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Improved Mekong Basin Runoff Estimate and Its Error Characteristics Using Pure Remotely Sensed Data Products

Fok, Hok Sum, Chen, Yutong, Wang, Lei, Tenzer, Robert, and He, Qing, 2021. Improved Mekong Basin Runoff Estimate and Its Error Characteristics Using Pure Remotely Sensed Data Products. Remote Sensing, 13(5):996, doi:10.3390/rs13050996.

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@ARTICLE{2021RemS...13..996F,
       author = {{Fok}, Hok Sum and {Chen}, Yutong and {Wang}, Lei and {Tenzer}, Robert and {He}, Qing},
        title = "{Improved Mekong Basin Runoff Estimate and Its Error Characteristics Using Pure Remotely Sensed Data Products}",
      journal = {Remote Sensing},
     keywords = {basin discharge, remote sensing hydrology, water balance, Mekong River Basin},
         year = 2021,
        month = mar,
       volume = {13},
       number = {5},
          eid = {996},
        pages = {996},
     abstract = "{Basin runoff is a quantity of river discharge per unit basin area
        monitored close to an estuary mouth, essential for providing
        information on the flooding and drought conditions of an entire
        river basin. Owing to a decreasing number of in situ monitoring
        stations since the late 1970s, basin runoff estimates using
        remote sensing have been advocated. Previous runoff estimates of
        the entire Mekong Basin calculated from the water balance
        equation were achieved through the hybrid use of remotely sensed
        and model-predicted data products. Nonetheless, these basin
        runoff estimates revealed a weak consistency with the in situ
        ones. To address this issue, we provide a newly improved
        estimate of the monthly Mekong Basin runoff by using the
        terrestrial water balance equation, purely based on remotely
        sensed water balance component data products. The remotely
        sensed water balance component data products used in this study
        included the satellite precipitation from the Tropical Rainfall
        Measuring Mission (TRMM), the satellite evapotranspiration from
        the Moderate Resolution Imaging Spectroradiometer (MODIS), and
        the inferred terrestrial water storage from the Gravity Recovery
        and Climate Experiment (GRACE). A comparison of our new estimate
        and previously published result against the in situ runoff
        indicated a marked improvement in terms of the Pearson's
        correlation coefficient (PCC), reaching 0.836 (the new estimate)
        instead of 0.621 (the previously published result). When a
        three-month moving-average process was applied to each data
        product, our new estimate further reached a PCC of 0.932, along
        with the consistent improvement revealed from other evaluation
        metrics. Conducting an error analysis of the estimated mean
        monthly runoff for the entire data timespan, we found that the
        usage of different evapotranspiration data products had a
        substantial influence on the estimated runoff. This indicates
        that the choice of evapotranspiration data product is critical
        in the remotely sensed runoff estimation.}",
          doi = {10.3390/rs13050996},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2021RemS...13..996F},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

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