Controls on spatial and temporal variation of nutrient uptake in three Michigan headwater streams

2007 ◽  
Vol 52 (5) ◽  
pp. 1964-1977 ◽  
Author(s):  
Timothy J. Hoellein ◽  
Jennifer L. Tank ◽  
Emma J. Rosi-Marshall ◽  
Sally A. Entrekin ◽  
Gary A. Lamberti
Keyword(s):  
Temporal Variation ◽  
Nutrient Uptake ◽  
Headwater Streams ◽  
Spatial And Temporal Variation

scholarly journals A model of potential carbon dioxide efflux from surface water across England and Wales using headwater stream survey data and landscape predictors

2014 ◽  
Vol 11 (7) ◽  
pp. 1911-1925 ◽  
Author(s):  
B. G. Rawlins ◽  
B. Palumbo-Roe ◽  
D. C. Gooddy ◽  
F. Worrall ◽  
H. Smith
Keyword(s):  
Temporal Variation ◽  
Headwater Streams ◽  
Spatial And Temporal Variation ◽  
Co2 Efflux ◽  
England And Wales ◽  
Partial Pressures ◽  
Catchment Areas ◽  
Geomorphic Features ◽  
Carbon Dioxide Efflux ◽  
Monthly Runoff

Abstract. Measurements of CO2 partial pressures (pCO2) in small headwater streams are useful for predicting potential CO2 efflux because they provide a single concentration representing a mixture from different hydrological pathways and sources in the catchment. We developed a model to predict pCO2 in headwater streams from measurements undertaken on snapshot samples collected from more than 3000 channels across the landscape of England and Wales. We used a subset of streams with upstream catchment areas (CA) of less than 8 km2 because below this scale threshold pCO2 was independent of CA. A series of catchment characteristics were found to be statistically significant predictors of pCO2, including three geomorphic variables (mean altitude, mean catchment slope and relief) and four groups of dominant catchment land cover classes (arable, improved grassland, suburban and all other classes). We accounted for year-round, temporal variation in our model of headwater pCO2 by including weekly or monthly analyses of samples from three headwater catchments with different land use and geomorphic features. Our model accounted for 24% of the spatial and temporal variation in pCO2. We combined predictions from the pCO2 model (on a 1 km grid) and monthly runoff volumes (litres) on 0.5° resolution grid across England and Wales to compute potential C fluxes to the atmosphere. Our model predicts an annual average potential C flux of 65.4 kt C across England and Wales (based on free C concentrations), with lower and upper 95% confidence values of 56.1 and 77.2 kt C, respectively.

scholarly journals A model of potential carbon dioxide efflux from surface water across England and Wales using headwater stream survey data and landscape predictors

2013 ◽  
Vol 10 (10) ◽  
pp. 16453-16490
Author(s):  
B. G. Rawlins ◽  
B. Palumbo-Roe ◽  
D. C. Gooddy ◽  
F. Worrall ◽  
H. Smith
Keyword(s):  
Temporal Variation ◽  
Headwater Streams ◽  
Spatial And Temporal Variation ◽  
Co2 Efflux ◽  
England And Wales ◽  
Partial Pressures ◽  
Catchment Areas ◽  
Geomorphic Features ◽  
Carbon Dioxide Efflux

Abstract. Measurements of CO2 partial pressures (pCO2) in small headwater streams are useful for predicting potential CO2 efflux because they provide a single concentration representing a mixture from different hydrological pathways and sources in the catchment. We developed a model to predict pCO2 in headwater streams from measurements undertaken on snapshot samples collected from more than 3000 channels across the landscape of England and Wales. We used a subset of streams with upstream catchment areas (CA) of less than 8 km2 because below this scale threshold pCO2 was independent of CA. A series of catchment characteristics were found to be statistically significant predictors of pCO2 including three geomorphic variables (mean altitude, mean catchment slope and relief) and four groups of dominant catchment land cover classes (arable, improved grassland, suburban and all other classes). We accounted for year-round, temporal variation in our model of headwater pCO2 by including weekly or monthly analyses of samples from three headwater catchments with different land use and geomorphic features. Our model accounted for 24% of the spatial and temporal variation in pCO2. We calculated monthly long-term (1961–1990) average flow volumes (litres) on a 1 km grid across England and Wales to compute potential C fluxes to the atmosphere. Our model predicts an annual average potential C flux of 60.8 kt C across England and Wales (based on free C concentrations), with lower and upper 95% confidence values of 52.3 and 71.4 kt C, respectively.

SPATIAL AND TEMPORAL VARIATION IN GROUNDWATER GEOCHEMISTRY IN THE HIGH PLAINS AQUIFER SYSTEM, SOUTHCENTRAL KANSAS

2016 ◽  
Author(s):  
Alexandria D. Richard ◽  
◽  
Adam E. Lane ◽  
Janet M. Paper ◽  
Ben R. Haller ◽  
...  
Keyword(s):  
Temporal Variation ◽  
Spatial And Temporal Variation ◽  
High Plains ◽  
High Plains Aquifer ◽  
Aquifer System ◽  
Groundwater Geochemistry

scholarly journals Spatial and Temporal Variation Characteristics of Snowfall in the Haihe River Basin from 1960 to 2016

Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1798
Author(s):  
Xu Wu ◽  
Su Li ◽  
Bin Liu ◽  
Dan Xu
Keyword(s):  
Temporal Variation ◽  
River Basin ◽  
Spatial And Temporal Variation ◽  
Haihe River Basin ◽  
Temperature Threshold ◽  
Threshold Method ◽  
Exponential Equation ◽  
Haihe River ◽  
The Haihe River Basin ◽  
Different Levels

The spatio-temporal variation of precipitation under global warming had been a research hotspot. Snowfall is an important part of precipitation, and its variabilities and trends in different regions have received great attention. In this paper, the Haihe River Basin is used as a case, and we employ the K-means clustering method to divide the basin into four sub-regions. The double temperature threshold method in the form of the exponential equation is used in this study to identify precipitation phase states, based on daily temperature, snowfall, and precipitation data from 43 meteorological stations in and around the Haihe River Basin from 1960 to 1979. Then, daily snowfall data from 1960 to 2016 are established, and the spatial and temporal variation of snowfall in the Haihe River Basin are analyzed according to the snowfall levels as determined by the national meteorological department. The results evalueted in four different zones show that (1) the snowfall at each meteorological station can be effectively estimated at an annual scale through the exponential equation, for which the correlation coefficient of each division is above 0.95, and the relative error is within 5%. (2) Except for the average snowfall and light snowfall, the snowfall and snowfall days of moderate snow, heavy snow, and snowstorm in each division are in the order of Zones III > IV > I > II. (3) The snowfall and the number of snowfall days at different levels both show a decreasing trend, except for the increasing trend of snowfall in Zone I. (4) The interannual variation trend in the snowfall at the different levels are not obvious, except for Zone III, which shows a significant decreasing trend.

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