scholarly journals ADDENDUM TO WATER RESOURCE ASSESSMENT IN THE NEW MEXICO PERMIAN BASIN.

2021 ◽  
Author(s):  
Alexander Reardon ◽  
Owen Lofton ◽  
Patricia Johnson ◽  
Thomas Lowry
Keyword(s):  
New Mexico ◽  
Water Resource ◽  
Resource Assessment ◽  
Permian Basin ◽  
Water Resource Assessment

scholarly journals Water Resource Assessment in the New Mexico Permian Basin

2018 ◽  
Author(s):  
Thomas Stephen Lowry ◽  
Michael D. Schuhen ◽  
Owen W. Lofton ◽  
La Tonya Nicole Walker ◽  
Patricia Blair Johnson ◽  
...  
Keyword(s):  
New Mexico ◽  
Water Resource ◽  
Resource Assessment ◽  
Permian Basin ◽  
Water Resource Assessment

scholarly journals Assimilation of D-InSAR snow depth data by an ensemble Kalman filter

2021 ◽  
Vol 14 (6) ◽  
Author(s):  
Jinming Yang ◽  
Chengzhi Li
Keyword(s):  
Remote Sensing ◽  
Kalman Filter ◽  
Water Resource ◽  
Ensemble Kalman Filter ◽  
Snow Depth ◽  
Resource Assessment ◽  
Measured Data ◽  
Hydrological Process ◽  
Depth Data ◽  
Water Resource Assessment

AbstractSnow depth mirrors regional climate change and is a vital parameter for medium- and long-term numerical climate prediction, numerical simulation of land-surface hydrological process, and water resource assessment. However, the quality of the available snow depth products retrieved from remote sensing is inevitably affected by cloud and mountain shadow, and the spatiotemporal resolution of the snow depth data cannot meet the need of hydrological research and decision-making assistance. Therefore, a method to enhance the accuracy of snow depth data is urgently required. In the present study, three kinds of snow depth data which included the D-InSAR data retrieved from the remote sensing images of Sentinel-1 synthetic aperture radar, the automatically measured data using ultrasonic snow depth detectors, and the manually measured data were assimilated based on ensemble Kalman filter. The assimilated snow depth data were spatiotemporally consecutive and integrated. Under the constraint of the measured data, the accuracy of the assimilated snow depth data was higher and met the need of subsequent research. The development of ultrasonic snow depth detector and the application of D-InSAR technology in snow depth inversion had greatly alleviated the insufficiency of snow depth data in types and quantity. At the same time, the assimilation of multi-source snow depth data by ensemble Kalman filter also provides high-precision data to support remote sensing hydrological research, water resource assessment, and snow disaster prevention and control program.

scholarly journals GLOBAL WATER RESOURCE ASSESSMENT INCLUDING GLACIER MELTWATER FROM MOUNTAINOUS REGIONS

2015 ◽  
Vol 71 (4) ◽  
pp. I_451-I_456
Author(s):  
Masahiro TANOUE ◽  
Satoshi WATANABE ◽  
Takahiro TSUNEKAWA ◽  
Naota HANASAKI ◽  
Yukiko HIRABAYASHI
Keyword(s):  
Water Resource ◽  
Resource Assessment ◽  
Mountainous Regions ◽  
Glacier Meltwater ◽  
Water Resource Assessment ◽  
Global Water
Sign in / Sign up

Export Citation Format

Share Document