Saeed Soltani and Reza Modarres

Abstract: The identification of spatial rainfall pattern is an essential task for hydrologists, climatologists as well as regional and local planners and managers. This is due to the variability of both the temporal spatial distribution of rainfall. In this study, a hierarchical and divisive cluster analysis was used to categorize these patterns of rainfall in Iran. According to results obtained, there are eight main spatial groups of annual rainfall over Iran. These groups can be classified into 3 main seasonal rainfall regimes namely, winter, winter-spring and fall regimes. The results also show that the elevation and sea neighborhood affect rainfall pattern of Iran. Moreover, a comparison between the Ward and average methods of hierarchical cluster analysis indicates that the Ward method performs the spatial pattern better.

Key Words: Rainfall pattern, Cluster Analysis, Ward Method, Iran

Abdul Rahim Samsudin, Bahaa-eldin Elwali A.Rahim,Wan Zuhairi Wan Yaacob  & Umar Hamzah

Abstract: Municipal solid waste disposal sites can be sources of groundwater contamination and the contamination problems are more likely to occur in humid areas, where the moisture available exceeds the ability of the waste pile absorb water. In tropical country like Malaysia which is characterized by high rainfall, the subsurface contamination problems are expected to occur. Seriousness of the pollution problem is still unknown and specific detailed study is generally needed. Two dimensional geoelectrical imaging has frequently been used in the subsurface pollution studies. The method maps the distribution of resistivity of subsurface materials. The  resistivity image provides general information on subsurface stratification of buried waste and  contaminated soil, as well the depth to the bedrock below the lines of traverse. Underground soil or water that has been contaminated by leachate usually has a significantly lower resistivity value. This paper discusses the results of the 2-D resistivity imaging which were conducted to identify and delineate the extent of contaminated soil and leachate plumes, as well as to assess the capability of the 2-D resistivity imaging as a pre-characterization tool for tracing the properties of disposed waste and its severity underneath a capped landfill sites. The imaging method was used in this study to map the contaminated subsurface soil and ground water at three municipal solid waste disposal sites namely Ampar Tenang (AT) open-tipping site, Bukit Kemuning (BK) capped landfill, and Taiping landfill (TL) where a total of twenty two 2-D resistivity lines were surveyed. The surveys were conducted using ABEM SAS1000 resistivity meter and LUND Automatic imaging system and the measured resistivity profiles were interpreted using 2-D resistivity inversion programme (RES2DINV). Generally the results of the measured resistivity values obtained from the three sites define the contaminated leachate plumes as electrically conductive anomalies of relatively low resistivity value less than 10 ohm-m.

Key words: 2-D Resistivity imaging, solid waste, disposal sites, and leachate plume.

Ahmed Said

Abstract: Watershed management requires the determination of both point and non-point sources of pollution within a watershed. The primary non-point source pollutants in a typical watershed are nutrients (mainly nitrogen and phosphorus), sediment, and pesticides. In the Snake River Basin, in Idaho, nutrients from non-point sources (primarily agricultural) are delivered to streams via storm water and irrigation runoff. However, the objectives of this study were to estimate the phosphorus loading from different sources in the Snake River Basin due to storm water events, to calculate the total nitrogen/phosphorus (TN/TP) ratios for land uses, and to compare and a precipitation runoff model and statistical regression with the measurements. The study used the Long-Term Hydrologic Impact Assessment (L-THIA) model to perform the analysis and to estimate the loss and gain in phosphorus loading. The gain was due to ground water discharge and point sources from industrial and commercial trout farms. The loss was attributed to phosphorus absorbance, existence of riparian vegetation, ground water discharge, or dilution from spring inflows. The results showed that phosphorus is the limiting nutrient. The L-THIA model gave more accurate results than the simple statistical regression.

Key Words: L-THIA model, water quality, sediment, Snake River Basin, Idaho

Xixi Wang, Assefa M. Melesse, and Wanhong Yang

Abstract: Although soil nitrate nitrogen (N) is a nutrient source for crop, it could be a potential nonpoint pollution source to the environment when its content remains high with an inappropriate management. Soil nitrate N content is affected by various factors, such as cultivation practices, N fertilizer application rate, soil properties, and climatic conditions. Understanding the effects of these factors on soil nitrate N content is necessary for nitrogen management and nonpoint source pollution control. Taking the data measured from 1996 to 1998 in a 25 ha row crop field located in Central Iowa, this paper intended to study the interwoven effects of these factors on soil nitrate N content using multivariate statistical analysis techniques of sample mean plots, a multivariate analysis of variance (MANOVA) model, and a multivariate linear regression model. The inferences made by the sample mean plots and MANOVA model indicate that the effects of these factors are additive, i.e., their main or direct effects are statistically significant but the interaction effects between and among them are insignificant at a 5% significance level. Incorporating these additive effects, a multivariate linear regression model was fitted to the dataset. The residual plots show that the dataset follows an approximate bivariate normal distribution, which is assumed by the MANOVA and multivariate linear regression models. The validation using the field data collected in 1999 indicated that the model explained more than 93% variations exhibited by the measured sublayed-averaged data on soil nitrate N content and soil moisture. However, this model is unable to account for the within-sublayer variations.

Key words: linear regression; multivariate statistics; nitrogen; NPS; soil moisture; spatial analysis; visualization.

