Regionalization of constraints on expected watershed response behavior for improved predictions in ungauged basins

Approaches to modeling the continuous hydrologic response of ungauged basins use observable physical characteristics of watersheds to either directly infer values for the parameters of hydrologic models, or to establish regression relationships between watershed structure and model parameters. Both these approaches still have widely discussed limitations, including impacts of model structural uncertainty. In this paper we introduce an alternative, model independent, approach to streamflow prediction in ungauged basins based on empirical evidence of relationships between watershed structure, climate and watershed response behavior. Instead of directly estimating values for model parameters, different hydrologic response behaviors of the watershed, quantified through model independent streamflow indices, are estimated and subsequently regionalized in an uncertainty framework. This results in expected ranges of streamflow indices in ungauged watersheds. A pilot study using 30 UK watersheds shows how this regionalized information can be used to constrain ensemble predictions of any model at ungauged sites. Dominant controlling characteristics were found to be climate (wetness index), watershed topography (slope), and hydrogeology. Main streamflow indices were high pulse count, runoff ratio, and the slope of the flow duration curve. This new approach provided sharp and reliable predictions of continuous streamflow at the ungauged sites tested.     

Impacts of projected climate change on sediment yield and dredging costs

Changes in climate may significantly affect how sediment moves through watersheds into harbours and channels that are dredged for navigation or flood control. Here, we applied a hydrologic model driven by a large suite of climate change scenarios to simulate both historical and future sediment yield and transport in two large, adjacent watersheds in the Great Lakes region. Using historical dredging expenditure data from the U.S. Army Corps of Engineers, we then developed a pair of statistical models that link sediment discharge from each river to dredging costs at the watershed outlet. Although both watersheds show similar slight decreases in streamflow and sediment yield in the near‐term, by Mid‐Century, they diverge substantially. Dredging costs are projected to change in opposite directions for the two watersheds; we estimate that future dredging costs will decline in the St. Joseph River by 8–16% by Mid‐Century but increase by 1–6% in the Maumee River. Our results show that the impacts of climate change on sediment yield and dredging may vary significantly by watershed even within a region and that agricultural practices will play a large role in determining future streamflow and sediment loads. We also show that there are large variations in responses across climate projections that cause significant uncertainty in sediment and dredging projections.     

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.     

Rainstorm-generated sediment yield model based on soil moisture proxies (SMP)

This study develops improved Soil Moisture Proxies (SMP) based suspended sediment yield (SMPSY) models corresponding to three antecedent moisture conditions (AMCs) (i.e., AMC-I-AMC-III) by coupling the improved initial abstraction (I_a-λ) model, the SMA procedure and the SMP concept for modelling the rainfall generated suspended sediment yield. The SMPSY models specifically incorporate a watershed storage index (S) model to accentuate the transformation from storm to storm and to avoid the sudden jumps in sediment yield computation. The workability of the SMPSY models is tested using a large dataset of rainfall and sediment yield (98 storm events) from twelve small watersheds and a comparison has been made with the existing MSY model. The goodness-of-fit (GOF) statistics is evaluated in terms of the Nash Sutcliffe efficiency (NSE), and error indices, i.e., root mean square error (RMSE), normalized root mean square error (nRMSE), standard error (SE), mean absolute error (MAE), and RMSE-observations standard deviation ratio (RSR). The NSE values vary from 74.31% to 96.57% and from 75.21% to 91.78%, respectively for the SPMSY and MSY model. The NSE statistics indicate that the SMPSY model has lower uncertainty in simulating sediment yield as compared to the MSY model. The error indices are lower for the SMPSY model than the MSY model for most of the watersheds. These results show that the SMPSY model has less uncertainty and performs better than the MSY model. A sensitivity analysis of the SMPSY model shows that the parameter β is most sensitive followed by parameter S, α and A. Overall, the results show that the characterization of soil moisture variability in terms of SMPs and incorporation of improved delivery ratio and runoff coefficient relationship improves the simulation of the erosion and sediment yield generation process.     

