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Louisiana has lost over 4800 km2 of coastal land since 1932, and a large-scale effort to restore coastal Louisiana is underway, guided by Louisiana’s Comprehensive Master Plan for a Sustainable Coast. This paper reviews science-based planning processes to address uncertainties in management decisions, and determine the most effective combination of restoration and flood risk reduction projects to reduce land loss, maintain and restore coastal environments, and sustain communities. The large-scale effort to restore coastal Louisiana is made more challenging by uncertainties in sediment in the Mississippi River, rising sea levels, subsidence, storms, oil and gas activities, flood-control levees, and navigation infrastructure. To inform decision making, CPRA uses structured approaches to incorporate science at all stages of restoration project planning and implementation to: (1) identify alternative management actions, (2) select the management action based on the best available science, and (3) assess performance of the implemented management decisions. Applied science and synthesis initiatives are critical for solving scientific and technical uncertainties in the successive stages of program and project management, from planning, implementation, operations, to monitoring and assessment. The processes developed and lessons learned from planning and implementing restoration in coastal Louisiana are relevant to other vulnerable coastal regions around the globe.
Angelina M. Freeman; James W. Pahl; Eric D. White; Summer Langlois; David C. Lindquist; Richard C. Raynie; Leigh Anne Sharp. A Review of How Uncertainties in Management Decisions Are Addressed in Coastal Louisiana Restoration. Water 2021, 13, 1528 .
AMA StyleAngelina M. Freeman, James W. Pahl, Eric D. White, Summer Langlois, David C. Lindquist, Richard C. Raynie, Leigh Anne Sharp. A Review of How Uncertainties in Management Decisions Are Addressed in Coastal Louisiana Restoration. Water. 2021; 13 (11):1528.
Chicago/Turabian StyleAngelina M. Freeman; James W. Pahl; Eric D. White; Summer Langlois; David C. Lindquist; Richard C. Raynie; Leigh Anne Sharp. 2021. "A Review of How Uncertainties in Management Decisions Are Addressed in Coastal Louisiana Restoration." Water 13, no. 11: 1528.
Current research on flooding risk often focuses on understanding hazards, de-emphasizing the complex pathways of exposure and vulnerability. We investigated the use of both hydrologic and social demographic data for flood exposure mapping with Random Forest (RF) regression and classification algorithms trained to predict both parcel- and tract-level flood insurance claims within New York State, US. Topographic characteristics best described flood claim frequency, but RF prediction skill was improved at both spatial scales when socioeconomic data was incorporated. Substantial improvements occurred at the tract-level when the percentage of minority residents, housing stock value and age, and the political dissimilarity index of voting precincts were used to predict insurance claims. Census tracts with higher numbers of claims and greater densities of low-lying tax parcels tended to have low proportions of minority residents, newer houses, and less political similarity to state level government. We compared this data-driven approach and a physically-based pluvial flood routing model for prediction of the spatial extents of flooding claims in two nearby catchments of differing land use. The floodplain we defined with physically based modeling agreed well with existing federal flood insurance rate maps, but underestimated the spatial extents of historical claim generating areas. In contrast, RF classification incorporating hydrologic and socioeconomic demographic data likely overestimated the flood-exposed areas. Our research indicates that quantitative incorporation of social data can improve flooding exposure estimates.
James Knighton; Brian Buchanan; Christian Guzman; Rebecca Elliott; Eric White; Brian Rahm. Predicting flood insurance claims with hydrologic and socioeconomic demographics via machine learning: Exploring the roles of topography, minority populations, and political dissimilarity. Journal of Environmental Management 2020, 272, 111051 .
AMA StyleJames Knighton, Brian Buchanan, Christian Guzman, Rebecca Elliott, Eric White, Brian Rahm. Predicting flood insurance claims with hydrologic and socioeconomic demographics via machine learning: Exploring the roles of topography, minority populations, and political dissimilarity. Journal of Environmental Management. 2020; 272 ():111051.
Chicago/Turabian StyleJames Knighton; Brian Buchanan; Christian Guzman; Rebecca Elliott; Eric White; Brian Rahm. 2020. "Predicting flood insurance claims with hydrologic and socioeconomic demographics via machine learning: Exploring the roles of topography, minority populations, and political dissimilarity." Journal of Environmental Management 272, no. : 111051.
