Variability Of Evapotranspiration Research Articles

Spatiotemporal variation in rice evapotranspiration under the influence of rice expansion: a case study in the Sanjiang Plain, Northeast China

Spatiotemporal variation in rice evapotranspiration under the influence of rice expansion: a case study in the Sanjiang Plain, Northeast China

Long-term trend and interannual variation in evapotranspiration of a young temperate Douglas-fir stand over 2002-2022 reveals the impacts of climate change.

The shortage of decades-long continuous measurements of ecosystem processes limits our understanding of how changing climate impacts forest ecosystems. We used continuous eddy-covariance and hydrometeorological data over 2002-2022 from a young Douglas-fir stand on Vancouver Island, Canada to assess the long-term trend and interannual variability in evapotranspiration (ET) and transpiration (T). Collectively, annual T displayed a decreasing trend over the 21 years with a rate of 1% yr-1, which is attributed to the stomatal downregulation induced by rising atmospheric CO2 concentration. Similarly, annual ET also showed a decreasing trend since evaporation stayed relatively constant. Variability in detrended annual ET was mostly controlled by the average soil water storage during the growing season (May-October). Though the duration and intensity of the drought did not increase, the drought-induced decreases in T and ET showed an increasing trend. This pattern may reflect the changes in forest structure, related to the decline in the deciduous understory cover during the stand development. These results suggest that the water-saving effect of stomatal regulation and water-related factors mostly determined the trend and variability in ET, respectively. This may also imply an increase in the limitation of water availability on ET in young forests, associated with the structural and compositional changes related to forest growth.

Estimating Evapotranspiration in the Qilian Mountains Using GRACE/GRACE-FO Satellite Data

Evapotranspiration (ET) is the most significant constituent of the response to climate warming. It serves as a crucial link in the soil–vegetation–atmospheric continuum. Analyzing the driving forces and response of ET to regional-scale climate warming holds scientific significance in improving global water resource assessment methods and drought monitoring techniques. The innovation presented in this article is the calculation of ET by using GRACE/GRACE-FO satellite data through the water balance equation. The inter-annual and seasonal changes in ET in different regions of the Qilian Mountains were analyzed, along with quantifying the contribution of environmental meteorological factors to ET. The ETGRACE and ETMonitor products have good consistency, with a monthly correlation coefficient of 0.92, an NSE coefficient of 0.80, and a root mean square error of 10.38 mm. The results indicate that the increasing trend of ET in the Qilian Mountains region exhibits a “medium–high–low” distribution pattern. The rate of increase in ET is 5.2 mm/year in the central segment. In spring and summer, the overall trend of ET is an increasing one. However, the central and western segments exhibit a slight decreasing trend of ET in autumn. During winter, the southern part of the Qilian Mountains experiences a notable reduction in ET. The correlation between the changes in ET and soil moisture exhibited a strong association, with soil moisture change contributing significantly to ET: 57.8% for the eastern section, 52.8% for the middle section, and 46.9% for the western section. The thermal effect primarily controls ET variations within eastern sections, where temperature change accounts for approximately 6.7% of the total variation in ET levels. Conversely, the moisture factor dominates western sections, where precipitation change accounts for about 6.5% of the total variation in ET levels. Due to the distinct gradient characteristics of environmental meteorological factors in the central segment, the fluctuation of these factors collaboratively drives ET changes. This article provides a new approach for obtaining continuous and reliable actual evapotranspiration in high-altitude areas.

Spatio-temporal variations of reference evapotranspiration using Innovative and Mann–Kendall trend analysis under limited weather data in semi-arid region of Indian Punjab

Spatio-temporal variations of reference evapotranspiration using Innovative and Mann–Kendall trend analysis under limited weather data in semi-arid region of Indian Punjab

Evaluation and Drivers of Four Evapotranspiration Products in the Yellow River Basin

