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Browsing by Author "Alamdari, Nasrin"

Now showing 1 - 4 of 4
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    Assessing the Effects of Climate Change on Water Quantity and Quality in an Urban Watershed Using a Calibrated Stormwater Model
    Alamdari, Nasrin; Sample, David J.; Steinberg, Peter; Ross, Andrew C.; Easton, Zachary M. (MDPI, 2017-06-27)
    Assessing climate change (CC) impacts on urban watersheds is difficult due to differences in model spatial and temporal scales, making prediction of hydrologic restoration a challenge. A methodology was developed using an autocalibration tool to calibrate a previously developed Storm Water Management Model (SWMM) of Difficult Run in Fairfax, Virginia. Calibration was assisted by use of multi-objective optimization. Results showed a good agreement between simulated and observed data. Simulations of CC for the 2041–2068 period were developed using dynamically downscaled North American Regional CC Assessment Program models. Washoff loads were used to simulate water quality, and a method was developed to estimate treatment performed in stormwater control measures (SCMs) to assess water quality impacts from CC. CC simulations indicated that annual runoff volume would increase by 6.5%, while total suspended solids, total nitrogen, and total phosphorus would increase by 7.6%, 7.1%, and 8.1%, respectively. The simulations also indicated that within season variability would increase by a larger percentage. Treatment practices (e.g., bioswale) that were intended to mitigate the negative effects of urban development will need to deal with additional runoff volumes and nutrient loads from CC to achieve the required water quality goals.
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    Evaluating the joint effects of climate and land use change on runoff and pollutant loading in a rapidly developing watershed
    Alamdari, Nasrin; Claggett, Peter; Sample, David J.; Easton, Zachary M.; Nayeb Yazdi, Mohammed (Elsevier, 2022-01-01)
    Communities are coping with changes in runoff quantity and quality, stemming mainly from changes in climate and land use/land cover (LULC); there is a need to identify the most adaptable strategies that improve community resilience. However, the joint impacts of climate and LULC change have rarely been assessed at local scales. To address these needs, we assessed the response of runoff and pollutant loads from Broad Run, a rapidly developing watershed in northern Virginia, to projected climate and LULC change. Climate data from two downscaled Global Climate Models (GCMs) were used to force an urban watershed model, the Storm Water Management Model (SWMM), while forecasts of LULC change were derived from the Chesapeake Bay Land Change Model (CBLCM). Two Representative Concentration Pathways (RCPs), 4.5 and 8.5, a historic baseline (1995–2020), and projected periods (2040–2065); and four LULC change scenarios designated agricultural conservation (AC), forest conservation (FC), growth management (GM), and historical trend (HT) were used to create a series of ensemble simulations of coupled LULC and climate change. Results indicated that, under RCP 8.5, annual precipitation is projected to increase substantially more than RCP 4.5. Projected LULC change resulted in a projected increase in imperviousness from 6.3% to 13.1%. Results indicated that climate change will likely increase the seasonal variability of runoff, Total Suspended Solids (TSS), Total Nitrogen (TN), and Total Phosphorus (TP) for both RCPs. The largest increase for a single LULC change (without climate change) scenario for runoff, TSS, TN, and TP was 32.6%, 33.4%, 31.6%, and 35.8%, respectively. which occurred with the HT scenario. Results of LULC change also indicated that more pollutant loads were associated with increased imperviousness from increased urban development and loss of deciduous forests and grasslands. The largest increase for climate and LULC change scenarios in runoff, TSS, TN, and TP was 67.6%, 66.7%, 63.4%, and 69.4%, respectively, which occurred with the RCP 8.5 and HT scenarios. Similar, but smaller increases were obtained for other scenarios, suggesting that climate and LULC change may be synergistic, likely undermining watershed restoration efforts. The results of our study also indicate that runoff, TSS, TN, and TP are expected to be more affected by changes in future LULC than by projected changes in climate. Our study can be used to inform watershed restoration efforts, urban planning, and environmental policy. The combined impact of climate and LULC change will likely generate increased runoff, and nutrients and sediment loading, indicating that robust mitigation strategies are needed for watershed restoration to succeed.
