Earth System Science Data | 2019
Integrated hydrometeorological, snow and frozen-ground observations in the alpine region of the Heihe River Basin, China
Abstract
Abstract. The alpine region is important in riverine and watershed\necosystems as a contributor of freshwater, providing and stimulating\nspecific habitats for biodiversity. In parallel, recent climate change,\nhuman activities and other perturbations may disturb hydrological processes\nand eco-functions, creating the need for next-generation observational and\nmodeling approaches to advance a predictive understanding of such processes\nin the alpine region. However, several formidable challenges, including the\ncold and harsh climate, high altitude and complex topography, inhibit\ncomplete and consistent data collection where and when it is needed, which hinders the\ndevelopment of remote-sensing technologies and alpine hydrological models.\nThe current study presents a suite of datasets consisting of long-term\nhydrometeorological, snow cover and frozen-ground data for investigating\nwatershed science and functions from an integrated, distributed and\nmultiscale observation network in the upper reaches of the Heihe River Basin\n(HRB) in China. Meteorological and hydrological data were monitored from an\nobservation network connecting a group of automatic meteorological stations\n(AMSs). In addition, to capture snow accumulation and ablation processes,\nsnow cover properties were collected from a snow observation superstation\nusing state-of-the-art techniques and instruments. High-resolution soil\nphysics datasets were also obtained to capture the freeze–thaw processes\nfrom a frozen-ground observation superstation. The updated datasets were\nreleased to scientists with multidisciplinary backgrounds (i.e., cryospheric\nscience, hydrology and meteorology), and they are expected to serve as a\ntesting platform to provide accurate forcing data and validate and evaluate\nremote-sensing products and hydrological models for a broader community. The\ndatasets are available from the Cold and Arid Regions Science Data Center at\nLanzhou ( https://doi.org/10.3972/hiwater.001.2019.db , Li, 2019).