This study has been carried out in the PRIN project “Enterprising”, aiming to monitor and model river flow processes during floods. In this context, in my work, I dealt with the impact of hydrodynamic processes on river biotic communities (exploited as biological sensors), miniaturized gauges, and theoretical methods. Therefore, the aims of the present PhD work followed different paths that share a fascinating common phenomenology, trying to form a robust and consistent understanding of some relevant aspects. The work can be described through the following list of separate activities: 1) evaluating the impact of external stressors on aquatic ecosystems directly by using biotic communities as real-time indicators; 2) developing low-cost sy stems for monitoring bedload and suspended sediment transport; and 3) developing sediment transport theories based on Entropic theory. In the following, I provide a summary of each of these three aspects.Future climate scenarios predict an increase in the frequency and intensity of extreme events; thus, it is crucial to understand how flood conditions affect biotic communities in aquatic ecosystems. In this study, freshwater mussels (FM), as reliable bioindicators for detecting environmental disturbances in aquatic ecosystems, were utilized. We performed experiments in a laboratory flume to evaluate the suitability of using FM for developing a tailored real-time biological early warning system (BEWS) for disturbances in the aquatic ecosystem. Stressors inducing such disturbances may be external (i.e., anthropic) or internal (i.e., floods). In particular, we used the valvometric technique to measure the FMs’ behaviour when subjected to increasing discharges/sediment transport in laboratory experiments, mimicking the onset of floods. On 30 March 2022, after laboratory validation, the FM system was installed at the Paglia River in Orvieto, where a gauging station was available for monitoring water level and discharge. On March 31st a flood occurred, which was recorded by the gauging station at the project site. This event caused a visible change in the individual FM behaviour, which was clearly evident when the gaping signals were analysed using the Continuous Wavelet Transform (CWT), a technique that proved particularly suitable for characterising FM behaviour also in laboratory experiments. Besides FM investigation, two low-cost systems for continuous monitoring of streambed scour/deposition and turbidity were introduced and tested in laboratory. We exploited a vertical string of photoresistors, partially buried in the sediments and used as streambed detector. Different river bed dynamics were considered for testing the streambed measurement device: propagation of sediment front and scour dynamics in different points around a pier of a bridge. The performance of the turbidimeter device was examined in the flume with the flow turbidity undergoing increasing and decreasing stepwise variations. Both measurement devices provided convincing results and showed the potential for being used in the field. Finally, as far as the theoretical contribution to the Enterprising project was concerned, two different types of sediment transport theories, ordinary bedload, and intense bedload, were developed, based on Entropy theory. Estimation of the velocity distribution based on the Entropy probability density function was developed and applied in past works with the lack of information about the sediment discharge. In this study, by using surface velocity, we were able to link the sediment discharge to the statistics of particle resting time at low Shields stress (ordinary bedload). This approach was subsequently applied to data on one cross-section of Adige River (Bolzano, Northern Italy), and also on Estero Morales River (Chile). As far as the comparison of theory and field measurements was possible, it looked satisfactorily. For the case of intense sediment transport (high Shields values), the extended kinetic theory has been applied to unidirectional steady-uniform flow through a statistic-mechanical model endowed with entropic information on the concentration profile. This made the solution pseudo-analytical, which can be straightforwardly achieved (without numerical approximation tools), and with great advantage in the understanding of the role of any terms in the physical balances. Overall, during my PhD project, because of its interdisciplinary nature, I encountered numerous challenges. At the same time, I experienced collaboration and multidisciplinary joint efforts, which enabled me to gain a more comprehensive understanding of the problem from a variety of perspectives. Consequently, I and my supervisors gained a deeper understanding of the nature of hydrodynamic effects on ecosystem biotic communities, which was the main objective of the project “Enterprising”, along with a novel awareness of how the entropic theory can be used in sediment transport and how the advancing technology can support the endless need of monitoring resources.
