Stable isotopes in water (e.g., δ2H and δ18O) are important indicators of hydrological and ecological patterns and processes. Tap water can reflect integrated features of regional hydrological processes and human activities. China is a large country with significant meteorological and geographical variations. This report presents the first national-scale survey of Stable Isotopes in Tap Water (SITW) across China. 780 tap water samples have been collected from 95 cities across China from December 2014 to December 2015. (1) Results yielded the Tap Water Line in China is δ2H = 7.72 δ18O + 6.57 (r2 = 0.95). (2) SITW spatial distribution presents typical “continental effect”. (3) SITW seasonal variations indicate clearly regional patterns but no trends at the national level. (4) SITW can be correlated in some parts with geographic or meteorological factors. This work presents the first SITW map in China, which sets up a benchmark for further stable isotopes research across China. This is a critical step toward monitoring and investigating water resources in climate-sensitive regions, so the human-hydrological system. These findings could be used in the future to establish water management strategies at a national or regional scale.
Stable isotopes of O and H in water are meaningful indicators of hydrological and ecological patterns and processes. The Global Network of Isotopes in Precipitation (GNIP) and the Global Network of Isotopes in Rivers (GNIR) are the two most important global databases of isotopes in precipitation and rivers. While the data of GNIP is almost globally distributed, GNIR has an incomplete spatial coverage, which hinders the utilization of river isotopes to study global hydrological cycle. To fill this knowledge gap, this study supplements GNIR and provides a river isotope database with global-coverage by the meta-analysis method, i.e., collecting 17015 additional data points from 215 published articles. Based on the newly compiled database, we find that (1) the relationship between δ18O and δ2H in river waters exhibits an asymmetric imbricate feature, and bifurcation can be observed in Africa and North America, indicating the effect of evaporation on isotopes; (2) multiple regression analysis with geographical factors indicates that spatial patterns of river isotopes are quite different across regions; (3) multiple regression with geographical and meteorological factors can well predict the river isotopes, which provides regional regression models with r2 of 0.50 to 0.89, and the best predictors in different regions are different. This work presents a global map of river isotopes and establishes a benchmark for further research on isotopes in rivers.
Abstract:Understanding the spatio-temporal dynamic of soil moisture is critical in hydrological and other land surface related studies. Until recently, however, there have been controversies about the relationship between spatial mean and spatial variance of soil moisture and the contributions of each of these factors to spatial variability. Therefore, in this study, spatial variability of soil moisture in a 7 km 2 forest catchment is analyzed by time-series data on soil moisture obtained at a total of 12 observation sites. Results showed that soil moisture spatial mean and spatial variance varied almost synchronously and in three cyclic patterns during the monitoring period from 1 April 2015 to 31 October 2015. The spatial mean-variance relationship during the ascending and descending periods of spatial mean could be well-fitted by upward and downward convex quadratic curves, respectively, indicating possible clockwise hysteresis of this relationship. It was found that all through the monitoring period, contributions of time-invariant factors on total spatial variance increased from 68.9% to 88.2% with depth, and temporally stable ranking of sites was obtained. Because of the high spatial variation of soil moisture in our study area, it should be noted that a large number of sample plots would be needed to adequately estimate the spatial variability of soil moisture.
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