Runoff Flow Research Articles

Experimental study of rainwater grate blocking and submergence of outfall on drainage network capacity

Accurately evaluating the performance of urban underground drainage network and its influencing factors is a challenging problem, as this process is affected by many complex factors. In this study, based on an overland flow experiment considering drainage process of pipe network, a series of physical model experiments were conducted to investigate the influences of different surface slopes, rainwater grate blockage and the submergence of outfall on the performance of the drainage pipe network system. The hydrographs of surface runoff and pipe network flow were recorded in collection tanks by precise digital pressure sensors to provide comprehensive information about the characteristics of drainage performance in the pipe network. Through a series of experimental data collection and analysis, the following conclusions are drawn from this study: (1) The longitudinal slope of the road decreases the pipe drainage capacity by 1.68%–8.94%, and this reduction effect is more significant with the increase of slope. (2) The blockage of rainwater grate at different locations has different impacts on the road drainage system, the downstream rainwater grate blockage has the most obvious impact on the performance of the drainage system, which reduces the drainage capacity by 22.59%–25.38%. (3) Different submergence degrees of rainwater outlet have different impacts on the drainage system. Under different slopes, the drainage capacity of the pipe network decreases by 1.88%–23.46% with the increase of the submergence degree of the outfall. These experimental results are helpful in understanding the working conditions of urban road drainage system and the influencing factors of the system's drainage capacity, and also provide measured data for verification of relevant numerical models and coefficient calibration.

Modeling run-off flow hydrographs using remote sensing data: an application to the Bashar basin, Iran

Abstract Precipitation is hard to access in countries like Iran, due to inadequate number of rain gauge stations. Remote sensing provides an alternative source of rainfall estimation. In this study, the effectiveness of the HEC-HMS model was evaluated using GPM (Global Precipitation Measurement Mission) satellite and rain gauge station data. The model was calibrated and validated using 5 flood events' data of a hydrometric station at the outlet of Bashar basin. Important flood parameters including peak discharge (QP), flood volume (V) and time of concentration (TC) were used to evaluate and compare the application of satellite and ground station data in the model, using various statistical indices. The accuracy of QP and V estimations using rain gauge data was higher than those obtained by satellite data. However, the difference between mean relative error (MRE) in QP estimation was about 1% (9.9% and 10.6% for rain gauge and satellite data, respectively). Conversely, higher accuracies were met for TC estimation using satellite (with MRE 9.1% and 10.2% for GPM and rain gauge data, respectively). Such results imply the sole utilization of satellite precipitation data is reliable for modeling hydrological key parameters, which can be helpful in areas with limited ground station coverage.

Soil water repellency along elevation gradients: The role of climate, land use and soil chemistry

The rate of water infiltration, surface runoff, and overland flow are all affected by soil water repellency (SWR), i.e., the reduced affinity for water caused by hydrophobic coatings on soil particles. SWR impacts water balance, which in turn affects ecosystem’s function and watersheds hydrology, but little is known about changes of these properties along elevation gradient. Here, we investigate variation in SWR along four elevation gradients in four Italian mountain peaks, encompassing different land use and vegetation types from Mediterranean to temperate and alpine ecosystems. A total of 240 soil samples were collected for 48 ecosystems, and SWR was determined using the molarity of an ethanol droplet test. Soil characteristics were assessed using texture, pH, organic matter content, and soil salinity. Climate data were obtained using WorldClim, and their relationship with SWR was examined. SWR showed a unimodal pattern along the four elevation levels and in all cases peaked at mid-elevations between 1000 and 2500 m a.s.l.. SWR was highest under coniferous and deciduous forests and lowest for arable and bare soil. Soil organic matter and pH were the main determinants of SWR, with a positive and negative correlation, respectively. As for climate, mean annual temperature showed a hump-shaped relationship with SWR. In detail, we found that soil was hydrophilic at the extremes of elevation gradient where mean annual temperatures are less than −3.4 °C for alpine bare soils and higher than 12.7 °C for arable soils. This study allowed us to show how land use, soil chemistry, and climate are related to SWR along an elevation gradient. Further research is needed to concretely evaluate the effect of SWR on erosion risk at the watershed scale in the context of climate change.

