Search

Search Results

• 1. [Article] Automatic Calibration of Water Quality and Hydrodynamic Model (CE-QUAL-W2)

  One of the most important purposes of surface water resource management is to develop predictive models to assist in identifying and evaluating operational and structural measures for improving water quality. ...

  Citation × Citation Citation Abstract Copy Title: Automatic Calibration of Water Quality and Hydrodynamic Model (CE-QUAL-W2) Author: Shojaei, Nasim Year: 2014 One of the most important purposes of surface water resource management is to develop predictive models to assist in identifying and evaluating operational and structural measures for improving water quality. To better understand the effects of external and internal nutrient and organic loading and the effects of reservoir operation, a model is often developed, calibrated, and used for sensitivity and management simulations. The importance of modeling and simulation in the scientific community has drawn interest towards methods for automated calibration. This study addresses using an automatic technique to calibrate the water quality model CE-QUAL-W2 (Cole and Wells, 2013). CE-QUAL-W2 is a two-dimensional (2D) longitudinal/vertical hydrodynamic and water quality model for surface water bodies, modeling eutrophication processes such as temperature-nutrient-algae-dissolved oxygen-organic matter and sediment relationships. The numerical method used for calibration in this study is the particle swarm optimization method developed by Kennedy and Eberhart (1995) and inspired by the paradigm of birds flocking. The objective of this calibration procedure is to choose model parameters and coefficients affecting temperature, chlorophyll a, dissolved oxygen, and nutrients (such as NH4, NO3, and PO4). A case study is presented for the Karkheh Reservoir in Iran with a capacity of more than 5 billion cubic meters that is the largest dam in Iran with both agricultural and drinking water usages. This algorithm is shown to perform very well for determining model parameters for the reservoir water quality and hydrodynamic model. Implications of the use of this procedure for other water quality models are also shown. Title: Automatic Calibration of Water Quality and Hydrodynamic Model (CE-QUAL-W2) Author: Shojaei, Nasim Year: 2014 One of the most important purposes of surface water resource management is to develop predictive models to assist in identifying and evaluating operational and structural measures for improving water quality. To better understand the effects of external and internal nutrient and organic loading and the effects of reservoir operation, a model is often developed, calibrated, and used for sensitivity and management simulations. The importance of modeling and simulation in the scientific community has drawn interest towards methods for automated calibration. This study addresses using an automatic technique to calibrate the water quality model CE-QUAL-W2 (Cole and Wells, 2013). CE-QUAL-W2 is a two-dimensional (2D) longitudinal/vertical hydrodynamic and water quality model for surface water bodies, modeling eutrophication processes such as temperature-nutrient-algae-dissolved oxygen-organic matter and sediment relationships. The numerical method used for calibration in this study is the particle swarm optimization method developed by Kennedy and Eberhart (1995) and inspired by the paradigm of birds flocking. The objective of this calibration procedure is to choose model parameters and coefficients affecting temperature, chlorophyll a, dissolved oxygen, and nutrients (such as NH4, NO3, and PO4). A case study is presented for the Karkheh Reservoir in Iran with a capacity of more than 5 billion cubic meters that is the largest dam in Iran with both agricultural and drinking water usages. This algorithm is shown to perform very well for determining model parameters for the reservoir water quality and hydrodynamic model. Implications of the use of this procedure for other water quality models are also shown. Close

• 2. [Article] Tidal-Fluvial and Estuarine Processes in the Lower Columbia River: II. Water Level Models, Floodplain Wetland Inundation, and System Zones

  Spatially varying water-level regimes are a factor controlling estuarine and tidal-fluvial wetland vegetation patterns. As described in Part I, water levels in the Lower Columbia River and estuary (LCRE) ...

