Subsurface Water Table Research Articles

Evaluation of meteorological drought effects on underground water level fluctuations using data mining methods (case study: semi-deep wells of Golestan province).

In most arid and semi-arid environments, groundwater is one of the precious resources threatened by water table decline and desiccation, thus it must be constantly monitored. Identifying the causes influencing the variations of the subsurface water level, such as meteorological drought, is one approach for monitoring these fluctuations. In the present study, the effect of two meteorological drought indices SPI and SPEI on the fluctuations of the underground water level was evaluated, as was their relationship with the drought index of the subsurface water level (SWI) using multivariate linear regression and M5 decision tree regression. After calculating climatic and hydrological drought indices in a 6-month time window for a long-term statistical period (1989-2018), the semi-deep aquifers of Golestan province, which is located in northern Iran, were considered as a research location for this purpose. The results demonstrated that the effect of meteorological drought does not immediately manifest in the changes of the subsurface water table and the hydrological drought index. By adding the meteorological drought index with a 6-month lag step, the average air temperature, and the total rainfall from the previous 6months as new variables, the correlation with the SWI index increases, so that in the best-case scenario, the M5 decision tree model provides the best result in predicting the SWI index. The second half of the year yielded a coefficient of determination of 0.92 and an error value of RMSE = 0.27 for the SPEI index. Among the meteorological drought indices, the SPEI index, which is based on precipitation and evapotranspiration, created a stronger link with the SWI index, which highlights the significance of potential evapotranspiration. It is a warning that, as a result of global warming, subsurface water tables in this region may fall in the future.

THE SILTING UP OF VEGETABLE CROP AREA IN GANDIOLAIS (NORTHERN COAST OF SENEGAL)

The Gandiolais is part of the large "Niayes" ecosystem in the Saint Louis region. It is bordered by active dunes from the recent Quaternary delimiting interdune depressions in which the sub-surface water table has favored the practice of vegetable crops. These vegetable cropping areas are production systems that are now facing silting up.
 Our results show that this silting is due to deflation and/or mass movement of dune soils. These two phenomena are generated by the sensitivity of dune soils to deflation by trade winds and drought. The resulting negative consequences include, among others, the abandonment of vegetable cropping activities by farmers.
 Solutions to reduce trade wind speeds and improve the cohesion and structuring of dune soils are proposed. In particular, we recommend the creation of windbreaks and the reconstitution of sufficient plant cover.

Detecting subsurface drainage pipes using a fully convolutional network with optical images

More than half of croplands in the Midwestern United States are equipped with subsurface drainage pipes to reduce excess water in productive but wet areas. The use of drainage systems not only reduces subsurface water table to prevent waterlogging and flooding but also increases nutrient losses by developing artificial preferential flow paths. The exact locations of subsurface drainage pipes are thus imperative to manage and monitor water quality and nonpoint source pollution. However, such data are not widely available due to private ownership. Previous studies used conventional image filtering methods, thermal images, and ground penetration radar to detect subsurface drainage pipes. Due to surface features, such as furrow and depressions, and their limited data availability, these experiments did not provide a robust approach to identify subsurface drainage pipes over a large area. To overcome these limitations, in this study, we propose a subsurface drainage pipe detection approach based on deep learning with optical images. Our deep learning approach uses a fully convolution network (FCN) architecture that takes an optical image patch as an input and gives an output of pixel-wise drainage pipe detection map. The FCN was trained and validated using optical image datasets obtained from a freeware Google Earth that provides temporally and spatially abundant data. The trained FCN was then applied to large-scale drainage pipe detection tasks to evaluate its performance. The performance comparison between the proposed deep learning approach and conventional image processing techniques (Sobel and Canny edge detection methods) was also carried out. The results demonstrate that the proposed deep learning approach shows accurate and robust drain line detection performance with an average Dice coefficient of 0.58 for validation sets, providing superior performance over the conventional image processing techniques.

