M.E. McClain
Please Note
8 records found
1
The objective of this work is motivated by a somewhat naïve, almost childish, question: “Is it possible to pick up a stone from a river and determine, just by measuring its shape, how far it has travelled?” Being able to answer this question reliably and accurately would create valuable opportunities to improve our understanding of river systems, to enhance restoration practices, infrastructure planning, and management, and to reduce natural hazards. Accurately identifying sediment pathways based on an easily measurable property would, for example, allow us to select which reaches in a network should be left free to flow, since they convey most of the sediments, or which should be more protected from erosion, since they represent major sediment sources.... ...
The objective of this work is motivated by a somewhat naïve, almost childish, question: “Is it possible to pick up a stone from a river and determine, just by measuring its shape, how far it has travelled?” Being able to answer this question reliably and accurately would create valuable opportunities to improve our understanding of river systems, to enhance restoration practices, infrastructure planning, and management, and to reduce natural hazards. Accurately identifying sediment pathways based on an easily measurable property would, for example, allow us to select which reaches in a network should be left free to flow, since they convey most of the sediments, or which should be more protected from erosion, since they represent major sediment sources....
The River Rotte Fish Migration Project
A bayesian Network approach for fish habitat suitability
The aim of this thesis is to develop an ecological model for fish habitat suitability in the river Rotte basin in the Netherlands that can be used in policy development for ecological restoration. The model serves as a decision support system to explain differences in fish population and evaluate the impact of management actions to modify fish habitat suitability. The river Rotte suits perfectly for this case study, because recently a fish passage has been realised between the Rotte and Nieuwe Maas to facilitate fish migration and expand living conditions. Furthermore, the river Rotte is a designated WFD water body, but the current status of the river varies between "poor" and "moderate" due to an unbalance between plant-loving and benthivorous fish species.
The model developed in this thesis is a Bayesian Belief Network model that predicts habitat factors for food preference and preference for habitat structure. The model is based on machine learning with a set of cases from monitoring data and predicts the probability distribution for fish habitat suitability for plant-loving and benthivorous fish species. The model has been applied to assess the impact of local conditions on fish habitat differentiation and to evaluate the impact of management actions on fish habitat suitability. The research shows that the Bayesian Belief Network model is very useable for policy making and facilitates the participation of various stakeholders. However, the current version of the model shows inadequate prediction accuracy and relies heavily on sampling data. This can be improved by expanding the scope of the model to include other water bodies in the Netherlands and by using metamodels for specific model variables.
Overall, the Bayesian Belief Network model is functional and usable for policy making, but further improvements are needed to enhance its prediction accuracy. This can be achieved through expanding the model's scope, evaluating its performance, and including more habitat factors in the model structure.
...
The aim of this thesis is to develop an ecological model for fish habitat suitability in the river Rotte basin in the Netherlands that can be used in policy development for ecological restoration. The model serves as a decision support system to explain differences in fish population and evaluate the impact of management actions to modify fish habitat suitability. The river Rotte suits perfectly for this case study, because recently a fish passage has been realised between the Rotte and Nieuwe Maas to facilitate fish migration and expand living conditions. Furthermore, the river Rotte is a designated WFD water body, but the current status of the river varies between "poor" and "moderate" due to an unbalance between plant-loving and benthivorous fish species.
The model developed in this thesis is a Bayesian Belief Network model that predicts habitat factors for food preference and preference for habitat structure. The model is based on machine learning with a set of cases from monitoring data and predicts the probability distribution for fish habitat suitability for plant-loving and benthivorous fish species. The model has been applied to assess the impact of local conditions on fish habitat differentiation and to evaluate the impact of management actions on fish habitat suitability. The research shows that the Bayesian Belief Network model is very useable for policy making and facilitates the participation of various stakeholders. However, the current version of the model shows inadequate prediction accuracy and relies heavily on sampling data. This can be improved by expanding the scope of the model to include other water bodies in the Netherlands and by using metamodels for specific model variables.