Predictive tools are widely used to study coastal and deltaic systems in support of basic research, planning efforts, engineering design, and the implementation of restoration or protection strategies. They have been extensively used to evaluate the effectiveness of natural and nature-based solutions (NNBS) to support ecosystem functions and services of coastal ecosystems and human communities experiencing increased risk from sea-level rise and severe storms. The potential benefits of NNBS are being increasingly recognized, particularly in remote areas or areas that are either technically or financially infeasible to be protected with levees or other difficult engineering alternatives. Local communities, however, are often excluded from proposing, screening, or evaluating NNBS as restoration and protection strategies. Communities are also not sufficiently involved in the development or application of the predictive tools. This research effort outlines an approach to developing knowledge-based predictive tools and a community engagement process to evaluate NNBS strategies proposed predominantly by local communities. Incorporating knowledge from local communities benefits and potentially improves the performance of predictive tools and their ability to capture visible trends and observations. To illustrate this concept, the authors present landscape models for coastal Louisiana that successfully reproduced the frequency of flooding of local roads, rate of shoreline erosion, salinity pattern changes, and presence/absence of key species (e.g., brown shrimp, oysters, and so forth). While these qualitative measures are not a substitute for well-established rigorous and quantitative model performance assessment approaches, they offer an effective approach to engage local communities and incorporate their knowledge in the development of the predictive models and the proposed protection and restoration strategies to be examined.
Ehab Meselhe; Yushi Wang; Eric White; Hoonshin Jung; Melissa M. Baustian; Scott Hemmerling; Monica Barra; Harris Bienn. Knowledge-Based Predictive Tools to Assess Effectiveness of Natural and Nature-Based Solutions for Coastal Restoration and Protection Planning. Journal of Hydraulic Engineering 2020, 146, 05019007 .
AMA StyleEhab Meselhe, Yushi Wang, Eric White, Hoonshin Jung, Melissa M. Baustian, Scott Hemmerling, Monica Barra, Harris Bienn. Knowledge-Based Predictive Tools to Assess Effectiveness of Natural and Nature-Based Solutions for Coastal Restoration and Protection Planning. Journal of Hydraulic Engineering. 2020; 146 (2):05019007.
Chicago/Turabian StyleEhab Meselhe; Yushi Wang; Eric White; Hoonshin Jung; Melissa M. Baustian; Scott Hemmerling; Monica Barra; Harris Bienn. 2020. "Knowledge-Based Predictive Tools to Assess Effectiveness of Natural and Nature-Based Solutions for Coastal Restoration and Protection Planning." Journal of Hydraulic Engineering 146, no. 2: 05019007.
Melissa M. Baustian; Hoonshin Jung; Harris C. Bienn; Monica Barra; Scott A. Hemmerling; Yushi Wang; Eric White; Ehab Meselhe. Engaging coastal community members about natural and nature-based solutions to assess their ecosystem function. Ecological Engineering: X 2020, 5, 1 .
AMA StyleMelissa M. Baustian, Hoonshin Jung, Harris C. Bienn, Monica Barra, Scott A. Hemmerling, Yushi Wang, Eric White, Ehab Meselhe. Engaging coastal community members about natural and nature-based solutions to assess their ecosystem function. Ecological Engineering: X. 2020; 5 ():1.
Chicago/Turabian StyleMelissa M. Baustian; Hoonshin Jung; Harris C. Bienn; Monica Barra; Scott A. Hemmerling; Yushi Wang; Eric White; Ehab Meselhe. 2020. "Engaging coastal community members about natural and nature-based solutions to assess their ecosystem function." Ecological Engineering: X 5, no. : 1.
This study uses modeling results for coastal Louisiana to examine spatial and temporal variation in future wetland loss, and how this variation is influenced by different causes of land loss represented in the modeled processes. Fifty-year model predictions illustrate specific vulnerabilities of the wetlands and the conditions under which they occur, e.g., long-term changes vs. specific events. Environmental scenarios were used to examine model sensitivity to changes in future patterns of precipitation, evapotranspiration, subsidence, and eustatic sea level rise. Based on the model results, the magnitude of wetland loss increases more than three-fold from low to high scenario. The model allows vegetation types to change over time as environmental conditions change. Each type is sensitive to different land-loss causing factors. Across all scenarios, the largest contributor to wetland loss is inundation loss of saline marsh ->40% of loss. Inundation loss of brackish marsh increases from low to high scenarios. Salinity induced loss of fresh wetlands increases from low to high scenario and coastwide contributes <10% of the total wetland loss. Marsh edge erosion is relatively consistent in magnitude across scenarios but its relative contribution decreases from low to high. Model outputs show two contrasting responses to environmental change over a 50-year simulation: a relatively linear response of land area over time, and a non-linear response where a large collapse event is triggered in a single year. Land loss varied dramatically over time within the 50-year simulations with little loss in the first two decades and high rates of loss 25–40 years into the future. Across most of the coast, and for all scenarios, the majority of land loss is caused by excessive inundation. Understanding the threshold conditions for inundation for different species and species mixtures is crucial to predictions of vegetation change, and subsequent wetland loss.
