Analytic network process (ANP)-based spatial decision support system (SDSS) for sustainable tourism planning in Cameron Highlands,Malaysia

Sustainable approach to tourism development is rarely addressed among authorities and participants. This research presents an approach based on an integrated use of analytic network process (ANP) and geographic information system (GIS) for sustainable tourism planning in Cameron Highlands, Malaysia. ANP was utilized to evaluate the relative priorities for the sustainable tourism development of the highlands based on chosen criteria. ANP results were then transferred into GIS environment and attached to their respective criterion maps. Subsequently, GIS-based sustainable tourism map was generated, which defines the various types of tourism activities that are compatible with the highlands according to the sensitivity of the highland’s environment. The final output was validated using Cameron Highlands Local Plan.     

A comparison of nearby incremental ground level and in plant concentrations of air pollutants emitted from electronics facilities

Air dispersion modeling by was recently conducted to predict the incremental ground level and inplant concentrations of toxic organic chemicals due to stack and fugitive emissions from Sama Jaya Free Industrial Zone (SJFIZ), Kuching, Sarawak, Malaysia. Simulations of organic air pollutants emitted from industrial facilities in SJFIZ from years 1996 to 2001 were carried out in September 2004 by members of Faculty of Engineering, Universiti Malaysia Sarawak (UNIMAS). The results indicated that there were negligible amount of maximum incremental ground level concentrations of less than 3×10^?2 μg/m³ for 365-day average, and less than 18×10^?2 μg/m³ for 24 h. average. For in-plant maximum incremental concentrations, it is found that the simulated results were much lower than TWA values, except xylene. The predicted in plant concentration of xylene was 119.21 (parts per million) ppm as compared to ACGIH TLV-TWA of 100 ppm approximately 19% higher than ACGIH recommended values. From this study, it was concluded that both nearby population and in plant workers were not potentially at risk to exposing organic chemicals far lower than the threshold limit levels set by ACGIH.     

Analytical solution of polymer slug injection with viscous fingering

We present an analytical solution to estimate the minimum polymer slug size needed to ensure that viscous fingering of chase water does not cause its breakdown during secondary oil recovery. Polymer flooding is typically used to improve oil recovery from more viscous oil reservoirs. The polymer is injected as a slug followed by chase water to reduce costs; however, the water is less viscous than the oil. This can result in miscible viscous fingering of the water into the polymer, breaking down the slug and reducing recovery. The solution assumes that the average effect of fingering can be represented by the empirical Todd and Longstaff model. The analytical calculation of minimum slug size is compared against numerical solutions using the Todd and Longstaff model as well as high resolution first contact miscible simulation of the fingering. The ability to rapidly determine the minimum polymer slug size is potentially very useful during enhanced oil recovery (EOR) screening studies.     

Distribution of tritium and stable isotopes in precipitation in Syria

Abstract

The paper discusses aspects of the isotopic composition (tritium and stable isotopes) of precipitation, which was monitored from 2000 to 2003 at 12 stations in Syria. The seasonal variations in δ¹⁸O are smaller at the western stations than at the eastern ones due to low seasonal temperature variations. A good correlation between δ²H and δ¹⁸O was obtained for each station, and the slopes of the local meteoric water lines are significantly lower than the Global Meteoric Water Line. Values of d-excess decrease from 19‰ at the western stations to 13‰ at the eastern ones, indicating the influence of precipitation generated by air masses coming from the Mediterranean Sea. A reliable altitude effect represented by depletion of heavy stable isotopes (δ¹⁸O and δ²H), of about??0.21‰ and??1.47‰ per 100 m elevation, respectively, was observed. Monthly tritium contents in precipitation, and seasonal variations, are less at the western stations than at the eastern ones. The weighted mean tritium values are between 3 and 9 TU, and increase with distance from the Syrian coast by 1 TU/100 km.

Citation Al Charideh, A. R. & Abou Zakhem, B. (2010) Distribution of tritium and stable isotopes in precipitation in Syria. Hydrol. Sci. J. 55(5), 832–843.     

Identification of homogenous regions in Gorganrood basin (Iran) for the purpose of regionalization

Estimation of flood in basins with poor condition of hydrometric stations as in quantity and quality is a dominant problem around the world, mainly in developing country where lack of funds and human resources cause more limitation in number of gauging stations. One of the areas that experience frequent floods and also suffer from small number of stations in Iran is Gorganrood basin. So there is a great need for the estimation and prediction of runoff in this area to prevent any future floods. Due to insufficient station in this area, direct prediction of flood is not applicable. Regional flood frequency analysis is a practical and widely used solution for these situations, which involves the identification of homogenous regions. Gorganrood region was hydrologically homogenized according to the extracted parameters that influence the floods. One of these parameters was Normalized Difference Vegetation Index (NDVI) driven from MODIS images. Curvature is another parameter that relates to topographic attributes. From factor analysis, the most appropriate variables were selected. According to these parameters (NDVI, curvature, area, slope…), the regions were classified into homogenous regions. For the purpose of homogenization, hierarchical (wards) clustering, fuzzy clustering and Kohonen method were applied. L-moment technique was used for the investigation of the results. The heterogeneity measure for one of the groups (Group 1) was more than two; therefore some modifications were applied. The region was grouped into two homogenous subregions. All of the clustering methods showed same results. The models showed that class 4 of NDVI is influential on flood in some return periods. The resulted models can be applied in future studies in different aspects of practical hydrology.     

