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Geothermal heat flow is an essential parameter for the exploration of geothermal energy. The cost is often prohibitive if dense heat flow measurements are arranged in the study area. Regardless, an increase in the limited and sparse heat flow observation points is needed to study the regional geothermal setting. This research is significant in order to provide a new reliable map of terrestrial heat flow for the subsequent development of geothermal resources. The Gradient Boosted Regression Tree (GBRT) prediction model used in this paper is devoted to solving the problem of an insufficient number of heat flow observations in North China. It considers the geological and geophysical information in the region by training the sample data using 12 kinds of geological and geophysical features. Finally, a robust GBRT prediction model was obtained. The performance of the GBRT method was evaluated by comparing it with the kriging interpolation, the minimum curvature interpolation, and the 3D interpolation algorithm through the prediction performance analysis. Based on the GBRT prediction model, a new heat flow map with a resolution of 0.25°×0.25° was proposed, which depicted the terrestrial heat flow distribution in the study area in a more detailed and reasonable way than the interpolation results. The high heat flow values were mostly concentrated in the northeastern boundary of the Tibet Plateau, with a few scattered and small-scale high heat flow areas in the southeastern part of the North China Craton (NCC) adjacent to the Pacific Ocean. The low heat flow values were mainly resolved in the northern part of the Trans-North China Orogenic belt (TNCO) and the southmost part of the NCC. By comparing the predicted heat flow map with the plate tectonics, the olivine-Mg#, and the hot spring distribution in North China, we found that the GBRT could obtain a reliable result under the constraint of geological and geophysical information in regions with scarce and unevenly distributed heat flow observations. [ABSTRACT FROM AUTHOR]

Thermal variations in surface and atmosphere observed from multiple satellites prior to strong earthquakes have been widely reported ever since seismic thermal anomalies were discovered three decades ago. These thermal changes are related to stress accumulation caused by the tectonic activities in the final stage of earthquake preparation. In the present paper, we focused on the thermal changes associated with the 2021 Madoi M 7.3 earthquake in China and analyzed the temporal and spatial evolution of the Index of Microwave Radiation Anomaly (IMRA) and the Index of Longwave Radiation Anomaly (ILRA) based on 8-year microwave brightness temperature (MWBT) and 14-year outgoing longwave radiation (OLR) data collected by satellites. We also explored their responses in different tectonic units (seismogenic fault zone and active tectonic block). Our results indicated that the enhanced IMRA was distributed along the seismogenic fault since mid-February and reappeared for a longer time and with stronger intensity in March and April 2021. The pronounced enhancement in the ILRA was observed within one month over Bayan Har tectonic and adjacent blocks. The higher ILRA over the tectonic blocks in the southern Tibet Plateau at the beginning of 2021 could be associated with the regional stress accumulation, as proven by the occurrences of two moderate earthquakes during this period. [ABSTRACT FROM AUTHOR]

Aboveground net primary productivity (ANPP) and rain-use efficiency (RUE) are important indicators in assessing the response of ecosystems to climate change. In this paper, the Changtang Plateau in the Tibetan Autonomous Region was selected as the study area to analyze the spatial and temporal changes of ANPP and RUE in grassland communities and their response to climate change. The results showed the following:(1) The spatial pattern of ANPP was closely related to rainfall on the Changtang Plateau. The average ANPP over the past 15 years increased gradually from the arid west to the humid east. A consistent pattern was exhibited in different grassland types and climate zones. (2) The RUE was higher at the east and west edges of the Changtang Plateau, especially in the arid west, but was lower in the center. From the perspective of different climatic zones, the average RUE in the southern Tibetan semiarid climate zone and the Ngari arid climate zone was significantly higher than that in other climate zones. However, the average RUE in different grassland types only varied from 0.07 to 0.09 g·m−2·mm−1. The spatial variation in RUE was more distinct in different climatic zones than in different grassland types. (3) Climate change influenced the interannual variation of ANPP and RUE, but the response of ANPP to rainfall showed a significant lag. The interannual change in RUE was negatively correlated with changes in precipitation. (4) In general, a greater area showed a significant increase rather than a decrease in ANPP on the Changtang Plateau, which meant that the grassland condition is improving. The temporal variation patterns of ANPP and RUE in different climate zones were consistent with the overall patterns on the Changtang Plateau, while the variation was not significant in different grassland types. [ABSTRACT FROM AUTHOR]