ALBERT

Notes: : Air temperatures are sometimes used as easy substitutes for stream temperatures. To examine the errors associated with this substitution, linear relationships between 39 Minnesota stream water temperature records and associated air temperature records were analyzed. From the lumped data set (38,082 daily data pairs), equations were derived for daily, weekly, monthly, and annual mean temperatures. Standard deviations between all measured and predicted water temperatures were 3.5°C (daily), 2.6°C (weekly), 1.9°C (monthly), and 1.3°C (annual). Separate analyses for each stream gaging station gave substantially lower standard deviations. Weather monitoring stations were, on average, 37.5 km from the stream. The measured water temperatures follow the annual air temperature cycle closely. No time lags were taken into account, and periods of ice cover were excluded from the analysis. If atmospheric CO2 doubles in the future, air temperatures in Minnesota are projected (CCC GCM) to rise by 4.3°C in the warm season (April-October). This would translate into an average 4.1°C stream temperature rise, provided that stream shading would remain unaltered.

Notes: : Theoretical equations that establish the relationship between sediment oxygen demand (SOD) in a lake and the flow velocity and dissolved oxygen concentration in the bulk water already exist. These theoretical equations for oxygen consumption in the sediment express biological consumption with Michaelis-Menten kinetics, and chemical consumption by a first order reaction. Data from laboratory experiments that were conducted to validate the theoretical equations also exist. These experiments were performed in a laboratory channel with well defined flow characteristics for three types of sediments. Herein, the theoretical equations are used to model the experimental data for the three types of sediments. The values used for the parameters in the theoretical equations are determined by iteration until a best fit is obtained for the relationship of SOD to flow velocity from both the theoretical model and experimental data. The goodness of fit is measured by the standard error of prediction and the regression coefficient.

Notes: : In order to obtain total short-wave albedos of snow and ice, both incident and reflected solar radiation were measured over a frozen lake surface using two different types of radiation measurement devices: a Kipp and Zonen thermopile pyranometer with a spectral sensitivity of 300 to 2800 nm and a LI-COR photovoltaic pyranometer with a spectral sensitivity of 400 to 1100 am. The spectral response of the LI-COR pyranometers limits its use as a short-wave radiation measurement device. Therefore, two equations were developed to adjust both the daily incident radiation data and the daily reflected radiation data measured by the LI-COR instrument to total short-wave radiation values, i.e., to the waveband of 300 to 2800 nm (visible to near-infrared spectrum). The LI-COR data were then adjusted, and a total short-wave adjusted albedo was calculated with a modeling efficiency of 0.97.

Notes: : The physical limnology of three modern wastewater stabilization ponds serving a small community in Minnesota was investigated over a 1-year period (July 1989 - October 1990). Water temperatures and associated meteorological parameters were recorded continuously; underwater light, dissolved oxygen, pH, and Secchi depth were measured intermittently (about weekly). Measurements of nutrients and planktonic species were made by other investigators. Water quality stratification dynamics were studied by analyzing variations of water temperature, dissolved oxygen, and pH distributions with time and over depth. Intermittent stratification and mixing of the shallow waste stabilization ponds (1–2 m deep) were documented and related to weather. The strong response of the ponds to seasonal and daily weather variations was observed. Three types of pond stratification conditions have been identified: (1) completely mixed during consecutive day and night, (2) stratified during the day and well-mixed during the night, and (3) continuously stratified during day and night. A diurnal cycle of stratification dynamics was first noticed in late April and persisted through summer and into fall. Differences in light attenuation and hence temperature stratification and DO distribution between pond 1 (primary), pond 2 (second primary) and pond 3 (secondary) in the wastewater treatment system were documented and related to different waste loading conditions. Temperature stratification affects chemical, microbial, and planktonic processes in the ponds. Results presented in this paper can be used to provide guidance for water quality sampling in monitoring of pond performance. Information on true mixing conditions is also needed to gain better understanding of important factors affecting pond operation, and for process simulations and reactor modeling of waste stabilization ponds.