Evapotranspiration is a key driver of water and energy exchanges between terrestrial surfaces and the atmosphere, significantly influencing ecosystem balances. This study focuses on the Yellow River Basin (YRB), where evapotranspiration impacts both ecological dynamics and human activities. By analyzing actual evapotranspiration data from 1982 to 2017, this research provides insights into its spatial and temporal patterns within the YRB. Furthermore, a comprehensive assessment and comparative analysis were performed on four distinct evapotranspiration product datasets: GLDAS-Noah, ERA5-Land, GLEAM v3.8a, and MOD16A2. Employing the Geodetector model, the research identified seven key influencing factors—the digital elevation model (DEM), slope, aspect, precipitation, temperature, soil moisture, and normalized difference vegetation index (NDVI)—and analyzed their impact on evapotranspiration variations, yielding the following insights: (1) Based on the monthly-scale actual evapotranspiration dataset from 1982 to 2017, the annual average evapotranspiration in the YRB fluctuated between 375 and 473 mm, with an average value of 425 mm. A declining trend in the region’s overall evapotranspiration was discerned using the Theil–Sen median slope estimator and Mann–Kendall trend test. (2) The datasets from GLDAS-Noah, ERA5-Land, and GLEAM exhibited the highest correlation with the observed datasets, all exceeding a correlation coefficient of 0.96. In contrast, the MOD16A2 dataset showed the least favorable performance. The ERA5-Land dataset was particularly noteworthy for its close alignment with observational benchmarks, as evidenced by the lowest recorded root mean square error (RMSE) of 5.09 mm, indicative of its outstanding precision. (3) Employing the Geodetector model, a thorough analysis was conducted of the interactions between evapotranspiration and seven critical determinants. The findings revealed that precipitation and the NDVI were the most significant factors influencing evapotranspiration, with q-values of 0.59 and 0.42 in 2010, and 0.71 and 0.59 in 2015, respectively. These results underscore their pivotal role as the main drivers of evapotranspiration variability within the YRB. Conversely, the q-values for slope in 2010 and 2015 were only 0.01 and nearly zero, respectively, indicating their minimal impact on the dynamics of evapotranspiration in the YRB.

Water use of Guinea grass as affected by rainfed local conditions and practices in Sub-Saharan Africa

Ongoing efforts are currently being made to rehabilitate drought-affected pastures in Sub-Saharan Africa. One approach being explored is the introduction of non-native grass species, such as Megathyrsus maximus (Guinea grass). This study aims to investigate the water use of Guinea grass in semi-arid environments under rainfed conditions. Additionally, it aims to a better understanding of the variability of water use in Guinea grass through the utilization of the Bagging machine learning algorithm. Split-plot field experiments were carried out over two consecutive rainy seasons (2020-2021). The treatments included two in-situ rainwater harvesting practices, RWH (ridging plus terracing and terracing alone), three seeding rates, SR (1.5, 2.5, and 3.5 kg ha-1), and two soil nitrogen fertilization rates, SF (95 kg N ha-1 and 0 kg N ha-1). These treatments were compared to a control plot that involved zero-tillage, no fertilization, and no rainwater harvesting. The collected datasets were analyzed using R, SPSS 15, and spreadsheets. The results showed significant differences in plant indices and soil moisture content among the treatments. However, the treatments had insignificant effects on seasonal actual crop evapotranspiration (ETa), which ranged from 1.93 to 3.29 mm day-1. The interactions between SR and RWH were found to have significant impacts on water use. The Bagging algorithm revealed that the variability in ETa could be attributed to SR (42%), RWH (31%), and SF (26%), respectively. The implementation of rainwater harvesting practices resulted in a significant reduction in water usage, saving 86% of the green water used with a water footprint of 0.25 m3 kg-1, compared to 1.7 m3 kg-1 for no adoption of RWH conditions. The water use of rainfed Guinea grass was also found highly sensitive to dry spells. Further detailed studies using multiple-layer models are recommended to gain a better understanding of the non-linear interactions in semi-arid environments.

Investigating meteorological wet and dry transitions in the Dutch Meuse River basin

