Bibliografías temáticas / Irrigation, Land Surface Model, Remote Sensing, Data Assimilation

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Literatura académica sobre el tema "Irrigation, Land Surface Model, Remote Sensing, Data Assimilation"

Autor: Grafiati

Publicado: 10 de marzo de 2023

Última modificación: 31 de julio de 2025

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Artículos de revistas sobre el tema "Irrigation, Land Surface Model, Remote Sensing, Data Assimilation"

Fan, Xingwang, Yanyu Lu, Yongwei Liu, Tingting Li, Shangpei Xun, and Xiaosong Zhao. "Validation of Multiple Soil Moisture Products over an Intensive Agricultural Region: Overall Accuracy and Diverse Responses to Precipitation and Irrigation Events." Remote Sensing 14, no. 14 (2022): 3339. http://dx.doi.org/10.3390/rs14143339.

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Remote sensing and land surface models promote the understanding of soil moisture dynamics by means of multiple products. These products differ in data sources, algorithms, model structures and forcing datasets, complicating the selection of optimal products, especially in regions with complex land covers. This study compared different products, algorithms and flagging strategies based on in situ observations in Anhui province, China, an intensive agricultural region with diverse landscapes. In general, models outperform remote sensing in terms of valid data coverage, metrics against observati

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Han, X., H. J. H. Franssen, R. Rosolem, R. Jin, X. Li, and H. Vereecken. "Correction of systematic model forcing bias of CLM using assimilation of cosmic-ray Neutrons and land surface temperature: a study in the Heihe Catchment, China." Hydrology and Earth System Sciences 19, no. 1 (2015): 615–29. http://dx.doi.org/10.5194/hess-19-615-2015.

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Abstract. The recent development of the non-invasive cosmic-ray soil moisture sensing technique fills the gap between point-scale soil moisture measurements and regional-scale soil moisture measurements by remote sensing. A cosmic-ray probe measures soil moisture for a footprint with a diameter of ~ 600 m (at sea level) and with an effective measurement depth between 12 and 76 cm, depending on the soil humidity. In this study, it was tested whether neutron counts also allow correcting for a systematic error in the model forcings. A lack of water management data often causes systematic input er

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Han, X., H. J. Hendricks Franssen, R. Rosolem, R. Jin, X. Li, and H. Vereecken. "Correction of systematic model forcing bias of CLM using assimilation of cosmic-ray neutrons and land surface temperature: a study in the Heihe catchment, China." Hydrology and Earth System Sciences Discussions 11, no. 7 (2014): 9027–66. http://dx.doi.org/10.5194/hessd-11-9027-2014.

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Abstract. The recent development of the non-invasive cosmic-ray soil moisture sensing technique fills the gap between point scale soil moisture measurements and regional scale soil moisture measurements by remote sensing. A cosmic-ray probe measures soil moisture for a footprint with a diameter of ~600 m (at sea level) and with an effective measurement depth between 12 and 76 cm, depending on the soil humidity. In this study, it was tested whether neutron counts also allow to correct for a systematic error in the model forcings. Lack of water management data often cause systematic input errors

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Modanesi, Sara, Christian Massari, Alexander Gruber, et al. "Optimizing a backscatter forward operator using Sentinel-1 data over irrigated land." Hydrology and Earth System Sciences 25, no. 12 (2021): 6283–307. http://dx.doi.org/10.5194/hess-25-6283-2021.

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Abstract. Worldwide, the amount of water used for agricultural purposes is rising, and the quantification of irrigation is becoming a crucial topic. Because of the limited availability of in situ observations, an increasing number of studies is focusing on the synergistic use of models and satellite data to detect and quantify irrigation. The parameterization of irrigation in large-scale land surface models (LSMs) is improving, but it is still hampered by the lack of information about dynamic crop rotations, or the extent of irrigated areas, and the mostly unknown timing and amount of irrigati

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Kumar, S. V., C. D. Peters-Lidard, J. A. Santanello, et al. "Evaluating the utility of satellite soil moisture retrievals over irrigated areas and the ability of land data assimilation methods to correct for unmodeled processes." Hydrology and Earth System Sciences 19, no. 11 (2015): 4463–78. http://dx.doi.org/10.5194/hess-19-4463-2015.

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Abstract. Earth's land surface is characterized by tremendous natural heterogeneity and human-engineered modifications, both of which are challenging to represent in land surface models. Satellite remote sensing is often the most practical and effective method to observe the land surface over large geographical areas. Agricultural irrigation is an important human-induced modification to natural land surface processes, as it is pervasive across the world and because of its significant influence on the regional and global water budgets. In this article, irrigation is used as an example of a huma

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Kumar, S. V., C. D. Peters-Lidard, J. A. Santanello, et al. "Evaluating the utility of satellite soil moisture retrievals over irrigated areas and the ability of land data assimilation methods to correct for unmodeled processes." Hydrology and Earth System Sciences Discussions 12, no. 6 (2015): 5967–6009. http://dx.doi.org/10.5194/hessd-12-5967-2015.

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Abstract. The Earth's land surface is characterized by tremendous natural heterogeneity and human engineered modifications, both of which are challenging to represent in land surface models. Satellite remote sensing is often the most practical and effective method to observe the land surface over large geographical areas. Agricultural irrigation is an important human induced modifications to natural land surface processes, as it is pervasive across the world and because of its significant influence on the regional and global water budgets. In this article, irrigation is used as an example of a

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Sun, Yule, Quanming Liu, Chunjuan Wang, Qi Liu, and Zhongyi Qu. "Improving Soil Moisture Estimation by Integrating Remote Sensing Data into HYDRUS-1D Using an Ensemble Kalman Filter Approach." Agriculture 15, no. 12 (2025): 1320. https://doi.org/10.3390/agriculture15121320.

