Search Results (15)

The effectiveness of existing and potential best management practices (BMPs) to cropped lands in the Jeannette Creek watershed (Thames River basin, Ontario, Canada) in reducing P loads at its pumped outlets was assessed using the Soil and Water Assessment Tool (SWAT). Existing BMPs consisted of banded, incorporated, and variable phosphorus (P)-rate application, conservation tillage, cover crops, and vegetative buffer strips. Potential BMPs consisted of banded P application, no-till, and a cover crop following winter wheat. Two separately delineated sub-watersheds, J1 and J2, characterized by a flat topography and distinct pumped outlets, were selected for analysis. Despite challenges in delineation, the SWAT model was successfully set up to assess the impact of BMPs in reducing P loads in these sub-watersheds. Each BMP was systematically removed, and the resulting simulated P loads were compared with the baseline scenario. Compared to cover crops or vegetative buffer strips, the implementation of conservation tillage and no-till, along with altering the mode of P application, offered superior effectiveness in reducing the P load. On average, the annual reduction in total P (P_tot) loads under existing BMPs was 9.2% in J1 and 11.3% in J2, whereas, under potential BMPs, this reduction exceeded 60% in both watersheds. Full article

Non-point source pollution poses a continuous threat to the quality of Great Lakes waters. To abate this problem, the Great Lakes Agricultural Stewardship Initiative (GLASI) was initiated in Ontario, Canada, with the primary aim of reducing phosphorus pollution. Therefore, a case-study analysis of the Wigle Creek watershed, one of the six priority watersheds under the GLASI program, was undertaken to evaluate the effectiveness of various existing and potential future Best Management Practices (BMPs) and to identify BMPs that might aid in mitigating the watershed’s contribution to phosphorus loads reaching Lake Erie. Given the watershed’s very flat topography, hydrological/nutrient modeling proved an extremely challenging exercise. The Soil and Water Assessment Tool (SWAT) model was used in this evaluation. Several digital elevation model (DEM) options were considered to accurately describe the watershed and represent flow conditions. A 30 m resolution DEM, implementing a modified burning in of streams based on ground truthing, was finally employed to develop the SWAT model’s drainage framework. The model was first calibrated for flow, sediment, and phosphorus loads. The calibrated model was used to evaluate the ability of potential BMPs (minimum tillage, no-till, retiring croplands into pasture, retiring croplands into forest, winter wheat cover crop, and vegetative filter strips) to reduce phosphorus loads compared to implemented practice. Converting all croplands into pasture or forest significantly decreased P loads reaching Lake Erie. Comparatively, a winter wheat cover crop had minimal effect on reducing phosphorus loading. Full article

Gully erosion susceptibility mapping (GESM) through predicting the spatial distribution of areas prone to gully erosion is required to plan gully erosion control strategies relevant to soil conservation. Recently, machine learning (ML) models have received increasing attention for GESM due to their vast capabilities. In this context, this paper sought to review the modeling procedure of GESM using ML models, including the required datasets and model development and validation. The results showed that elevation, slope, plan curvature, rainfall and land use/cover were the most important factors for GESM. It is also concluded that although ML models predict the locations of zones prone to gullying reasonably well, performance ranking of such methods is difficult because they yield different results based on the quality of the training dataset, the structure of the models, and the performance indicators. Among the ML techniques, random forest (RF) and support vector machine (SVM) are the most widely used models for GESM, which show promising results. Overall, to improve the prediction performance of ML models, the use of data-mining techniques to improve the quality of the dataset and of an ensemble estimation approach is recommended. Furthermore, evaluation of ML models for the prediction of other types of gully erosion, such as rill–interill and ephemeral gully should be the subject of more studies in the future. The employment of a combination of topographic indices and ML models is recommended for the accurate extraction of gully trajectories that are the main input of some process-based models. Full article

