A Synthesis of Climate Change Impacts on Stormwater Management Systems: Designing for Resiliency and Future Challenges

Urban sprawl has resulted in great losses of vegetation areas, an increase in impervious surfaces, and consequently the direct flow of stormwater into stream channels (i.e., the immediate flow of stormwater into stream channels, in comparison to the indirect flow that is represented by practices aiming to retain stormwater for a certain period of time and treat the polluted stormwater prior to flowing into the stream channels such as detention/retention basins, among others). Stormwater management systems such as catch basins (CBs) are needed to reduce the effect of stormwater runoff. Preventative maintenance, repair, and replacement of CBs are critical to achieve stormwater management best practices. Those practices prevent the blockage of the stormwater system, limit the pollutants in storm sewers, and reduce the risk of flooding. However, no preceding research studies have been conducted to model and simulate the serviceability of CBs and to determine optimal strategies for operating CBs. To that extent, this study establishes a framework to develop and validate an optimal and adaptive maintenance, repair, and overhaul (MRO) strategy for CBs. In relation to that, an agent-based model (ABM) integrated with Monte Carlo simulation was developed for all 560 CBs in New York City’s District 5 and was statistically validated using 99% confidence intervals. The MRO parameters were optimized to minimize the total cost of the system and attain the desired level of serviceability of CBs. Sensitivity analysis was conducted to guide the maintenance planning process of CBs and reveal the effect of the input parameters on the model’s behavior. In addition, ten thousand Monte Carlo iterations were simulated to derive the distributions of the defined parameters. The results proved that in order to minimize the overall cost of repair, maintenance, and replacement of CBs and attain a minimum serviceability threshold of 80%, the following optimal MRO policy needs to be implemented: having seven service crews (where service crews are human resources (i.e., MRO teams) needed to perform the required maintenance, repair, and replacement work), implementing a replacing policy, and replacing CBs after five maintenance periods. The findings revealed that the service crews represent the most critical parameter in affecting the total cost and serviceability of CBs. This research contributes to the existing literature by offering a better knowledge of the management process of CBs and devising optimal MRO strategies for properly operating them. Ultimately, this research helps decision-makers and engineers increase the lifespan of CBs and limit their risks of breakdown, increase their efficiency, and avoid unnecessary costs. The proposed model is flexible and can be implemented to any geographical area and with other model/system parameters, which makes it adaptive for any scenario and area presented by the user. Finally, maintaining stormwater management practices helps in protecting the environment by decreasing the demand on stormwater systems, reducing flooding, protecting people and properties, promoting healthier rivers, and consequently creating more sustainable communities.

Global decline in capacity of coral reefs to provide ecosystem services

Comparative performance and cost-integrated life cycle assessment of low impact development controls for sustainable stormwater management

Big-data mining approaches based on Artificial Intelligence models can help forecast biodiversity changes before they happen. These approaches can predict macroscopic species distribution patterns and trends that can inform preventive measures to avoid the loss of ecosystem functions and services. They can, therefore, help study and mitigate climate change implications on biodiversity conservation in fragile ecosystems. Wetlands are particularly fragile ecosystems where climate change poses severe risks and has dramatically reduced their size over the past century, with profound consequences on biodiversity and ecosystem services. Through big-data mining approaches, we can predict future wetland biodiversity trends in the context of climate change. This paper proposes such predictive analysis for a specific wetland: The Massaciuccoli Lake basin in Tuscany, Italy. This basin is a critical tourist attraction due to its rich biodiversity, making it an area of interest for citizens, tourists, and scientists. However, the region's suitability for native and non-native species is at risk due to climate and land-use change. Using machine-learning models, we predict the potential effects of climate change on animal spatial distribution in the basin under different greenhouse gas emission scenarios. The results suggest that habitat suitability has generally improved from 1950 to today, presumably owing to the targeted conservation strategies adopted in the area, but climate change will severely reduce bird biodiversity by 2050 while favouring several insect species' proliferation and other species' habitat change, even under a medium-emission scenario. This will lead to significant changes in the basin's biodiversity. Our methodology is adaptable to other wetland basins, being fully based on open data and models. The spatially explicit modelling used in this research provides valuable information for policymakers and spatial planners, complementing traditional biodiversity trend analyses.

