Estimating stormwater runoff for community gardens in New York City

ediblecity: an R package to model and estimate the benefits of urban agriculture

Urban agriculture is gaining attraction to become one of the pillars of the urban ecological transition and to increase food security in an urbanized planet. However, there is a lack of systematic quantification of the benefits provided by urban agriculture solutions. In this paper, we present an R package to estimate several indicators related to benefits of urban agriculture. The goal is to provide a tool for researchers and practitioners interested in the impacts of urban agriculture. The ediblecity package provides functions to calculate 8 indicators: urban heat island, runoff prevention, green areas accessibility, NO 2 sequestration, jobs created in commercial gardens, volunteers involved in community gardens, green per capita and, finally, food production. Moreover, the package also provides a function to generate scenarios with different implementations of urban agriculture. We illustrate the use of the package by comparing three scenarios in a neighborhood of Girona (Spain), which is included in the package as an example dataset. There, we compare scenarios with an increasing amount of urban agriculture solutions. The ediblecity package is open-source software. This allows other R developers to contribute to the package, providing new functionalities or improving the existing ones.

Effects and productive performance of urban agriculture on collective and environmental health in the city of Rio de Janeiro, Brazil

Urban agriculture may help promote key indicators, such as improvement of environmental health and food security and reduction of social inequality. The present article aims to help understand the current situation of urban agriculture in the city of Rio de Janeiro by focusing on the Hortas Cariocas Program (HCP). To this end, two approaches were adopted. The first one was qualitative and based on a descriptive exploratory method that was used to survey and analyze the impacts caused by the program on the communities involved. The second one was quantitative and based on data envelopment analysis (DEA), which was used to assess and understand the program's productive performance from 2007 to 2019. The program's performance showed two peaks, one in 2012 with 80.21% and the other one in 2016 with 100.00% of the productive performance score. The behavior of the annual performance scores can be explained by the increases in the number of people who got directly involved (number of producers) and in the occupied area (number of seedbeds), as they reflect the socio-environmental character of the HCP.

Determination of Pollution and Environmental Risk Assessment of Stormwater and the Receiving River, Case Study of the Sudół River Catchment, Poland

Changes in the land use of urban catchments and the discharge of stormwater to rivers are causing surface water pollution. Measurements were taken of the quality of discharged stormwater from two areas with different types of development: a residential area and a residential-commercial area, as well as the quality of the Sudół River water below the sewer outlets. The following indicators were studied: TSS, COD, N-NO₃, N-NO₂, TKN, TN, TP, Zn, Cu, Hg, HOI, and PAHs. The influence of land use on the magnitudes of flows in the river was modeled using the SCS-CN method and the Snyder Unit Hydrograph Model. The results showed an increase in sealing and a resulting increase in surface runoff. Concentrations of pollutants in stormwater and analysis of the potential amounts of loadings contributed by the analyzed stormwater outlets indicate that they may be responsible for the failure to meet environmental targets in the Sudół River. Environmental risk assessment shows that the aquatic ecosystem is at risk. A risk factor indicating a high risk of adverse environmental effects was determined for N-NO₃, Zn, and Cu, among others.

Urban Flood-Risk Assessment: Integration of Decision-Making and Machine Learning

Urban flood-risk mapping is an important tool for the mitigation of flooding in view of continuing urbanization and climate change. However, many developing countries lack sufficiently detailed data to produce reliable risk maps with existing methods. Thus, improved methods are needed that can help managers and decision makers to combine existing data with more soft semi-subjective data, such as citizen observations of flood-prone and vulnerable areas in view of existing settlements. Thus, we present an innovative approach using the semi-subjective Analytic Hierarchy Process (AHP), which integrates both subjective and objective assessments, to help organize the problem framework. This approach involves measuring the consistency of decision makers’ judgments, generating pairwise comparisons for choosing a solution, and considering criteria and sub-criteria to evaluate possible options. An urban flood-risk map was created according to the vulnerabilities and hazards of different urban areas using classification and regression-tree models, and the map can serve both as a first stage in advancing flood-risk mitigation approaches and in allocating warning and forecasting systems. The findings show that machine-learning methods are efficient in urban flood zoning. Using the city Rasht in Iran, it is shown that distance to rivers, urban drainage density, and distance to vulnerable areas are the most significant parameters that influence flood hazards. Similarly, for urban flood vulnerability, population density, land use, dwelling quality, household income, distance to cultural heritage, and distance to medical centers and hospitals are the most important factors. The integrated technique for both objective and semi-subjective data as outlined in the present study shows credible results that can be obtained without complicated modeling and costly field surveys. The proposed method is especially helpful in areas with little data to describe and display flood hazards to managers and decision makers.

