分类： 地球科学 >> 大气科学 提交时间： 2024-03-13 合作期刊: 《干旱区科学》
摘要： Xinjiang Uygur Autonomous Region is a typical inland arid area in China with a sparse and uneven distribution of meteorological stations, limited access to precipitation data, and significant water scarcity. Evaluating and integrating precipitation datasets from different sources to accurately characterize precipitation patterns has become a challenge to provide more accurate and alternative precipitation information for the region, which can even improve the performance of hydrological modelling. This study evaluated the applicability of widely used five satellite-based precipitation products (Climate Hazards Group InfraRed Precipitation with Station (CHIRPS), China Meteorological Forcing Dataset (CMFD), Climate Prediction Center morphing method (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), and Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (TMPA)) and a reanalysis precipitation dataset (ECMWF Reanalysis v5-Land Dataset (ERA5-Land)) in Xinjiang using ground-based observational precipitation data from a limited number of meteorological stations. Based on this assessment, we proposed a framework that integrated different precipitation datasets with varying spatial resolutions using a dynamic Bayesian model averaging (DBMA) approach, the expectation-maximization method, and the ordinary Kriging interpolation method. The daily precipitation data merged using the DBMA approach exhibited distinct spatiotemporal variability, with an outstanding performance, as indicated by low root mean square error (RMSE=1.40 mm/d) and high Person's correlation coefficient (CC=0.67). Compared with the traditional simple model averaging (SMA) and individual product data, although the DBMA-fused precipitation data were slightly lower than the best precipitation product (CMFD), the overall performance of DBMA was more robust. The error analysis between DBMA-fused precipitation dataset and the more advanced Integrated Multi-satellite Retrievals for Global Precipitation Measurement Final (IMERG-F) precipitation product, as well as hydrological simulations in the Ebinur Lake Basin, further demonstrated the superior performance of DBMA-fused precipitation dataset in the entire Xinjiang region. The proposed framework for solving the fusion problem of multi-source precipitation data with different spatial resolutions is feasible for application in inland arid areas, and aids in obtaining more accurate regional hydrological information and improving regional water resources management capabilities and meteorological research in these regions.
分类： 环境科学技术及资源科学技术 >> 环境科学技术基础学科 提交时间： 2022-03-24 合作期刊: 《干旱区科学》
摘要： Studies on the ecosystem service value (ESV) of gardens are critical for informing evidence- based land management practices based on an understanding of the local ecosystem. By analyzing equivalent value factors (EVFs), this paper evaluated the values of 11 ecosystem services of gardens in the Yellow River Basin of China in 2019. High-precision land use survey data were used to improve the accuracy of the land use classification, garden areas, and spatial distribution of the ESVs of gardens. The results showed that garden ecosystem generally had high ESVs, especially in terms of the ESV of food production, which is worthy of further research and application to the practice of land use planning and management. Specifically, the value of one standard EVF of ecosystem services in 2019 was 3587.04 CNY/(hm2a), and the ESV of food production of gardens was much higher than that of croplands. Garden ecosystem provided an ESV of 1348.66108 CNY/a in the Yellow River Basin. The areas with the most concentrated ESVs of gardens were located in four regions: downstream in the Shandong-Henan zone along the Yellow River, mid-stream in the Shanxi-Shaanxi zone along the Yellow River, the Weihe River Basin, and upstream in the Qinghai-Gansu-Ningxia-Inner Mongolia zone along the Yellow River. The spatial correlation of the ESVs in the basin was significant (global spatial autocorrelation index Moran's I=0.464), which implied that the characteristics of high ESVs adjacent to high ESVs and low ESVs adjacent to low ESVs are prominent. In the Yellow River Basin, the contribution of the ESVs of gardens to the local environment and economy varied across regions. We also put forward some suggestions for promoting the construction of ecological civilization in the Yellow River Basin. The findings of this study provide important contributions to the research of ecosystem service evaluation in the Yellow River Basin.
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