Modeling climate change impacts on urban storm sewer network performance using SWMM

LID (Low impact Development) has been widely promoted as a measure against urban flooding which has been recently increasing due to urbanization and climate change. However, studies that consider the combined effects of spatially distributing multiple LIDs simultaneously in an urban area of specific size as urban planning scenarios are few. In this study, two cases of past rainfall data (short duration and long duration heavy rainfall), are used to simulate the effects of 3 different urban planning scenarios of distributed LID (i.e. combined LIDs implementable at the 1) building-level, 2) in open spaces, and 3) combined implementation of both 1&2), in addition to simulating for separate implementation of each LID type using the Storm Water Management Model (SWMM). The results show that in the case of short duration heavy rainfall, all 3 LID scenarios provide a greater decrease in the rate of flood volume with comparison to the case of long duration heavy rainfall. This points to the fact that LIDs have a high potential to mitigate flood volumes resulting from short duration heavy rainfall - the type of rainfall which has become more frequent recently. Furthermore, the paper also organizes the LID types according to their implementability under different urban planning scenarios, and shows that such combined use of LIDs results in higher flood mitigation efficacy.

Responses of fine particulate matter (PM2.5) air quality to future climate, land use, and emission changes: Insights from modeling across shared socioeconomic pathways

Effect difference of climate change and urbanization on extreme precipitation over the Guangdong-Hong Kong-Macao Greater Bay Area

A comprehensive hydrological model, like the storm water management model (SWMM), has been widely used for rainfall-runoff simulation. In recent years, simple and effective modern modeling techniques have also brought great attention to the prediction of runoff with rainfall input. A comparative case study between SWMM and a presently developed fuzzy logic model for the predictions of total runoff within the watershed of Cascina Scala, Pavia in Italy is presented. A data set of 23 events from 2000 to 2003 including with the total rainfall and total runoff are adopted to train fuzzy logic parameters. Other data (1990–1995) with detailed time variations of rainfall and runoff are available for the setup and calibration of SWMM for runoff modeling. Among the 1990–1995 data, 35 independent rainfall events are selected to test the prediction performance of the SWMM and fuzzy logic models by comparing the predicted total runoffs with measured data. Comparisons and performance analyses in terms of the root-mean-squared error and coefficient of efficiency are made between the SWMM and the fuzzy logic model. The predicted total runoffs from either the SWMM or the fuzzy logic model are found to agree reasonably well with the measured data. For large rainfall events, the fuzzy logic model generally outperforms the SWMM unless the modification of the impervious ratio is applied to improve the SWMM results. However, the SWMM can produce the time varying hydrograph whereas fuzzy logic is subject to limitation of the methodology and is unable to generate such an output.

Evaluating the joint effects of climate and land use change on runoff and pollutant loading in a rapidly developing watershed

Developing sustainable strategies by LID optimization in response to annual climate change impacts

Urban road networks function as surface passage for floodwater transport during extreme storm events to reduce potential risks in the city. However, precise estimation of these flow rates presents a significant challenge. This difficulty primarily stems from the intricate three-dimensional flow fields at road intersections, which the traditional one-dimensional models, such as Storm Water Management Model (SWMM), fail to precisely capture. The two-dimensional and three-dimensional hydraulic models are overly complex and computationally intensive and thus not particularly efficient. This study addresses these issues by integrating a semiempirical flow diversion formula into the SWMM source code. The semiempirical formula, derived from hydraulic experiments and computational fluid dynamics simulations, captures the flow dynamics at T-shaped intersections. The modified SWMM’s performance was evaluated against experimental data, and the original SWMM, the two-dimensional MIKE21, and the three-dimensional FLUENT models. The results indicate that the modified SWMM matches the precision of the two-dimensional MIKE21, while significantly reducing computational time. Compared to MIKE21, this study achieved a Nash-Sutcliffe efficiency of 0.9729 and a root mean square error of 0.042, with computational time reduced by 99%. The modified SWMM is suitable for real-sized urban road networks. It provides a high-precision tool for urban road drainage system computation that is crucial for effective stormwater management.

