Shesh R. Koirala

Temporal Variation and Persistence of Bacteria in Streams

Better understanding of bacterial fate and transport in watersheds is necessary for improved regulatory management of impaired streams. Novel statistical time series analyses of coliform data can be a useful tool for evaluating the dynamics of temporal variation and persistence of bacteria within a watershed. For this study, daily total coliform data for the Little River in East Tennessee from 1 Oct. 2000 to 31 Dec. 2005 were evaluated using novel time series techniques. The objective of this study was to analyze the total coliform concentration data to: (i) evaluate the temporal variation of the total coliform, and (ii) determine whether the total coliform concentration data demonstrated any long-term or short-term persistence. For robust analysis and comparison, both time domain and frequency domain approaches were used for the analysis. In the time domain, an autoregressive moving average approach was used; whereas in the frequency domain, spectral analysis was applied. As expected, the analyses showed that total coliform concentrations were higher in summer months and lower in winter months. However, the more interesting results showed that the total coliform concentration exhibited short-term as well as long-term persistence ranging from about 4 wk to approximately 1 yr, respectively. Comparison of the total coliform data to hydrologic data indicated both runoff and baseflow are responsible for the persistence.

Effective saturated hydraulic conductivity of two‐dimensional random multifractal fields

0.991, p < 0.0001). Thisrelationship indicates that hKidecreases with increasing long-range spatial correlation among the K values in the field. Furthermore, as hKi decreases it becomes increasingly dominated by flow channeling. This is because high values of K become more and more clustered as p decreases. This approach may prove useful for the prediction of hKi from generalized dimensions estimated by multifractal analysis of field measurements of K. The results may also be applicable to the design of sampling strategies for multiple small-scale slug tests at a given resolution. Citation: Koirala, S. R., E. Perfect, R. W. Gentry, and J. W. Kim (2008), Effective saturated hydraulic conductivity of two-dimensional random multifractal fields, Water Resour. Res., 44, W08410, doi:10.1029/2007WR006199.

Hurst Analysis of Hydrologic and Water Quality Time Series

A continued important area of research in hydrologic modeling is the issue of spatial and temporal scaling of biogeochemical properties and processes. Hurst analysis, which is a fractal-based scale invariant approach for analyzing long-term time series data, can provide insight into this issue as a quantitative approach for evaluating temporal scale in time series. The objectives of this paper were to compute the Hurst coefficient (H) for hydrologic and water quality variables, to study the effects of seasonality on H, and to determine how the H for the water quality indicators are related to that of the hydrologic parameters (e.g., discharge and rainfall). Two sites were investigated, Little River and Walker Branch, both located in east Tennessee. The water quality indicators include total coliform for Little River data and nitrate, chloride, sulfate, and calcium concentrations for Walker Branch data. H was estimated using spectral analysis. It was found that H for water quality indicators were significa...

Hurst Analysis of Hydrologic and Water Quality Signals

An important area of research in hydrologic modeling is the issue of scaling of certain deterministic properties at various spatial and temporal scales. Hurst analysis, which is a fractal based scale invariant approach for analyzing long-term time series data, may be a solution for the scaling issues in physical processes. The objectives of this paper were, to compute Hurst coefficient (H) for hydrologic and water quality indicators, to study the effect of seasonality on H and to determine how H of each of these indicators is related to that of hydrologic variables (discharge and rainfall). The water quality indicators include nitrate, chloride, sulfate and calcium concentrations for Walker Branch data. H was estimated using spectral analysis. It was found that both data series (untransformed and deseasonalized) are useful to study the watershed response for water quality indicators. The comparison of untransformed and deseasonalized data series appears to show that higher H values of these data series are due to seasonal processes and that once the seasonality is removed in the data (deseasonalized), the series appears to shift toward random (H values near 0.5).

Using Hydrologic Tracers as a Risk Assessment Tool in a Karstic Watershed

Watershed studies using a variety of observational parameters are being implemented to assess how pathogen indicators migrate through rural watersheds. The objectives of the research are to examine the presence and persistence of Bacteriodes and E. coli in several east Tennessee watersheds through observations made in the main channel. Evaluation of combined surface water and groundwater inputs should be evaluated when considering possible regulatory actions through establishment of total maximum daily loads. Further, correlations between hydrologic parameters, water quality, Bacteriodes, and E. coli. are being evaluated in order to examine watershed processes in the system and determine their behavioral response to watershed practices and hydrologic stresses. The experimental design includes a preliminary synoptic evaluation of the water chemistry and bacteria during baseflow conditions through repeated measurements. Streams are known to gain and lose flow throughout the watershed, with certain areas being in proximity to karst features. Definitive causation of bacteria at baseflow is speculative at this point. Sinkhole topography is hypothesized to play an important role in the occurrence of bacteria in the channel which may provide rapid hydrologic transport to and from the channel on a seasonal basis, although direct observation from sinkholes and springs have not been made at this point in the study. The study will provide a robust dataset for evaluating landuse input functions for hydrologic inputs to the watershed.