LID practice plans at watershed scales. Finally, a decision support tool, which linked L-THIA-LID 2.1 with the A Multi-ALgorithm Genetically Adaptive Multiobjective (AMALGAM) method using the multilevel spatial optimization (MLSOPT) framework, was developed to optimally select and place BMPs/LID practices. The decision support tool was applied to an urban watershed near Indianapolis, Indiana. Optimization results at the hydrologic response unit scale indicated that for sites with different features, the optimal BMP/LID practice solutions to attain the same environmental goals differed. For sites with the same characteristics, the optimal implementation of practices could vary significantly for different environmental goals. For higher expenditures, the implementation levels and types of favored practices tended to increase relative to those for lower expenditures. Watershed scale results showed that for initial expenditures of practices, the environmental benefits increased rapidly as expenditures increased. However, beyond certain expenditure levels, additional spending did not result in noticeable additional environmental impacts. Compared to random placement of practices, the optimization strategy provided 3.9 to 7.7 times the level of runoff/pollutant load reductions for the same expenditures. To obtain the same environmental benefits, costs of random practices placement were 4.2 to 14.5 times the optimized practice placement cost. Results indicate that the decision support tool is capable of supporting decision makers in optimally selecting and placing BMPs and LID practices at watershed scales

Decision-Support System for LID Footprint Planning and Urban Runoff Mitigation in the Lower Rio Grande Valley of South Texas

To address regional flooding in the United States, federal and state agencies are adopting strict drainage policies in any large-scale commercial development within the watershed boundary. The conventional approach of implementing a wet detention pond (WP) reduces the land cover and causes operation and maintenance challenges eventually. The present study developed a decision-support system (DSS) in the Lower Rio Grande Valley region of South Texas for optimal selection of Best Management Practices (BMPs) by substituting a portion of the WP footprint with three regionally promising low-impact development practices, namely, porous concrete pavement (PCP), bioretention (BR), and bioswale (BS). Source Load Assessment and Management Model for Windows (WinSLAMM) was used as the foundation for the DSS database and algorithm development. This tool suggested that the implementation of bioswale alone can considerably reduce the footprint and construction cost. Less than 0.95 ha of installation of BR and BS can mitigate 79–91% of runoff from a maximum of 5 ha of commercial development. A combination of BR, BS, and WP was found to reduce runoff significantly (~100%), which suggests that the successful adoption of DSS might support better planning of the urban stormwater management in the Lower Rio Grande Valley (LRGV)

Performance assessment of coupled green-grey-blue systems for Sponge City construction

This is the final version. Available from Elsevier via the DOI in this record. In recent years, Sponge City has gained significant interests as a way of urban water management. The kernel of Sponge City is to develop a coupled green-grey-blue system which consists of green infrastructure at the source, grey infrastructure (i.e. drainage system) at the midway and receiving water bodies as the blue part at the terminal. However, the current approaches for assessing the performance of Sponge City construction are confined to green-grey systems and do not adequately reflect the effectiveness in runoff reduction and the impacts on receiving water bodies. This paper proposes an integrated assessment framework of coupled green-grey-blue systems on compliance of water quantity and quality control targets in Sponge City construction. Rainfall runoff and river system models are coupled to provide quantitative simulation evaluations of a number of indicators of land-based and river quality. A multi-criteria decision-making method, i.e., Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is adopted to rank design alternatives and identify the optimal alternative for Sponge City construction. The effectiveness of this framework is demonstrated in a typical plain river network area of Suzhou, China. The results demonstrate that the performance of Sponge City strategies increases with large scale deployment under smaller rainfall events. In addition, though surface runoff has a dilution effect on the river water quality, the control of surface pollutants can play a significant role in the river water quality improvement. This framework can be applied to Sponge City projects to achieve the enhancement of urban water management.Royal Academy of Engineering (RAE)National Natural Science Foundation of ChinaBeijing Nature Science FoundationMajor Science and Technology Program for Water Pollution Control and Treatmen

Optimizing Low Impact Development Controls for Sustainable Urban Flood Risk Management