Impacts of longwall mining speeds on permeability of weakly cemented strata and subsurface watertable: a case study

The negative impacts of underground longwall coal mining on water resources and ecological environment are associated with changing overburden permeability and subsurface watertable. For weakly cemented strata characterized by short diagenesis, low strength, easy swelling and mudding with water, overburden permeability and subsurface watertable are highly sensitive to the advancing speed of the longwall. In this paper, the longwall panel 21103 in Yili No.4 Coal Mine, Xinjiang, China, where weakly cemented strata exist in Jurassic and Palaeogene systems, was taken as the case to study the response of overburden permeability and subsurface watertable to different advancing speeds. Results show that there is a butterfly-shaped permeability-increasing area comprised of a trapezoid and double V-shaped subareas in overburden. Generally, the permeability curves of aquiclude are of double peaks. In shallow aquifer, there is an exponential decline in the maximum drawdown of watertable, while a linear decline in lateral influence range as the speed goes up. If constrained by the ultimate watertable drawdown still being able to sustain the regular growth of vegetative covers, the optimal minimum advancing speed of panel 21103 is determined as 8 m/d, which is demonstrated by field verification.

Integrated geophysical investigation for the characterisation of valley bottom soil at Ilora, Southwestern Nigeria

ABSTRACT Hydromorphic soils have potential for sustainable agricultural production due to shallow water deposition, accumulation of organic matter and residual available moisture for farming during dry season. Integrated geophysical investigations comprising Ground Penetrating Radar (GPR) and Vertical Electrical Sounding (VES) were conducted on a valley bottom soil at Ilora, Southwestern Nigeria to determine subsurface geometry, lithology and water table in relation to its agricultural significance. Seventeen GPR profiles were established while twenty eight VES were conducted using Schlumberger array. Three test pits were excavated to a depth of 1 m for ground truth. Horizons revealed on the GPR are; sub-parallel reflections assumed to be fine muddy sand rich in organic matter, low amplitude and weak reflections indicating attenuated signal because of high moisture content and mutiple chaotic, non-parallel reflectors. The VES results show system of two to four geo-electric layers with average overburden thickness of about 7 m. The excavated pits show intercalation of clayey and loamy soil and revealed water level to be 0.8 m. The integrated geophysical approach applied has successfully identified the spatial pattern of clayey soil, overburden thickness and water level of the valley bottom soil which help retention of water during dry season.

Evaluation of surface ponding and runoff generation in a seasonally frozen drained agricultural field

Surface runoff is often poorly quantified in hydrologic studies of subsurface drained fields, as it is a relatively minor component of the water balance and difficult to measure in large fields. However, conservation practices that seek to mitigate pollutant transport through subsurface drainage may increase surface runoff, and therefore it needs to be better understood. The goal of this study was to determine the frequency and extent of occurrence of surface ponding and runoff, and to understand their generation processes in a seasonally frozen, subsurface drained agricultural field in eastern Indiana. Three different methods were used. Surface ponding was monitored with a time-lapse camera at the edge of the field for three years. A water table threshold for surface ponding was determined using photo evidence of ponding together with water table depth measurements and used to estimate ponding. The DRAINMOD hydrologic model was calibrated and validated by comparing model predictions of subsurface drainage and water table depth with 10 years of field observations and used to predict surface ponding and runoff. The simulation results indicated that surface runoff represented 1–10% of annual precipitation, while subsurface drainage represented between 26 and 45%. On average, 45% of simulated ponding occurred during the cold season (December-March) indicating the importance of soil freezing and snow accumulation. However, during parts of the cold season, DRAINMOD simulations of snow accumulation and melt were poor, resulting in drain flow under-prediction and runoff over-prediction during these periods. Water table depth measurements above the defined threshold provided a simple alternate for prediction of saturation excess ponding events in the absence of direct measurements. Results from both simulations and observations indicated that all of the ponding events in this location were generated by saturation excess rather than infiltration excess processes.

