4.6 Article

A Combined Clustering and Trends Analysis Approach for Characterizing Reference Evapotranspiration in Veneto

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Environmental Sciences

Trend Analysis and Identification of the Meteorological Factors Influencing Reference Evapotranspiration

Tagele Mossie Aschale et al.

Summary: Investigating the trends and sensitivity of reference evapotranspiration (ETo) to meteorological variables is important for water resource management and climate variability analysis. This study analyzed a 17-year dataset from a Mediterranean climate region and found a downward trend in ETo in November, as well as downward trends in solar radiation and rainfall during autumn. Other meteorological variables showed an upward trend, with specific humidity and wind speed having the highest and lowest contribution to ETo trends, respectively.
Article Agronomy

Future trends of reference evapotranspiration in Sicily based on CORDEX data and Machine Learning algorithms

Fabio Di Nunno et al.

Summary: The study evaluated the reference evapotranspiration in Sicily using historical and future climate parameters, and divided the region into three homogeneous areas using a hierarchical algorithm. Machine learning algorithms were then used to forecast future evapotranspiration. The results showed that evapotranspiration increased for all three regions during the forecast period, with higher increases observed in the inland areas. This approach provides a comprehensive analysis of evapotranspiration trends in different regions.

AGRICULTURAL WATER MANAGEMENT (2023)

Article Engineering, Environmental

Spatio-temporal analysis of drought in Southern Italy: a combined clustering-forecasting approach based on SPEI index and artificial intelligence algorithms

Fabio Di Nunno et al.

Summary: By dividing Southern Italy into homogeneous drought regions using three clustering algorithms (K-mean, Hierarchical, and Expectation-Maximization), reliable prediction of spatio-temporal drought variation can be achieved. This study utilized gridded data of the Standardized Precipitation Evapotranspiration Index (SPEI6) to assess drought trends and developed Machine Learning (ML) algorithms for forecasting drought events. The hybrid M5P-SVR model outperformed individual M5P and SVR models, making it suitable for forecasting long and severe drought events.

STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT (2023)

Article Environmental Sciences

Spatial-temporal variations of terrestrial evapotranspiration across China from 2000 to 2019

Jing Fu et al.

Summary: This study investigated the spatiotemporal variations of terrestrial evapotranspiration (ET) in China from 2000 to 2019 and analyzed the driving factors behind these changes. The results showed that climate variation, including increasing precipitation and wind speed, had a significant impact on ET. The study also found that increasing temperature, decreasing sunshine duration and relative humidity contributed to the increase in ET to some extent. The findings provide valuable insights into the role of climate variability in hydrological processes and the potential impacts of ET variability on the climate system.

SCIENCE OF THE TOTAL ENVIRONMENT (2022)

Article Environmental Sciences

The Complex and Spatially Diverse Patterns of Hydrological Droughts Across Europe

D. Pena-Angulo et al.

Summary: This study presents a new data set of gauged streamflow for Europe and assesses changes in the characteristics of hydrological droughts across different regions. Results reveal complex spatial patterns of hydrological droughts in Europe over the past six decades, with more frequent and severe droughts in southern and central Europe and opposite trends in northern Europe.

WATER RESOURCES RESEARCH (2022)

Article Green & Sustainable Science & Technology

Are We Adapting to Climate Change? Evidence from the High-Quality Agri-Food Sector in the Veneto Region

Dana Salpina et al.

Summary: Adaptation to climate change is crucial for the agri-food sector, particularly for Geographic Indications (GIs). The level of concern and implementation of adaptation measures varies depending on the type of GI, crop system, and altitude of production areas. Multiple barriers to adaptation are identified. Recommendations include recognizing the functions of Consortia and Producers Organizations, expanding adaptation strategies beyond GIs, and developing participatory knowledge provision systems.

SUSTAINABILITY (2022)

Article Geosciences, Multidisciplinary

Streamflow trends in the Tigris river basin using Mann-Kendall and innovative trend analysis methods

Veysel Gumus et al.

Summary: This study determines the trends of streamflow values in the Tigris basin, Turkey, using the Mann-Kendall test and innovative trend analysis method. The results show a significant decrease in streamflow in most of the gauge stations, particularly in the middle region of the basin.

