scholarly journals Assessing the Feasibility of a Cloud-Based, Spatially Distributed Modeling Approach for Tracking Green Stormwater Infrastructure Runoff Reductions

Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 255
Author(s):  
Gary Conley ◽  
Nicole Beck ◽  
Catherine Riihimaki ◽  
Krista McDonald ◽  
Michelle Tanner
Keyword(s):  
Spatial Data ◽  
Program Effectiveness ◽  
Urban Runoff ◽  
Integrated Approach ◽  
Regulatory Compliance ◽  
Annual Runoff ◽  
Catchment Scale ◽  
Design Storm ◽  
Runoff Reduction ◽  
Green Stormwater Infrastructure

Use of green stormwater infrastructure (GSI) to mitigate urban runoff impacts has grown substantially in recent decades, but municipalities often lack an integrated approach to prioritize areas for implementation, demonstrate compelling evidence of catchment-scale improvements, and communicate stormwater program effectiveness. We present a method for quantifying runoff reduction benefits associated with distributed GSI that is designed to align with the spatial scale of information required by urban stormwater implementation. The model was driven by a probabilistic representation of rainfall events to estimate annual runoff and reductions associated with distributed GSI for various design storm levels. Raster-based calculations provide estimates on a 30-m grid, preserving unique combinations of drainage factors that drive runoff production, hydrologic storage, and infiltration benefits of GSI. The model showed strong correspondence with aggregated continuous runoff data from a set of urbanized catchments in Salinas, California, USA, over a three-year monitoring period and output sensitivity to the storm drain network inputs. Because the model runs through a web browser and the parameterization is based on readily available spatial data, it is suitable for nonmodeling experts to rapidly update GSI features, compare alternative implementation scenarios, track progress toward urban runoff reduction goals, and demonstrate regulatory compliance.

scholarly journals Highly Resolved Rainfall-Runoff Simulation of Retrofitted Green Stormwater Infrastructure at the Micro-Watershed Scale

Land ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 339 ◽  
Author(s):  
Sami Towsif Khan ◽  
Fernando Chapa ◽  
Jochen Hack
Keyword(s):  
High Resolution ◽  
Spatial Data ◽  
Surface Runoff ◽  
Spatial Databases ◽  
Google Earth ◽  
Urban Land Use ◽  
Small Scale ◽  
Runoff Reduction ◽  
Intense Storm ◽  
Green Stormwater Infrastructure

Green Stormwater Infrastructure (GSI), a sustainable engineering design approach for managing urban stormwater runoff, has long been recommended as an alternative to conventional conveyance-based stormwater management strategies to mitigate the adverse impact of sprawling urbanization. Hydrological and hydraulic simulations of small-scale GSI measures in densely urbanized micro watersheds require high-resolution spatial databases of urban land use, stormwater structures, and topography. This study presents a highly resolved Storm Water Management Model developed under considerable spatial data constraints. It evaluates the cumulative effect of the implementation of dispersed, retrofitted, small-scale GSI measures in a heavily urbanized micro watershed of Costa Rica. Our methodology includes a high-resolution digital elevation model based on Google Earth information, the accuracy of which was sufficient to determine flow patterns and slopes, as well as to approximate the underground stormwater structures. The model produced satisfactory results in event-based calibration and validation, which ensured the reliability of the data collection procedure. Simulating the implementation of GSI shows that dispersed, retrofitted, small-scale measures could significantly reduce impermeable surface runoff (peak runoff reduction up to 40%) during frequent, less intense storm events and delay peak surface runoff by 5–10 min. The presented approach can benefit stormwater practitioners and modelers conducting small scale hydrological simulation under spatial data constraint.

scholarly journals Highly Resolved Rainfall-Runoff Simulation of Retrofitted Green Stormwater Infrastructure at the Micro-Watershed Scale

2020 ◽  
Author(s):  
Sami Towsif Khan ◽  
Fernando Chapa ◽  
Jochen Hack
Keyword(s):  
High Resolution ◽  
Spatial Data ◽  
Surface Runoff ◽  
Spatial Databases ◽  
Google Earth ◽  
Urban Land Use ◽  
Small Scale ◽  
Runoff Reduction ◽  
Intense Storm ◽  
Green Stormwater Infrastructure