Ascertaining the spatiotemporal accuracy of precipitation is a challenge for hydrologists and planners for flood protection measures. The objective of this study was to compare streamflow simulations using rain gauge and radar data from a watershed in Southern Ontario, Canada, using the Hydrologic Engineering Center’s event-based distributed Hydrologic Modeling System (HEC-HMS). The model was run using the curve number (CN) and the Green and Ampt infiltration methods. The results show that the streamflow simulated with rain gauge data compared better with the observed streamflow than the streamflow simulated using radar data. However, when the Mean Field Bias (MFB) corrections were applied, the quality of the streamflow results obtained from radar rainfall data improved. The results showed no significant difference between the simulated streamflow using the SCS and the Green and Ampt infiltration approach. However, the SCS method is reasonably more appropriate for modeling the runoff at the sub-basin-scale than the Green and Ampt infiltration approach. With the SCS method, the simulated and observed runoff amount obtained using rain gauge rainfall showed an R² value of 0.88 and 0.78 for MFB-corrected radar and 0.75 for radar only. For the Green and Ampt modeling option, the R² value for the simulated and observed runoff amounts were 0.87 with rain gauge, 0.66 with radar only, and 0.68 with MFB-corrected radar rainfall inputs. The NSE values for rain gauge input ranged from 0.65 to 0.35. Overall, three values were less than 0.5 for streamflow for both the methods. For seven radar rainfall events, the NSE was greater than 0.5, with a range of very good to satisfactory. The analysis of RSR showed a very good comparison of stream flow using the SCS curve number method and Green and Ampt method using different rainfall inputs. Only one value, the 2 November 2003 event, was above 0.7 for rain gauge-based streamflow. The other RSR values were in the range of “very good”. Overall, the study showed better results for the simulated runoff with the MFB-corrected radar rainfall when compared with the simulations obtained using radar rainfall only. Therefore, MFB-corrected radar could be explored as a substitute rainfall source. Full article

The focus of this study is to investigate the effects of climate change on the hydrologic regimes in Ontario, Canada. The variables include total precipitation, the form of precipitation (snowfall and rainfall), and the temperature during winter. The winter season is hydrologically significant for Canadian conditions. The historical data for 70 years, from 1939 to 2008, on total precipitation, snowfall, rainfall, and temperature over the winter period were analyzed using least-squares regressions, Alexandersson’s Standard Normal Homogeneity Test, and the Mann–Kendall test for 13 stations across Ontario to identify positive and negative trends and their significance. The analysis of the precipitation indices reveals no significant trend in the winter total precipitation, decreasing trends in winter snowfall, and increasing trends in winter rainfall. The snowy day analysis depicts a large scatter across the province, with the number ranging from 40 days to 80 days, which shows that the number of snowy days varies considerably over the years at all stations. The analysis showed that the change in snowy-rainy days is attributed to the significant upward trend of the daily mean winter minimum temperature for almost all the stations. Therefore, the changes in the form of precipitation during winter may affect water management including streamflow, tile drainage flow, soil erosion, sediment and nutrient transport to surface water bodies, and the effectiveness of best management practices being used for managing non-point source pollution. Full article

Climate change and rapid urbanization could possibly increase the vulnerability of the Great Lakes Basin, Canada, which is the largest surface freshwater system in the world. This study explores the joint impact of climate change and land-use changes on the hydrology of a rapidly urbanizing Credit River watershed which lets out into Lake Ontario 25 km southwest of downtown Toronto, Ontario (ON), Canada; we began by classifying the watershed into urban and rural sections. A non-parametric Mann–Kendall test and the Sen slope estimator served to detect and describe the annual-, seasonal-, and monthly-scale trends in the climate variables (temperature, precipitation, and evapotranspiration), as well as the streamflow characteristics (median annual streamflow, baseflow, Runoff Coefficients (RC), Flow Duration Curve (FDC), Center of Volume (COV), and Peak Over Threshold (POT)) since 1916 for four rural and urban sub-watersheds. The temperature, precipitation and evapotranspiration (1950–2019) showed significant increasing trends for different months and seasons. Furthermore, the results indicated that the median annual streamflow, 7-day annual minimum flow, and days above normal are increasing; meanwhile, the annual maximum streamflow is decreasing. A total of 230 datasets were tested for their trends; of these, 80% and 20% increasing and decreasing trends were obtained, respectively. Of the total, significant trends (<0.05%) of 32% and 2% increasing and decreasing, respectively, were observed. The results of the FDC analysis indicated a decline in the annual and winter 10:90 exceedance ratio over the years for the rural and urban sub-watershed gauges. The BFI results show that the BFI of the rural areas was, on average, 18% higher than that of the urban areas. In addition, the RC also showed the influence of land-use and population changes on the watershed hydrology, as the RC for the urban gauge area was 19.3% higher than that for the rural area gauge. However, the difference in the RC was the lowest (5.8%) in the summer. Overall, the findings from this study highlight the annual, seasonal, and monthly changes in the temperature, precipitation, evapotranspiration, and streamflow in the watershed under study. Based on the available monitored data, it was difficult to quantify the changes in the streamflow over the decade which were attributable to population growth and land-cover use and management changes due to municipal official planning in the watershed. Full article