Assessing ammonium pollution and mitigation measures through a modified watershed non-point source model

Watershed water quality modeling is a valuable tool for managing ammonium (NH4+) pollution. However, simulating NH4+ pollution presents unique challenges due to the inherent instability of NH4+ in natural environment. This study modified the widely-used Soil and Water Assessment Tool (SWAT) model to simulate non-point source (NPS) NH4+ processes, specifically incorporating the simulation of land-to-water NH4+ delivery. The Jiulong River Watershed (JRW) is the study area, a coastal watershed in Southeast China with substantial sewage discharge, livestock farming, and fertilizer application. The results demonstrate that the modified model can effectively simulate the NPS NH4+ processes. It is recommended to use multiple sets of observations to calibrate NH4+ simulation to enhance model reliability. Despite constituting a minor proportion (5.6 %), point source inputs significantly contribute to NH4+ load at watershed outlet (32.4∼51.9 %), while NPS inputs contribute 15.3∼17.3 % of NH4+ loads. NH4+ primarily enters water through surface runoff and lateral flow, with negligible leaching. Average NH4+ land-to-water delivery rate is about 2.35 to 2.90 kg N/ha/a. High delivery rates mainly occur at agricultural areas. Notably, proposed NH4+ mitigation measures, including urban sewage treatment enhancement, livestock manure management improvement, and fertilizer application reduction, demonstrate potential to collectively reduce the NH4+ load at watershed outlet by 1/4 to 1/3 and significantly enhance water quality standard compliance frequency. Insights gained from modeling experience in the JRW offer valuable implications for NH4+ modeling and management in regions with similar climates and significant anthropogenic nitrogen inputs.

Application of SWAT Model for Assessment of Surface Runoff in Flash Flood Areas

In addition to changes in the amount of rain, changes in land use upstream are considered a factor that directly affects the maximum runoff flow in a basin, especially in areas that have experienced floods and flash floods. This research article presents the application of the SWAT model to assess runoff in areas that have experienced flash floods, in order to analyze the proportion of land use change to the maximum runoff. Study areas that experienced flash floods were in three basins in Thailand (Lam Saphung Basin, Phrom River Basin, and Chern River Basin Part 1, which is a sub-basin of the Nam Chi River Basin). This study analyzed two main factors that influenced runoff in the river basin by considering two simulation situations: (1) changes in land use affecting runoff assessed by considering land use maps in 2006, 2008, 2010, 2015, 2017, 2019, and 2021 when using rainfall data only in the year 2021 for all cases and (2) changes in the amount of rainfall influencing runoff by considering the rainfall records in 2006, 2008, 2010, 2015, 2017, 2019, and 2021 when using the land use data only in the year 2021 for all cases. The results of the study found that the SWAT model can be effectively applied to estimate annual runoff in areas that have experienced flash floods under eight parameters with R2 values of 0.74, 0.82, and 0.74 for the Lam Saphung River Basin, Phrom River Basin, and Chern River Basin Part 1, respectively. In addition, it was found that the proportion of land use changes that involved changes from forested areas to residential areas was the greatest from 2008 to 2010 in the Phrom River Basin and Chern River Basin Part 1. This resulted in an increase in the maximum runoff amounts of 77.78% and 46.87%, respectively. When land use was constant, it was found that the rainfall in 2010, which was the highest, also had the greatest impact on the runoff in all three areas.