Green Stormwater Infrastructure (GSI), a sustainable engineering design approach for managing urban stormwater runoff, has long been recommended as an alternative to conventional conveyance-based stormwater management strategies to mitigate the adverse impact of sprawling urbanization. Hydrological and hydraulic simulations of small-scale GSI measures in densely urbanized micro watersheds require high-resolution spatial databases of urban land use, stormwater structures, and topography. This study presents a highly resolved Storm Water Management Model developed under considerable spatial data constraints. It evaluates the cumulative effect of the implementation of dispersed, retrofitted, small-scale GSI measures in a heavily urbanized micro watershed of Costa Rica. Our methodology includes a high-resolution digital elevation model based on Google Earth information, whose accuracy was sufficient to determine flow patterns and slopes, as well as to approximate the subsurface stormwater structures. The model produced satisfactory results in event-based calibration and validation, which ensured the reliability of the data collection procedure. Simulating the implementation of GSI shows that dispersed, retrofitted, small-scale measures could significantly reduce impermeable surface runoff (peak runoff reduction up to 40%) during frequent, less intense storm events and delay peak surface runoff 5-10 minutes. The presented approach can benefit stormwater practitioners and modelers conducting small scale hydrological simulation under spatial data constraint.

Large-Scale Application of Biofiltration Swale Runoff Management Practices

2007 ◽  
Vol 2 (2) ◽  
Author(s):  
William C. Lucas
Keyword(s):  
Large Scale ◽  
Management Practices ◽  
Peak Flow ◽  
Low Impact Development ◽  
Urban Runoff ◽  
Management Model ◽  
Check Dams ◽  
Runoff Reduction ◽  
Impervious Area ◽  
Hydrologic Responses

Retaining rainfall where it lands is a fundamental benefit of Low Impact Development (LID). The Delaware Urban Runoff Management Model (DURMM) was developed to address the benefits of LID design. DURMM explicitly addresses the benefits of impervious area disconnection as well as swale flow routing that responds to flow retardance changes. Biofiltration swales are an effective LID BMP for treating urban runoff. By adding check dams, the detention storage provided can also reduce peak rates. This presentation explores how the DURMM runoff reduction approach can be integrated with detention routing procedures to project runoff volume and peak flow reductions provided by BMP facilities. This approach has been applied to a 1,200 unit project on 360 hectares located in Delaware, USA. Over 5 km of biofiltration swales have been designed, many of which have stone check dams placed every 30 to 35 meters to provide detention storage. The engineering involved in the design of such facilities uses hydrologic modeling based upon TR-20 routines, as adapted by the DURMM model. The hydraulic approach includes routing of flows through the check dams. This presentation summarizes the hydrological network, presents the hydrologic responses, along with selected hydrographs to demonstrate the potential of design approach.

scholarly journals Dominant climatic factors driving annual runoff changes at the catchment scale across China

2016 ◽  
Vol 20 (7) ◽  
pp. 2573-2587 ◽  
Author(s):  
Zhongwei Huang ◽  
Hanbo Yang ◽  
Dawen Yang
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Climate Changes ◽  
Climatic Factors ◽  
Southern China ◽  
Resource Planning ◽  
Annual Runoff ◽  
Net Radiation ◽  
Catchment Scale ◽  
The Impact

Abstract. With global climate changes intensifying, the hydrological response to climate changes has attracted more attention. It is beneficial not only for hydrology and ecology but also for water resource planning and management to understand the impact of climate change on runoff. In addition, there are large spatial variations in climate type and geographic characteristics across China. To gain a better understanding of the spatial variation of the response of runoff to changes in climatic factors and to detect the dominant climatic factors driving changes in annual runoff, we chose the climate elasticity method proposed by Yang and Yang (2011). It is shown that, in most catchments of China, increasing air temperature and relative humidity have negative impacts on runoff, while declining net radiation and wind speed have positive impacts on runoff, which slow the overall decline in runoff. The dominant climatic factors driving annual runoff are precipitation in most parts of China, net radiation mainly in some catchments of southern China, air temperature and wind speed mainly in some catchments in northern China.

Modelling the influence of irrigation abstractions on Scotland’s water resources

2003 ◽  
Vol 48 (10) ◽  
pp. 127-134 ◽  
Author(s):  
S.M. Dunn ◽  
N. Chalmers ◽  
M. Stalham ◽  
A. Lilly ◽  
B. Crabtree ◽  
...  
Keyword(s):  
Spatial Data ◽  
East Coast ◽  
Climatic Conditions ◽  
Balance Model ◽  
Catchment Scale ◽  
European Water ◽  
Irrigation Control ◽  
The Difference ◽  
Potato Crops ◽  
Modelling Approach

