English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Rainfall information is a prerequisite to and plays a vital role in driving hydrological models. However, limited by the observation methods, the obtained precipitation data, at present, are still too coarse. In this study, a new downscaling method was proposed to obtain high spatial resolution (~1 km/hourly) precipitation estimates based on Integrated Multi-satellitE Retrievals for GPM (IMERG) data at hourly scale. Compared with original IMERG data, the downscaled precipitation results showed the similar spatial patterns with those of original IMERG data, but with finer spatial resolution. In addition, the downscaled precipitation estimates were further analyzed to quantify their improvements using the Coupled Routing and Excess STorage (CREST) model across Ganjiang River basin. Compared with the observed streamflow, the downscaled precipitation results showed satisfying hydrological performance, with Nash-Sutcliffe Coefficient of Efficiency (NSCE), Root Mean Square Error (RMSE), Relative Bias (BIAS), and Correlation Coefficient (CC). The improvement in terms of four statistic metrics in terms of streamflow simulation also indicated great potential of hydrological utility for the downscaled precipitation results.

The First Comparisons of IMERG and the Downscaled Results Based on IMERG in Hydrological Utility over the Ganjiang River Basin