Evaluating the present annual water budget of a Himalayan headwater river basin using a high‐resolution atmosphere‐hydrology model

Abstract

Understanding the present water budget in Himalayan Basins is a challenge due to poor in situ coverage, incomplete or unreliable records, and the limitations of coarse resolution gridded data set. In the study, a two‐way coupled implementation of the Weather Research and Forecasting (WRF) Model and the WRF‐Hydro hydrological modeling extension package (WRF/WRF‐Hydro) was employed in its offline configuration, over a 10 year simulation period for a mountainous river basin in North India. A triple nest is employed, in which the innermost domain had 3 km for atmospheric model grids and 300 m for hydrological components. Two microphysical parameterization (MP) schemes are quantitatively evaluated to reveal how differently MP influences orographic‐related precipitation and how it impacts hydrological responses. The WRF‐Hydro modeling system shows reasonable skill in capturing the spatial and temporal structure of high‐resolution precipitation, and the resulting stream flow hydrographs exhibit a good correspondence with observation at monthly timescales, although the model tends to generally underestimate streamflow amounts. The Thompson Scheme fits better to the observations in the study. More importantly, WRF shows that for high‐altitude precipitation, a high “bias” is exhibited in winter precipitation from WRF, which is about double to triple that as estimated from valley‐sited rain gauges and remotely sensed precipitation estimates from Tropical Rainfall Measuring Mission and Asian Precipitation ‐ Highly‐Resolved Observational Data Integration Towards Evaluation. Given the full annual cycle pattern and amount in high‐altitude precipitation and the statistical correspondence in discharge, it is concluded that the WRF‐Hydro modeling system shows potential for explicitly predicting potential changes in the atmospheric‐hydrology cycle of ungauged or poorly gauged basins.

Cloud Resolving WRF Simulations of Precipitation and Soil Moisture Over the Central Tibetan Plateau: An Assessment of Various Physics Options

“…The MP scheme has a significant effect on precipitation in terms of the accumulated precipitation, diurnal cycle, frequency, and persistence time. Overall, the new Thompson scheme outperforms the Lin and WSM6 schemes in the 2‐month simulation, which is consistent with other studies for 1‐week to 3‐month simulations (Li et al, ; Maussion et al, ). The good performance of the new Thompson scheme can be attributed to its special features, including a double moment for the cloud ice (Cassola et al, ), applying the unique mass diameter relationship for snow particles (Song & Sohn, ), and adopting the gamma function to represent the graupel category (Jankov et al, ).…”

“…The evaluations with different time scales reached different conclusions over the TP. For example, the comparison of different microphysical schemes suggested that the Thompson scheme performs better than the other schemes in the spatiotemporal variability of precipitation for 1‐week to 3‐month simulations (Li et al, ; Maussion et al, , ). He et al () found that the Lin scheme performs best in a heavy precipitation event simulation over the TP compared with the schemes of Kesser, Ferrier, and the WRF Single‐Moment 3, 5, 6‐classes.…”

Bias Correction of High‐Resolution Regional Climate Model Precipitation Output Gives the Best Estimates of Precipitation in Himalayan Catchments

“…However, despite the fine spatiotemporal resolution and improved representation of key dynamical and physical processes of a regional climate model, their representation of precipitation (and the subsequent impact of bias correction) over the HKKH remains uncertain. For example, previous studies examining the performance of the Weather Research and Forecasting (WRF) model at high resolution in the HKKH region have typically focused on either one small river catchment or over larger regions that considered only a limited number of in situ measurements for relatively short periods of time of 1 year or less (Bonekamp et al, ; Collier & Immerzeel, ; Li et al, ; Maussion et al, ; Norris et al, ; Orr et al, ), therefore failing to fully assess the model's ability to reproduce the actual detailed patterns of precipitation. Furthermore, though multiple studies have shown the importance of bias correction of precipitation over topographically complex regions (e.g., Bordoy & Burlando, ; Lafon et al, ; Teutschbein & Seibert, ), the usefulness of such methods over the HKKH has yet to be conclusively proven (Shrestha et al, ).…”

Assessment of the Weather Research and Forecasting (WRF) model for simulation of extreme rainfall events in the upper Ganga Basin

“…The Goddard scheme is a slight modification from the PLin scheme for icewater saturation. In general, all the MP schemes are known to influence the rainfall simulations at fine grid resolution by influencing the water phase component (Li et al, 2017). Since each physics scheme is associated with a distinct feature, it is important to examine the effect of their interactions on the rainfall simulations.…”

“…Extremely heavy rainfall on shorter timescales are particularly difficult to predict in mountainous terrains and continue to be a challenge to operational and research communities (Das et al, 2008;Li et al, 2017). Global models have been employed in several studies to understand the large-scale circulation pattern and for quantitative analysis of the monsoon rainfall, but due to their coarse resolution, they are unable to represent the local to regional characteristics of monsoon rainfall.…”