<p><strong>Environmental disturbances driven by climate change are causing unprecedented degradation of natural systems across the globe. Rapid environmental changes limit our capacity to forecast future habitat conditions based on historical benchmarks as we face scenarios unlike any observed in the past. Tropical coral reefs are experiencing widespread biodiversity and habitat loss due to increasingly frequent marine heatwaves, intense storms, pathogens, pollutants, and human exploitation. Reef flattening has been observed across the entire range of latitudes where coral reefs develop. Coral reef fauna are specialised to inhabit one of the most structurally complex habitats in the world, making them particularly vulnerable to habitat degradation. The flattening of reef habitats changes system dynamics and jeopardizes the stability of the ecosystem services we rely on reefs to provide. In this thesis, I develop and explore ecosystem models that explicitly consider the influence of habitat quality on dynamic processes. Using parameters that simulate a generic reef ecosystem, I manipulate habitat quality in several ways, revealing key aspects of the interaction between fish communities and habitat quality with a focus on the provision of ecosystem services. These models can be used as predictive tools to inform ecosystem management strategies and determine trade-offs in decision-making, allowing us to plan for a future where coral reef ecosystems are likely to be drastically different from those of the past.</strong></p><p>To set the stage for this work, Chapter 1 begins with a comprehensive overview of coral reef ecosystems and the critical issues threatening their survival. The relationship between various ecological factors and their collective impacts on coral reefs is highlighted, focussing on trophic relationships and the consequences of disturbance. This is followed by a detailed examination of structural complexity in marine environments, emphasizing its crucial role as a structuring force in reef ecosystems. The next section dives into the functional ecology of reefs, reviewing observed impacts of habitat change on the functioning and structure of reef communities. Considering the myriad threats to reefs, current management efforts are explored, focusing on the role of ecosystem models in policy, strategic planning, and decision-making. Finally, I provide a framework for the research, detailing the primary objectives of each chapter and the work as a whole.</p><p>As ecosystem engineers on reefs, hard corals form complex, three-dimensional structures as they grow. These structures provide refuge from competitors, predators, and environmental stressors. By influencing predator-prey interactions, reef refuges promote juvenile survivorship and facilitate the transfer of energy up the food chain, allowing reefs to support abundant and diverse fish communities. In Chapter 2, I explore the impact of the refuge profile, a metric that quantifies both the abundance of predation refuges on a reef and the size range of fish that they can accommodate. Using a size-based ecosystem model, I evaluate how different sizes and distributions of refuges impact the ecosystem and affect the provision of ecosystem services. Model predictions indicate that refuges used by fish between 5 and 10 cm in length significantly increase fish biomass and fisheries yields, highlighting the importance of small-scale refuges for sustaining coral reef health. I also identify features of refuge profiles that maximise three valuable reef services: reef resilience, potential fisheries productivity, and ecotourism. These insights can inform the strategic design of artificial reefs to support ecosystem services through climate change.</p><p>Ecosystem models that capture trophic dynamics are valuable tools for predicting and managing the effects of exploitation and environmental change. Accounting for species interaction through food-web links reveals ecosystem-wide impacts of changes to dynamics processes, providing a more comprehensive view of potential outcomes of environmental change. Unfortunately, most of these frameworks require extensive data to set up, making them difficult to use for coral reefs and more difficult to generalize. Data collection, monitoring, and management enforcement are a consistent challenge for most of the world’s coral reefs, which develop along tropical coastlines, often in remote regions. Size-spectrum models offer a simpler perspective on trophic modelling, employing the assumption that predator-prey interactions are determined primarily by body size. However, there are no size-spectrum frameworks available for managers that incorporate a measure of habitat quality, a key component of reef ecosystems. Chapter 3 presents MizerReef, a novel R package that facilitates the development of dynamic, multi-species size-spectrum models specifically tailored for coral reef ecosystems. By incorporating the critical role of predation refuges, MizerReef enables users to simulate complex interactions among multiple species groups under various scenarios of habitat degradation. The chapter also presents some examples of package use and a set of steady-state parameters tuned for comparison to the size-spectrum model presented in Chapter 2. The MizerReef package offers a feasible pathway towards large-scale modelling of coral reef ecosystems to support management and maintain crucial services through climate change.</p><p>Physical traits, such as body shape and swimming ability, and behavioural traits, such as foraging strategy and activity pattern, shape the relationship between an organism and its environment. Functional structure, defined as the abundance and diversity of these traits within an environment, plays a pivotal role in how communities respond to disturbance and exploitation, influencing overall system stability. As reef habitat quality diminishes, functional structure also tends to change, and these shifts can have profound impacts on ecosystem service provision. Chapter 4 investigates how changes to the refuge profile impact ecosystem services and fish assemblage structure using a generic reef ecosystem model set up with MizerReef and several of the refuge profiles designated in Chapter 2. Predictions indicate that fish assemblage composition is dependent on the refuge profile. Profiles that supported the highest reef resilience in Chapter 2 were dominated by parrotfish, reinforcing the concept that reef resilience is supported by small-scale habitat structure. However, the productivity of the profile deemed best for fishing was also supported primarily by parrotfish, emphasizing the trade-offs involved in exploiting reefs with plentiful small predation refuges. Herbivores generally appear to benefit from habitat structure at any size while the productivity of larger piscivores is hindered by plentiful refuge. These results reveal a more resolved picture of how habitat quality affects reef communities, allowing us to fine-tune management strategies to support essential reef functions.</p><p>Coral reefs are subject to a multitude of stressors on local and global scales. Disturbances can cause rapid changes in the entire community, but also more subtle shifts that play out over decades. The process of reef flattening and recovery is continuous and dynamic and can result in a variety of stable ecosystem states. Considering the inherent limitations of steady-state dynamics in accounting for the episodic nature of disturbances and their impacts, Chapter 5 addresses the critical need to understand how coral reef ecosystems respond to acute environmental change. Using historical data, I develop a realistic timeline describing how the refuge profile changes following disturbance, with a particular focus on the consequences of mass bleaching events. This is used to create a new degradation dynamic for the MizerReef package that simulates changes to the refuge profile for three common disturbed coral reef states: coral rubble-dominated, macroalgae-dominated, and recovered. Predictions indicate that the assemblage composition of disturbed reefs is dependent on the recovery trajectory. Recovered reefs have the potential to support relatively stable fish assemblages, but macroalgal and rubble reefs become dominated by herbivores and generalist predators, respectively. This information can help managers plan for different degradation scenarios and demonstrates the potential for MizerReef to explore temporal dynamics.</p><p>This thesis encompasses a comprehensive exploration of the intricate relationships between habitat quality, community dynamics, and ecosystem service provision within a coral reef ecosystem model. Through a series of innovative modelling approaches, it sheds light on the role of structural complexity in sustaining reef biodiversity and the functionality of reef-associated communities. The findings underscore the urgent necessity for informed management strategies that prioritize habitat quality and structural complexity to mitigate the adverse effects of environmental disturbances. Ultimately, this thesis contributes to our understanding of coral reef ecosystems, providing a foundation for future efforts to preserve these critical habitats in the face of unprecedented global change.</p>