Using Machine Learning to Identify and Optimize Sensitive Parameters in Urban Flood Model Considering Subsurface Characteristics

This study presents a novel method for optimizing parameters in urban flood models, aiming to address the tedious and complex issues associated with parameter optimization. First, a coupled one-dimensional pipe network runoff model and a two-dimensional surface runoff model were integrated to construct an interpretable urban flood model. Next, a principle for dividing urban hydrological response units was introduced, incorporating surface attribute features. The K-means algorithm was used to explore the clustering patterns of the uncertain parameters in the model, and an artificial neural network (ANN) was employed to identify the sensitive parameters. Finally, a genetic algorithm (GA) was used to calibrate the parameter thresholds of the sub-catchment units in different urban land-use zones within the flood model. The results demonstrate that the parameter optimization method based on K-means-ANN-GA achieved an average Nash-Sutcliffe efficiency coefficient (NSE) of 0.81. Compared to the ANN-GA and K-means-deep neural networks (DNN) methods, the proposed method better characterizes the runoff generation and flow processes. This study demonstrates the significant potential of combining machine learning techniques with physical knowledge in parameter optimization research for flood models.

Precipitation-dependent sensitivity of suspended sediment concentration to turbidity in a mountainous river in southwestern China

Suspended sediment concentration (SSC) has been used as a key indicator in various environmental studies concerning, for example, ecological integrity, river morphology, aquatic and riverine biota, and the management of river and reservoir systems. River turbidity has been widely used as a proxy indicator of SSC. However, the relationship between the two parameters varies considerably under different conditions. The present study investigated the relationships between SSC and turbidity under different rainfall conditions in the Baisha River, a mountainous river located in southwestern China. Data were continuously collected on site from 2015 to 2021. The results showed a significant positive correlation between SSC and turbidity, with the median slope model exhibiting the best linear fit. In addition, the linear regression slopes varied significantly between different seasons and rainfall intensities in the following descending orders: dry season (1.05) > rainy season (0.97), no rainfall (1.14) > non-erosive rainfall (0.99) > erosive rainfall (0.95), and mild rainfall (1.05) > moderate rainfall (0.97) > heavy rainfall (0.93) > rainstorm (0.89). Overall, during the rainy season and under higher rainfall intensities, the regression slope was gentler. This study discussed the mechanisms through which rainfall conditions affected the SSC-turbidity relationship. It was shown that such a relationship was generally influenced by sediment transport in the runoff and river water flow flux, and the number of suspended particles as well as their size were considered as main factors. The results of this study revealed the impact of rainfall conditions on the SSC-turbidity relationship and provided a reference for the rapid assessment of the suspended sediment load in mountain river basins at high altitudes. In addition, based on the results obtained, it is expected that a new method for predicting event-based soil erosion can be applied in similar high-altitude mountain valleys.

A fuzzy TOPSIS-based approach for prioritizing low-impact development methods in high-density residential areas.

The study successfully implemented six low-impact development (LID) methods to manage surface runoff in urban areas: green roof, infiltration trench, bio retention cell, rain barrel, green roof combined with infiltration trench, and rain barrel combined with bio-retention cell. Each method has unique benefits in mitigating surface runoff effects in urban environments. The following four indicators were used to evaluate the methods: runoff volume reduction, peak runoff flow rate reduction, economic sustainability, and social sustainability. The study, which lasted approximately 4 months, was conducted in an eastern Tehran metropolis residential area with a mix of old and new buildings. The SWMM model determined runoff volume and peak flow values, and a price analysis list determined the economic index. Local experts completed 25 questionnaires to evaluate the social index. Fuzzy TOPSIS multi-indicator decision criteria were used to prioritize LID methods, and the Rain barrel + Bio retention cell combined scenario emerged as the best option based on all four criteria. The method reduced peak runoff flow by 23.1-66.1% under rainfall with 10-year return periods. The green roof + infiltration trench method had the highest percentage reduction of 2,737 m3, while the infiltration trench had the lowest reduction of 273 m3.

