Hydraulic Conductivity
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2021 ◽  
Vol 8 (1-2) ◽  
pp. 26-31
Adebola Adekunle ◽  
Fidelis Nkeshita ◽  
Adetayo Akinsanya

This study investigated the influence of leachate prepared from Telfairia occidentalis on the geotechnical and geochemical properties of termite mound soil obtained from the premises of the federal university of agriculture, Abeokuta, south-western Nigeria. The termite mound soil samples were collected from three different locations and each sample collected was contaminated by mixing with leachates in percentage increments of 0% 10%, 15% and 20% of dry weight of the air-dried soil. The soil samples were subjected to Atterberg limits and hydraulic conductivity tests for geotechnical observation and X-ray fluorescence tests for geochemical tests. The range of values for the geotechnical analyses were obtained as; plastic limit (9.1% – 14.2%), liquid limit (28.6 % – 61%), plasticity index ((18.2% – 49.5%) and hydraulic conductivity (1.85 – 4.1 x 10-8) cm/sec) with a resultant reduction in the plastic limit, liquid limit and plasticity index values but an increase in the hydraulic conductivity of the samples as the leachate concentration increased. The results from X-ray fluorescence analyses after 20% leachate contamination showed that the major elemental chemical composition for the three samples were comprised of SiO2 (56.25 – 56.5%), Al2O3 (28.42 – 28.50%), Fe2O3 (4.46 – 6.5%), TiO2 (1.08 – 1.23%), CaO (1.45 – 1.60%), P2O5 (0 – 0.04%), K2O (0.9 – 6.1%) and MnO (0.02 – 4.7%). There was a marginal alteration of the indices with the values inferring the presence of a minimum composition of feldspar and a major composition of quartz-rich minerals and thus lending more credence to the presence of silicates as shown from the X-ray fluorescence results. It also infers that the termite mounds are predominantly made from sand materials. The termite soil samples obtained from the aforementioned locations may not be suitable for engineering works unless stabilization procedure is adopted.

2021 ◽  
Zhongxia Li ◽  
Junwei Wan ◽  
Tao Xiong ◽  
Hongbin Zhan ◽  
Linqing He ◽  

Abstract. This study provides experimental evidence of Forchheimer flow and transition between different flow regimes from the perspective of pore size of permeable stone. We have firstly carried out the seepage experiments of permeable stones with four different mesh sizes, including 24 mesh size, 46 mesh size, 60 mesh size, and 80 mesh size, which corresponding to mean particle sizes (50 % by weight) of 0.71 mm, 0.36 mm, 0.25 mm, and 0.18 mm. The seepage experiments show that obvious deviation from Darcian flow regime is visible. In addition, the critical specific discharge corresponding to the transition of flow regimes (from pre-Darcian to post-Darcian) increases with the increase of particle sizes. When the “pseudo” hydraulic conductivity (K) (which is computed by the ratio of specific discharge and the hydraulic gradient) increases with the increase of specific discharge (q), the flow regime is denoted as the pre-Darcian flow. After the specific discharge increases to a certain value, the “pseudo” hydraulic conductivity begins to decrease, and this regime is called the post-Darcian flow. In addition, we use the mercury injection experiment to measure the pore size distribution of four permeable stones with different particle sizes, and the mercury injection curve is divided into three stages. The beginning and end segments of the mercury injection curve are very gentle with relatively small slopes, while the intermediate mercury injection curve is steep, indicating that the pore size in permeable stones is relatively uniform. The porosity decreases as the mean particle sizes increases, and the mean pore size can faithfully reflect the influence of particle diameter, sorting degree and arrangement mode of porous medium on seepage parameters. This study shows that the size of pores is an essential factor for determining the flow regimes. In addition, the Forchheimer coefficients are also discussed in which the coefficient A (which is related to the linear term of the Forchheimer equation) is linearly related to 1/d 2 as A = 0.0025 (1/d 2) + 0.003; while the coefficient B (which is related to the quadratic term of the Forchheimer equation) is a quadratic function of 1/d as B =1.14E-06 (1/d)2 − 1.26E-06 (1/d). The porosity (n) can be used to reveal the effect of sorting degree and arrangement on seepage coefficient. The larger porosity leads to smaller coefficients A and B under the condition of the same particle size.

Water ◽  
2021 ◽  
Vol 13 (23) ◽  
pp. 3376
Pierre Claver Ngenzebuhoro ◽  
Alain Dassargues ◽  
Tarik Bahaj ◽  
Philippe Orban ◽  
Ilias Kacimi ◽  

The study area, in northwestern Burundi, is an alluvial plain consisting of fine clayey sands and coarse sands with mixed lithology. The aquifer of the lower Rusizi plain could be considered as confined under a clay layer. A 2D horizontal groundwater flow model was developed under steady-state conditions using the Modflow software. The study aims to determine the most productive areas of this confined alluvial aquifer and the main aquifer inflow and outflow values together with the recharge and river–aquifer interactions. The groundwater potential is dependent on the spatial distribution of hydraulic conductivity and aquifer thickness values providing the local transmissivity values. The calibrated model made it possible to assess the spatial distribution of the hydraulic conductivity values at the regional scale, which ranged from 6 × 10−6 (contact between alluvial plain and Precambrian basement) to 7.5 × 10−3 m/s (coastal barriers). The results also provided the computed groundwater flow directions, and an estimation of the groundwater levels in areas not yet investigated by drilling. The results of the computed groundwater flow budget allowed us to deduce that recharge and river–aquifer interaction constitute the main inflow while the downwards boundaries (where piezometric heads could be prescribed) are the main zones where outflows occur. The results of this model can be used in the planning of pumping test programs, locating areas with high groundwater potential to plan water supply for different private and public users. This predictive tool will contribute to the resolution of problems related to the use and integrated management of the groundwater resource in this part of Burundi.