Mountainous areas on the Tibetan Plateau (TP) are of particular hydrological concern as topography and atmospheric conditions can result in large and sudden floods, and pose critical threats to water-related safety and sustainability in neighboring countries. The Yarlung Zangbo (YZ) river basin is the largest river basin on the southern TP, but the ways in which flood discharges in this basin will evolve under 21st-century climate change and the effect of precipitation extremes and glacier melt remain unclear. Here, we comprehensively quantify the future evolution of extreme flood frequency and intensity under 21st-century climate change, and determine the predominant drivers of flood changes in the YZ basin. We show that total runoff is projected to increase owing to continued wetting throughout the 21st century under two different shared socioeconomic pathways (SSPs) in the YZ basin. Both the frequency and intensity of flood extremes are projected to increase under both SSPs, primarily driven by enhanced total days and magnitude when daily precipitation estimates > 95th percentile. Glacier melt is projected to enhance the intensity and frequency of extreme floods by 12%–23% under both SSPs. This study aims to close the knowledge gap regarding future flood risks in the TP’s rainfall- or meltwater-impacted basins.

Green infrastructure is a sustainable, environmentally friendly, and resilient method to manage stormwater in urban catchments, which is followed all over the world. Despite intense monsoons, the influence of catchment-scale spatial variations in green infrastructure on stormwater mitigation remains poorly understood, highlighting a critical research gap. This study employs the storm water management model (SWMM) rainfall-runoff model to evaluate the efficiency of green infrastructure in an urban catchment in Kozhikode, Kerala, a high-rainfall region in southwestern India. This study measured the effectiveness of green infrastructure by assessing its ability to decrease peak runoff. The findings indicate that using an optimal combination of green infrastructure components leads to significant reductions in runoff peaks. Specifically, the study reveals that by using 50% of the available land, the optimal combination achieves reductions of 23% for a 2-year return period, 21.6% for a 10-year return period, 9.48% for a 50-year return period, and 6.15% for a 100-year return period rainfall event. Furthermore, spatial analysis suggests that focusing near the northwestern portion of the catchment, rather than dispersing green infrastructure throughout, can lead to a greater reduction in flood volume with 26% and 14% during rainfall events with return periods of 50 and 100 years, respectively. Applying green infrastructure to 25% of the total available land achieved this enhanced reduction. These findings provide valuable insights for decision makers, helping them identify optimal locations for installing green infrastructure and effectively manage urban flood risks by understanding its impact on various aspects of the urban water cycle.

A new tool for automatic calibration of the Storm Water Management Model (SWMM)

The Pan-Third Pole (PTP) region, which encompasses the Eurasian highlands and their surroundings, has experienced unprecedented, accelerated warming during the past decades. This study evaluates the performance of historical simulation runs of the Coupled Model Intercomparison Project (CMIP6) in capturing spatial patterns and temporal variations observed over the PTP region for mean and extreme temperatures. In addition, projected changes in temperatures under four Shared Socioeconomic Pathway (SSP) scenarios (SSP1‐2.6, SSP2‐4.5, SSP3-7.0, and SSP5‐8.5) are also reported. Four indices were used to characterize changes in temperature extremes: the annual maximum value of daily maximum temperature (TXx), the annual minimum value of daily minimum temperature (TNn), and indices for the percentage of warm days (TX90p) and warm nights (TN90p). Results indicate that most CMIP6 models generally capture the characteristics of the observed mean and extreme temperatures over the PTP region, but there still are slight cold biases in the Tibetan Plateau. Future changes of mean and extreme temperatures demonstrate that a strong increase will occur for the entire PTP region during the twenty-first century under all four SSP scenarios. Between 2015 and 2099, ensemble area-averaged annual mean temperatures are projected to increase by 1.24 °C/100 year, 3.28 °C/100 year, 5.57 °C/100 year, and 7.40 °C/100 year for the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, respectively. For TXx and TNn, the most intense warming is projected in Central Asia. The greatest number of projected TX90p and TN90p will occur in the Southeast Asia and Tibetan Plateau, respectively.