Optimal conservation planning of multiple hydrological ecosystem services under land use and climate changes in Teshio river watershed, northernmost of Japan

Climate and land use change can profoundly impact the provision of ecosystem services (ES) over time, particularly in the landscape of open fields along with growing urbanization and rising demand for space, food and energy. Policymakers are keen on knowing the combined effects of climate and land use change on ESs as a critical issue in human well-being. However, deep knowledge of how to identify these relationships is still lacking. This research aims to undertake a comprehensive assessment of soil- and water-related ES, and improvement in understanding how they are affected by climate and land use change. We applied the Integrated Valuation of Ecosystem Services and Trade-offs model for four ES (soil retention, nutrient delivery ratio, carbon storage, and water yield) for the years 2000 and 2018 in the Nitra region, Slovakia. We investigated the spatial and temporal changes in ES provision and determined the hotspots and coldspots of multiple ES. We found that soil retention, water yield, and carbon storage display a rising trend while the nutrient delivery ratio showed a decreasing trend over the past 18 years. Although all the mentioned services mainly attributed to land use change, the relative contribution of climate change was not deniable. Forests in the north and east and distributed urbanization and agriculture are the hotspots and coldspots for all ESs, respectively. Our results, in terms of determining the relative importance of land use and climate change and identifying the sensitive areas of ES provision, provide a scientific basis for ecosystem conservation and management priority setting at the local and regional levels.