Legislation to control abstraction of water in Scotland is limited and for purposes such as irrigation there are no restrictions in place over most of the country. This situation is set to change with implementation of the European Water Framework Directive. As a first step towards the development of appropriate policy for irrigation control there is a need to assess the current scale of irrigation practices in Scotland. This paper presents a modelling approach that has been used to quantify spatially the volume of water abstractions across the country for irrigation of potato crops under typical climatic conditions. A water balance model was developed to calculate soil moisture deficits and identify the potential need for irrigation. The results were then combined with spatial data on potato cropping and integrated to the sub-catchment scale to identify the river systems most at risk from over-abstraction. The results highlight that the areas that have greatest need for irrigation of potatoes are all concentrated in the central east-coast area of Scotland. The difference between irrigation demand in wet and dry years is very significant, although spatial patterns of the distribution are similar.

scholarly journals Configuring Green Infrastructure for Urban Runoff and Pollutant Reduction Using an Optimal Number of Units

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1528 ◽  
Author(s):  
Carlos Martínez ◽  
Arlex Sanchez ◽  
Roberto Galindo ◽  
Aelaf Mulugeta ◽  
Zoran Vojinovic ◽  
...  
Keyword(s):  
Green Infrastructure ◽  
Urban Runoff ◽  
Optimal Number ◽  
Volume Reduction ◽  
Pollution Load ◽  
Flood Volume ◽  
Runoff Reduction ◽  
Trade Offs ◽  
Load Peak ◽  
Peak Runoff

Green infrastructure (GI) has been regarded as an effective intervention for urban runoff reduction. Despite the growing interest in GI, the technical knowledge that is needed to demonstrate their advantages, cost, and performance in reducing runoff and pollutants is still under research. The present paper describes a framework that aims to obtain the optimal configuration of GI (i.e., the optimal number of units distributed within the catchment) for urban runoff reduction. The research includes an assessment of the performance of GI measures dealing with pollution load, peak runoff, and flood volume reduction. The methodological framework developed includes: (1) data input, (2) GI selection and placement, (3) hydraulic and water quality modelling, and (4) assessing optimal GI measures. The framework was applied in a highly urbanized catchment in Cali, Colombia. The results suggest that if the type of GI measure and its number of units are taken into account within the optimisation process, it is possible to achieve optimal solutions to reduce the proposed reduction objectives with a lower investment cost. In addition, the results also indicate a pollution load, peak runoff, and flood volume reduction for different return periods of at least 33%, 28%, and 60%, respectively. This approach could assist water managers and their stakeholders to assess the trade-offs between different GI.

scholarly journals A Quantity–Quality Model to Assess the Effects of Source Control Stormwater Management on Hydrology and Water Quality at the Catchment Scale

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1415 ◽  
Author(s):  
Abdul Razaq Rezaei ◽  
Zubaidah Ismail ◽  
Mohammad Hossein Niksokhan ◽  
Muhammad Amin Dayarian ◽  
Abu Hanipah Ramli ◽  
...  
Keyword(s):  
Water Quality ◽  
Best Management Practices ◽  
Urban Areas ◽  
Low Impact Development ◽  
Real Field ◽  
Rain Garden ◽  
Quality Model ◽  
Catchment Scale ◽  
Runoff Reduction ◽  
Peak Runoff

The vast development of urban areas has resulted in the increase of stormwater peak runoff and volume. Water quality has also been adversely affected. The best management practices (BMPs) and low impact development (LID) techniques could be applied to urban areas to mitigate these effects. A quantity–quality model was developed to simulate LID practices at the catchment scale using the US Environmental Protection Agency Storm Water Management Model (US EPA SWMM). The purpose of the study was to investigate the impacts of LID techniques on hydrology and water quality. The study was performed in BUNUS catchment in Kuala Lumpur, Malaysia. This study applied vegetated swale and rain garden to assess the model performance at a catchment scale using real field data. The selected LIDs occupied 7% of each subcatchment (of which 40% was swale and 30% was rain garden). The LID removal efficiency was up to 40% and 62% for TN and TSS, respectively. The peak runoff reduction was up to 27% for the rainfall of up to 70 mm, and up to 19% for the rainfall of between 70 and 90 mm, respectively. For the longer storm events of higher than 90 mm the results were not as satisfactory as expected. The model was more effective in peak runoff reduction during the shorter rainfall events. As for the water quality, it was satisfactory in all selected rainfall scenarios.

scholarly journals Study on the Variation of Annual Runoff and Influencing Factors in Kuye River during the Past 60 Years