Identifying resilient Eastern Massasauga Rattlesnake (Sistrurus catenatus) peatland hummock hibernacula

At the northern limit of the Eastern Massasauga Rattlesnake’s (Sistrurus catenatus (Rafinesque, 1818)) range, individuals spend up to half the year overwintering. In hummock hibernacula found in peatlands, it is likely that subsurface temperature and water table position are contributing factors dictating habitat suitability. As a step towards assessing the vulnerability of hibernacula to anthropogenic changes, we combined subsurface temperature and water table dynamics to assess the likelihood that unflooded and unfrozen conditions were present in hummock hibernacula. Our results indicate that taller hummocks are more resilient to an advancing frost line and fluctuating water table by providing a larger area and duration of unfrozen and unflooded conditions, and a critical overwintering depth that is farther from the hummock surface. In two study sites along eastern Georgian Bay, an unflooded and unfrozen zone was present for over 90% of the overwintering period for hummocks taller than 25–27 cm. Our findings highlight the vulnerability of peatland hummocks to variability of winter weather where deep freezing and (or) water table rise may nonlinearly reduce resilience. This suggests that height is not the only component affecting the suitability of hummock hibernacula and that further research should examine the structure and spatial arrangement of hummocks within a peatland.

Mathematical Modelling of Arctic Polygonal Tundra with Ecosys: 1. Microtopography Determines How Active Layer Depths Respond to Changes in Temperature and Precipitation

AbstractMicrotopographic variation that develops among features (troughs, rims, and centers) within polygonal landforms of coastal arctic tundra strongly affects movement of surface water and snow and thereby affects soil water contents (θ) and active layer depth (ALD). Spatial variation in ALD among these features may exceed interannual variation in ALD caused by changes in climate and so needs to be represented in projections of changes in arctic ALD. In this study, increases in near‐surface θ with decreasing surface elevation among polygon features at the Barrow Experimental Observatory (BEO) were modeled from topographic effects on redistribution of surface water and snow and from lateral water exchange with a subsurface water table during a model run from 1981 to 2015. These increases in θ caused increases in thermal conductivity that in turn caused increases in soil heat fluxes and hence in ALD of up to 15 cm with lower versus higher surface elevation which were consistent with increases measured at BEO. The modeled effects of θ caused interannual variation in maximum ALD that compared well with measurements from 1985 to 2015 at the Barrow Circumpolar Active Layer Monitoring (CALM) site (R2 = 0.61, RMSE = 0.03 m). For higher polygon features, interannual variation in ALD was more closely associated with annual precipitation than mean annual temperature, indicating that soil wetting from increases in precipitation may hasten permafrost degradation beyond that caused by soil warming from increases in air temperature. This degradation may be more rapid if increases in precipitation cause sustained wetting in higher features.

Ground-penetrating radar (GPR) responses for sub-surface salt contamination and solid waste: modeling and controlled lysimeter studies.

The assessment of polluted areas and municipal solid waste (MSW) sites using non-destructive geophysical methods is timely and much needed in the field of environmental monitoring and management. The objectives of this study are (i) to evaluate the ground-penetrating radar (GPR) wave responses as a result of different electrical conductivity (EC) in groundwater and (ii) to conduct MSW stratification using a controlled lysimeter and modeling approach. A GPR wave simulation was carried out using GprMax2D software, and the field test was done on two lysimeters that were filled with sand (Lysimeter-1) and MSW (Lysimeter-2). A Pulse EKKO-Pro GPR system with 200- and 500-MHz center frequency antennae was used to collect GPR field data. Amplitudes of GPR-reflected waves (sub-surface reflectors and water table) were studied under different EC levels injected to the water table. Modeling results revealed that the signal strength of the reflected wave decreases with increasing EC levels and the disappearance of the subsurface reflection and wave amplitude reaching zero at higher EC levels (when EC >0.28S/m). Further, when the EC level was high, the plume thickness did not have a significant effect on the amplitude of the reflected wave. However, it was also found that reflected signal strength decreases with increasing plume thickness at a given EC level. 2D GPR profile images under wet conditions showed stratification of the waste layers and relative thickness, but it was difficult to resolve the waste layers under dry conditions. These results show that the GPR as a non-destructive method with a relatively larger sample volume can be used to identify highly polluted areas with inorganic contaminants in groundwater and waste stratification. The current methods of MSW dumpsite investigation are tedious, destructive, time consuming, costly, and provide only point-scale measurements. However, further research is needed to verify the results under heterogeneous aquifer conditions and complex dumpsite conditions.