Denise Reed; Yushi Wang; Ehab Meselhe; Eric White. Modeling wetland transitions and loss in coastal Louisiana under scenarios of future relative sea-level rise. Geomorphology 2019, 352, 106991 .
AMA StyleDenise Reed, Yushi Wang, Ehab Meselhe, Eric White. Modeling wetland transitions and loss in coastal Louisiana under scenarios of future relative sea-level rise. Geomorphology. 2019; 352 ():106991.
Chicago/Turabian StyleDenise Reed; Yushi Wang; Ehab Meselhe; Eric White. 2019. "Modeling wetland transitions and loss in coastal Louisiana under scenarios of future relative sea-level rise." Geomorphology 352, no. : 106991.
Coastal Louisiana hosts 37% of the coastal wetland area in the conterminous US, including one of the deltaic coastal regions more susceptible to the synergy of human and natural impacts causing wetland loss. As a result of the construction of flood protection infrastructure, dredging of channels across wetlands for oil/gas exploration and maritime transport activities, coastal Louisiana has lost approximately 4900 km2 of wetland area since the early 1930s. Despite the economic relevance of both wetland biomass and net primary productivity (NPP) as ecosystem services, there is a lack of vegetation simulation models to forecast the trends of those functional attributes at the landscape level as hydrological restoration projects are implemented. Here, we review the availability of peer-reviewed biomass and NPP wetland data (below and aboveground) published during the period 1976–2015 for use in the development, calibration and validation of high spatial resolution (
Victor H. Rivera-Monroy; Courtney Elliton; Siddhartha Narra; Ehab Meselhe; Xiaochen Zhao; Eric White; Charles E. Sasser; Jenneke M. Visser; Xuelian Meng; Hongqing Wang; Zuo Xue; Fernando Jaramillo; Rivera- Monroy; Zhao; Meng; Wang; Xue. Wetland Biomass and Productivity in Coastal Louisiana: Base Line Data (1976–2015) and Knowledge Gaps for the Development of Spatially Explicit Models for Ecosystem Restoration and Rehabilitation Initiatives. Water 2019, 11, 2054 .
AMA StyleVictor H. Rivera-Monroy, Courtney Elliton, Siddhartha Narra, Ehab Meselhe, Xiaochen Zhao, Eric White, Charles E. Sasser, Jenneke M. Visser, Xuelian Meng, Hongqing Wang, Zuo Xue, Fernando Jaramillo, Rivera- Monroy, Zhao, Meng, Wang, Xue. Wetland Biomass and Productivity in Coastal Louisiana: Base Line Data (1976–2015) and Knowledge Gaps for the Development of Spatially Explicit Models for Ecosystem Restoration and Rehabilitation Initiatives. Water. 2019; 11 (10):2054.
Chicago/Turabian StyleVictor H. Rivera-Monroy; Courtney Elliton; Siddhartha Narra; Ehab Meselhe; Xiaochen Zhao; Eric White; Charles E. Sasser; Jenneke M. Visser; Xuelian Meng; Hongqing Wang; Zuo Xue; Fernando Jaramillo; Rivera- Monroy; Zhao; Meng; Wang; Xue. 2019. "Wetland Biomass and Productivity in Coastal Louisiana: Base Line Data (1976–2015) and Knowledge Gaps for the Development of Spatially Explicit Models for Ecosystem Restoration and Rehabilitation Initiatives." Water 11, no. 10: 2054.
Using the Mississippi River as a tool for restoration has been a key element of restoration planning in Louisiana for decades. The results of allowing river water and sediment back into the coastal system are manifested in a number of places in present day Louisiana, with additional plans for large scale sediment and water diversions from the Mississippi River. Many previous numerical modeling studies have focused on sediment delivery to Louisiana estuaries. This study examines the effects of river diversions on salinity gradients in receiving estuarine basins. The Integrated Compartment Model, a planning-level model that simulates multi-decadal change in estuarine hydrodynamics and wetland systems under assumed sea-level rise scenarios, was used to assess the estuarine salinity gradient under potential management regimes. The simulations for current conditions are compared to a future 50-year simulation with additional diversions, as well as cases with a variety of diversion options. This modeling analysis shows that without additional action, 50-years of sea-level rise could result in substantial increases in salinity throughout the Mississippi Delta Plain estuaries. This can be largely offset with additional large river diversions which can maintain variable salinity gradients throughout the estuary basins.
Eric D. White; Ehab Meselhe; Denise Reed; Alisha Renfro; Natalie Peyronnin Snider; Yushi Wang. Mitigating the Effects of Sea-Level Rise on Estuaries of the Mississippi Delta Plain Using River Diversions. Water 2019, 11, 2028 .