The Netherlands has traditionally focused on managing flood risk. However, the frequent occurrence of droughts in recent years has brought attention to managing both extremes. Transitions between these opposite extremes pose additional challenges to water management, requiring a trade-off between water storage during dry periods and flood control during wet periods. In this study, we develop a framework to define wet and dry meteorological events and study their transitions using timeseries of meteorological data namely, precipitation, temperature and potential evapotranspiration. The magnitudes of event characteristics are retained, which presents a different approach to the normalized climate indices (like the Standardized Precipitation Index) commonly used in literature. We apply this framework to the Dutch part of the Meuse River basin in northwestern Europe using climate observations between 1951 and 2022. Our analysis shows a statistically significant increase in the amount of water lost from potential evapotranspiration compared to water gained from precipitation between April and September of the water year and an increase in the length of this drying period over the past decades. Such trends in the drying period are related to variability in potential evapotranspiration caused by rising temperatures in the region, indicating the potential for increased water shortage in Spring and Summer due to future temperature increases. We also identify abrupt transitions between opposite extreme events where there is a lack of water at the end of the second event as meteorological situations that challenge water management due to overlapping impacts like flash flooding, less time for water storage, and reduced water availability. We see such conditions occur in 6% of the wet-dry transitions and 20% of the dry-wet transitions, highlighting meteorological scenarios to which the hydrological response of the catchment can be simulated to increase our understanding of the combined risk of floods and droughts.

Vegetation and Evapotranspiration Analyses on Climate Maps

This study focuses on the investigation of evapotranspiration (ET) processes under the climatic and geographical characteristics of Turkey. Evapotranspiration refers to the process by which plants transfer water vapour to the atmosphere and is an important part of the water cycle. Vegetation cover, climatic conditions and topographic structures in different regions of Turkey are among the main factors affecting evapotranspiration. In this study, the seasonal and annual variations of evapotranspiration in different regions of Turkey are discussed and the importance of this process in water resources management, agriculture, ecosystems and climate change is emphasised. This research focuses on conducting an evapotranspiration analysis in Turkey by employing imagery data from NASA Global Land Data Assimilation System Version 2 (GLDAS-2), MODIS, TerraClimate, SMAP Level-4, and Penman-Monteith-Leuning Evapotranspiration V2 (PML_V2) sources. Evapotranspiration, a pivotal process in the hydrological cycle, significantly impacts water resource management and ecosystem dynamics. This study aims to provide a comprehensive assessment of evapotranspiration dynamics across diverse regions within Turkey. For Turkey, SSM data between 2016-2022 and LST data between 2000-2022 were obtained from MODIS images. In the study, regression analyses were performed with evapotranspiration values and SSM and LST data. The best result was a medium level relationship (R 0.56) between evapotranspiration generated from SMAP Level-4 data and LST. A high correlation (R 0.87) was observed with SSM. Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) precipitation data between 1981 and 2023 and Surface pressure (PS) data between 1981 and 2023 were obtained from MERRA image. Regression analyses were performed between evapotranspiration data and PS and Precipitation values. A moderate relationship (R 0.37) was observed between evapotranspiration and PS generated from MOD16A2 V105 data. A moderate relationship (R 0.55) was observed between evapotranspiration and precipitation generated from TerraClimate data. This study aims to contribute to the development of strategies to effectively manage water resources and improve agricultural sustainability by analysing evapotranspiration in various regions of Turkey. Understanding evapotranspiration processes under the climatic diversity and geographical structure of Turkey will be an important step in planning and managing the future use of water resources.

Estimation of water consumption volume and water efficiency in irrigated and rainfed agriculture based on the WaPOR database in Iran

ABSTRACT To evaluate the WaPOR model across the entire country of Iran, initially, 16 provinces located in four different climatic regions were selected for calculating and comparing the evapotranspiration using both the FAO-56 method and the WaPOR approach. The comparison of 10-day evapotranspiration values obtained from the FAO56 method and WaPOR demonstrates that the WaPOR model exhibits the highest correlation with FAO-56 values in semi-arid regions, with an R2 = 0.95 and an RMSE = 0.43. The analysis of evapotranspiration variations indicates that the evapotranspiration in the Caspian Sea and Zagros foothill regions has experienced more significant changes from 2015 to 2022. The annual analysis of net blue water productivity demonstrates that the net productivity in rainfed lands strongly depends on the precipitation received. Also, considering the importance of investigating the accuracy of biomass estimation, the correlation between the accuracy of biomass estimation and actual evapotranspiration was examined in four Iran climatic regions. Using the WaPOR model provides acceptable results for water consumption management and assessment in different regions and climates of Iran, particularly in agricultural lands. The WaPOR model can serve as a guide for determining reliable values of evapotranspiration and planning related to water resources in the agricultural sector in Iran.