Identifying scale‐emergent, nonlinear, asynchronous processes of wetland methane exchange

AbstractMethane (CH4) exchange in wetlands is complex, involving nonlinear asynchronous processes across diverse time scales. These processes and time scales are poorly characterized at the whole‐ecosystem level, yet are crucial for accurate representation of CH4 exchange in process models. We used a combination of wavelet analysis and information theory to analyze interactions between whole‐ecosystem CH4 flux and biophysical drivers in two restored wetlands of Northern California from hourly to seasonal time scales, explicitly questioning assumptions of linear, synchronous, single‐scale analysis. Although seasonal variability in CH4 exchange was dominantly and synchronously controlled by soil temperature, water table fluctuations, and plant activity were important synchronous and asynchronous controls at shorter time scales that propagated to the seasonal scale. Intermittent, subsurface water table decline promoted short‐term pulses of methane emission but ultimately decreased seasonal CH4 emission through subsequent inhibition after rewetting. Methane efflux also shared information with evapotranspiration from hourly to multiday scales and the strength and timing of hourly and diel interactions suggested the strong importance of internal gas transport in regulating short‐term emission. Traditional linear correlation analysis was generally capable of capturing the major diel and seasonal relationships, but mesoscale, asynchronous interactions and nonlinear, cross‐scale effects were unresolved yet important for a deeper understanding of methane flux dynamics. We encourage wider use of these methods to aid interpretation and modeling of long‐term continuous measurements of trace gas and energy exchange.

A diagnosis of sub-surface water table dynamics in low hydraulic conductivity soils in the sugar cane fields of Pongola, South Africa

Water and land are the two natural resources restraining crop production in South Africa. With the increasing demand for food, emphasis has shifted from the sole reliance on rain fed crop production, to irrigation. The deterioration in irrigation water quality from surface water sources is, however, posing a big challenge to the sustainability of irrigated crop production. This is because more water is required for leaching, resulting in shallow water tables in agricultural lands. The installation of well designed subsurface drainage systems alone is not enough; the provision of timely maintenance is also necessary. In this study, the extent and severity of problems as a consequence of shallow water tables and their possible causes were investigated at three sugarcane fields in Pongola, South Africa, having low hydraulic conductivity soils. Also investigated were soil salinity levels and the temporal variation in the salinity of the irrigation water. A water table map of a 32 ha sugarcane field was generated, using observed water table depth (WTD) data from 36 piezometers monitored from September 2011 to February 2012. Out of the total 32 ha under cultivation, 12% was found to be affected by shallow WTDs of less than the 1.0 m design WTD. The inability of natural drainage to cope with subsurface drainage needs and the poor maintenance of subsurface drainage systems contributed to the shallow water tables in the area. Furthermore, the currently adopted drainage design criteria also proved unsatisfactory with mean observed water table depth and drainage discharge (DD) of 20% and 50%, respectively, less than their respective design levels. The salinity of the irrigation water was, on average, 32% higher than threshold tolerance level of sugarcane. The root zone soil salinity levels at the three study sites were greater than the 1.7 dS m−1 threshold for sugar cane. The subsurface drainage design criteria adopted at the site needs to be revisited by ensuring that the slope of the land is taken into consideration in the drainage design in addition to adhering to a recommended maintenance schedule.

Evaluation of DRAINMOD for Potato Crop under Cold Conditions in the Canadian Prairies

<abstract> <b><sc>Abstract.</sc></b> Subsurface drainage is used for removing excess water in poorly drained agricultural lands. The performance of subsurface drainage systems varies depending on the soil, crop, and climatic factors. Field evaluation of drainage systems under different field conditions can be costly and time-consuming, necessitating the use of computer models for the design and the evaluation of long-term performance. DRAINMOD is a widely used model for simulating shallow groundwater hydrology in poorly or artificially drained farmlands. The objective of this study was to evaluate DRAINMOD for simulating the hydrology and potato (Solanum tuberosum) crop yield under cold climatic conditions. Data were obtained from a field study that was conducted during 2010 to 2012 in southern Manitoba in a fine sandy loam soil. DRAINMOD calibration and validation were done using data from subsurface-drained plots with drain spacing of 15 m and average drain depth of 1.06 m. Daily subsurface drainage flow, weather parameters, irrigation rate, and water table depth were measured onsite. Subsurface drainage and water table depth were the main variables that were evaluated with DRAINMOD simulations. In general, DRAINMOD predictions of subsurface drainage flow and water table depth were in good agreement with observed values on a daily basis. Statistical parameters showed that DRAINMOD predictions of daily water table depth were more accurate than model predictions of daily drainage flow. The Nash-Sutcliffe modeling efficiency values were in the range of 0.69 to 0.76 for drainage flow and 0.57 to 0.94 for water table depth. The mean absolute error was between 70 and 134 mm for water table depth predictions and between 0.42 and 0.44 mm for drainage flow predictions. The root mean square error was 0.77 to 1.14 mm for drainage flow and 83 to 147 mm for water table depth. DRAINMOD overpredicted potato yield by up to 1%. Based on the results, it is concluded that DRAINMOD predictions of the shallow groundwater hydrology under cold climate were satisfactory.

