A dataset of soil moisture in Xishuangbanna tropical seasonal rain forests (2009–2017)

Abstract

As the carrier of material circulation and energy flow, soil moisture plays an important role in terrestrial forest ecosystems. Observing soil moisture is beneficial for unveiling the hydrological characteristics, water conservation capacity and ecosystem service function of forest ecosystems. The tropical rain forest is among the most biodiverse ecosystems. There are large areas of tropical rain forests in Xishuangbanna, where the tropical seasonal rain forest represents a prominent vegetation type. Conducting continuous, long-term and high-quality ecological monitoring is one of the main tasks of China Ecosystem Research Network (CERN). Soil moisture content is an important indicator in the long-term site-specific water environment observations within the terrestrial ecosystems monitored by CERN. This dataset comprises soil moisture content data collected from January 2009 to December 2017 at the Xishuangbanna Station for Tropical Rainforest Ecosystem Studies of the Chinese Academy Sciences (also known as National Forest Ecosystem Research Station at Xishuangbanna, BNF for short), with a total of 2,879 entries. The determination method used for this dataset is fixed-point continuous observation using Time Domain Reflectometry (TDR) instruments; observations were conducted at multiple, ranging from 0–10 cm, 10–20 cm, 20–30 cm, 30–40 cm, 40–50 cm, 50–70 cm, 70–90 cm and 90–110 cm. The observation frequency consists of 3 times per month, respectively at the beginning, middle and end of each month. The observations were conducted strictly according to the CERN observation and quality control protocols. The dataset is readily available for online sharing and serves as essential foundational data for conducting research on tropical forest hydrology under the global climate change and different vegetation environments.