Omid Mohseni

Stream temperature/air temperature relationship: a physical interpretation

Abstract In studies of the potential effects of global climate change on freshwater ecosystems, water temperature is a primary factor. Linear regressions of stream temperature versus air temperature are attractive for this purpose, because they require only one input variable (air temperature) which can be simulated by General Circulation Models (GCMs) better than other climate variables. Under a warmer climate scenario, high stream temperatures must be projected by extrapolation. The question arises whether linear extrapolation is valid. To answer the question, the heat exchange processes that contribute to surface water temperature have been analyzed and related to air temperature on a weekly time scale. The equilibrium temperature concept introduced by Edinger has been used. In stream reaches with large drainage area, stream temperature can be approximated by equilibrium temperature. At elevated air temperatures, the vapor pressure deficit above a water surface increases drastically (even in humid regions) causing strong evaporative cooling and hence a flatter stream temperature/air temperature relationship. At low air temperatures, stream temperatures often reach 0°C as an asymptote. If an upstream flow control (dam, reservoir release) or a waste heat input is present, the lower asymptotic value can be larger than 0°C. As a result of these upper and lower constraints for stream temperatures, the stream temperature/air temperature relationship resembles an S-shaped function rather than a straight line. Linear extrapolations to high and low air temperatures are therefore not justified.

A nonlinear regression model for weekly stream temperatures

To estimate weekly stream temperatures needed for fish habitat evaluation throughout an annual cycle, a four-parameter, nonlinear function of weekly air temperatures was used. The regression function was developed separately for the warming season and the cooling season to take heat storage effects (hysteresis) into account. Regression functions were developed for stream temperatures recorded over a 3-year period (1978–1980) at 584 U.S. Geological Survey (USGS) gaging stations in the contiguous United States. Representative air temperatures were obtained from the closest of 197 weather stations. The distance between a stream gaging station and the corresponding weather station was from 1.4 to 244 km. These distances did not have a significant effect on the goodness of fit. The regression model fitted the weekly stream temperatures at 573 stream gaging stations (98% of all records used) with a coefficient of determination larger than 0.7. For 491 records (84% of all gaging stations) the coefficient was >0.9. At 56 gaging stations (10% of all records used), estimated maximum stream temperatures were smaller than at least four weekly stream temperatures recorded for the period of study. Consequently, the model is deemed successfully applicable (with 99% confidence) to more than 89% of the stream gaging stations. The average coefficient of determination of the stream temperature projection for these stations is 0.93 ± 0.01.

Global Warming and Potential Changes in Fish Habitat in U.S. Streams

To project potential habitat changes of 57 fish species under global warming, their suitable thermal habitat at 764 stream gaging stations in the contiguous United States was studied. Global warming was specified by air temperature increases projected by the Canadian Centre of Climate Modelling General Circulation Model for a doubling of atmospheric CO2. The aquatic thermal regime at each gaging station was related to air temperature using a nonlinear stream temperature/air temperature relationship.Suitable fish thermal habitat was assumed to be constrained by both maximum temperature and minimum temperature tolerances. For cold water fishes with a 0 °C lower temperature constraint, the number of stations with suitable thermal habitat under a 2×CO2 climate scenario is projected to decrease by 36%, and for cool water fishes by 15%. These changes are associated with a northward shift of the range. For warm water fishes with a 2 °C lower temperature constraint, the potential number of stations with suitable thermal habitat is projected to increase by 31%.

