John S. Selker

Bio: John S. Selker is an academic researcher from Oregon State University. The author has contributed to research in topics: Soil water & Water content. The author has an hindex of 51, co-authored 268 publications receiving 9916 citations. Previous affiliations of John S. Selker include University of Nevada, Reno & Ben-Gurion University of the Negev.

Soil Moisture Measurement for Ecological and Hydrological Watershed-Scale Observatories: A Review

Abstract: At the watershed scale, soil moisture is the major control for rainfall–runoff response, especially where saturation excess runoff processes dominate. From the ecological point of view, the pools of soil moisture are fundamental ecosystem resources providing the transpirable water for plants. In drylands particularly, soil moisture is one of the major controls on the structure, function, and diversity in ecosystems. In terms of the global hydrological cycle, the overall quantity of soil moisture is small, ∼0.05%; however, its importance to the global energy balance and the distribution of precipitation far outweighs its physical amount. In soils it governs microbial activity that affects important biogeochemical processes such as nitrification and CO2 production via respiration. During the past 20 years, technology has advanced considerably, with the development of different electrical sensors for determining soil moisture at a point. However, modeling of watersheds requires areal averages. As a result, point measurements and modeling grid cell data requirements are generally incommensurate. We review advances in sensor technology, particularly emerging geophysical methods and distributed sensors, aimed at bridging this gap. We consider some of the data analysis methods for upscaling from a point to give an areal average. Finally, we conclude by offering a vision for future research, listing many of the current scientific and technical challenges.

Moving beyond heterogeneity and process complexity: A new vision for watershed hydrology

Abstract: Field studies in watershed hydrology continue to characterize and catalogue the enormous heterogeneity and complexity of rainfall runoff processes in more and more watersheds, in different hydroclimatic regimes, and at different scales. Nevertheless, the ability to generalize these findings to ungauged regions remains out of reach. In spite of their apparent physical basis and complexity, the current generation of detailed models is process weak. Their representations of the internal states and process dynamics are still at odds with many experimental findings. In order to make continued progress in watershed hydrology and to bring greater coherence to the science, we need to move beyond the status quo of having to explicitly characterize or prescribe landscape heterogeneity in our (highly calibrated) models and in this way reproduce process complexity and instead explore the set of organizing principles that might underlie the heterogeneity and complexity. This commentary addresses a number of related new avenues for research in watershed science, including the use of comparative analysis, classification, optimality principles, and network theory, all with the intent of defining, understanding, and predicting watershed function and enunciating important watershed functional traits.

Distributed fiber-optic temperature sensing for hydrologic systems

Abstract: Instruments for distributed fiber-optic measurement of temperature are now available with temperature resolution of 0.01°C and spatial resolution of 1 m with temporal resolution of fractions of a minute along standard fiber-optic cables used for communication with lengths of up to 30,000 m. We discuss the spectrum of fiber-optic tools that may be employed to make these measurements, illuminating the potential and limitations of these methods in hydrologic science. There are trade-offs between precision in temperature, temporal resolution, and spatial resolution, following the square root of the number of measurements made; thus brief, short measurements are less precise than measurements taken over longer spans in time and space. Five illustrative applications demonstrate configurations where the distributed temperature sensing (DTS) approach could be used: (1) lake bottom temperatures using existing communication cables, (2) temperature profile with depth in a 1400 m deep decommissioned mine shaft, (3) air-snow interface temperature profile above a snow-covered glacier, (4) air-water interfacial temperature in a lake, and (5) temperature distribution along a first-order stream. In examples 3 and 4 it is shown that by winding the fiber around a cylinder, vertical spatial resolution of millimeters can be achieved. These tools may be of exceptional utility in observing a broad range of hydrologic processes, including evaporation, infiltration, limnology, and the local and overall energy budget spanning scales from 0.003 to 30,000 m. This range of scales corresponds well with many of the areas of greatest opportunity for discovery in hydrologic science.

Environmental temperature sensing using Raman spectra DTS fiber-optic methods

Abstract: [1] Raman spectra distributed temperature sensing (DTS) by fiber-optic cables has recently shown considerable promise for the measuring and monitoring of surface and near-surface hydrologic processes such as groundwater–surface water interaction, borehole circulation, snow hydrology, soil moisture studies, and land surface energy exchanges. DTS systems uniquely provide the opportunity to monitor water, air, and media temperatures in a variety of systems at much higher spatial and temporal frequencies than any previous measurement method. As these instruments were originally designed for fire and pipeline monitoring, their extension to the typical conditions encountered by hydrologists requires a working knowledge of the theory of operation, limitations, and system accuracies, as well as the practical aspects of designing either short- or long-term experiments in remote or challenging terrain. This work focuses on providing the hydrologic user with sufficient knowledge and specifications to allow sound decisions on the application and deployment of DTS systems.

Fiber optics opens window on stream dynamics

Abstract: A new approach to monitoring surface waters using distributed fiber optic temperature sensing is presented, allowing resolutions of temperature of 0.01°C every meter along a fiber optic cable of up to 10,000 m in length. We illustrate the potential of this approach by quantifying both stream temperature dynamics and groundwater inflows to the Maisbich, a first-order stream in Luxembourg (49°47?N, 6°02?E). The technique provides a very rich dataset, which may be of interest to many types of environmental research, notably that of stream ecosystems.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

Abstract: From the Publisher: The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

The Ensemble Kalman Filter: Theoretical formulation and practical implementation

Abstract: The purpose of this paper is to provide a comprehensive presentation and interpretation of the Ensemble Kalman Filter (EnKF) and its numerical implementation. The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it. This paper reviews the important results from these studies and also presents new ideas and alternative interpretations which further explain the success of the EnKF. In addition to providing the theoretical framework needed for using the EnKF, there is also a focus on the algorithmic formulation and optimal numerical implementation. A program listing is given for some of the key subroutines. The paper also touches upon specific issues such as the use of nonlinear measurements, in situ profiles of temperature and salinity, and data which are available with high frequency in time. An ensemble based optimal interpolation (EnOI) scheme is presented as a cost-effective approach which may serve as an alternative to the EnKF in some applications. A fairly extensive discussion is devoted to the use of time correlated model errors and the estimation of model bias.

Embracing the unknown: disentangling the complexities of the soil microbiome.

Abstract: Soil microorganisms are clearly a key component of both natural and managed ecosystems. Despite the challenges of surviving in soil, a gram of soil can contain thousands of individual microbial taxa, including viruses and members of all three domains of life. Recent advances in marker gene, genomic and metagenomic analyses have greatly expanded our ability to characterize the soil microbiome and identify the factors that shape soil microbial communities across space and time. However, although most soil microorganisms remain undescribed, we can begin to categorize soil microorganisms on the basis of their ecological strategies. This is an approach that should prove fruitful for leveraging genomic information to predict the functional attributes of individual taxa. The field is now poised to identify how we can manipulate and manage the soil microbiome to increase soil fertility, improve crop production and improve our understanding of how terrestrial ecosystems will respond to environmental change.