Article
Environmental Sciences
Luiz Claudio Valle Junior, George Vourlitis, Leone Francisco Curado, Rafael Palacios, Jose Nogueira, Francisco Lobo, Abu Reza Md Towfiqul Islam, Thiago Rodrigues
Summary: In the study, it was found that wind speed and actual vapor pressure have less impact on ETo estimation in the Cerrado region, while temperature and radiation data are more crucial. Radiation data were identified to have the highest impact on ETo estimates in the study area, and FAO procedures for estimating radiation may not be suitable when radiation data are missing.
Article
Water Resources
Elahe Zoratipour, Amir Soltani Mohammadi, Amin Zoratipour
Summary: This study aimed to accurately estimate daily wheat evapotranspiration in central Khuzestan province during 2019-2020 using two remote sensing algorithms: Surface Energy Balance System (SEBS) and Surface Energy Balance Algorithm for Land (SEBAL). The results were compared with various direct and indirect methods, and the SEBS and SEBAL algorithms showed the highest compatibility with lysimeter data. The study recommends the use of energy balance algorithms in Khuzestan province due to their high accuracy.
APPLIED WATER SCIENCE
(2023)
Article
Engineering, Civil
Milan Gocic, Mohammad Arab Amiri
Summary: The study examined the impact of using the optimum set of time lags on the prediction accuracy of monthly ET0 using artificial neural network, showing that more time lags lead to more efficient monthly ET0 prediction.
WATER RESOURCES MANAGEMENT
(2021)
Article
Multidisciplinary Sciences
Deniz Levent Koc, Mueg Erkan Can
Summary: Reference evapotranspiration (ETo) is a crucial variable for water resource management, irrigation practices, agricultural and hydro-meteorological studies, and modeling hydrological processes. The FAO56 Penman-Monteith (PM) method is widely accepted and accurate for estimating ETo in different environments and climates. However, this study evaluated the performance of the FAO56-PM method, Hargreaves-Samani (HS) equations, and multiple linear regression models (MLR) using climatic variables in Adana Plain. The FAO56-PM method accurately estimated ETo when wind speed and relative humidity data were unavailable, while HS equations and MLR models varied in performance depending on the combination of climatic variables used.
Article
Multidisciplinary Sciences
Deniz Levent Koc
Summary: Reference evapotranspiration (ETo) is crucial for irrigation practices and water resources management. The FAO-56 Penman-Monteith (PM) equation is the most accurate method to calculate ETo, but it requires multiple meteorological variables, limiting its applicability in regions with poor meteorological observations. Many empirical equations, including the FAO-24 Pan method, have been developed to estimate ETo. In this study, the performance of eight K-pan models was evaluated in Adana, Turkey, with the Wahed & Snyder model showing the best performance at the seasonal and monthly scales.
Article
Environmental Sciences
Mohammed Achite, Muhammad Jehanzaib, Mohammad Taghi Sattari, Abderrezak Kamel Toubal, Nehal Elshaboury, Andrzej Walega, Nir Krakauer, Ji-Young Yoo, Tae-Woong Kim
Summary: This study compares different machine learning approaches for estimating daily evapotranspiration and finds that the feed forward neural network model performs the best.
Article
Environmental Sciences
D. C. D. Melo, J. A. A. Anache, V. P. Borges, D. G. Miralles, B. Martens, J. B. Fisher, R. L. B. Nobrega, A. Moreno, O. M. R. Cabral, T. R. Rodrigues, B. Bezerra, C. M. S. Silva, A. A. Meira Neto, M. S. B. Moura, T. Marques, S. Campos, J. S. Nogueira, R. Rosolem, R. M. S. Souza, A. C. D. Antonino, D. Holl, M. Galleguillos, J. F. Perez-Quezada, A. Verhoef, L. Kutzbach, J. R. S. Lima, E. S. Souza, M. Gassman, C. F. Perez, N. Tonti, G. Posse, D. Rains, P. T. S. Oliveira, E. Wendland
Summary: Multiple remote sensing-based evapotranspiration models were evaluated across various biomes, climate zones, and land uses in South America. All four models satisfactorily predicted evapotranspiration, with GLEAM and PT-JPL showing consistently higher correlations, and PM-MOD and PM-VI presenting better responses in terms of percent bias. Model skill seemed to be related to biome and climate, with wet to moderately wet environments yielding the best results. Further adaptation of individual algorithms may be necessary to account for the intrinsic characteristics of climates and ecosystems in South America.
