PREDICTION OF STREAM TEMPERATURE IN FORESTED WATERSHEDS1

ABSTRACT: Removal of streamside vegetation changes the energy balance of a stream, and hence its temperature. A common approach to mitigating the effects of logging on stream temperature is to require establishment of buffer zones along stream corridors. A simple energy balance model is described for prediction of stream temperature in forested headwater watersheds that allows evaluation of the performance of such measures. The model is designed for application to “worst case” or maximum annual stream temperature, under low flow conditions with maximum annual solar radiation and air temperature. Low flows are estimated via a regional regression equation with independent variables readily accessible from GIS databases. Testing of the energy balance model was performed using field data for mostly forested basins on both the west and east slopes of the Cascade Mountains, and was then evaluated using the regional equations for low flow and observed maximum reach temperatures in three different east slope Cascades catchments. A series of sensitivity analyses showed that increasing the buffer width beyond 30 meters did not significantly decrease stream temperatures, and that other vegetation parameters such as leaf area index, average tree height, and to a lesser extent streamside vegetation buffer width, more strongly affected maximum stream temperatures.     

Sensitivity of Thermal Habitat of a Trout Stream to Potential Climate Change,Wisconsin, United States1

Abstract: Airborne thermal remote sensing from four flights on a single day from a single‐engine airplane was used to collect thermal infrared data of a 10.47‐km reach of the upper East Branch Pecatonica River in southwest Wisconsin. The study uses a one‐dimensional stream temperature model calibrated with the longitudinal profiles of stream temperature created from the four thermal imaging flights and validated with three days of continuous stream temperature data from instream data loggers on the days surrounding the thermal remote‐sensing campaign. Model simulations were used to quantify the sensitivity of stream thermal habitat to increases in air and groundwater temperature and changes in base flow. The simulations indicate that stream temperatures may reach critical maximum thresholds for brook trout (Salvelinus fontinalis) and brown trout (Salmo trutta) mortality, particularly if both air temperature increases and base flow declines. The approach demonstrates that thermal infrared data can greatly assist stream temperature model validation due to its high spatial resolution, and that this spatially continuous stream temperature data can be used to pinpoint spatial heterogeneity in groundwater inflow to streams. With this spatially distributed data on thermal heterogeneity and base‐flow accretion, stream temperature models considering various climate change scenarios are able to identify thermal refugia that will be critical for fisheries management under a changing climate.     

Historical and Future Stream Temperature Change Predicted by a Lidar‐Based Assessment of Riparian Condition and Channel Width

Riparian forests attenuate solar radiation, thereby mediating an important component of the thermal budget of streams. Here, we investigate the relationship between riparian degradation, stream temperature, and channel width in the Chehalis River Basin, Washington State. We used lidar data to measure canopy opening angle, the angle formed between the channel center and trees on both banks; we assumed historical tree heights and calculated the change in canopy angle relative to historical conditions. We then developed an empirical relationship between canopy angle and water temperature using existing data, and simulated temperatures between 2002 and 2080 by combining a tree growth model with climate change scenarios from the NorWeST regional prediction. The greatest change between historical and current conditions (~7°C) occurred in developed portions of the river network, with the highest values of change predicted at channel widths less than ~40 m. Tree growth lessened climate change increases in maximum temperature and the length of river exceeding biologically critical thresholds by ~50%–60%. Moreover, the maximum temperature of channels with bankfull widths less than ~50 m remained similar to current conditions, despite climate change increases. Our findings are consistent with a possible role for the riparian landscape in explaining the low sensitivity of stream temperatures to air temperatures observed in some small mountain streams.     

