Suspended sediment load transport in the Mississippi River basin at St. Louis: temporal scaling and nonlinear determinism

This study investigates the dynamic behavior of suspended sediment load transport at different temporal scales in the Mississippi River basin. Data corresponding to five successively doubled temporal scales (i.e. daily, two‐day, four‐day, eight‐day and 16‐day) from the St. Louis gaging station in Missouri are analyzed. The investigation is focused on identifying possible low‐dimensional deterministic behavior in the suspended sediment load transport dynamics, with an aim towards reduction in model complexity. The correlation dimension method is used to identify low‐dimensional determinism. The suspended sediment load dynamics are represented through phase‐space reconstruction, and the variability is estimated using the (proximity of) reconstructed vectors in the phase space. The results indicate the presence of low‐dimensional determinism in the suspended sediment load series at each of the five temporal scales, with the variables dominantly governing the dynamics in the order of three or four. These results not only suggest the appropriateness of relatively simpler models but also hint at possible scale invariance in the suspended sediment load transport dynamics. Copyright © 2006 John Wiley & Sons, Ltd.     

Nonlinear determinism in river flow: prediction as a possible indicator

Whether or not river flow exhibits nonlinear determinism remains an unresolved question. While studies on the use of nonlinear deterministic methods for modeling and prediction of river flow series are on the rise and the outcomes are encouraging, suspicions and criticisms of such studies continue to exist as well. An important reason for this situation is that the correlation dimension method, used as a nonlinear determinism identification tool in most of those studies, may possess certain limitations when applied to real river flow series, which are always finite and often short and also contaminated with noise (e.g. measurement error). In view of this, the present study addresses the issue of nonlinear determinism in river flow series using prediction as a possible indicator. This is done by (1) reviewing studies that have employed nonlinear deterministic methods (coupling phase‐space reconstruction and local approximation techniques) for river flow predictions and (2) identifying nonlinear determinism (or linear stochasticity) based on the level of prediction accuracy in general, and on the prediction accuracy against the phase‐space reconstruction parameters in particular (termed as the ‘inverse approach’). The results not only provide possible indications to the presence of nonlinear determinism in the river flow series studied, but also support, both qualitatively and quantitatively, the low correlation dimensions reported for such. Therefore, nonlinear deterministic methods are a viable complement to linear stochastic ones for studying river flow dynamics, if sufficient caution is exercised in their applications and in interpreting the outcomes. Copyright © 2006 John Wiley & Sons, Ltd.     

A physical interpretation of the deterministic fractal–multifractal method as a realization of a generalized multiplicative cascade

In this study, we attempt to offer a solid physical basis for the deterministic fractal–multifractal (FM) approach in geophysics (Puente, Phys Let A 161:441–447, 1992; J Hydrol 187:65–80, 1996). We show how the geometric construction of derived measures, as Platonic projections of fractal interpolating functions transforming multinomial multifractal measures, naturally defines a non-trivial cascade process that may be interpreted as a particular realization of a random multiplicative cascade. In such a light, we argue that the FM approach is as “physical” as any other phenomenological approach based on Richardson’s eddies splitting, which indeed lead to well-accepted models of the intermittencies of nature, as it happens, for instance, when rainfall is interpreted as a quasi-passive tracer in a turbulent flow. Although neither a fractal interpolating function nor the specific multipliers of a random multiplicative cascade can be measured physically, we show how a fractal transformation “cuts through” plausible scenarios to produce a suitable realization that reflects specific arrangements of energies (masses) as seen in nature. This explains why the FM approach properly captures the spectrum of singularities and other statistical features of given data sets. As the FM approach faithfully encodes data sets with compression ratios typically exceeding 100:1, such a property further enhances its “physical simplicity.” We also provide a connection between the FM approach and advection–diffusion processes.     

A penalty finite difference model for Navier-Stokes flow problem in sedimentation basins

An explicit finite difference solution procedure for the 2D, unsteady, turbulent and incompressible Navier-Stokes flow problem is developed. The innovative feature of the numerical model is the use of a penalty function technique. To illustrate the effectiveness of the model, two numerically predicted flow patterns for laboratory size sedimentation tanks are compared to actual experimental results. The predicted flow pattern shows a satisfactory match with experimental data.     

