Article
Environmental Sciences
Yongzhi Bao, Tingxi Liu, Limin Duan, Xin Tong, Honglan Ji, Lan Zhang, V. P. Singh
Summary: Accurately simulating stomatal conductance is crucial for understanding carbon and water cycle processes and improving evapotranspiration simulations. This study found that the SW-BB model performed better in estimating evapotranspiration in a mobile dune ecosystem, especially during extreme drought periods. Incorporating soil moisture into stomatal conductance models significantly improved performance, with SM showing the highest sensitivity to stomatal conductance and evapotranspiration.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Agronomy
Haofang Yan, Song Huang, Jianyun Zhang, Chuan Zhang, Guoqing Wang, Lanlan Li, Shuang Zhao, Mi Li, Baoshan Zhao
Summary: The study used the S-W model and D-K method to estimate evaporation and transpiration in tea fields, finding that both methods were able to calculate E and T separately. However, the S-W model had slightly higher accuracy in estimating ETc compared to the D-K method.
Article
Agronomy
Han Chen, Albert Z. Jiang, Jinhui Jeanne Huang, Han Li, Edward McBean, Vijay P. Singh, Jiawei Zhang, Zhiqing Lan, Junjie Gao, Ziqi Zhou
Summary: In this study, an enhanced version of the Shuttleworth-Wallace two-source model is proposed, which combines deep learning and Bayesian parameter optimization techniques to improve the estimation and partitioning of evapotranspiration and its components. The model's performance is verified using eddy correlation and stable water isotope observations, and the Bayesian model evidence is utilized for model evaluation and selection. The enhanced model provides more accurate simulation results and guidance for irrigation measures in urban forest areas.
AGRICULTURAL AND FOREST METEOROLOGY
(2022)
Article
Agronomy
Xiang Gao, Xurong Mei, Jinsong Zhang, Jinfeng Cai, Fengxue Gu, Weiping Hao, Daozhi Gong
Summary: In this study, modified versions of the SWm, PTm, and DKm models were developed and compared for estimating evapotranspiration (ET) and its components in a rainfed spring maize cropland on the Loess Plateau. The results showed that all three models performed well in estimating 30 min and daily ET and its components during the growing seasons. The DKm model had the best performance in estimating 30 min ET, while the PTm model outperformed the other two models in estimating daily ET and daily plant transpiration (Tp). The DKm model also performed well in reproducing daily soil evaporation (Es), but not as well as the other two models in estimating ET and Tp. Therefore, the PTm model was recommended for estimating ET in rainfed spring maize on the Loess Plateau.
AGRICULTURAL AND FOREST METEOROLOGY
(2023)
Article
Agronomy
Chunan Xiao, Jiabing Cai, Baozhong Zhang, Hongfang Chang, Zheng Wei
Summary: Field surface temperature data were analyzed and optimized using thermal infrared sensors and an algorithm, improving the accuracy of evapotranspiration estimation in the S-I model. The estimation of soil evaporation and canopy transpiration was refined through the Revised S-W model. This study provides valuable insights into the accurate estimation of evapotranspiration using different models in different regions, and its application in precision irrigation management.
AGRICULTURAL WATER MANAGEMENT
(2023)
Article
Geography, Physical
Chenyang Xu, Shuangqiao Liao, Minghao Lin, Qian Yue, Jizhe Xia
Summary: Although pesticides are widely used to enhance crop yield, they are harmful to the environment and human health. This study developed a simplified plant uptake model to estimate pesticide absorption by plants from soil based on plant transpiration. Using remote sensing techniques and MODIS data, the model generated spatiotemporal patterns of pesticide contamination.
INTERNATIONAL JOURNAL OF DIGITAL EARTH
(2023)
Article
Biodiversity Conservation
Ismail Mondal, Sandeep Thakur, Aakash De, Tarun Kumar De
Summary: This study utilizes the METRIC model to estimate the spatial distribution of daily evapotranspiration in the Sundarban Biosphere Reserve in India. The results show that forests and water bodies have the highest evapotranspiration rates, while croplands have the lowest rates. The use of satellite imagery validates the accuracy of the METRIC model and highlights its significance in water conservation and evapotranspiration estimation using satellite technology.