AMA StyleEric D. White, Ehab Meselhe, Denise Reed, Alisha Renfro, Natalie Peyronnin Snider, Yushi Wang. Mitigating the Effects of Sea-Level Rise on Estuaries of the Mississippi Delta Plain Using River Diversions. Water. 2019; 11 (10):2028.
Chicago/Turabian StyleEric D. White; Ehab Meselhe; Denise Reed; Alisha Renfro; Natalie Peyronnin Snider; Yushi Wang. 2019. "Mitigating the Effects of Sea-Level Rise on Estuaries of the Mississippi Delta Plain Using River Diversions." Water 11, no. 10: 2028.
The ability, or lack thereof, for wetlands in coastal Louisiana to maintain elevation capital has been well documented in the literature to be a function of local and regional factors as well as environmental conditions. The Integrated Compartment Model (ICM) framework developed for the state of Louisiana’s Coastal Master Plan models hydrologic, vegetation, and wetland elevation dynamics and captures regional and local dynamics of wetland elevation, inundation and sedimentation processes. It provides insights into the relative sensitivities of wetland evolution to environmental drivers under uncertain future environmental conditions. A systematic, and computationally efficient modeling exercise was conducted to test coastal marsh survival across a wide range of possible future relative sea level rise rate scenarios. Model results indicate a diverse response with respect to sediment deposition and marsh survival driven by regional subsidence rates and proximity to suspended sediment sources. Sediment poor regions of coastal Louisiana are particularly sensitive to relative sea level rise under all but the most optimistic of future sea level rise rates simulated. Coastal marshes with high sediment availability fare much better under most scenarios tested, despite high rates of relative sea level rise.
Eric D. White; Denise J. Reed; Ehab A. Meselhe. Modeled Sediment Availability, Deposition, and Decadal Land Change in Coastal Louisiana Marshes under Future Relative Sea Level Rise Scenarios. Wetlands 2019, 39, 1233 -1248.
AMA StyleEric D. White, Denise J. Reed, Ehab A. Meselhe. Modeled Sediment Availability, Deposition, and Decadal Land Change in Coastal Louisiana Marshes under Future Relative Sea Level Rise Scenarios. Wetlands. 2019; 39 (6):1233-1248.
Chicago/Turabian StyleEric D. White; Denise J. Reed; Ehab A. Meselhe. 2019. "Modeled Sediment Availability, Deposition, and Decadal Land Change in Coastal Louisiana Marshes under Future Relative Sea Level Rise Scenarios." Wetlands 39, no. 6: 1233-1248.
Understanding spatiotemporal patterns of salinity in Barataria Basin in coastal Louisiana is important to better understand and manage operations of existing and proposed freshwater and sediment diversions from the Mississippi River into the estuary. In this study, a comprehensive salinity dataset was compiled which covered the entire basin and included data from 1990 through 2015. The data were aggregated into daily mean salinity timeseries across Barataria Basin at a variety of spatial scales and used to analyze historic patterns. Simulations were conducted with two hydrodynamic models, the Integrated Compartment Model (ICM) and Delft3D. The Delft3D model output was overlaid with observed geo-tagged locations of bottlenose dolphins that were sampled from the southwest quadrant of the basin. The ICM simulations were used to assess the impact of existing freshwater and proposed sediment diversion projects which reintroduce riverine water into the estuary. The salinity in the uppermost portions of the basin is sensitive primarily to the existing freshwater diversion, whereas additional flows from a proposed sediment diversion result in additional freshening. The lowermost region of the basin is most sensitive to the proposed sediment diversion; however, the magnitude varies by diverted flow volumes and assumed sea levels in the Gulf of Mexico.
Eric D. White; Francesca Messina; Leland Moss; Ehab Meselhe. Salinity and Marine Mammal Dynamics in Barataria Basin: Historic Patterns and Modeled Diversion Scenarios. Water 2018, 10, 1015 .
AMA StyleEric D. White, Francesca Messina, Leland Moss, Ehab Meselhe. Salinity and Marine Mammal Dynamics in Barataria Basin: Historic Patterns and Modeled Diversion Scenarios. Water. 2018; 10 (8):1015.
Chicago/Turabian StyleEric D. White; Francesca Messina; Leland Moss; Ehab Meselhe. 2018. "Salinity and Marine Mammal Dynamics in Barataria Basin: Historic Patterns and Modeled Diversion Scenarios." Water 10, no. 8: 1015.