Sensitivity of stream temperatures in the United States to air temperatures projected under a global warming scenario

To project mean weekly stream temperature changes in response to global climate warming and for studies of freshwater ecosystems, a four-parameter nonlinear function of weekly air temperatures was used. One parameter, the upper bound stream temperature, was obtained by extreme value analysis from stream temperature data, and the other three parameters were obtained by least squares regression analysis. The least squares regression function was developed separately for the warming season and the cooling season (hysteresis) to take heat storage due to snowmelt or reservoir operations into account. There were very weak correlations between model parameters and annual or seasonal air temperatures. To project weekly stream temperatures under a 2 × CO2 climate scenario, weekly air temperature data from 166 weather stations, incremented by the output of the Canadian Center of Climate Modelling (CCC) general circulation model (GCM), were applied to nonlinear stream temperature models developed for 803 stream gaging stations. An error analysis indicated that only 39 stream gaging stations would not exhibit a significant change under the CCC-GCM 2 × CO2 climate scenario. The projections at the remaining 764 stream gaging stations showed that mean annual stream temperatures in the contiguous United States would increase by 2°–5°C, least near the West Coast and most in the Missouri River and Ohio River basins. On average, there would be a 1°–3°C increase in the maximum and minimum weekly stream temperatures under the 2 × CO2 climate scenario, most in the central United States. It was also found that most streams would experience the maximum change in weekly stream temperatures in spring (March–June). The minimum changes in stream temperatures are projected to occur in winter (December and January) and summer (July and August) throughout the United States.

Assessment of hydrodynamic separators for storm-water treatment

Hydrodynamic separators are proprietary underground devices designed to remove floatable debris e.g., leaves, trash, oil and to remove suspended solids from storm-water runoff by sedimentation. They are designed for storm-water treatment in urban areas to meet tight space constraints. Limited data on the suspended solids removal performance of installed devices are available, and existing data are questionable because of the problems associated with assessment by monitoring. The objectives of our research are to: 1 investigate the feasibility and practicality of field testing to assess the performance of hydrodynamic separators as underground storm-water treatment devices; 2 evaluate the effects of sediment size and storm-water discharge on the performance of six devices from different manufac- turers; and 3 develop a universal approach for predicting the performance of a device for any given application. In the field tests, a controlled and reproducible synthetic storm event containing sediment of a well defined size distribution and concentration was fed to a precleaned device. The captured sediment was then removed, dried, sieved, and weighed. To assess the performance of the devices, suspended sediment removal efficiency was related to a Peclet number, which accounts for two major processes that control performance: 1 settling of particles; and 2 turbulent diffusion or mixing of particles. After analyzing the data, all devices showed similar behavior, therefore, a three-parameter performance function was proposed for all devices. Performance functions were developed from the result of the field tests and parallel testing of two other full-scale devices in the laboratory. The performance functions can be used to determine the efficiency of the tested devices and to improve the selection and sizing of hydrodynamic separators and the assessment of their overall performance after installation.

A monthly streamflow model

To estimate the potential consequences of projected global warming on streamflow, a deterministic model for a monthly timescale has been developed. The model structure is based on the water budget theory and contains deterministic relationships to estimate four components of streamflow: direct runoff, interflow, base flow, and snowmelt. The model inputs are six climate variables for each time step and 10 watershed parameters. The model has four calibration parameters which are related to direct runoff and snowmelt runoff. The model has been applied to the Little Washita River watershed in Oklahoma and the Baptism River watershed in Minnesota. The former is an agricultural watershed with a warm and seasonally dry climate, and the latter is a forested watershed with a cool and humid climate. The model simulates mean monthly streamflow in the Baptism River with a Nash-Sutcliffe coefficient (NSC) of 0.99 and a correlation coefficient of 0.83. For the Little Washita River the same simulation measures are 0.94 and 0.89, respectively.

Water Budgets of Two Watersheds in Different Climatic Zones under Projected Climate Warming