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Reliable soil moisture projections are critical for optimizing crop productivity and water savings in irrigation in arid and semi-arid regions. However, capturing their spatial and temporal variability is difficult when using individual observations, modeling, or satellite-based methods. Here, we present an integrated framework that combines satellite-derived soil moisture estimates, ground-based observations, the HYDRUS-1D vadose zone model, and the ensemble Kalman filter (EnKF) data assimilation method to improve soil moisture simulations over saline-affected farmland in the Hetao irrigation

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Ouaadi, Nadia, Lionel Jarlan, Saïd Khabba, Jamal Ezzahar, Michel Le Page, and Olivier Merlin. "Irrigation Amounts and Timing Retrieval through Data Assimilation of Surface Soil Moisture into the FAO-56 Approach in the South Mediterranean Region." Remote Sensing 13, no. 14 (2021): 2667. http://dx.doi.org/10.3390/rs13142667.

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Agricultural water use represents more than 70% of the world’s freshwater through irrigation water inputs that are poorly known at the field scale. Irrigation monitoring is thus an important issue for optimizing water use in particular with regards to the water scarcity that the semi-arid regions are already facing. In this context, the aim of this study is to develop and evaluate a new approach to predict seasonal to daily irrigation timing and amounts at the field scale. The method is based on surface soil moisture (SSM) data assimilated into a simple land surface (FAO-56) model through a pa

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Chang, Hongfang, Jiabing Cai, Baozhong Zhang, Zheng Wei, and Di Xu. "Early Yield Forecasting of Maize by Combining Remote Sensing Images and Field Data with Logistic Models." Remote Sensing 15, no. 4 (2023): 1025. http://dx.doi.org/10.3390/rs15041025.

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Early forecasting of crop yield from field to region is important for stabilizing markets and safeguarding food security. Producing a precise forecasting result with fewer inputs is an ongoing goal for the large-area yield evaluation. We present one approach of yield prediction for maize that was explored by incorporating remote-sensing-derived land surface temperature (LST) and field in-season data into a series of logistic models with only a few parameters. Continuous observation data of maize were utilized to calibrate and validate the corresponding logistic models for regional biomass esti

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Khan, Ihsan Ullah, Mudassar Iqbal, Zeshan Ali, Abu Bakar Arshed, Mo Wang, and Rana Muhammad Adnan. "Evaluation and Mapping of Snow Characteristics Using Remote Sensing Data in Astore River Basin, Pakistan." Atmosphere 16, no. 5 (2025): 550. https://doi.org/10.3390/atmos16050550.

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Being an agricultural country, Pakistan requires lots of water for irrigation. A major portion of its water resources is located in the upper indus basin (UIB). The snowmelt runoff generated from high-altitude areas of the UIB provides inflow into the Indus river system that boosts the water supply. Snow accumulation during the winter period in the highlands in the watershed(s) becomes a source of water inflow during the snow-melting period, which is described according to characteristics like snow depth, snow density, and snow water equivalent. Snowmelt water release (SWE) and snowmelt water

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Tesis sobre el tema "Irrigation, Land Surface Model, Remote Sensing, Data Assimilation"

Modanesi, Sara. "Innovative Use of Earth Observation and Land Surface Modeling for Tracking the Effects of Irrigation on the Terrestrial Water Cycle." Doctoral thesis, 2022. http://hdl.handle.net/2158/1275878.

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In recent years, human water needs have been steadily increasing and they are currently dominated by agricultural activities for food production worldwide. Furthermore, the increase in population and climatic change are expected to raise the current demand of water highlighting the necessity for more efficient irrigation systems. In this context, the combined effect of human pressure (i.e. irrigation) and the increase of extreme natural phenomena, such as drought events, has a strong impact on the global water budget with a local depletion of water resources, especially groundwater. However, o

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Capítulos de libros sobre el tema "Irrigation, Land Surface Model, Remote Sensing, Data Assimilation"

Akyürek Z. and Şorman A.Ü. "Assessment of different topographic corrections in MODIS data for mapping effective snow covered areas in mountainous terrain." In Remote Sensing for a Changing Europe. IOS Press, 2009. https://doi.org/10.3233/978-1-58603-986-8-61.

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Topography and its derivatives (altitude, slope and aspect) have an effect on satellite-measured radiances. For mountainous areas the sun zenith and azimuth angles, as well as direction of observation relative to these are more limiting factors. In this paper four topographic normalization methods were used to correct the reflectance values of medium spatial resolution satellite data, namely MODIS. The performance of the topographic normalization methods is examined for snow covered areas of the study area located in the eastern part of Turkey. Modeling of snow-covered area in the mountainous

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Actas de conferencias sobre el tema "Irrigation, Land Surface Model, Remote Sensing, Data Assimilation"

Zhu, He, Shifeng Huang, Kun Yang, Jianwei Ma, Yongmin Yang, and Yayong Sun. "Study on the Soil Moisture Content Modelling and Data Assimilation Based on Remote Sensing and Land Surface Model." In IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2019. http://dx.doi.org/10.1109/igarss.2019.8898355.

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