Intelligent monitoring of surface evapotranspiration in the Heihe River Basin based on SEBS modelling

[Objective] The Heihe River Basin, located in northwestern China, is the second largest inland basin in China, and its water resources play a crucial role in the ecology, agriculture and human life of the region. The aim of this study is to investigate the spatial and temporal variations of surface evapotranspiration in the Heihe River Basin and the potential impacts of these variations on water resource management. [Methods] To achieve this goal, we applied the PM-based dual-source model, a meteorological model for estimating global surface ET, which takes into account a variety of factors such as temperature, humidity, wind speed and downward solar shortwave radiation. By analysing the meteorological data and remote sensing data of the Black River Basin, we first investigated the spatial and temporal distribution of surface evapotranspiration. [Conclusion] The results show that surface evapotranspiration shows obvious seasonal and regional variations and is significantly affected by meteorological conditions. The inversion of surface ET in the Heihe River Basin by this dual-source model needs to be improved, and the trend of ET values calculated by the model is relatively small compared with the actual values.

Response of evapotranspiration to the 2022 unprecedented extreme drought in the Yangtze River Basin

AbstractThe response of evapotranspiration (ET) to drought is essential for understanding water availability under drought conditions, which has received increasing scientific attention but remains highly uncertain. An unprecedented extreme drought sweeping the whole Yangtze River Basin during the summer and autumn of 2022 provides a novel opportunity to explore the ET response to drought within large river basins. Here, we apply multiple ET products to investigate the spatiotemporal variation of ET during the 2022 extreme drought and analyse the response of ET to drought in the Yangtze River Basin. The results show that this drought, characterized by widespread substantial precipitation deficit and high level of atmospheric evaporative demand (AED), leads to evident abnormal ET. Over the whole basin, ET exhibits a notable increase in the initial 2 months of this drought, which can significantly reduce water availability. However, despite continued high AED, the increase in ET fails to remain in the following months due to limited moisture supply. This suggests that ET response to drought varies as drought progresses. Among other drought events from 2003 to 2022, the response of ET is similar to that in the 2022 extreme drought. Specifically, for most sub‐basins, ET typically shows positive anomalies in the early stage of drought, followed by negative anomalies in the late stage. Generally, our findings improve the understanding of the dynamic response of ET to drought at the basin scale, which is crucial for basin water security.

Evapotranspiration variation of soil‐plant‐atmosphere continuum in subalpine scrubland of Qilian Mountains in China

AbstractThe water cycle in the soil‐plant‐atmosphere continuum is an important element of hydrological and ecological studies, and differences in the composition characteristics of hydrogen and oxygen stable isotopes in different water bodies can indicate water cycling processes. In this study, hydrogen and oxygen isotopes of precipitation, soil water and plant water samples had been collected in the subalpine scrubland of the Qilian Mountains from May to October 2019. The Craig‐Gordon model, the isotopic steady‐state (ISS) assumption, the Keeling Plot model and the two‐source mixing model were used to analyse the stable isotope compositions of different water bodies, the stable isotope characteristics of water vapour of soil evaporation and plant transpiration and the variation of evapotranspiration in the SPAC of the subalpine scrubland. The results showed that plant transpiration (FT) contributed 87.28% and 86.95% to evapotranspiration and soil evaporation (FE) contributed 12.72% and 13.05% to evapotranspiration in the growing season on semi‐sunny and semi‐shaded aspects, respectively, indicating that evapotranspiration in the subalpine scrubland mainly came from the transpiration of scrubland plants. In the early of the growing season (May–June), due to the rapid expansion of plant leaves, the contribution of transpiration to evapotranspiration was at a high level, which intensified transpiration and led to a gradual increase of the transpiration contribution. In the middle of the growing season (July–August), owing to better conditions of rain and heat that made plants grow vigorously, plant transpiration made the highest contribution to evapotranspiration more than 90%, which caused to an overwhelming contribution of plant transpiration to evapotranspiration. In the later of growing season (September to October), the contribution of plant transpiration to evapotranspiration decreased significantly while that of soil evaporation increased, which was because plant photosynthesis and respiration gradually declined for losing their leaves of scrub plants and the relative atmospheric humidity was lower.