Overall, the Bayesian Belief Network model is functional and usable for policy making, but further improvements are needed to enhance its prediction accuracy. This can be achieved through expanding the model's scope, evaluating its performance, and including more habitat factors in the model structure.
Let It Flow: Implementation of Environmental Flows In Dutch Water Management
Identifying challenges and opportunities
What Wets the Wetlands?
Reconstructing the Mara Wetland surface water dynamics through coupling satellite derived inundation patterns with hydrological field data
In this study, the spatiotemporal inundation pattern of the Mara Wetland in Tanzania is reconstructed using optical remote sensing data. The annual fluctuations in aerial wetland extent are analysed in parallel to the fluctuations of local water balance components: downstream water level of Lake Victoria, upstream discharge, direct precipitation and evaporation. The analyses aims to shed light on the underlying mechanisms and hydrological processes that control the hydric status of the wetland. Comparing the temporal changes in extent with surrounding physical processes provides insight on the responsiveness of the wetland to specific water balance components.
The intra- and inter-annual trends in inundation of the Mara Wetland are reproduced for the years 2017, 2018, 2019. The Random Forests (RF) algorithm is trained bi-seasonally (using bands and derived water and vegetation indices from Sentinel-2 data and a Digital Elevation Model (DEM) as input variables), and used to classify the land-covers of the wetland region in a semi-automated way for a total of 73 Sentinel-2 scenes. The scenes are classified into 7 individual land-cover classes; 3 wetland classes (open water, flooded vegetation, wet floodplain) and 4 dryland classes (dry floodplain, wet agriculture, dry agriculture, bare land). The overall classification accuracy achieved (based on an independent validation set, not used to train the classification algorithm) is 98.6 %. The spatiotemporal variability of the inundated area is used in combination with available hydrological field-data to reproduce the local water balance.
The seasonal expansion and contraction of the wetland follows a consistent bi-modal regime, and the results from the waterbalance affirm the importance of local precipitation in the seasonal expansion and contraction of the wetland. The base-flow supplied by the Mara River, together with the backwater from Lake Victoria appear to be at equilibrium at the extent of the permanent swamp during the dry season, insinuating the importance of the riverflow during these low-rainfall months. The occasional yet extreme flood events induced by high discharge rates are expected to play a specific ecological role in the wetland, and should be accounted for during future dam operations upstream. ...
In this study, the spatiotemporal inundation pattern of the Mara Wetland in Tanzania is reconstructed using optical remote sensing data. The annual fluctuations in aerial wetland extent are analysed in parallel to the fluctuations of local water balance components: downstream water level of Lake Victoria, upstream discharge, direct precipitation and evaporation. The analyses aims to shed light on the underlying mechanisms and hydrological processes that control the hydric status of the wetland. Comparing the temporal changes in extent with surrounding physical processes provides insight on the responsiveness of the wetland to specific water balance components.
The intra- and inter-annual trends in inundation of the Mara Wetland are reproduced for the years 2017, 2018, 2019. The Random Forests (RF) algorithm is trained bi-seasonally (using bands and derived water and vegetation indices from Sentinel-2 data and a Digital Elevation Model (DEM) as input variables), and used to classify the land-covers of the wetland region in a semi-automated way for a total of 73 Sentinel-2 scenes. The scenes are classified into 7 individual land-cover classes; 3 wetland classes (open water, flooded vegetation, wet floodplain) and 4 dryland classes (dry floodplain, wet agriculture, dry agriculture, bare land). The overall classification accuracy achieved (based on an independent validation set, not used to train the classification algorithm) is 98.6 %. The spatiotemporal variability of the inundated area is used in combination with available hydrological field-data to reproduce the local water balance.
The seasonal expansion and contraction of the wetland follows a consistent bi-modal regime, and the results from the waterbalance affirm the importance of local precipitation in the seasonal expansion and contraction of the wetland. The base-flow supplied by the Mara River, together with the backwater from Lake Victoria appear to be at equilibrium at the extent of the permanent swamp during the dry season, insinuating the importance of the riverflow during these low-rainfall months. The occasional yet extreme flood events induced by high discharge rates are expected to play a specific ecological role in the wetland, and should be accounted for during future dam operations upstream.