ANALYSIS AND MODELING OF LONG-TERM STREAM TEMPERATURES ON THE STEAMBOAT CREEK BASIN,OREGON: IMPLICATIONS FOR LAND USE AND FISH HABITAT1

ABSTRACT: Steamboat Creek basin is an important source of timber and provides crucial spawning and rearing habitat for anadromous steelhead trout (Oncorhynchus mykiss). Because stream temperatures are near the upper limit of tolerance for the survival of juvenile steelhead, the possible long-term effect of clear-cut logging on stream temperatures was assessed. Twenty-year (1969–1989) records of summer stream temperature and flow from four tributaries and two reaches of Steamboat Creek and Boulder Creek (a nearby unlogged watershed) were analyzed. Logging records for the Steamboat Creek basin and air temperature records also were used in the analysis. A time-series model of the components of stream temperature (seasonal cycle of solar radiation, air temperature, streamflow, an autoregressive term of order 1, and a linear trend variable) was fitted to the water-temperature data. The linear trend variable was significant in all the fitted models except Bend Creek (a tributary fed by cool ground-water discharge) and Boulder Creek. Because no trends in either climate (i.e., air temperature) or streamflow were found in the data, the trend variable was associated with the pre-1969 loss and subsequent regrowth of riparian vegetation and shading canopies.     

River temperature sensitivity to hydraulic and meteorological parameters

A sensitivity analysis is performed to evaluate river temperature variations in response to changes in hydraulic and meteorological conditions. The effects of instream flow, river geometry, and weather factors on daily mean and daily maximum river temperatures are quantified by analytical solutions to a simplified model. The influence coefficient method is used to determine river temperature sensitivity. The sensitivity analysis presents quantitative evidence that river temperatures are more sensitive to instream flowrate, upstream inflow temperature, air temperature, humidity and solar radiation than to other parameters including wind speed and channel geometry and morphometry. It is found that the sensitivity of river temperatures to flow is as significant as that to weather. Daily maximum river temperature is more sensitive to flowrate than daily mean temperature. Adapting the concept of 'diminishing returns', a critical instream flowrate is identified, which divides high and low sensitivity of water temperatures to flowrate. The critical flowrate can be used to determine practically achievable and economically feasible flow requirements for summer river temperature control. The sensitivity results can assist in streamflow management and reservoir operation for protections of habitat and aquatic environment.     

Do Energy‐Based PET Models Require More Input Data than Temperature‐Based Models? — An Evaluation at Four Humid FluxNet Sites

It is well established that wet environment potential evapotranspiration (PET) can be reliably estimated using the energy budget at the canopy or land surface. However, in most cases the necessary radiation measurements are not available and, thus, empirical temperature‐based PET models are still widely used, especially in watershed models. Here we question the presumption that empirical PET models require fewer input data than more physically based models. Specifically, we test whether the energy‐budget‐based Priestley‐Taylor (P‐T) model can reliably predict daily PET using primarily air temperature to estimate the radiation fluxes and associated parameters. This method of calculating PET requires only daily minimum and maximum temperature, day of the year, and latitude. We compared PET estimates using directly measured radiation fluxes to PET calculated from temperature‐based radiation estimates at four humid AmeriFlux sites. We found good agreement between P‐T PET calculated from measured radiation fluxes and P‐T PET determined via air temperature. In addition, in three of the four sites, the temperature‐based radiation approximations had a stronger correlation with measured evapotranspiration (ET) during periods of maximal ET than fully empirical Hargreaves, Hamon and Oudin methods. Of the three fully empirical models, the Hargreaves performed the best. Overall, the results suggest that daily PET estimates can be made using a physically based approach even when radiation measurements are unavailable.     

RIPARIAN MICROCLIMATE AND STREAM TEMPERATURE RESPONSE TO FOREST HARVESTING: A REVIEW1

Forest harvesting can increase solar radiation in the riparian zone as well as wind speed and exposure to air advected from clearings, typically causing increases in summertime air, soil, and stream temperatures and decreases in relative humidity. Stream temperature increases following forest harvesting are primarily controlled by changes in insolation but also depend on stream hydrology and channel morphology. Stream temperatures recovered to pre‐harvest levels within 10 years in many studies but took longer in others. Leaving riparian buffers can decrease the magnitude of stream temperature increases and changes to riparian microclimate, but substantial warming has been observed for streams within both unthinned and partial retention buffers. A range of studies has demonstrated that streams may or may not cool after flowing from clearings into shaded environments, and further research is required in relation to the factors controlling downstream cooling. Further research is also required on riparian microclimate and its responses to harvesting, the influences of surface/subsurface water exchange on stream and bed temperature regimes, biological implications of temperature changes in headwater streams (both on site and downstream), and methods for quantifying shade and its influence on radiation inputs to streams and riparian zones.     

