Micro paddy lysimeter for monitoring solute transport in paddy environment

The micro paddy lysimeter (MPL) was developed and evaluated for its performance to simulate solute transport in paddy environment under laboratory conditions. MPLs were constructed using soil collected from Field Museum Honmachi of Tokyo University of Agriculture and Technology, Japan. For the physical characteristics of the hardpan layer, parameters such as thickness, and soil aggregate size, affecting the percolation rate were studied. For the plow layer, two types of plow soils, sieved and un-sieved soils were compared. The sieved soil plow layer was produced by mixing air-dried soils of different aggregate sizes of D > 9.50, 9.50 ≥ D > 4.75, 4.75 ≥ D > 2.0 mm and D ≤ 2.0 mm at 47.1, 19.5, 20.6, and 12.8%, respectively. The un-sieved plow layer soil was directly used after collecting from the field. Inert tracer was applied to ponding water with controlled boundary conditions to evaluate the reproducibility of the soil hydraulic characteristics. HYDRUS-1D was used to evaluate the movement of bromide tracer in the MPL. The proposed conditions of the MPL were that the hardpan layer can be made from soil aggregates smaller than 0.425 mm with 2 cm thickness and that the plow layer can be prepared with sieved or un-sieved soils. With these conditions, the obtained results proved that MPLs can be a useful tool to simulate solute transport in paddy environment.

A lysimeter experimental study and numerical characterisation of the leaching of incinerator bottom ash waste

Incinerator bottom ash (IBA) is a residual produced from incinerating municipal solid waste. In the past, IBA presented a big waste disposal problem; however, various recycling approaches have been adopted in recent years to mitigate this problem, as well as to provide a useful alternative to using primary aggregate resources. The use of IBA as an alternative to conventional aggregates in different civil engineering construction applications helps to conserve premium grade aggregate supplies; however, when IBA is in contact with water in the field, as a consequence of precipitation events or changes in water table, elements, such as salts and heavy metals, may be released to the soil and ground water. In this work, IBA waste was mixed with limestone aggregate to produce a blend with acceptable mechanical properties and minimum environmental risks for use as road foundation. The study focused on evaluating potential environmental impacts of some constituents, including sulphate, chloride, sodium, copper, zinc and lead in IBA blends using a lysimeter as a large scale leaching tool. Moreover, a specific scenario simulating field conditions was adopted in the lysimeter to assess the potential impact of changing conditions, such as IBA content in the blend, liquid to solid ratio (L/S) and pH value, on long-term release of heavy metals and salts. Then, numerical modelling was used to predict the release of the aforementioned constituents from IBA based on initial measurement of intrinsic material properties and the kinetic desorption process concept. Experimental results showed that zinc and lead were released in very low concentrations but sodium and sulphate were in high concentrations. The control limestone only blend also demonstrated low release concentrations of constituents in comparison to IBA blends, where constituent concentrations increased with increase in IBA content. Experimental results were compared with numerical results obtained using a non-equilibrium desorption model. Good agreement was found between the two sets of data. 

Spatial and temporal distribution of solute leaching in heterogeneous soils: analysis and application to multisampler lysimeter data

Accurate assessment of the fate of salts, nutrients, and pollutants in natural, heterogeneous soils requires a proper quantification of both spatial and temporal solute spreading during solute movement. The number of experiments with multisampler devices that measure solute leaching as a function of space and time is increasing. The breakthrough curve (BTC) can characterize the temporal aspect of solute leaching, and recently the spatial solute distribution curve (SSDC) was introduced to describe the spatial solute distribution. We combined and extended both concepts to develop a tool for the comprehensive analysis of the full spatio-temporal behavior of solute leaching. The sampling locations are ranked in order of descending amount of total leaching (defined as the cumulative leaching from an individual compartment at the end of the experiment), thus collapsing both spatial axes of the sampling plane into one. The leaching process can then be described by a curved surface that is a function of the single spatial coordinate and time. This leaching surface is scaled to integrate to unity, and termed S can efficiently represent data from multisampler solute transport experiments or simulation results from multidimensional solute transport models. The mathematical relationships between the scaled leaching surface S, the BTC, and the SSDC are established. Any desired characteristic of the leaching process can be derived from S. The analysis was applied to a chloride leaching experiment on a lysimeter with 300 drainage compartments of 25 cm2 each. The sandy soil monolith in the lysimeter exhibited fingered flow in the water-repellent top layer. The observed S demonstrated the absence of a sharp separation between fingers and dry areas, owing to diverging flow in the wettable soil below the fingers. Times-to-peak, maximum solute fluxes, and total leaching varied more in high-leaching than in low-leaching compartments. This suggests a stochastic–convective transport process in the high-flow streamtubes, while convection–dispersion is predominant in the low-flow areas. S can be viewed as a bivariate probability density function. Its marginal distributions are the BTC of all sampling locations combined, and the SSDC of cumulative solute leaching at the end of the experiment. The observed S cannot be represented by assuming complete independence between its marginal distributions, indicating that S contains information about the leaching process that cannot be derived from the combination of the BTC and the SSDC.