  Citation × Citation Citation Abstract Copy Title: Tidal-Fluvial and Estuarine Processes in the Lower Columbia River: II. Water Level Models, Floodplain Wetland Inundation, and System Zones Author: Jay, David A, Borde, Amy B., Diefenderfer, Heida Year: 2016 Spatially varying water-level regimes are a factor controlling estuarine and tidal-fluvial wetland vegetation patterns. As described in Part I, water levels in the Lower Columbia River and estuary (LCRE) are influenced by tides, river flow, hydropower operations, and coastal processes. In Part II, regression models based on tidal theory are used to quantify the role of these processes in determining water levels in the mainstem river and floodplain wetlands, and to provide 21-year inundation hindcasts. Analyses are conducted at 19 LCRE mainstem channel stations and 23 tidally exposed floodplain wetland stations. Sum exceedance values (SEVs) are used to compare wetland hydrologic regimes at different locations on the river floodplain. A new predictive tool is introduced and validated, the potential SEV (pSEV), which can reduce the need for extensive new data collection in wetland restoration planning. Models of water levels and inundation frequency distinguish four zones encompassing eight reaches. The system zones are the wave- and current-dominated Entrance to river kilometer (rkm) 5; the Estuary (rkm-5 to 87), comprised of a lower reach with salinity, the energy minimum (where the turbidity maximum normally occurs), and an upper estuary reach without salinity; the Tidal River (rkm-87 to 229), with lower, middle, and upper reaches in which river flow becomes increasingly dominant over tides in determining water levels; and the steep and weakly tidal Cascade (rkm-229 to 234) immediately downstream from Bonneville Dam. The same zonation is seen in the water levels of floodplain stations, with considerable modification of tidal properties. The system zones and reaches defined here reflect geological features and their boundaries are congruent with five wetland vegetation zones. Title: Tidal-Fluvial and Estuarine Processes in the Lower Columbia River: II. Water Level Models, Floodplain Wetland Inundation, and System Zones Author: Jay, David A, Borde, Amy B., Diefenderfer, Heida Year: 2016 Spatially varying water-level regimes are a factor controlling estuarine and tidal-fluvial wetland vegetation patterns. As described in Part I, water levels in the Lower Columbia River and estuary (LCRE) are influenced by tides, river flow, hydropower operations, and coastal processes. In Part II, regression models based on tidal theory are used to quantify the role of these processes in determining water levels in the mainstem river and floodplain wetlands, and to provide 21-year inundation hindcasts. Analyses are conducted at 19 LCRE mainstem channel stations and 23 tidally exposed floodplain wetland stations. Sum exceedance values (SEVs) are used to compare wetland hydrologic regimes at different locations on the river floodplain. A new predictive tool is introduced and validated, the potential SEV (pSEV), which can reduce the need for extensive new data collection in wetland restoration planning. Models of water levels and inundation frequency distinguish four zones encompassing eight reaches. The system zones are the wave- and current-dominated Entrance to river kilometer (rkm) 5; the Estuary (rkm-5 to 87), comprised of a lower reach with salinity, the energy minimum (where the turbidity maximum normally occurs), and an upper estuary reach without salinity; the Tidal River (rkm-87 to 229), with lower, middle, and upper reaches in which river flow becomes increasingly dominant over tides in determining water levels; and the steep and weakly tidal Cascade (rkm-229 to 234) immediately downstream from Bonneville Dam. The same zonation is seen in the water levels of floodplain stations, with considerable modification of tidal properties. The system zones and reaches defined here reflect geological features and their boundaries are congruent with five wetland vegetation zones. Close

• 3. [Article] Exploring, Exploiting and Evolving Diversity of Aquatic Ecosystem Models: a Community Perspective

  Here, we present a community perspective on how to explore, exploit and evolve the diversity in aquatic ecosystem models. These models play an important role in understanding the functioning of aquatic ...