Many watershed models employ the Soil Conservation Service Curve Number (SCS-CN) approach for runoff simulation based on soil and land use information. These models implicitly assume that runoff is generated by the Hortonian process and; therefore, cannot correctly account for the effects of topography, variable source area (VSA) and/or soil moisture distribution in a watershed. This paper presents a new distributed CN-VSA method that is based on the SCS-CN approach to estimate runoff amount and uses the topographic wetness index (TWI) to distribute the runoff-generating areas within the watershed spatially. The size of the saturated-watershed areas and their spatial locations are simulated by assuming an average annual value of potential maximum retention. However, the literature indicates significant seasonal variation in potential maximum retention which can considerably effect water balance and amount of nonpoint source pollution. This paper focuses on developing a modified distributed CN-VSA method that accounts for the seasonal changes in the potential maximum retention. The results indicate that the modified distributed CN-VSA approach is better than distributed CN-VSA to simulate runoff amount and spatial distribution of runoff-generating areas. Overall, the study results are significant for improved understanding of hydrological response of watershed where seasonal factors describe the potential maximum retention, and, thus, saturation excess runoff generation in the watershed. Full article

The detrimental impacts of agricultural subsurface tile flows and their associated pollutants on water quality is a major environmental issue in the Great Lakes region and many other places globally. A strong understanding of water quality indicators along with the contribution of tile-drained agriculture to water contamination is necessary to assess and reduce a significant source of non-point source pollution. In this study, DRAINMOD, a field-scale hydrology and water quality model, was applied to assess the impact of future climatic change on depth to water table, tile flow and associated nitrate loss from an 8.66 ha agricultural field near Londesborough, in Southwestern Ontario, Canada. The closest available climate data from a weather station approximately 10 km from the field site was used by the Ontario Ministry of Natural Resources and Forestry (MNRF) to generate future predictions of daily precipitation and maximum and minimum air temperatures required to create the weather files for DRAINMOD. Of the 28 models applied by MNRF, three models (CGCM3T47-Run5, GFDLCM2.0, and MIROC3.2hires) were selected based on the frequency of the models recommended for use in Ontario with SRA1B emission scenario. Results suggested that simulated tile flows and evapotranspiration (ET) in the 2071–2100 period are expected to increase by 7% and 14% compared to 1960–1990 period. Results also suggest that under future climates, significant increases in nitrate losses (about 50%) will occur along with the elevated tile flows. This work suggests that climate change will have a significant effect on field hydrology and water quality in tile-drained agricultural regions. Full article

Non-point source (NPS) pollution is an important problem that has been threatening freshwater resources throughout the world. Best Management Practices (BMPs) can reduce NPS pollution delivery to receiving waters. For economic reasons, BMPs should be placed at critical source areas (CSAs), which are the areas contributing most of the NPS pollution. The CSAs are the areas in a watershed where source coincides with transport factors, such as runoff, erosion, subsurface flow, and channel processes. Methods ranging from simple index-based to detailed hydrologic and water quality (HWQ) models are being used to identify CSAs. However, application of these methods for Canadian watersheds remains challenging due to the diversified hydrological conditions, which are not fully incorporated into most existing methods. The aim of this work is to review potential methods and challenges in identifying CSAs under Canadian conditions. As such, this study: (a) reviews different methods for identifying CSAs; (b) discusses challenges and the current state of CSA identification; and (c) highlights future research directions to address limitations of currently available methods. It appears that applications of both simple index-based methods and detailed HWQ models to determine CSAs are limited in Canadian conditions. As no single method/model is perfect, it is recommended to develop a ‘Toolbox’ that can host a variety of methods to identify CSAs so as to allow flexibility to the end users on the choice of the methods. Full article

