Stochastic Transfer Function Model and Neural Networks to Estimate Soil Moisture1

Abstract: A practical methodology is proposed to estimate the three‐dimensional variability of soil moisture based on a stochastic transfer function model, which is an approximation of the Richard’s equation. Satellite, radar and in situ observations are the major sources of information to develop a model that represents the dynamic water content in the soil. The soil‐moisture observations were collected from 17 stations located in Puerto Rico (PR), and a sequential quadratic programming algorithm was used to estimate the parameters of the transfer function (TF) at each station. Soil texture information, terrain elevation, vegetation index, surface temperature, and accumulated rainfall for every grid cell were input into a self‐organized artificial neural network to identify similarities on terrain spatial variability and to determine the TF that best resembles the properties of a particular grid point. Soil moisture observed at 20 cm depth, soil texture, and cumulative rainfall were also used to train a feedforward artificial neural network to estimate soil moisture at 5, 10, 50, and 100 cm depth. A validation procedure was implemented to measure the horizontal and vertical estimation accuracy of soil moisture. Validation results from spatial and temporal variation of volumetric water content (vwc) showed that the proposed algorithm estimated soil moisture with a root mean squared error (RMSE) of 2.31% vwc, and the vertical profile shows a RMSE of 2.50% vwc. The algorithm estimates soil moisture in an hourly basis at 1 km spatial resolution, and up to 1 m depth, and was successfully applied under PR climate conditions.     

Evaluating Alternative Temporal Survey Designs for Monitoring Wetland Area and Detecting Changes Over Time in California

Evaluation of wetland extent and changes in extent is a foundation of many wetland monitoring and assessment programs. Probabilistic sampling and mapping provides a cost‐effective alternative to comprehensive mapping for large geographic areas. One unresolved challenge for probabilistic or design‐based approaches is how best to monitor both status (e.g., extent at a single point in time) and trends (e.g., changes in extent over time) within a single monitoring program. Existing wetland status and trends (S&T) monitoring programs employ fixed sampling locations; however, theoretical evaluation and limited implementation in other landscape monitoring areas suggest that alternative designs could increase statistical efficiency and overall accuracy. In particular, designs that employ both fixed and nonfixed sampling locations (alternately termed permanent and temporary samples), termed sampling with partial replacement (SPR), are considered to efficiently and effectively balance monitoring current status with detection of trends. This study utilized simulated sampling to assess the performance of fixed sampling locations, SPR, and strictly nonfixed designs for monitoring wetland S&T over time. Modeled changes in wetland density over time were used as inputs for sampling simulations. In contrast to previous evaluations of SPR, the results of this study support the use of a fixed sampling design and show that SPR may underestimate both S&T.     

Efficacy of Vegetated Buffers in Preventing Transport of Fecal Coliform Bacteria from Pasturelands

An experimental study was conducted in Tillamook, Oregon, USA, to quantify the effectiveness of edge-of-field vegetated buffers for reducing transport of fecal coliform bacteria (FCB) from agricultural fields amended with dairy cow manure. Installation of vegetated buffers on loamy soils dramatically reduced the bacterial contamination of runoff water from manure-treated pasturelands, but the size of the vegetated buffer was not an important determinant of bacterial removal efficiency. Only 10% of the runoff samples collected from treatment cells having vegetated buffers exhibited FCB concentrations >200 colony forming units (cfu)/100 mL (a common water quality standard value), and the median concentration for all cells containing vegetated buffers was only 6 cfu/100 mL. The presence of a vegetated buffer of any size, from 1 to 25 m, generally reduced the median FCB concentration in runoff by more than 99%. Results for FCB load calculations were similar. Our results suggest that where substantial FCB contamination of runoff occurs from manure-treated pasturelands, it might be disproportionately associated with specific field or management conditions, such as the presence of soils that exhibit low water infiltration and generate larger volumes of runoff or the absence of a vegetated buffer. Buffer size regulations that do not consider such differences might not be efficient or effective in reducing bacterial contamination of runoff.     

Uncertainty Models for Estimates of Physical Characteristics of River Segments Over Large Areas

Spatially comprehensive estimates of the physical characteristics of river segments over large areas are required in many large‐scale analyses of river systems and for the management of multiple basins. Remote sensing and modeling are often used to estimate river characteristics over large areas, but the uncertainties associated with these estimates and their dependence on the physical characteristics of the segments and their catchments are seldom quantified. Using test data with varying degrees of independence, we derived analytical models of the uncertainty associated with estimates of upstream catchment area (CA), segment slope, and mean annual discharge for all river segments of a digital representation of the hydrographic network of France. Although there were strong relationships between our test data and estimates at the scale of France, there were also large relative local uncertainties, which varied with the physical characteristics of the segments and their catchments. Discharge and CA were relatively uncertain where discharge was low and catchments were small. Discharge uncertainty also increased in catchments with large rainfall events and low minimum temperature. The uncertainty of segment slope was strongly related to segment length. Our uncertainty models were consistent across large regions of France, suggesting some degree of generality. Their analytical formulation should facilitate their use in large‐scale ecological studies and simulation models.     

The relationship between sustainable development and resource use from a geographic perspective

Geography provides the basic building blocks for the study of resource use and sustainable development, inasmuch as it categorizes the human environment. Within the environment are resources that are needed for the survival of society. As resources are largely limited and finite, humans as agents of change must employ techniques that allow an efficient and lasting use of the available resources in their environment. This paper discusses the nexus between geography, resource exploitation, use, and sustainable development. It also discusses the characteristics, types, and classification of resources, development and sustainable development as well as the challenges and strategies for attaining sustainable development, particularly in developing countries.     

Arizona Hazardous Air Pollutants Monitoring Program

ABSTRACT

In order to evaluate the existing risk to public health in Arizona related to hazardous air pollution, ambient air monitoring for selected hazardous air pollutants (HAPs) was carried out in 1994-1996 in several representative urban and rural areas of Arizona. A wide range of organic HAPs was monitored, requiring a variety of sampling and analysis methods. Stainless steel SUMMA canisters were used for collection of volatile hydrocarbons and halocarbons, which were analyzed by capillary gas chromatography with flame ionization and electron capture detection (GC-FID/ECD). Carbonyl compounds were collected using 2,4-dinitrophenylhydrazine-impregnated cartridges and analyzed by high performance liquid chromatog-raphy with ultraviolet detection. Semi-volatile and non-volatile polycyclic aromatic compounds were collected using a sampling train consisting of a filter followed by a PUF/XAD-4/PUF sandwich cartridge. Following extraction, samples were analyzed by capillary GC with mass spectrometric detection (GC-MS). Database software was developed for data processing and reporting functions. This paper describes the sampling strategy and the sampling and analysis methods employed in the monitoring program and presents a summary of all the results obtained during the duration of the sampling program.