The role of eddies in solute transport and recovery in rock fractures: Implication for groundwater remediation

A better understanding of solute transport and retention mechanism in rock fractures has been challenging due to difficulty in their direct observations in microscale rough‐walled fractures. Six representative troughs in a rough‐walled fracture were selected for microscale observations of eddy formation with increasing flow velocity and its effect on spatiotemporal changes of solute concentration. This experimental study was enabled by a microscale visualization technique of micro particle image velocimetry. With increasing flow velocity (Re ≤ 2.86), no eddies were generated, and solutes along the main streamlines transported rapidly, whereas those near the wall moved slowly. A larger amount of solutes remained trapped at all troughs at Re = 2.86 than Re < 1. For Re = 8.57, weak eddies started to be developed at the troughs on the lee side, which little contributed to overall solute flushing in the fracture. Accordingly, a large of amount of water was needed for solute flushing. The flow condition of 1 < Re < 10, before a full development of eddies, was least favourable in terms of time and amount of remediation fluid required to reach a target concentration. After large eddies were fully developed at troughs on the lee side for Re = 17.13, solutes were substantially reduced by eddies with less amount of water. Fully developed eddies were found to enhance solute transport and recovery, as opposed to a general consensus that eddies trap and delay solutes. Direct inflow into troughs on the stoss side also made a great contribution to solute flushing out of the troughs. This study indicates that fully developed eddies or strong inflows at troughs are highly possible to form for Re > 10 and this flow range could be favourable for efficient remediation.     

Spatial–temporal variability and hydrologic connectivity of runoff generation areas in a North Alabama pasture—implications for phosphorus transport

This study delineated spatially and temporally variable runoff generation areas in the Sand Mountain region pasture of North Alabama under natural rainfall conditions, and demonstrated that hydrologic connectivity is important for generating hillslope response when infiltration‐excess (IE) runoff mechanism dominates. Data from six rainfall events (13·7–32·3 mm) on an intensively instrumented pasture hillslope (0·12 ha) were analysed. Analysis of data from surface runoff sensors, tipping bucket rain gauge and HS‐flume demonstrated spatial and temporal variability in runoff generation areas. Results showed that the maximum runoff generation area, which contributed to runoff at the outlet of the hillslope, varied between 67 and 100%. Furthermore, because IE was the main runoff generation mechanism on the hillslope, the data showed that as the rainfall intensity changed during a rainfall event, the runoff generation areas expanded or contracted. During rainfall events with high‐intensity short‐ to medium‐duration, 4–8% of total rainfall was converted to runoff at the outlet. Rainfall events with medium‐ to low‐intensity, medium‐duration were found less likely to generate runoff at the outlet. In situ soil hydraulic conductivity (k) was measured across the hillslope, which confirmed its effect on hydrologic connectivity of runoff generation areas. Combined surface runoff sensor and k‐interpolated data clearly showed that during a rainfall event, lower k areas generate runoff first, and then, depending on rainfall intensity, runoff at the outlet is generated by hydrologically connected areas. It was concluded that in IE‐runoff‐dominated areas, rainfall intensity and k can explain hydrologic response. The study demonstrated that only connected areas of low k values generate surface runoff during high‐intensity rainfall events. Identification of these areas would serve as an important foundation for controlling nonpoint source pollutant transport, especially phosphorus. The best management practices can be developed and implemented to reduce transport of phosphorus from these hydrologically connected areas. Copyright © 2009 John Wiley & Sons, Ltd.     

Hydrocarbons and other volatile components in alkaline rocks from the Ukrainian shield and Kola Peninsula