Crops can uptake only a fraction of nitrogen from nitrogenous fertilizer, while losing the remainder through volatilization, leaching, immobilization and emissions from soils. The emissions of nitrogen in the form of nitrous oxide (N₂O) have a strong potency for global warming and depletion of stratospheric ozone. N₂O gets released due to nitrification and denitrification processes, which are aided by different environmental, management and soil variables. In recent years, researchers have focused on understanding and simulating the N₂O emission processes from agricultural farms and/or watersheds by using process-based models like Daily CENTURY (DAYCENT), Denitrification-Decomposition (DNDC) and Soil and Water Assessment Tool (SWAT). While the former two have been predominantly used in understanding the science of N₂O emission and its execution within the model structure, as visible from a multitude of research articles summarizing their strengths and limitations, the later one is relatively unexplored. The SWAT is a promising candidate for modeling N₂O emission, as it includes variables and processes that are widely reported in the literature as controlling N₂O fluxes from soil, including nitrification and denitrification. SWAT also includes three-dimensional lateral movement of water within the soil, like in real-world conditions, unlike the two-dimensional biogeochemical models mentioned above. This article aims to summarize the N₂O emission processes, variables affecting N₂O emission and recent advances in N₂O emission modeling techniques in SWAT, while discussing their applications, strengths, limitations and further recommendations. Full article

Water security is the capability of a community to have adequate access to good quality and a sufficient quantity of water as well as safeguard resources for the future generations. Understanding the spatial and temporal variabilities of water security can play a pivotal role in sustainable management of fresh water resources. In this study, a long-term water security analysis of the Grand River watershed (GRW), Ontario, Canada, was carried out using the soil and water assessment tool (SWAT). Analyses on blue and green water availability and water security were carried out by dividing the GRW into eight drainage zones. As such, both anthropogenic as well as environmental demand were considered. In particular, while calculating blue water scarcity, three different methods were used in determining the environmental flow requirement, namely, the presumptive standards method, the modified low stream-flow method, and the variable monthly flow method. Model results showed that the SWAT model could simulate streamflow dynamics of the GRW with ‘good’ to ‘very good’ accuracy with an average Nash–Sutcliffe Efficiency of 0.75, R² value of 0.78, and percentage of bias (PBIAS) of 8.23%. Sen’s slope calculated using data from over 60 years confirmed that the blue water flow, green water flow, and storage had increasing trends. The presumptive standards method and the modified low stream-flow method, respectively, were found to be the most and least restrictive method in calculating environmental flow requirements. While both green (0.4–1.1) and blue (0.25–2.0) water scarcity values showed marked temporal and spatial variabilities, blue water scarcity was found to be the highest in urban areas on account of higher water usage and less blue water availability. Similarly, green water scarcity was found to be highest in zones with higher temperatures and intensive agricultural practices. We believe that knowledge of the green and blue water security situation would be helpful in sustainable water resources management of the GRW and help to identify hotspots that need immediate attention. Full article

This paper focuses on understanding the effects of projected climate change on streamflow dynamics of the Grand and Thames rivers of the Northern Lake Erie (NLE) basin. A soil water assessment tool (SWAT) model is developed, calibrated, and validated in a base-period. The model is able to simulate the monthly streamflow dynamics with ‘Good’ to ‘Very Good’ accuracy. The calibrated and validated model is then subjected with daily bias-corrected future climatic data from the Canadian Regional Climate Model (CanRCM4). Five bias-correction methods and their 12 combinations were evaluated using the Climate Model data for hydrologic modeling (CMhyd). Distribution mapping (DM) performed the best and was used for further analysis. Two future time-periods and two IPCC AR5 representative concentration pathways (RCPs) are considered. Results showed marked temporal and spatial variability in precipitation (−37% to +63%) and temperature (−3 °C to +14 °C) changes, which are reflected in evapotranspiration (−52% to +412%) and soil water storage (−60% to +12%) changes, resulting in heterogeneity in streamflow (−77% to +170%) changes. On average, increases in winter (+11%), and decreases in spring (–33%), summer (−23%), and autumn (−15%) streamflow are expected in future. This is the first work of this kind in the NLE and such marked variability in water resources availability poses considerable challenges to water resources planners and managers. Full article