Melissa M. Baustian; F. Ryan Clark; Andrea S. Jerabek; Yushi Wang; Harris C. Bienn; Eric D. White. Modeling current and future freshwater inflow needs of a subtropical estuary to manage and maintain forested wetland ecological conditions. Ecological Indicators 2018, 85, 791 -807.
AMA StyleMelissa M. Baustian, F. Ryan Clark, Andrea S. Jerabek, Yushi Wang, Harris C. Bienn, Eric D. White. Modeling current and future freshwater inflow needs of a subtropical estuary to manage and maintain forested wetland ecological conditions. Ecological Indicators. 2018; 85 ():791-807.
Chicago/Turabian StyleMelissa M. Baustian; F. Ryan Clark; Andrea S. Jerabek; Yushi Wang; Harris C. Bienn; Eric D. White. 2018. "Modeling current and future freshwater inflow needs of a subtropical estuary to manage and maintain forested wetland ecological conditions." Ecological Indicators 85, no. : 791-807.
Modeling the distribution and habitat capacities of key estuarine species can be used to identify hot spots, areas where species density is significantly higher than surrounding areas. This approach would be useful for establishing a baseline for evaluating future environmental scenarios across a landscape. We developed species distribution models for early juvenile life stages of brown shrimp (Farfantepenaeus aztecus), white shrimp (Litopenaeus setiferus), blue crab (Callinectes sapidus), and spotted seatrout (Cynoscion nebulosus) in order to delineate the current coastal hot spots that provide the highest quality habitat conditions for these estuarine-dependent species in Louisiana. Response curves were developed from existing long-term fisheries-independent monitoring data to identify habitat suitability for fragmented marsh landscapes. Response curves were then integrated with spatially explicit input data to generate species distribution models for the coastal region of Louisiana. Using spatial autocorrelation metrics, we detected clusters of suitable habitat across the Louisiana coast, but only 1% of the areas were identified as true hot spots with the highest habitat quality for nekton. The regions identified as hot spots were productive fringing marsh habitats that are considered the most vulnerable to natural and anthropogenic impacts. The species distribution models identify the coastal habitats which currently provide the greatest capacity for key estuarine species and will be used in the Louisiana coastal planning process to evaluate how species distributions may change under various environmental and restoration scenarios.
Ann Commagere Hijuelos; Shaye E. Sable; Ann M. O’Connell; James P. Geaghan; David C. Lindquist; Eric D. White. Application of Species Distribution Models to Identify Estuarine Hot Spots for Juvenile Nekton. Estuaries and Coasts 2016, 40, 1183 -1194.
AMA StyleAnn Commagere Hijuelos, Shaye E. Sable, Ann M. O’Connell, James P. Geaghan, David C. Lindquist, Eric D. White. Application of Species Distribution Models to Identify Estuarine Hot Spots for Juvenile Nekton. Estuaries and Coasts. 2016; 40 (4):1183-1194.
Chicago/Turabian StyleAnn Commagere Hijuelos; Shaye E. Sable; Ann M. O’Connell; James P. Geaghan; David C. Lindquist; Eric D. White. 2016. "Application of Species Distribution Models to Identify Estuarine Hot Spots for Juvenile Nekton." Estuaries and Coasts 40, no. 4: 1183-1194.
A U.S. EPA (EPA) model was developed for the Cathedral Run stormwater wetland (Philadelphia, Pennsylvania). This research presents a formal sensitivity analysis of hydraulic and hydrologic model parameters contributing uncertainty with the multiobjective generalized sensitivity analysis (MOGSA) algorithm. The parameters identified as significant include: percent routed (PR), subcatchment soils, subcatchment width, wetland soils, and the flood weir coefficient. These results suggest that this model is well parameterized for detailed simulations of stormwater control installations, and contests the existence of a globally sensitive set of parameters. This research demonstrates that detailed models of stormwater control installations are significantly affected by uncertainty related to parameters beyond traditional calibration (i.e., runoff generation) parameters. The authors present a monitoring design based on wetland water surface elevation. The simplified monitoring scheme obtained statistically significant calibration data as determined through MOGSA. The generalized likelihood uncertainty estimation (GLUE) algorithm was then applied to develop marginal posterior model parameter distributions and two-dimensional (2D) probability spaces using a formal Bayesian likelihood function. The GLUE results demonstrate the importance of uncertainty and equifinality within the context of stormwater wetland modeling.
James Knighton; Edward Lennon; Luis Bastidas; Eric White. Stormwater Detention System Parameter Sensitivity and Uncertainty Analysis Using SWMM. Journal of Hydrologic Engineering 2016, 21, 05016014 .
AMA StyleJames Knighton, Edward Lennon, Luis Bastidas, Eric White. Stormwater Detention System Parameter Sensitivity and Uncertainty Analysis Using SWMM. Journal of Hydrologic Engineering. 2016; 21 (8):05016014.
