Use of general circulation model output in the creation of climate change scenarios for impact analysis

Many scientific studies warn of a rapid global climate change during the next century. These changes are understood with much less certainty on a regional scale than on a global scale, but effects on ecosystems and society will occur at local and regional scales. Consequently, in order to study the true impacts of climate change, regional scenarios of future climate are needed. One of the most important sources of information for creating scenarios is the output from general circulation models (GCMs) of the climate system. However, current state-of-the-art GCMs are unable to simulate accurately even the current seasonal cycle of climate on a regional basis. Thus the simple technique of adding the difference between 2 × CO₂ and 1 × CO₂ GCM simulations to current climatic time series cannot produce scenarios with appropriate spatial and temporal details without corrections for model deficiencies. In this study a technique is developed to allow the information from GCM simulations to be used, while accommodating for the deficiencies. GCM output is combined with knowledge of the regional climate to produce scenarios of the equilibrium climate response to a doubling of the atmospheric CO₂ concentration for three case study regions, China, Sub-Saharan Africa and Venezuela, for use in biological effects models. By combining the general climate change calculated with several GCMs with the observed patterns of interannual climate variability, reasonable scenarios of temperature and precipitation variations can be created. Generalizations of this procedure to other regions of the world are discussed.     

Spatial variability of rainfall at an experimental station in Niger,West Africa

Summary Variability of rainfall in the semi-arid regions can cause problems in evaluating experimental trials. To describe the spatial rainfall patterns over a large experimental station, rainfall was monitored during the 1986 and 1987 rainy seasons using 18 raingages over the 500 ha experimental station of ICRISAT Sahelian Center, in Niger, West Africa. Average relative variability of individual rain storms, defined as the percentage deviation from the mean, varied from 2 to 62%, while the variability over the rainy season was 17.1%. Isohyetal patterns of individual rain storms as well as seasonal totals showed distinct coherence in the spatial pattern over the station. The effects of total volume, duration, direction and intensity of storms and the time of year on the spatial correlations were analyzed. Storm value showed a large influence on the correlation decay with distance. Correlations in the W — E and SW — NE directions were higher in comparison to those in the N — S and NW — SE directions. Point rainfall measurements were better correlated with the network average rainfall than with the rainfall recorded at the meteorological station. Variograms among raingages revealed that the distance of independence was approximately 1 000 m for almost all storms. Use of a network of raingages over agricultural experiment stations reduces the average relative variability of areal rainfall estimates and provides a means to develop simple relations for estimation of point rainfall for individual applications.With 8 Figures     

Magnetic anomalies over thin plates and their analysis

The magnetic anomaly over a two-dimensional thin horizontal plate is similar to the first horizontal derivative of the magnetic anomaly over a thick dipping dike of infinite depth extent but with a different direction of magnetization. Hence, the magnetic anomalies of thin plates may be integrated along the profile and the pseudomagnetic potential anomaly thus obtained may be interpreted using any standard method of interpreting dike anomalies. Expressions for the Fourier amplitude and phase spectra of the magnetic anomaly over a thin plate are also derived and procedures to evaluate the parameters of the plate from the spectra are formulated.     

Describing near surface, transient flow processes in unconfined aquifers below irrigated lands: A deforming finite element model for heterogeneous aquifers

Hydrologic models of irrigated lands generally adopt either a basin-scale or a root-zone perspective. While basin-wide macro-scale models rely on the aggregation of important spatial and temporal data across large areas, micro-scale root-zone models depend on the definition of rigid boundaries around the zone of plant–soil–water interaction. In reality, irrigation management decisions are made on a field by field basis and can interact across field boundaries. This paper first describes a shallow water table model, based on deforming finite element (DFE) framework, to characterize the near-surface field-to-field hydrologic response to various irrigation and drainage management regimes along a gently sloping alluvial fan. The model is then enhanced through changing geometry of a fluctuating water table below a series of irrigated fields. Such an enhancement also offers computational flexibility relative to the saturated–unsaturated models commonly used in micro-scale studies. The model is designed with the alluvial fan aquifers of California’s western San Joaquin Valley as reference systems.     

Reliability-based robust design for reinforcement of jointed rock slope

Traditional reliability-based design methodologies often involve selection of design which is of lowest cost and satisfies safety requirements. But, this design is sensitive to variation in statistics of input parameters (noise parameters) and might become unsatisfactory if an underestimation of coefficient of variation of input parameters is made. A relatively new design methodology known as robust geotechnical design (RGD) is applied for the case of reinforcement of rock slope using end-anchored rock bolts. This ensures selection of a cost-effective and safe design for which probability of failure (P_f) of reinforced rock slope is least sensitive to the noise parameters. Reliability-based RGD approach involves evaluation of P_f for each design with different possible noise parameters. Finding P_f for the complex geotechnical structure is computationally expensive, and thus an augmented radial basis function-based response surface is used as a surrogate to the finite element model of rock slope. This response surface, being very efficient, also performs well for a range of values of noise parameters. Later, minimum distance algorithm is applied to obtain a cost-effective and robust design. Finally, a comparison is made in the costs between two robust designs obtained for different target probability of failure for the same rock slope.     