Abstract. Streams are natural features in urban landscapes that can provide ecosystem services for urban residents. However, urban streams are under increasing pressure caused by multiple anthropogenic impacts, including increases in human population and associated impervious surface area, and accelerated climate change. The ability to anticipate these changes and better understand their effects on streams is important for developing and implementing strategies to mitigate potentially negative effects. In this study, stream flow was monitored during April–November (2011 and 2012), and the data were used to apply the Storm Water Management Model (SWMM) for five urban watersheds in central Iowa, USA, representing a gradient of percent impervious surface (IS, ranging from 5.3 to 37.1%). A set of three scenarios was designed to quantify hydrological responses to independent and combined effects of climate change (18% increase in precipitation), and land cover change (absolute increases between 5.2 and 17.1%, based on separate projections of impervious surfaces for the five watersheds) for the year 2040 compared to a current condition simulation. An additional set of three scenarios examined stream response to different distributions of land cover change within a single watershed. Hydrological responses were quantified using three indices: unit-area peak discharge, flashiness (R-B Index; Richards–Baker Index), and runoff ratio. Stream hydrology was strongly affected by watershed percent IS. For the current condition simulation, values for all three indices were five to seven times greater in the most developed watershed compared to the least developed watershed. The climate change scenario caused a 20.8% increase in unit-area peak discharge on average across the five watersheds compared to the current condition simulation. The land cover change scenario resulted in large increases for all three indices: 49.5% for unit-area peak discharge, 39.3% for R-B Index, and 73.9% for runoff ratio, on average, for the five watersheds. The combined climate and land cover change scenario resulted in slight increases on average for R-B Index (43.7%) and runoff ratio (74.5%) compared to the land cover change scenario, and a substantial increase, on average, in unit area peak discharge (80.1%). The scenarios for different distributions of land cover change within one watershed resulted in changes for all three indices, with an 18.4% increase in unit-area peak discharge for the midstream scenario, and 17.5% (downstream) and 18.1% (midstream) increases in R-B Index, indicating sensitivity to the location of potential additions of IS within a watershed. Given the likelihood of increased precipitation in the future, land use planning and policy tools that limit expansion of impervious surfaces (e.g. by substituting pervious surfaces) or mitigate against their impacts (e.g. by installing bioswales) could be used to minimize negative effects on streams.