WATER RESOURCES RESEARCH
(2021)
Article
Water Resources
Arash Adib, Seyed Shahab Oddin Kalantarzadeh, Mohammad Mahmoudian Shoushtari, Morteza Lotfirad, Ali Liaghat, Masoud Oulapour
Summary: This study compares three different methods for estimating reference evapotranspiration in Ahvaz and Dezful, Iran. The results show that the Artificial Neural Network with Genetic Algorithm optimization and the M5 tree model are the most accurate methods. In terms of meteorological parameters, maximum temperature has the most influence, followed by wind speed.
APPLIED WATER SCIENCE
(2023)
Article
Environmental Sciences
Fernando Onate-Valdivieso, Arianna Onate-Paladines, Deiber Nunez
Summary: This study analyzed the capabilities of four satellite sensors with different spatial and temporal resolutions (LANDSAT 8, ASTER, MODIS and SENTINEL 3) in calculating the reference crop evapotranspiration (ETo) using images and products obtained. The FAO Penman-Monteith equation was used in both traditional and remote sensing approaches to estimate ETo values. The accuracy of the satellite products was evaluated through cross-validation, comparing them with values obtained from meteorological stations. The study found that spatial resolution had a direct correlation with the accuracy of ETo estimates, with LANDSAT 8 products being the most accurate. However, SENTINEL 3 was preferred for continuous ETo monitoring.
Article
Meteorology & Atmospheric Sciences
Stephany Callanaupa Gutierrez, Hans Segura Cajachagua, Miguel Saavedra Huanca, Jose Flores Rojas, Yamina Silva Vidal, Joan Cuxart
Summary: This study provides insights into the mechanisms of evapotranspiration in the high central Peruvian Andes, revealing its modulation by water- and energy-limited states, as well as its correlations with meteorological variables and soil moisture. The variation of evapotranspiration with different seasons and meteorological conditions highlights the need for considering soil moisture in estimating evapotranspiration in this region.
ATMOSPHERIC RESEARCH
(2021)
Article
Ecology
Pei-Yuan Chen
Summary: This study analyzed the correlations between meteorological/substrate moisture variables and evapotranspiration (ET) in order to understand the factors influencing the thermal performance of green roofs in a subtropical climate. The study found that ET may have a higher influence on the temperature difference between green and original roofs than other meteorological variables or substrate water content. It also discovered that daily ET is highly correlated with weather-related variables and substrate water content under wet and dry substrate conditions, respectively. The study suggests that an optimal range of substrate moisture can maximize the function of a green roof in reducing surface temperature and downward substrate-bottom flux.
ECOLOGICAL ENGINEERING
(2022)
Article
Agronomy
Shicheng Yan, Lifeng Wu, Junliang Fan, Fucang Zhang, Yufeng Zou, You Wu
Summary: The study proposed a novel hybrid XGB model with WOA algorithm to estimate daily ET0 in different regions of China, showing better performance than conventional models and providing more accurate estimation of ET0 for irrigation scheduling and water resource planning.
AGRICULTURAL WATER MANAGEMENT
(2021)
Article
Environmental Sciences
Qiong Su, Vijay P. Singh
Summary: The Priestley-Taylor (PT) method is commonly used to calculate reference evapotranspiration (ETo) in hydrologic and crop models, but its default coefficient may not be reliable across different climatic regions. This study derived an analytical expression of PT coefficient (PTa) using the Penman-Monteith method, which improved the accuracy of ETo estimation. The global monthly PTa dataset is open-source and can be incorporated into models. The study also found that radiative component was the main driver of global ETo changes, and the impact of available energy and wind speed on ETo variations intensified in a warming climate.
WATER RESOURCES RESEARCH
(2023)
Article
Agriculture, Multidisciplinary
Masoud Karbasi, Mehdi Jamei, Mumtaz Ali, Anurag Malik, Zaher Mundher Yaseen
Summary: The study utilized an efficient deep learning model called AED-BiLSTM to forecast 1-3 weeks ahead of weekly ETo. The model outperformed other machine learning models in terms of accuracy and ability, and showed better performance in arid and semi-arid climates.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Article
Geosciences, Multidisciplinary
Amin Gharehbaghi, Birol Kaya
Summary: Due to difficulties in data measurement and collection, it is necessary to use empirical formulas calibrated locally to estimate evapotranspiration in continental climates. This study calibrated six empirical evapotranspiration formulas and found that Jensen and haise's (1963) formula was the best for estimating evapotranspiration in Central Anatolia.