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    Modeling Climate Change Impacts on the Effectiveness of Stormwater Control Measures in Urban Watersheds
    Alamdari, Nasrin (Virginia Tech, 2018-08-30)
    Climate change (CC) science has made significant progress in development of predictive models. Despite these recent advances, the assessment of CC impacts in urban watersheds remains an area of active research, in part due to the small temporal and spatial scales needed to adequately characterize urban systems. Urban watersheds have been the focus of considerable efforts to restore hydrology and water quality, and the aquatic habitat of receiving waters, yet CC impacts threaten to reduce the effectiveness of these efforts. Thus, assessing the impacts of CC in urban watershed assessment are essential for assuring the success of water quality improvement programs and is an important research need. Simulations of CC for the 2041-2068 period were developed using downscaled Global Climate Models (GCMs) from the North American Regional CC Assessment Program (NARCCAP) and Coupled Model Intercomparison Project Phase 5 (CMIP5) to forecast precipitation and temperature time series. This data were then used to force a Storm Water Management Model (SWMM) of the Difficult Run watershed of Fairfax County, Virginia, a tributary of Potomac River, which flows into Chesapeake Bay. NARCCAP uses a scenario represents a medium-high greenhouse gas emissions assumption, A2; the latter, uses five GCMs, and two Representative Concentration Pathways (RCP 4.5 and 8.5) scenarios in an ensemble approach to better assess variability of model predictions in presenting precipitation, temperature, runoff quantity and quality. Then, the effects of CC on runoff peak, volume, and nutrient and sediment loads delivered to the Chesapeake Bay and on the treatment performance of a very common stormwater control measure (SCM), retention ponds, was assessed. Rainwater Harvesting (RWH) systems are an unusual SCM in that they recycle and reuse stormwater, normally from rooftops, and increase water supply and reduce runoff. The efficiency of RWH systems for projected CC for these dual purposes was assessed. NARCAAP data for selected locations across the U.S. were statistically downscaled using a modified version of the equiratio cumulative distribution function matching method to create a time series of projected precipitation and temperature. These data were used to force a simulation model, the Rainwater Analysis and Simulation Program (RASP) to assess the impacts of CC on RWH with respect to the reliability of water supply and runoff capture. To support CC modeling, an easy-to-use software tool, RSWMM-Cost, was developed. RSWMM-Cost automates the execution of SWMM, which is commonly used for simulating urban watersheds. Several features were incorporated into the RSWMM-Cost tool, including automated calibration, sensitivity analysis, and cost optimization modules; the latter can assist in identifying the most cost-effective combination of SCMs in an urban watershed. As an example, RSWMM-Cost was applied to a headwater subcatchment the Difficult Run watershed.
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    Water supply and runoff capture reliability curves for hypothetical rainwater harvesting systems for locations across the U.S. for historical and projected climate conditions
    Alamdari, Nasrin; Sample, David J.; Liu, Jia; Ross, Andrew C. (Elsevier, 2018-03-11)
    The data presented in this article are related to the research article entitled “Assessing climate change impacts on the reliability of rainwater harvesting systems” (Alamdari et al., 2018) [1]. This article evaluated the water supply and runoff capture reliability of rainwater harvesting (RWH) systems for locations across the U.S. for historical and projected climate conditions. Hypothetical RWH systems with varying storage volumes, rooftop catchment areas, irrigated areas, and indoor wSater demand based upon population from selected locations were simulated for historical (1971–1998) and projected (2041–2068) periods, the latter dataset was developed using dynamic downscaling of North American Regional Climate Change (CC) Assessment Program (NARCCAP). A computational model, the Rainwater Analysis and Simulation Program (RASP), was used to compute RWH performance with respect to the reliability of water supply and runoff capture. The reliability of water supply was defined as the proportion of demands that are met; and the reliability of runoff capture was defined as the amount stored and reused, but not spilled. A series of contour plots using the four design variables and the reliability metrics were developed for historical and projected conditions. Frequency analysis was also used to characterize the long-term behavior of rainfall and dry duration at each location. The full data set is made publicly available to enable critical or extended analysis of this work.