Precise GPS Positioning by Applying Ionospheric Corrections from an Active Control Network

In this article, initial results are presented of a method to improve fast carrier phase ambiguity resolution over longer baselines (with lengths up to about 200 km). The ionospheric delays in the global positioning system (GPS) data of these long baselines mainly hamper successful integer ambiguity resolution, a prerequisite to obtain precise positions within very short observation time spans. A way to correct the data for significant ionospheric effects is to have a GPS user operate within an active or permanently operating network use ionospheric estimates from this network. A simple way to do so is to interpolate these ionospheric estimates based on the expected spatial behaviour of the ionospheric delays. In this article such a technique is demonstrated for the Dutch Active Control Network (AGRS.NL). One hour of data is used from 4 of the 5 reference stations to obtain very precise ionospheric corrections after fixing of the integer ambiguities within this network. This is no problem because of the relatively long observation time span and known positions of the stations of the AGRS.NL. Next these interpolated corrections are used to correct the GPS data from the fifth station for its ionospheric effects. Initial conclusions about the performance of this technique are drawn in terms of improvement of integer ambiguity resolution for this baseline. ? 1999 John Wiley & Sons, Inc.     

Hydrological response to future land-use change and climate change in a tropical catchment

Hydrological response to expected future changes in land use and climate in the Samin catchment (278 km²) in Java, Indonesia, was simulated using the Soil and Water Assessment Tool model. We analysed changes between the baseline period 1983–2005 and the future period 2030–2050 under both land-use change and climate change. We used the outputs of a bias-corrected regional climate model and six global climate models to include climate model uncertainty. The results show that land-use change and climate change individually will cause changes in the water balance components, but that more pronounced changes are expected if the drivers are combined, in particular for changes in annual streamflow and surface runoff. The findings of this study will be useful for water resource managers to mitigate future risks associated with land-use and climate changes in the study catchment.     

Uncertainty in high and low flows due to model structure and parameter errors

This paper aims to investigate the uncertainty in simulated extreme low and high flows originating from hydrological model structure and parameters. To this end, three different rainfall-runoff models, namely GR4J, HBV and Xinanjiang, are applied to two subbasins of Qiantang River basin, eastern China. The Generalised Likelihood Uncertainty Estimation approach is used for estimating the uncertainty of the three models due to parameter values, henceforth referred as parameter uncertainty. Uncertainty in simulated extreme flows is evaluated by means of the annual maximum discharge and mean annual 7-day minimum discharge. The results show that although the models have good performance for the daily flows, the uncertainty in the extreme flows could not be neglected. The uncertainty originating from parameters is larger than uncertainty due to model structure. The parameter uncertainty of the extreme flows increases with the observed discharge. The parameter uncertainty in both the extreme high flows and the extreme low flows is the largest for the HBV model and the smallest for the Xinanjiang model. It is noted that the extreme low flows are mostly underestimated by all models with optimum parameter sets for both subbasins. The largest underestimation is from Xinanjiang model. Therefore it is not reliable enough to use only one set of the parameters to make the prediction and carrying out the uncertainty study in the extreme discharge simulation could give an overall picture for the planners.     

Obtaining Accurate Isotopic Compositions with the Double Spike Technique: Practical Considerations

Ever‐increasing precision in isotope ratio measurements requires a concomitant small bias within and between laboratories. The double spike technique is the most suitable method to obtain reliable isotope composition data that are accurately corrected for instrumental mass fractionation. Compared with other methods, such as sample‐calibrator bracketing (SCB), only the double spike technique can correct for all sources of fractionation after equilibration of the sample with the double spike, such as that incurred during chemical separation and measurement. In addition, it is not dependent on a priori assumptions of perfect matrix matching of samples to reference materials or quantitative recovery of the sample through the chemical separation procedure to yield accurate results. In this review article, we present a detailed discussion of the merits of the double spike technique, how to design and calibrate a suitable double spike and analytical strategies. Our objective is to offer a step‐by‐step introduction to the use of the double spike technique in order to lower potential barriers that researchers new to the subject might face, such that double spiking will replace SCB as the measurement method of choice.     

