Abstract
More than 5 decades of monitoring has documented wide and systematic variation in the stable isotopic composition of precipitation across the globe. This variation is controlled by climatological processes that govern the source, transport and precipitation of atmospheric moisture. Given the ordered and spatially continuous nature of these processes, variation in precipitation isotopic composition represents a near-ideal system for spatial analysis using geostatistical methods. Spatial analysis of precipitation isotopic composition has a long history, and a wide range of methodologies have been applied to the problem of mapping and predicting isotopic compositions at scales ranging from 102 to 104 km. These range from basic space-only interpolation approaches to more quantitative regression and coupled geostatistical/regression techniques, each with particular benefits and drawbacks. Within the last decade, improved methods for generating quantitative predictions of precipitation isotope ratio distributions and the widespread dissemination of precipitation isoscapes via the world wide web have help spur the development of numerous applications of these data products in climatology, hydrology, ecology, and forensics. Current and future research emphasis on continued improvements in water isotope ratio monitoring and novel isoscapes model parameterizations should help lead to the development of dynamic precipitation isoscapes, incorporating both spatial and temporal variation, and enable new research and applications.
Keywords
- Isotopic Composition
- Spatial Autocorrelation
- Geostatistical Method
- Semivariogram Model
- Water Isotope
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Bowen, G.J. (2010). Statistical and Geostatistical Mapping of Precipitation Water Isotope Ratios. In: West, J., Bowen, G., Dawson, T., Tu, K. (eds) Isoscapes. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3354-3_7
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