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.     

A framework to estimate sediment loads using distributions with covariates: Beaurivage River watershed (Québec,Canada)

A framework to estimate sediment loads based on the statistical distribution of sediment concentrations and various functional forms relating distribution characteristics (e.g. mean and variance) to covariates is developed. The covariates are used as surrogates to represent the main processes involved in sediment generation and transport. Statistical models of increasing complexity are built and compared to assess their relative performance using available sediment concentration and covariate data. Application to the Beaurivage River watershed (Québec, Canada) is conducted using data for the 1989–2004 period. The covariates considered in this application are streamflow and calendar day. A comparison of different statistical models shows that, in this case, the log‐normal distribution with a mean value depending on streamflow (power law with an additive term) and calendar day (sinusoidal), a constant coefficient of variation for streamflow dependence and a constant standard deviation for calendar day dependence provide the best result. Model parameters are estimated using the maximum likelihood estimation technique. The selected model is then used to estimate the distribution of annual sediment loads for the Beaurivage River watershed for a selected period. A bootstrap parametric method is implemented to account for uncertainties in parameter values and to build the distributions of annual loads. Comparison of model results with estimates obtained using the empirical ratio estimator shows that the latter were rarely within the 0·1–0·9 quantile interval of the distributions obtained with the proposed approach. Copyright © 2008 John Wiley & Sons, Ltd.     

WATERSHED SEDIMENT YIELD AND RANGELAND HEALTH

lINTRoDUCTIoNDifferencesintheprevailinglanduseandmanagementofaridandsemiaridareasaredeterminedinlargepartbyclimate.AridareasgenerallyreceivetoolittleprecipitationtosupportdrylandagricultureordomesticlivestockgrazingalthoughtheyaregrazedbywildIife,andattimes,bydomesticlivestock.Incontrast,insemiaridareasadequatemoistureisusuallyavaiIableatsometimeduringtheyeartoproduceforageforlivestockandwildlife,andtherearesomeyearswhendrylandcropproductionissuccessful.However,bothclimatesarecharacterize…     

Assessing effects of model complexity and structure on predictions of hydrological responses using serial and parallel model design

By utilizing functional relationships based on observations at plot or field scales, water quality models first compute surface runoff and then use it as the primary governing variable to estimate sediment and nutrient transport. When these models are applied at watershed scales, this serial model structure, coupling a surface runoff sub-model with a water quality sub-model, may be inappropriate because dominant hydrological processes differ among scales. A parallel modeling approach is proposed to evaluate how best to combine dominant hydrological processes for predicting water quality at watershed scales. In the parallel scheme, dominant variables of water quality models are identified based entirely on their statistical significance using time series analysis. Four surface runoff models of different model complexity were assessed using both the serial and parallel approaches to quantify the uncertainty on forcing variables used to predict water quality. The eight alternative model structures were tested against a 25-year high-resolution data set of streamflow, suspended sediment discharge, and phosphorous discharge at weekly time steps. Models using the parallel approach consistently performed better than serial-based models, by having less error in predictions of watershed scale streamflow, sediment and phosphorus, which suggests model structures of water quantity and quality models at watershed scales should be reformulated by incorporating the dominant variables. The implication is that hydrological models should be constructed in a way that avoids stacking one sub-model with one set of scale assumptions onto the front end of another sub-model with a different set of scale assumptions.     

Streamflow forecasting in remote areas

Forecasts of runoff volumes are required in order to maximize the utility of water-supply sources. In remote areas where hydrologic and land-use data are sparse, forecast models are needed; such models should be conceptually rational so they can be transferred to remote watersheds where data are sparse. A series of models were calibrated for a large watershed in India. A spatially-distributed seasonally-varying model having a structure similar to the rational method was found to provide precise, unbiased estimates of 10-day streamflow volumes. The model was tested on a watershed that was not used for calibration, with the results indicating a high correlation between the observed and measured streamflow. Thus, the model should provide good estimates of streamflow volumes on other ungaged watersheds.     