STREAM TEMPERATURE INCREASES AND LAND USE IN A FORESTED OREGON WATERSHED1

ABSTRACT: The Salmon Creek Watershed drains 325 km² of forested terrain in the Cascade Mountains of western Oregon. Over a 30–year period (from 1955 to 1984) average daily maximum and minimum stream temperatures, calculated from the 10 warmest days of each year, have risen 6°C and 2°C, respectively. In contrast, a small decrease in maximum air temperatures was found over the same period. Regression analysis indicated a highly significant (p < 0.01) relationship between a cumulative index of forest harvesting and maximum stream temperatures. Maximum temperatures also tended to increase for several years following major peak flow events. The interaction between harvest activity (logging and road construction), changing forest and riparian management practices and the occurrence of natural hydrologic events (peak flows and associated mass soil movements) tend to obscure specific cause-and-effect relationships regarding long-term changes in maximum stream temperature.     

Comparison of two stream temperature models and evaluation of potential management alternatives for the Speed River, Southern Ontario

Concerns over increased water temperature of the Speed River as it flows through the City of Guelph in Southern Ontario and an observed relationship between summer stream temperatures and low dissolved oxygen levels in the river prompted an investigation into potential stream temperature management practices. Two mechanistic stream temperature models, SNTEMP and CE-QUAL-W2, were applied to the Speed River in order to gauge the effectiveness of various stream temperature management options. Calibrated versions of both models performed well (0.2 degrees C相似文献   

Evaluation of various global solar radiation models for Nigeria

This study assessed the performance of six solar radiation models. The objective was to determine the most accurate model for estimating global solar radiation on a horizontal surface in Nigeria. Twenty-two years meteorological data sets collected from the Nigerian Meteorological agency and the National Aeronautics and Space Administration for the three regions, covering the entire climatic zones in Nigeria were utilized for calibrating and validating the selected models for Nigeria. The accuracy and applicability of various models were determined for three locations (Abuja, Benin City, and Sokoto), which spread across Nigeria using seven viable statistical indices. This study found that the estimation results of considered models are statistically significant at the 95% confidence level, but their accuracy varies from one location to another. However, the multivariable regression relationship deduced in terms of sunshine ratio, air temperature ratio, maximum air temperature, and cloudiness performs better than other relationships. The multivariable relationship has the least root mean square error and mean absolute bias error, not exceeding 1.0854 and 0.8160 MJ m^?2 day^?1, respectively, and monthly relative percentage error in the range of ± 12% for the study areas.     

STREAM TEMPERATURE UNDER AN INADEQUATE BUFFER STRIP IN THE SOUTHEAST PIEDMONT1

ABSTRACT: A paired watershed experiment on the southeastern Piedmont to determine the effect of clearcutting loblolly pine on water quantity, quality, and timing has shown that stream water temperatures we increased as much as 20°F even though a partial buffer strip of trees and shrubs were left in place to shade the stream. Water time minimum stream temperatures were lowered as much as 10°F by the same treatment. A stream temperature model now in use did not predict such elevated temperatures. The authors suggest that forest cover reductions in areas of gentle land relief may elevate the temperature of shallow ground water moving to the stream, even with a substantial buffer strip Ln place.     