Drainage Retention Capacity (DREC) of Krisak Mountain Meadows Agricultural Area (Jizera Mountains, Czech Republic) for Mitigation of Negative Impacts of Climate Change

Installing drainage systems in saturated soils decreases the level of the subsurface water table and enables the creation of groundwater reservoirs without gravity water – i.e. drainage retention capacity (DREC). DREC, developed by the hydraulic functions of a drainage system, can be defined as a groundwater reservoir, which is limited by soil surface and which occupies an intermediate position in the water table. It is shaped in a parabola form, above the drains. DREC mitigates the negative impact of hydrological extremes, e.g. floods or rainstorms. The purpose of this paper is, to present a methodology for determining DREC on the basis of the height of the water level, in the midway between the drains; with description of the use of DREC for estimation of the rate of potential flooding of the landscape surface; and to describe the application of DREC in a drainage engineering project commissioned by the Ministry of Agriculture of the Czech Republic for water regime protection in the Krisak mountain meadow agricultural area, Jizera Mountains, Czech Republic. The results obtained from in-situ experimental testing confirmed that the equations that are presented in this paper can serve as a reliable tool for DREC approximation.

Near-surface permeability in a supraglacial drainage basin on the Llewellyn Glacier, Juneau Icefield, British Columbia

Abstract. Supraglacial channel networks link time varying melt production and meltwater routing on temperate glaciers. Such channel networks often include components of both surface transport in streams and subsurface porous flow through near-surface ice, firn or snowpack. Although subsurface transport if present will likely control network transport efficacy, it is the most poorly characterized component of the system. We present measurements of supraglacial channel spacing and network properties on the Juneau Icefield, subsurface water table height, and time variation of hydraulic characteristics including diurnal variability in water temperature. We combine these data with modeling of porous flow in weathered ice to infer near-surface permeability. Estimates are based on an observed phase lag between diurnal water temperature variations and discharge, and independently on measurement of water table surface elevation away from a stream. Both methods predict ice permeability on a 1–10 m scale in the range of 10−10–10−11 m2. These estimates are considerably smaller than common parameterizations of surface water flow on bare ice in the literature, as well as smaller than most estimates of snowpack permeability. For supraglacial environments in which porosity/permeability creation in the subsurface is balanced by porous flow of meltwater, our methods provide an estimate of microscale hydraulic properties from observations of supraglacial channel spacing.

Modeling water, carbon, and nitrogen dynamics for two drained pine plantations under intensive management practices

