Experimental study for determination of infiltration rate of soils in field using double ring infiltrometer

Infiltration is the process of penetration of water into the ground surface and the intensity of this process is known as infiltration rate. The infiltration rate is expressed in term of volume of water poured per ground surface per unit of time. Soil erosion, surface runoff & ground water recharge are affected by this process. At a certain moment the maximum infiltration rate can be indicated by the infiltration capacity of soil. Infiltration of water into the soil can be determined by a simple instrument called Double ring infiltrometer. The cylindrical ring infiltrometer consist of single metal cylinder. These cylinders are partially inserted into the ground and water is filled up to a margin inside the cylinder and after that the speed of penetration of water is measured with respect to the time and depth of penetration of water inside the cylinder. Four types of cylinders are taken for this experiment of diameter 15cm, 30cm, 45cm & 60cm and they are experimented as 15-45cm & 30-60cm double ring infiltrometer. To spread the water vertically after infiltration we use double ring infiltrometer. Double ring infiltrometer is better than single ring infiltrometer. In single ring infiltrometer the water will spread horizontally & vertically both, from which water will not move only towards the ground water but using double ring infiltrometer the water will penetrate in one direction that is towards the ground water without much wastage of water

Rainfall Reliability Evaluation for Stability of Municipal Solid Waste Landfills on Slope

[[abstract]]A method to assess the reliability for the stability of municipal solid waste (MSW) landfills on slope due to rainfall infiltration is proposed. Parameter studies are first done to explore the influence of factors on the stability of MSW. These factors include rainfall intensity, duration, pattern, and the engineering properties of MSW. Then 100 different combinations of parameters are generated and associated stability analyses of MSW on slope are performed assuming that each parameter is uniform distributed around its reason ranges. In the following, the performance of the stability of MSW is interpreted by the artificial neural network (ANN) trained and verified based on the aforementioned 100 analysis results. The reliability for the stability of MSW landfills on slope is then evaluated and explored for different rainfall parameters by the ANN model with first-order reliability method (FORM) and Monte Carlo simulation (MCS).[[incitationindex]]SCI[[booktype]]紙

Integration of artificial neural network and geographic information system applications in simulating groundwater quality

Background: Although experiments on water quality are time consuming and expensive, models are often employed as supplement to simulate water quality. Artificial neural network (ANN) is an efficient tool in hydrologic studies, yet it cannot predetermine its results in the forms of maps and geo-referenced data. Methods: In this study, ANN was applied to simulate groundwater quality and geographic information system (GIS) was used as pre-processing and post-processing tool in simulating water quality in the Mazandaran Plain (Caspian southern coasts, Iran). Groundwater quality was simulated using multilayer perceptron (MLP) network. The determination of groundwater quality index (GWQI) and the estimation of effective factors in groundwater quality were also undertaken. After modeling in ANN, the model validation was carried out. Also, the study area was divided with the pixels 1×1 km (raster format) in GIS medium. Then, the model input layers were combined and a raster layer which comprised the model inputs values and geographic coordinate was generated. Using geographic coordinate, the values of pixels (model inputs) were inputted into ANN (Neuro Solutions software). Groundwater quality was simulated using the validated optimum network in the sites without water quality experiments. In the next step, the results of ANN simulation were entered into GIS medium and groundwater quality map was generated based on the simulated results of ANN. Results: The results revealed that the integration of capabilities of ANN and GIS have high accuracy and efficiency in the simulation of groundwater quality. Conclusion: This method can be employed in an extensive area to simulate hydrologic parameters. Keywords: Water quality, GWQI, MLP, Mazandaran Plai

Rainfall-Runoff modeling of river Kosi using SCS-CN method and ANN

A rainfall-runoff model is a mathematical model describing the rainfall - runoff relations of a catchment area, drainage basin or watershed. In other words, the model calculates the conversion of rainfall into runoff. There can be used many methods to calculate the runoff among which the methods used in the current report are • SCS-CN Method • Artificial Neural Network (ANN) In rainfall-runoff modeling SCS-CN uses the soil information, rainfall, storm duration, soil texture, type & amount of vegetation cover and conservation practices are considered while a new dimension has been added to the modeling approach through the adoption of the ANN technique as these models possess desirable attributes of universal approximation, and the ability to learn from examples. The performance comparison of both the models is made with coefficient of determination (R2) which is coming to be 0.82 in case of SCS-CN method and 0.89 in case of ANN. Further a comparison is made of both the models i.e. ANN and SCS-CN for the runoff of river Kosi in year 2009