Fifty-eight years and counting of watershed science at the Caspar Creek Experimental Watersheds in northern California

The Caspar Creek Experimental Watersheds are the site of a long-term paired watershed study in the northern Coast Ranges of California. The watersheds are predominately forested with coast redwood and Douglas-fir. Old-growth forest was logged between 1860 and 1904. Two harvesting experiments have been completed since then and a third experiment is currently underway. Caspar Creek data are split into three phases corresponding to three experiments: Phase 1 (1962–1985) reports on a selection harvest (1971–1973) and initial recovery in the South Fork watershed; Phase 2 (1985–2017) includes clearcut harvesting of ~50% of the North Fork watershed (1985–1992) and recovery; and Phase 3 (2017 onward) corresponds to a second selection harvest in the South Fork watershed with a range of subwatershed harvest intensities (2017–2019) and recovery. All three experiments included harvest-related road-building and relied primarily on measurements of streamflow and sediment delivery from both treated and reference watersheds. Major findings include modest increases in post-harvest peak flows and cumulative flow volumes, post-harvest low flows that initially increased and then decreased 12 to 15 years after harvesting, and the consequences of different yarding techniques and road design on sediment yields. Some of the data for Phase 1 and Phase 2 are available in a USDA Forest Service online archive. The archived data include precipitation, streamflow, suspended sediment concentrations, turbidity, accumulated weir pond sediment volumes, bedload transport rates, water stable isotope data, and geospatial data. Archiving activities are ongoing. Phase 3 data are currently being collected and will be archived after a post-harvest monitoring period.     

Modelling changes in suspended sediment from forest road surfaces in a coastal watershed of British Columbia

Erosion from logging road surfaces, cut slopes, banks, and ditches represents a chronic source of sediment input to streams that can degrade aquatic habitats. Road surface erosion is of particular concern because the magnitude of sediment generation when traffic levels are high can be large. Current models for predicting sediment production from roads require information on area‐specific sediment delivery, which is not often available. Here, we developed a model to quantify suspended sediment concentrations (SSC) generated by forest roads surfaces under different conditions of use and density. This model is designed for a typical medium‐size coastal watershed of British Columbia or the American Pacific Northwest, and was applied to the Chilliwack River watershed as a case study. The results illustrate that intensive use of forest roads combined with high road density can increase the number of extreme sedimentation events over a predetermined threshold. A comparison of the effects of road density and the level of road use suggests that the level of road use is more important than the road density for the generation of fine sediment from road surfaces. However, the model omits the impact of roads on mass movements in a watershed, which represent a major source of sediment in steep watersheds, so the effect of road density is likely more substantial than the model predicts. The model is an attempt to overcome field data limitations by using an empirical relation between SSC and traffic variables, and presents a starting point for more intensive field studies that could be used to validate it. Copyright © 2013 John Wiley & Sons, Ltd.     

How much complexity is needed to simulate watershed streamflow and water quality? A test combining time series and hydrological models

Modelled hydrologic processes are represented in a set of numerical equations; the complexity of which can be measured by the total number of variables needed. A single dominant hydrologic process could control the hydrologic response of a watershed, and so the identification of the corresponding dominant variable(s) would aid in identifying a parsimonious model and in collecting more reliable data. By accounting for both model complexity and serial correlation in the variables, a model is used to identify the dominant variables for representing watershed scale streamflow, sediment transport and phosphorus yields. Long‐term water quantity and quality data were used to show that rainfall and non‐linear soil water storage were the dominant variables for weekly streamflow, suspended sediment and particulate phosphorus. Model accuracy did not consistently improve when other statistically significant variables were included. The results suggest that improved model performance may not justify the added model complexity. As such, identification of dominant variables would be the priority for developing parsimonious hydrologic models, especially at watershed scales. Copyright © 2013 John Wiley & Sons, Ltd.     