Comprehensive investigation of flood-resilient neighborhoods: the case of Adama City, Ethiopia

Adama is the second most populous city in Ethiopia and experiences frequent flash floods that have a detrimental impact on the community’s livelihood. To this effect, this study emphasizes the significance of conducting a comprehensive investigation to identify flood-resilient neighborhoods in Adama City. By considering the existing spatial pattern and morphology that are resilient to urban flooding, the city can enhance its flood management strategies in the future. The findings of this study demonstrate varying levels of spatial connectivity within Adama City. Detailed examination of two neighborhoods identified through space syntax analysis with high and low spatial connectivity revealed important insights into flood resilience. The high-connective neighborhoods exhibited well-interconnected street systems with manageable street spacing, facilitating efficient runoff flow and effective flood management during flooding events. These neighborhoods also had shorter block sizes with frequent intersections, promoting better water drainage and reducing the risk of flooding during heavy rain events. The grid pattern observed in these areas allowed for efficient water runoff through multiple drainage paths, including the street surfaces. On the contrary, neighborhoods with low spatial connectivity exacerbated urban flooding. The lack of connectivity and abundance of dead-end streets posed challenges for flood evacuation during emergencies. Irregular block arrangements disrupted the natural drainage system, aggravating the potential for urban flooding. These findings have implications for other flood-prone areas of neighborhoods in Adama City and similar urban areas in the global south on how human settlements are arranged spatially to mitigate urban flood vulnerability.

Parameters Cp and Ct in Snyder Synthetic Unit Hydrograph Due to Land Use Changes in Napel Sub-watershed, Bengawan Watershed

The parameters Cp and Ct depend on the characteristics and slope of the watershed. Watershed characteristics include types of land use that are always dynamic over time. The slope of the watershed affects the smoothness and velocity of runoff flow. The development of an area will cause changes in land use which tend to become more impermeable, of course also affecting the smoothness and speed of runoff flow. This of course results in changes in Cp and Ct in a watershed. Changes in land use in the Napel watershed within 7 years starting from 2015 to 2021 have decreased in areas of jungle forest and other water catchment areas. This research was conducted to determine the influence of land use change on peak discharge and Cp and Ct parameters. The method used is the Snyder Synthetic Unit Hydrograph, which has been tested for suitability against the Measured Unit Hydrograph with validation results included in the very strong correlation category. The Ct value used in 2015 was 1.65 and in 2021 it was 0.78 while the Cp value used in 2015 was 1.4 and in 2021 it was 1.1. The results of the analysis using the Snyder method produced a discharge of 417.882 m3/s in 2015 and 619.52 m3/s in 2021. The resulting discharge shows a significant increase.

Urban Resilience through Green Roofing: A Literature Review on Dual Environmental Benefits

Urban areas face significant environmental challenges, notably rainwater management and the urban heat island effect. As sustainable ecological infrastructures, Green roofs provide dual benefits in addressing these issues. The literature review thoroughly explores how effective green roofs are at boosting urban resilience by mitigating Urban Heat Island effects and enhancing stormwater control. Findings across various studies indicate that green roofs could significantly reduce surface and ambient temperatures, with some studies reporting surface temperature reductions of up to 30 °C. Additionally, green roofs contribute to stormwater management by retaining at lseast 51% of annual rainfall, thereby reducing runoff volume and peak flow rates. By synthesizing data from 28 case studies worldwide, this review highlights the substantial environmental benefits green roofs offer in urban settings. Our analysis suggests that broader implementation and further research into green roof technologies are essential for sustainable urban development. This paper calls for increased integration of green roofs into urban planning to leverage their environmental benefits, particularly in mitigating climate change impacts and enhancing urban ecological systems.

Inconsistent using FLOOD and Flooding Development of EPA SWMM for Assessing Flood Occurrences in Vulnerable Urban Watershed Considering Extreme Rainfall Events

