Multi‐site evaluation of hydrology component of SWAT in the coastal plain of southwest Georgia

Simulation of watershed scale hydrologic and water quality processes is important for watershed assessments. Proper characterization of the accuracy of these simulations, particularly in cases with limited observed data, is critical. The Soil & Water Assessment Tool (SWAT) is frequently used for watershed scale simulation. The accuracy of the model was assessed by extrapolating calibration results from a well studied Coastal Plain watershed in Southwest Georgia, USA, to watersheds within the same geographic region without further calibration. SWAT was calibrated and validated on a 16.7‐km² subwatershed within the Little River Experimental Watershed by varying six model parameters. The optimized parameter set was then applied to a watershed of similar land use and soils, a smaller watershed with different land use and soils and three larger watersheds within the same drainage system without further calibration. Simulation results with percent bias (PB) ±15% ≤ PB < ±25% and Nash–Sutcliffe efficiency (NSE) 0.50 < NSE ≤ 0.65 were considered to be satisfactory, whereas those with PB < ±10% and 0.75 < NSE ≤ 1.00 were considered very good. With these criteria, simulation results for the five non‐calibration watersheds were satisfactory to very good. Differences across watersheds were attributed to differences in soils, land use, and surficial aquifer characteristics. These results indicate that SWAT can be a useful tool for predicting streamflow for ungauged watersheds with similar physical characteristics to the calibration watershed studied here and provide an indication of the accuracy of hydrologic simulations for ungauged watersheds. Copyright © 2012 John Wiley & Sons, Ltd.     

Hydrologic comparison between a forested and a wetland/lake dominated watershed using SWAT

The Soil and Water Assessment Tool (SWAT) is a physically‐based hydrologic model developed for agricultural watersheds, which has been infrequently validated for forested watersheds, particularly those with deep overwinter snow accumulation and abundant lakes and wetlands. The goal of this study was to determine the applicability of SWAT for modelling streamflow in two watersheds of the Ontonagon River basin of northern Michigan which differ in proportion of wetland and lake area. The forest‐dominated East Branch watershed contains 17% wetland and lake area, whereas the wetland/lake‐dominated Middle Branch watershed contains 26% wetland and lake area. The specific objectives were to: (1) calibrate and validate SWAT models for the East Branch and Middle Branch watersheds to simulate monthly stream flow, and (2) compare the effects of wetland and lake abundance on the magnitude and timing of streamflow. Model calibration and validation was satisfactory, as determined by deviation of discharge D and Nash and Sutcliffe coefficient values E that compared simulated monthly mean discharge versus measured monthly mean discharge. Streamflow simulation discrepancies occurred during summer and fall months and dry years. Several snow melting parameters were found to be critical for the SWAT simulation: TIMP (snow temperature lag factor) and SMFMX and SMFMN (melting factors). Snow melting parameters were not transferable between adjacent watersheds. Differences in seasonal pattern of long‐term monthly streamflow were found, with the forest‐dominated watershed having a higher peak flow during April but a lower flow during the remainder of the year in comparison to the wetland and lake‐dominated watershed. The results suggested that a greater proportion of wetland and lake area increases the capacity of a watershed to impound surface runoff and to delay storm and snow melting events. Representation of wetlands and lakes in a watershed model is required to simulate monthly stream flow in a wetland/lake‐dominated watershed. Copyright © 2007 John Wiley & Sons, Ltd.     