Assessment of suspended sediment transport in four alpine watersheds (France): influence of the climatic regime

High‐frequency water discharge and suspended sediment concentration (SSC) databases were collected for 3 years on four contrasted watersheds: the Asse and the Bléone (two Mediterranean rainfall regime watersheds) and the Romanche and the Ferrand (two rainfall–snowmelt regime watersheds). SSCs were calculated from turbidity recordings (1‐h time step), converted into SSC values. The rating curve was calculated by means of simultaneous SSC measurement taken by water sampling and turbidity recording. Violent storms during springtime and autumn were responsible for suspended sediment transport on the Asse and the Bléone rivers. On the Ferrand and the Romanche, a large share of suspended sediment transport was also caused by local storms, but 30% of annual fluxes results from snowmelt or icemelt which occurred from April to October. On each watershed, SSC up to 50 g l^?1 were observed. Annual specific fluxes ranged from 450 to 800 t km^?2 year^?1 and 40–80% of annual suspended sediment fluxes occurred within 2% of the time. These general indicators clearly demonstrate the intensity of suspended sediment transport on these types of watersheds. Suspended sediment fluxes proved to be highly variable at the annual scale (inter‐annual variability of specific fluxes) as well as at the event scale (through a hysteresis loop in the SSC/Q relationship) on these watersheds. In both cases, water discharge and precipitations were the main processes involved in suspended sediment production and transport. The temporal and spatial variability of hydro‐meteorological processes on the watershed provides a better understanding of suspended sediment dynamics. Copyright © 2009 John Wiley & Sons, Ltd.     

Distributed discharge and sediment concentration predictions in the sub‐humid Ethiopian highlands: the Debre Mawi watershed

Experimental research in the Ethiopian highlands found that saturation excess induced runoff and erosion are common in the sub‐humid conditions. Because most erosion simulation models applied in the highlands are based on infiltration excess, we, as an alternative, developed the Parameter Efficient Distributed (PED) model, which can simulate water and sediment fluxes in landscapes with saturation excess runoff. The PED model has previously only been tested at the outlet of a watershed and not for distributed runoff and sediment concentration within the watershed. In this study, we compare the distributed storm runoff and sediment concentration of the PED model against collected data in the 95‐ha Debre Mawi watershed and three of its nested sub‐watersheds for the 2010 and 2011 rainy seasons. In the PED model framework, the hydrology of the watershed is divided between infiltrating and runoff zones, with erosion only taking place from two surface runoff zones. Daily storm runoff and sediment concentration values, ranging from 0.5 to over 30 mm and from 0.1 to 35 g l^?1, respectively, were well simulated. The Nash Sutcliffe efficiency values for the daily storm runoff for outlet and sub‐watersheds ranged from 0.66 to 0.82, and the Nash–Sutcliffe efficiency for daily sediment concentrations were greater than 0.78. Furthermore, the model uses realistic fractional areas for surface and subsurface flow contributions, for example between saturated areas (15%), degraded areas (30%) and permeable areas (55%) at the main outlet, while close similarity was found for the remaining hydrology and erosion parameter values. One exception occurred for the distinctly greater transport limited parameter at the actively gullying lower part of the watershed. The results suggest that the model based on saturation excess provides a good representation of the observed spatially distributed runoff and sediment concentrations within a watershed by modelling the bottom lands (as opposed to the uplands) as the dominant contributor of the runoff and sediment load. Copyright © 2014 John Wiley & Sons, Ltd.     