Gas chromatography and other analytical techniques (EMR, PMR, and IR spectroscopy) were used to examine volatile components (CH₄, C₂-C₃, CO₂, CO, H₂, H₂O, and others) in alkaline rocks and minerals from the Ukrainian Shield (eight massifs and dikes of grorudites) and from the Khibina and Lovozero massifs in the Baltic Shield. The alkaline rocks from the Ukrainian Shield are mostly of Proterozoic (1.7–2.1 Ga) age. The alkaline rocks from the Kola Peninsula were confirmed to be rich in methane (21 ± 14 μl/g on average) and other hydrocarbons, whereas the analogous rocks from the Ukrainian Shield are poor in methane (2.1 ± 1.6 μl/g on average at a maximum of 14 μl/g). The latter rocks are richer in CO₂, which is one of the major volatile components of alkaline rocks, including agpaitic nepheline syenites from the Kola Peninsula. The rocks from the Ukrainian Shield often have elevated contents of nitrogen (up to 20 μl/g). The reasons for the differences in the composition of volatile components of rocks from the Kola Peninsula and Ukrainian Shield are as follows: the agpaitic crystallization trends of large massifs in the Kola Peninsula and much less clearly pronounced agpaitic trends in the small massifs in the Ukrainian Shield, the affiliation of these rocks with different complexes, the deeper erosion levels of the Ukrainian alkaline massifs, different ages of these rocks, etc.     

Neuro‐control of seismically excited steel structure through sensitivity evaluation scheme

The neuro‐controller training algorithm based on cost function is applied to a multi‐degree‐of‐freedom system; and a sensitivity evaluation algorithm replacing the emulator neural network is proposed. In conventional methods, the emulator neural network is used to evaluate the sensitivity of structural response to the control signal. To use the emulator, it should be trained to predict the dynamic response of the structure. Much of the time is usually spent on training of the emulator. In the proposed algorithm, however, it takes only one sampling time to obtain the sensitivity. Therefore, training time for the emulator is eliminated. As a result, only one neural network is used for the neuro‐control system. In the numerical example, the three‐storey building structure with linear and non‐linear stiffness is controlled by the trained neural network. The actuator dynamics and control time delay are considered in the simulation. Numerical examples show that the proposed control algorithm is valid in structural control. Copyright © 2001 John Wiley & Sons, Ltd.     

Improvement of spatial interpolation accuracy of daily maximum air temperature in urban areas using a stacking ensemble technique

ABSTRACT

The reliable and robust monitoring of air temperature distribution is essential for urban thermal environmental analysis. In this study, a stacking ensemble model consisting of multi-linear regression (MLR), support vector regression (SVR), and random forest (RF) optimized by the SVR is proposed to interpolate the daily maximum air temperature (T_max) during summertime in a mega urban area. A total of 10 geographic variables, including the clear-sky averaged land surface temperature and the normalized difference vegetation index, were used as input variables. The stacking model was compared to Cokriging, three individual data-driven methods, and a simple average ensemble model, all through leave-one-station-out cross validation. The stacking model showed the best performance by improving the generalizability of the individual models and mitigating the sensitivity to the extreme daily T_max. This study demonstrates that the stacking ensemble method can improve the accuracy of spatial interpolation of environmental variables in various research fields.     

Horizontal and vertical distribution of PCBs and chlorinated pesticides in sediments from Masan Bay,Korea

Horizontal and vertical distributions of organochlorine compounds (OCs) were determined in sediments from Masan Bay. The concentrations of polychlorinated biphenyls (PCBs), dichlorodiphenyltrichloroethanes (DDTs), HCB, hexachlorocyclohexanes (HCHs) and chlordane related compounds (CHLs) in sediments were in the range of 1.24-41.4, 0.28-89.2, 0.02-0.59, nd-1.03, and nd-2.56 ng/g, respectively. The spatial distribution of OCs showed a negative gradient from the inner of the bay to outer part of the bay, indicating that the source of OCs was probably located inside the bay. Compositional pattern of PCB congeners showed a relatively high concentration of high-chlorinated congeners in the inner part of the bay and a relatively low concentration of low-chlorinated congeners in the outer part. In sediment core from Masan Bay maximum concentrations of PCBs and DDTs are observed in the subsurface samples and correspond to an age of early 1980s and late 1960s. The concentration profiles of PCBs and DDTs in sediments of Masan Bay appear to correspond to use of PCBs and DDTs in Korea.     