Effects of drought on ecosystem evapotranspiration and gross primary productivity in the Haihe River Basin

Evapotranspiration is a crucial component of the hydrological cycle and Gross Primary Productivity (GPP) is the largest flux in the global carbon cycle. However, both evapotranspiration and GPP are significantly affected by climate disasters, especially extreme drought events. Therefore, in this study, MODIS product data from 2002 to 2021 was used to analyze the spatiotemporal variations of actual evapotranspiration (ET), potential evapotranspiration (PET) and GPP within the Haihe River Basin. Then extreme drought events were identified by using EDDI drought index. A statistical analysis was performed to assess the impact of extreme drought on ecosystem evapotranspiration and GPP. The results showed that: (1) the annual evapotranspiration in the Haihe River Basin fluctuated greatly, ET showed a general increasing trend which was higher in the eastern region and lower in the central and western regions, PET showed an overall decreasing trend which was higher in the central and western regions and lower in the eastern region; (2) the annual GPP in the Haihe River Basin from 2002 to 2021 was 646.88 g C/m2/a and the increase rate was 14.75 g C/m2/a, which exhibited a decreasing trend from the northern to the southern and central-western regions; (3) under extreme drought conditions, ET decreased compared with the mean value, while PET increased, the Zhangweihe and the Tuhaimajiahe sub-basins were the most affected, with ET decreasing by 16.36% and PET increasing by 7.00% compared to the reference year. Additionally, extreme drought led to a decrease in GPP, with a reduction ranging from 7% to 18%.

Net Radiation Drives Evapotranspiration Dynamics in a Bottomland Hardwood Forest in the Southeastern United States: Insights from Multi-Modeling Approaches

Evapotranspiration (ET) is a major component of the water budget in Bottomland Hardwood Forests (BHFs) and is driven by a complex intertwined suite of meteorological variables. The understanding of these interdependencies leading to seasonal variations in ET is crucial in better informing water resource management in the region. We used structural equation modeling and AIC modeling to analyze drivers of ET using Eddy covariance water flux data collected from a BHF located in the Russel Sage Wildlife Management Area (RSWMA). It consists of mature closed-canopy deciduous hardwood trees with an average canopy height of 27 m. A factor analysis was used to characterize the shared variance among drivers, and a path analysis was used to quantify the independent contributions of individual drivers. In our results, ET and net radiation (Rn) showed similar variability patterns with Vapor Pressure Deficit (VPD) and temperature in the spring, summer, and autumn seasons, while they differed in the winter season. The path analysis showed that Rn has the strongest influence on ET variations via direct and indirect pathways. In deciduous forests like BHFs, our results suggest that ET is more energy dependent during the growing season (spring and summer) and early non-growing season (autumn) and more temperature dependent during the winter season.

Global evapotranspiration from high-elevation mountains has decreased significantly at a rate of 3.923 %/a over the last 22 years

Clarifying the responses of human activities and climate change to the water cycle under variable environments is crucial for accurately assessing regional water balance. An analysis of the changes in actual evapotranspiration and its driving factors was conducted in the global high-elevation mountains during the period from 2001 to 2022. Utilizing 18 formulas for calculating evapotranspiration, which are based on comprehensive, temperature, radiation, and mass transfer, and then simulated the variations in reference evapotranspiration. Furthermore, we optimized the ET simulation model based on the most effective simulation results and projected future changes using scenario simulation data. Our findings reveal that: 1) ET at high-elevation mountains has significantly decreased at an average rate of 3.923 %/a, with monthly values ranging from 31.179 to 33.652 mm and an average of 32.646 mm; 2) The radiation-based model of Irmark-Allen is particularly well-suited for simulating ET at high-elevation mountains, with precision analysis and the Taylor diagram confirming its superior simulation performance. After optimizing the model using the method of least squares, the value of R2 before and after the optimization were 0.633 and 0.853, respectively. 3) An upward trend in ET under both SSP245 and SSP585 scenario in future simulation projections. Attribution analysis has identified Vapor Pressure Deficit as the key positive driver influencing the change of ET in global high-elevation mountains. Structural equation modeling further reveals that variations in net radiation and precipitation play a significant role in altering evapotranspiration rates. Meanwhile，The water balance analysis reveals that ET has been declining from 2001 to 2022. This phenomenon can be largely attributed to the substantial decline in vapor pressure deficit, the rise in the Normalized Difference Vegetation Index signifying increased vegetation cover, and the reduction in shallow soil moisture during the same period. These factors collectively explain the notable decrease in ET observed in high-elevation mountains.