Predicting phosphorus dynamics in complex terrains using a variable source area hydrology model

Phosphorus (P) loss from agricultural watersheds has long been a critical water quality problem, the control of which has been the focus of considerable research and investment. Preventing P loss depends on accurately representing the hydrological and chemical processes governing P mobilization and transport. The Soil and Water Assessment Tool (SWAT) is a watershed model commonly used to predict run‐off and non‐point source pollution transport. SWAT simulates run‐off employing either the curve number (CN) or the Green and Ampt methods, both assume infiltration‐excess run‐off, although shallow soils underlain by a restricting layer commonly generate saturation‐excess run‐off from variable source areas (VSA). In this study, we compared traditional SWAT with a re‐conceptualized version, SWAT‐VSA, that represents VSA hydrology, in a complex agricultural watershed in east central Pennsylvania. The objectives of this research were to provide further evidence of SWAT‐VSA's integrated and distributed predictive capabilities against measured surface run‐off and stream P loads and to highlight the model's ability to drive sub‐field management of P. Thus, we relied on a detailed field management database to parameterize the models. SWAT and SWAT‐VSA predicted discharge similarly well (daily Nash–Sutcliffe efficiencies of 0.61 and 0.66, respectively), but SWAT‐VSA outperformed SWAT in predicting P export from the watershed. SWAT estimated lower P loss (0.0–0.25 kg ha^?1) from agricultural fields than SWAT‐VSA (0.0–1.0+ kg ha^?1), which also identified critical source areas – those areas generating large run‐off and P losses at the sub‐field level. These results support the use of SWAT‐VSA in predicting watershed‐scale P losses and identifying critical source areas of P loss in landscapes with VSA hydrology. Copyright © 2014 John Wiley & Sons, Ltd.     

Regression‐based approach to low flow prediction in the Maryland Piedmont region under joint climate and land use change

We examine the low flow records for six urbanized watersheds in the Maryland Piedmont region and develop regression equations to predict annual minimum low flow events. The effects of both future climate (based on precipitation and temperature projections from two climate models: Hadley and the Canadian Climate Centre (CCC)) and land use change are incorporated to illustrate possible future trends in low flows. A regression modelling approach is pursued to predict the minimum annual 7‐day low flow estimates for the proposed future scenarios. A regional regression model was calibrated with between 10 and 50 years of daily precipitation, daily average temperature, annual imperviousness, and the daily observed flow time‐series across six watersheds. Future simulations based on a 55 km² urbanizing watershed just north of Washington, DC, were performed. When land use and climate change were employed singly, the former predicted no trends in low flows and the latter predicted significant increasing trends under Hadley and no trends under CCC. When employed jointly, however, low flows were predicted to decrease significantly under CCC, whereas Hadley predicted no significant trends in low flows. Antecedent precipitation was the most influential predictor on low flows, followed by urbanization. Copyright © 2006 John Wiley & Sons, Ltd.     

Nested‐Scale Nutrient Flux in a Mixed‐Land‐Use Urbanizing Watershed

To improve quantitative understanding of mixed‐land‐use impacts on nutrient yields, a nested‐scale experimental watershed study design (n = 5) was applied in a 303(d), clean water act impaired urbanizing watershed of the lower Missouri River Basin, USA. From 2010 to 2013, water samples (n = 858 sample days per site) were analysed for total inorganic nitrogen (TIN‐N), nitrite (NO₂–N) nitrate (NO₃–N), ammonia (NH₃–N), and total phosphorus (TP‐P). Annual, seasonal, and monthly flow‐weighted concentrations (FWCs) and nutrient yields were estimated. Mean nutrient concentrations were highest where agricultural land use comprised 58% of the drainage area (NH₃ = 0.111 mg/l; NO₂ = 0.045 mg/l; NO₃ = 0.684 mg/l, TIN = 0.840 mg/l; TP = 0.127 mg/l). Average TP‐P increased by 15% with 20% increased urban land use area. Highly variable annual precipitation was observed during the study with highest nutrient yields during 2010 (record setting wet year) and lowest nutrient yields during 2012 (extreme drought year). Annual TIN‐N and TP‐P yields exceeded 10.3 and 2.04 kg ha^?1 yr^?1 from the agricultural dominated headwaters. Mean annual NH₃–N, NO₂–N, NO₃–N, TIN‐N, and TP‐P yields were 0.742, 0.400, 4.24, 5.38, and 0.979 kg ha^?1 yr^?1, respectively near the watershed outlet. Precipitation accounted for the majority of the explained variance in nutrient yields (R² values from 0.68 to 0.85). Nutrient yields were also dependent on annual precipitation of the preceding year (R² values from 0.87 to 0.91) thus enforcing the great complexity of variable mixed‐land‐use mediated source‐sink nutrient yield relationships. Study results better inform land managers and best management practices designed to mitigate nutrient pollution issues in mixed‐land‐use freshwater ecosystems. Copyright © 2015 John Wiley & Sons, Ltd.     

