Variability of Temperature and Its Impact on Reference Evapotranspiration: The Test Case of the Apulia Region (Southern Italy)

Elferchichi, Abderraouf; Giorgio, Giuseppina Anna; Lamaddalena, Nicola; Ragosta, Maria; Telesca, Vito

doi:10.3390/su9122337

Cited by 17 publications

(13 citation statements)

References 49 publications

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“…The results included in this section intend to demonstrate the use of accurate and low computationally cost algorithms to monitor the flow of an artificial channel, serving mainly to collect water coming from springs and to [ 23 , 24 ] spill it into the sea. They fall within the hydrodynamics characterization of the channel with video-sensors and image-sensors [ 25 ].…”

Section: Resultsmentioning

confidence: 99%

Video-Sensing Characterization for Hydrodynamic Features: Particle Tracking-Based Algorithm Supported by a Machine Learning Approach

Lay-Ekuakille

Okitadiowo

Ugwiri

et al. 2021

Sensors

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The efficient and reliable monitoring of the flow of water in open channels provides useful information for preventing water slow-downs due to the deposition of materials within the bed of the channel, which might lead to critical floods. A reliable monitoring system can thus help to protect properties and, in the most critical cases, save lives. A sensing system capable of monitoring the flow conditions and the possible geo-environmental constraints within a channel can operate using still images or video imaging. The latter approach better supports the above two features, but the acquisition of still images can display a better accuracy. To increase the accuracy of the video imaging approach, we propose an improved particle tracking algorithm for flow hydrodynamics supported by a machine learning approach based on a convolutional neural network-evolutionary fuzzy integral (CNN-EFI), with a sub-comparison performed by multi-layer perceptron (MLP). Both algorithms have been applied to process the video signals captured from a CMOS camera, which monitors the water flow of a channel that collects rain water from an upstream area to discharge it into the sea. The channel plays a key role in avoiding upstream floods that might pose a serious threat to the neighboring infrastructures and population. This combined approach displays reliable results in the field of environmental and hydrodynamic safety.

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Section: Resultsmentioning

confidence: 99%

Video-Sensing Characterization for Hydrodynamic Features: Particle Tracking-Based Algorithm Supported by a Machine Learning Approach

Lay-Ekuakille

Okitadiowo

Ugwiri

et al. 2021

Sensors

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“…The monitoring of sudden and extreme events [ 1 ] through the use of real-time sensors and sensing systems can be of paramount importance for setting up the actions necessary to prevent further risks and damages.…”

Section: Introductionmentioning

confidence: 99%

Image Sensors for Wave Monitoring in Shore Protection: Characterization through a Machine Learning Algorithm

Lay-Ekuakille

Okitadiowo

Luccio

et al. 2021

Sensors

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Waves propagating on the water surface can be considered as propagating in a dispersive medium, where gravity and surface tension at the air–water interface act as restoring forces. The velocity at which energy is transported in water waves is defined by the group velocity. The paper reports the use of video-camera observations to study the impact of water waves on an urban shore. The video-monitoring system consists of two separate cameras equipped with progressive RGB CMOS sensors that allow 1080p HDTV video recording. The sensing system delivers video signals that are processed by a machine learning technique. The scope of the research is to identify features of water waves that cannot be normally observed. First, a conventional modelling was performed using data delivered by image sensors together with additional data such as temperature, and wind speed, measured with dedicated sensors. Stealth waves are detected, as are the inverting phenomena encompassed in waves. This latter phenomenon can be detected only through machine learning. This double approach allows us to prevent extreme events that can take place in offshore and onshore areas.

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“…The fifth report (AR5) issued by the Intergovernmental Panel on Climate Change (IPCC) in 2013 stated that the global surface temperature increased by 0.85 • C from 1880 to 2012 and would increase by 0.3 to 0.7 • C in the next 30 years. In addition, the report points out that human activities are the main cause of climate warming [1,2]. Climate change can lead to changes in global hydrological processes, including melting glaciers, rising sea levels, and deterioration of the living environment [3].…”

Section: Introductionmentioning

confidence: 99%

The Impact of Reservoirs on Runoff Under Climate Change: A Case of Nierji Reservoir in China

Men

Liu

Tian

et al. 2019

Water

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Reservoirs play an important role in responding to natural disasters (such as flood and drought) by controlling the runoff. With the climate changing, the frequency and intensity of flood and drought are likely to increase. Thus, the impact of reservoirs on runoff under climate change needs to be studied to cope with future floods and drought. In this study, the Nierji Reservoir located on the Nenjiang River Basin was chosen to explore the impact. The Nenjiany River Basin is the vital water source in the water resources transfer project in Northeast China. Climate change in Nenjiang River Basin was analyzed using the 1980 to 2013 climate observations. The results show that the temperature of the basin significantly (p < 0.05) increased while the precipitation significantly (p < 0.05) decreased. Based on the result, nine kinds of different climate scenarios were set up. For different climate scenarios, the Hydroinformatic Modeling System (HIMS) model and the HIMS model with the reservoir calculation module were used to simulate runoff during the no reservoir operation period (1980–2000) and reservoir operation period (2007–2013), respectively. The impact of reservoirs on runoff under climate change is studied. Results show that the Nierji Reservoir can effectively relieve the impact of climate change on downstream runoff. When temperature increases or precipitation decreases, there are larger differences in runoff over the non-flood period, especially during periods of no reservoir operation. Reservoir operation under climate change can provide reliability in drought protection.

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Variability of Temperature and Its Impact on Reference Evapotranspiration: The Test Case of the Apulia Region (Southern Italy)

Cited by 17 publications

References 49 publications

Video-Sensing Characterization for Hydrodynamic Features: Particle Tracking-Based Algorithm Supported by a Machine Learning Approach

Video-Sensing Characterization for Hydrodynamic Features: Particle Tracking-Based Algorithm Supported by a Machine Learning Approach

Image Sensors for Wave Monitoring in Shore Protection: Characterization through a Machine Learning Algorithm

The Impact of Reservoirs on Runoff Under Climate Change: A Case of Nierji Reservoir in China

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