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.     

Minimax regret optimization analysis for a regional solid waste management system

Solid waste management (SWM) facilities are crucial for environmental management and public health in urban regions. Due to the waste management hierarchy, one of the greatest challenges that organizations face today is to figure out how to diversify the treatment options, increase the reliability of infrastructure systems, and leverage the redistribution of waste streams among incineration, compost, recycling, and other facilities to their competitive advantage region wide. Systems analysis plays an important role for regionalization assessment of integrated SWM systems, leading to provide decision makers with break-through insights and risk-informed strategies. This paper aims to apply a minimax regret optimization analysis for improving SWM strategies in the Lower Rio Grande Valley (LRGV), an economically fast growing region in the US. Based on different environmental, economic, legal, and social conditions, event-based simulation in the first stage links estimated waste streams in major cities in LRGV with possible solid waste management alternatives. The optimization analysis in the second stage emphasizes the trade-offs and associated regret evaluation with respect to predetermined scenarios. Such optimization analyses with multiple criteria have featured notable successes, either by public or private efforts, in diverting recyclables, green waste, yard waste, and biosolids from the municipal solid waste streams to upcoming waste-to-energy, composting, and recycling facilities. Model outputs may link prescribed regret scenarios in decision making with various scales of regionalization policies. The insights drawn from the system-oriented, forward-looking, and preventative study can eventually help decision-makers and stakeholders gain a scientific understanding of the consequences of short-term and long-term decisions relating to sustainable SWM in the fast-growing US-Mexico borderland.     

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.     

Long-Term Relationship between Phosphorus Inputs and Wetland Phosphorus Concentrations in a Northern Everglades Marsh

Assessments of long-term relationships between changes innutrient inputs and wetland nutrient concentrations can becomplicated by fluctuations in other environmental factors aswell as by problems typical of long-term monitoring data.Consequently, statistical analysisof these types of data sets requirescareful consideration of environmental covariates, potentialbiases in the monitoring design, and irregularities caused bychanges in field sampling protocols. We evaluated therelationship between anthropogenic phosphorus (P) inputs andwater-column total P (TP) concentrations in a northernEverglades marsh by statistically analyzing available datacollected from several sampling programs over the past 20 years(1978–1997). Canal inputs of agricultural runoff contributemost of the P to the marsh and have produced a zone ofenrichment within the marsh during the past few decades.Regression analyses showed that both canal and marsh TPconcentrations increased during the 1980s and then decreased inthe 1990s. However, the statistical relationship between canal Pinputs and marsh TP, while significant, generally was weakexcept for marsh locations adjacent to the canal. Strongerrelationships existed between marsh TP and hydrologic parameterssuch as marsh water depth, which is controlled by changes inweather patterns and marsh management. In particular, dryconditions during the 1980s may have contributed to observedincreases in marsh P concentrations and the movement of a P`front' further into the marsh. Higher rainfall and water depthsand agricultural best management programs initiated during the1990s have been associated with reduced P concentrations incanal waters entering the marsh. While it is anticipated thatthis reduction eventually will result in lower marsh TPconcentrations, this effect is not yet evident, possibly due tointernal loading of P from enriched marsh soils. Our findingsillustrate some of the environmental factors that can complicateattempts to develop empirical relationships between P inputs andwetland P concentrations and to use such relationships to forecast changesin marsh concentrations based on past monitoring data alone.     

Spectral tests of randomness for spatial point patterns

We develop a spectral framework for testing the hypothesis of complete spatial randomness (CSR) for a spatial point pattern. Five formal tests based on the periodogram (sample spectrum) proposed in Mugglestone (1990) are considered. A simulation study is used to evaluate and compare the power of the tests against clustered, regular and inhomogeneous alternatives to CSR. A subset of the tests is shown to be uniformly more powerful than the others against the alternatives considered. The spectral tests are also compared with three widely used space-domain tests that are based on the mean nearest-neighbor distance, the reduced second-order moment function (K-function), and a bivariate Cramér-von Mises statistic. The test based on the scaled cumulative R-spectrum is more powerful than the space-domain tests for detecting clustered alternatives to CSR, especially when the number of events is small.     

Adverse effects in wild fish living downstream from pharmaceutical manufacture discharges

A set of biochemical and histological responses was measured in wild gudgeon collected upstream and downstream of urban and pharmaceutical manufacture effluents. These individual end-points were associated to fish assemblage characterisation. Responses of biotransformation enzymes, neurotoxicity and endocrine disruption biomarkers revealed contamination of investigated stream by a mixture of pollutants. Fish from sampled sites downstream of the industrial effluent exhibited also strong signs of endocrine disruption including vitellogenin induction, intersex and male-biased sex-ratio. These individual effects were associated to a decrease of density and a lack of sensitive fish species. This evidence supports the hypothesis that pharmaceutical compounds discharged in stream are involved in recorded endocrine disruption effects and fish population disturbances and threaten disappearance of resident fish species. Overall, this study gives argument for the utilisation of an effect-based monitoring approach to assess impacts of pharmaceutical manufacture discharges on wild fish populations.