Effect of watershed subdivision on simulation of water balance components

The present effect of watershed subdivision on simulated water balance components using the thoroughly tested Soil and Water Assessment Tool (SWAT) model has been evaluated for the Nagwan watershed in eastern India. Observed meteorological and hydrological data (daily rainfall, temperature, relative humidity and runoff) for the years 1995 to 1998 were collected and used. The watershed and sub‐watershed boundaries, slope and soil texture maps were generated using a geographical information system. A supervised classification method was used for land‐use/cover classification from satellite imagery of 1996. In order to study the effect of watershed subdivision, the watershed was spatially defined into three decomposition schemes, namely a single watershed, and 12 and 22 sub‐watersheds. The simulation using the SWAT model was done for a period of 4 years (1995 to 1998). Results of the study showed a perfect water balance for the Nagwan watershed under all of the decomposition schemes. Results also revealed that the number and size of sub‐watersheds do not appreciably affect surface runoff. Except for runoff, there was a marked variation in the individual components of the water balance under the three decomposition schemes. Though the runoff component of the water balance showed negligible variation among the three cases, variations were noticed in the other components: evapotranspiration (5 to 48%), percolation (2 to 26%) and soil water content (0·30 to 22%). Thus, based on this study, it is concluded that watershed subdivision has a significant effect on the water balance components. Copyright © 2005 John Wiley & Sons, Ltd.     

A simple concept for calibrating runoff thresholds in quasi‐distributed variable source area watershed models

Most semi‐distributed watershed water quality models divide the watershed into hydrologic response units (HRU) with no flow among them. This is problematic when watersheds are delineated to include variable source areas (VSAs) because it is the lateral flows from upslope areas to downslope areas that generate VSAs. Although hydrologic modellers have often successfully calibrated these types of models, there can still be considerable uncertainty in model results. In this paper, a topographic‐index‐based method is described and tested to distribute effective soil water holding capacity among HRUs, which can be subsequently adjusted using the watershed baseflow coefficient. The method is tested using a version of the Soil and Water Assessment Tool (SWAT) model that simulates VSA runoff and is applied to two watersheds: a New York State (NYS) watershed, and one in the head waters of the Blue Nile Basin (BNB) in Ethiopia. Daily streamflow predicted using effective soil water storage capacities based only on the topographic index were reassuringly accurate in both the NYS watershed (daily Nash Sutcliffe (E) = 0·73) and in the BNB (E = 0·70). Using the baseflow coefficient to adjust the effective soil water storage capacity only slightly improved streamflow predictions in NYS (E = 0·75) but substantially improved the BNB predictions (E = 0·80). By comparison, the standard SWAT model, which uses the traditional look‐up tables to determine a runoff curve number, performed considerably less accurately in un‐calibrated form (E = 0·51 for NYS and E = 0·45 for BNB), but improved substantially when explicitly calibrated to streamflow measurements (E = 0·76 for NYS and E = 0·67 for the BNB). The calibration method presented here provides a parsimonious, systematic approach to using established models in VSA watersheds that reduces the ambiguity inherent in model calibration. Copyright © 2011 John Wiley & Sons, Ltd.     