Evapotranspiration fusion and attribution analysis in the upper and middle reaches of the Yellow River Basin

Study regionThe Upper and Middle Reaches of the Yellow River Basin Study focusTaking the upper and middle reaches of the Yellow River as the research area, 15 types of models developed by the fusion of four multi-source products of GLDAS-Noah V2.1, ERA5-Land, GLEAM v3.6a and GLEAM v3.6b were assessed. Based on the fusion results of actual evapotranspiration(ET), the key factors that drive the spatial variation in actual evapotranspiration was explored, the land surface parameters of Fu formula in different watersheds were estimated, the relationship between land surface parameters and ecological construction measures was established, and the contribution rate of precipitation, potential evapotranspiration, NDVI and check-dam control area to ET change was quantified. New hydrological insights for the regionThe multi-year average actual evapotranspiration from 2003 to 2018 in the watersheds controlled by Tangnaihai, Lanzhou, Toudaoguai, Longmen and Tongguan is 378, 368, 346, 368 and 410 mm/year, respectively. The optimal fusion of the actual evapotranspiration is employing the Extreme Learning Machine to fuse the GLDAS-Noah V2.1 and GLEAM v3.6b products. The long-term actual evapotranspiration estimated from the Fu formula incorporating the ecological construction measures have high agreement with the fusion results. The impact of soil moisture on the spatial variation of actual evapotranspiration is significant. The contribution rate of precipitation to ET change is the highest, followed by NDVI, potential evapotranspiration and check-dam control area.

ET cool home: innovative educational activities on evapotranspiration and urban heat

Abstract. Teaching evapotranspiration (ET) in university courses often focuses on either oversimplified process descriptions or complex empirical calculations, both of which lack grounding in students' real-world experiences and prior knowledge. This calls for a more applied approach to teaching about ET that connects concepts to experience for improved educational outcomes. One such opportunity exists at the intersections between ET and heat in cities, where a growing majority of the world's population lives, including many of our students. In this work we describe an ET educational activity that integrates theory with practical design, taking advantage of the close link between ET processes and urban heat patterns. In a benchtop experiment, students measure ET variations across common land surfaces (e.g., asphalt, grass, and mulch) through water and energy balance approaches. The experiment is paired with an “urban heat tour” in the campus environment, facilitated by portable infrared cameras, offering firsthand observation of urban heat patterns. These two activities, together, provide context in which students can understand the difference in ET across various land covers, describe the relationship between ET and land surface temperatures, and explain the impacts of urban design on heat dynamics. The activities are adaptable to serve a diversity of student backgrounds and to different educational contexts, including public demonstrations and pre-university classrooms.

Main influencing factors of terrestrial evapotranspiration for different land cover types over the Tibetan Plateau in 1982–2014

Introduction: Terrestrial evapotranspiration (ET) over the Tibetan Plateau (TP) has important implications for the global water cycle, climate change, and ecosystem, and its changes and driving factors have drawn increasing attention. Previous research studies have minimally quantified the effects and identified the pathways of the influencing factors on ET over different land surface types.Methods: In this study, we analyze the spatiotemporal distribution and variation of ET over the TP in 1982–2014 based on multiple datasets. Furthermore, the effects of each influencing factor on ET are quantified over different land surface types, and the major influencing factors and their affecting pathways are identified using structure equation modeling (SEM), which is a statistical method used to analyze relationships among multiple variables.Results: The results show that the climatology of ET decreases gradually from southeastern to northwestern TP, with the maximum spatial averaged value of 379.979 ± 0.417 mm a−1 for the fifth generation of European Reanalysis (ERA5) and the minimum of 249.899 ± 0.469 mm a−1 for the Global Land Data Assimilation System (GLDAS). The most significant differences among the ET datasets mainly occur in the summer. The annual ET averaged over the TP presents an increased trend from 1982 to 2014, as shown by all of the ET datasets. However, there are larger discrepancies in the spatial distribution of the increased trend for these datasets. The assessment result shows that the 0.05° land evapotranspiration dataset for the Qinghai–Tibet Plateau (LEDQTP) has the highest temporal correlation coefficient (0.80) and the smallest root-mean-square error (23.50 mm) compared to the observations. Based on LEDQTP, we find that precipitation is the main influencing factor of ET, which primarily affects ET through direct pathways in bare soil and grassland regions, with standardized estimates of 0.521 and 0.606, respectively. However, in meadow and shrub and forest regions, the primary factor influencing ET is air temperature, which is primarily affected by an indirect pathway through a vapor pressure deficit. Air temperature is also the controlling factor in sparse vegetation regions, but it affects ET through a direct pathway.Discussion: This study may provide some new useful information on the effects of climate change on ET in different land cover types over the TP.

