Jan M. H. Hendrickx

Noninvasive Soil Water Content Measurement Using Electromagnetic Induction

The feasibility of soil water content measurement using electromagnetic induction was investigated in an arid region of southern New Mexico. Soil water measurements were taken monthly with a neutron probe at 65 equally spaced stations along a 1950-m transect. At the same time, noninvasive electrical conductivity measurements of the soil were taken with a Geonics EM-31 ground conductivity meter. Using 16 months of measurements, we found a linear relationship exists between bulk soil electrical conductivity and total soil water content in the top 1.5 m of the profile. A simple linear regression model was developed to describe the relationship between soil water content and bulk soil electrical conductivity. The spatial and temporal accuracy of the regression model is addressed as well as the total number of neutron access tubes needed to accurately calibrate the model. By comparison with the neutron scattering method the electromagnetic induction method is quite accurate for the prediction of water content changes over time. The speed and ease of use combined with the accuracy of the measurements make the ground conductivity meter a valuable tool for rapid, noninvasive soil water measurements.

Occurrence of soil water repellency in arid and humid climates

Abstract Soil water repellency generally tends to increase during dry weather while it decreases or completely vanishes after heavy precipitation or during extended periods with high soil water contents. These observations lead to the hypothesis that soil water repellency is common in dry climates and rare in humid climates. The study objective is to test this hypothesis by examining the occurrence of soil water repellency in an arid and humid climate. The main conclusion of this study is that the effect of climate on soil water repellency is very limited. Field observations in the arid Middle Rio Grande Basin in New Mexico (USA) and the humid Piedras Blancas Watershed in Colombia show that the main impact of climate seems to be in which manner it affects the production of organic matter. An extremely dry climate will result in low organic matter production rates and, therefore, less potential for the development of soil water repellency. On the other hand, a very humid climate is favorable for organic matter production and, therefore, for the development of water repellency.

New piecewise-continuous hydraulic functions for modeling preferential flow in an intermittent-flood-irrigated field

Modeling water flow in macroporous field soils near saturation has been a major challenge in vadose zone hydrology. Using in situ and laboratory measurements, we developed new piecewise-continuous soil water retention and hydraulic conductivity functions to describe preferential flow in tile drains under a flood-irrigated agricultural field in Las Nutrias, New Mexico. After incorporation into a two-dimensional numerical flow code, CHAIN_2D, the performance of the new piecewise-continuous hydraulic functions was compared with that of the unimodal van Genuchten-Mualem model and with measured tile-flow data at the field site during a number of irrigation events. Model parameters were collected/estimated by site characterization (e.g., soil texture, surface/ subsurface saturated/unsaturated soil hydraulic property measurements), as well as by local and regional-scale hydrologic monitoring (including the use of groundwater monitoring wells, piezometers, and different surface-irrigation and subsurface-drainage measurement systems). Comparison of numerical simulation results with the observed tile flow indicated that the new piecewise-continuous hydraulic functions generally predicted preferential flow in the tile drain reasonably well following all irrigation events at the field site. Also, the new bimodal soil water retention and hydraulic conductivity functions performed better than the unimodal van Genuchten-Mualem functions in terms of describing the observed flow regime at the field site.

Advanced Concepts on Remote Sensing of Precipitation at Multiple Scales

ADVANCED CONCEPTS ON REMOTE SENSING OF PRECIPITATION AT MULTIPLE SCALES by S oroosh S orooshian , A mir A gha K ouchak , P hillip A rkin , J ohn E ylander , E fi F oufoula -G eorgiou , R ussell H armon , J an M. H. H endrickx , B isher I mam , R obert K uligowski , B rian S kahill , and G ail S kofronick -J ackson Overview of Recommendations (i) Uncertainty of merged products and multisensor observations warrants a great deal of research. Quantification of uncertainties and their propa- gation into combined products is vital for future development. (ii) Future improvements in satellite-based precipi- tation retrieval algorithms will rely on more in- depth research on error properties in different climate regions, storm regimes, surface condi- tions, seasons, and altitudes. Given such infor- mation, precipitation algorithms for retrieval, AFFILIATIONS : S orooshian , A gha K ouchak , I mam —University of California, Irvine, Irvine, California; A rkin —University of Maryland, College Park, Maryland; E ylander —U.S. Army Engineer Research and Development Center, Hanover, New Hampshire; F oufoula -G eorgiou —University of Minnesota, Minneapolis, Minnesota; H armon —Army Research Laboratory, Durham, North Carolina; H endrickx —New Mexico Tech, Socorro, New Mexico; K uligowski —NOAA/NESDIS/ STAR, Camp Springs, Maryland; S kahill —U.S. Army Engineer Research and Development Center, Vicksburg, Mississippi; S kofronick -J ackson —NASA GSFC, Greenbelt, Maryland CORRESPONDING AUTHOR : Soroosh Sorooshian, Department of Civil & Environmental Engineering, University of California, Irvine, Irvine, CA 92697 E-mail: soroosh@uci.edu DOI:10.1175/2011BAMS3158.1 In final form 18 April 2011

