A GIS based screening tool for locating and ranking of suitable stormwater harvesting sites in urban areas

Spatial allocation of bioretention cells considering interaction with shallow groundwater: A simulation-optimization approach

Green infrastructure (GI), as one type of ecological stormwater management practices, can potentially alleviate water problems and deliver a wide range of environmental benefits in urban areas. GIs are often planned and designed to reduce runoff and mitigate pollution. However, the influence of GI on groundwater hydrology and that of shallow groundwater on GI performance was seldom considered. This study utilized a calibrated surface-subsurface hydrological model, i.e., Storm Water Management Model coupled with USGS's modular hydrologic model (SWMM-MODFLOW) to consider the interaction between GI and groundwater into the process of GI planning. The optimal implementation ratio, aggregation level and upstream-downstream location of bioretention cells (BC, one type of GI) under different planning objectives and hydrogeologic conditions was explored. The consideration of groundwater management exerted a significant impact on the optimal spatial allocation of BCs. The results showed that when groundwater management was more concerned than runoff control, BCs were recommended to be allocated more apart from each other and more upstream in the catchment because more-distributed and upstream BCs can result in lower groundwater table rise which is beneficial. BCs were overall recommended to be allocated in areas of deeper groundwater tables, coarser soils, and flatter topographies. However, the spatial features of BCs are related to each other, the choice of them are affected by various hydrogeologic factors simultaneously. The exact location of BCs should be determined by considering the trade-off between runoff control efficiency and groundwater impact. The findings obtained in this study can provide guidance on GI planning in shallow groundwater areas.

A spatial planning-support system for generating decentralised urban stormwater management schemes

Current Water Sensitive Urban Design (WSUD) models are either purely technical or overly simplified, lacking consideration of urban planning and stakeholder preferences to adequately support stakeholders. We developed the Urban Biophysical Environments and Technologies Simulator (UrbanBEATS), which integrates stormwater management with urban planning to support the design and implementation of WSUD. This study specifically describes and tests UrbanBEATS' WSUD Planning Module, which combines spatial analysis, infrastructure design, preference elicitation and Monte Carlo methods to generate feasible stormwater management and harvesting infrastructure options in greenfield and existing urban environments. By applying UrbanBEATS to a real-world greenfield development case study in Melbourne, Australia (with data sourced from the project's water management plans and design consultants), we explore the variety of options generated by the model and analyse them collectively to demonstrate that UrbanBEATS can design similar WSUD systems (e.g. select suitable technology types, their sizes and locations) to actual infrastructure choices.

Evaluating hotspots for stormwater harvesting through participatory sensing

Geographic Information Systems have been widely accepted to manage and manipulate spatial data associated with the hydrologic response of a watershed. Due to climate change and drought impacts, there is a need to conserve freshwater resources, which can be accomplished by introducing the concept of stormwater harvesting. Apart from hotspot identification and site screening, several economic, social, cultural, environmental aspects need to be considered before finalizing the suitable site for stormwater harvesting. The shortlisted sites are commonly ranked by considering various parameters, i.e. water demand, availability of stormwater and distance to end-use locations, which relate to economic aspects. In the present study, socio-environmental considerations are also constituted by adopting a web-GIS based approach. The geospatial datasets and metadata associated with the study area are organized as a repository in the open source database server (PostgreSQL/PostGIS), which is further assessed and analyzed by using GeoServer. This technique publishes the geospatial datasets to the public domain websites that can be accessed and visualized around the clock and across the world. This will help stakeholders gather and store responses from water planners and inhabitants, while minimizing the time and cost associated with field visits for collecting individual responses. In this respect, a questionnaire is prepared that includes queries associated with site selection and the responses are gathered from various institutions, water professionals, stakeholders and residents. Once the responses are collected, the Analytic Hierarchy Process has been implemented to compute the relative weights of each criterion with respect to the responses collected. The weights thus obtained assisted the planners in deciding the suitable stormwater harvesting site for Dehradun city in India. In context to responses gathered the sites 'B' and 'D' are given the maximum weightage to be the suitable sites in the study region. Also, the socio-environmental criteria such as 'community acceptance', 'recreational activities' and 'need for water reuse' have gathered the maximum weightage from the responses for the specific sites. Hence, the proposed methodology demonstrated how water professionals, civilians, planners, stakeholders and public can be included as participants in water-related decision making processes.

A comprehensive review of spatial allocation of LID-BMP-GI practices: Strategies and optimization tools

Low-impact development (LID), best management practice (BMP), and green infrastructure (GI) are semi-engineered stormwater management practices that have been widely studied and implemented worldwide. Implemented in the complex environment of urban areas, LID-BMP-GI practices often intertwine with a very large number of hydro-environmental and socio-economic considerations and constraints. Therefore, they need to be carefully selected, designed, and allocated within an urban area. Both planning and optimization can lead to more systematic and strategic approaches to address this multi-scale, multi-parameter problem of practice allocation. In this review, we first identify the main components of the strategic planning cycle, their scope and inter-relationships, and their corresponding mathematical representations. We then present a comprehensive review of the existing literature on spatial allocation optimization tools (SAOTs) for LID-BMP-GI practices and summarize the generic structure and the systematic typology of the existing SAOTs. We conclude with a discussion of several current research gaps in the spatial allocation of LID-BMP-GI practices. In this review, we aim to summarize the strategies and optimization tools for the spatial allocation of LID-BMP-GI practices that are beneficial to practitioners. The other aim is to provide recommendations for future research on the development of more advanced and comprehensive SAOTs.