JOURNAL OF EARTH SYSTEM SCIENCE (2022)

Article Engineering, Civil

Streamflow Variations in Monthly, Seasonal, Annual and Extreme Values Using Mann-Kendall, Spearmen's Rho and Innovative Trend Analysis

Muhammad S. Ashraf et al.

Summary: This study investigates variations in streamflow at 20 stations in the upper Indus river basin using different methods, finding that extremely low flows are increasing more significantly than extremely high flows. This may lead to constant pressure on water resources availability in the lower Indus plains where agricultural activities are dependent.

WATER RESOURCES MANAGEMENT (2021)

Article Meteorology & Atmospheric Sciences

Spatiotemporal trends in reference evapotranspiration and its driving factors in Bangladesh

Jannatun Nahar Jerin et al.

Summary: This study examined the spatiotemporal variations in ETo and the factors influencing these variations in Bangladesh using various analytical methods. The research revealed an evapotranspiration paradox in Bangladesh and demonstrated that meteorological factors have varying impacts on ETo.

THEORETICAL AND APPLIED CLIMATOLOGY (2021)

Article Engineering, Environmental

Artificial Intelligence models for prediction of the tide level in Venice

Francesco Granata et al.

Summary: The study developed several different tidal forecast models, with models based on Artificial Intelligence algorithms performing well. The M5P algorithm showed the best performance in most cases, accurately predicting tide levels in Venice. Good predictions were achieved even when meteorological factors were neglected.

STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT (2021)

Article Environmental Sciences

Forecasting of Extreme Storm Tide Events Using NARX Neural Network-Based Models

Fabio Di Nunno et al.

Summary: Extreme values of high tides are influenced by various factors, prompting the development of a system in Venice to protect the city from flooding caused by the highest tides. Previous research has successfully predicted these extreme values using NARX neural networks, with two distinct models demonstrating high accuracy.

ATMOSPHERE (2021)

Article Agronomy

Forecasting evapotranspiration in different climates using ensembles of recurrent neural networks

Francesco Granata et al.

Summary: This study developed three Recurrent Neural Network-based models for short-term ahead actual evapotranspiration prediction using deep learning algorithms. The LSTM models were more accurate than NARX models under subtropical climatic conditions in South Florida, while NARX models generally provided more accurate results in the semi-arid climate of Central Nevada.

AGRICULTURAL WATER MANAGEMENT (2021)

Article Meteorology & Atmospheric Sciences

Regionalization of evapotranspiration using fuzzy dynamic clustering approach. Part 1: Formation of regions in India

Swapan K. Masanta et al.

INTERNATIONAL JOURNAL OF CLIMATOLOGY (2020)

Article Green & Sustainable Science & Technology

Common agricultural policy and sustainable management of areas with natural handicaps. The Veneto Region case study

Maria Bruna Zolin et al.

ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY (2020)

Article Meteorology & Atmospheric Sciences

Innovative trend analysis of annual and seasonal rainfall and extreme values in Shaanxi, China, since the 1950s

Hao Wu et al.

INTERNATIONAL JOURNAL OF CLIMATOLOGY (2017)

Article Multidisciplinary Sciences

Flood dynamics in urbanised landscapes: 100 years of climate and humans' interaction

G. Sofia et al.

SCIENTIFIC REPORTS (2017)

Article Meteorology & Atmospheric Sciences

Clustering of Regional-Scale Extreme Precipitation Events in Southern Switzerland

Yannick Barton et al.

MONTHLY WEATHER REVIEW (2016)

Article Engineering, Civil

An innovative method for trend analysis of monthly pan evaporations

Ozgur Kisi

JOURNAL OF HYDROLOGY (2015)

Article Engineering, Civil

Innovative Trend Analysis Methodology

Zekai Sen

JOURNAL OF HYDROLOGIC ENGINEERING (2012)

Article Statistics & Probability

An ANOVA-type nonparametric diagnostic test for heteroscedastic regression models

Lan Wang et al.

JOURNAL OF NONPARAMETRIC STATISTICS (2008)