Preferential transport of nitrate to a tile drain in an intermittent-flood-irrigated field: Model development and experimental evaluation

A comprehensive field experiment was conducted near Las Nutrias, New Mexico, to study field-scale flow and transport in the vadose zone. The field data were analyzed in terms of a two-dimensional numerical model based on the Richards equation for variably saturated water flow, convection-dispersion equations with first-order chemical decay chains for solute transport, and bimodal piecewise-continuous unsaturated hydraulic functions to account for preferential flow of water and nitrate-nitrogen (NO3-N; loosely used as NO3 ) following flood irrigation events at the experimental site. The model was tested against measured NO3 flux concentrations in a subsurface tile drain, several monitoring wells and nested piezometers, and against resident NO3 concentrations in the soil profile (obtained at 52 spatial locations and four depths along a transect). NO3 transport at the field site could be described better with the bimodal hydraulic functions than using the conventional approach with unimodal van Genuchten-Mualem type hydraulic functions. Average resident nitrate concentrations measured across the soil profile were predicted reasonably well. However, NO3 flux concentrations in the subsurface tile drain and piezometers at the field site were occasionally underestimated or overestimated depending upon the irrigation sequence in three field benches, probably reflecting unrepresented three-dimensional regional flow/transport processes. Limiting the capture zone to a region closer to the tile drain did lead to a better match with observed sharp increases and decreases in predicted NO3 flux concentrations during the irrigation events. On the basis of this result we inferred that the preferential flow intercepted by the tile drain was generated in close proximity of the drain and essentially oriented vertically. In summary, our study suggests that irrigation scheduling in adjacent field plots, drainage design (e.g., spacing between tiles, drain depth, drain diameter) and effectiveness (e.g., drain blockage), preferential flow in (horizontal) surface-opened shallow cracks and (vertical) macropores, and transient regional groundwater flow can add significant uncertainty to the predictions of (local-scale) flow and transport to a tile drain.

GIS-based NEXRAD Stage III precipitation database: automated approaches for data processing and visualization

This study develops a geographical information system (GIS) approach for automated processing of the Next Generation Weather Radar (NEXRAD) Stage III precipitation data. The automated processing system, implemented by using commercial GIS and a number of Perl scripts and C/C++ programs, allows for rapid data display, requires less storage capacity, and provides the analytical and data visualization tools inherent in GIS as compared to traditional methods. In this paper, we illustrate the development of automatic techniques to preprocess raw NEXRAD Stage III data, transform the data to a GIS format, select regions of interest, and retrieve statistical rainfall analysis over user-defined spatial and temporal scales. Computational expense is reduced significantly using the GIS-based automated techniques. For example, 1-year Stage III data processing (~9000 files) for the West Gulf River Forecast Center takes about 3 days of computation time instead of months of manual work. To illustrate the radar precipitation database and its visualization capabilities, we present three application examples: (1) GIS-based data visualization and integration, and ArcIMS-based web visualization and publication system, (2) a spatial-temporal analysis of monsoon rainfall patterns over the Rio Grande River Basin, and (3) the potential of GIS-based radar data for distributed watershed models. We conclude by discussing the potential applications of automated techniques for radar rainfall processing and its integration with GIS-based hydrologic information systems.