Comparison of AnnAGNPS and SWAT model simulation results in USDA‐CEAP agricultural watersheds in south‐central Kansas

This study was conducted under the USDA‐Conservation Effects Assessment Project (CEAP) in the Cheney Lake watershed in south‐central Kansas. The Cheney Lake watershed has been identified as ‘impaired waters’ under Section 303(d) of the Federal Clean Water Act for sediments and total phosphorus. The USDA‐CEAP seeks to quantify environmental benefits of conservation programmes on water quality by monitoring and modelling. Two of the most widely used USDA watershed‐scale models are Annualized AGricultural Non‐Point Source (AnnAGNPS) and Soil and Water Assessment Tool (SWAT). The objectives of this study were to compare hydrology, sediment, and total phosphorus simulation results from AnnAGNPS and SWAT in separate calibration and validation watersheds. Models were calibrated in Red Rock Creek watershed and validated in Goose Creek watershed, both sub‐watersheds of the Cheney Lake watershed. Forty‐five months (January 1997 to September 2000) of monthly measured flow and water quality data were used to evaluate the two models. Both models generally provided from fair to very good correlation and model efficiency for simulating surface runoff and sediment yield during calibration and validation (correlation coefficient; R², from 0·50 to 0·89, Nash Sutcliffe efficiency index, E, from 0·47 to 0·73, root mean square error, RMSE, from 0·25 to 0·45 m³ s^?1 for flow, from 158 to 312 Mg for sediment yield). Total phosphorus predictions from calibration and validation of SWAT indicated good correlation and model efficiency (R² from 0·60 to 0·70, E from 0·63 to 0·68) while total phosphorus predictions from validation of AnnAGNPS were from unsatisfactory to very good (R² from 0·60 to 0·77, E from ? 2·38 to 0·32). The root mean square error–observations standard deviation ratio (RSR) was estimated as excellent (from 0·08 to 0·25) for the all model simulated parameters during the calibration and validation study. The percentage bias (PBIAS) of the model simulated parameters varied from unsatisfactory to excellent (from 128 to 3). This study determined SWAT to be the most appropriate model for this watershed based on calibration and validation results. Copyright © 2008 John Wiley & Sons, Ltd.     

Using equilibrium temperature to assess thermal disturbances in rivers

Flow regulation is widely known to modify the thermal regime of rivers. Here, we examine the sensitivity of an empirical approach, the Equilibrium Temperature Concept (ETC), to detect both the effects of hydraulic infrastructures on the annual thermal cycle and the recovery of the thermal equilibrium with the atmosphere. Analysis was undertaken in a Pyrenean river (the Noguera Pallaresa, Ebro basin) affected by a series of reservoirs and hydropower plants. Equilibrium temperature (T_e) is defined as the water temperature (T_w) at which the sum of all heat fluxes is zero. Based on the assumption of a linear relationship between T_e and T_w, we identified changes in the T_e–T_w regression slope, used as an indicator of a thermal alteration in river flow. We also assessed the magnitude of the alteration by examining the regression slope and its statistical significance. Variations in the regression parameters were used as indicators of the influence of factors other than atmospheric conditions on water temperature. Observed T_w showed a linear relationship with T_e at all river stations. However, the slopes of the T_e–T_w relationship appeared to be lower in the reaches downstream from hydraulic infrastructures, particularly below large dams. A seasonal analysis indicated that T_e–T_w relationships had higher slopes and lower p‐values during autumn, while no significant differences were found at other seasons. Although thermal characteristics did not strongly depend on atmospheric conditions downstream of hydraulic infrastructures, the river recovered to pre‐alteration conditions with distance downstream, indicating the natural tendency of water to attain thermal equilibrium with the atmosphere. Accepting associated uncertainties, mostly because of the quality of the data and the lack of consideration of other factors influencing the thermal regime (e.g. discharge), ETC appears to be a simple and effective method to identify thermal alterations in regulated rivers. Copyright © 2015 John Wiley & Sons, Ltd.     