This paper reports results of a study to test the reliability of the DRAINMOD-FOREST model for predicting water, soil carbon (C) and nitrogen (N) dynamics in intensively managed forests. The study site, two adjacent loblolly pine ( Pinus taeda L.) plantations (referred as D2 and D3), are located in the coastal plain of North Carolina, USA. Controlled drainage (with weir and orifice) and various silvicultural practices, including nitrogen (N) fertilizer application, thinning, harvesting, bedding, and replanting, were conducted on the study site. Continuous collection of hydrological and water quality data (1988–2008) were used for model evaluation. Comparison between predicted and measured hydrologic variables showed that the model accurately predicted long-term subsurface drainage dynamics and water table fluctuations in both loblolly pine plantations. Predicted mean and standard deviation of annual drainage matched measured values very well: 431 ± 217 vs. 436 ± 231 mm for D2 site and 384 ± 152 vs. 386 ± 160 mm for D3 site. Nash–Sutcliffe coefficients (NSE) were above 0.9 for drainage predictions on annual and monthly basis and above 0.86 for predictions of daily water table fluctuations. Compared to measurements in other similar studies, the model also reasonably estimated long-term dynamics of organic matter pools on forest floor and in forest soil. Predicted mean and standard deviation of annual nitrate exports were comparable to measured values: 1.6 ± 1.3 vs. 1.5 ± 1.5 kg ha −1 for D2 site, and 1.4 ± 1.3 vs. 1.3 ± 1.1 kg ha −1 for D3 site, respectively. Predicted nitrate export dynamics were also in excellent agreement with field measurements as indicated by NSE above 0.90 and 0.84 on annual and monthly bases, respectively. The model, thus successfully tested, was applied to predicted hydrological and biogeochemical responses to drainage water management and silvicultural practices. Specifically, the model predicted reduced rainfall interception and ET after clear cutting, both of which led to increased water yield and elevated water table, as expected. The model also captured temporary changes in nitrogen transformations following forest harvesting, including increased mineralization, nitrification, denitrification, and decreased plant uptake. Overall, this study demonstrated that DRAINMOD-FOREST can predict water, C and N dynamics in drained pine forests under intensive management practices.

Zonation and Prediction of Land Subsidence (Case Study-Kerman, Iran)

Drought and Immethodical ground water withdrawal in recent years has caused numerous problems such as subsidence due to falling of subsurface water table, the reduction of water quality, etc. in cities across the world. This research as a case study deals with harmful effects of subsurface water withdrawal in the city of Kerman and practical monitoring of the subsidence and makes prediction of land subsidence. The artificial neural network has been used for modeling the monitored results and prediction of future subsidence. A surveying network with more than 500 installed benchmarks in an area of 334 square kilometer has been used to measure the subsidence of the city area. Benchmarks were installed in the beginning of 2004 and were monitored at the end of 2004, 2006, and 2007. For modeling, extra data were obtained from Iranian Surveying Organization for the years before 2004. The resulting model showed that, the subsidence varies between zero and 15cm per year in different parts of the City, which depends on the subsurface-layered soils, their compressibility, and the manner of subsurface water withdrawal.

Effect of soil texture, tailwater height, and pore‐water pressure on the morphodynamics of migrating headcuts in upland concentrated flows

AbstractRill and gully erosion in upland and agricultural areas can result in significant soil degradation worldwide, and headcuts are the primary mechanism by which this landscape dissection occurs. Experiments were conducted to further examine the morphodynamic behavior of actively migrating headcuts in upland concentrated flows with varying boundary conditions. The effect of soil texture greatly modified the erodibility of the select soils, and headcut migration rates, scour depths, and sediment discharges were correlated to the critical shear stress and erodibility of the select soils. The effect of increasing tailwater height greatly reduced the nappe entry angle at the brink of the headcut, completely arresting the soil erosion processes. Altering subsurface pore‐water pressures markedly changed the erodibility coefficients of the select soil, which caused greater headcut migration rates and sediment discharges, yet shallower scour holes, in the presence of a subsurface water table. Current analytic formulations based on jet impingement theory successfully predicted these experimental observations, further demonstrating the utility of such analytic formulations in advancing watershed management technology. Copyright © 2009 John Wiley &amp; Sons, Ltd.

A low‐dimensional physically based model of hydrologic control of shallow landsliding on complex hillslopes