The Potential of Knowing More: A Review of Data-Driven Urban Water Management

The promise of collecting and utilizing large amounts of data has never been greater in the history of urban water management (UWM). This paper reviews several data-driven approaches which play a key role in bringing forward a sea change. It critically investigates whether data-driven UWM offers a promising foundation for addressing current challenges and supporting fundamental changes in UWM. We discuss the examples of better rain-data management, urban pluvial flood-risk management and forecasting, drinking water and sewer network operation and management, integrated design and management, increasing water productivity, wastewater-based epidemiology and on-site water and wastewater treatment. The accumulated evidence from literature points toward a future UWM that offers significant potential benefits thanks to increased collection and utilization of data. The findings show that data-driven UWM allows us to develop and apply novel methods, to optimize the efficiency of the current network-based approach, and to extend functionality of today's systems. However, generic challenges related to data-driven approaches (e.g., data processing, data availability, data quality, data costs) and the specific challenges of data-driven UWM need to be addressed, namely data access and ownership, current engineering practices and the difficulty of assessing the cost benefits of data-driven UWM.

GIS methods for sustainable stormwater harvesting and storage using remote sensing for land cover data - location assessment

Identification of potential sites for rainwater harvesting (RWH) is an important step toward maximizing water availability and land productivity in arid semiarid regions. Characterised as a "water scarce" country, Egypt has limited fresh water supplies, and is expected to suffer from water stress by the year 2030. Therefore, it is important to develop any means available to supply water and maintain human habitability in a sustainable manner. Practiced or simply indispensable in many countries around the world, rainwater harvesting (RWH) promotes a sustainable and efficient manner of exploiting water resources. In the present study, suitable areas for sustainable stormwater harvesting and storage in Egypt were identified using remote sensing for land cover data - location assessment linked to a decision support system (DSS). The DSS took into consideration a combination of thematic layers such as rainfall surplus, slope, potential runoff coefficient (PRC), land cover/use, and soil texture. Taking into account five thematic layers, the spatial extents of RWH suitability areas were identified by an analytical hierarchy process (AHP). The model generated a RWH map with five categories of suitability: excellent, good, moderate, poor and unsuitable. The spatial distribution of these categories in the area investigated was such that 4.8% (47910 km(2)) and 14% (139739 km(2)) of the study area was classified as excellent or good in terms of RWH, respectively, while 30.1% (300439 km(2)), 47.6% (474116 km(2)) and 3.5% (34935 km(2)) of the area were classified as moderate, unsuitable and poor, respectively. Most of the areas with excellent to good suitability had slopes of between 2% and 8% and were intensively cultivated areas. The major soil type in the excellent suitability areas was loam, while rainfall ranged from 100 to 200 mm yr(-1). The use of a number of RWH sites in the excellent areas is recommended to ensure successful implementation of RWH systems.

Assessment of public health risk associated with viral contamination in harvested urban stormwater for domestic applications

Capturing stormwater is becoming a new standard for sustainable urban stormwater management, which can be used to supplement water supply portfolios in water-stressed cities. The key advantage of harvesting stormwater is to use low impact development (LID) systems for treatment to meet water quality requirement for non-potable uses. However, the lack of scientific studies to validate the safety of such practice has limited its adoption. Microbial hazards in stormwater, especially human viruses, represent the primary public health threat. Using adenovirus and norovirus as target pathogens, we investigated the viral health risk associated with a generic scenario of urban stormwater harvesting practice and its application for three non-potable uses: 1) toilet flushing, 2) showering, and 3) food-crop irrigation. The Quantitative Microbial Risk Assessment (QMRA) results showed that food-crop irrigation has the highest annual viral infection risk (median range: 6.8×10(-4)-9.7×10(-1) per-person-per-year or pppy), followed by showering (3.6×10(-7)-4.3×10(-2)pppy), and toilet flushing (1.1×10(-7)-1.3×10(-4)pppy). Disease burden of each stormwater use was ranked in the same order as its viral infection risk: food-crop irrigation>showering>toilet flushing. The median and 95th percentile risk values of toilet-flushing using treated stormwater are below U.S. EPA annual risk benchmark of ≤10(-4)pppy, whereas the disease burdens of both toilet-flushing and showering are within the WHO recommended disease burdens of ≤10(-6)DALYspppy. However, the acceptability of showering risk interpreted based on the U.S. EPA and WHO benchmarks is in disagreement. These results confirm the safety of stormwater application in toilet flushing, but call for further research to fill the data gaps in risk modeling as well as risk benchmarks.

Visual Analysis of Public Utility Service Problems in a Metropolis

Issues about city utility services reported by citizens can provide unprecedented insights into the various aspects of such services. Analysis of these issues can improve living quality through evidence-based decision making. However, these issues are complex, because of the involvement of spatial and temporal components, in addition to having multi-dimensional and multivariate natures. Consequently, exploring utility service problems and creating visual representations are difficult. To analyze these issues, we propose a visual analytics process based on the main tasks of utility service management. We also propose an aggregate method that transforms numerous issues into legible events and provide visualizations for events. In addition, we provide a set of tools and interaction techniques to explore such issues. Our approach enables administrators to make more informed decisions.