Effects of differential hillslope‐scale water retention characteristics on rainfall–runoff response at the Landscape Evolution Observatory

Hillslopes turn precipitation into runoff and thus exert important controls on various Earth system processes. It remains difficult to collect reliable data necessary for understanding and modeling these Earth system processes in real catchments. To overcome this problem, controlled experiments are being conducted at the Landscape Evolution Observatory at Biosphere 2, The University of Arizona. Previous experiments have revealed differences in hydrological response between 2 landscapes within Landscape Evolution Observatory, even though both landscapes were designed to be identical. In an attempt to discover where the observed differences stem from, we use a fully 3‐dimensional hydrological model (CATchment HYdrology) to show the effect of soil water retention characteristics and saturated hydraulic conductivity on the hydrological response of these 2 hillslopes. We also show that soil water retention characteristics can be derived at hillslope scale from experimental observations of soil moisture and matric potential. It is found that differences in soil packing between the 2 landscapes may be responsible for the observed differences in hydrological response. This modeling study also suggests that soil water retention characteristics and saturated hydraulic conductivity have a profound effect on rainfall–runoff processes at hillslope scale and that parametrization of a single hillslope may be a promising step in modeling rainfall–runoff response in real catchments.     

Seasonality of low flows and dominant processes in the Rhine River

Low flow forecasting is crucial for sustainable cooling water supply and planning of river navigation in the Rhine River. The first step in reliable low flow forecasting is to understand the characteristics of low flow. In this study, several methods are applied to understand the low flow characteristics of Rhine River basin. In 108 catchments of the Rhine River, winter and summer low flow regions are determined with the seasonality ratio (SR) index. To understand whether different numbers of processes are acting in generating different low flow regimes in seven major sub-basins (namely, East Alpine, West Alpine, Middle Rhine, Neckar, Main, Mosel and Lower Rhine) aggregated from the 108 catchments, the dominant variable concept is adopted from chaos theory. The number of dominant processes within the seven major sub-basins is determined with the correlation dimension analysis. Results of the correlation dimension analysis show that the minimum and maximum required number of variables to represent the low flow dynamics of the seven major sub-basins, except the Middle Rhine and Mosel, is 4 and 9, respectively. For the Mosel and Middle Rhine, the required minimum number of variables is 2 and 6, and the maximum number of variables is 5 and 13, respectively. These results show that the low flow processes of the major sub-basins of the Rhine could be considered as non-stochastic or chaotic processes. To confirm this conclusion, the rescaled range analysis is applied to verify persistency (i.e. non-randomness) in the processes. The estimated rescaled range statistics (i.e. Hurst exponents) are all above 0.5, indicating that persistent long-term memory characteristics exist in the runoff processes. Finally, the mean values of SR indices are compared with the nonlinear analyses results to find significant relationships. The results show that the minimum and maximum numbers of required variables (i.e. processes) to model the dynamic characteristics for five out of the seven major sub-basins are the same, but the observed low flow regimes are different (winter low flow regime and summer low flow regime). These results support the conclusion that a few interrelated nonlinear variables could yield completely different behaviour (i.e. dominant low flow regime).     

SPLITAREA: an algorithm for weighted splitting of faces in the context of a planar partition

Geographic data themes modelled as planar partitions are found in many GIS applications (e.g. topographic data, land cover, zoning plans, etc.). When generalizing this kind of 2D map, this specific nature has to be respected and generalization operations should be carefully designed. This paper presents a design and implementation of an algorithm to perform a split operation of faces (polygonal areas).

The result of the split operation has to fit in with the topological data structure supporting variable-scale data. The algorithm, termed SPLITAREA, obtains the skeleton of a face using a constrained Delaunay triangulation. The new split operator is especially relevant in urban areas with many infrastructural objects such as roads. The contribution of this work is twofold: (1) the quality of the split operation is formally assessed by comparing the results on actual test data sets with a goal/metric we defined beforehand for the ‘balanced’ split and (2) the algorithm allows a weighted split, where different neighbours have different weights due to different compatibility. With the weighted split, the special case of unmovable boundaries is also explicitly addressed.

The developed split algorithm can also be used outside the generalization context in other settings. For example, to make two cross-border data sets fit, the algorithm could be applied to allow splitting of slivers.