Time-lag effects of vegetation responses to soil moisture evolution: a case study in the Xijiang basin in South China

The time-lag effects of droughts on vegetation responses vary significantly across a large-scale river basin. The spatio-temporal response characteristics obtained are important for decision making processes on the allocation and transportation of regional water resources in mitigating drought impacts. Here we consider the Xijiang (West River) basin in South China as a case study, which has experienced severe drought events since the beginning of the 21st century. A threshold level approach is employed to identify the major drought events over the basin in the first decade of this century. The vegetation responses to land soil water evolution are examined, particularly for the severe drought events occurred. The time-lag effects of the vegetation responses within the basin range within 0–96 days. The lower reaches of the headwater sub-basins in the west part of the Xijiang basin are identified as the regions with short time-lag effects. The enhanced vegetation index (EVI) shows consistent responses to the soil water evolution in conjunction with the climate aridity in this area, which is the drought-vulnerable area in the Xijiang basin.     

Prediction of vegetation anomalies over an inland river basin in north‐western China

Vegetation cover plays an important role in linking the atmosphere, water, and land and is deemed as a key indicator in the terrestrial ecological system. Therefore, it is of great importance to monitor vegetation dynamics and understand the mechanisms of vegetation change, including that driven by climate change. This study examines (a) the evolution of vegetation dynamics over the Heihe River Basin in the typical arid zone in north‐western China using nonparametric Mann–Kendall test and Thiel Sen's slope; (b) the relationships between remotely sensed vegetation indices (normalized difference vegetation index [NDVI] and enhanced vegetation index [EVI]) and hydroclimatic variables based on correlation analysis; and (c) the prediction of vegetation anomalies using a multiple linear regression model. For the analysis, the Moderate Resolution Imaging Spectroradiometer NDVI/EVI product and the gridded daily meteorological data at a spatial resolution of 0.125° over the period 2001–2010 are considered. The results indicate that vegetation cover improved over a large proportion during 2001–2010, with a significant trend towards warm and wet, characterized by an increase in average annual temperature and precipitation by 0.042 °C/year and 5.8 mm/year, respectively. We test the feasibility of NDVI and EVI in quantifying the responses of vegetation anomaly to climate change and develop a statistical model to predict vegetation dynamics in the basin. The NDVI‐based model is found to be more reliable than the EVI‐based model, partly due to the vegetation characteristics and geomorphologic properties of the study region. The proposed model performs well when there is no lag time between meteorological factors and vegetation indices for grassland and cropland, whereas 1‐month lead time prediction is found to be best for forest. The soil water content is introduced as an extra explanatory variable, which effectively improves the prediction accuracy for different land use types. In general, the predictive ability of the proposed model is stable and satisfactory, and the model can provide useful early warning information for regional water resources management under changing climate.     

Landfill site selection based on reliability concepts using the DRASTIC method and AHP integrated with GIS – a case study of Bengaluru city,India

The selection of landfill sites for municipal solid waste (MSW) disposal involves consideration of geological, hydrological and environmental parameters which exhibit large spatial variability. Therefore, it is necessary to define, to what extent the chosen sites are reliable such that the probability of environmental pollution and health risks to population is minimal. In the present study, groundwater vulnerability to contamination has been assessed using the standard DRASTIC method. The results showed that the study region has 9.45% of very less, 32.94% of less, 25.47% of moderate, 22.79% of high and 9.35% of very high vulnerable zones. The study also revealed that none of the landfills are located in safe zones. This suggests that it requires proper remedial measures to avoid environmental pollution. A landfill site selection process has been carried out using the Analytical Hierarchy Process integrated with Geographical Information System tools. The obtained results showed that only 3.59?km² (0.08%) of the total area is suitable for landfills. The reliability analysis of the site suitability revealed that landfills are located at unreliable locations where the probability of risk to environmental pollution is high. The presented approach assists decision-makers in selecting reliable locations for the safe disposal of MSW.