A multimodel comparison for assessing water temperatures under changing climate conditions via the equilibrium temperature concept: case study of the Middle Loire River,France

This paper investigates three categories of models that are derived from the equilibrium temperature concept to estimate water temperatures in the Loire River in France and the sensitivity to changes in hydrology and climate. We test the models' individual performances for simulating water temperatures and assess the variability of the thermal responses under the extreme changing climate scenarios that are projected for 2081–2100. We attempt to identify the most reliable models for studying the impact of climate change on river temperature (T_w). Six models are based on a linear relationship between air temperatures (T_a) and equilibrium temperatures (T_e), six depend on a logistic relationship, and six rely on the closure of heat budgets. For each category, three approaches that account for the river's thermal exchange coefficient are tested. In addition to air temperatures, an index of day length is incorporated to compute equilibrium temperatures. Each model is analysed in terms of its ability to simulate the seasonal patterns of river temperatures and heat peaks. We found that including the day length as a covariate in regression‐based approaches improves the performance in comparison with classical approaches that use only T_a. Moreover, the regression‐based models that rely on the logistic relationship between T_e and T_a exhibit root mean square errors comparable (0.90 °C) with those obtained with a classical five‐term heat budget model (0.82 °C), despite a small number of required forcing variables. In contrast, the regressive models that are based on a linear relationship T_e = f(T_a) fail to simulate the heat peaks and are not advisable for climate change studies. The regression‐based approaches that are based on a logistic relationship and the heat balance approaches generate notably similar responses to the projected climate changes scenarios. This similarity suggests that sophisticated thermal models are not preferable to cruder ones, which are less time‐consuming and require fewer input data. Copyright © 2012 John Wiley & Sons, Ltd.     

Calibration of paired watersheds: Utility of moving sums in presence of externalities

Historically, paired watershed studies have been used to quantify the hydrological effects of land use and management practices by concurrently monitoring 2 similar watersheds during calibration (pretreatment) and post‐treatment periods. This study characterizes seasonal water table and flow response to rainfall during the calibration period and tests a change detection technique of moving sums of recursive residuals (MOSUM) to select calibration periods for each control–treatment watershed pair when the regression coefficients for daily water table elevation were most stable to minimize regression model uncertainty. The control and treatment watersheds were 1 watershed of 3–4‐year‐old intensely managed loblolly pine (Pinus taeda L.) with natural understory, 1 watershed of 3–4‐year‐old loblolly pine intercropped with switchgrass (Panicum virgatum), 1 watershed of 14–15‐year‐old thinned loblolly pine with natural understory (control), and 1 watershed of switchgrass only. The study period spanned from 2009 to 2012. Silvicultural operational practices during this period acted as external factors, potentially shifting hydrologic calibration relationships between control and treatment watersheds. MOSUM results indicated significant changes in regression parameters due to silvicultural operations and were used to identify stable relationships for water table elevation. None of the calibration relationships developed using this method were significantly different from the classical calibration relationship based on published historical data. We attribute that to the similarity of historical and 2010–2012 leaf area index on control and treatment watersheds as moderated by the emergent vegetation. Although the MOSUM approach does not eliminate the need for true calibration data or replace the classic paired watershed approach, our results show that it may be an effective alternative approach when true data are unavailable, as it minimizes the impacts of external disturbances other than the treatment of interest.     

Incorporating landscape depression heterogeneity into the Soil and Water Assessment Tool (SWAT) using a probability distribution