Bio-sensors and Miniaturized Technology for Fine Sediments Monitoring in Laboratory and Field Sites, Associated with Entropic Interpretation of Ordinary and Intense Bed-load
Pilbala, Ashkan
2024
Abstract
This study has been carried out in the PRIN project “Enterprising”, aiming to monitor and model river flow processes during floods. In this context, in my work, I dealt with the impact of hydrodynamic processes on river biotic communities (exploited as biological sensors), miniaturized gauges, and theoretical methods. Therefore, the aims of the present PhD work followed different paths that share a fascinating common phenomenology, trying to form a robust and consistent understanding of some relevant aspects. The work can be described through the following list of separate activities: 1) evaluating the impact of external stressors on aquatic ecosystems directly by using biotic communities as real-time indicators; 2) developing low-cost sy stems for monitoring bedload and suspended sediment transport; and 3) developing sediment transport theories based on Entropic theory. In the following, I provide a summary of each of these three aspects.Future climate scenarios predict an increase in the frequency and intensity of extreme events; thus, it is crucial to understand how flood conditions affect biotic communities in aquatic ecosystems. In this study, freshwater mussels (FM), as reliable bioindicators for detecting environmental disturbances in aquatic ecosystems, were utilized. We performed experiments in a laboratory flume to evaluate the suitability of using FM for developing a tailored real-time biological early warning system (BEWS) for disturbances in the aquatic ecosystem. Stressors inducing such disturbances may be external (i.e., anthropic) or internal (i.e., floods). In particular, we used the valvometric technique to measure the FMs’ behaviour when subjected to increasing discharges/sediment transport in laboratory experiments, mimicking the onset of floods. On 30 March 2022, after laboratory validation, the FM system was installed at the Paglia River in Orvieto, where a gauging station was available for monitoring water level and discharge. On March 31st a flood occurred, which was recorded by the gauging station at the project site. This event caused a visible change in the individual FM behaviour, which was clearly evident when the gaping signals were analysed using the Continuous Wavelet Transform (CWT), a technique that proved particularly suitable for characterising FM behaviour also in laboratory experiments. Besides FM investigation, two low-cost systems for continuous monitoring of streambed scour/deposition and turbidity were introduced and tested in laboratory. We exploited a vertical string of photoresistors, partially buried in the sediments and used as streambed detector. Different river bed dynamics were considered for testing the streambed measurement device: propagation of sediment front and scour dynamics in different points around a pier of a bridge. The performance of the turbidimeter device was examined in the flume with the flow turbidity undergoing increasing and decreasing stepwise variations. Both measurement devices provided convincing results and showed the potential for being used in the field. Finally, as far as the theoretical contribution to the Enterprising project was concerned, two different types of sediment transport theories, ordinary bedload, and intense bedload, were developed, based on Entropy theory. Estimation of the velocity distribution based on the Entropy probability density function was developed and applied in past works with the lack of information about the sediment discharge. In this study, by using surface velocity, we were able to link the sediment discharge to the statistics of particle resting time at low Shields stress (ordinary bedload). This approach was subsequently applied to data on one cross-section of Adige River (Bolzano, Northern Italy), and also on Estero Morales River (Chile). As far as the comparison of theory and field measurements was possible, it looked satisfactorily. For the case of intense sediment transport (high Shields values), the extended kinetic theory has been applied to unidirectional steady-uniform flow through a statistic-mechanical model endowed with entropic information on the concentration profile. This made the solution pseudo-analytical, which can be straightforwardly achieved (without numerical approximation tools), and with great advantage in the understanding of the role of any terms in the physical balances. Overall, during my PhD project, because of its interdisciplinary nature, I encountered numerous challenges. At the same time, I experienced collaboration and multidisciplinary joint efforts, which enabled me to gain a more comprehensive understanding of the problem from a variety of perspectives. Consequently, I and my supervisors gained a deeper understanding of the nature of hydrodynamic effects on ecosystem biotic communities, which was the main objective of the project “Enterprising”, along with a novel awareness of how the entropic theory can be used in sediment transport and how the advancing technology can support the endless need of monitoring resources.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.14242/179495
URN:NBN:IT:UNITN-179495