Methods for prediction of soil dielectric properties: a review

Electromagnetic sensors such as ground penetrating radar and electromagnetic induction sensors are among the most widely used methods for the detection of buried land mines and unexploded ordnance. However, the performance of these sensors depends on the dielectric properties of the soil, which in turn are related to soil properties such as texture, bulk density, and water content. To predict the performance of electromagnetic sensors it is common to estimate the soil dielectric properties using models. However, the wide variety of available models, each with its own characteristics, makes it difficult to select the appropriate one for each occasion. In this paper we present an overview of the available methods, ranging from phenomenological Cole-Cole and Debye models to volume-based dielectric mixing models, and (semi-) empirical pedotransfer functions.

New Mexico scintillometer network: supporting remote sensing and hydrologic and meteorological models.

In New Mexico, a first-of-its-kind network of seven large aperture scintillometer (LAS) sites was established in 2006 to measure sensible heat fluxes over irrigated fields, riparian areas, deserts, lava flows, and mountain highlands. Wireless networking infrastructure and auxiliary meteorological measurements facilitate real-time data assimilation. LAS measurements are advantageous in that they vastly exceed the footprint size of commonly used ground measurements of sensible and latent heat fluxes (~100 m2), matching the pixel size of satellite images or grid cells of hydrologic and meteorological models (~0.1–5 km2). Consequently, the LAS measurements can be used to validate, calibrate, and force hydrologic, remote sensing, and weather forecast models. Initial results are presented for 1) variability and error of sensible heat flux measurements by scintillometers over heterogeneous terrain and 2) the validation of the Surface Energy Balance Algorithm for Land (SEBAL) applied to Moderate Resolution Imagin...

Geologic origins of salinization in a semi-arid river: The role of sedimentary basin brines

Semi-arid and arid rivers typically exhibit increasing salinity levels downstream, a trend often attributed to irrigated agriculture, primarily due to evapotranspiration. In contrast, the results of our investigations in one salinized river suggest that geological sources of salt added by groundwater discharge are more important than agricultural effects. We performed detailed synoptic sampling of the Upper Rio Grande– Rio Bravo, an arid-climate river with signifi cant irrigated agriculture, and identifi ed a series of salinity increases localized at the distal ends of sedimentary basins. Using Cl/Br, Ca/Sr, 87 Sr/ 86 Sr, and 36 Cl/Cl ratios and δ 234 U values as environmental tracers, we show that these increases result from localized discharge of high-salinity groundwater of a sedimentary brine source. These groundwater fl uxes, while very small (<1 m 3 s –1 ), are the dominant solute input and, combined with downstream evapotranspirative concentration, result in salinization. Furthermore, 36 Cl/Cl ratios and δ 234 U values for these brines are close to secular equilibrium, indicating brine ages on the order of millions of years. The recognition of a substantial geologic salinity source for the Rio Grande implies that alternative salinity management solutions, such as interception of saline groundwater, might be more effective in reducing salinity than changes in agricultural practices.

Radar Detection of Buried Landmines in Field Soils

The contrast in the dielectric constant between a landmine and the surrounding soil is one of the most important parameters to be considered when using ground penetrating radar (GPR) for landmine detection. For most geologic materials the dielectric constant lies within a range of 3 to 30, with dry sand at the lower end of this range at about 3 to 5. Nonmetallic antitank landmines have dielectric constants within a range of about 3 to 10 depending on their composition. A model was developed to predict whether or not field conditions are appropriate for use of GPR instruments. The predictions of this model were validated using GPR profiles in field soils with different soil textures at various soil water contents. Model predictions and field measurements provide convincing evidence that increasing the soil water content around a nonmetallic landmine can improve detection in sand and silt soils. However, data for the clay soils suggest that under elevated soil water conditions detection of nonmetallic landmines are not improved; instead radar images in these soils become worse with increasing soil water content. Data suggest that detection of metallic landmines also degrades with increasing soil water content in sandy soils. The field data are in agreement with the model predictions. Our experimental and model results demonstrate the great potential and the pitfalls of landmine sensors based on GPR. Knowledge of soil texture, dry bulk density, and water content are necessary to determine or predict whether soil conditions are suitable or not for GPR mine detection. The model presented here can be useful for making this determination.