ECOLOGICAL INDICATORS
(2022)
Article
Meteorology & Atmospheric Sciences
Tao Su, Taichen Feng, Bicheng Huang, Zixuan Han, Zhonghua Qian, Guolin Feng, Wei Hou, Wenjie Dong
Summary: The study analyses the temporal variation of actual evapotranspiration (AE) over China during 1980-2015 using an ensemble of six reanalyses and a complementary-relationship-based AE dataset. It reveals significant increase in annual mean AE in China, with major regime shifts occurring around 1998. Climate change and landscape characteristics are identified as the primary causes for changes in AE in different regions of China.
INTERNATIONAL JOURNAL OF CLIMATOLOGY
(2022)
Article
Geosciences, Multidisciplinary
Monica Ionita, Viorica Nagavciuc
Summary: This study found that drought severity has significantly increased in Central Europe and the Mediterranean region over the past three decades, while Northern Europe has become wetter. The lack of significant changes in precipitation may be a contributing factor to the different drought characteristics in various regions.
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES
(2021)
Article
Environmental Sciences
Tian Hu, Kaniska Mallick, Patrik Hitzelberger, Yoanne Didry, Gilles Boulet, Zoltan Szantoi, Benjamin Koetz, Itziar Alonso, Madeleine Pascolini-Campbell, Gregory Halverson, Kerry Cawse-Nicholson, Glynn C. Hulley, Simon Hook, Nishan Bhattarai, Albert Olioso, Jean-Louis Roujean, Philippe Gamet, Bob Su
Summary: The ECOSTRESS mission collects thermal images to understand the variations in terrestrial evapotranspiration in response to soil water availability and atmospheric aridity. The ECOSTRESS ET products generated in the EEH using different models were evaluated and compared. The STIC and SEBS models showed comparable performances, while the TSEB model had higher errors. The STIC ET estimates had higher accuracy than the operational ECOSTRESS ET product from the NASA PT-JPL model.
WATER RESOURCES RESEARCH
(2023)
Article
Environmental Sciences
Kyle Knipper, Martha Anderson, Nicolas Bambach, William Kustas, Feng Gao, Einara Zahn, Christopher Hain, Andrew McElrone, Oscar Rosario Belfiore, Sebastian Castro, Maria Mar Alsina, Sebastian Saa
Summary: Accurate estimation of evapotranspiration (ET) is crucial for water-limited cropping systems. In this study, two formulations of the atmosphere-land exchange inverse model (ALEXI) and associated flux disaggregation technique (DisALEXI), namely DisALEXI-PT and DisALEXI-PM, were evaluated for partitioned evaporation (E) and transpiration (T) in vineyards and orchards. The results showed that DisALEXI-PT overestimated E and slightly underestimated T, while DisALEXI-PM agreed better with partitioned fluxes, albeit overestimating T under certain conditions. The analysis suggested that DisALEXI-PM achieved convergence with ALEXI ET by adjusting E and T proportionally, while DisALEXI-PT convergence relied on adjustments to E. These findings have implications for improving modeling frameworks and water use efficiency in water-limited systems.
Article
Environmental Sciences
Alhousseine Diarra, Lionel Jarlan, Said Khabba, Michel Le Page, Salah Er-Raki, Riad Balaghi, Soufyane Charafi, Abdelghani Chehbouni, Rafiq El Alami
Summary: This study used the two-source energy budget model, combined with MODIS leaf area index, land surface temperature, and meteorological data, to derive daily latent heat flux maps at the kilometer scale in the Tensift catchment in Morocco. By comparing the model outputs with in situ meteorological measurements and eddy covariance observations, the accuracy of the model was evaluated. The study also analyzed the seasonal and interannual evapotranspiration in relation to local climate and land use, and discussed the potential applications of the proposed method in improving grain yield prediction and detecting newly irrigated areas for arboriculture.