Increased urbanization and a changing climate are contributing to an increased urban flood risk. Low Impact Development (LID) is a green infrastructure approach to help mitigate this risk. Analysis of flooding potential and socioeconomic factors of an urban area are essential in determining how to best implement these controls. The objectives of the study was to identify the most prominent areas for LID implementation and develop a framework for identifying LID controls within a multiobjective optimization framework. Coupled risk assessment and socioeconomic analysis was used to determine the potential areas to implement LID controls to achieve continuous benefits. A risk assessment methodology was developed to delineate the greatest flooding risk areas in sewersheds. A socioeconomic analysis framework was then adapted to assess the areas that would be most likely to adopt and successfully maintain LID controls. A simulation-optimization framework was then developed by coupling Stormwater Management Model (SWMM 5) with the Borg Multiobjective Evolutionary Algorithm (MOEA). This methodology analyzed different LID implementation solutions with a cost function to determine the most cost effective LID solutions. The PCSWMM interface was used to create the model for a large urban sewershed in Windsor, Ontario, Canada. The model tested LID measures against eight different scenarios consisting of both historical climate data and future predicted climate change data with the objectives of reducing peak flows in the sewer system, reducing total runoff across the sewershed and minimizing the cost of LID implementation. The results provide stormwater management professionals and decision makers cost-benefit information for different LID implementation scenarios to help assess the feasibility of LID in this area and to make infrastructure investment decisions

Structural Best Management Practices (BMPs) and hydrological effects modelling using swat for urban watershed

Orientador: Prof. Dr. Cristovao V.S. FernandesDissertação (mestrado) - Universidade Federal do Paraná, Setor de Tecnologia, Programa de Pós-Graduação em Engenharia de Recursos Hídricos e Ambiental. Defesa : Curitiba, 15/03/2019Inclui referências: p. 128-141Resumo: As Best Management Practices (BMPs) têm sido usadas como solução para mitigação de condições de pós-desenvolvimento em bacias urbanas e rurais. Estes dispositivos regulam vazões e volumes, além de capturar poluentes do escoamento superficial usando vários mecanismos. Estes dispositivos têm sido estudados e seu uso disseminado em vários países. Concomitantemente, o melhoramento de modelos de transporte e destinação de constituintes para investigar os efeitos, algoritmos para otimizar a busca por locais ótimos de instalação e facilitação da avaliação de entradas e saídas trouxe à luz vários desafios no que tange a modelagem dos fenômenos, incluindo a seleção de escalas de dimensão e tempo adequadas à representação dos fenômenos. A revisão de literatura demonstra uma fronteira clara entre usar inputs massivos de dados e computação exaustiva em modelos para descrição detalhada dos processos ou a adoção de abordagens mais simplificadas que capturem áreas maiores a custos menores de levantamento de dados. Neste estudo o Soil and Water Assessment Tool (SWAT) é utilizado como solução harmônica para modelagem em bacias com usos do solo mistos. Para vencer os desafios acima citados, BMPs são tratadas como zonas de recarga, isto é, zonas com Números de Curva (CN) menores. A localização destes dispositivos no modelo é realizada utilizando critérios consolidados de viabilidade através de ferramentas já desenvolvidas. Quatro cenários de redução percentual são utilizados para avaliação das melhoras de fluxo nas escalas da Hydrological Response Unit (HRU), subbacia e curso do rio(reach): 10%, 30%, 50% e 70%. As mudanças foram avaliadas na escala diária e anual, usando aplicações desenvolvidas em Python para automatizar a parametrização do modelo e a entrada e saída de dados. O estudo foi bem-sucedido em conceber a geração de múltiplos cenários, assim como em produzir ferramentas que auxiliem a entrada e saída de dados. Os resultados demonstram que a criação de zonas de recarga é mais eficaz em regiões onde há mais capacidade de retenção do solo. Do contrário, a redução do escoamento superficial tende a chegar em um limite, a partir do qual não há mais roteamento do escoamento superficial. Em HRUs e subbacias onde as condições de solo são favoráveis, a dinâmica de roteamento superficial e subsuperficial é modificada, fazendo com que a recarga dos aquíferos aumente e as recessões sejam mais lentas. Em geral, não são visíveis efeitos na escala da subbacia e no curso principal do rio, uma vez que muito do escoamento superficial é roteado como escoamento lateral ou fluo de subsuperfície. Além disso, a superposição dos efeitos para o resto da bacia é muito pequena na escala diária. Palavras-chave: SWAT. Bacias Urbanas. Python. Best Management Practices Hidrologia.Abstract: Best Management Practice (BMP) devices have been employed as a solution for both agricultural and urban watershed post-development effect mitigation. These devices regulate flow and capture runoff pollutants using various mechanisms. Such devices have been studied and its use disseminated in several countries. Concurrently, the enhancement of pollutant fate and transport models to assess the effects, search for optimal locations and facilitate inputs has brought to light several challenges concerning the modelling of physical phenomena, especially the one related to selecting time and size scales for adequate representation. The literature revision demonstrates that a clear boundary between using massive data inputs and computation-exhaustive models for thorough process description or more simplified approaches that capture larger areas at a more affordable data cost has limited the comprehension and description of BMP hydrological processes at the subbasin and watershed scale. In this study, SWAT is used a harmonic solution for modelling mixed land-use watersheds. To overcome the challenges stated, BMPs are treated as recharge - lower Curve Number (CN) zones, in feasible scenarios generated using an pre-built-tool and consolidated feasibility topographic, hydrological and space-distribution features. Four scenarios were generated: 10, 30, 50 70% CN reductions were tested and evaluated at the daily HRU/subbasin and subbasin yearly average scales, using developed applications for automating the parameter change and Input/output operations. The study was successful in automating the BMP scenario generation and multiple scenario generation as well as output data analysis. Results show that the creation of recharge zones is more effective at regions where more soil storage is available. Otherwise, runoff reduction tends to reach a limit. In HRUs and subbasins where soil conditions are favorable, the entire soil water and groundwater flow dynamics is modified, causing aquifer recharge to increase on average and recessions to be slower. Generally, no effects can be noticed at the subbasin o reach scale, as much of the runoff is also routed either as lateral flow or groundwater flow. The superposition of such effects to the rest of the watershed results in small differences at the daily scale. Keywords: SWAT. Urban watersheds. Python. Best Management Practices. Hydrology