Evaluation of physical and morphometric parameters for water resource management in Gad Watershed,Western Ghats,India: an integrated geoinformatics approach

The selected study area is a coastal watershed which receives high rainfall in the monsoon season. During this period, most of the water input to the watershed drains to the Arabian Sea without any adequate use due to the rugged topography of the watershed. Hence, an attempt has been made to assess the physical properties specifically morphometric parameters of the Gad watershed using geoinformatics techniques along with field evidence for understanding the relationship between fluvial landforms and hydro-physical parameters in the region. Morphometric parameters have been analyzed and integrated with physical parameters like topography, rainfall, soil, land use–land cover, geology, and geomorphology for evaluating the potential water resource availability in the Gad watershed. The results of the study have shown that there is high surface water availability in the watershed with very low water retaining capacity, mainly in the upper region of the watershed due to presence of basaltic bedrock and steep slopes. Based on this work, a water resource management plan has been suggested at a subwatershed level which established on the physical properties and morphological characteristics of the study area.     

Automatic Registration of INSAT-3D Daily Images Using Mutual Information and Stochastic Optimization Technique

An automatic image registration approach is presented here can be used to register daily images of Indian geostationary satellite system INSAT-3D acquired every 30 min’ interval without use of any ground control points (GCPs). There is always a pressing need to register meteorological images that are acquired over earth from geostationary platforms every 15–30 min, covering almost one-third of the earth. Weather forecast activities include derivation of atmospheric motion vectors, which demand immediate processing of such images to a reasonable accuracy in terms of its relative location accuracy. Generally followed approaches make use of image navigation models and GCPs drawn from known landmarks in land ocean boundaries and correlate image features before estimating a transform to warp the current acquisition to a known geometry. However, the hierarchical (coarse to fine) approach explained here makes use of intensity based Mutual Information as a similarity measure from a population of pixels selected randomly and uses stochastic gradient descent optimizer to estimate an affine transform between registering image pair, delivers satisfactory results.     

Nonlinear extensions of a fractal–multifractal approach for environmental modeling

We present the extension of a deterministic fractal geometric procedure aimed at representing the complexity of patterns encountered in environmental applications. The procedure, which is based on transformations of multifractal distributions via fractal functions, is extended through the introduction of nonlinear perturbations in the generating iterated linear maps. We demonstrate, by means of various simulations based on changes in parameters, that the nonlinear perturbations generate yet a richer collection of interesting patterns, as reflected by their overall shapes and their statistical and multifractal properties. It is shown that the nonlinear extensions yield structures that closely resemble complex hydrologic spatio-temporal datasets, such as rainfall and runoff time series, and width-functions of river networks. The implications of this nonlinear approach for environmental modeling and prediction are discussed.     

Fabrication of Nanoparticle-Doped Polyvinyl Alcohol-Cellulose Acetate Membrane and Characterization of the Surface Enhancement

In the present study, nanocomposite polymeric membranes are fabricated using polyvinyl alcohol (PVA), cellulose acetate (CA) as polymers, and dimethyl sulfoxide (DMSO) as the solvent. To enhance the performance of the membrane, nanoparticles like TiO₂, CaO, CdO, and ZrO are added to the polymeric solution and the doped polymeric solution is cast on a glass plate. Nine combinations of membranes are fabricated with two different concentrations (0.1% and 0.2%) of nanoparticles. The basic properties of the membranes such as density, porosity, viscosity, permeability, pure water flux, and water content are studied for the samples. Membrane pore structure and surface properties are identified and it is found that doping nanoparticles on the surface of membranes improve mechanical strength, stability, pore size, etc., allowing the membranes to perform better in extreme industrial-level effluent treatment applications. High-resolution scanning electron microscopy (SEM) shows the homogeneous dispersion of ZrO, TiO₂, CaO, and CdO nanoparticles on the surface of the PVA-CA membrane. The doping of nanoparticles on the PVA-CA membrane results in improved mechanical strength and good chemical oxidation stability. In comparison, the PCD-TiO₂ sample shows high thermal stability and oxidation stability at high temperatures until 200°C, which has a high potential for treating industrial effluents.