Soonil D.D.V. Rughooputh

EROSION MODELLING AND SOIL LOSS PREDICTION UNDER CHANGING LAND USE FOR A CATCHMENT ON MAURITIUS

ABSTRACT Sugarcane is the dominant form of agriculture on the island of Mauritius but the industry is facing increasing financial constraints that will probably lead to greater diversity in agriculture. Although sugarcane is considered a soil conservation crop, little is known of the current erosion rates on the island and the effect of changing crop types on sediment yields. Modelling of the potential soil loss in the Rivierre Des Anguilles, a southern catchment on Mauritius, was undertaken to obtain an understanding of the extent to which soil erosion is affected by different land use. Two erosion models are applied within a GIS framework: the Revised Universal Soil Loss Equation (RUSLE) and the Soil Loss Estimation Model of Southern Africa (SLEMSA). RUSLE is further used to predict soil loss for the catchment under three potential crop diversification scenarios. Although soil loss ranges considerably, model outputs show a similar trend in mean soil loss rates between the cropping systems in the catchment. Rates are generally highest on steep slopes (>20%) with high annual rainfall (2 400mm) along the river and in the upper catchment area. Predicted soil loss results indicate a strong inverse relationship with vegetation cover; infrequently disturbed land use types such as natural vegetation, tea and banana plantations have low soil loss values (1 to 4 t.ha−1.yr−1), whereas frequently disturbed land use types such as intercropped cane and vegetables have moderate (13 t.ha−1.yr−1) to very high (80 t.ha−1.yr−1) soil loss rates. Results show that land use change to pineapple and vegetables will have a considerable influence on soil erosion with mean soil loss for the catchment doubling and quadrupling respectively. Such crops should be confined to low slope angles and be supported by soil management practices.

Photophysical aspects and conformational issues of conjugated polymers

Chromism, attributed to the family of conjugated polymers, is no doubt due to conformational changes of the conjugated backbone. The mechanism responsible for this transition remains, however, poorly understood despite being the subject of numerous papers. In this paper, photophysical investigations are made in an effort to elucidate the driving force(s) behind this mechanism. It is argued that this mechanism is a single-chain effect, whilst it involves an intrachain collapse to adopt a quasi-microcrystalline nature existing in solution.

Temporal sensitivity analysis of erosivity estimations in a high rainfall tropical island environment

Abstract The Erosivity ndex (EI) and the odified ournier ndex (MFI) are two commonly used methods in calculating the R factor of the universal soil loss equation/revised universal soil loss equation formula. Using auritius as a case study, the value of high‐resolution data versus long‐term totals in erosivity calculations is investigated. A limited number of four auritius eteorological ervices stations located on the west coast and the entral lateau provided the study with detailed rainfall data for 6 years at 6‐min intervals. Rainfall erosivity for erosive events was calculated using different set interval data. In this study, within the , the use of 6‐min rainfall intervals during erosive rainfall gave estimates of around 10% more erosivity than the 30‐min time intervals and 33% more rainfall erosivity than the 60‐min rainfall measurements. When the was used to determine erosivity through annual and monthly rainfall totals, substantially higher erosivity than the method was calculated in both regions. This stems from the large amount of non‐erosive rainfall that is generated on auritius. Even when the was used to calculate erosivity through monthly and annual rainfall totals derived purely from erosive rainfall, erosivity calculations were not comparable to those from high‐resolution data within the . We suggest that for the computation of erosivity, rainfall data with the highest possible resolution should be utilised if available and that the application of annual and monthly rainfall totals to assess absolute soil erosion risk within a high rainfall tropical environment must be used with caution.

Application of a RUSLE-based soil erosion modelling on Mauritius Island

Soil erosion by water is one of the most important natural resources management problems in the world. The damages it causes on-site are soil loss, breakdown of soil structure, and decline in organic matter content, nutrient content, fertility, and infiltration rate. Lands with the highest erosion risk on Mauritius Island are crop cultivations (sugarcane, tea, vegetables) on erosion-susceptible terrain (slopes >20% coupled with highly erodible soils). The locations of such lands on Mauritius were mapped during previous, qualitatively based regional-scale erosion studies. In order to propose soil conservation strategies, there is a need to apply a more quantitative approach to supplement the previous, qualitatively based studies. This paper reports an application of the Revised Universal Soil Loss Equation (RUSLE) within a geographical information system in order to estimate soil loss on the island, and particularly for the high-erosion areas. Results show that total soil loss on the island is estimated at 298 259 t year–1, with soil loss from high-erosion areas summing 84 780 t year–1 (28% of total soil loss). If all of the high-erosion areas were afforested, their soil loss would be reduced to 10 264 t year–1, i.e. a reduction of 88% for the high-erosion areas and a reduction of 25% for the island. This study thus calls for soil and water conservation programs directed to these erosion-prone areas before the land degradation and environmental damage they are causing become irreversible. The methodological approach used in this work to quantitatively estimate soil loss from erosion-prone areas can be adopted in other countries as the basis for a nationwide erosion assessment in order to better inform environmental policy needs for soil and water conservation.

