Soil property varies randomly in a field and there is some correlation between its values at any two points. Especially, in an artificial soil structure like an embankment, it has some anisotropic spatial correlation due to constructive features. In our earlier work, the effect of the standard deviation and the correlation distance of soil permeability on total flow rate in a random field with isotropic spatial correlation has been clarified and spatial spanning of lower or higher permeability that forms "impervious wall" or "flow path" has been reproduced by Percolation theory. This paper attempts to evaluate objectively fracture characteristics of random field with anisotropic spatial correlation by using fractal dimensions. Spatially correlated random fields with anisotropic spatial correlation distance are generated, and fractal dimensions are examined for each of these random fields. As a result, the fractal dimensions are shown to have some close relation to the anisotropic spatial correlation in random fields.

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Estimating the characteristics of groundwater contamination source is a very important topic in geo-environmental studies. In the present study, an applicability of Genetic Algorithm (GA) to the problem of identifying the contamination source is examined. Six parameters of the contamination source are identified by this method, which are its location, its size (the length of the source that is assumed to extend linearly), its initial concentration, reduction factor, and the time when contamination begins. The effect of the data acquisition intervals and the number of observation points on GA performances is investigated. It is found that increasing the number of observation points is more effective than increasing the observation frequency at one point in order to improve the accuracy of estimation. The variations of concentration at a point far from the source are calculated using estimated parameters to examine the predictability. As a result, it is shown that the accuracy of estimated parameters greatly affect the prediction. Moreover, a limit of application of GA on heterogeneous aquifers generated based on geo-statistics is also examined. It is found that if the hydraulic conductivity is distributed within two orders of the heterogeneity, GA provides the parameters of practical precision.

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Literatures are reviewed to give an overview of the causes, effects and remedies of groundwater nitrate contamination. It is evident that groundwater nitrate contamination is a worldwide problem, which needs to be controlled because of its implications on human health. Many environmental, geological, hydrological and agricultural factors are associated with groundwater nitrate contamination. Anthropogenic sources, mainly due to application of excess nitrogen-based fertilizer to the agricultural fields, livestock manure, and uncontrolled septic tanks, cause nitrate contamination. As a remedy of the problem, treatment of contaminated water may be a solution, but treatment process is expensive and all nitrates cannot be removed from the water by any of the techniques. Therefore, rather than nitrate removal from contaminated water, protection of groundwater from potential contamination is preferred. A location specific management model is indeed needed, which establishes the relationship between the management indicators and the groundwater nitrate concentration. Literatures show that usual processes of managing nitrate-contaminated aquifers are: to identify the sources and causes of contamination and then to find out a management model either by aquifer vulnerability analyses or simulation technique. However, in most of the cases it is very difficult to construct a definite correlation between the groundwater nitrate concentrations and aquifer vulnerability potential indicators, which limits management of nitrate-contaminated aquifers using the vulnerability map. On the other hand, groundwater nitrate simulation is also complicated due to the complexity of nitrate leaching flux estimation. Most of the nitrate simulation models are physically-based, which require many input parameters, thus limiting their actual field application. On the contrary, there are very few conceptual models requiring less data, but their predictive capability with regard of assessing the impacts of alternative management practices is questionable. To overcome these problems we must have to find out alternative techniques. For instance, incorporating Artificial Neural Network (ANN) in vulnerability analyses or developing nitrate leaching model of conceptual quasi-physical type may be a solution.

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Distribution of water in an interconnected irrigation tanks system is discussed using mathematical models. Temporal variations in the storage volumes of irrigation tanks are modeled as ordinary differential equations describing flow continuity. The optimal control theory is applied to those continuity equations and a performance index evaluating the storage deviations from the target values as well as the terminal time when an irrigation tank dries up. A minimum principle is deduced to characterize an optimal strategy for release discharges in the connection channels. It is shown that such an optimal strategy is obtained via forward calculation by means of adjoint system. Demonstrative simulations are implemented under appropriate settings of the target values, weight in the performance index, and water saving strategy of demand side. The results show that this methodology is simple and feasible.

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A finite element modeling for three-dimensional analysis of saturated-unsaturated steady state seepage flow in hydrogeological complexity is attempted in order to investigate the effect of grouting works on seeping water losses from the damsite and reservoir of the Nakadake Dam, Japan. In the left hillside of the reservoir, the area where groundwater level is lower than the full water level of the dam reservoir stretches far from the damsite and therefore how to design the grouting works becomes a crucial problem. To clear up the effect of the rainfall recharge on seepage flow, two series of analysis are carried out: Series A and B with and without rainfall recharge, respectively. For the respective series, total flow rates and seepage losses are estimated in relation to the length of the grouting works. To investigate in more detail flow rates across the grouting limb, the partial flow rates across seven fragmented limbs are compared. As a result, the total flow rate for Series A is larger than that for Series B, but there is a slight difference in flow rate characteristics between both series. When the limb length is 1.20 and 1.88 times as large as the magnitude of full reservoir water depth, the total flow rate becomes about 43% and 55% of that without grouting works, respectively. In the latter case, however, seepage loss is not so effectively reduced although the limb is longer. This is because the flow taking a detour without going through the grouted limb significantly contributes to the aggregate seepage loss.

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