Modelling the hydrology of North American Prairie watersheds is complicated because of the existence of numerous landscape depressions that vary in storage capacity. The Soil and Water Assessment Tool (SWAT) is a widely applied model for long‐term hydrological simulations in watersheds dominated by agricultural land uses. However, several studies show that the SWAT model has had limited success in handling prairie watersheds. In past works using SWAT, landscape depression storage heterogeneity has largely been neglected or lumped. In this study, a probability distributed model of depression storage is introduced into the SWAT model to better handle landscape storage heterogeneity. The work utilizes a probability density function to describe the spatial heterogeneity of the landscape depression storages that was developed from topographic characteristics. The integrated SWAT–PDLD model is tested using datasets for two prairie depression dominated watersheds in Canada: the Moose Jaw River watershed, Saskatchewan; and the Assiniboine River watershed, Saskatchewan. Simulation results were compared to observed streamflow using graphical and multiple statistical criterions. Representation of landscape depressions within SWAT using a probability distribution (SWAT–PDLD) provides improved estimations of streamflow for large prairie watersheds in comparison to results using a lumped, single storage approach. Copyright © 2016 John Wiley & Sons, Ltd.     

Stream temperature response to variable glacier coverage in coastal watersheds of Southeast Alaska

We measured stream temperature continuously during the 2011 summer run‐off season (May through October) in nine watersheds of Southeast Alaska that provide spawning habitat for Pacific salmon. The nine watersheds have glacier coverage ranging from 0% to 63%. Our goal was to determine how air temperature and watershed land cover, particularly glacier coverage, influence stream temperature across the seasonal glacial meltwater hydrograph. Multiple linear regression models identified mean watershed elevation (related to glacier extent) and watershed lake coverage (%) as the strongest landscape controls on mean monthly stream temperature, with the weakest (May) and strongest (July) models explaining 86% and 97% of the temperature variability, respectively. Mean weekly stream temperature was significantly correlated with mean weekly air temperature in seven streams; however, the relationships were weak to non‐significant in the streams influenced by glacial run‐off. Streams with >30% glacier coverage showed decreasing stream temperatures with rising summer air temperatures, whereas those with <30% glacier coverage exhibited summertime warming. Glaciers also had a cooling effect on monthly mean stream temperature during the summer (July through September) equivalent to a decrease of 1.1 °C for each 10% increase in glacier coverage. The maximum weekly average temperature (an index of thermal suitability for salmon) in the six glacial streams was substantially below the lower threshold for optimum salmon growth. This finding suggests that although glaciers are important for moderating summer stream temperatures, future reductions in glacier run‐off may actually improve the thermal suitability of some glacially dominated streams in Southeast Alaska for salmon. Copyright © 2013 John Wiley & Sons, Ltd.     

Short‐term stream water temperature observations permit rapid assessment of potential climate change impacts

Assessment of potential climate change impacts on stream water temperature (T_s) across large scales remains challenging for resource managers because energy exchange processes between the atmosphere and the stream environment are complex and uncertain, and few long‐term datasets are available to evaluate changes over time. In this study, we demonstrate how simple monthly linear regression models based on short‐term historical T_s observations and readily available interpolated air temperature (T_a) estimates can be used for rapid assessment of historical and future changes in T_s. Models were developed for 61 sites in the southeastern USA using ≥18 months of observations and were validated at sites with longer periods of record. The T_s models were then used to estimate temporal changes in T_s at each site using both historical estimates and future T_a projections. Results suggested that the linear regression models adequately explained the variability in T_s across sites, and the relationships between T_s and T_a remained consistent over 37 years. We estimated that most sites had increases in historical annual mean T_s between 1961 and 2010 (mean of +0.11 °C decade^?1). All 61 sites were projected to experience increases in T_s from 2011 to 2060 under the three climate projections evaluated (mean of +0.41 °C decade^?1). Several of the sites with the largest historical and future T_s changes were located in ecoregions home to temperature‐sensitive fish species. This methodology can be used by resource managers for rapid assessment of potential climate change impacts on stream water temperature. Copyright © 2014 John Wiley & Sons, Ltd.     