A Framework for Evaluating the Effects of Green Infrastructure in Mitigating Pollutant Transferal and Flood Events in Sunnyside, Houston, TX

There is a growing and critical need to develop solutions for communities that are at particular risk of the impacts of the nexus of hazardous substances and natural disasters. In urban areas at high risk for flooding and lacking proper land-use controls, communities are vulnerable to environmental contamination from industrial land uses during flood events. This research uniquely applied a series of landscape pzerformance models to evaluate such associations including (1) the Green Values National Stormwater Calculator, (2) the Value of Green Infrastructure Tool, and (3) the Long-Term Hydrologic Impact Assessment Model. This paper presents a framework for combining landscape performance models, which are often only individually applied, to evaluate green infrastructure impacts on flood mitigation and pollutant transfer during flooding events using the Sunnyside neighborhood in Houston, Texas, USA, as a case site. The results showed that the plan reduced the risk of flooding, decreased stormwater runoff contaminants, and provided a possible direction to protect vulnerable communities.

Ecosystem Services of Urban Agriculture: Perceptions of Project Leaders, Stakeholders and the General Public

Within the scholarly debate, Urban Agriculture (UA) has been widely acknowledged to provide diverse environmental and socio-cultural ecosystem services (ESs) for cities. However, the question of whether these potential benefits are also recognized as such by the involved societal groups on the ground has not yet been investigated. This paper aims at (1) assessing the perceived ESs of UA, comparing the views of different societal groups in the city of Bologna, Italy (namely: UA project leaders, stakeholders and the general public) and (2) to identify differences in the evaluation of specific UA types (indoor farming, high-tech greenhouses, peri-urban farms, community-supported agriculture, community rooftop garden and urban co-op). In total, 406 individuals evaluated 25 ESs via a standardized Likert-scale survey. The study unveiled similarities and divergences of perceptions among the different societal groups. The statistical analysis indicated that the general public and UA stakeholders agree on the high relevance of socio-cultural ESs, while provisioning ESs was considered as less significant. UA types focusing on social innovation were expected to provide higher socio-cultural ESs whereas peri-urban activities were more closely linked to habitat ESs. We assume that involvement and knowledge of UA are determining factors for valuing the provision of ESs through UA, which needs to be considered for ES valuation, particularly in a policymaking context.

Greening the Browns: A Bio-Based Land Use Framework for Analysing the Potential of Urban Brownfields in an Urban Circular Economy

The Circular Economy (CE) is expected to accelerate the use of resources with bio-based origin. Cities have an important role in such an economy, not only as main consumers but also because vegetation provides numerous ecosystem services essential for the well-being of urban dwellers. Urban lands are, however, heavily burdened with both past and present activities and ongoing urbanization. Retrofitting obsolete and potentially contaminated brownfields provides an opportunity to engage with bio-based land uses within the city. At the same time, plants are an important part of Gentle Remediation Options (GROs), a more sustainable alternative for managing contamination risks and restoring soil health. This paper (1) provides a tentative selection of Urban Greenspaces (UGSs) relevant for brownfields, and a compilation of ecosystem services provided by the selected UGSs, and (2) presents a framework covering the 14 selected bio-based land uses on brownfields, including GRO interventions over time. This framework provides three practical tools: the conceptualization of linkages between GROs and prospective UGS uses, a scatter diagram for the realization of 14 UGS opportunities on brownfields, and a decision matrix to analyze the requirements for UGS realization on brownfields.

Citizen Science-Informed Community Master Planning: Land Use and Built Environment Changes to Increase Flood Resilience and Decrease Contaminant Exposure

Communities adjacent to concentrated areas of industrial land use (CAILU) are exposed to elevated levels of pollutants during flood disasters. Many CAILU are also characterized by insufficient infrastructure, poor environmental quality, and socially vulnerable populations. Manchester, TX is a marginalized CAILU neighborhood proximate to several petrochemical industrial sites that is prone to frequent flooding. Pollutants from stormwater runoff discharge from industrial land uses into residential areas have created increased toxicant exposures. Working with local organizations, centers/institutes, stakeholders, and residents, public health researchers sampled air, water, indoor dust, and outdoor soil while researchers from landscape architecture and urban planning applied these findings to develop a community-scaled master plan. The plan utilizes land use and built environment changes to increase flood resiliency and decrease exposure to contaminants. Using a combination of models to assess the performance, costs, and benefits of green infrastructure and pollutant load impacts, the master plan is projected to capture 147,456 cubic feet of runoff, and create $331,400 of annual green benefits by reducing air pollution and energy use, providing pollution treatment, increase carbon dioxide sequestration, and improve groundwater replenishment. Simultaneously, there is a 41% decrease across all analyzed pollutants, reducing exposure to and transferal of toxic materials.