Regional and Local Scale Modeling of Stream Temperatures and Spatio-Temporal Variation in Thermal Sensitivities

Understanding variation in stream thermal regimes becomes increasingly important as the climate changes and aquatic biota approach their thermal limits. We used data from paired air and water temperature loggers to develop region-scale and stream-specific models of average daily water temperature and to explore thermal sensitivities, the slopes of air–water temperature regressions, of mostly forested streams across Maryland, USA. The region-scale stream temperature model explained nearly 90 % of the variation (root mean square error = 0.957 °C), with the mostly flat coastal plain streams having significantly higher thermal sensitivities than the steeper highlands streams with piedmont streams intermediate. Model R ² for stream-specific models was positively related to a stream’s thermal sensitivity. Both the regional and the stream-specific air–water temperature regression models benefited from including mean daily discharge from regional gaging stations, but the degree of improvement declined as a stream’s thermal sensitivity increased. Although catchment size had no relationship to thermal sensitivity, steeper streams or those with greater amounts of forest in their upstream watershed were less thermally sensitive. The subset of streams with three or more summers of temperature data exhibited a wide range of annual variation in thermal sensitivity at a site, with the variation not attributable to discharge, precipitation patterns, or physical attributes of streams or their watersheds. Our findings are a useful starting point to better understand patterns in stream thermal regimes. However, a more spatially and temporally comprehensive monitoring network should increase understanding of stream temperature variation and its controls as climatic patterns change.     

Using Landsat data to estimate evapotranspiration of winter wheat

An evapotranspiration (ET) model that accurately estimates daily water use and soil moisture on a regional basis is required for many agricultural and hydrological studies. The model should use meterological data that are readily available and crop information that is responsive to the changing vigor of the plants.We evaluated an ET model with a weighing lysimeter and then applied it to winter wheatfields at four Kansas locations. Model inputs are solar radiation, temperature, precipitation, and leaf area index (LAI); included in the outputs are estimates of transpiration, evaporation, and soil moisture. An equation was developed to estimate LAI from Landsat data. Because LAI can be estimated from satellites, the ET model can potentially be used on a regional basis.     

Using LiDAR Data Analysis to Estimate Changes in Insolation Under Large‐Scale Riparian Deforestation1

Greenberg, Jonathan Asher, Erin L. Hestir, David Riano, George J. Scheer, and Susan L. Ustin, 2012. Using LiDAR Data Analysis to Estimate Changes in Insolation Under Large‐Scale Riparian Deforestation. Journal of the American Water Resources Association (JAWRA) 48(5): 939‐948. DOI: 10.1111/j.1752‐1688.2012.00664.x Abstract: Riparian vegetation provides shade from insolation to stream channels. A consequence of removing vegetation may be an increase in insolation that can increase water temperatures and negatively impact ecosystem health. Although the mechanisms of riparian shading are well understood, spatially explicit, mechanistic models of shading have been limited by the data requirements of precisely describing the three‐dimensional structure of a riparian corridor. Remotely acquired, high spatial resolution LiDAR data provide detailed three‐dimensional vegetation structure and terrain topography over large regions. By parameterizing solar radiation models that incorporate terrain shadowing with LiDAR data, we can produce spatially explicit estimates of insolation. As a case study, we modeled the relative change in insolation on channels in the Sacramento‐San Joaquin River Delta under current conditions and under a hypothesized deforested Delta using classified LiDAR, rasterized at a 1‐m resolution. Our results suggest that the removal of levee vegetation could result in a 9% increase in solar radiation incident on Delta waters, and may lead to water temperature increases. General, coarse‐scale channel characteristics (reach width, azimuth, levee vegetation cover, and height) only accounted for 72% of the variation in the insolation. This indicates that the detailed information derived from LiDAR data has greater explanatory power than coarser reach‐scale metrics often used for insolation estimates.     