AbstractHillslopes have complex three‐dimensional shapes that are characterized by their plan shape, profile curvature of surface and bedrock, and soil depth. To investigate the stability of complex hillslopes (with different slope curvatures and plan shapes), we combine the hillslope‐storage Boussinesq (HSB) model with the infinite slope stability method. The HSB model is based on the continuity and Darcy equations expressed in terms of storage along the hillslope. Solutions of the HSB equation account explicitly for plan shape by introducing the hillslope width function and for profile curvature through the bedrock slope angle and the hillslope soil depth function. The presented model is composed of three parts: a topography model conceptualizing three‐dimensional soil mantled landscapes, a dynamic hydrology model for shallow subsurface flow and water table depth (HSB model) and an infinite slope stability method based on the Mohr–Coulomb failure law. The resulting hillslope‐storage Boussinesq stability model (HSB‐SM) is able to simulate rain‐induced shallow landsliding on hillslopes with non‐constant bedrock slope and non‐parallel plan shape. We apply the model to nine characteristic hillslope types with three different profile curvatures (concave, straight, convex) and three different plan shapes (convergent, parallel, divergent). In the presented model, the unsaturated storage has been calculated based on the unit head gradient assumption. To relax this assumption and to investigate the effect of neglecting the variations of unsaturated storage on the assessment of slope stability in the transient case, we also combine a coupled model of saturated and unsaturated storage and the infinite slope stability method. The results show that the variations of the unsaturated zone storage do not play a critical role in hillslope stability. Therefore, it can be concluded that the presented dynamic slope stability model (HSB‐SM) can be used safely for slope stability analysis on complex hillslopes. Our results show that after a certain period of rainfall the convergent hillslopes with concave and straight profiles become unstable more quickly than others, whilst divergent convex hillslopes remain stable (even after intense rainfall). In addition, the relation between subsurface flow and hillslope stability has been investigated. Our analyses show that the minimum safety factor (FS) occurs when the rate of subsurface flow is a maximum. In fact, by increasing the subsurface flow, stability decreases for all hillslope shapes. Copyright © 2008 John Wiley &amp; Sons, Ltd.

The role of bedrock topography on subsurface storm flow

We conducted a detailed study of subsurface flow and water table response coupled with digital terrain analysis (DTA) of surface and subsurface features at the hillslope scale in Panola Mountain Research Watershed (PMRW), Georgia. Subsurface storm flow contributions of macropore and matrix flow in different sections along an artificial trench face were highly variable in terms of timing, peak flow, recession characteristics, and total flow volume. The trench flow characteristics showed linkages with the spatial tensiometer response defining water table development upslope. DTA of the ground surface did not capture the observed spatial patterns of trench flow or tensiometric response. However, bedrock surface topographic indices significantly improved the estimation of spatial variation of flow at the trench. Point‐scale tensiometric data were also more highly correlated with the bedrock surface‐based indices. These relationships were further assessed for temporal changes throughout a rainstorm. Linkages between the bedrock indices and the trench flow and spatial water table responses improved during the wetter periods of the rainstorm, when the hillslope became more hydrologically connected. Our results clearly demonstrate that in developing a conceptual framework for understanding the mechanisms of runoff generation, local bedrock topography may be highly significant at the hillslope scale in some catchments where the bedrock surface acts as a relatively impermeable boundary.

Formation of weathering rinds on andesite

AbstractTo explore the mechanisms of weathering‐rind formation, rock properties of an andesite cobble were investigated. The andesite cobble studied in this paper was taken from a fluvial terrace which formed around 290 ka BP in the Nasuno‐ga‐hara area, central Japan. The sampled cobble has a double weathering rind comprising an outer brown zone (brown band) and an inner pale grey zone (white band) with thicknesses of 3 mm and 7 mm, respectively. The boundary between the outer brown band and the inner white band is clearly defined, whereas the boundary between the white band and the grey fresh‐looking interior of the rock is not so clearly defined.Mineralogical, chemical, chromatic and mechanical properties of the cobble were investigated in the laboratory. The outer zone, the brown band, is characterized by high brittleness, high FeO+Fe2O3 content, and low contents of CaO, MgO, Na2O and K2O. The oxidation of iron accounts for the brown colour of the rind. This outer zone is considered to have experienced both oxidation and dissolution. The inner zone, the white band, is characterized by hardness reduction and the dissolution of alkali/alkaline earth metals towards the surface of the cobble. This inner band is considered to have experienced only dissolution.The formation of the weathering rinds can be explained by changes in water‐movement directions in terrace deposits. Alkali/alkaline earth metals dissolve when water is supplied to a cobble from the surrounding matrix. Subsequently, the dissolved metals move out of the cobble accompanied by outward water movement when the subsurface water table is low. The concentrations of CaO, MgO, Na2O,K2O and Al2O3, therefore, decrease in both weathering bands, but iron tends to remain as ferric hydroxides in the outer brown band. Processes of dissolution and oxidation have produced the brown band. Copyright © 2001 John Wiley &amp; Sons, Ltd.