Subashisa Dutta, Ashok Mishra, S Kar  and Sushma Panigrahy

Abstract: An approach to estimate the curve number (CN) at each pixel unit of a satellite imagery, which is a key parameter in the widely used Soil Conservation Service Curve Number (SCSCN) hydrologic model, is proposed. Instead of mapping land use and its temporal dynamics from satellite imageries, this approach linearly unmixes the multi-spectral radiances into three fractional layers which primarily control the degree of saturation within a watershed occurring due to a 25 cm-depth storm event, i.e., physically interpreted as the CN. The fraction layers used are water, sand and pure vegetation. In order to obtain a relationship between the fractional statistics and CN, a multi-correlationship analysis of known combinations of land use, hydrologic condition and hydrologic soil group is carried out in an agricultural watershed. The obtained relationship is applied onto the fractional layers to compute the spatial distribution of CN. The performance of the SCS-CN model with the spatial CN is found to be 14% more accurate than that of the model results with only land use information from satellite imageries. The spatial difference of two CN layers in which the one represents the condition of the watershed before soil and water conservation measures was taken up and the other for the post conservation period indicates change in the hydrologic response of the watershed spatially.

Key words: Curve Number; Satellite Imagery; Watershed modeling; GIS.

M. Kholghi and S.M. Hosseini

Abstract: In interpolation of groundwater properties such as transmissivity, due to the unknown distributed values of the variables and heterogenity, the best and the unbiased aspects are frequently difficult to obtain. Therefore, applying a modern technique is necessary to obtain a real estimation of transmissivity. To gain the transmissivity values as an input data in groundwater modelling, the ordinary log kriging method has been used. In this study, the efficiency of the Adaptive Network based Fuzzy Inference System (ANFIS), artificial neural networks and ordinary kriging are investigated for interpolation of transmissivity in an unconfined aquifer. The results indicate that ANFIS model is more efficient to estimate the transmissivity in comparison with the ANN and kriging  models. With these results, we can propose ANFIS model to interpolate the transmissivity values in groundwater modelling processes.

Keywords: Transmissivity, Kriging, Artificial Neural Network, ANFIS.

P.J. Davies, J.W. Cox, N.K. Fleming, W.J. Dougherty, D.M. Nash and J.L. Hutson

Abstract:Research has been conducted at Flaxley Agricultural Centre in South Australia to predict phosphorus loss in surface runoff from dairy pastures. Part of the research investigated if the topography based, spatially distributed hydrological model - TOPMODEL could be adapted to successfully predict phosphorus loads off dryland and irrigated catchments, where variable source area hydrology is considered a dominant process. This was carried out by integrating one season of field measured runoff and P load data with rainfall and evapotranspiration data. The methodology uses TOPMODEL to simulate runoff volume and spatial extent of saturated areas, using a topographic index - ln(As/tanB) to distribute variable source areas across catchments, within a loose coupled GIS framework. Using the simulations of runoff from the dryland and irrigated catchments, phosphorus loads in surface runoff were then simulated, using an empirically established, terrain-based phosphorus load index relatable to variable source runoff (TOPMODEL-PLI).

Keywords: TOPMODEL, Hydrological modelling, terrain analysis, surface water, phosphorus

Ramin Safamanesh, Wan Nor Azmin Sulaiman and Mohammad Firuz Ramli

Abstract: Watershed degradation due to soil erosion and sedimentation is one of the major environmental problems in Iran. In addressing the issue, a study on the validity of an empirical model of Pacific South West Inter Agency Committee Method (MPSIAC) to predict annual average sediment yield to Zargeh watershed was undertaken. The MPSIAC method incorporates nine environmental factors that contribute to sediment yield of the watershed namely: surface geology, soil, climate, runoff, topography, ground cover, land use, channel and upland erosion. Open-source Geographic Resources Analysis Support System (GRASS) was used to facilitate the spatial interpolation of the nine model factors and interpretation of predicted sediment yield for the entire watershed. Twenty year sediment yield records from 1980 to 1999 were used to validate the simulated model results. Simple linear regression analysis between simulated model results and actual field records indicated that there was a significant correlation (P < 0.05) with r2 = 0.6124. The results suggested that the model is suitable for predicting yearly average sediment yield on a long term basis fo the Iranian watersheds with similar conditions.

Keywords: MPSIAC, Erosion, Sediment Yield.

A.C. Ekwe_, N.N. Onu and K.M.Onuoha

Abstract: We have used the concept of Da - Zarrouk parameters (transverse unit resistance (R) and longitudinal conductance (C)) in porous media to determine aquifer hydraulic characteristics within the middle Imo river basin. The lithostratigraphic units within the study area include: Imo formation, Bende - Ameki formation, Ogwashi Asaba formation and Benin formation. The direct current electrical resistivity method was utilized for the present study. Twenty-four (24) vertical electrical soundings (VES) using the Schlumberger array was acquired for the study area. A maximum current electrode spacing (AB) of 1000 meters was used. Eight of the soundings were carried out near existing boreholes. A combination of curve matching techniques and computer iterative modelling was used in processing the data. Results show that the depth to water table  varies between 12m at Ife and 153m at Aba Branch. Interpretative cross - section along two profiles show that aquifer thicknesses range between 9m and 104m. The diagnostic Kσ = constant value was used to delineate the different lithostratigraphic units within the study area. We have also used the established relationship between aquifer characteristics and geoelectric parameters to estimate hydraulic conductivity and transmissivity values of all the sounding locations including areas where boreholes were non - existent. Hydraulic conductivity varies between 1.24 m/day at Amuzukwu and 26.41 m/day at Obinze. Transmissivity values also vary between 41m2/day at Osuachara and 1370 m2/day at Obinze.

Keywords: Aquifer hydraulic characteristics, Dar - Zarrouk parameters, Resistivity, Imo River Basin, Nigeria.