  Citation × Citation Citation Abstract Copy Title: Exploring, Exploiting and Evolving Diversity of Aquatic Ecosystem Models: a Community Perspective Author: Janssen, Annette B.G., Arhonditsis, George B., Beusen, Arthur, Bolding, Karsten, Bruce, Louise, Bruggeman, Jorn, Couture, Raoul-Marie, Downing, Andrea S., Elliott, J. Alex, Frassl, Marieke A., Gal, Gideon, Gerla, Daan J., Hipsey, Matthew R., Hu, Fenjuan, Ives, Stephen C., Janse, Jan H., Jeppesen, Erik, Jöhnk, Klaus D., Kneis, David, Kong, Xiangzhen, Kuiper, Jan J., Lehmann, Moritz K., Lemmen, Carsten, Özkundakci, Deniz, Petzoldt, Thomas, Rinke, Karsten, Robson, Barbara J., Sachse, René, Schep, Sebastiaan A., Schmid, Martin, Scholten, Huub, Teurlincx, Sven, Trolle, Dennis, Troost, Tineke A., Van Dam, Anne A., Van Gerven, Luuk P.A., Weijerman, Mariska, Wells, Scott A., Mooij, Wolf M. Year: 2015 Here, we present a community perspective on how to explore, exploit and evolve the diversity in aquatic ecosystem models. These models play an important role in understanding the functioning of aquatic ecosystems, filling in observation gaps and developing effective strategies for water quality management. In this spirit, numerous models have been developed since the 1970s. We set off to explore model diversity by making an inventory among 42 aquatic ecosystem modellers, by categorizing the resulting set of models and by analysing them for diversity. We then focus on how to exploit model diversity by comparing and combining different aspects of existing models. Finally, we discuss how model diversity came about in the past and could evolve in the future. Throughout our study, we use analogies from biodiversity research to analyse and interpret model diversity. We recommend to make models publicly available through open-source policies, to standardize documentation and technical implementation of models, and to compare models through ensemble modelling and interdisciplinary approaches. We end with our perspective on how the field of aquatic ecosystem modelling might develop in the next 5–10 years. To strive for clarity and to improve readability for non-modellers, we include a glossary. Title: Exploring, Exploiting and Evolving Diversity of Aquatic Ecosystem Models: a Community Perspective Author: Janssen, Annette B.G., Arhonditsis, George B., Beusen, Arthur, Bolding, Karsten, Bruce, Louise, Bruggeman, Jorn, Couture, Raoul-Marie, Downing, Andrea S., Elliott, J. Alex, Frassl, Marieke A., Gal, Gideon, Gerla, Daan J., Hipsey, Matthew R., Hu, Fenjuan, Ives, Stephen C., Janse, Jan H., Jeppesen, Erik, Jöhnk, Klaus D., Kneis, David, Kong, Xiangzhen, Kuiper, Jan J., Lehmann, Moritz K., Lemmen, Carsten, Özkundakci, Deniz, Petzoldt, Thomas, Rinke, Karsten, Robson, Barbara J., Sachse, René, Schep, Sebastiaan A., Schmid, Martin, Scholten, Huub, Teurlincx, Sven, Trolle, Dennis, Troost, Tineke A., Van Dam, Anne A., Van Gerven, Luuk P.A., Weijerman, Mariska, Wells, Scott A., Mooij, Wolf M. Year: 2015 Here, we present a community perspective on how to explore, exploit and evolve the diversity in aquatic ecosystem models. These models play an important role in understanding the functioning of aquatic ecosystems, filling in observation gaps and developing effective strategies for water quality management. In this spirit, numerous models have been developed since the 1970s. We set off to explore model diversity by making an inventory among 42 aquatic ecosystem modellers, by categorizing the resulting set of models and by analysing them for diversity. We then focus on how to exploit model diversity by comparing and combining different aspects of existing models. Finally, we discuss how model diversity came about in the past and could evolve in the future. Throughout our study, we use analogies from biodiversity research to analyse and interpret model diversity. We recommend to make models publicly available through open-source policies, to standardize documentation and technical implementation of models, and to compare models through ensemble modelling and interdisciplinary approaches. We end with our perspective on how the field of aquatic ecosystem modelling might develop in the next 5–10 years. To strive for clarity and to improve readability for non-modellers, we include a glossary. Close