John S. Selker

Fingered Flow in Two Dimensions 2. Predicting Finger Moisture Profile

An exact integral solution for the moisture profile in growing fingers in sandy soil is derived from Richards equation. The solution provides moisture content along a finger as a function of position and time and provides applicable results, including the calculation of the asymptotic mattic potential of a growing finger and a method of obtaining the unsaturated conductivity in a single experiment. The solution is verified experimentally through comparison with measurements of matric potential and moisture content using high-speed tensiometers.

Fingered Flow in Two Dimensions 1. Measurement of Matric Potential

Precise management of the changing matric potential during infiltration into unsaturated soil required the development of miniature, high-speed, planar tensiometers. A novel design was developed, with response time of less than 1 s. The applicability of the devices is shown through measurements of the matric potential in growing instabilities, both in the induction zone and along the vertical finger profile. Tensiometry is demonstrated to be a practical method of obtaining data with high temporal and spatial resolution for the study of dynamic flow fields and facilitates testing of theoretical results for unstable flow fields.

A simple accurate method to predict time of ponding under variable intensity rainfall

[1] The prediction of the time to ponding following commencement of rainfall is fundamental to hydrologic prediction of flood, erosion, and infiltration. Most of the studies to date have focused on prediction of ponding resulting from simple rainfall patterns. This approach was suitable to rainfall reported as average values over intervals of up to a day but does not take advantage of knowledge of the complex patterns of actual rainfall now commonly recorded electronically. A straightforward approach to include the instantaneous rainfall record in the prediction of ponding time and excess rainfall using only the infiltration capacity curve is presented. This method is tested against a numerical solution of the Richards equation on the basis of an actual rainfall record. The predicted time to ponding showed mean error � 7% for a broad range of soils, with and without surface sealing. In contrast, the standard predictions had average errors of 87%, and worst-case errors exceeding a factor of 10. In addition to errors intrinsic in the modeling framework itself, errors that arise from averaging actual rainfall records over reporting intervals were evaluated. Averaging actual rainfall records observed in Israel over periods of as little as 5 min significantly reduced predicted runoff (75% for the sealed sandy loam and 46% for the silty clay loam), while hourly averaging gave complete lack of prediction of ponding in some of the cases.

Tree rainfall interception measured by stem compression

A method for measuring whole-tree interception of precipitation is presented which employs mechanical displacement sensors to measure trunk compression caused by the water captured by the tree. This direct and nondestructive method is demonstrated to be sensitive to less than 5 kg of interception field tests in Netherlands and Ghana.

Distributed temperature sensing as a down-hole tool in hydrogeology

Distributed Temperature Sensing (DTS) technology enables down-hole temperature monitoring to study hydrogeological processes at unprecedentedly high frequency and spatial resolution. DTS has been widely applied in passive mode in site investigations of groundwater flow, in-well flow, and subsurface thermal property estimation. However, recent years have seen the further development of the use of DTS in an active mode (A-DTS) for which heat sources are deployed. A suite of recent studies using A-DTS down-hole in hydrogeological investigations illustrate the wide range of different approaches and creativity in designing methodologies. The purpose of this review is to outline and discuss the various applications and limitations of DTS in down-hole investigations for hydrogeological conditions and aquifer geological properties. To this end, we first review examples where passive DTS has been used to study hydrogeology via down-hole applications. Secondly, we discuss and categorize current A-DTS borehole methods into three types. These are thermal advection tests, hybrid cable flow logging, and heat pulse tests. We explore the various options with regards to cable installation, heating approach, duration, and spatial extent in order to improve their applicability in a range of settings. These determine the extent to which each method is sensitive to thermal properties, vertical in well flow, or natural gradient flow. Our review confirms that the application of DTS has significant advantages over discrete point temperature measurements, particularly in deep wells, and highlights the potential for further method developments in conjunction with other emerging fiber optic based sensors such as Distributed Acoustic Sensing. This article is protected by copyright. All rights reserved.

