Stochastic GIS-Based Water Resources/Quality Modeling of the Land Water Interface

Salah, Ahmad M.; Nelson, Everett J.

doi:10.1061/40856(200)217

Cited by 2 publications

(19 citation statements)

References 3 publications

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“…While the implementation is specific to these models, the framework and approach is general and can be applied to other models. This study demonstrates the ability to link GSSHA with CE‐QUAL‐W2, even though GSSHA uses horizontal two‐dimensional (2D) grids and CE‐QUAL‐W2 uses vertical 2D grids (Salah 2009). WMS (Aquaveo 2009) was used as a platform to implement the tools, to perform model set‐up, to run the routines to link the models and to analyse the results (Salah 2009).…”

Section: Introductionmentioning

confidence: 96%

“…This study demonstrates the ability to link GSSHA with CE‐QUAL‐W2, even though GSSHA uses horizontal two‐dimensional (2D) grids and CE‐QUAL‐W2 uses vertical 2D grids (Salah 2009). WMS (Aquaveo 2009) was used as a platform to implement the tools, to perform model set‐up, to run the routines to link the models and to analyse the results (Salah 2009). The framework presented herein can be used with other models or implemented in other multi‐model tools, such as the EPA BASINS platform (US‐EPA 2007).…”

Section: Introductionmentioning

confidence: 96%

“…In this approach, the best overland flow model is used to model the basin hydrology, with specialized routing and reservoir models used for water quantity and quality issues (Calder 2005). Owing to model optimization, the models typically do not have the same spatial or temporal resolutions, causing difficulties when linking one model to another (Salah 2009). Several approaches have been developed to perform basin‐wide analysis with multiple models, with most using a geographical interface.…”

Section: Introductionmentioning

confidence: 99%

“…Liu and Gupta (2007), for example, demonstrated how incorporating parameter variability provides better information. A single model can be modified to incorporate uncertainty relatively easily by performing multiple simulations with stochastically selected input variables (Salah 2009). Although developing a stochastic framework for linked stochastic models is more difficult (Salah 2009), it provides a quantifiable way to incorporate uncertainty in management decisions, while also providing the benefits of using ‘best‐of‐class’ models.…”

Section: Introductionmentioning

confidence: 99%

“…Gridded Surface Sub‐surface Hydrological Analysis is a 2‐D surface model that uses horizontal grids to compute overland flow and run‐off, based on meteorological input and physical watershed parameters. Although it includes stream and reservoir routing, it assumes a vertically averaged profile during routing because it is based on horizontal grids (Downer & Ogden 2006; Salah 2009). Major components of GSSHA include spatially‐ and temporally varying precipitation, snowfall accumulation and melting, precipitation interception, infiltration, evapo‐transpiration, surface run‐off routing, simple lake storage and routing, unsaturated zone soil moisture accounting, saturated groundwater flow, wetland peat layer hydraulics, overland sediment erosion, transport and deposition, in‐stream sediment transport and overland contaminant transport, and uptake (Downer & Ogden 2006).…”

Section: Introductionmentioning

confidence: 99%

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A framework for implementing spatial and temporal uncertainty in integrated water resources modelling

Salah¹,

Nelson

Williams

2011

Lakes & Reservoirs

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This study discusses research that develops a general framework and presents a specific implementation of a stochastic modelling system, using linked overland flow and routing simulation models. The specific implementation uses the Gridded Surface Sub-surface Hydrological Analysis (GSSHA) overland flow model, and the reservoir routing and quality model CE-QUAL-W2, to develop the stochastic modelling system. For stochastic simulations, modellers can define up to six GSSHA parameters for stochastic treatment, select the appropriate probability density functions and range, and determine the number of runs in the simulation. The tools described herein then create the correct input and output files, run the linked simulation models using the defined stochastic parameters, and aggregate the voluminous results. Interactive tools were developed to compute credible intervals from the results, and create reports that present the variability in a manner that is easily understood and communicated. Model set-up and development, stochastic and statistical parameter input, stochastic simulation execution and results analysis were implemented using the Watershed Modeling System, model pre-and postprocessing system. This study presents the tools, algorithms and user interfaces developed to implement the linked stochastic modelling system, as well as a simple example demonstrating the tools and the type of analysis supported by this system.

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Section: Introductionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A framework for implementing spatial and temporal uncertainty in integrated water resources modelling

Salah¹,

Nelson

Williams

2011

Lakes & Reservoirs

View full text Add to dashboard Cite

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Tools and Algorithms to Link Horizontal Hydrologic and Vertical Hydrodynamic Models and Provide a Stochastic Modeling Framework

Salah¹,

Nelson

Williams

2010

J Adv Model Earth Syst

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We present algorithms and tools we developed to automatically link an overland flow model to a hydrodynamic water quality model with different spatial and temporal discretizations. These tools run the linked models which provide a stochastic simulation frame. We also briefly present the tools and algorithms we developed to facilitate and analyze stochastic simulations of the linked models. We demonstrate the algorithms by linking the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model for overland flow with the CE-QUAL-W2 model for water quality and reservoir hydrodynamics. GSSHA uses a two-dimensional horizontal grid while CE-QUAL-W2 uses a two-dimensional vertical grid. We implemented the algorithms and tools in the Watershed Modeling System (WMS) which allows modelers to easily create and use models. The algorithms are general and could be used for other models. Our tools create and analyze stochastic simulations to help understand uncertainty in the model application. While a number of examples of linked models exist, the ability to perform automatic, unassisted linking is a step forward and provides the framework to easily implement stochastic modeling studies.

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Stochastic GIS-Based Water Resources/Quality Modeling of the Land Water Interface

Cited by 2 publications

References 3 publications

A framework for implementing spatial and temporal uncertainty in integrated water resources modelling

A framework for implementing spatial and temporal uncertainty in integrated water resources modelling

Tools and Algorithms to Link Horizontal Hydrologic and Vertical Hydrodynamic Models and Provide a Stochastic Modeling Framework

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