Parched Kaveri
A preliminary assessment of flow alteration and ecological condition of sub-basins of Kaveri river using global datasets
Environmental flows forms the link between ecological health of a river and the ecosystem services we derive from it. It can be a great tool to achieve twin objective of maintaining the ecosystem integrity of freshwater habitats and deciding trade-offs for ensuring sustainable water management in a river basin. This study focuses on developing a holistic methodology for preliminary assessment of ecosystem integrity or ecological health of a river basin, which can be easily adapted to other river basins using open source global datasets. The proposed methodology was applied to Kaveri basin to test its applicability and identify the limitations of available global datasets. A widely accepted regional environmental flow assessment framework, ELOHA (Ecological Limits of Hydrological Alteration) was adapted by using global datasets. A global river classification dataset was used to identify the river classes in Kaveri basin. Monthly hydrological alteration in magnitude at the location of gauge stations was calculated, using PCR-GLOBWB data as reference for natural flow conditions, in absence of records for natural flow in a highly modified Kaveri basin. An ecosystem integrity indicator framework was developed to assess the hydrologic, geomorphic and ecological modifications in the river basin. Indicators grouped under four main categories - Connectivity status, Land Use, Biodiversity, Water Quality were adopted using exiting global datasets and values for all the sub-basins of Kaveri basin were estimated.
Finally an attempt to derive flow alteration-ecological response was made. Threatened fish species percentage, quantified using IUCN spatial dataset, showed an increase in value with increase in alteration in flow magnitude. No clear relationship was observed when data for other taxonomic groups like plants, molluscs, odonata, shrimps and crabs were used. Hence, species of concern (IUCN red list category - CR, EN,VU) data can be useful in deriving preliminary flow alteration-ecological response relationship. An attempt to find linkage between flow alteration and floodplain gross primary productivity was also made. In dry season an inverse relationship was observed at few gauge stations but in general other climatic factors like rainfall and evapotranspiration had greater influence on gross primary productivity. Impact on gross primary productivity due to flow alteration could not be isolated using existing datasets because of coarse resolution. ...
Environmental flows forms the link between ecological health of a river and the ecosystem services we derive from it. It can be a great tool to achieve twin objective of maintaining the ecosystem integrity of freshwater habitats and deciding trade-offs for ensuring sustainable water management in a river basin. This study focuses on developing a holistic methodology for preliminary assessment of ecosystem integrity or ecological health of a river basin, which can be easily adapted to other river basins using open source global datasets. The proposed methodology was applied to Kaveri basin to test its applicability and identify the limitations of available global datasets. A widely accepted regional environmental flow assessment framework, ELOHA (Ecological Limits of Hydrological Alteration) was adapted by using global datasets. A global river classification dataset was used to identify the river classes in Kaveri basin. Monthly hydrological alteration in magnitude at the location of gauge stations was calculated, using PCR-GLOBWB data as reference for natural flow conditions, in absence of records for natural flow in a highly modified Kaveri basin. An ecosystem integrity indicator framework was developed to assess the hydrologic, geomorphic and ecological modifications in the river basin. Indicators grouped under four main categories - Connectivity status, Land Use, Biodiversity, Water Quality were adopted using exiting global datasets and values for all the sub-basins of Kaveri basin were estimated.
Finally an attempt to derive flow alteration-ecological response was made. Threatened fish species percentage, quantified using IUCN spatial dataset, showed an increase in value with increase in alteration in flow magnitude. No clear relationship was observed when data for other taxonomic groups like plants, molluscs, odonata, shrimps and crabs were used. Hence, species of concern (IUCN red list category - CR, EN,VU) data can be useful in deriving preliminary flow alteration-ecological response relationship. An attempt to find linkage between flow alteration and floodplain gross primary productivity was also made. In dry season an inverse relationship was observed at few gauge stations but in general other climatic factors like rainfall and evapotranspiration had greater influence on gross primary productivity. Impact on gross primary productivity due to flow alteration could not be isolated using existing datasets because of coarse resolution.