Heat Transfer in the Environment: Development and Use of Fiber-Optic Distributed Temperature Sensing

In the environment, heat transfer mechanisms are combined in a variety of complex ways. Solar radiation warms the atmosphere, the oceans, and the earth’s surface, driving weather and climate (Lean & Rind, 1998). Clouds and aerosols reflect a fraction of the incoming solar radiation and partially absorb the infrared radiation that comes from the earth’s surface, allowing the existence of acceptable temperatures for the biota and human survival (Norand, 1920; Moya-Larano, 2010). In water bodies, absorption and scattering of solar radiation results in stratification of the water column (Branco & Torgersen, 2009). Cooling conditions, e.g., convective night-time cooling, at the water surface can destroy the stratification and thus, mix the water column (Henderson-Sellers, 1984). In open water bodies solar radiation also induces evaporation: as water changes its phase, heat is transferred from the water body into the atmosphere by the release of latent heat (Brutsaert, 1982). Within the earth, temperature increases with depth. The temperature at the earth’s center is estimated to be on the order of 6000 °C (Alfe et al., 2002). An average geothermal gradient of 25-30 °C km-1 (Fridleifsson et al., 2008) indicates that approximately 40 TW (4 × 1013 W) flow from the earth’s interior to its surface (Sclater et al., 1981). Much of this heat is the result of radioactive decay of potassium, uranium, and thorium (Lee et al., 2009). In the shallow subsurface, this geothermal gradient can be disturbed by groundwater flow and atmospheric conditions (Uchida et al., 2003; Bense & Kooi, 2004). By measuring the temperature in the environment, it is possible to elucidate the main heat transfer mechanisms controlling different environmental, ecological, geological or engineering processes. Many of these processes span spatial scales from millimeters to kilometers. This extreme range of spatial scaling has been a barrier limiting observation, description, and modeling of these processes. In the past, temperature measurements have been performed at small scales (spanning millimeters, centimeters, or a few meters) or at large scales (spanning tens of meters or kilometers (Alpers et al., 2004)). However, for spatial scales between these two disparate scales and in a variety of media, there is a lack of

Flume testing of underwater seep detection using temperature sensing on or just below the surface of sand or gravel sediments

Temperature anomalies can identify locations of seeps of groundwater into surface waters. However, the methods sensitivity to details such as thermometer burial depth, sediment material, seep velocity, and surface water current are largely unknown. We report on a series of laboratory flume experiments in which controlled seeps under variable sediment texture, surface currents, burial depth, and temperature differentials were imposed. The focus of the study is temperature effects at the sediment surface to a few centimeters below the sediment surface, as these locations are of particular interest when using fiber-optic distributed temperature sensors (DTS). The data demonstrate: (1) without surface water flow, seep-related thermal anomalies were apparent in all cases, i.e., the method is feasible in such cases; (2) probe burial is helpful for fine sediment although not effective with coarse bed sediment, i.e., the method is strongly sensitive to sediment properties; (3) placing a thin rubber sheet over an unburied thermal probe increases detection of seeps in some circumstances, but not in others, and is generally not as robust as probe burial; and (4) local surface flow velocity, details of probe position and depth, and seepage velocity all influence observed temperature anomalies, limiting the opportunity to quantify seepage velocity, particularly with unburied temperature sensors. Overall, these findings suggest optimal installation would be at a well-defined depth within fine sediment, that installation in gravel and coarser sediment is not suited to the method if there are any significant surface currents, and that more data would be required to obtain accurate estimates of seepage velocity, though a single sensor may be sufficient to identify the location of seepage.

Tension infiltrometer enhancements with automated pneumatic control and more durable base plate

[1]xa0Measurement of soil hydraulic retention and conduction parameters using tension infiltrometers has been found to be useful but has suffered from unreliable instrument membranes at the soil interface and the need for manual control, which limits the range of boundary conditions that can feasibly be established. An automated design is presented that is capable of maintaining time-varying pressure and flux using high-speed computer-regulated pneumatic valves. Further, a durable stainless steel supply membrane designed to withstand multiple uses under harsh field conditions with bubbling pressure head <−0.60 m H2O is demonstrated.