Quantifying soil contamination and identifying interventions to limit health risks

Numerous toxicants contaminate soil and negatively affect the environments that children explore. Accurately measuring these toxicants and characterizing the level of soil contamination may be difficult and must include measurements of both the environmental concentrations and the exposure responses of human populations. This article reviews the current methods and technologies available for quantifying soil contamination. Several intervention strategies exist for limiting human exposure to contaminated soils and the strengths and weaknesses of these methods are discussed. Lastly, current policies on soil contamination and the importance of protecting vulnerable populations by developing means to improve health conditions for children are reviewed.

Residents’ Attention and Awareness of Urban Edible Landscapes: A Case Study of Wuhan, China

More and more urban residents in China have suffered from food insecurity and failed to meet the national recommendation of daily fruit and vegetable consumption due to rapid urbanization in recent years. Introducing edible landscapes to urban greening systems represents an opportunity for improving urban food supply and security. However, residents’ opinion on urban edible landscapes has rarely been discussed. In this study, questionnaire surveys were performed in eight sample communities in Wuhan, China, to collect the information on residents’ attention and awareness of urban edible landscapes. Results indicated that nearly one-third of the respondents were unaware of edible landscapes before the interview. Most residents thought that an edible landscape could promote efficient land use (57.26%) and express special ornamental effects (54.64%), but quite a few didn’t believe that growing edible plants in urban public spaces could increase food output (37.10%) and improve food quality (40.12%). Overall, 45.65% and 32.73% of the growers performed their cultivation behavior in private and semiprivate spaces, respectively. Lack of public areas for agriculture use was regarded as the main barrier restricting the development of urban horticulture by 55.86% of growers and 59.51% of non-growers. The residents were also worried about their property manager’s opposition, possible conflicts, and complex relationships with their neighbors. Food policies and infrastructure support from local governments and official institutions were needed to ensure the successful implementation of edible landscapes in urban areas.

A runoff trading system to meet watershed-level stormwater reduction goals with parcel-level green infrastructure installation

Green infrastructure (GI) has been recommended widely to reduce runoff from the built environment. However, reliance on public land for GI implementation could cause a heavy financial burden on local governments. Although economic incentives and market-based mechanisms may encourage public participation in managing stormwater by installing GI on private parcels, a runoff trading market has not been fully developed in practice. To establish a market, in part, requires a watershed-based planning framework and fully informed parcel owners in regard to tradable credits, costs, and benefits. We propose a scenario-based Stormwater Management Planning Support System for Trading Runoff Abatement Credits (SMPSS-TRAC) to facilitate the calculation and allocation of stormwater runoff abatement credits in order to assist the decision-making of GI investment. We apply SMPSS-TRAC to a watershed located in Hamilton County, Ohio, USA and develop five scenarios representing increasing use of GI. We test the scenarios under a 5-year rainfall intensity and set a cap of runoff for each scenario at a level that is equal to the runoff from an undeveloped status (1.03-inch runoff depth for the watershed). With the proposed SMPSS-TRAC, the watershed authority could encourage all parcel owners to install suitable GI or purchase credits from the market. When detention basins are needed to meet a stated goal, the watershed authority would build them on vacant lots and share costs with all parcels within the same sub-catchment. The last scenario with four types of GI installed, shows that the watershed reaches market equilibrium and generates 15,358 m³ credit surplus. SMPSS-TRAC has the potential for including multiple stakeholders' preferences and concerns in searching for preferable scenarios.

Development of a scenario-based stormwater management planning support system for reducing combined sewer overflows (CSOs)