PHYSICS AND CHEMISTRY OF THE EARTH
(2022)
Article
Water Resources
Amina Khatun, Poulomi Ganguli, Deepak Singh Bisht, Chandranath Chatterjee, Bhabagrahi Sahoo
Summary: This study investigates the physical association between Predecessor Rain Events (PREs) and peak runoff generation in seven catchments over the Upper Mahanadi River basin (UMRB), India. By developing a statistical-dynamical framework, the study assesses the compounding impact of PREs versus riverine floods during both retrospective and projected climate. The results show an increase in compound flood hazard in larger catchments during the projected period when considering PRE as the covariate.
HYDROLOGICAL PROCESSES
(2022)
Article
Engineering, Civil
Ashutosh Pati, Bhabagrahi Sahoo
Summary: In this study, the physically-based VPMS model was coupled with the SWMM model to simulate and study urban pluvial flooding. The study evaluated the impact of different channel representations and low-impact development techniques on flooding. The results showed that high-resolution channel representation and bioretention cell technique were more effective in reducing flooding.
JOURNAL OF HYDROLOGIC ENGINEERING
(2022)
Article
Environmental Sciences
Nikul Kumari, Ankur Srivastava, Sumant Kumar
Summary: Rainfall is crucial for various water management sectors, but accurate estimation of hydrological components is challenging due to the variability of rainfall and limited meteorological stations. This study established an empirical relationship between rainfall and runoff in the Telibandha Lake Catchment in central India, and found that the NDWI values were highest during July-September with a good relationship between seasonal NDWI and mean monthly rainfall data.
JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING
(2022)
Article
Geography, Physical
Ankur Srivastava, Omer Yetemen, Patricia M. Saco, Jose F. Rodriguez, Nikul Kumari, Kwok P. Chun
Summary: Topography affects precipitation intensity and distribution, influencing climate and vegetation. Previous studies focused on bare soil conditions and there are limited research on precipitation effects on landform patterns in aspect-controlled semi-arid ecosystems. This study used the CHILD landscape evolution model combined with the BGM vegetation dynamics model to analyze the coevolution of semi-arid landform-vegetation ecosystems. The results identified elevation control, aspect, and drainage network as major drivers of vegetation distribution, and the combination of orographic precipitation and spatially varied solar radiation played a key role in generating topographic asymmetry.
EARTH SURFACE PROCESSES AND LANDFORMS
(2022)
Article
Water Resources
Amina Khatun, Bhabagrahi Sahoo, Chandranath Chatterjee
Summary: This study evaluates the performance of different bias-correction techniques for rainfall forecasts and finds that the copula and eKSOM methods outperform the traditional quantile mapping approach. The eKSOM method shows better skills in capturing the seasonality of observed rainfall.
HYDROLOGICAL SCIENCES JOURNAL
(2022)
Article
Environmental Sciences
Debi Prasad Sahoo, Bhabagrahi Sahoo, Manoj Kumar Tiwari, Goutam Kumar Behera
Summary: This study proposes a novel framework that combines remote sensing images and machine learning algorithms to estimate daily streamflow in the Brahmani River Basin in India. The results show that all developed models can simulate streamflow well, with the SVRFUS model performing the best in reproducing different streamflow regimes. This approach has the potential to be applied in other world-river basins to estimate ecological flow regimes and facilitate aquatic environmental management.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2022)
Article
Water Resources
Amina Khatun, Chandranath Chatterjee, Gaurav Sahu, Bhabagrahi Sahoo
Summary: A novel smoothing-based long short-term memory (Smooth-LSTM) framework is proposed for flood forecasting up to five days ahead, and compared with other models. The Smooth-LSTM model shows higher efficiency and better reproduction of peak floods compared to the benchmark LSTM, ANN, and MIKE models. It is found to be robust in operational flood forecasting, with lower uncertainty and the least sensitivity to redundant input information.