THE NATURE OF EROSIVE RAINFALL ON A TROPICAL VOLCANIC ISLAND WITH AN ELEVATED INTERIOR

Mauritius is a typical tropical volcanic island with a distinct elevated central plateau above 550 m.a.s.l. Rainfall depth, duration, intensity, kinetic energy, and erosivity were analysed for 385 erosive rainfall events at five locations over a five-year period (2004 to 2008). Two Mauritius Meteorological Services stations located on the west coast and three sited on the Central Plateau provide detailed rainfall data at 6-minute intervals. Erosive storm events are found to differ markedly between the coastal lowlands and the elevated interior with regard to the frequency, the total rainfall generated, the duration, total kinetic energy, and total erosivity of individual events. However, mean kinetic energy, mean and maximum rainfall erosivity (EI30), and maximum intensities (I30) from individual erosive events do not show this distinct differentiation. The distribution of kinetic energy and erosivity generated by individual events at the two altitudes are also significantly different. Although erosivity measured during summer exceeds that recorded in winter, the data indicate that large percentages of winter rainfall events on Mauritius are erosive and rainfall from non-tropical cyclones can pose a substantial erosion risk. Soil erosion risk occurs from storm-scale to synoptic-scale events, and extreme rainfall events generate the bulk of the erosivity. This paper also highlights that the use of rainfall records at an event scale in soil erosion risk assessments on tropical islands with a complex topography increases the effectiveness of erosivity estimates.

Neural network process vision systems for flotation process

Froth flotation is a process whereby valuable minerals are separated from waste by exploiting natural differences or by chemically inducing differences in hydrophobicity. Flotation processes are difficult to model because of the stochastic nature of the froth structures and the ill‐defined chemorheology of these systems. In this paper a hierarchical configuration hybrid neural network has been used to interpret froth images in a copper flotation process. This hierarchical neural network uses two Pulse‐Coupled Neural Networks (PCNNs) as preprocessors that ‘convert’ the froth images into corresponding binary barcodes. Our technique demonstrates the effectiveness of the hybrid neural network for process vision, and hence, its potential for use for real time automated interpretation of froth images and for flotation process control in the mining industry. The system is simple, inexpensive and is very reliable.

Intra-event characteristics of extreme erosive rainfall on Mauritius

Abstract Mauritius is a volcanic island with a raised interior where extreme rainfall events dominate rainfall erosivity. Intra-event characteristics of the 120 highest erosive events at six selected locations between 2004 and 2008 were analyzed to provide the first detailed intra-storm data for a tropical island environment. On Mauritius, spatial variation is evident in the characteristics of extreme erosive rainfall recorded at the stations, with a noticeable increase in rainfall depth, duration, kinetic energy, and erosivity of extreme events with altitude. Extreme events in the raised interior (central plateau) show high variability of peak intensity over time as well as a higher percentage of events in which the greatest intensity occurs in the latter part of the event. Intra-event distribution of rainfall in the interior of the island shows that rainfall there has a higher potential to exceed infiltration rates as well as the ability to generate high peak runoff rates and cause substantial soil loss. The study suggests that even though within-event rainfall characteristics are complex, they have implications for soil erosion risk, and that, in tropical island environments, the within-storm distribution of rainfall should be incorporated in soil-loss modeling.

Identification and classification of galaxies using a biologically-inspired neutral network

Recognition/Classification of galaxies is an important issue in the large-scale study of the Universe; it is not a simple task. According to estimates computed from the Hubble Deep Field (HDF), astronomers predict that the universe may potentially contain over 100 billion galaxies. Several techniques have been reported for the classification of galaxies. Parallel developments in the field of neural networks have come to a stage that they can participate well in the recognition of objects. Recently, the Pulse-Coupled Neural Network (PCNN) has been shown to be useful for image pre-processing. In this paper, we present a novel way to identify optical galaxies by presenting the images of the galaxies to a hierarchical neural network involving two PCNNs. The image is presented to the network to generate binary barcodes (one per iteration) of the galaxies; the barcodes are unique to the input galactic image. In the current study, we exploit this property to identify optical galaxies by comparing the signatures (binary barcode) from a corresponding database.

Land cover of Mauritius Island

In this digital era, high-resolution imagery offers a rapid and inexpensive means of monitoring land use changes. Digitally monitoring dynamic landscape change is a versatile way of facilitating rapid strategic decision making in a sustainable manner in a world of increasing complexity. Whilst a cadastral land information system is useful as a database, its use is limited for research purposes involving the manipulation of images – such as in studying flood-prone areas or land erosion susceptibility. In this paper, we report a land cover map for Mauritius Island (1859 km2), in the Indian Ocean, at a scale of 1:100,000 (A1-size paper). Inputs used to create the map are a SPOT satellite image, published map series at 1:25,000 scale, and selected ground truth surveys for validation. In total, 11 feature types, which are representative of the islands surface cover, have been mapped.

Evaluation of Congestion Relief Proposals in a Capital City

This paper aims at analyzing three different solutions suggested for traffic congestion relief in Port Louis, the busiest city of Mauritius. It evaluates the impact of the three alternatives which are the use of Light Rail Transit (LRT) as an alternative mode of transport, the construction of a Ring road around Port Louis, and the upgrading of the current bus network into a Bus Rapid Transit (BRT) system. The impact of these three solutions has been evaluated by performing Traffic Cellular Automata (TCA) simulations. Our studies reveal that the Ring road will lead to more congestion while introducing the LRT or upgrading the current bus network will reduce congestion significantly.