Technical Note: Evaluation and bias correction of an observations-based global runoff dataset using historical streamflow observations from small tropical catchments in the Philippines
Authors: Ibarra Daniel E. , David Carlos Primo C. , Tolentino Pamela Louise M. 
Published: February 2020

Abstract. The predictability of freshwater availability is one of the most important issues facing the world's population. Even in relatively wet tropical regions, seasonal fluctuations in the water cycle complicate the consistent and reliable supply of water to urban, industrial and agricultural demands. Importantly, historic streamflow monitoring datasets are crucial in assessing our ability to model and subsequently plan for future hydrologic changes. In this technical note we evaluate a new global product of monthly runoff (GRUN_v1; Ghiggi et al., 2019) using small tropical catchments in the Philippines. This observations-based monthly runoff product is evaluated using archived monthly streamflow data from 55 catchments with at least 10 years of data, extending back to 1946 in some cases. These catchments are completely independent of the GRUN gridded product as no catchments in the Philippines were of sufficient size to fulfil the original filtering criteria and databases of these data were either not digitized or difficult to compile. Using monthly runoff observations from catchments with more than 10 years of data between 1946 and 2014, we demonstrate across all observations significant but weak correlation (r2 = 0.372) and skilful prediction (Volumetric Efficiency = 0.363 and log(Nash–Sutcliff Efficiency) = 0.453) between the predicted values and the observations. At a regional scale we demonstrate that GRUN performs best among catchments located in Climate Types III (no pronounced maximum rainfall with short dry season) and IV (evenly distributed rainfall, no dry season). We also find a weak negative correlation between volumetric efficiency and catchment area, and a positive correlation between volumetric efficiency and mean observed runoff. Further, analysis of individual rivers demonstrates systematic biases (over and under) in baseflow during the dry season, and under-prediction of peak flow during some wet months among most catchments. These results demonstrate the potential utility of GRUN and future data products of this nature with due consideration and correction of systematic biases at the individual basin level to: (1) assess trends in regional scale runoff over the past century, (2) validate hydrologic models for un-monitored catchments in the Philippines, and (3) assess the impact of hydrometeorological phenomenon to seasonal water supply in this wet but drought prone archipelago. Finally, to correct for underprediction during wet months we perform a log-transform bias correction which greatly improves the nationwide Root Mean Square Error between GRUN and the observations by an order of magnitude (2.648 vs. 0.292 mm/day). This technical note demonstrates the importance of performing such corrections when accounting for the proportional contribution of catchments from smaller catchments in tropical land such as the Philippines to global tabulations of discharge.