scholarly journals Bayesian merging of numerical modeling and remote sensing for saltwater intrusion quantification in the Vietnamese Mekong Delta

2021 ◽  
Author(s):  
Anh Phuong Tran ◽  
Chien Pham ◽  
Phong Le ◽  
Thanh Thuy Nguyen ◽  
Cuong Tran ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Numerical Simulation ◽  
Numerical Simulations ◽  
Saltwater Intrusion ◽  
Mekong Delta ◽  
Data Sources ◽  
Hybrid Technique ◽  
Landsat Images ◽  
Multiple Data ◽  
Agriculture And Food

Saltwater intrusion has become one of the most concerning issues in the Vietnamese Mekong Delta (VMD) due to its increasing impacts on agriculture and food security of Vietnam. Reliable estimation of salinity plays a crucial role to mitigate the impacts of saltwater intrusion. This study developed a hybrid technique that merges satellite imagery with numerical simulations to improve the estimation of salinity in the VMD. The salinity derived from Landsat images and by numerical simulations was fused using the Bayesian inference technique. The results indicate that our technique significantly reduces the uncertainties and improves the accuracy of salinity estimates. The Nash-Sutcliffe coefficient is 0.73, which is much higher than that of numerical simulation (0.69) and Landsat estimation (0.67). The correlation coefficient between the merged and measured salinity is relatively high (0.75). The variance of the ensemble salinity errors (2.57 ppt) is lower than that of Landsat estimation (3.65 ppt) and numerical simulations (8.69 ppt). The proposed approach in this study shows a great potential to combine multiple data sources of a variable of interest to improve its accuracy and reliability wherever these data are available.

Integration of statistical and administrative agricultural data from Namibia

2021 ◽  
pp. 1-22
Author(s):  
Emily Berg ◽  
Johgho Im ◽  
Zhengyuan Zhu ◽  
Colin Lewis-Beck ◽  
Jie Li
Keyword(s):  
Measurement Error ◽  
Data Collection ◽  
Administrative Data ◽  
Statistical Data ◽  
Data Sources ◽  
Extension Programs ◽  
Multiple Data ◽  
Administrative Agencies ◽  
Crop Area ◽  
Using Data

Statistical and administrative agencies often collect information on related parameters. Discrepancies between estimates from distinct data sources can arise due to differences in definitions, reference periods, and data collection protocols. Integrating statistical data with administrative data is appealing for saving data collection costs, reducing respondent burden, and improving the coherence of estimates produced by statistical and administrative agencies. Model based techniques, such as small area estimation and measurement error models, for combining multiple data sources have benefits of transparency, reproducibility, and the ability to provide an estimated uncertainty. Issues associated with integrating statistical data with administrative data are discussed in the context of data from Namibia. The national statistical agency in Namibia produces estimates of crop area using data from probability samples. Simultaneously, the Namibia Ministry of Agriculture, Water, and Forestry obtains crop area estimates through extension programs. We illustrate the use of a structural measurement error model for the purpose of synthesizing the administrative and survey data to form a unified estimate of crop area. Limitations on the available data preclude us from conducting a genuine, thorough application. Nonetheless, our illustration of methodology holds potential use for a general practitioner.

Exploring young learners’ L2 development and perceptions of mixed-age and same-age peer interactions in EFL mixed-age classrooms

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Tomas Kos
Keyword(s):  
Foreign Language ◽  
Peer Interactions ◽  
Language Instruction ◽  
Data Sources ◽  
Foreign Language Instruction ◽  
Young Learners ◽  
Multiple Data ◽  
L2 Development ◽  
Post Test ◽  
Mixed Age

Abstract Although foreign language instruction in mixed-age (M-A) is gaining popularity (Heizmann and Ries and Wicki 2015; Lau and Juby-Smith and Desbiens, 2017; Shahid Kazi and Moghal and Aziz 2018; Thurn 2011), the research is scarce. Drawing from multiple data sources, this study investigated to what extent do peer interactions among M-A and same-age (S-A) pairs aid L2 development and how students perceive their interactions. In this study, the same learners (N=24) aged between 10 and 12 interacted with the same and different age partners during common classroom lessons in two EFL classrooms. The results suggest that both S-A and M-A peer interactions aided L2 development. Although S-A pairs outperformed M-A pairs on the post-test, the results are not statistically significant. The analysis of students’ perceptions revealed that the majority of students prefer working in S-A to M-A pairs. In addition to age/proficiency differences, factors such as students’ relationships and perceptions of one’s own and partner’s proficiency greatly impact how they interact with one another.

scholarly journals Examining Deep Learning Models with Multiple Data Sources for COVID-19 Forecasting

2020 ◽  
Author(s):  
Lijing Wang ◽  
Aniruddha Adiga ◽  
Srinivasan Venkatramanan ◽  
Jiangzhuo Chen ◽  
Bryan Lewis ◽  
...  
Keyword(s):  
Deep Learning ◽  
Data Sources ◽  
Learning Models ◽  
Multiple Data Sources ◽  
Multiple Data

scholarly journals Saltwater intrusion into groundwater systems in the Mekong Delta and links to global change

2021 ◽  
Author(s):  
Han Xiao ◽  
Yin Tang ◽  
Hai-Ming Li ◽  
Lu Zhang ◽  
Thanh Ngo-Duc ◽  
...  
Keyword(s):  
Global Change ◽  
Saltwater Intrusion ◽  
Mekong Delta ◽  
Groundwater Systems

scholarly journals Attribution of Long-Term Evapotranspiration Trends in the Mekong River Basin with a Remote Sensing-Based Process Model

2021 ◽  
Vol 13 (2) ◽  
pp. 303
Author(s):  
Shi Hu ◽  
Xingguo Mo
Keyword(s):  
Remote Sensing ◽  
Water Resources ◽  
Solar Radiation ◽  
River Basin ◽  
Mekong Delta ◽  
Mekong River ◽  
Catchment Management ◽  
Mekong River Basin ◽  
Area Index ◽  
Available Water

Using the Global Land Surface Satellite (GLASS) leaf area index (LAI), the actual evapotranspiration (ETa) and available water resources in the Mekong River Basin were estimated with the Remote Sensing-Based Vegetation Interface Processes Model (VIP-RS). The relative contributions of climate variables and vegetation greening to ETa were estimated with numerical experiments. The results show that the average ETa in the entire basin increased at a rate of 1.16 mm year−2 from 1980 to 2012 (36.7% of the area met the 95% significance level). Vegetation greening contributed 54.1% of the annual ETa trend, slightly higher than that of climate change. The contributions of air temperature, precipitation and the LAI were positive, whereas contributions of solar radiation and vapor pressure were negative. The effects of water supply and energy availability were equivalent on the variation of ETa throughout most of the basin, except the upper reach and downstream Mekong Delta. In the upper reach, climate warming played a critical role in the ETa variability, while the warming effect was offset by reduced solar radiation in the Mekong Delta (an energy-limited region). For the entire basin, the available water resources showed an increasing trend due to intensified precipitation; however, in downstream areas, additional pressure on available water resources is exerted due to cropland expansion with enhanced agricultural water consumption. The results provide scientific basis for practices of integrated catchment management and water resources allocation.

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