Chicago/Turabian StyleJames Knighton; Edward Lennon; Luis Bastidas; Eric White. 2016. "Stormwater Detention System Parameter Sensitivity and Uncertainty Analysis Using SWMM." Journal of Hydrologic Engineering 21, no. 8: 05016014.
This paper proposes an approach to estimating the uncertainty related to EPA Storm Water Management Model model parameters, percentage routed (PR) and saturated hydraulic conductivity (Ksat), which are used to calculate stormwater runoff volumes. The methodology proposed in this paper addresses uncertainty through the development of probability distributions for urban hydrologic parameters through extensive calibration to observed flow data in the Philadelphia collection system. The established probability distributions are then applied to the Philadelphia Southeast district model through a Monte Carlo approach to estimate the uncertainty in prediction of combined sewer overflow volumes as related to hydrologic model parameter estimation. Understanding urban hydrology is critical to defining urban water resource problems. A variety of land use types within Philadelphia coupled with a history of cut and fill have resulted in a patchwork of urban fill and native soils. The complexity of urban hydrology can make model parameter estimation and defining model uncertainty a difficult task. The development of probability distributions for hydrologic parameters applied through Monte Carlo simulations provided a significant improvement in estimating model uncertainty over traditional model sensitivity analysis. Copyright © 2013 John Wiley & Sons, Ltd.
James Knighton; Eric White; Edward Lennon; Rajesh Rajan. Development of probability distributions for urban hydrologic model parameters and a Monte Carlo analysis of model sensitivity. Hydrological Processes 2013, 28, 5131 -5139.
AMA StyleJames Knighton, Eric White, Edward Lennon, Rajesh Rajan. Development of probability distributions for urban hydrologic model parameters and a Monte Carlo analysis of model sensitivity. Hydrological Processes. 2013; 28 (19):5131-5139.
Chicago/Turabian StyleJames Knighton; Eric White; Edward Lennon; Rajesh Rajan. 2013. "Development of probability distributions for urban hydrologic model parameters and a Monte Carlo analysis of model sensitivity." Hydrological Processes 28, no. 19: 5131-5139.
Eric White; Philadelphia Water Department; James Knighton; Gary Martens; Matthew Plourde; Rajesh Rajan. Geoprocessing Tools for Surface and Basement Flooding Analysis in SWMM. Journal of Water Management Modeling 2013, 1 .
AMA StyleEric White, Philadelphia Water Department, James Knighton, Gary Martens, Matthew Plourde, Rajesh Rajan. Geoprocessing Tools for Surface and Basement Flooding Analysis in SWMM. Journal of Water Management Modeling. 2013; ():1.
Chicago/Turabian StyleEric White; Philadelphia Water Department; James Knighton; Gary Martens; Matthew Plourde; Rajesh Rajan. 2013. "Geoprocessing Tools for Surface and Basement Flooding Analysis in SWMM." Journal of Water Management Modeling , no. : 1.
Zachary M. Easton; M. Todd Walter; Daniel R. Fuka; Eric D. White; Tammo S. Steenhuis. A simple concept for calibrating runoff thresholds in quasi-distributed variable source area watershed models. Hydrological Processes 2011, 25, 3131 -3143.
AMA StyleZachary M. Easton, M. Todd Walter, Daniel R. Fuka, Eric D. White, Tammo S. Steenhuis. A simple concept for calibrating runoff thresholds in quasi-distributed variable source area watershed models. Hydrological Processes. 2011; 25 (20):3131-3143.
Chicago/Turabian StyleZachary M. Easton; M. Todd Walter; Daniel R. Fuka; Eric D. White; Tammo S. Steenhuis. 2011. "A simple concept for calibrating runoff thresholds in quasi-distributed variable source area watershed models." Hydrological Processes 25, no. 20: 3131-3143.