Using combined sewer systems to handle excess stormwater runoff is common in older urban areas. Combined sewer overflow (CSO) events occur when hydraulic capacity is exceeded, and untreated wastewater discharges to surface waters. As urban population density increases, and more demand is placed on infrastructure, CSO events happen more often and cause serious environmental problems and public-health risks. Recently, green infrastructure (GI) has been integrated with existing gray infrastructure (GrayI) to reduce CSO events. However, there lacks a goal-oriented planning framework for eliminating CSOs at a watershed/sewershed scale. Moreover, existing stormwater simulations based on catchments or other geographic units, do not consider spatial variation within the unit, such as distribution, attribution, ownership, and management of GI. We propose a scenario-based Stormwater Management Planning Support System for CSOs (SMPSS-CSO) to provide a platform for reducing CSO events by coordinating parcel-based installations of GI. We applied the SMPSS-CSO to a sewershed with a single CSO location in Cincinnati, Ohio and developed four scenarios representing increased use of GI (rain barrels, green roofs, porous pavements, and detention basin) based on its cost, difficulty of installation, and property ownership. Runoff quantity, time of concentration, and peak flow rate were simulated using the curve number method. Our analysis shows a 41% reduction in stormwater runoff is necessary to eliminate CSO events for a two-year rainfall, required 97.25% of private and 27.59% of public parcels to install GI. GI alone cannot eliminate CSO events in this sewershed and must be incorporated with additional GrayI (e.g., storage tanks, pipes). The SMPSS-CSO has the potential for including multiple stakeholders' preferences and concerns in the searching for preferable scenarios.

Multitemporal Geospatial Evaluation of Urban Agriculture and (Non)-Sustainable Food Self-Provisioning in Milan, Italy

Urban agriculture in Global North cities is strongly promoted as a sustainable solution to achieve different goals, such as food production, quality of life, and well-being. Although several attempts have been made to evaluate urban agriculture production, few studies have investigated food production in a multitemporal geospatial way and considered per capita population needs, gender, and age strata consumption. This study presents a spatiotemporal quantification of urban agriculture in the city of Milan (Italy) for assessing food self-provisioning potential. We utilized high-resolution Google Earth images and ancillary data to create a detailed cadaster of urban agriculture for the years 2007 and 2014. Based on four scenarios of food production and statistical data on vegetables and cereals consumption, we estimated current total production and requirements for the city dwellers. Our results showed that the actual extension of vegetable gardens (98 ha) and arable land (2539 ha) in the best scenario could satisfy approximately 63,700 and 321,000 consumers of vegetables and cereal products, respectively. Overall, current urban agriculture production is not able to meet vegetables and cereal consumption for more than 1.3 million city residents. Scenario estimates suggest rethinking land use promoting horticultural production to achieve more sustainable food systems.

An ensemble prediction of flood susceptibility using multivariate discriminant analysis, classification and regression trees, and support vector machines

Floods, as a catastrophic phenomenon, have a profound impact on ecosystems and human life. Modeling flood susceptibility in watersheds and reducing the damages caused by flooding is an important component of environmental and water management. The current study employs two new algorithms for the first time in flood susceptibility analysis, namely multivariate discriminant analysis (MDA), and classification and regression trees (CART), incorporated with a widely used algorithm, the support vector machine (SVM), to create a flood susceptibility map using an ensemble modeling approach. A flood susceptibility map was developed using these models along with a flood inventory map and flood conditioning factors (including altitude, slope, aspect, curvature, distance from river, topographic wetness index, drainage density, soil depth, soil hydrological groups, land use, and lithology). The case study area was the Khiyav-Chai watershed in Iran. To ensure a more accurate ensemble model, this study proposed a framework for flood susceptibility assessment where only those models with an accuracy of >80% were permissible for use in ensemble modeling. The relative importance of factors was determined using the Jackknife test. Results indicated that the MDA model had the highest predictive accuracy (89%), followed by the SVM (88%) and CART (0.83%) models. Sensitivity analysis showed that slope percent, drainage density, and distance from river were the most important factors in flood susceptibility mapping. The ensemble modeling approach indicated that residential areas at the outlet of the watershed were very susceptible to flooding, and that these areas should, therefore, be prioritized for the prevention and remediation of floods.

Resilience through Regeneration: The economics of repurposing vacant land with green infrastructure

Many urban areas affected by flood disasters are also becoming increasingly ecologically and socially fragmented due to the accumulation of vacant properties. While redevelopment is often viewed as the primary objective in regenerating vacant properties, they can also potentially provide ecological and hydrological land uses. Rather than chasing development- based incentives for regenerating vacant lots in high flood-risk communities, a balance should be sought between new developmental land uses and green infrastructure to help counteract stormwater runoff and flood effects, or "Resilience through Regeneration." This paper uses landscape performance measures to evaluate the economic and hydrologic performance of green infrastructure regeneration projects for three marginalized neighborhoods in Houston, Texas, USA. Each project site is characterized by excessive vacant lots and flood issues. Results suggest that, when using green infrastructure to regenerate vacant properties, 1) flood risk continually decreases, 2) upfront economic costs increase in the short term (when compared to conventional development), and 3) the long-term economic return on investment is much higher.