Notes: : Evidence is presented that snowmelt runoff from an urban watershed can produce density current intrusions (underflows) in a lake. Several episodes of density current intrusions are documented. Water temperatures and salinities measured near the bottom of a 10 m deep Minneapolis lake during the late winter warming periods in 1989, 1990, 1991, and 1995 show significant rapid changes which are correlated with observed higher air temperatures and snowmelt runoff. The snowmelt runoff entering this particular lake (Ryan Lake) has increased electrical conductivity, salinity, and density. The source of the salinity is the salt spread on urban streets in the winter. Heating of littoral waters in spring may also contribute to the occurrence of the sinking flows, but is clearly not the only cause.

Notes: Abstract Correlations between four climate parameters and streamflow in three Minnesota streams were investigated. Runoff values measured over periods of up to 37 years were correlated with precipitation, air temperature, wind, and dew point temperature. The overall objective was to examine if relationships can be obtained which require only readily available input parameters without calibration. Such relationships would be of great use, e.g. to compute future lake water budgets without recourse to more detailed and complex hydrologic runoff models. Monthly, seasonal, and annual time frames were investigated. A seasonal time frame using 3 month averages gave the closest fit for the linear regressions without time lag. Although the watershed sizes varied from 360 to 49,600 square kilometers, the 3 month period seemed sufficiently long to average long term hydrologic processes such as infiltration, evaporation, and groundwater flow. An equation was found for each season (3 months) for each of the rivers. Winter (December, January, February) regressions required only precipitation data; spring regressions required air temperature and precipitation; summer and fall regressions were found with precipitation, air temperature, dew point temperature, and wind speed. The coefficients in the regression equations were related to the watershed characteristics. The r2 values were highest for the Zumbro River in spring (0.69) and lowest for the Baptism River in winter (0.14). Root mean square error values ranged from 2.8 mm/mo for the Mississippi River in winter to 18 mm/mo for the Baptism River in spring. The coefficients of variability (CV) ranged from 0.24 to 0.52. Overall the results were disappointing but not all bad. Climate parameters without watershed parameters can characterize runoff only within limits. To project possible future runoff averages the GISS GCM-values for the 2 × CO2 climate scenario were applied to the seasonal runoff regression equations. The projections were that the spring runoff values would decrease by up to 35% while in the other seasons streamflows would increase by up to 50%. Annual runoff would not change significantly enough to be predictable. The results were in the range of changes predicted by other investigations using very different techniques. Since predictions were based on equations found with past records, it was implied that the land cover would remain unchanged in the 2 × CO2 environment. This may be unrealistic and needs further investigation.

Notes: Abstract To simulate effects of projected climate change on water temperature characteristics of small lakes in the contiguous U.S., a deterministic, one-dimensional year-round water temperature model is applied. In cold regions the model simulates ice and snow cover on a lake. The lake parameters required as model input are surface area, maximum depth, and Secchi depth as a measure of radiation attenuation and trophic state. The model is driven by daily weather data. Weather records from 209 stations in the contiguous U.S. for the period 1961–1979 were used to represent present climate conditions. The projected climate change owing to a doubling of atmospheric CO2 was obtained from the output of the Canadian Climate Center General Circulation Model. The simulated water temperature and ice characteristics are related to the geometric and trophic state lake characteristics and to geographic location. By interpolation, the sensitivity of lake water temperature characteristics to latitude, longitude, lake geometry and trophic status can therefore be quantified for small lakes in the contiguous U.S. The 2× CO2 climate scenario is projected to increase maximum and minimum lake surface temperatures by up to 5.2°C. (Maximum surface water temperatures in lakes near the northern and the southern border of the contiguous U.S. currently differ by up to 13°C.) Maximum temperature differences between lake surface and lake bottom are projected to increase in average by only 1 to 2°C after climate warming. The duration of seasonal summer stratification is projected to be up to 66 days longer under a 2×CO2 climate scenario. Water temperatures of less than 8°C are projected to occur on lake bottoms during a period which is on the order of 50 days shorter under a 2×CO2 climate scenario. With water temperature change projected to be as high as 5.2°C, ecological impacts such as shifts in species distributions and in fish habitat are most likely. Ice covers on lakes of northern regions would also be changed strongly.