Evaluation of effective groundwater recharge of freshwater lens in small islands by the combined modeling of geoelectrical data and water heads

In small islands, a freshwater lens can develop due to the recharge induced by rain. Magnitude and spatial distribution of this recharge control the elevation of freshwater and the depth of its interface with salt water. Therefore, the study of lens morphology gives useful information on both the recharge and water uptake due to evapotranspiration by vegetation. Electrical resistivity tomography was applied on a small coral reef island, giving relevant information on the lens structure. Variable density groundwater flow models were then applied to simulate freshwater behavior. Cross validation of the geoelectrical model and the groundwater model showed that recharge exceeds water uptake in dunes with little vegetation, allowing the lens to develop. Conversely, in the low-lying and densely vegetated sectors, where water uptake exceeds recharge, the lens cannot develop and seawater intrusion occurs. This combined modeling method constitutes an original approach to evaluate effective groundwater recharge in such environments.
[Comte, J.-C., O. Banton, J.-L. Join, and G. Cabioch (2010), Evaluation of effective groundwater recharge of freshwater lens in small islands by the combined modeling of geoelectrical data and water heads, Water Resour. Res., 46, W06601, doi:10.1029/2009WR008058.]

Neural Network Modeling of Rheological Parameters of Grouts Containing Viscosity-Modifying Agent

The development of artificial neural network (ANN) models to predict the rheological behavior of grouts is described is this paper and the sensitivity of such parameters to the variation in mixture ingredients is also evaluated. The input parameters of the neural network were the mixture ingredients influencing the rheological behavior of grouts, namely the cement content, fly ash, ground-granulated blast-furnace slag, limestone powder, silica fume, water-binder ratio (w/b), high-range water-reducing admixture, and viscosity-modifying agent (welan gum). The six outputs of the ANN models were the mini-slump, the apparent viscosity at low shear, and the yield stress and plastic viscosity values of the Bingham and modified Bingham models, respectively. The model is based on a multi-layer feed-forward neural network. The details of the proposed ANN with its architecture, training, and validation are presented in this paper. A database of 186 mixtures from eight different studies was developed to train and test the ANN model. The effectiveness of the trained ANN model is evaluated by comparing its responses with the experimental data that were used in the training process. The results show that the ANN model can accurately predict the mini-slump, the apparent viscosity at low shear, the yield stress, and the plastic viscosity values of the Bingham and modified Bingham models of the pseudo-plastic grouts used in the training process. The results can also predict these properties of new mixtures within the practical range of the input variables used in the training with an absolute error of 2%, 0.5%, 8%, 4%, 2%, and 1.6%, respectively. The sensitivity of the ANN model showed that the trend data obtained by the models were in good agreement with the actual experimental results, demonstrating the effect of mixture ingredients on fluidity and the rheological parameters with both the Bingham and modified Bingham models.

Hydraulic Subsurface Measurements and Hydrodynamic Modeling as Indicators for Groundwater Flow Systems in the Rotondo Granite, Central Alps (Switzerland)

Regional groundwater flow in high mountainous terrain is governed by a multitude of factors such as geology, topography, recharge conditions, structural elements such as fracturation and regional fault zones as well as man-made underground structures. By means of a numerical groundwater flow model, we consider the impact of deep underground tunnels and of an idealized major fault zone on the groundwater flow systems within the fractured Rotondo granite. The position of the free groundwater table as response to the above subsurface structures and, in particular, with regard to the influence of spatial distributed groundwater recharge rates is addressed. The model results show significant unsaturated zones below the mountain ridges in the study area with a thickness of up to several hundred metres. The subsurface galleries are shown to have a strong effect on the head distribution in the model domain, causing locally a reversal of natural head gradients. With respect to the position of the catchment areas to the tunnel and the corresponding type of recharge source for the tunnel inflows (i.e. glaciers or recent precipitation), as well as water table elevation, the influence of spatial distributed recharge rates is compared to uniform recharge rates. Water table elevations below the well exposed high-relief mountain ridges are observed to be more sensitive to changes in groundwater recharge rates and permeability than below ridges with less topographic relief. In the conceptual framework of the numerical simulations, the model fault zone has less influence on the groundwater table position, but more importantly acts as fast flow path for recharge from glaciated areas towards the subsurface galleries. This is in agreement with a previous study, where the imprint of glacial recharge was observed in the environmental isotope composition of groundwater sampled in the subsurface galleries. Copyright © 2012 John Wiley & Sons, Ltd.