A deterministic monthly runoff model (MINRUN96)was applied to watersheds with substantially differentclimates. One watershed is in the north-central U.S.(Minnesota) and is heavily timbered. The other is inthe south-central U.S. (Oklahoma) and is mainlycovered with pastures and agricultural crops. Runoffwas simulated for past historical climate and twoprojected 2 × CO2 climate scenarios. The output ofGeneral Circulation Models (GCMs) was used to specifythe two 2 × CO2 climate scenarios. One GCM is theGoddard Institute of Space Studies (GISS) model andthe other is from the Canadian Center of ClimateModelling (CCC). In the northern watershed morerunoff is projected to occur in winter under a warmerclimate and less runoff in spring. About 80%increase in fall runoff and 20% decrease in soilmoisture in June and July is projected for thesouthern watershed. When runoff simulations for the2 × CO2 climate scenarios were compared to pastrunoff, it was apparent that the change in runoffdepended on both the season and the magnitude of theprecipitation change. An increase in springprecipitation caused a significant increase in directrunoff, whereas an increase in fall precipitationcaused only a slight increase in total runoff. Alsothe runoff-precipitation relationship in the warm andseasonally dry southern watershed is very differentfrom that in the temperate and humid climate of thenorth. Therefore, runoff responses to projectedclimate change are substantially different in the tworegions.

SAFL Baffle retrofit for suspended sediment removal in storm sewer sumps

Standard sumps (manholes) provide a location for pipe junctions and maintenance access in stormwater drainage systems. Standard sumps can also remove sand and silt particles from stormwater, but have a high propensity for washout of the collected sediment. With appropriate maintenance these sumps may qualify as a stormwater best management practice (BMP) device for the removal of suspended sediment from stormwater runoff. To decrease the maintenance frequency and prevent standard sumps from becoming a source of suspended sediment under high flow conditions, a porous baffle, named the SAFL Baffle, has been designed and tested as a retrofit to the sump. Multiple configurations with varying percent open area and different angles of attack were evaluated in scale models. An optimum configuration was then constructed at the prototype scale and evaluated for both removal efficiency and washout. Results obtained with the retrofit indicate that with the right baffle dimensions and porosity, sediment washout from the sump at high flow rates can be almost eliminated, and removal efficiency can be significantly increased at low flow rates. Removal efficiency and washout functions have been developed for standard sumps retrofitted with the SAFL Baffle. The results of this research provide a new, versatile stormwater treatment device and implemented new washout and removal efficiency testing procedures that will improve research and development of stormwater treatment devices.

Improving suspended sediment measurements by automatic samplers

Suspended solids either as total suspended solids (TSS) or suspended sediment concentration (SSC) is an integral particulate water quality parameter that is important in assessing particle-bound contaminants. At present, nearly all stormwater runoff quality monitoring is performed with automatic samplers in which the sampling intake is typically installed at the bottom of a storm sewer or channel. This method of sampling often results in a less accurate measurement of suspended sediment and associated pollutants due to the vertical variation in particle concentration caused by particle settling. In this study, the inaccuracies associated with sampling by conventional intakes for automatic samplers have been verified by testing with known suspended sediment concentrations and known particle sizes ranging from approximately 20 μm to 355 μm under various flow rates. Experimental results show that, for samples collected at a typical automatic sampler intake position, the ratio of sampled to feed suspended sediment concentration is up to 6600% without an intake strainer and up to 300% with a strainer. When the sampling intake is modified with multiple sampling tubes and fitted with a wing to provide lift (winged arm sampler intake), the accuracy of sampling improves substantially. With this modification, the differences between sampled and feed suspended sediment concentration were more consistent and the sampled to feed concentration ratio was accurate to within 10% for particle sizes up to 250 μm.

Runoff Temperature Model for Paved Surfaces

Interest in thermal pollution due to storm-water runoff has risen significantly since it was recognized that fish habitat in coldwater streams may deteriorate or even disappear following urban development or logging. The need to project changes in both runoff temperature and volume in response to land use changes has been recognized. Surface runoff hydrographs can be predicted or simulated using a variety of existing models. Few tools exist to predict or simulate the thermograph of that runoff, i.e., the water flow rate and temperature as a function of time. To simulate runoff temperature for small parcels of land of uniform cover such as parking lots, a new hydrothermal runoff model was developed. The runoff portion of the model is semianalytical and spatially integrated. The runoff model is discrete in time, so that it may be used to analyze events with observed rainfall intensity variations at a resolution of 15 min or less. The runoff model closely approximates the simulation results of a one-dimensio...