Simulated water budget of a small forested watershed in the continental/maritime hydroclimatic region of the United States

Annual streamflows have decreased across mountain watersheds in the Pacific Northwest of the United States over the last ~70 years; however, in some watersheds, observed annual flows have increased. Physically based models are useful tools to reveal the combined effects of climate and vegetation on long‐term water balances by explicitly simulating the internal watershed hydrological fluxes that affect discharge. We used the physically based Simultaneous Heat and Water (SHAW) model to simulate the inter‐annual hydrological dynamics of a 4 km² watershed in northern Idaho. The model simulates seasonal and annual water balance components including evaporation, transpiration, storage changes, deep drainage, and trends in streamflow. Independent measurements were used to parameterize the model, including forest transpiration, stomatal feedback to vapour pressure, forest properties (height, leaf area index, and biomass), soil properties, soil moisture, snow depth, and snow water equivalent. No calibrations were applied to fit the simulated streamflow to observations. The model reasonably simulated the annual runoff variations during the evaluation period from water year 2004 to 2009, which verified the ability of SHAW to simulate the water budget in this small watershed. The simulations indicated that inter‐annual variations in streamflow were driven by variations in precipitation and soil water storage. One key parameterization issue was leaf area index, which strongly influenced interception across the catchment. This approach appears promising to help elucidate the mechanisms responsible for hydrological trends and variations resulting from climate and vegetation changes on small watersheds in the region. Copyright © 2015 John Wiley & Sons, Ltd.     

Suspended sediment estimation using neuro-fuzzy and neural network approaches/Estimation des matières en suspension par des approches neurofloues et à base de réseau de neurones

Abstract

The abilities of neuro-fuzzy (NF) and neural network (NN) approaches to model the streamflow–suspended sediment relationship are investigated. The NF and NN models are established for estimating current suspended sediment values using the streamflow and antecedent sediment data. The sediment rating curve and multi-linear regression are also applied to the same data. Statistic measures were used to evaluate the performance of the models. The daily streamflow and suspended sediment data for two stations—Quebrada Blanca station and Rio Valenciano station—operated by the US Geological Survey were used as case studies. Based on comparison of the results, it is found that the NF model gives better estimates than the other techniques.     

Hydroclimate controls over seasonal sediment yield in two adjacent High Arctic watersheds

Interannual variations in seasonal sediment transfer in two High Arctic non‐glacial watersheds were evaluated through three summers of field observations (2003–2005). Total seasonal discharge, controlled by initial watershed snow water equivalence (SWE) was the most important factor in total seasonal suspended sediment transfer. Secondary factors included melt energy, snow distribution and sediment supply. The largest pre‐melt SWE of the three years studied (2004) generated the largest seasonal runoff and disproportionately greater suspended sediment yield than the other years. In contrast, 2003 and 2005 had similar SWE and total runoff, but reduced runoff intensity resulted in lower suspended sediment concentrations and lower total suspended sediment yield in 2005. Lower air temperatures at the beginning of the snowmelt period in 2003 prolonged the melt period and increased meltwater storage within the snowpack. Subsequently, peak discharge and instantaneous suspended sediment concentrations were more intense than in the otherwise warmer 2005 season. The results for this study will aid in model development for sediment yield estimation from cold regions and will contribute to the interpretation of paleoenvironmental records obtained from sedimentary deposits in lakes. Copyright © 2007 John Wiley & Sons, Ltd.     

A comparison of MODIS and NOHRSC snow‐cover products for simulating streamflow using the Snowmelt Runoff Model

Remote sensing is an important source of snow‐cover extent for input into the Snowmelt Runoff Model (SRM) and other snowmelt models. Since February 2000, daily global snow‐cover maps have been produced from data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS). The usefulness of this snow‐cover product for streamflow prediction is assessed by comparing SRM simulated streamflow using the MODIS snow‐cover product with streamflow simulated using snow maps from the National Operational Hydrologic Remote Sensing Center (NOHRSC). Simulations were conducted for two tributary watersheds of the Upper Rio Grande basin during the 2001 snowmelt season using representative SRM parameter values. Snow depletion curves developed from MODIS and NOHRSC snow maps were generally comparable in both watersheds: satisfactory streamflow simulations were obtained using both snow‐cover products in larger watershed (volume difference: MODIS, 2·6%; NOHRSC, 14·0%) and less satisfactory streamflow simulations in smaller watershed (volume difference: MODIS, −33·1%; NOHRSC, −18·6%). The snow water equivalent (SWE) on 1 April in the third zone of each basin was computed using the modified depletion curve produced by the SRM and was compared with in situ SWE measured at Snowpack Telemetry sites located in the third zone of each basin. The SRM‐calculated SWEs using both snow products agree with the measured SWEs in both watersheds. Based on these results, the MODIS snow‐cover product appears to be of sufficient quality for streamflow prediction using the SRM in the snowmelt‐dominated basins. Copyright © 2005 John Wiley & Sons, Ltd.     