Investigating the of Water treatment residuals on Phosphorus mobility derived from biosolid application to Willow coppice

Short rotation willow coppice (SRWC) treatment of biosolids is limited by the oversupply of biosolid derived phosphorus; this can lead to eventual losses of phosphorus to water. Water treatment residuals (WTR), a by-product of potable water treatment, have been identified as a viable soil amendment for mitigation of phosphorus loss. WTR exploit the capacity of internally held aluminium oxide-hydroxide complexes to immobilise labile phosphorus. However indiscriminate additions to plots can result in inadequate control or excessive immobilization of soluble P, leading to crop deficiencies. Four commercially grown common willow (Salix) genotypes (Terra Nova, Endeavour, Resolution and Tora) were grown in soil amended with WTR at five different application rates (0, 10, 25, 50 and 100 tonne ha-1 air-dry basis) in a glasshouse pot experiment. The effects of application rates on plant yields, tissue P concentrations, P uptake and soil labile P availability were measured. Results indicate labile P was reduced with increasing WTR application rates, without any negative agronomic impacts.

Soil Moisture Deficit as a predictor of the trend in soil water status of grass fields

Nutrient loss from agricultural land following organic fertilizer spreading can lead to eutrophication and poor water quality. The risk of pollution is partly related to the soil water status during and after spreading. In response to these issues, a decision support system (DSS) for nutrient management has been developed to predict when soil and weather conditions are suitable for slurry spreading. At the core of the DSS, the Hybrid Soil Moisture Deficit (HSMD) model estimates soil water status relative to field capacity (FC) for three soil classes (well, moderately and poorly drained) and has potential to predict the occurrence of a transport vector when the soil is wetter than FC. Three years of field observation of volumetric water content was used to validate HSMD model predictions of water status and to ensure correct use and interpretation of the drainage classes. Point HSMD model predictions were validated with respect to the temporal and spatial variations in volumetric water content and soil strength properties. It was found that the HSMD model predictions were well related to topsoil water content through time, but a new class intermediate between poor and moderate, perhaps ‘imperfectly drained’, was needed. With correct allocations of a field into a drainage class, the HSMD model predictions reflect field scale trends in water status and therefore the model is suitable for use at the core of a DSS.

Coupling ground and airborne geophysical data with upscaling techniques for regional groundwater modeling of heterogeneous aquifers: Case study of a sedimentary aquifer intruded by volcanic dykes in Northern Ireland

In highly heterogeneous aquifer systems, conceptualization of regional groundwater flow models frequently results in the generalization or negligence of aquifer heterogeneities, both of which may result in erroneous model outputs. The calculation of equivalence related to hydrogeological parameters and applied to upscaling provides a means of accounting for measurement scale information but at regional scale. In this study, the Permo-Triassic Lagan Valley strategic aquifer in Northern Ireland is observed to be heterogeneous, if not discontinuous, due to subvertical trending low-permeability Tertiary dolerite dykes. Interpretation of ground and aerial magnetic surveys produces a deterministic solution to dyke locations. By measuring relative permeabilities of both the dykes and the sedimentary host rock, equivalent directional permeabilities, that determine anisotropy calculated as a function of dyke density, are obtained. This provides parameters for larger scale equivalent blocks, which can be directly imported to numerical groundwater flow models. Different conceptual models with different degrees of upscaling are numerically tested and results compared to regional flow observations. Simulation results show that the upscaled permeabilities from geophysical data allow one to properly account for the observed spatial variations of groundwater flow, without requiring artificial distribution of aquifer properties. It is also found that an intermediate degree of upscaling, between accounting for mapped field-scale dykes and accounting for one regional anisotropy value (maximum upscaling) provides results the closest to the observations at the regional scale.