Determining Mexican climate-adaptive environmental flows reference values for people and nature
A hydrology-based approach for preventive environmental water allocation
The aim of this research is to evaluate the effect of different flushing operation scenarios on the physical habitats at the ecologically relevant meso-scale. An idealised, depth-averaged hydro-morphodynamic model is set up in Delft3D-Flow, a modelling software package developed by Deltares. The model represents a reach of the Avisio, a river situated in the Eastern Italian Alps. Across this river, the Pezzè dam was built in 1952, trapping all incoming sediments. Every three years the dam is flushed, which gained more public attention over the last years. A specific reach was chosen as a reference case as it consists of a channel bar topography where fine sediments accumulate up to ten times more during a flushing event than in other, more channelised reaches. It is therefore considered the most affected by the flushing event. The reach has a length of roughly a kilometre and is situated 10 kilometres downstream of the dam.
The hydro-morphodynamic model assumes a non-erodible bed, as the coarsened river bed is not expected to move significantly during a flushing event. This bed has the shape of an alternate bar topography. The simulation of the flushing event is simplified as an influx of bed load transport with a fraction size of one millimetre, and a magnitude close to the equilibrium transport capacity. Deposition occurs upstream and to a higher extent downstream of the bars, where flow velocities are low and secondary flow aids the movement of sediments into these areas. Subsequently, a clean water peak is imposed to investigate its effectiveness in removing the fine sediments from the reach. The hydrograph of this peak is varied in shape, duration and magnitude to simulate different operation scenarios and natural rainfall runoff events.
By applying the Mesohabitat Evaluation Model (MEM), a habitat suitability model developed for the meso-scale, it was possible to divide the reach into classes based on flow velocity, flow depth and shear stress. Such classification highly depends on the governing discharge. The classes are mainly distinctive by the division between high and low energy classes and in this way show a high correlation to the deposition of fines. The model suggests that fine sediments remain in the system only when low energy classes are present. Although the MEM classification aims at the meso-scale, it follows a micro-scale approach and therefore undermines the advantages of assessment at the ecologically more relevant meso-scale. It is recommended to develop the MEM-procedure by accounting for neighbouring computational cells.
The MEM-procedure gives an useful indication of the spatial variety in deposition and erosion patterns. It however does not provide insight into the implications of sedimentation to the ecology, without the coupling with a biological model. Such a biological model describes the suitability of the physical habitat for a specific organism and thereby incorporates a functional goal.
As such a biological model could, due to time restrictions, not be applied in this research it was chosen to perform a micro-scale based suitability study. This illustrates the potential of morphodynamic modelling as a tool for habitat suitability modelling. Simplified preference curves were derived for spawning trout, of which the physical habitat requirements are sensitive to the deposition of fine sediments. It was found that the deposition of fine sediments hardly effects this habitat. When required nonetheless, any considered peak flow recovers a substantial amount of suitable habitat. This implies that, if a clean water peak of a sufficient magnitude follows the flushing operation, the impact on the spawning habitat, and probably any habitat, is minimal.
Whether such a clean water peak occurs, can be partly controlled by the dam operation, but also depends on the hydrology of the catchment. A ten-year hydrological time series of the Avisio river, measured upstream of the dam, shows that the catchment of this reservoir does not provide sufficient water to guarantee a clean water peak during any season. However, with the significant contribution of two tributaries that flow into the Avisio river between the dam and the reference reach, it is highly probable that a peak flow of sufficient magnitude occurs during high flow season. To ensure the benefits of a clean water peak, it is recommended to plan the flushing event at the start of the high water season, which lasts from May to July. For other rivers, it might be possible to adopt such a clean water peak as part of the flushing operation strategy, providing a higher level of control. Even though this study suggests that the implications of the flushing event to the physical habitats are minimal, and of no comparison to the potential direct impacts, this method of evaluation shows potential to assess other morphological relevant events and even long term morphological changes.