In the last decade, Lake Erie, one of the great lakes bordering Canada and the USA has been under serious threat due to increased phosphorus levels originating from agricultural fields. Large scale watersheds contributing to Lake Erie from the USA side are being simulated using hydrological and water quality (H/WQ) models such as the Soil and Water Assessment Tool (SWAT) and the results from the model are being used by policy and decision makers to implement better management decisions to solve emerging phosphorus issues. On the Canadian side, modeling applications are limited to either small watersheds or one major watershed contributing to Lake Erie. To the best of our knowledge, no efforts have been made to model the entire contributing watersheds to Lake Erie from Canada. This study applied the SWAT model for Northern Lake Erie Basin (NLEB; entire contributing basin to Lake Erie). Various provincial, national and global inputs of weather, land use and soil at various resolutions was assessed to evaluate the effects of input data types on the simulation of hydrological processes and streamflows. Twelve scenarios were developed using the input combinations and selected scenarios were evaluated at selected locations along the Grand and Thames Rivers using model performance statistics, and graphical comparisons of time variable plots and flow duration curves (FDCs). In addition, various hydrological components such as surface runoff, water yield, and evapotranspiration were also evaluated. Global level coarse resolution weather and soil did not perform better compared to fine resolution national data. Interestingly, in the case of land use, global and national/provincial land use were close, however, fine resolution provincial data performed slightly better. This study found that interpolated weather data from Environment Canada climate station observations performed slightly better compared to the measured data and therefore could be a good choice to use for large-scale H/WQ modeling studies. Full article

The SWATDRAIN model was developed by incorporating the subsurface flow model, DRAINMOD, into a watershed scale surface flow model, SWAT (Soil and Water Assessment tool), to simulate the hydrology and water quality of agricultural watersheds. The model is capable of simulating hydrology under different agricultural management and climate scenarios. As an application of the SWATDRAIN model, the impact of climate change on surface/subsurface flow was evaluated in the Canagagigue Creek watershed in southern Ontario, Canada. Using the assumption that there has been no change in land cover and land management, the model was applied to simulate annual, seasonal, and monthly changes in surface and subsurface flows at the outlet of the watershed under current and future climate conditions. The climate scenario under consideration in this study for 2015–2044 was derived from CGCM2 (Canadian Global Circulation Model 2), with A2 scenario for future climatic simulation. The SWATDRAIN model’s ability to predict the impacts of future climate change scenarios in agricultural watersheds due to monthly NSE (Nash Sutcliffe Efficiency), PBIAS (Percent Bias), and RSR (Root Mean Square Error) values of 0.74, 3.67, and 0.37, respectively, for the validation phase. The results showed that general climate change effects more spring and winter hydrology than summer hydrology. The results show that the annual flow is expected to increase in future, which will lead to an increase in the sediment loads in the stream. Full article

Selecting the right model to simulate a specific watershed has always been a challenge, and field testing of watersheds could help researchers to use the proper model for their purposes. The performance of three popular Geographic Information System (GIS)-based watershed simulation models (European Hydrological System Model (MIKE SHE), Agricultural Policy/Environmental Extender (APEX) and Soil and Water Assessment Tool (SWAT)) were evaluated for their ability to simulate the hydrology of the 52.6 km² Canagagigue Watershed located in the Grand River Basin in southern Ontario, Canada. All three models were calibrated for a four-year period and then validated using an independent four-year period by comparing simulated and observed daily, monthly and annual streamflow. The simulated flows generated by the three models are quite similar and closely match the observed flow, particularly for the calibration results. The mean daily/monthly flow at the outlet of the Canagagigue Watershed simulated by MIKE SHE was more accurate than that simulated by either the SWAT or the APEX model, during both the calibration and validation periods. Moreover, for the validation period, MIKE SHE predicted the overall variation of streamflow slightly better than either SWAT or APEX. Full article