Adapting ecosystem restoration for sustainable development in a changing world

This study aims at contributing to the vulnerability and adaptation to climate changes (CC) analysis of bordering communities of Togodo Reserve, in order to enhance their resilience. Specifically, the present study attempted to (i) identify the climatic hazards of the WRT; (ii) determine the impacts of climate variability and change on their livelihoods; (iii) assess the socio-economic vulnerability of these communities to food insecurity in relation to CC; and (iv) identify indigenous adaptation strategies to control the effects of CC. The methodological approach used is based on a factual research and a field investigation. The investigation is conducted in two villages around the reserve, namely Deve and Gbohoule. The results showed that climate variability and change were appreciated in different indicators by the local communities living around the WRT: Droughts, flooding, high winds and temperature increase with severe consequences on the communities (famine, destruction of tangible and intangible properties, loss of human life, populations’ migration). The communities are aware that humans are responsible for these events that have become recurrent from 2007 and occur almost every year. According to them, the causes of climate changes are deforestation (due to overexploitation of timber, fuelwood and shifting agriculture), bush fires, rapid increase in population, anger of gods due to irregularities of sacrifices and violations of customs. The communities are vulnerable to main climatic hazards and suffered from food insecurity. The factorial correspondence analysis (FCA)) carried out shows that the perception of the degree of exposure of households to risks depends on their standard of livelihood. Facing these climate events, the populations develop many adaptive strategies of which most are consistent with the national orientations and strategies. These adaptive strategies must be reinforced and supported in order to reduce the vulnerability of these populations to climate changes. Key words: Climate variability and change, communities, livelihood, vulnerability and adaptation, Wildlife Reserve of Togodo.

Computer models are widely used to help make decisions about real-world systems. As computer models of large and complex systems can have long run-times and high-dimensional input spaces, it is often necessary to use emulation to assess uncertainties in computer model output. This paper presents methodology for emulation of complex computer models motivated by a real-world example in energy policy. The computer model studied is an economic model of investment in electricity generation in Great Britain. The computer model was used to select parameters in a government policy designed to incentivize investment in renewable technologies to meet government targets. Limited computing time meant that few runs of the computer model were available to fit an emulator. The statistical methodology developed was therefore focused on accurately capturing the uncertainty in computer model output arising from the small number of available model runs. A varying coefficient emulator is proposed to model uncertainty in model output when extrapolating away from model runs. To maximize use of the small number of runs available, this varying coefficient emulator is paired with a criterion-based procedure for design selection.

Ecological systems and natural resources are significant sources to generate human well-being (Millennium Ecosystem Assessment 2005; TEEB 2010; Summers et al. 2012). Climatic and socio-economic changes will have many adverse impacts on natural systems and thus threaten human well-being (Schroter et al. 2005; Metzger et al. 2006; Staudinger et al. 2012). Therefore, there is an urgent need for society to adapt to these future challenges in order to preserve ecosystem services (ES) and secure human well-being for future generations. The amount of literature concerning impact assessments of climate change on ES has been growing in recent years, with the consensus being that climate change has already an effect on the supply of ES, thus threatening human well-being and that immediate action is needed (Schroter et al. 2005; Briner et al. 2012; Elkin et al. 2013; IPCC 2014). Facing this need for action requires the integration of ES in regional and local decision making processes on climate change adaptation (Daily et al. 2009; UNEP 2012; Loft et al. 2015). Including multiple ES simultaneously into this decision making process and identifying ES of concern, which require immediate action (Metternicht et al. 2014), reduces the risk of unintended trade-offs between adaptation measures.