GENERATION OF SYNTHETIC AND MISSING CLIMATIC DATA FOR PUERTO RICO1

ABSTRACT: Climatic data such as temperature, solar radiation, relative humidity, and wind speed have been widely used to estimate evapotranspiration. Moat of the solar radiation data and portions of the relative humidity data are either not available or missing from the records in Puerto Rico. Depending upon the availability and data characteristics of records, three methods (including a regression technique, an averaging of historical data, and a regional average) were used to generate missing data, and a time series analysis was used to synthesize a series of climatic data. The limitations and applicability of each method are discussed. The results showed that the time series analysis method can be successfully used to synthesize a series of monthly solar radiations for several stations. The regression technique and the regional average can be successfully applied to generate missing monthly solar radiation data. The regression technique and the averaging of historical data have been satisfactorily used to interpolate missing monthly relative humidity. The explained variance (R²) varied from 0.68 to 0.88, which are both significant at the 0.05 level of significance.     

Enhancing Hyrdological Simulation Program – FORTRAN Model Channel Hydraulic Representation1

Abstract: The hydrological simulation program – FORTRAN (HSPF) is a comprehensive watershed model that employs depth‐area‐volume‐flow relationships known as the hydraulic function table (FTABLE) to represent the hydraulic characteristics of stream channel cross‐sections and reservoirs. An accurate FTABLE determination for a stream cross‐section site requires an accurate determination of mean flow depth, mean flow width, roughness coefficient, longitudinal bed slope, and length of stream reach. A method that uses regional regression equations to estimate mean flow depth, mean flow width, and roughness coefficient is presented herein. FTABLES generated by the proposed method (Alternative Method) and FTABLES generated by Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) were compared. As a result, the Alternative Method was judged to be an enhancement over the BASINS method. First, the Alternative Method employs a spatially variable roughness coefficient, whereas BASINS employs an arbitrarily selected spatially uniform roughness coefficient. Second, the Alternative Method uses mean flow width and mean flow depth estimated from regional regression equations whereas BASINS uses mean flow width and depth extracted from the National Hydrography Dataset (NHD). Third, the Alternative Method offers an option to use separate roughness coefficients for the in‐channel and floodplain sections of compound channels. Fourth, the Alternative Method has higher resolution in the sense that area, volume, and flow data are calculated at smaller depth intervals than the BASINS method. To test whether the Alternative Method enhances channel hydraulic representation over the BASINS method, comparisons of observed and simulated streamflow, flow velocity, and suspended sediment were made for four test watersheds. These comparisons revealed that the method used to estimate the FTABLE has little influence on hydrologic calibration, but greatly influences hydraulic and suspended sediment calibration. The hydrologic calibration results showed that observed versus simulated daily streamflow comparisons had Nash‐Sutcliffe efficiencies ranging from 0.50 to 0.61 and monthly comparisons had efficiencies ranging from 0.61 to 0.84. Comparisons of observed and simulated suspended sediments concentrations had model efficiencies ranging from 0.48 to 0.56 for the daily, and 0.28 to 0.70 for the monthly comparisons. The overall results of the hydrological, hydraulic, and suspended sediment concentration comparisons show that the Alternative Method yielded a relatively more accurate FTABLE than the BASINS method. This study concludes that hydraulic calibration enhances suspended sediment simulation performance, but even greater improvement in suspended sediment calibration can be achieved when hydrological simulation performance is improved. Any improvements in hydrological simulation performance are subject to improvements in the temporal and spatial representation of the precipitation data.     

Prediction of global solar radiation using support vector machines

This article utilizes Support Vector Machines (SVM) for predicting global solar radiation (GSR) for Sharurha, a city in the southwest of Saudi Arabia. The SVM model was trained using measured air temperature and relative humidity. Measured data of 1812 values for the period from 1998–2002 were obtained. The measurement data of 1600 were used for training the SVM, and the remaining 212 were used for comparison between the measured and predicted values of GSR. The GSR values were predicted using the following four combinations of data sets: (i) Daily mean air temperature and day of the year as inputs, and global solar radiation as output; (ii) daily maximum air temperature and day of the year as inputs, and GSR as output; (iii) daily mean air temperature and relative humidity and day of the year as inputs, and GSR as output; and (iv) daily mean air temperature, day of the year, relative humidity, and previous day’s GSR as inputs, and GSR as output. The mean square error was found to be 0.0027, 0.0023, 0.0021, and 7.65 × 10^?4 for case (i), (ii,), (iii), and (iv) respectively, while the corresponding absolute mean percentage errors were 5.64, 5.08, 4.48, and 2.8%. Obtained results show that the SVM method is capable of predicting GSR from measured values of temperature and relative humidity.     

