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

Debjani Ghatak,Christopher Hain,Martha Anderson,Birendra Bajracharya,Sujay Kumar,Mir A. Matin,Benjamin Zaitchik

doi:10.3390/hydrology5040057

Abstract

Accurate meteorological estimates are critical for process-based hydrological simulation and prediction. This presents a significant challenge in mountainous Asia where in situ meteorological stations are limited and major river basins cross international borders. In this context, remotely sensed and model-derived meteorological estimates are often necessary inputs for distributed hydrological analysis. However, these datasets are difficult to evaluate on account of limited access to ground data. In this case, the implications of uncertainty associated with precipitation forcing for hydrological simulations is explored by driving the South Asia Land Data Assimilation 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 a widespread simulated streamflow and evapotranspiration. A combination of satellite-derived and limited in situ data are applied to evaluate model simulations and, by extension, to constrain the estimates of precipitation. The results show that available gridded precipitation estimates based on in situ data may systematically underestimate precipitation in mountainous regions and that performance of gridded satellite-derived or modeled precipitation estimates varies systematically across the region. Since no station-based data or product including station data is satisfactory everywhere, our results suggest that the evaluation of the hydrological simulation of streamflow and ET can be used as an indirect evaluation of precipitation forcing based on ground-based products or in-situ data. South Asia LDAS produces reasonable evapotranspiration and streamflow when forced with appropriate meteorological forcing and the choice of meteorological forcing should be made based on the geographical location as well as on the purpose of the simulations.

Highlights

There is a pressing need for objective, reliable, and physically consistent information on the variability in water resources across South Asia
We examined LSM predictions including evapotranspiration and streamflow in order to assess the impact that precipitation forcing has on the realism of hydrological simulation
Even though the South Asia LDAS includes a large area that includes much of Afghanistan, the Tibetan Plateau, China, and Myanmar, we focus our analysis on transboundary rivers that originate in the Hindu Kush-Himalaya (HKH) and flow south

Summary

Introduction

There is a pressing need for objective, reliable, and physically consistent information on the variability in water resources across South Asia. This is true for transboundary hydrological basins that have headwaters in the Hindu Kush-Himalaya (HKH) mountain belt. These mountains give rise to some of the longest rivers of the world and these rivers, in turn, provide water resources to hundreds of millions of people spread across numerous countries. Hydrological monitoring and prediction in these critical river basins is fraught with uncertainty, which poses challenges to cooperative transboundary management, flood warnings, preparedness activities, and projections of hydrologic change under global warming and upstream development. Climate change increases the uncertainty, intensity, and the frequency of hydrological extremes [7,8]

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Results

Conclusion