Search Results (5)

Land cover change is prevalent in the eastern Kentucky Appalachian region, mainly due to increased surface mining activities. This study explored the potential change in land cover and its relationship with stream discharge and sediment yield in a watershed of the Cumberland River near Harlan, Kentucky, between 2001 and 2016, using the Soil and Water Assessment Tool (SWAT). Two land cover scenarios for the years 2001 and 2016 were used separately to simulate the surface runoff and sediment yield at the outlet of the Cumberland River near Harlan. Land cover datasets from the National Land Cover Database (NLCD) were used to reclassify the land cover type into the following classes: water, developed, forest, barren, shrubland, and pasture/grassland. Evaluation of the relationship between the land cover change on discharge and sediment was performed by comparing the average annual basin values of streamflow and sediment from each of the land cover scenarios. The SWAT model output was evaluated based on several statistical parameters, including the Nash–Sutcliffe efficiency coefficient (NSE), RMSE-observations standard deviation ratio (RSR), percent bias (PBIAS), and the coefficient of determination (R²). Moreover, P-factor and R-factor indices were used to measure prediction uncertainty. The model showed an acceptable range of agreement for both calibration and validation between observed and simulated values. The temporal land cover change showed a decrease in forest area by 2.42% and an increase in developed, barren, shrubland, and grassland by 0.11%, 0.34%, 0.53%, and 1.44%, respectively. The discharge increased from 92.34 mm/year to 104.7 mm/year, and sediment increased from 0.83 t/ha to 1.63 t/ha from 2001 to 2016, respectively. Based on results from the model, this study concluded that the conversion of forest land into other land types could contribute to increased surface runoff and sediment transport detached from the soil along with runoff water. The research provides a robust approach to evaluating the effect of temporal land cover change on Appalachian streams and rivers. Such information can be useful for designing land management practices to conserve water and control soil erosion in the Appalachian region of eastern Kentucky. Full article

This study aims to evaluate the performance of the Soil and Water Assessment Tool (SWAT), a simple Auto-Regressive with eXogenous input (ARX) model, and a gene expression programming (GEP)-based model in one-day-ahead discharge prediction for the upper Kentucky River Basin. Calibration of the models were carried out for the period of 2002–2005 using daily flow at a stream gauging station unaffected by the flow regulation. Validation of the calibrated models were executed for the period of 2008–2010 at the same gauging station along with another station 88 km downstream. GEP provided the best calibration (coefficient of determination (R) value 0.94 and Nash-Sutcliffe Efficiency (NSE) value of 0.88) and validation (R values of 0.93 and 0.93, NSE values of 0.87 and 0.87, respectively) results at the two gauging stations. While SWAT performed reasonably well in calibration (R value 0.85 and NSE value 0.72), its performance somewhat degraded in validation (R values of 0.85 and 0.82, NSE values of 0.65 and 0.65, for the two stations). ARX performed very well in calibration (R value 0.92, NSE value 0.82) and reasonably well in validation (R values of 0.88 and 0.92, NSE values of 0.76 and 0.85) at the two stations. Research results suggest that sophisticated hydrological models could be outperformed by simple data-driven models and GEP has the advantage to generate functional relationships that allows investigation of the complex nonlinear interrelationships among the input variables. Full article

Waterborne diseases are a global problem that causes more than 2.2 million deaths annually. Therefore, the present study was focused on microbiological contamination of both ground and surface water by means of total coliform, Escherichia coli (E. coli), Salmonella spp., Shigella spp. and Campylobacter spp. Seventy two groundwater and 45 surface water sampling locations were selected to collect water from the head, transitional and meandering regions of the Kelani River Basin for a period of one year (both dry and wet seasons). The results of the study revealed that the entire Kelani River basin was contaminated with total coliform and E. coli bacteria and almost all the sampling locations exceed Sri Lanka Standards Institute (SLSI) guideline value given for drinking water (0 CFU/100 mL). Further, in groundwater, 17 locations were positive for Salmonella spp., whereas only 2 locations were positive for Campylobacter spp. In surface water, 26 and three sampling locations were positive for Salmonella spp. and Campylobacter spp., respectively. In this study, 23 different human pathogenic serovars were isolated and the Salmonella enterica serovar Kentucky was identified as the commonest type. Thus, the result of the study revealed that the consumption of raw water from the Kelani River Basin is unsafe and possible to cause gastrointestinal diseases. Full article

Climatic variability can lead to large‐scale alterations in the hydrologic cycle, some of which can be characterized in terms of indices involving precipitation depth, duration and frequency. This study evaluated the spatiotemporal behavior of precipitation indices over the Kentucky River watershed for both the baseline period of 1986–2015 and late‐century time frame of 2070–2099. Historical precipitation data were collected from 16 weather stations in the watershed, while future rainfall time‐series were obtained from an ensemble of 10 Coupled Model Intercomparison Project Phase 5 (CMIP5) global circulation models under two future emission pathways: Representative Concentration Pathways (RCP) 4.5 and 8.5. Annual trends in seven precipitation indices were analyzed: total precipitation on wet days (PRCPTOT), maximum length (in days) of dry and wet periods (CDD and CWD, respectively), number of days with precipitation depth ≥20 mm (R20mm), maximum five‐day precipitation depth (RX5day), simple daily precipitation index (SDII) and standardized precipitation index (SPI, a measure of drought severity). Non‐parametric Mann–Kendall test results indicated significant trends for only ≈11% of the stationindex combinations, corresponding to generally increasing trends in PRCPTOT, CWD, R20mm and RX5day and negative trends for the others. Projected magnitudes for PRCPTOT, CDD, CWD, RX5day and SPI, indices associated with the macroweather regime, demonstrated general consistency with trends previously identified and indicated modest increases in PRCPTOT and CWD, slight decrease in CDD, mixed results for RX5day, and increased non‐drought years in the late century relative to the baseline period. Late‐century projections for the remaining indices (SDII, R20mm) demonstrated behavior counter to trends in the trends identified in the baseline period data, suggesting that these indices—which are more closely linked with the weather regime and daily GCM outputs—were relatively less robust. Full article

Increasingly available and a virtually uninterrupted supply of satellite-estimatedrainfall data is gradually becoming a cost-effective source of input for flood predictionunder a variety of circumstances. However, most real-time and quasi-global satelliterainfall products are currently available at spatial scales ranging from 0.25^o to 0.50^o andhence, are considered somewhat coarse for dynamic hydrologic modeling of basin-scaleflood events. This study assesses the question: what are the hydrologic implications ofuncertainty of satellite rainfall data at the coarse scale? We investigated this question onthe 970 km² Upper Cumberland river basin of Kentucky. The satellite rainfall productassessed was NASA’s Tropical Rainfall Measuring Mission (TRMM) Multi-satellitePrecipitation Analysis (TMPA) product called 3B41RT that is available in pseudo real timewith a latency of 6-10 hours. We observed that bias adjustment of satellite rainfall data canimprove application in flood prediction to some extent with the trade-off of more falsealarms in peak flow. However, a more rational and regime-based adjustment procedureneeds to be identified before the use of satellite data can be institutionalized among floodmodelers. Full article