A HYPOTHESIS ABOUT FACTORS THAT AFFECT MAXIMUM SUMMER STREAM TEMPERATURES ACROSS MONTANE LANDSCAPES1

ABSTRACT: Temperature is an important variable structuring lotic biotas, but little is known about how montane landscapes function to determine stream temperatures. We developed an a priori hypothesis that was used to predict how watershed elements would interact to affect stream temperatures. The hypothesis was tested in a series of path analyses using temperature data from 26 sites on second‐order to fourth‐order streams across a fifth‐order Rocky Mountain watershed. Based on the performance of the first hypothesis, two revised versions of the hypothesis were developed and tested that proved to be more accurate than the original hypothesis. The most plausible of the revised hypotheses accounted for 82 percent of the variation in maximum stream temperature, had a predicted data structure that did not deviate from the empirical data structure, and was the most parsimonious. The final working hypothesis suggested that stream temperature maxima were directly controlled by a large negative effect from mean basin elevation (direct effect = ‐0.57, p < 0.01) and smaller effects from riparian tree abundance (direct effect = ‐0.28, p = 0.03), and cattle density (direct effect = 0.24, p = 0.05). Watershed slope, valley constraint, and the abundance of grass across a watershed also affected temperature maxima, but these effects were indirect and mediated through cattle density and riparian trees. Three variables included in the a priori hypothesis ‐ watershed aspect, stream width, and watershed size ‐ had negligible effects on maximum stream temperatures and were omitted from the final working hypothesis.     

PHYSICAL DETERMINANTS OF ECONOMIC VALUE OF RIPARIAN BUFFERS IN AN AGRICULTURAL WATERSHED1

ABSTRACT: Economic values of riparian buffers in a watershed are evaluated by the changes in the net economic return for farming with and without riparian buffers when achieving the same water quality objectives. The simulated water quality impacts of alternative farming systems using SWAT and experimental data for riparian buffers are used in a mathematical optimization model to estimate net economic return for farming subject to a water quality objective. Physical characteristics such as stream length, channel slope, average land slope, cropland percentage and several soil attributes are identified in the watershed using ARC/INFO GIS. A regression model is then used to evaluate the impacts of these physical characteristics on the estimated economic values of buffers. The study is conducted in Goodwater Creek watershed, Missouri. The results show the estimated economic value of buffers is significantly affected by some soil properties, stream length, and cropland percentage in watershed and can be used to improve the effectiveness of riparian buffers at watershed and regional levels.     

Modelling air temperature gradients across managed small streams in western Washington

Leaving riparian strips on both sides of a stream is widely accepted to be an effective management approach in sustaining the valuable functions of stream and riparian ecosystems. The authors' overall objective is to provide microclimatic information for assessing the effectiveness of these strips. During the summer of 1993 and 1994, air temperatures were collected across 20 small, buffered streams in western Washington, USA, including five streams sampled before and after harvesting of the forest. These data were statistically analysed to examine the effects of adjacent harvesting with preservation of 16–72 m riparian forest strips. Regression models were developed to predict air temperatures at the stream and buffer edges, the difference between two locations, and seasonal changes. The authors found: (1) clearcutting in winter 1993/94 increased air temperature on the stream by up to 4°C, and changes in temperature variability from the stream to the upland, measured by coefficient of variation (CV), were significantly higher after harvesting; (2) forest buffers provided minimal protection for stream air temperature during the middle of summer (July) but were more effective early and late in the season; (3) buffer width was not a significant variable in predicting stream air temperature, suggesting that even a 72 m buffer was not sufficient to maintain a stream environment because of greater depth of edge influences.1998 Academic Press