Simulating and optimizing stormwater best management practices in University of Louisville watershed.

Urbanization disrupts natural soil profiles and as watersheds are urbanized, their surfaces become impervious and this will result in reduction of infiltration. For this reason, many cities are facing problems with treating runoff water. Best management practices (BMPs) consist of built systems designed to reduce and control the quality of runoff water in urban areas and help to control the direction of it. This system guides water to a structural soil retention area beneath the pavement where it is then temporary stored. BMPs are based of rainwater withholding (such as infiltration basins) or infiltration into the soil (such as permeable pavement). In this project we are to create a stormwater management model for campus using a modeling software for the purpose of guiding future BMP types and locations by predicting different scenarios\u27 efficiency based on runoff water reduction

Impacts of Landscape Change on Water Resources

Changes in land use and land cover can have many drivers, including population growth, urbanization, agriculture, demand for food, evolution of socio-economic structure, policy regulations, and climate variability. The impacts of these changes on water resources range from changes in water availability (due to changes in losses of water to evapotranspiration and recharge) to degradation of water quality (increased erosion, salinity, chemical loadings, and pathogens). The impacts are manifested through complex hydro-bio-geo-climate characteristics, which underscore the need for integrated scientific approaches to understand the impacts of landscape change on water resources. Several techniques, such as field studies, long-term monitoring, remote sensing technologies, and advanced modeling studies, have contributed to better understanding the modes and mechanisms by which landscape changes impact water resources. Such research studies can help unlock the complex interconnected influences of landscape on water resources in terms of quantity and quality at multiple spatial and temporal scales. In this Special Issue, we published a set of eight peer-reviewed articles elaborating on some of the specific topics of landscape changes and associated impacts on water resources