Assessing the Potential Impact of Rising Production of Industrial Wood Pellets on Streamflow in the Presence of Projected Changes in Land Use and Climate: A Case Study from the Oconee River Basin in Georgia, United States

This study examines the impact of projected land use changes in the context of growing production of industrial wood pellets coupled with expected changes in precipitation and temperature due to the changing climate on streamflow in a watershed located in the northeastern corner of the Oconee River Basin. We used the Soil and Water Assessment Tool (SWAT) for ascertaining any changes in streamflow over time. The developed model was calibrated over a seven-year period (2001–2007) and validated over another seven-year period (2008–2014). Any changes in streamflow were simulated for a combination of 10 land use and climate change cases, from 2015 to 2028, under the two scenarios of High and Low Demand for industrial wood pellets. Our results suggest that streamflow is relatively stable (<1% change) for land use and temperature-related cases relative to the base case of no change in land use and climate. However, changes in precipitation by ±10% lead to considerable changes (±25%) in streamflow relative to the base case. Based on our results, expected changes in precipitation due to the changing climate will determine any changes in the streamflow, rather than projected land use changes in the context of rising demand for industrial wood pellets for export purposes in the selected watershed, keeping land under urban areas as constant. This study contributes to our broader understanding of the sustainability of the transatlantic industrial wood pellet trade; however, we suggest undertaking similar research at a larger spatial scale over a longer time horizon for understanding trade-offs across carbon, biodiversity, and water impacts of the transatlantic industrial wood pellet trade.

Denoising- Jittering data pre-processing technique to improve artificial intelligence based rainfall- runoff modeling

Successful modeling of hydro-environmental processes widely relies on quantity and quality of accessible data and noisy data might effect on the functioning of the modeling. On the other hand in training phase of any Artificial Intelligence (AI) based model, each training data set is usually a limited sample of possible patterns of the process and hence, might not show the behavior of whole population. Accordingly in the present article first, wavelet-based denoising method was used in order to smooth hydrological time series and then small normally distributed noises with the mean of zero and various standard deviations were generated and added to the smoothed time series to form different denoised-jittered training data sets, for Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) modeling of daily rainfall – runoff process of the Oconee River watershed located in USA. To evaluate the modeling performance, the outcomes were compared with the results of multi linear regression (MLR) and Auto Regressive Integrated Moving Average (ARIMA) models. Comparing the achieved results via the trained ANN and ANFIS models using denoised-jittered data showed that the proposed data processing approach which serves both denoising and jittering techniques could improve performance of the ANN and ANFIS based rainfall-runoff modeling of the Oconee River Watershed up to 13% and 11% in the verification phase.

Life history and distribution of the Oconee burrowing crayfish, Cambarus truncatus

The Oconee burrowing crayfish, Cambarus truncatus, is endemic to the Oconee River watershed in central Georgia. Very little is known about this primary burrower’s life history or distribution. To gather life history data, a non-invasive study was conducted using Norrocky burrowing crayfish traps and burrowing crayfish nets at Balls Ferry State Park in Toomsboro, Georgia. Crayfish were captured, measured, tagged, and released to determine growth rate, reproductive stage, and association with physiochemical factors. Thirty-six specimens were captured during the study of which twenty-five were tagged and released. Ten of the individuals were recaptured multiple times. Form I males were found in the months of February, March, May, October, and November. Female glair gland activity was present from February – May, when four in-berry females were captured; females held an average of 28 eggs. Glair gland activity peaked again during the months of October and November. Cambarus truncatus exhibited a growth rate of about 1 mm in total carapace length per molt until plateauing at about 34 mm total carapace length. The largest specimen collected was a female measuring 34.6 mm in total carapace length. The known distribution of C. truncatus was increased from 15 to 26 localities during this study, and now encompasses six counties within the Oconee River watershed.