Quantifying contributions of snowmelt water to streamflow using graphical and chemical hydrograph separation

In this study, we characterize the snowmelt hydrological response of nine headwater watersheds in southeast Wyoming by separating streamflow into three components using a combination of tracer and graphical approaches. First, continuous 15-min records of specific conductance (SC) from 2016 to 2018 were used to separate streamflow into annual contributions, representing water that contributes to streamflow in a given year that entered the watershed in the same year being considered, and perennial contributions, representing water that contributes to streamflow in a given year that entered the watershed in previous years. Then, diurnal streamflow cycles occurring during the snowmelt season were used to graphically separate annual contributions into rapid diurnal snowmelt contributions, representing water with the relatively fastest hydrological response and shortest residence time, and delayed annual contributions, representing water with relatively longer residence time in the watershed before becoming streamflow. On average, mean annual total streamflow was comprised of between 22% and 46% perennial contributions, 7% and 14% rapid diurnal snowmelt contributions, and 46% and 55% delayed annual contributions across the watersheds. A hysteresis index describing SC-discharge patterns indicated that, annually, most watersheds showed negative, concave, anti-clockwise hysteretic direction suggesting faster flow pathways dominate streamflow on the rising limb of the annual hydrograph relative to the falling limb. At the daily timescale during snowmelt-induced diurnal streamflow cycles, hysteresis was negative, but with a clockwise direction, implying that rapid diurnal snowmelt contributions generated from the concurrent daily snowmelt, with lower SC, arrived after delayed annual contribution peaks and preferentially contributed on the falling limb of diurnal cycles. South-facing watersheds were more susceptible to early season snowmelt at slower rates, resulting in less annual and more perennial contributions. Conversely, north-facing watersheds had longer snow persistence and larger proportions of annual contributions and rapid diurnal snowmelt contributions. Watersheds with surficial geology dominated by glacial deposits had a lower proportion of rapid diurnal snowmelt contributions compared to watersheds with large percentages of bedrock surficial geology.     

Watershed modelling of hydrology and water quality in the Sacramento River watershed,California

Agricultural pollutant runoff is a major source of water contamination in California's Sacramento River watershed where 8500 km² of agricultural land influences water quality. The Soil and Water Assessment Tool (SWAT) hydrology, sediment, nitrate and pesticide transport components were assessed for the Sacramento River watershed. To represent flood conveyance in the area, the model was improved by implementing a flood routing algorithm. Sensitivity/uncertainty analyses and multi‐objective calibration were incorporated into the model application for predicting streamflow, sediment, nitrate and pesticides (chlorpyrifos and diazinon) at multiple watershed sites from 1992 to 2008. Most of the observed data were within the 95% uncertainty interval, indicating that the SWAT simulations were capturing the uncertainties that existed, such as model simplification, observed data errors and lack of agricultural management data. The monthly Nash–Sutcliffe coefficients at the watershed outlet ranged from 0.48 to 0.82, indicating that the model was able to successfully predict streamflow and agricultural pollutant transport after calibration. Predicted sediment loads were highly correlated to streamflow, whereas nitrate, chlorpyrifos and diazinon were moderately correlated to streamflow. This indicates that timing of agricultural management operations plays a role in agricultural pollutant runoff. Best management practices, such as pesticide use limits during wet seasons, could improve water quality in the Sacramento River watershed. The calibrated model establishes a modelling framework for further studies of hydrology, water quality and ecosystem protection in the study area. Copyright © 2012 John Wiley & Sons, Ltd.