<p>We compare the stochastic behaviour of temperature outputs of climate models for the 20th century<br>to the historical data (stations and reanalysis fields) at several temporal and spatial scales. In<br>particular we examine the marginal distributions and the dependence structure with emphasis on<br>the Hurst-Kolmogorov behaviour. The comparison aims to contribute to the quantification of<br>reliability and predictive uncertainty of temperature climate model outputs over different scales in a<br>framework of assessing their relevance for engineering planning and design.</p><p><br>(Acknowledgement: This research is conducted within the frame of the course "Stochastic Methods"<br>of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA<br>provided moral support for the participation of the students in the Assembly.)</p>

A dynamic assessment tool for exploring and communicating vulnerability to floods and climate change

This chapter examines the causes of climate and the variability and long-term changes in the climate. Improvements in the understanding of the factors that contribute to climate and climatic change along with increasingly abundant, high-resolution and high-quality environmental data and rapid advances in computing capabilities, have allowed for substantial improvements in climate modelling over the past few decades. These model improvements provide better opportunities to implement insightful decisions to enhance the human condition as part of the physical-human process-response system. The pendulum has now seemingly swung towards an increasing responsibility of environmental planners, community organizations, national leaders and intergovernmental agencies to use the climate model output in efforts for capacity building in their long-range pursuit of sustainability.

First posted January 25, 2024 For additional information, contact: Director, Dakota Water Science CenterU.S. Geological Survey821 East Interstate Avenue, Bismarck, ND 585031608 Mountain View Road, Rapid City, SD 57702Contact Pubs Warehouse Flood-frequency analysis, also called peak-flow frequency or flood-flow frequency analysis, is essential to water resources management applications including critical structure design and floodplain mapping. Federal guidelines for doing flood-frequency analyses are presented in a U.S. Geological Survey Techniques and Methods Report known as Bulletin 17C. A basic assumption within Bulletin 17C is that for drainage basins without major hydrologic alterations, statistical properties of the distribution of annual peak streamflows (peak flows) are stationary; that is, the mean, variance, and skew are constant. The stationarity assumption has been widely accepted within the flood-frequency community; however, a better understanding of long-term climatic persistence and concerns about potential climate change and land-use change has caused a reexamination of the stationarity assumption. Flood-frequency analyses that do not incorporate observed trends and abrupt changes may result in a poor representation of the true flood risk. Bulletin 17C does not offer guidance for incorporating nonstationarities when estimating floods, and it describes a need for studies that incorporate changing climate or basin characteristics. In response to this need and a history of concern regarding nonstationarity peak flows in the region, this study was done by the U.S. Geological Survey, in cooperation with the Departments of Transportation of Illinois, Iowa, Michigan, Minnesota, Missouri, South Dakota, and Wisconsin; the Montana Department of Natural Resources and Conservation; and the North Dakota Department of Water Resources, to assess potential nonstationarity in peak flows in the north-central United States.This chapter summarizes the methods used to detect hydroclimatic changes in peak-flow data in the study region. A wide range of analyses and statistical approaches are applied to document the primary mechanisms controlling floods and characterize temporal changes in hydroclimatic variables and peak flow. Four periods were selected for analysis of peak flow, daily streamflow, and climate data. The periods are (1) a 100-year period, 1921–2020; (2) a 75-year period, 1946–2020; (3) a 50-year period, 1971–2020; and (4) a 30-year period, 1991–2020. The climate data consist of monthly time series estimates of temperature, precipitation, potential evapotranspiration, actual evapotranspiration, snowfall, soil moisture storage, snow water equivalent, and runoff on a 3.1-mile by 3.1-mile grid for the conterminous United States.Statistical and graphical analyses were used to investigate potential changes in hydrology and climate. The starting point for these analyses was the initial data analysis of peak flow described in Bulletin 17C, which includes plotting the peak flow and checking for autocorrelation, monotonic trends, and changes points. Analyses were added to examine additional features in the data. To examine potential causal drivers of changes, the climate data were analyzed graphically and statistically. Results are provided in a U.S. Geological Survey data release. The study limitations are documented for users of the results.