Abstract
Extreme hydrologic events are getting more frequent under a changing climate, and a reliable hydrological modeling framework is important to understand their mechanism. However, existing hydrological modeling frameworks are mostly constrained to a relatively coarse resolution, unrealistic input information, and insufficient evaluations, especially for the large domain, and they are, therefore, unable to address and reconstruct many of the water-related issues (e.g., flooding and drought). In this study, a 0.0625-degree (~6 km) resolution variable infiltration capacity (VIC) model developed for China from 1970 to 2016 was extensively evaluated against remote sensing and ground-based observations. A unique feature in this modeling framework is the incorporation of new remotely sensed vegetation and soil parameter dataset. To our knowledge, this constitutes the first application of VIC with such a long-term and fine resolution over a large domain, and more importantly, with a holistic system-evaluation leveraging the best available earth data. The evaluations using in-situ observations of streamflow, evapotranspiration (ET), and soil moisture (SM) indicate a great improvement. The simulations are also consistent with satellite remote sensing products of ET and SM, because the mean differences between the VIC ET and the remote sensing ET range from −2 to 2 mm/day, and the differences for SM of the top thin layer range from −2 to 3 mm. Therefore, this continental-scale hydrological modeling framework is reliable and accurate, which can be used for various applications including extreme hydrological event detections.
Highlights
Climate change and human activities impose substantial influences on hydrological cycles and water resources, resulting in considerable challenges in multi-scale hydrological research [1]
Compared with other researches aiming to produce the state-of-the-art terrestrial hydrological dataset [15,39], our study mainly focuses on developing and evaluating a hydrological modeling framework that can be extended to couple with the China Meteorological Administration Land Data Simulation System (CLDAS), which provides real-time meteorological inputs and soil moisture (SM) conditions at the same resolution (i.e., 0.0625◦ ) [40]
For the basins with small rainfall and runoff (i.e., Shetang, Maojiahe, and Tsyamusy), the simulations with the default parameters do not match the observations well during the low-flow seasons, but the performance was substantially improved after parameter update and calibration
Summary
Climate change and human activities impose substantial influences on hydrological cycles and water resources, resulting in considerable challenges in multi-scale hydrological research [1]. A high-quality hydrological modeling is key to the improved understanding of land–atmosphere interactions, surface and subsurface interactions, water quality, and human impacts on the terrestrial water cycle [3], which can serve as a benchmark for evaluating extreme events and for preventing record-setting disasters in advance [4,5]. Developing a reliable and accurate hydrological modeling is recognized as important for understanding the implications of climate change [6] and improving the ability of scientists to narrow uncertainties in water resources management [7].
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