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All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Influence of Precipitation Forcing Uncertainty on Hydrological Simulations with the NASA South Asia Land Data Assimilation System

Accurate meteorological estimates are critical for process-based hydrological simulationand prediction. This presents a significant challenge in mountainous Asia where in situmeteorological stations are limited and major river basins cross international borders. In thiscontext, remotely sensed and model-derived meteorological estimates are often necessary inputsfor distributed hydrological analysis. However, these datasets are difficult to evaluate on accountof limited access to ground data. In this case, the implications of uncertainty associated withprecipitation forcing for hydrological simulations is explored by driving the South Asia Land DataAssimilation System (South Asia LDAS) using a range of meteorological forcing products.MERRA2, GDAS, and CHIRPS produce a wide range of estimates for rainfall, which causes awidespread simulated streamflow and evapotranspiration. A combination of satellite-derived andlimited in situ data are applied to evaluate model simulations and, by extension, to constrain theestimates of precipitation. The results show that available gridded precipitation estimates based onin situ data may systematically underestimate precipitation in mountainous regions and thatperformance of gridded satellite-derived or modeled precipitation estimates varies systematicallyacross the region. Since no station-based data or product including station data is satisfactoryeverywhere, our results suggest that the evaluation of the hydrological simulation of streamflowand ET can be used as an indirect evaluation of precipitation forcing based on ground-basedproducts or in-situ data. South Asia LDAS produces reasonable evapotranspiration and streamflowwhen forced with appropriate meteorological forcing and the choice of meteorological forcingshould be made based on the geographical location as well as on the purpose of the simulations.

South Asia land data assimilation system (South As↗
DOE OSTI2017

Continuous energy cross section adjustment: a new method to generalize nuclear data assimilation for a wider range of applications.

This work presents a new method to perform continuous-energy cross section adjustment. The proposed method is based on recently developed Monte Carlo perturbation capabilities with continuous-energy sensitivity functions implemented in an extended Serpent version. The generation of continuous energy basis functions aseigendecomposition of the covariance matrices and the Generalized Least Squares method applied to these functions are described. The new approach is verified against standard, multi-group adjustment methodologies in a case study involving four different response functions in Jezebel. The results obtained by the two approaches for the selected case study are presented and compared in term of adjusted cross sections, adjusted covariance matrices, and uncertainty reduction.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