Urban flood, commonly known as urban water congestion, is a type of water hazard that poses significant challenges for urban residents and water management experts. Chittagong, an essential economic hub in Bangladesh, renowned for its role as a port city, comprises a diverse range of land use, including residential, industrial, and commercial sectors. The Chaktai canal, an important element of Chittagong drainage system, is connected to the Karnaphuli river, playing a vital role in managing drainage by handling a substantial portion of the city water. Therefore, this research evaluated the operational efficiency of a specific drainage network under the influence of altered rainfall events using the Storm Water Management Model (SWMM). Using ArcGIS 10.4, the land use pattern of the area was researched, incorporating data from field surveys and secondary sources. SWMM 5.1 integrated watershed data, and further simulation was carried out to estimate runoff in various sub-catchments and drainage network limitations during heavy rain. During the intense monsoon period, the tool determined the average runoff depth, considering backwater effects and robust tidal surges, resulting in a depth of 3.3m compared to 2.6m in the dry season. This research evaluated the influence of impervious land use changes on urban drainage systems. While meteorological factors alone render drainage network sufficient in dry periods, the outfall shows vulnerability during the rainy season, with an allowance of only 0.7m, jeopardizing the catchment through flood. It contributed a schematic sub-catchment representation, emphasizing that flood events depend on volume runoff and peak flow in urban drainage system. SWMM model was used to illustrate the catchment surface runoff and interconnected node depths via conduits, as well as the current catchment scenario comprehensively.

The Implementation of Resilience Engineering to Deal with Climate Change Impact

Climate change is a very interesting subject, because it has been compelling us to review our thinking, our development concepts, practices, paradigms, models, and so on from the view of the environment. In such introspections, we may identify the mistakes, weaknesses and unintended consequences of our development concepts, practices; and we may try to overcome those mistakes and will be conscious to avoid such shortcomings in the future. Land and water resources degradation are the major problems in the world. Poor land use practices and improper management systems have played a significant role in causing high soil erosion rates, sediment transport, and loss of agricultural nutrients. This causes various effects on resource bases like deforestation, expansion of residential areas, and agricultural land. The watershed is also facing high erosion due to the effects of intense rainfall of the watershed which aggravates the land cover change of the watershed. This continuous change in land cover has influenced the water balance of the watershed by changing the magnitude and pattern of the components of stream flow between surface runoff and groundwater flow in increasing the extent of the water management problem. In this study, the assessments of resilience engineering and its function as a framework for the environmental issues, such as resilience and management of water and public infrastructure has been done. After risk assessment, we obtained five risk levels and their corresponding resilience levels. The two can be regarded as negatively correlated. And at the same time, four corresponding adaptions are also proposed according to the resilience levels.

Calculation of Proper Time of Concentration for Drainage Design in Construction Projects for Urban Development

The design and construction of a proper drainage system are important for any urban development project, small or big. Hydrological and hydraulic calculations are used to design the drainage systems. The calculation of peak flow is one of the common hydrological methods applied to determine the drain sizes for all construction projects. Peak flows and hydrographs can be calculated using several techniques. In order to calculate the peak flow, the design rainfall duration has to be appropriate, which will reflect the critical storm duration. The critical storm duration, on the other hand, depends on the time of concentration (tc) of the catchment. However, most of the equations for tc available in the literature are empirical. At least 23 equations could be traced in various references, which consist of different geophysical and other hydrological parameters. This paper is intended to explain the importance of the proper use of tc to calculate peak runoff flow for construction projects, as accurately as possible. A review of the existing methods used to calculate the time of concentration revealed inconsistencies among a few methods found in the literature. The correct value of the time of concentration (tc) is important for the application of the Rational Method, as the value of tc helps the designer assume the storm duration critical to get the maximum peak flow value. If the critical storm duration is not used in the Rational Method, the drain will be undersized, and the overflow of the storm runoff may happen. Therefore, ample attention should be given to the calculation of the time of concentration to ensure the safety, economy, and sustainability of the drainage system in any development project.