Article
Geochemistry & Geophysics
Abdollah Masoud Darya, Muhammad Mubasshir Shaikh, Ilias Fernini, Hamid AlNaimiy
Summary: This study investigates the temporal and spatial variability of ionospheric irregularities using data from a global navigation satellite system receiver. The results show that even during a solar minimum period, significant pre-sunset scintillation occurrences have been observed, particularly during the winter solstices. The study also finds that the impact of scintillation on GNSS constellations varies, with GPS being the most affected and BeiDou and Galileo satellites being the least affected.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Environmental Sciences
Indira Bose, Faisal Hossain, Hisham Eldardiry, Shahryar Ahmad, Nishan K. Biswas, Ahmad Zeeshan Bhatti, Hyongki Lee, Mazharul Aziz, Md Shah Kamal Khan
Summary: The study proposed an improved Irrigation Advisory System (IAS) by integrating GRACE and Landsat TIR data, which can significantly reduce groundwater usage and improve sustainability in irrigation districts in South Asia.
WATER RESOURCES RESEARCH
(2021)
Article
Environmental Sciences
Martha C. Anderson, Yang Yang, Jie Xue, Kyle R. Knipper, Yun Yang, Feng Gao, Chris R. Hain, William P. Kustas, Kerry Cawse-Nicholson, Glynn Hulley, Joshua B. Fisher, Joseph G. Alfieri, Tilden P. Meyers, John Prueger, Dennis D. Baldocchi, Camilo Rey-Sanchez
Summary: This study explores the combination of Landsat and ECOSTRESS imaging for high-resolution ET image timeseries, demonstrating the value of ECOSTRESS's higher temporal sampling and discussing challenges in using land-surface temperature for ET retrieval.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Agronomy
Asma Abou Ali, Lhoussaine Bouchaou, Salah Er-Raki, Mohammed Hssaissoune, Youssef Brouziyne, Jamal Ezzahar, Said Khabba, Adnane Chakir, Adnane Labbaci, Abdelghani Chehbouni
Summary: This study aims to determine the crop coefficient and irrigation strategy for citrus in a semi-arid region to meet the crop's water requirements. By monitoring and measuring the meteorological and soil conditions of the citrus orchard, the researchers were able to estimate key parameters such as evapotranspiration, crop coefficient, and actual evapotranspiration, and develop a sustainable irrigation plan.
AGRICULTURAL WATER MANAGEMENT
(2023)
Article
Environmental Sciences
Abdenbi Elaloui, El Mahdi El Khalki, Mustapha Namous, Khalid Ziadi, Hasna Eloudi, Elhousna Faouzi, Latifa Bou-Imajjane, Morad Karroum, Yves Tramblay, Abdelghani Boudhar, Abdelghani Chehbouni
Summary: The focus of this research was to assess the impact of climate change on the rate of soil erosion in the High Atlas of Morocco. The results indicate that climate change is projected to significantly increase the potential for soil erosion by the end of the century.
Article
Agronomy
Nadia Ouaadi, Lionel Jarlan, Said Khabba, Michel Le Page, Adnane Chakir, Salah Er-Raki, Pierre-Louis Frison
Summary: Rationalizing the use of agricultural water is crucial in semi-arid areas facing water shortages and food security threats. The FAO-56 approach, relying on accurate estimation of crop water requirement, is challenged by optical data limitations caused by persistent cloud cover. This study explores the potential of all-weather C-band Sentinel-1 radar observations for field-scale assessment. Empirical relationships between crop coefficients and interferometric coherence were evaluated and demonstrated promising results as a substitute for NDVI in estimating actual evapotranspiration under persistent cloud cover.
AGRICULTURAL WATER MANAGEMENT
(2023)
Article
Environmental Sciences
Nadia Rhoujjati, Yassine Ait Brahim, Lahoucine Hanich, Ali Rhoujjati, Nicolas Patris, Abdelghani Chehbouni, Lhoussaine Bouchaou
Summary: Morocco, as part of the Mediterranean basin, faces challenges in terms of water resources due to its semi-arid climate and high demand. This study conducted in the Middle Atlas Mountains reveals significant spatio-temporal variations in precipitation isotopic composition. The findings highlight the influence of large-scale water vapor transport from the ocean and local cloud microphysical processes on winter and summer precipitation in the region. Rating: 7/10.