Advanced evapotranspiration forecasting in Central Italy: Stacked MLP-RF algorithm and correlated Nystrom views with feature selection strategies

Evapotranspiration is a key parameter in hydrology, particularly in the field of water resources management. Reference evapotranspiration (ETo) stands as a crucial metric, embodying the influence of climate on water loss from both soil and plant surfaces. The accurate forecasting of future ETo values is paramount for informed decision-making in agricultural practices and water supply planning. The anticipation of evapotranspiration variations supports optimized irrigation, drought assessment, and efficient water allocation. Employing innovative algorithms, specifically the Multilayer Perceptron-Random Forest (MLP-RF) Stacked Model and the Correlated Nystrom Views (XNV), this study focuses on predicting ETo up to 60 days ahead in Agro Pontino, an area in Central Italy known for its flourishing agricultural production in the Mediterranean Europe. A Radial Basis Function (RBF) Neural Network serves as a benchmark. Taking into account firstly all available weather-climatic variables and subsequently adopting two different strategies for reducing the variables, based respectively on Principal Component Analysis and feature selection using Particle Swarm Optimization, three distinct sets of input variables were considered. The models based on the complete set of exogenous climatic variables demonstrated superior accuracy. However, even models relying on only mean temperature, maximum relative humidity, and shortwave solar radiation as inputs produced good results, also for the 60-day forecasting horizon, with Kling-Gupta Efficiency (KGE) and Mean Absolute Percentage Error (MAPE) equal to 0.98 and 8.356 %, respectively, in the case of MLP-RF Stacked Model. The latter consistently outperformed XNV and RBF across various combinations of input variables and forecasting horizons. Notably, the reduction in accuracy with extended forecasting horizons was mild, suggesting the potential for accurate results over significantly more extended horizons. These forecasting models facilitate precise irrigation scheduling, minimizing water wastage and conserving resources. This targeted approach enhances crop yields, quality, and environmental sustainability, rendering agriculture economically viable and adaptable to climate variability.

Evaluating the Climate Change Trends and Spatiotemporal Variations of Evapotranspiration: A Case Study in El-Beheira Governorate, Egypt

Aims: Evapotranspiration (ET) is crucial for determining crop water requirements, while climate change and global warming are major concerns. Therefore, in this study, we aimed at evaluating the climate change trends and the spatiotemporal variations in ET in a selected area located in El-Beheira Governorate, Egypt, while accounting for potential land use/land cover (LULC) changes. Methodology: We analyzed three Landsat images acquired in 1984, 2001, and 2020 to assess LULC changes in the study area. Climate change was studied from 1984 to 2021 using data from NASA's Prediction of Worldwide Energy Resource (POWER) project. We also used the Terra MODIS MOD16A3GF Version 6.1 ET product from 2000 to 2021 to evaluate the spatiotemporal variations of ET. Results: LULC change detection showed that the unchanged agricultural area from 1984 to 2020 accounted for 29.3% of the study area and was used to evaluate the changes of ET. Evaluating climate change revealed that there was an increased trend in temperature, relative humidity (RH), and precipitation, while no change was observed in wind speed. Similarly, the anomalies changes of temperature, RH, and precipitation had an increasing trend while wind speed was constant. On the other hand, the yearly ET values calculated from 2000 to 2021 had an increasing trend. There was a moderate correlation between RH and precipitation, as well as between ET and precipitation. Conclusion: The increased trends in climatic parameters such as temperature will eventually require changes in crop patterns to adjust to these changes and maintain a profitable yield. Furthermore, the increase in ET will result in an increase in crop water requirements, which is problematic, especially considering the limited water resources in Egypt.