A multi basin analysis of runoff and erosion in the Blue Nile Basin, Ethiopia was conducted to elucidate sources of runoff and sediment. Erosion is arguably the most critical problem in the Blue Nile Basin, as it limits agricultural productivity in Ethiopia, degrades benthos in the Nile, and results in sedimentation of dams in downstream countries. A modified version of the Soil and Water Assessment Tool (SWAT) model was developed to predict runoff and sediment losses from the Ethiopian Blue Nile Basin. The model simulates saturation excess runoff from the landscape using a simple daily water balance coupled to a topographic wetness index in ways that are consistent with observed runoff processes in the basin. The spatial distribution of landscape erosion is thus simulated more correctly. The model was parameterized in a nested design for flow at eight and sediment at three locations in the basin. Subbasins ranged in size from 1.3 to 174 000 km2, and interestingly, the partitioning of runoff and infiltrating flow could be predicted by topographic information. Model predictions showed reasonable accuracy (Nash Sutcliffe Efficiencies ranged from 0.53–0.92) with measured data across all sites except Kessie, where the water budget could not be closed; however, the timing of flow was well captured. Runoff losses increased with rainfall during the monsoonal season and were greatest from areas with shallow soils and large contributing areas. Analysis of model results indicate that upland landscape erosion dominated sediment delivery to the main stem of the Blue Nile in the early part of the growing season when tillage occurs and before the soil was wetted up and plant cover was established. Once plant cover was established in mid August landscape erosion was negligible and sediment export was dominated by channel processes and re-suspension of landscape sediment deposited early in the growing season. These results imply that targeting small areas of the landscape where runoff is produced can be the most effective at controlling erosion and protecting water resources. However, it is not clear what can be done to manage channel erosion, particularly in first order streams in the basin.
Z. M. Easton; D. R. Fuka; Eric White; A. S. Collick; Biniam Ashagre; M. McCartney; S. B. Awulachew; A. A. Ahmed; T. S. Steenhuis. A multi basin SWAT model analysis of runoff and sedimentation in the Blue Nile, Ethiopia. Hydrology and Earth System Sciences 2010, 14, 1827 -1841.
AMA StyleZ. M. Easton, D. R. Fuka, Eric White, A. S. Collick, Biniam Ashagre, M. McCartney, S. B. Awulachew, A. A. Ahmed, T. S. Steenhuis. A multi basin SWAT model analysis of runoff and sedimentation in the Blue Nile, Ethiopia. Hydrology and Earth System Sciences. 2010; 14 (10):1827-1841.
Chicago/Turabian StyleZ. M. Easton; D. R. Fuka; Eric White; A. S. Collick; Biniam Ashagre; M. McCartney; S. B. Awulachew; A. A. Ahmed; T. S. Steenhuis. 2010. "A multi basin SWAT model analysis of runoff and sedimentation in the Blue Nile, Ethiopia." Hydrology and Earth System Sciences 14, no. 10: 1827-1841.
Watershed scale hydrological and biogeochemical models rely on the correct spatial-temporal prediction of processes governing water and contaminant movement. The Soil and Water Assessment Tool (SWAT) model, one of the most commonly used watershed scale models, uses the popular curve number (CN) method to determine the respective amounts of infiltration and surface runoff. Although appropriate for flood forecasting in temperate climates, the CN method has been shown to be less than ideal in many situations (e.g. monsoonal climates and areas dominated by variable source area hydrology). The CN model is based on the assumption that there is a unique relationship between the average moisture content and the CN for all hydrologic response units (HRUs), and that the moisture content distribution is similar for each runoff event, which is not the case in many regions. Presented here is a physically based water balance that was coded in the SWAT model to replace the CN method of runoff generation. To compare this new water balance SWAT (SWAT-WB) to the original CN-based SWAT SWAT-CN), two watersheds were initialized; one in the headwaters of the Blue Nile in Ethiopia and one in the Catskill Mountains of New York. In the Ethiopian watershed, streamflow predictions were better using SWAT-WB than SWAT-CN [Nash-Sutcliffe efficiencies (NSE) of 0?79 and 0?67, respectively]. In the temperate Catskills, SWAT-WB and SWAT-CN predictions were approximately equivalent (NSE >0?70). The spatial distribution of runoff-generating areas differed greatly between the two models, with SWAT-WB reflecting the topographical controls imposed on the model. Results show that a water balance provides results equal to or better than the CN, but with a more physically based approach
Eric D. White; Zachary M. Easton; Daniel R. Fuka; Amy S. Collick; Enyew Adgo; Matthew McCartney; Seleshi B. Awulachew; Yihenew G. Selassie; Tammo S. Steenhuis. Development and application of a physically based landscape water balance in the SWAT model. Hydrological Processes 2010, 25, 915 -925.
AMA StyleEric D. White, Zachary M. Easton, Daniel R. Fuka, Amy S. Collick, Enyew Adgo, Matthew McCartney, Seleshi B. Awulachew, Yihenew G. Selassie, Tammo S. Steenhuis. Development and application of a physically based landscape water balance in the SWAT model. Hydrological Processes. 2010; 25 (6):915-925.
Chicago/Turabian StyleEric D. White; Zachary M. Easton; Daniel R. Fuka; Amy S. Collick; Enyew Adgo; Matthew McCartney; Seleshi B. Awulachew; Yihenew G. Selassie; Tammo S. Steenhuis. 2010. "Development and application of a physically based landscape water balance in the SWAT model." Hydrological Processes 25, no. 6: 915-925.