HYDROLOGICAL SCIENCES JOURNAL
(2023)
Article
Engineering, Civil
Amina Khatun, Bhabagrahi Sahoo, Chandranath Chatterjee
Summary: This study proposes two error-updating frameworks based on the MIKE11-NAM-HD model for 1-5 days ahead inflow forecasting. The hybrid Cop-SOM model demonstrates improved rainfall forecast skills with up to 5 days lead-time, and the bcMIKE-LSTM error-updating framework achieves high NSE scores within a 5-day lead-time.
JOURNAL OF HYDROLOGY
(2023)
Article
Environmental Sciences
Urmila R. Panikkar, Roshan Srivastav, Ankur Srivastava
Summary: Anthropically-induced land-use/land cover (LULC) changes have significant impacts on hydrological processes and flow regimes, leading to socio-economic and environmental damages. This study quantifies the hydrological changes induced by LULC changes in an urbanizing watershed and analyzes the variations in streamflow and extremes. The results show that LULC changes significantly influence soil moisture, evapotranspiration (ET), and groundwater contribution, affecting the generation of extreme flows.
Article
Green & Sustainable Science & Technology
Mahipal Choudhary, Nishant K. Sinha, Monoranjan Mohanty, Somasundaram Jayaraman, Nikul Kumari, Bikram Jyoti, Ankur Srivastava, Jyoti K. Thakur, Nirmal Kumar, Pramod Jha, Dhiraj Kumar, Jitendra Kumar, Rahul Mishra, Ravi H. Wanjari, Ranjeet S. Chaudhary, Kuntal M. Hati, Jaideep K. Bisht, Arunava Pattanayak
Summary: The present study evaluated the long-term effects of organic and inorganic fertilisers on soil properties under the soybean-wheat cropping system in vertisols of the semi-arid region. The results showed that continuous application of manure plus inorganic fertiliser improved soil aggregate stability and organic carbon content, which are crucial for maintaining soil health and sustainability.
Article
Engineering, Civil
Silvia Barbetta, Bhabagrahi Sahoo, Bianca Bonaccorsi, Trushnamayee Nanda, Chandranath Chatterjee, Tommaso Moramarco, Ezio Todini
Summary: The effect of flood waves entering into artificial reservoirs must be carefully considered for dam management. The optimization of dam management should be based on forecasting water volume entering the reservoir and planning releases. Flood forecasting models can provide discharge predictions and support civil protection activities for flood mitigation.
JOURNAL OF HYDROLOGY
(2023)
Article
Environmental Sciences
Arunima Singh, Sunni Kanta Prasad Kushwaha, Subrata Nandy, Hitendra Padalia, Surajit Ghosh, Ankur Srivastava, Nikul Kumari
Summary: This study aimed to assess aboveground biomass (AGB) in the Barkot Forest Range, Uttarakhand, India by integrating Terrestrial Laser Scanner (TLS) and ALOS PALSAR L-band Synthetic Aperture Radar (SAR) data. Various parameters were derived from the ALOS SAR data, and TLS was used to obtain diameter at breast height (dbh) and tree height. The integration of SAR and TLS data using Random Forest (RF) and Artificial Neural Network (ANN) showed that RF performed better in estimating the biomass with an R-2 value of 0.94 and an RMSE of 59.72 ton ha(-1).
Article
Environmental Studies
Sirisha Adamala, Ayyam Velmurugan, Nikul Kumari, T. Subramani, T. P. Swarnam, V. Damodaran, Ankur Srivastava
Summary: Water erosion is a significant problem leading to land degradation globally. Assessing the extent of erosion in different land use contexts is crucial for implementing appropriate conservation measures. In the Andaman and Nicobar Islands, urbanization and deforestation have contributed to accelerated erosion. Agriculture in the islands also faces severe soil erosion, mainly due to cultivation practices and mono-cropping. A study using runoff plots and a soil erosion model was conducted to quantify soil and nutrient losses and estimate erosion spatially.
Article
Environmental Sciences
Sabinaya Biswal, Bhabagrahi Sahoo, Madan K. Jha, Mahendra K. Bhuyan
Summary: This study proposes a copula-based framework to obtain reliable river cross-sections from SRTM and ASTER DEMs and successfully simulates observed streamflow and water levels. The developed models can derive synthetic river cross-sections and simulate streamflow regimes and water levels under data-scarce conditions.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2023)
Correction
Meteorology & Atmospheric Sciences
Nikul Kumari, Ankur Srivastava, Umesh Chandra Dumka