...
The aim of this research is to evaluate the effect of different flushing operation scenarios on the physical habitats at the ecologically relevant meso-scale. An idealised, depth-averaged hydro-morphodynamic model is set up in Delft3D-Flow, a modelling software package developed by Deltares. The model represents a reach of the Avisio, a river situated in the Eastern Italian Alps. Across this river, the Pezzè dam was built in 1952, trapping all incoming sediments. Every three years the dam is flushed, which gained more public attention over the last years. A specific reach was chosen as a reference case as it consists of a channel bar topography where fine sediments accumulate up to ten times more during a flushing event than in other, more channelised reaches. It is therefore considered the most affected by the flushing event. The reach has a length of roughly a kilometre and is situated 10 kilometres downstream of the dam.
The hydro-morphodynamic model assumes a non-erodible bed, as the coarsened river bed is not expected to move significantly during a flushing event. This bed has the shape of an alternate bar topography. The simulation of the flushing event is simplified as an influx of bed load transport with a fraction size of one millimetre, and a magnitude close to the equilibrium transport capacity. Deposition occurs upstream and to a higher extent downstream of the bars, where flow velocities are low and secondary flow aids the movement of sediments into these areas. Subsequently, a clean water peak is imposed to investigate its effectiveness in removing the fine sediments from the reach. The hydrograph of this peak is varied in shape, duration and magnitude to simulate different operation scenarios and natural rainfall runoff events.
By applying the Mesohabitat Evaluation Model (MEM), a habitat suitability model developed for the meso-scale, it was possible to divide the reach into classes based on flow velocity, flow depth and shear stress. Such classification highly depends on the governing discharge. The classes are mainly distinctive by the division between high and low energy classes and in this way show a high correlation to the deposition of fines. The model suggests that fine sediments remain in the system only when low energy classes are present. Although the MEM classification aims at the meso-scale, it follows a micro-scale approach and therefore undermines the advantages of assessment at the ecologically more relevant meso-scale. It is recommended to develop the MEM-procedure by accounting for neighbouring computational cells.
The MEM-procedure gives an useful indication of the spatial variety in deposition and erosion patterns. It however does not provide insight into the implications of sedimentation to the ecology, without the coupling with a biological model. Such a biological model describes the suitability of the physical habitat for a specific organism and thereby incorporates a functional goal.
As such a biological model could, due to time restrictions, not be applied in this research it was chosen to perform a micro-scale based suitability study. This illustrates the potential of morphodynamic modelling as a tool for habitat suitability modelling. Simplified preference curves were derived for spawning trout, of which the physical habitat requirements are sensitive to the deposition of fine sediments. It was found that the deposition of fine sediments hardly effects this habitat. When required nonetheless, any considered peak flow recovers a substantial amount of suitable habitat. This implies that, if a clean water peak of a sufficient magnitude follows the flushing operation, the impact on the spawning habitat, and probably any habitat, is minimal.
Whether such a clean water peak occurs, can be partly controlled by the dam operation, but also depends on the hydrology of the catchment. A ten-year hydrological time series of the Avisio river, measured upstream of the dam, shows that the catchment of this reservoir does not provide sufficient water to guarantee a clean water peak during any season. However, with the significant contribution of two tributaries that flow into the Avisio river between the dam and the reference reach, it is highly probable that a peak flow of sufficient magnitude occurs during high flow season. To ensure the benefits of a clean water peak, it is recommended to plan the flushing event at the start of the high water season, which lasts from May to July. For other rivers, it might be possible to adopt such a clean water peak as part of the flushing operation strategy, providing a higher level of control. Even though this study suggests that the implications of the flushing event to the physical habitats are minimal, and of no comparison to the potential direct impacts, this method of evaluation shows potential to assess other morphological relevant events and even long term morphological changes.