An improved process-based representation of stream solute transport in the soil and water assessment tools

Hydrological models have long been used to study the interactions between land, surface and groundwater systems, and to predict and manage water quantity and quality. The soil and water assessment tool (SWAT), a widely used hydrological model, can simulate various ecohydrological processes on land and subsequently route the water quality constituents through surface and subsurface waters. So far, in-stream solute transport algorithms of the SWAT model have only been minimally revised, even though it has been acknowledged that an improvement of in-stream process representation can contribute to better model performance with respect to water quality. In this study, we aim to incorporate a new and improved solute transport model into the SWAT model framework. The new process-based model was developed using in-stream process equations from two well established models—the One-dimensional Transport with Inflow and Storage model and the Enhanced Stream Water Quality Model. The modified SWAT model (Mir-SWAT) was tested for water quality predictions in a study watershed in Germany. Compared to the standard SWAT model, Mir-SWAT improved dissolved oxygen (DO) predictions by removing extreme low values of DO (<6 mg/L) simulated by SWAT. Phosphate concentration peaks were reduced during high flows and a better match of daily predicted and measured values was attained using the Mir-SWAT model (R² = 0.17, NSE = −0.65, RSR = 1.29 with SWAT; R² = 0.28, NSE = −0.04, RSR = 1.02 with Mir-SWAT). In addition, Mir-SWAT performed better than the SWAT model in terms of Chlorophyll-a content particularly during winter months, improving the NSE and RSR for monthly average Chl-a by 74 and 42%, respectively. With the new model improvements, we aim to increase confidence in the stream solute transport component of the model, improve the understanding of nutrient dynamics in the stream, and to extend the applicability of SWAT for reach-scale analysis and management.     

Hydrologic metrics for status‐and‐trends monitoring in urban and urbanizing watersheds

Local governmental agencies are increasingly undertaking potentially costly “status‐and‐trends” monitoring to evaluate the effectiveness of stormwater control measures and land‐use planning strategies or to satisfy regulatory requirements. Little guidance is presently available for such efforts, and so we have explored the application, interpretation, and temporal limitations of well‐established hydrologic metrics of runoff changes from urbanization, making use of an unusually long‐duration, high‐quality data set from the Pacific Northwest (USA) with direct applicability to urban and urbanizing watersheds. Three metrics previously identified for their utility in identifying hydrologic conditions with biological importance that respond to watershed urbanization—T_Qmean (the fraction of time that flows exceed the mean annual discharge), the Richards‐Baker Index (characterizing flashiness relative to the mean discharge), and the annual tally of wet‐season day‐to‐day flow reversals (the total number of days that reverse the prior days' increasing or decreasing trend)—are all successful in stratifying watersheds across a range of urbanization, as measured by total contributing area of urban development. All metrics respond with statistical significance to multidecadal trends in urbanization, but none detect trends in watershed‐scale urbanization over the course of a single decade. This suggests a minimum period over which dependable trends in hydrologic alteration (or improvement) can be detected with confidence. The metrics also prove less well suited to urbanizing watersheds in a semi‐arid climate, with only flow reversals showing a response consistent with prior findings from more humid regions. We also explore the use of stage as a surrogate for discharge in calculating these metrics, recognizing potentially significant agency cost savings in data collection with minimal loss of information. This approach is feasible but cannot be implemented under current data‐reporting practices, requiring measurement of water‐depth values and preservation of the full precision of the original recorded data. With these caveats, however, hydrologic metrics based on stage should prove as or more useful, at least in the context of status‐and‐trends monitoring, as those based on subsequent calculations of discharge.     

Effects of Watershed Land Use and Lake Morphometry on the Trophic State of Chinese Lakes: Implications for Eutrophication Control

