Exploring the Solution Space of Semi-structured Geographical Problems Using Genetic Algorithms

Semi-structured geographical problems are often addressed by groups of decision-makers. Each group member is likely to have a specific set of objectives that they wish to address and a unique perspective on the way in which the problem should be solved. The solution to such problems often requires consensus building and compromise among decision-makers as they attempt to optimize their own criteria. The set of criteria adopted by a particular decision-maker constrains the set of solutions he/she will deem acceptable. Compromise among multiple decision-makers can occur at the intersection of these constrained solution sets. Knowledge about the criteria space, the solution space, and the relation between the two is often incomplete for semi-structured problems. New tools are needed to explore, analyze, and visualize the solution space of a problem with respect to multiple analytical models and criteria. In this research we explore the utility of genetic algorithms as an effective means to: (1) search the solution space of geographical problems; (2) visualize the spatial ramifications of alternative criteria spaces; and (3) identify compromise solutions.     

Flood variability east of Australia’s Great Dividing Range

The variability of flow in river channels influences the spatial and temporal variability of many biophysical processes including the transport of sediment and waterborne pollutants and the recruitment of aquatic animals and plants. In this study, inter- and intra-basin patterns of flood variability are examined for catchments east of Australia’s Great Dividing Range. Three measures of flood variability are explored with uncertainty quantified using bootstrap resampling. The two preferred measures of flood variability (namely a flood quantile ratio and a power law scaling coefficient) produced similar results. Catchments in the wet tropics of far north Queensland experience low flood variability. Flood variability increased southwards through Queensland, reaching a maximum in the vicinity of the Fitzroy and Burnett River basins. The small near-coast catchments of southern Queensland and northern New Wales experience low flood variability. Flood variability is also high in the southern Hunter River and Hawkesbury–Nepean basins. Using L-moment ratio diagrams with data from 424 streamflow stations, we also conclude that the Generalised Pareto distribution is preferable for modelling flood frequency curves for this region. These results provide a regional perspective that can be used to develop new hypotheses about the effects of hydrologic variability on the biophysical characteristics of these Australian rivers.     

Searching for periodicities in the MACHO light curve of LMC X-2

Using the exceptional long-term monitoring capabilities of the MACHO project, we present here the optical history of LMC X-2 for a continuous 6-yr period. These data were used to investigate the previously claimed periodicities for this source of 8.15 h and 12.54 d: we find upper limits of 0.10 mag and 0.09 mag, respectively.     

Optical and infrared photometry of the Type IIn SN 1998S: days 11–146

We present contemporaneous optical and infrared (IR) photometric observations of the Type IIn SN 1998S covering the period between 11 and 146 d after discovery. The IR data constitute the first ever IR light curves of a Type IIn supernova. We use blackbody and spline fits to the photometry to examine the luminosity evolution. During the first 2–3 months, the luminosity is dominated by the release of shock-deposited energy in the ejecta. After ∼100 d the luminosity is powered mostly by the deposition of radioactive decay energy from 0.15±0.05 M_⊙ of ⁵⁶Ni which was produced in the explosion. We also report the discovery of an astonishingly high IR excess, K − L '=2.5, that was present at day 130. We interpret this as being due to thermal emission from dust grains in the vicinity of the supernova. We argue that to produce such a high IR luminosity so soon after the explosion, the dust must be pre-existing and so is located in the circumstellar medium of the progenitor. The dust could be heated either by the UV/optical flash (IR echo) or by the X-rays from the interaction of the ejecta with the circumstellar material.     

Generalized inversion of the Korteweg–de Vries equation

A generalized inverse is presented for the Korteweg–de Vries (KdV) equation, an initial condition and data from synthetic but realistic solitary internal waves. The synthetic data are statistically consistent with hypothesized levels of error in the KdV equation, initial condition and observing system. The observing system consists of point-wise measurements of the pycnocline displacement, either at fixed locations or from a ship drifting in the soliton current. These synthetic inversions are designed using the environmental conditions and disturbances observed by Pinkel [J. Phys. Oceanogr. 30 (2000) 2906]. The inverse solution is found by minimizing a quadratic cost functional, which yields a weighted least-squares best-fit to the KdV equation, the initial condition and the data. The weight for each squared residual is derived from its hypothesized covariance.The minimal value of the least-squares estimator (or cost function) is the test statistic for the error hypotheses and is shown here to be a reliable indicator of grossly incorrect hypotheses. In particular, it will be shown that even with just a single ship survey, the method does lead to decisive tests of hypotheses concerning the level of error in the model. Also, neglect of ship drift is found to be less deleterious to the inversion than is neglect of error in the KdV dynamics.The inverse is calculated by the iterated, direct representer algorithm [Ocean Model. 3 (2001) 137], which is readily extended to include parameter estimation. Significant skill is found for estimating the linear phase speed.     

Uncertainty analysis along the ecological quality status of water bodies: the response of the Posidonia oceanica multivariate index (POMI) in three Mediterranean regions

Uncertainty analyses allow the identification and quantification of the factors that contribute to the potential misclassification of the ecological status of water bodies, helping to improve the sampling design used in monitoring. Here we used a Posidonia oceanica multivariate index (POMI) bio-monitoring dataset covering a total of 81 sites distributed throughout 28 water bodies from the coast of Catalonia, Balearic Islands and Croatia to determine the levels of uncertainty associated with each region and how they change according to the quality status of water bodies. Overall, variability among sites (meadows) within water bodies was the factor that generated the greatest risk of misclassification among the three regions, within which the Balearic Islands had the lowest uncertainty, followed by Croatia and Catalonia. When water bodies classified in good/high quality were separated from those in moderate/poor status classes, we found that the latter displayed higher levels of uncertainty than the former.     

Suspended sediment monitoring in alluvial gullies: A laboratory and field evaluation of available measurement techniques

Gully erosion is a significant source of fine suspended sediment (<63 μm) and associated nutrient pollution to freshwater and marine waterways. Researchers, government agencies, and monitoring groups are currently using monitoring methods designed for streams and rivers (e.g., autosamplers, rising stage samplers, and turbidity loggers) to evaluate suspended sediment in gullies. This is potentially problematic because gullies have several hydrological features and monitoring operational challenges that differ to those of continually flowing streams and rivers (e.g., short and intense flows, high suspended sediment concentrations, and rapid scouring and aggradation). Here we present a laboratory and field-based assessment of the performance of common suspended sediment monitoring techniques applied to gullies. We also evaluate a recently-described method; the pumped active suspended sediment (PASS) sampler, which has been modified for monitoring suspended sediment in gully systems. Discrete autosampling provided data at high temporal resolution, however, it had poor collection efficiency (25 ± 10%) of coarser sediment particles (i.e., sand). Rising stage sampling, while robust and cost-effective, suffered from large amounts of condensation under field conditions (25–35% of sampler volume), due to harsh climatic conditions creating large diurnal temperature differences at the field site, thereby diluting sample concentrations and introducing additional measurement uncertainty. The turbidity logger exhibited a highly variable response when calibrated at each site with physically collected suspended sediment samples (R² = 0.17–0.83), highlighting that this approach should be used with caution. The modified PASS sampler proved to be a reliable and representative measurement method for gully sediment water quality, however, the time-integrated nature of the method limits its temporal resolution compared to the other monitoring methods. We recommend monitoring suspended sediment in alluvial gully systems using a combination of complementary techniques (e.g., PASS and RS samplers) to account for the limitations associated with individual methods.