Short-term hydropower optimization driven by innovative time-adapting econometric model

Avesani, Diego; Zanfei, Ariele; Marco, Nicola Di; Galletti, Andrea; Ravazzolo, Francesco; Righetti, Maurizio; Majone, Bruno

doi:10.1016/j.apenergy.2021.118510

Cited by 33 publications

(16 citation statements)

References 71 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The average annual precipitation ranges from 500 mm in the northwest of the region to 1600 mm in the southern part of the basin (Lutz et al, 2016;Diamantini et al, 2018;Laiti et al, 2018). A projected decrease in snowfall in winter and anticipated earlier snowmelt, essentially due to rising temperatures associated with global warming Gampe et al, 2016), will likely affect the Adige streamflow regime by the second half of the 21st century (Bard et al, 2015;Majone et al, 2016). This may have relevant consequences on water resources and hydropower production, which is particularly relevant in this region of the Alps (Zolezzi et al, 2009;Majone et al, 2016;Avesani et al, 2022); the reader is referred to Chiogna et al (2016) for a comprehensive review of the hydrological stressors acting in the Adige Basin as well as the area's ecological status.…”

Section: Study Areamentioning

confidence: 99%

Analysis of high streamflow extremes in climate change studies: how do we calibrate hydrological models?

Majone

Avesani

Zulian

et al. 2022

Hydrol. Earth Syst. Sci.

Self Cite

View full text Add to dashboard Cite

Abstract. Climate change impact studies on hydrological extremes often rely on hydrological models with parameters inferred through calibration procedures using observed meteorological data as input forcing. We show that this procedure can lead to a biased evaluation of the probability distribution of high streamflow extremes when climate models are used. As an alternative approach, we introduce a methodology, coined “Hydrological Calibration of eXtremes” (HyCoX), in which the calibration of the hydrological model, as driven by climate model output, is carried out by maximizing the probability that the modeled and observed high streamflow extremes belong to the same statistical population. The application to the Adige River catchment (southeastern Alps, Italy) by means of HYPERstreamHS, a distributed hydrological model, showed that this procedure preserves statistical coherence and produces reliable quantiles of the annual maximum streamflow to be used in assessment studies.

show abstract

Section: Study Areamentioning

confidence: 99%

Analysis of high streamflow extremes in climate change studies: how do we calibrate hydrological models?

Majone

Avesani

Zulian

et al. 2022

Hydrol. Earth Syst. Sci.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Indeed, streamflow forecasting is considered a paramount focus in hydrological research, as emphasized in recent studies like [56,57]. Different temporal resolution and lead time of the prediction are based on the kind of application, such as energy production [2], water supply systems [62] and floods [5]. In Alpine Regions, the complexity increases due to the spatial heterogeneity of the area, which mainly influences the temperature and precipitation variability [8,51].…”

Section: Introductionmentioning

confidence: 99%

Exploring the Feasibility of Data-Driven Models for Short-Term Hydrological Forecasting in South Tyrol: Challenges and Prospects

Torre,

Lombardi,

Menapace

et al. 2023

Preprint

Self Cite

View full text Add to dashboard Cite

Short-term hydrological forecasting is crucial for suitable multipurpose water resource management involving water uses, hydrological security, and renewable production. In the Alpine Regions such as South Tyrol, characterized by several small watersheds, quick information is essential to feed the decision processes in critical cases such as flood events. Predicting water availability ahead is equally crucial for optimizing resource utilization, such as irrigation or snow-making. The increasing data availability and computational power led to data-driven models becoming a serious alternative to physically based hydrological models, especially in complex conditions such as the Alpine Region and for short predictive horizons. This paper proposes a data-driven pipeline to use the local ground station data to infer information in a Support Vector Regression model, which can forecast streamflow in the main closure points of the area at hourly resolution with 48 hours of lead time. The main steps of the pipeline are analysed and discussed, with promising results that depend on available information, watershed complexity, and human interactions in the catchment. The presented pipeline, as it stands, offers an accessible tool for integrating these models into decision-making processes to guarantee real-time streamflow information at several points of the hydrological network. Discussion enhances the potentialities, open challenges, and prospects of short-term streamflow forecasting to accommodate broader studies.

show abstract

“…Throughout human history, dams/reservoirs have served to increase the discharge of low flows to ensure adequate water supply services, irrigation, recharge of groundwater, pollution abatement, wildlife conservation, industrial use, recreation, storing water in times of surplus, hydropower and releasing it in times of shortage [1][2][3]. Mitigating floods and making a significant contribution to the efficient management of limited water resources that are unevenly distributed and subject to large seasonal fluctuations [4,5] are key contributions of dams/reservoirs.…”

Section: Introductionmentioning

confidence: 99%

Introducing the Circularity Index for Dams/Reservoirs (CIDR)

Patino-Alonso

Espejo

Zazo

et al. 2023

Water

View full text Add to dashboard Cite

The world currently faces significant hydrologic changes associated with global climate change, such as changes in precipitation patterns, rising surface temperature, and increases in the frequency and intensity of floods and droughts, which will affect the design capacity and operating characteristics of dams/reservoirs. This brings new challenges to current water management strategies. This research is aimed to create, apply, and provide a novel indicator named Circularity Index for Dams/Reservoirs (CIDR) that allows the determination of the water circularity level on the dual dam/reservoir system; that is to evaluate the water efficiency levels and the circular water flows for the processes at a site. This new method has hydrological, economic, and environmental variables as well as social ones. This indicator is defined as the sum of the scores of the eleven indicators comprising the model multiplied by the weight. The method has been implemented giving the same weight for each indicator. It has been successfully applied in the 18 dam/reservoir systems managed by the Duero River Basin, located in the region of “Castilla y León” (Spain). The CIDR provides maximum information in a single indicator value ranging from 0 to 55. A higher value of CIDR indicates a better practice of water circularity management. The results probe the increased utility of the index and suggest that six dams/reservoirs present high circularity of water flow.

show abstract

Short-term hydropower optimization driven by innovative time-adapting econometric model

Cited by 33 publications

References 71 publications

Analysis of high streamflow extremes in climate change studies: how do we calibrate hydrological models?

Analysis of high streamflow extremes in climate change studies: how do we calibrate hydrological models?

Exploring the Feasibility of Data-Driven Models for Short-Term Hydrological Forecasting in South Tyrol: Challenges and Prospects

Introducing the Circularity Index for Dams/Reservoirs (CIDR)

Contact Info

Product

Resources

About