Technical and allocative efficiency of irrigation water use in the Guanzhong Plain, China

Due to increasing water scarcity, accelerating industrialization and urbanization, efficiency of irrigation water use in Northern China needs urgent improvement. Based on a sample of 347 wheat growers in the Guanzhong Plain, this paper simultaneously estimates a production function, and its corresponding first-order conditions for cost minimization, to analyze efficiency of irrigation water use. The main findings are that average technical, allocative, and overall economic efficiency are 0.35, 0.86 and 0.80, respectively. In a second stage analysis, we find that farmers’ perception of water scarcity, water price and irrigation infrastructure increase irrigation water allocative efficiency, while land fragmentation decreases it. We also show that farmers’ income loss due to higher water prices can be offset by increasing irrigation water use efficiency.

Effects of arsenic-contaminated irrigation water on growth, yield, and nutrient concentration in rice

A study was undertaken to determine the effects of different concentrations of arsenic (As) in irrigation water on Boro (dry-season) rice (Oryza sativa) and their residual effects on the following Aman (wet-season) rice. There were six treatments, with 0, 0.1, 0.25, 0.5, 1, and 2 mg As L-1 applied as disodium hydrogen arsenate. All the growth and yield parameters of Boro rice responded positively at lower concentrations of up to 0.25 mg As L-1 in irrigation water but decreased sharply at concentrations more than 0.5 mg As L-1. Arsenic concentrations in grain and straw of Boro rice increased significantly with increasing concentration of As in irrigation water. The grain As concentration was in the range of 0.25 to 0.97 μg g-1 and its concentration in rice straw varied from 2.4 to 9.6 μg g-1 over the treatments. Residual As from previous Boro rice showed a very similar pattern in the following Aman rice, although As concentration in Aman rice grain and straw over the treatments was almost half of the As levels in Boro rice grain. Arsenic concentrations in both grain and straw of Boro and Aman rice were found to correlate with iron and be antagonistic with phosphorus. Copyright © Taylor & Francis Group, LLC.

Arsenic uptake and accumulation in rice (Oryza sativa L.) irrigated with contaminated water

Long-term use of arsenic contaminated groundwater to irrigate crops, especially paddy rice (Oryza sativa L.) has resulted in elevated soil arsenic levels in Bangladesh. There is, therefore, concern regarding accumulation of arsenic in rice grown on these soils. A greenhouse pot experiment was conducted to evaluate the impact of arsenic-contaminated irrigation water on the growth and uptake of arsenic into rice grain, husk, straw and root. There were altogether 10 treatments which were a combination of five arsenate irrigation water concentrations (0-8 mg As l^-1) and two soil phosphate amendments. Use of arsenate containing irrigation water reduced plant height, decreased rice yield and affected development of root growth. Arsenic concentrations in all plant parts increased with increasing arsenate concentration in irrigation water. However, arsenic concentration in rice grain did not exceed the maximum permissible limit of 1.0 mg As kg^-1. Arsenic accumulation in rice straw at very high levels indicates that feeding cattle with such contaminated straw could be a direct threat for their health and also, indirectly, to human health via presumably contaminated bovine meat and milk. Phosphate application neither showed any significant difference in plant growth and development, nor in As concentrations in plant parts.

Latent vs. Observed Variables: Analysis of Irrigation Water Efficiency Using SEM and SUR

In this paper we compare conceptualising single factor technical and allocative efficiency as indicators of a single latent variable, or as separate observed variables. In the former case, the impacts on both efficiency types are analysed by means of structural equation modeling (SEM), in the latter by seemingly unrelated regression (SUR). We compare estimation results of the two approaches based on a dataset on single factor irrigation water use efficiency obtained from a survey of 360 farmers in the Guanzhong Plain, China. The main methodological findings are that SEM allows identification of the most important dimension of irrigation water efficiency (technical efficiency) via comparison of their factor scores and reliability. Moreover, it reduces multicollinearity and attenuation bias. It thus is preferable to SUR. The SEM estimates show that perception of water scarcity is the most important positive determinant of both types of efficiency, followed by irrigation infrastructure, income and water price. Furthermore, there is a strong negative reverse effect from efficiency on perception.