Water ◽  
2021 ◽  
Vol 13 (23) ◽  
pp. 3330
Ali ZA. Al-Ozeer ◽  
Alaa M. Al-Abadi ◽  
Tariq Abed Hussain ◽  
Alan E. Fryar ◽  
Biswajeet Pradhan ◽  

Knowledge of the groundwater potential, especially in an arid region, can play a major role in planning the sustainable management of groundwater resources. In this study, nine machine learning (ML) algorithms—namely, Artificial Neural Network (ANN), Decision Jungle (DJ), Averaged Perceptron (AP), Bayes Point Machine (BPM), Decision Forest (DF), Locally-Deep Support Vector Machine (LD-SVM), Boosted Decision Tree (BDT), Logistic Regression (LG), and Support Vector Machine (SVM)—were run on the Microsoft Azure cloud computing platform to model the groundwater potential. We investigated the relationship between 512 operating boreholes with a specified specific capacity and 14 groundwater-influencing occurrence factors. The unconfined aquifer in the Nineveh plain, Mosul Governorate, northern Iraq, was used as a case study. The groundwater-influencing factors used included elevation, slope, curvature, topographic wetness index, stream power index, soil, land use/land cover (LULC), geology, drainage density, aquifer saturated thickness, aquifer hydraulic conductivity, aquifer specific yield, depth to groundwater, distance to faults, and fault density. Analysis of the contribution of these factors in groundwater potential using information gain ratio indicated that aquifer saturated thickness, rainfall, hydraulic conductivity, depth to groundwater, specific yield, and elevation were the most important factors (average merit > 0.1), followed by geology, fault density, drainage density, soil, LULC, and distance to faults (average merit < 0.1). The average merits for the remaining factors were zero, and thus, these factors were removed from the analysis. When the selected ML classifiers were used to estimate groundwater potential in the Azure cloud computing environment, the DJ and BDT models performed the best in terms of all statistical error measures used (accuracy, precision, recall, F-score, and area under the receiver operating characteristics curve), followed by DF and LD-SVM. The probability of groundwater potential from these algorithms was mapped and visualized into five groundwater potential zones: very low, low, moderate, high, and very high, which correspond to the northern (very low to low), southern (moderate), and middle (high to very high) portions of the study area. Using a cloud computing service provides an improved platform for quickly and cheaply running and testing different algorithms for predicting groundwater potential.

2021 ◽  
Vol 44 (4) ◽  
pp. 1-10
Moisés Lemos ◽  
Lucas Guimarães ◽  
André Cavalcante

Several regions in Brazil and the world suffer from the presence of collapsible soils. The development of theories for understanding the phenomenon is significant because the increase of water content is associated with several reasons (e.g., precipitation, rupture of sewage, and water systems). Although some theories explain the behavior of various types of soils, they fail to explain collapsible and structured soils. In this research, an alternative interpretation of the consolidation theory is verified and calibrated for collapsible soil. The alternative model was applied to experimental data from a latosol from southeastern Brazil, and comparisons with the classical theory showed a difference in the saturated hydraulic conductivity of around 100 times. The observation showed promising results compared with the saturated hydraulic conductivity of the field (Guelph Permeameter). Furthermore, consolidation tests verified the collapse potential, the variation of consolidation coefficient and saturated hydraulic conductivity, and the total settlement prevision due to the presence of bleach and washing powder.

Mahdi Zoorabadi ◽  
Serkan Saydam ◽  
Wendy Timms ◽  
Bruce Hebblewhite

2021 ◽  
Vol 11 (1) ◽  
Adriano Losso ◽  
Andreas Bär ◽  
Lucrezia Unterholzner ◽  
Michael Bahn ◽  
Stefan Mayr

AbstractDuring winter, conifers at the alpine treeline suffer dramatic losses of hydraulic conductivity, which are successfully recovered during late winter. Previous studies indicated branch water uptake to support hydraulic recovery. We analyzed water absorption and redistribution in Picea abies and Larix decidua growing at the treeline by in situ exposure of branches to δ2H-labelled water. Both species suffered high winter embolism rates (> 40–60% loss of conductivity) and recovered in late winter (< 20%). Isotopic analysis showed water to be absorbed over branches and redistributed within the crown during late winter. Labelled water was redistributed over 425 ± 5 cm within the axes system and shifted to the trunk, lower and higher branches (tree height 330 ± 40 cm). This demonstrated relevant branch water uptake and re-distribution in treeline conifers. The extent of water absorption and re-distribution was species-specific, with L. decidua showing higher rates. In natura, melting snow might be the prime source for absorbed and redistributed water, enabling embolism repair and restoration of water reservoirs prior to the vegetation period. Pronounced water uptake in the deciduous L. decidua indicated bark to participate in the process of water absorption.

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