Hydrological evaluation of open-access precipitation and air temperature datasets using SWAT in a poorly gauged basin in Ethiopia

Abstract

Precipitation and air temperature are key drivers of watershed models. Currently there are many open-access gridded precipitation and air temperature datasets at different spatial and temporal resolutions over global or quasi-global scale. Motivated by the scarcity and substantial temporal and spatial gaps in ground measurements in Africa, this study evaluated the performance of three open-access precipitation datasets (i.e. CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data), TRMM (Tropical Rainfall Measuring Mission) and CFSR (Climate Forecast System Reanalysis)) and one air temperature dataset (CFSR) in driving Soil and Water Assessment Tool (SWAT) model in simulation of daily and monthly streamflow in the upper Gilgel Abay Basin, Ethi temperature from sparse gauge stations were also used to drive SWAT model and the results were compared with those using open-access datasets. After a comprehensive comparison of a total of eight model scenarios with different combinations of precipitation and air temperature inputs, we draw the following conclusions: (1) using measured precipitation from even sparse available stations consistently yielded better performance in streamflow simulation than using all three open-access precipitation datasets; (2) using CFSR air temperature yielded almost identical performance in streamflow simulation to using measured air temperature from gauge stations; (3) among the three open-access precipitation, overall CHIRPS yielded best performance. These results suggested that the CHIRPS precipitation available at high spatial resolution (0.05 ) together with CFSR air temperature can be a promising alternative open-access data source for streamflow simulation in this data-scarce area in the case of limited access to desirable gauge data.

The vertical influence of temperature and precipitation on snow cover variability in the Central Tianshan Mountains, Northwest China

“…Duan, Liu, Tuo, Chiogna, and Disse (2016) evaluated eight gridded precipitation products against interpolated rain gauge data at the common 0.25°spatial resolution, showing that CHIRPS comparably ranks as one of the top three best performing products in terms of a suite of statistical metrics. In addition, good performance of CHIRPS was also found in many other regions (Duan et al, 2019). We chose CHIRPS because of its fine solution (0.05°) and demonstrated good performance.…”

Re-evaluation of the Power of the Mann-Kendall Test for Detecting Monotonic Trends in Hydrometeorological Time Series

“…Compared to parametric tests (e.g., regression coefficient test), non-parametric tests (e.g., the MK test and Spearman' rho test) have no requirements of homoscedasticity or prior assumptions on the distribution of the data sample (Önöz and Bayazit, 2003) and are less sensitive to outliers (Hamed and Ramachandra Rao, 1998;Hamed, 2007). As the MK test statistic is determined by the ranks and sequences of time series rather than the original values, it is robust when dealing with nonnormally distributed data, censored data, and time series with missing values (Hirsch and Slack, 1984), which are commonly encountered in hydrometeorological time series (Duan et al, 2018(Duan et al, , 2019Gao et al, 2018Gao et al, , 2019Dong et al, 2019).…”

The Response of the Aerosol Distribution to Monsoon Intensity Over the Summer Monsoon Transition Zone

“…The concentration of aerosol in East Asia is relatively high, which is due to the large emissions associated with rapid economic growth and industrialization. The interaction between the East Asian summer monsoon (EASM) and aerosols had attracted much attention in climatic and environmental studies, such as the deterioration of air quality, intensification of drought, and exacerbated flooding disasters (Gao et al, 2018;Wang et al, 2018;Zhu et al, 2018;Duan et al, 2019;Yu et al, 2019). The aerosol concentration in eastern China had shown rising trend after South Asia over time.…”