Models accurately representing the underlying hydrological processes and sediment dynamics in the Nile Basin are necessary for optimum use of water resources. Previous research in the Abay (Blue Nile) has indicated that direct runoff is generated either from saturated areas at the lower portions of the hillslopes or from areas of exposed bedrock. Thus, models that are based on infiltration excess processes are not appropriate. Furthermore, many of these same models are developed for temperate climates and might not be suitable for monsoonal climates with distinct dry periods in the Nile Basin. The objective of this study is to develop simple hydrology and erosion models using saturation excess runoff principles and interflow processes appropriate for a monsoonal climate and a mountainous landscape. We developed a hydrology model using a water balance approach by dividing the landscape into variable saturated areas, exposed rock and hillslopes. Water balance models have been shown to simulate river flows well at intervals of 5 days or longer when the main runoff mechanism is saturation excess. The hydrology model was developed and coupled with an erosion model using available precipitation and potential evaporation data and a minimum of calibration parameters. This model was applied to the Blue Nile. The model predicts direct runoff from saturated areas and impermeable areas (such as bedrock outcrops) and subsurface flow from the remainder of the hillslopes. The ratio of direct runoff to total flow is used to predict the sediment concentration by assuming that only the direct runoff is responsible for the sediment load in the stream. There is reasonable agreement between the model predictions and the 10‐day observed discharge and sediment concentration at the gauging station on Blue Nile upstream of Rosaries Dam at the Ethiopia–Sudan border. Copyright © 2009 John Wiley & Sons, Ltd.
Tammo S. Steenhuis; Amy S. Collick; Zachary M. Easton; Elias S. Leggesse; Haimanote Bayabil; Eric White; Seleshi Bekele Awulachew; Enyew Adgo; Abdassalam Abdalla Ahmed. Predicting discharge and sediment for the Abay (Blue Nile) with a simple model. Hydrological Processes 2009, 23, 3728 -3737.
AMA StyleTammo S. Steenhuis, Amy S. Collick, Zachary M. Easton, Elias S. Leggesse, Haimanote Bayabil, Eric White, Seleshi Bekele Awulachew, Enyew Adgo, Abdassalam Abdalla Ahmed. Predicting discharge and sediment for the Abay (Blue Nile) with a simple model. Hydrological Processes. 2009; 23 (26):3728-3737.
Chicago/Turabian StyleTammo S. Steenhuis; Amy S. Collick; Zachary M. Easton; Elias S. Leggesse; Haimanote Bayabil; Eric White; Seleshi Bekele Awulachew; Enyew Adgo; Abdassalam Abdalla Ahmed. 2009. "Predicting discharge and sediment for the Abay (Blue Nile) with a simple model." Hydrological Processes 23, no. 26: 3728-3737.
Researchers are assessing the beneficial effects of conservation practices on water quality with hydrologic models. The assessments depend heavily on accurate simulation of water yield. This study was conducted to improve Soil and Water Assessment Tool (SWAT) hydrologic model daily water yield estimates in the Little River Experimental Watershed (LREW) in south Georgia. The SWAT code was altered to recognize a difference in curve number between growing and dormant seasons, to use an initial abstraction (Ia), of 0.05S rather than 0.2S, and to adjust curve number based on the level of soil saturation in low-lying riparian zones. Refinements were made to two SWAT input parameters, SURLAG and ALPHA_BF, from a previous set of calibration parameters. The combined changes improved the daily Nash-Sutcliffe model efficiency (NSE) from 0.42 to 0.66 for water yield at the outlet of the 16.9 km2 subwatershed K of the LREW for the ten-year period 1995 to 2004. Further calibration of the SURLAG coefficient yielded the largest improvement of five alterations, and changing Ia effected the next largest improvement. Over the ten-year investigation period, the model predicted annual average water yield within 1% of measured streamflow, and deviation between observed and simulated values for stormflow was
Eric White; Gary W Feyereisen; Tamie L Veith; D. D. Bosch. Improving Daily Water Yield Estimates in the Little River Watershed: SWAT Adjustments. Transactions of the ASABE 2009, 52, 69 -79.
AMA StyleEric White, Gary W Feyereisen, Tamie L Veith, D. D. Bosch. Improving Daily Water Yield Estimates in the Little River Watershed: SWAT Adjustments. Transactions of the ASABE. 2009; 52 (1):69-79.
Chicago/Turabian StyleEric White; Gary W Feyereisen; Tamie L Veith; D. D. Bosch. 2009. "Improving Daily Water Yield Estimates in the Little River Watershed: SWAT Adjustments." Transactions of the ASABE 52, no. 1: 69-79.