Effect of landscape irrigation regulations on runoff volume from low-density residential catchments during two California droughts

The severe drought in California (2012–2016) generated significant public and government concern. State and local watering regulations were enacted to reduce residential and commercial water-use during the droughts. This study presents a comparison of residential runoff volumes before and after local landscape irrigation regulations were enacted during the droughts of 2008 and 2012–2016. Each sampling site (Folsom 1 and Folsom 2) was a storm drain outfall that drained a low-density residential catchment in the City of Folsom. Dry season runoff measured at the sampling sites represents neighborhood outdoor water waste, mainly from landscape irrigation. During the drought of 2012–2016, median runoff flows were significantly reduced after local landscape irrigation regulations were enacted. The daily runoff pattern was also highly influenced by regulation, with reductions of daily peak runoff flows on 4–5 days in a week after watering regulations were enacted. The number of peak flow events in the daily runoff pattern were reduced during this period. In addition, a significant reduction in mean runoff volume occurred. Based on these results, the watering regulations enacted by the City of Folsom had a positive effect on reducing urban runoff from residential neighborhoods during the dry season. As the results are from monitoring sites in a relatively small geographical area, further work should evaluate reductions in irrigation runoff from other California locations to determine if this is a localized phenomenon.

Rock surface flow accelerates rill erosion of excavated slopes in karst mining areas

Rock surface flow is the secondary distribution of precipitation and inflow on the rock surface, an essential runoff generation mode in karst areas. The effects of rock surface flow on soil erosion in karst regions cannot be ignored. However, its impact on rill erosion in karst slopes remains unclear. The objectives of this study were to investigate the impact of rock surface flow on rill erosion, rill morphological characteristics, rill flow hydraulic characteristics, and hydrodynamic mechanisms. A field runoff plot (3 m long, 1 m wide and 0.3 m deep) with three inflow rates (2, 3, and 4 L/min) was subjected to runoff simulation experiments under two typical rock surface morphologies in karst areas: smooth rock surface (SRS) and karren rock surface (KRS), with bare slope (BS) as the control group. The results revealed that rock surface flow aggravated the soil and water loss of the excavated slope. Compared to BS, the runoff yield for SRS and KRS increased by 81.49 % and 61.91 %, respectively. Meanwhile, the soil loss of SRS and KRS were 2.50 times and 5.56 times greater. The rills below the rock outcrops didn’t develop into a rill network after formation, owing to the rock surface morphology. Rill depth was the best indicator of rill morphology for evaluating rill erosion on slopes below rock outcrops. The Reynolds number and Darcy–Weisbach resistance coefficient were the optimal hydraulic parameters to predict the rill erosion of the SRS and KRS, respectively. At the same time, the runoff power and flow shear stress were the best hydrodynamic parameters to describe the rill erosion mechanism of SRS and KRS. These results provide a scientific basis for further understanding the mechanism of soil erosion on karst slopes and for preventing soil erosion on karst slopes in mining areas.

Evaluation of Drainage Network System (Case Study of Pangkajene Kepulauan State Agricultural Polytechnic Campus Area)

The purpose of this research is to identify the condition of highway drainage channels and evaluate the existing highway drainage network system in accommodating runoff discharge, channel dimensions and flow direction in channels that occur inundation in the Pangkajene Islands State Agricultural Polytechnic Campus area which is expected to help solve flooding problems in the area. The research method used is descriptive quantitative, which is a method of calculation and description of the results of field data processing. Secondary data collection includes; rainfall data for the last 10 years, obtained from the Department of Resources; topographic maps, drainage network maps and situation maps, obtained from the Politani Pangkep Campus planning section. Primary data collection is obtained from direct measurements in the field using a Waterpass measuring instrument to measure elevation and channel length. The results of this study found that the drainage capacity < 2-year and 5-year return period Plan Flood Discharge, so planning is needed to increase drainage capacity