The global water cycle has undergone considerable changes since pre-industrial times due to global climate change and land-use changes. These drivers will almost certainly continue to change during the course of this century. However, where, how, and to which extent terrestrial moisture recycling will change as a result remains unclear.Mutually consistent scenarios of climate change and land-use changes for the 21st century are provided by the Shared Socioeconomic Pathways (SSPs). The SSPs provide a framework of five different narratives involving varying degrees of challenges associated with mitigation or adaptation. From each narrative follow different implications for emissions, energy, and land use. The SSPs serve as the conceptual framework behind the sixth generation of the Coupled Model Intercomparison Project, CMIP6.Terrestrial moisture recycling is often assessed using atmospheric moisture tracking models. An example is UTrack, a Lagrangian model to track moisture through three-dimensional space. Here we present a new forward-tracking version of UTrack that is forced by output of a CMIP6 model to study how terrestrial moisture recycling may change across the globe until the end of the  21st century in a range of SSPs, from mild to severe: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. For this forcing, we chose the Norwegian Earth System Model version 2, or NorESM2. It has a temporal resolution of one day and a spatial resolution of 1.25° × 0.9375° at eight pressure levels.We find that across the 21st century, the global terrestrial moisture recycling ratio decreases with the severity of the Shared Socioeconomic Pathways (SSPs). We calculate a decrease in global terrestrial precipitation recycling by 2.1% with every degree of global warming. Because the SSPs represent internally consistent scenarios of both global warming and global land cover changes, it is hard to distinguish the relative contributions of these two, but the evidence points at a major influence of global warming on moisture recycling.We find spatial differences in trends in recycling ratios, but which are broadly consistent among SSPs. If a change in precipitation (either drying or wetting) coincides with an increase in terrestrial precipitation recycling ratio, we call it land-dominated. We call the change in precipitation ocean-dominated if it coincides with a decrease in terrestrial precipitation recycling ratio. Land dominance tends to occur in regions with already large terrestrial precipitation recycling ratios, mainly interior South America (land-dominated drying) and eastern Asia (land-dominated wetting). Land-dominated drying may also happen in eastern Europe, in central America and in subtropical sub-Saharan Africa. Ocean-dominance, mainly in the form of wetting, is found primarily in the high northern latitudes and in central Africa.We also simulated the changes in basin recycling for the 27 major river basins of the world, confirming the overall tendency of decreasing recycling with severity of the SSP, as well as its spatial variations.

The present work reviews the main challenges regarding adaptation of urban drainage networks to climate change by comparing 32 case studies from 29 articles, published between 2003 and 2020. The aim is to: (i) identify the state-of-the-art scientific approaches of adaptation of urban drainage networks to climate change; (ii) assess whether or not these approaches incorporated monetization of the adaptation practices and the associated costs/benefits; and (iii) define a novel approach (Blueprint) for the future development and assessment of urban drainage network adaptation to climate change and other drivers. First, the motivation is provided that makes urban drainage adaptation a globally relevant issue. Second, the main impacts of climate change on precipitation, flooding and urban drainage systems are discussed. Then, current practices are described. Finally, a blueprint for an integrated urban adaptation framework to climate change and other drivers is proposed. Our research indicated that future quantity and quality of urban runoff is not widely addressed in the scientific literature. The Storm Water Management Model is the most widely used software in modeling adaptation options. Solutions such as plans of maintenance and rehabilitation, public awareness, flood forecasting and warning, mobility measures and insurance measures are not widely reflected in the literature. Uncertainties of climate projections and bias correction methods are still significant, and uncertainties of socio-economic scenarios, hydrologic and hydrodynamic models, and adaptation options are not fully addressed. Finally, environmental cost and benefits associated with the ecosystem services provided by the adaptation options are not fully addressed.

Urban waterlogging occurred frequently in recent years, causing serious social harms and huge economic losses. Accurate waterlogging warning is important for disaster prevention and mitigation. Urban rainstorm waterlogging processing based on Geographic Information System (GIS) and Storm Water Management Model (SWMM) can provide prediction and management of flood situation, but the previous methods of catchments from a single aspect of hydrology or geometry cannot reflect the dual impact of pipe networks and terrain to drainage, and the available inundation algorithms achieved some unreasonable results due to the artificial boundaries. In this paper, a methodology for simple 2-D inundation analysis in urban area using SWMM and GIS is introduced, which need not edit SWMM’s original code. Furthermore, a geometric method of catchments division and inundation algorithm are proposed to improve accuracy. The revised catchments division method provides a good result of supplementing the drainage of terrain, and the improved inundation algorithm can obtain a reasonable inundation distribution based on the principle of source diffusion and dynamic distribution without any boundary limit. The case study was performed in Longwen District of Zhangzhou, and good results are achieved: (1) The external outflow percentage of the revise method is always bigger than that of the geometric method, and the value of the revised method is 25.18%, while that of geometric method is only 19.56% at rainfall peak, and (2) the less the rainfall is, the less grids flooded in two algorithms there are with only 14.30% when the rainfall is 0.1 mm.