Water quality in lakes is influenced by a large number of watershed and lake characteristics. In this study, we examined the relative effects of watershed land use and lake morphology on the trophic state of 19 lakes in the Yunnan plateau and lower Yangtze floodplain, the two most eutrophic regions in China. Trophic state parameters consisted of total nitrogen, total phosphorus, chemical oxygen demand, chlorophyll‐a, Secchi depth, and trophic state index, while lake morphometric variables included area, maximum depth, mean depth, water residence time (WRT), volume, and length to width ratio. Percentages of forest, grassland, cropland, unused land, built‐up land, and water body in each lake's watershed were extracted from a land use map interpreted from Landsat TM images. A t‐test indicated that lower Yangtze floodplain lakes were shallower and had higher percentages of cropland and built‐up land in watersheds than Yunnan plateau lakes. Pearson's correlation analysis indicated that both watershed land use and lake morphometric variables were significantly related to most of the trophic state parameters. However, stepwise regression analyses demonstrated that the trophic state of the lower Yangtze floodplain lakes was mainly controlled by the percentages of cropland and built‐up land in watersheds, while that of Yunnan plateau lakes was mostly determined by the lake depth and WRT. These results suggest that the relative effects of watershed land use and lake morphology on lake trophic state are dependent on the lake's location. This study can provide some useful information in watershed land use management for controlling eutrophication in Chinese lakes.     

Evaluating the impacts of climate change and switchgrass production on a semiarid basin

Climate and land use changes greatly modify hydrologic regimes. In this paper, we modelled the impacts of biofuel cultivation in the US Great Plains on a 1061‐km² watershed using the Soil and Water Assessment Tool (SWAT) hydrologic model. The model was calibrated to monthly discharges spanning 2002–2010 and for the winter, spring, and summer seasons. SWAT was then run for a climate‐change‐only scenario using downscaled precipitation and a projected temperature for 16 general circulation model (GCM) runs associated with the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios A2 scenario spanning 2040–2050. SWAT was also run on a climate change plus land use change scenario in which Alamo switchgrass (Panicum virgatum L.) replaced native range grasses, winter wheat, and rye (89% of the basin). For the climate‐change‐only scenario, the GCMs agreed on a monthly temperature increase of 1–2 °C by the 2042–2050 period, but they disagreed on the direction of change in precipitation. For this scenario, decreases in surface runoff during all three seasons and increases in spring and summer evapotranspiration (eT) were driven predominantly by precipitation. Increased summer temperatures also significantly contributed to changes in eT. With the addition of switchgrass, changes in surface runoff are amplified during the winter and summer, and changes in eT are amplified during all three seasons. Depending on the GCM utilized, either climate change or land use change (switchgrass cultivation) was the dominant driver of change in surface runoff while switchgrass cultivation was the major driver of changes in eT. Copyright © 2014 John Wiley & Sons, Ltd.     

Climate change sensitivity assessment of streamflow and agricultural pollutant transport in California's Central Valley using Latin hypercube sampling

Bracketing the uncertainty of streamflow and agricultural runoff under climate change is critical for proper future water resource management in agricultural watersheds. This study used the Soil and Water Assessment Tool (SWAT) in conjunction with a Latin hypercube climate change sampling algorithm to construct a 95% confidence interval (95CI) around streamflow, sediment load, and nitrate load predictions under changes in climate for the Sacramento and San Joaquin River watersheds in California's Central Valley. The Latin hypercube algorithm sampled 2000 combinations of precipitation and temperature changes based on Intergovernmental Panel on Climate Change projections from multiple General Circulation Models. Average monthly percent changes of the upper and lower 95CI limits compared to the present‐day simulation and a statistic termed the “r‐factor” (average width of the 95CI band divided by the standard deviation of the 95CI bandwidth) were used to assess watershed sensitivities. 95CI results indicate that streamflow and sediment runoff in the Sacramento River watershed are more likely to decrease under climate change compared to present‐day conditions, whereas the increase and decrease for nitrate runoff were found to be equal. For the San Joaquin River watershed, streamflow slightly decreased under climate change, whereas sediment and nitrate runoff increased compared to present‐day climate. Comparisons of watershed sensitivities indicate that the San Joaquin River watershed is more sensitive to climate changes than the Sacramento River watershed, which is largely caused by the high density of agricultural land. Copyright © 2012 John Wiley & Sons, Ltd.