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Determining mean transit times in headwater catchments is critical for understanding catchment functioning and understanding their responses to changes in landuse or climate. Determining whether mean transit times (MTTs) correlate with drainage density, slope angle, area, or land cover permits a better understanding of the controls on water flow through catchments and allows first-order predictions of MTTs in other catchments to be made. This study assesses whether there are identifiable controls on MTTs determined using 3H in headwater catchments of southeast Australia. Despite MTTs at baseflow varying from a few years to >100 years, it was difficult to predict MTTs using single or groups of readily-measured catchment attributes. The lack of readily-identifiable correlations hampers the prediction of MTTs in adjacent catchments even where these have similar geology, land use, and topography. The long MTTs of the Australian headwater catchments are probably in part due to the catchments having high storage volumes in deeply-weathered regolith, combined with low recharge rates due to high evapotranspiration. However, the difficulty in estimating storage volumes at the catchment scale hampers the use of this parameter to estimate MTTs. The runoff coefficient (the fraction of rainfall exported via the stream) is probably also controlled by evapotranspiration and recharge rates. Correlations between the runoff coefficient and MTTs in individual catchments allow predictions of MTTs in nearby catchments to be made. MTTs are shorter in high rainfall periods as the catchments wet up and shallow water stores are mobilized. Despite the contribution of younger water, the major ion geochemistry in individual catchments commonly does not correlate with MTTs, probably reflecting heterogeneous reactions and varying degrees of evapotranspiration. Documenting MTTs in catchments with high storage volumes and/or low recharge rates elsewhere is important for understanding MTTs in diverse environments.  相似文献   
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All BeiDou navigation satellite system (BDS) satellites are transmitting signals on three frequencies, which brings new opportunity and challenges for high-accuracy precise point positioning (PPP) with ambiguity resolution (AR). This paper proposes an effective uncalibrated phase delay (UPD) estimation and AR strategy which is based on a raw PPP model. First, triple-frequency raw PPP models are developed. The observation model and stochastic model are designed and extended to accommodate the third frequency. Then, the UPD is parameterized in raw frequency form while estimating with the high-precision and low-noise integer linear combination of float ambiguity which are derived by ambiguity decorrelation. Third, with UPD corrected, the LAMBDA method is used for resolving full or partial ambiguities which can be fixed. This method can be easily and flexibly extended for dual-, triple- or even more frequency. To verify the effectiveness and performance of triple-frequency PPP AR, tests with real BDS data from 90 stations lasting for 21 days were performed in static mode. Data were processed with three strategies: BDS triple-frequency ambiguity-float PPP, BDS triple-frequency PPP with dual-frequency (B1/B2) and three-frequency AR, respectively. Numerous experiment results showed that compared with the ambiguity-float solution, the performance in terms of convergence time and positioning biases can be significantly improved by AR. Among three groups of solutions, the triple-frequency PPP AR achieved the best performance. Compared with dual-frequency AR, additional the third frequency could apparently improve the position estimations during the initialization phase and under constraint environments when the dual-frequency PPP AR is limited by few satellite numbers.  相似文献   
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International Journal of Earth Sciences - Stratigraphically well-defined volcanic rocks in Palaeozoic volcano-sedimentary units of the Frankenwald area (Saxothuringian Zone, Variscan Orogen) were...  相似文献   
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