Assessment of drought vulnerability based on the soil moisture PDF

This paper studies the statistics of the soil moisture condition and its monthly variation for the purpose of evaluating drought vulnerability. A zero-dimensional soil moisture dynamics model with the rainfall forcing by the rectangular pulses Poisson process model are used to simulate the soil moisture time series for three sites in Korea: Seoul, Daegu, and Jeonju. These sites are located in the central, south-eastern, and south-western parts of the Korean Peninsular, respectively. The model parameters are estimated on a monthly basis using hourly rainfall data and monthly potential evaporation rates obtained by the Penmann method. The resulting soil moisture simulations are summarized on a monthly basis. In brief, the conclusions of our study are as follows. (1) Strong seasonality is observed in the simulations of soil moisture. The soil moisture mean is less than 0.5 during the dry spring season (March, April, and June), but other months exceed the 0.5 value. (2) The spring season is characterized by a low mean value, a high standard deviation and a positive skewness of the soil moisture content. On the other hand, the wet season is characterized by a high mean value, low standard deviation, and negative skewness of the soil moisture content. Thus, in the spring season, much drier soil moisture conditions are apparent due to the higher variability and positive skewness of the soil moisture probability density function (PDF), which also indicates more vulnerability to severe drought occurrence. (3) Seoul, Daegue, and Jeonju show very similar overall trends of soil moisture variation; however, Daegue shows the least soil moisture contents all through the year, which implies that the south-eastern part of the Korean Peninsula is most vulnerable to drought. On the other hand, the central part and the south-western part of the Korean peninsula are found to be less vulnerable to the risk of drought. The conclusions of the study are in agreement with the climatology of the Korean Peninsula.     

Climate Warming and Water Management Adaptation for California

The ability of California's water supply system to adapt to long-term climatic and demographic changes is examined. Two climate warming and a historical climate scenario are examined with population and land use estimates for the year 2100 using a statewide economic-engineering optimization model of water supply management. Methodologically, the results of this analysis indicate that for long-term climate change studies of complex systems, there is considerable value in including other major changes expected during a long-term time-frame (such as population changes), allowing the system to adapt to changes in conditions (a common feature of human societies), and representing the system in sufficient hydrologic and operational detail and breadth to allow significant adaptation. While the policy results of this study are preliminary, they point to a considerable engineering and economic ability of complex, diverse, and inter-tied systems to adapt to significant changes in climate and population. More specifically, California's water supply system appears physically capable of adapting to significant changes in climate and population, albeit at a significant cost. Such adaptation would entail large changes in the operation of California's large groundwater storage capacity, significant transfers of water among water users, and some adoption of new technologies.     

Irrigated area determination: a case study in the Province of San Juan,Argentina

Much of the central-western region of Argentina, where San Juan Province is located, experiences arid to semi-arid climatic conditions with low average annual rainfall accompanied by substantial evapotranspiration. Consequently, a viable crop industry depends to a large extent upon irrigation from major river systems. Increasing demand for water in the lower basin of the San Juan River is emphasizing the need for more accurate estimates of water used for irrigation. Since the water demand for a particular crop is very closely related to crop area, monitoring the area of crop under irrigation is considered a proxy for the amount of water used. Landsat 5 imagery for the growing season, field data and aerial photographs were used to evaluate crop area.     

Importance of no‐rain measurements on the comparison of radar and rain gauge rain rate

This study evaluated four possible cases of comparing radar and rain gauge rain rate for the detection of mean‐field bias. These four cases, or detection designs, consider in this study are: (1) design 1‐uses all the data sets available, including zero radar rain rate and zero rain gauge rain rate, (2) design 2—uses the data sets of positive radar rain rate and zero or positive rain gauge rain rate, (3) design 3—uses the data sets of zero or positive radar rain rate and positive rain gauge rain rate and (4) design 4—uses the data sets of positive radar rain rate and positive rain gauge rain rate. A theoretical review of these four detection designs showed that only the design 1 causes no design bias, but designs 2, 3 and 4 can cause positive, negative and negative design biases, respectively. This theoretical result was also verified by applying these four designs to the rain rate field generated by a multi‐dimensional rain rate model, as well as to that of the Mt Gwanak radar in Korea. The results from both applications showed that especially the design 4, which is generally used for the detection of mean‐field bias of radar rain rate, causes a serious design bias; therefore, is inappropriate as a design for detecting the mean‐field bias of radar rain rate. Copyright © 2009 John Wiley & Sons, Ltd.