Title: Geoenvironmental Assessment for Nitrate Pollution of Surface and Groundwater by Fertilization (A Study in Shiroishi Plain, Japan)

Abstract: In the view of the above this research paper is aimed at presenting the results and findings on the effects of all these developed agricultural practices, as well as over fertilization, on the surface water quality, shallow groundwater and deep groundwater table. Shiroishi Plain in Japan is selected for this ideal study. Sampling was continued for year- around subject to different climatic condition and tillage systems. Several samples of the drainage water at the outlet of the creeks in to the interceptor drains, deep groundwater (around 80 m deep) and interceptor drain waster samples were measured in monthly basis. This research found that nitrate-N concentration in samples collected in subsurface drainage shows the highest fig.s with compared with the others. It implies that the nitrate-N derived from the fertilizers applied to the agricultural beds are retained in the subsurface drainage water. The Ariake clay layer lies under the bed does not allow the nitrate-N to leached into the under ground due to its special physical, chemical and engineering characteristics. Therefore, underground water remains unpolluted and not vulnerable to even contamination by fertilizers and the degree of vulnerability gets higher because there is no leaching process of nutrients through the ariake clay layer. Therefore, it is proposed carry out more in-depth studies to investigate the sustainability of present agricultural practices and developed more environmentally unfriendly and economically unviable. When we consider the economic aspects of current practices, the removal of nutrients through subsurface drainage is considered to be great economical loss to farmers. It help to preserve the quality of water in interceptor drains so that farmers could be able to reuse this water in case of water shortage in the area. This would subsequently help reduce extraction of excessive ground water for agricultural use and thereby could be able to reduce the magnitude of land subsidence in the area by considerable extent.

Title: Particle Swarm Optimization Feedforward Neural Network for Hourly Rainfall-runoff Modeling in Bedup Basin, Malaysia

Abstract: Owing to the complexity of the hydrological process, Backpropagation Neural Network (BPNN) is the single superior model that is able to calibrate the rainfall-runoff relationship accurately using only rainfall and runoff data. However, BPNN convergence rate is relatively slow and being trapped at the local minima. Therefore, a new evolutionary algorithm (EA) namely Particle swarm optimization (PSO) is proposed to train the feedforward neural network. This Particle Swarm Optimization Feedforward Neural Network (PSONN) is applied to model the hourly rainfall-runoff relationship for Bedup Basin. With the input data of current rainfall, antecedent rainfall, antecedent runoff, the optimal configuration of PSONN successfully simulate current runoff accurately with R=0.975 and E2=0.9605 for training data set and R=0.947 and E2=0.9461 for testing data set. Meanwhile, PSONN also proved its ability to predict the runoff accurately at the lead-time of 3, 6, 9 and 12-hour ahead.

Title: Incorporation Of White Cement Dust On Rubber Modified Asphalt Concrete Mixtures

Abstract: The effect of using white cement dust (WCD) as a mineral filler on the mechanical performance of asphalt concrete mixtures modified with crump rubber was investigated. Crumb rubber content of 15% as a percentage of the binder were used. Four WCD contents were considered, namely; 0%, 10%, 20% and 30% by weight of mineral filler. The mechanical performance of the studied mixtures was evaluated based on Marshall Properties, indirect tensile strength, and unconfined compressive strength. Laboratory testing has revealed an enhancement in the mechanical performance of rubber modified asphalt concrete mixtures when cement dust was used. Marshall stability, the unit weight, the indirect tensile strength and the unconfined compressive strength increased with the increase of cement dust content. The flow, voids of total mix (% VTM) and voids of mineral aggregate (% VMA) values decreased as the cement dust content increased.