Integrated geoelectrical resistivity,hydrochemical and soil property analysis methods to study shallow groundwater in the agriculture area,Machang, Malaysia

Integrated geoelectrical resistivity, hydrochemical and soil property analysis methods were used to study the groundwater characteristics of sandy soils within a shallow aquifer in the agriculture area, Machang. A pilot test investigation was done prior to the main investigation. The area was divided into two sites. Test-Site 1 is non-fertilized; Test-Site 2 is the former regularly fertilized site. From the surface to depths of 75 cm, a lower average resistivity was obtained in Test-Site 2 (around 0.37 less than in Test-Site 1). The presence of nitrate and chloride contents in pore water reduced the resistivity values despite the low moisture content. The pH values for the whole area range from 4.11 to 6.88, indicating that the groundwater is moderately to slightly acidic. In the southern region, concentration of nitrate is considered to be high (>20 mg/l), while it is nearly zero in the northern region. In the south, the soil properties are similar. However, the geoelectrical model shows lower resistivity values (around 18 Ω m) at the sites with relatively high nitrate concentration in the groundwater (>20 mg/l). Conversely, the sites with low nitrate concentration reveal the resistivity values to be higher (>35 Ω m). Basement and groundwater potential maps are generated from the interpolation of an interpreted resistivity model. The areas that possibly have nitrate-contaminated groundwater have been mapped along with groundwater flow patterns. The northern part of the area has an east to west groundwater flow pattern, making it impossible for contaminated water from the southern region to enter, despite the northern area having a lower elevation.     

Quantifying uncertainties associated with depth duration frequency curves

Uncertainty in depth–duration–frequency (DDF) curves is usually disregarded in the view of difficulties associated in assigning a value to it. In central Iran, precipitation duration is often long and characterized with low intensity leading to a considerable uncertainty in the parameters of the probabilistic distributions describing rainfall depth. In this paper, the daily rainfall depths from 4 stations in the Zayanderood basin, Iran, were analysed, and a generalized extreme value distribution was fitted to the maximum yearly rainfall for durations of 1, 2, 3, 4 and 5 days. DDF curves were described as a function of rainfall duration (D) and return period (T). Uncertainties of the rainfall depth in the DDF curves were estimated with the bootstrap sampling method and were described by a normal probability density function. Standard deviations were modeled as a function of rainfall duration and rainfall depth using 10⁴ bootstrap samples for all the durations and return periods considered for each rainfall station.     

A geospatial model for the optimization grazing management in semi-arid rangeland of Iran

Extensive livestock grazing even in unsuitable land has increasingly grown in most parts of semi-arid rangeland. Therefore, it is of paramount importance to identify suitable land for livestock grazing for optimum utilization while causing minimum impact to the environment. This paper adapted the schematic model based on the concepts presented by the Food and Agriculture Organization of suitability analysis for optimal grazing management in semi-arid rangeland in Iran. Factors affecting extensive grazing were determined and incorporated into the model. Semi-arid rangeland with variable such as climate and other agents were examined for common types of animal grazing and the advantages and limitations were elicited. Many ecosystem components affect land suitability for livestock grazing but due to time and funding restrictions, the most important and feasible elements were investigated. Within the model parameters, three submodels including water accessibility source, forage production, and erosion sensitivity were considered. Suitable areas at four levels of suitability were determined using geographic information systems. This suitability modeling approach was adopted due to its simplicity and the minimal time required for transforming and analyzing datasets. The most important reducing factors in model suitability were found to be: (a) land use and vegetation cover (in relation to soil erosion sensitivity), (b) the amount of the available forage in comparison with the total production, and (c) the existence of less palatability plants among the pasture plant species (forage production suitability). The results of the study would be beneficial to rangeland managers in devising measures more wisely to cope with the limitations and enhance the health and productivity of the rangelands.     

Monitoring rangeland ground cover vegetation using multitemporal MODIS data

The aim of the present research is to monitor changes in herbage production during the grazing season in the Semirom and Brojen regions, Iran, using multitemporal Moderate Resolution Imaging Spectroradiometer (MODIS) data. At first, various preprocessing steps were applied to a topography map. The atmospheric and topographic corrections were applied using subtraction of the dark object method and the Lambert method. Image processing, including false-color composite, principal component analysis, and vegetation indices were employed to produce land use and pasture production maps. Vegetation sampling was carried out over a period of 4 months during June–September 2008, using a stratified random sampling method. Twenty random sampling points were selected, and herbage production was estimated and verified with the double-checking method. Four MODIS data sets were used in this study. The models for image processing and integrating ground data with satellite images were processed, and the resulting images were categorized into seven classes. Finally, the land covers were verified for accuracy. A postclassification analysis was carried out to verify the seven class change detections. The results confirmed that Normalized Difference Vegetation Index (NDVI) and Soil-Adjusted Vegetation Index (SAVI) maps had a close relationship with the field data. The indices produced with shortwave infrared bands had a close relationship with field data where the ground cover and yields were high. The R ² value observed was 0.85. The changes in the pasture vegetation were high during the growing season in more than 90 % of the pastures. During the growing season, most changes in the pastures belonged to class 5 and 2 in the NDVI and SAVI index maps, respectively.