Surface-water quantity and quality data, Rocky Flats Environmental Technology Site near Denver Colorado, water year 1996

1997 ◽  
Author(s):  
M.E. Smith ◽  
J.W. Unruh ◽  
C.H. Thompson
Keyword(s):  
Surface Water ◽  
Quality Data ◽  
Water Quantity ◽  
Environmental Technology ◽  
Rocky Flats ◽  
Water Quantity And Quality

scholarly journals Evaluation of Temporal Contribution of Groundwater to a Small Lake through Analyses of Water Quantity and Quality

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2879 ◽  
Author(s):  
Jeonga Kim ◽  
Sung-Wook Jeen ◽  
Jeonghoon Lee ◽  
Kyung-Seok Ko ◽  
Dong-Chan Koh ◽  
...  
Keyword(s):  
Surface Water ◽  
Quality Parameters ◽  
Water Levels ◽  
Quality Analysis ◽  
Quality Data ◽  
Water Quantity ◽  
Small Lake ◽  
Rainwater Infiltration ◽  
Site Water ◽  
Water Quantity And Quality

Groundwater can flow into or out of surface water and thus can greatly affect the quantity and quality of surface water. In this study, we conducted a water quantity and quality analysis for 11 months in 2018 and 2019 to evaluate the temporal contribution of groundwater to surface water at Osongji, a small lake located in Jeonju-si, Jeollabuk-do, Korea. Groundwater fluxes and groundwater and surface water levels were measured using seepage meters and a piezometer, respectively. On-site water quality parameters, cations, and anions for groundwater and surface water were analyzed. Hydrogen and oxygen isotopes for groundwater, surface water, and rainwater were also analyzed. Groundwater influx did not correlate directly to precipitation, suggesting that it may be delayed after rainwater infiltration. Aqueous chemistry indicated that the hydrogeochemical characteristics of surface water were substantially affected by groundwater. The isotopic composition of surface water changed over time, indicating a different contribution of groundwater in different seasons. This study shows that water quantity and quality data can be used in combination to evaluate temporal changes in the groundwater contribution to surface water.

Response of surface water quantity and quality to agricultural water use intensity in upstream Hutuo River Basin, China

2019 ◽  
Vol 212 ◽  
pp. 378-387
Author(s):  
Shumin Han ◽  
Qiuli Hu ◽  
Yonghui Yang ◽  
Yanmin Yang ◽  
Xinyao Zhou ◽  
...  
Keyword(s):  
Surface Water ◽  
River Basin ◽  
Water Use ◽  
Water Quantity ◽  
Agricultural Water ◽  
Agricultural Water Use ◽  
Water Quantity And Quality

scholarly journals Runoff water quantity and quality data from native tallgrass prairie and crop–livestock systems in Oklahoma between 1977 and 1999

2020 ◽  
Vol 49 (4) ◽  
pp. 1062-1072
Author(s):  
Amanda M. Nelson ◽  
Daniel N. Moriasi ◽  
Ann‐Marie Fortuna ◽  
Jean L. Steiner ◽  
Patrick J. Starks ◽  
...  
Keyword(s):  
Tallgrass Prairie ◽  
Quality Data ◽  
Water Quantity ◽  
Runoff Water ◽  
Livestock Systems ◽  
Water Quantity And Quality

scholarly journals Assessment of surface-water quantity and quality, Eagle River watershed, Colorado, 1947-2007

2011 ◽  
Author(s):  
Cory A. Williams ◽  
Jennifer L. Moore ◽  
Rodney J. Richards
Keyword(s):  
Surface Water ◽  
Water Quantity ◽  
River Watershed ◽  
Water Quantity And Quality

scholarly journals Physics-Informed Data-Driven Models to Predict Surface Runoff Water Quantity and Quality in Agricultural Fields

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 200 ◽  
Author(s):  
Jing Liang ◽  
Wenzhe Li ◽  
Scott Bradford ◽  
Jiří Šimůnek
Keyword(s):  
Surface Water ◽  
Surface Runoff ◽  
Overland Flow ◽  
Data Driven ◽  
Water Quantity ◽  
Soil Conditions ◽  
Runoff Water ◽  
Physically Based ◽  
Physically Based Models ◽  
Water Quantity And Quality

Contaminants can be rapidly transported at the soil surface by runoff to surface water bodies. Physically-based models (PBMs), which are based on the mathematical description of main hydrological processes, are key tools for predicting surface water impairment. Along with PBMs, data-driven models are becoming increasingly popular for describing the behavior of hydrological and water resources systems since these models can be used to complement or even replace physically based-models. Here we propose a new data-driven model as an alternative to a physically-based overland flow and transport model. First, we have developed a physically-based numerical model to simulate overland flow and contaminant transport. A large number of numerical simulations was then carried out to develop a database containing information about the impact of various relevant factors on surface runoff quantity and quality, such as different weather patterns, surface topography, vegetation, soil conditions, contaminants, and best management practices. Finally, the resulting database was used to train data-driven models. Several Machine Learning techniques were explored to find input-output functional relations. The results indicate that the Neural Network model with two hidden layers performed the best among selected data-driven models, accurately predicting runoff water quantity and quality over a wide range of parameters.

Actinide Migration from Contaminated Soil to Surface Water at the Rocky Flats Environmental Technology Site

2002 ◽  
Vol 39 (sup3) ◽  
pp. 485-488 ◽  
Author(s):  
Peter H. Santschi ◽  
Kimberly Roberts
Keyword(s):  
Surface Water ◽  
Contaminated Soil ◽  
Environmental Technology ◽  
Rocky Flats

Surface water quantity and quality assessment in Pinios River, Thessaly, Greece

Desalination ◽  
2010 ◽  
Vol 250 (1) ◽  
pp. 266-273 ◽  
Author(s):  
A. Loukas
Keyword(s):  
Surface Water ◽  
Quality Assessment ◽  
Water Quantity ◽  
Pinios River ◽  
Water Quantity And Quality
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