2018 ◽  
Vol 7 (2) ◽  
pp. 72
Author(s):  
Zhihua MA ◽  
Qiaoling GUO ◽  
Ning SU
Keyword(s):  
Human Activities ◽  
Large Scale ◽  
High Strength ◽  
Annual Runoff ◽  
Runoff Variation ◽  
Runoff Reduction ◽  
Filter Methods ◽  
Runoff Series ◽  
Concentration Degree ◽  
The Impact

In this study, observed runoff series from a hydro-station respectively named Wenjiachuan station in the Kuye river was manipulated for monthly annual variation analysis assisted by using nonuniformity coefficient and concentration degree(period).the cumulative filter methods was employed to detect the trend of inner-annual runoff. Based on meteorological and hydrological data of the Wenjiachuan hydrologic station from 1955 to 2015, the paper studied the variation tendency, the abrupt and periodic changes of annual runoff using the Mann-Kendall non-parametric test and accumulation anomaly curve. Double mass curve was used to estimate the impact of human activities and climate change on the runoff variation. The curve of seasonal runoff distribution for Wenjiachuan station appeared two peak patterns. The annual runoff declined markedly, the effect of climate on runoff decreased, the influence of human activities on runoff gradually increased the human activities are the primary factors leading to the reduction of annual runoff. In human activities, large-scale water and soil conservation measures and high-strength coal mining have produced significant effects on the annual runoff reduction in Kuye River.

scholarly journals A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models

2010 ◽  
Vol 7 (5) ◽  
pp. 7191-7229 ◽  
Author(s):  
S. N. Gosling ◽  
R. G. Taylor ◽  
N. W. Arnell ◽  
M. C. Todd
Keyword(s):  
Climate Change ◽  
Hydrological Model ◽  
Climate Model ◽  
Annual Runoff ◽  
Structural Uncertainty ◽  
Hydrological Models ◽  
Catchment Scale ◽  
Monthly Runoff ◽  
Global Mean ◽  
Impacts Of Climate Change

Abstract. We present a comparative analysis of projected impacts of climate change on river runoff from two types of distributed hydrological model, a global hydrological model (GHM) and catchment-scale hydrological models (CHM). Analyses are conducted for six catchments that are global in coverage and feature strong contrasts in spatial scale as well as climatic and developmental conditions. These include the Liard (Canada), Mekong (SE Asia), Okavango (SW Africa), Rio Grande (Brazil), Xiangxi (China) and Harper's Brook (UK). A single GHM (Mac-PDM.09) is applied to all catchments whilst different CHMs are applied for each catchment. The CHMs include SLURP v. 12.2 (Liard), SLURP v. 12.7 (Mekong), Pitman (Okavango), MGB-IPH (Rio Grande), AV-SWAT-X 2005 (Xiangxi) and Cat-PDM (Harper's Brook). Simulations of mean annual runoff, mean monthly runoff and high (Q5) and low (Q95) monthly runoff under baseline (1961–1990) and climate change scenarios are presented. We compare the simulated runoff response of each hydrological model to (1) prescribed increases in global-mean air temperature of 1.0, 2.0, 3.0, 4.0, 5.0 and 6.0 °C relative to baseline from the UKMO HadCM3 Global Climate Model (GCM) to explore response to different amounts of climate forcing, and (2) a prescribed increase in global-mean air temperature of 2.0 °C relative to baseline for seven GCMs to explore response to climate model structural uncertainty. We find that the differences in projected changes of mean annual runoff between the two types of hydrological model can be substantial for a given GCM, and they are generally larger for indicators of high and low monthly runoff. However, they are relatively small in comparison to the range of projections across the seven GCMs. Hence, for the six catchments and seven GCMs we considered, climate model structural uncertainty is greater than the uncertainty associated with the type of hydrological model applied. Moreover, shifts in the seasonal cycle of runoff with climate change are represented similarly by both hydrological models, although for some catchments the monthly timing of high and low flows differs. This implies that for studies that seek to quantify and assess the role of climate model uncertainty on catchment-scale runoff, it may be equally as feasible to apply a GHM as it is to apply a CHM, especially when climate modelling uncertainty across the range of available GCMs is as large as it currently is. Whilst the GHM is able to represent the broad climate change signal that is represented by the CHMs, we find however, that for some catchments there are differences between GHMs and CHMs in mean annual runoff due to differences in potential evapotranspiration estimation methods, in the representation of the seasonality of runoff, and in the magnitude of changes in extreme (Q5, Q95) monthly runoff, all of which have implications for future water management issues.

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