Linking elevated rainfall with sewage discharge volume

Abstract The intricate hydrological processes elucidating the interplay between rainfall and flow manifest through rainwater's traversal along diverse routes, encompassing surface runoff and subsurface flow. While the foundational association between these entities is discernible, the convoluted intricacies characterizing this correlation defy straightforward comprehension. Examining the data between 2019 and 2022, the average daily sewage outflow was 12,518 m3/d, with occasional peaks of up to 50,440 m3/d. The wastewater treatment plant's capacity of 35,000 m3/d was usually not exceeded. Overall, average daily sewage outflows varied between 11,716 m3/d and 13,969 m3/d during the studied period. Comprehending this interrelationship holds pivotal significance for the optimization of water-resource-management strategies. A moderate correlation (r = 0.42) between daily rainfall levels and sewage discharge was found in the dataset covering 2018–2023. When categorizing daily rainfall into groups labelled “A” through “G” and comparing them to sewage flows, a pattern emerged: Rain-free days in group “A” had the lowest average sewage flow (10,996 m3/d), while heavy rain days in group “G”, had the highest average flow (22,112 m3/d). This observation underscores a significant correlation between intensified rainfall and increased volume of sewage discharge. Through a comprehensive analysis of factors such as sewage composition, meteorological dynamics and chronological sequences, we will gain an enhanced ability to prognosticate and govern sewage systems. The significance of this is heightened within the context of evolving climatic dynamics.

Green roof infrastructure outperforms grey technology in flood mitigation in São Paulo’s urbanized region

São Paulo City, Brazil, a densely urbanized area in a tropical climate region, is facing increasing challenges from flooding. However, a promising solution has emerged in the form of Nature-Based Solutions (NBS) infrastructure, surpassing traditional grey technology in flood mitigation. This article examines the effectiveness of green roofs in reducing flood risks and highlights their superiority over conventional approaches. We analyzed the direct impacts of surface permeabilization in public areas (sidewalks, streets, and squares) and private areas (urban lots, subdivisions) on runoff volume and peak flow in the Aricanduva River basin in São Paulo city. We used a thoroughly validated hydrological model to compare the interference in the land use of the watershed between a green infrastructure type called Green Roof (GR) and a gray technology called Permeable Pavement (PP), in terms of hydrological efficiency in mitigating floods. The flow and water level simulations for varying areas with GR or PP covered a wide range, allowing for situations above or below the canal overflow level, which provided a good distinction of the impact of boundary conditions. Overall, we observed a positive hydrological response, with a reduction in peak flow and runoff volume proportional to the increase in permeable area, and consequently, proportional to the increase in GR or PP surface within the contributing area. As the main contribution, the hydrological performance calculated with the variation of GR was remarkably superior to the variation of PP in terms of requiring a smaller coverage area with interference to prevent overflow or achieve equivalent efficiency. It is worth noting that the substitution of approximately 24% of the gray roof area with GR prevented canal overflow, which is notably lower than the required substitution of approximately 40% for PP interference. We reinforce the relevance of green roofs as an option to mitigate intense hydrological effects in urban areas and, more importantly, paves the way for other NBS with the same hydrological principles and environmental co-benefits to work individually or in combination.

Re-Engineering Dew-Harvesting Cactus Macrostructures to Enhance Water Collection as an Adaptive Climate Change Strategy: An Experimental Comparison

The spinal structures found on Copiapoa cinerea var. haseltoniana, an efficient dew-harvesting cactus, were fabricated and evaluated both in a climate chamber and outdoors in dewy conditions. A mix of aluminium and steel was used to fabricate these surfaces, with aluminium being used for everything but the replicated spine features, which were constructed from steel. Each surface was entirely coated with a highly emissive paint containing an alumina–silicate OPUR additive. Three replica versions (stem only, spine only, and stem & spine) were compared to a flat planar reference surface. Experimental results demonstrated that all three biomimetic macro-structured surfaces significantly enhanced dew harvesting compared to the reference surface. It was established that the stem & spine replica, spine replica, and stem replica all demonstrated significantly more dew harvesting, with mean efficiency ratios in respect of the reference surface of 1.08 ± 0.03, 1.08 ± 0.02, and 1.02 ± 0.01, respectively. Furthermore, the method of surface water collection was found to influence the water collection rate. The diagonal run-off flow across a flat planar surface was 34% more efficient than the parallel run-off flow on the same surface. These findings provide valuable insights for the construction and installation of biomimetic-inspired dew-harvesting devices, particularly in regions that are most challenged by decreasing dew yields as a result of climate change.