ENVIRONMENTAL EARTH SCIENCES
(2023)
Editorial Material
Environmental Sciences
Salah Er-Raki, Abdelghani Chehbouni
Article
Environmental Sciences
Ayoub Guemouria, Abdelghani Chehbouni, Salwa Belaqziz, Terence Epule Epule, Yassine Ait Brahim, El Mahdi El Khalki, Driss Dhiba, Lhoussaine Bouchaou
Summary: This study investigates the interactions between supply and demand in order to achieve integrated water resources management and successfully manage water resources at the Souss-Massa Basin scale using a System Dynamics approach. The results indicate that current policies do not lead to sustainable water management, and the sustainability of water resources in the basin is mainly impacted by surface water availability, irrigated areas, and irrigation efficiency.
Article
Environmental Sciences
Badr-eddine Sebbar, Said Khabba, Olivier Merlin, Vincent Simonneaux, Chouaib El Hachimi, Mohamed Hakim Kharrou, Abdelghani Chehbouni
Summary: In this study, a new spatial downscaling strategy of hourly ERA5-Land temperature data is presented. The results show that correcting and downscaling the 9 km resolution ERA5-Land temperature using multiple machine learning techniques significantly improves the spatial distribution of hourly local temperature.
Article
Environmental Sciences
Myriam Benkirane, Abdelhakim Amazirh, Nour-Eddine Laftouhi, Said Khabba, Abdelghani Chehbouni
Summary: Accurate rainfall monitoring is challenging in semi-arid mountainous environments due to its variability and inconsistent gauge measurement. Earth observation of precipitation estimations can overcome this limitation. The study evaluates the hydro-statistical performance of GPM IMERG products and corrects for bias. The results show high accuracy for all IMERG products and suggest that IMERG-F provides satisfactory hydrological performance. IMERG-L performs slightly better than IMERG-E, but overestimated discharge during flood events compared to gauge data.
Article
Remote Sensing
Karima Mazirh, Said El Goumi, Mounsif Ibnoussina, Omar Witam, Mohamed Nocairi, Rachida Kasimi, Salah Er-Raki
Summary: Climate change and rapid urbanization have had a significant impact on green spaces and natural resources in African countries. A study in Marrakech used remote-sensing data to monitor changes in land cover and land use from 1990 to 2020, showing a decrease of almost 35% in vegetation cover over the investigation period.
CANADIAN JOURNAL OF REMOTE SENSING
(2023)
Article
Environmental Sciences
Oumaima Kaissi, Salwa Belaqziz, Mohamed Hakim Kharrou, Salah Erraki, Chouaib El Hachimi, Abdelhakim Amazirh, Abdelghani Chehbouni
Summary: This study addresses the challenge of obtaining the required meteorological parameters for estimating reference evapotranspiration (ET0) by leveraging machine learning and deep learning models. The importance of mean air temperature and global solar radiation as essential predictors for accurate ET0 estimation is highlighted. Additionally, the study compares different deep learning models and finds that machine learning models outperform deep learning architectures for small and medium-sized datasets.
MODELING EARTH SYSTEMS AND ENVIRONMENT
(2023)
Article
Remote Sensing
Jamal Elfarkh, Kasper Johansen, Victor Angulo, Omar Lopez Camargo, Matthew F. Mccabe
Summary: Land Surface Temperature (LST) is a crucial variable used in various applications, and while satellites offer moderate-resolution LST data, unmanned aerial vehicles (UAVs) can provide high-resolution thermal infrared measurements. However, the continuous and rapid variation in LST poses challenges in producing orthomosaics from UAV-based image collections. This research examines LST variations during standard 15-20 min UAV flights over diverse surfaces and identifies factors such as wind speed, solar radiation, irrigation, and atmospheric conditions that contribute to temperature variations. Understanding these factors is essential for developing correction procedures and interpreting UAV-based thermal infrared data and orthomosaics.
Article
Automation & Control Systems
Willians Ribeiro Mendes, Arthur Moraes Videira, Salah Er-Raki, Derek M. Heeren, Ritaban Dutta, Fabio M. U. Araujo
Summary: An intelligent variable rate irrigation system is proposed for optimized irrigation, utilizing satellite imagery and other input parameters. The system can detect and characterize spatial variability of crops, and the fuzzy logic approach solves uncertainties in irrigation systems, improving irrigation precision.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)