Hydrologic models are indispensable tools for water resource planning and management. Accurate model predictions are critical for better water resource development and management decisions. Single-site model calibration and calibrating a watershed model at the watershed outlet are commonly adopted strategies. In the present study, for the first time, a multi-site calibration for the Soil and Water Assessment Tool (SWAT) in the Kelani River Basin with a catchment area of about 2340 km2 was carried out. The SWAT model was calibrated at five streamflow gauging stations, Deraniyagala, Kithulgala, Holombuwa, Glencourse, and Hanwella, with drainage areas of 183, 383, 155, 1463, and 1782 km2, respectively, using three distinct calibration strategies. These strategies were, utilizing (1) data from downstream and (2) data from upstream, both categorized here as single-site calibration, and (3) data from downstream and upstream (multi-site calibration). Considering the performance of the model during the calibration period, which was examined using the statistical indices R2 and NSE, the model performance at Holombuwa was upgraded from “good” to “very good” with the multi-site calibration technique. Simultaneously, the PBIAS at Hanwella and Kithulgala improved from “unsatisfactory” to “satisfactory” and “satisfactory” to “good” model performance, while the RSR improved from “good” to “very good” model performance at Deraniyagala, indicating the innovative multi-site calibration approach demonstrated a significant improvement in the results. Hence, this study will provide valuable insights for hydrological modelers to determine the most appropriate calibration strategy for their large-scale watersheds, considering the spatial variation of the watershed characteristics, thereby reducing the uncertainty in hydrologic predictions.
This study investigates the combined impacts of climate change and agricultural conservation on the magnitude and uncertainty of nutrient loadings in the Maumee River Watershed, the second-largest watershed of the Laurentian Great Lakes. Two scenarios — baseline agricultural management and increased agricultural conservation — were assessed using an ensemble of five Soil and Water Assessment Tools driven by six climate models. The increased conservation scenario included raising conservation adoption rates from a baseline of existing conservation practices to feasible rates in the near future based on farmer surveys. This increased adoption of winter cover crops on 6%–10% to 60% of cultivated cropland; subsurface placement of phosphorus fertilizers on 35%–60% to 68% of cultivated cropland; and buffer strips intercepting runoff from 29%–34% to 50% of cultivated cropland. Increased conservation resulted in statistically significant (p ≤ 0.05) reductions in annual loads of total phosphorus (41%), dissolved reactive phosphorus (18%), and total nitrogen (14%) under the highest emission climate scenario (RCP 8.5). While nutrient loads decreased with increased conservation relative to baseline management for all watershed models, different conclusions on the true effectiveness of conservation under climate change may be drawn if only one watershed model was used.
The separate and synergistic effects of land use and climate change on water quality variables in Old Woman Creek (OWC) watershed were evaluated using a hydrological model set up in Soil and Water Assessment Tool (SWAT) for the OWC watershed. Model calibration was done using a multi-objective evolutionary algorithm and pareto optimization. The Parameter-Elevation Regressions on Independent Slopes Model (PRISM) climate data and the 20 different Global Circulation Models (GCMs) developed by the Coupled Model Intercomparison Project Phase five (CMIP5) were used. Validation was done using the streamflow data from USGS gaging station and water quality data from the water quality lab, Heidelberg University. The simulation was divided into two land use scenarios: Scenario 1 for constant land use and Scenario 2 where land use was varied. Both land use simulations were run in four time periods to account for climate change: historical (1985–2014), current to near future (2018–2045), mid-century (2046–2075), and late-century (2076–2100) climate windows. For the historical period, the average of all the simulations made from the 20 different CMIP5 GCMs shows good agreement with the PRISM results for flow and the water quality variables of interest with smaller inter-model variability compared to PRISM results. For the other three climate windows, the results of Scenario 1 show an increase in flow and eight water quality variables (sediment (total suspended sediment), organic nitrogen, organic phosphorus (particulate p), mineral phosphorus (soluble reactive p), chlorophyll a, carbonaceous biochemical oxygen demand (CBOD), dissolved oxygen, total nitrogen) across the climate windows but a slight decrease in one water quality variable, mineral phosphorus in the mid-century. The results of Scenario 2 show a greater increase in flow, and the eight water quality variables across the climate windows show a relatively larger decrease in one water quality variable (mineral phosphorus). The projected land use change has little impact compared to the projected climate change on OWC watershed in the 21st century.
The effect of agricultural practices on water quality of Old Woman Creek (OWC) watershed was evaluated in a hydrological model using the Parameter-elevation Regressions on Independent Slopes Model (PRISM) climate data and 20 different global circulation models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). A hydrological model was set up in the Soil and Water Assessment Tool (SWAT), while calibration was done using a Multi-Objective Evolutionary Algorithm and Pareto Optimization with PRISM climate data. Validation was done using the measured data from the USGS gage station at Berlin Road in the OWC watershed and water quality data were obtained from the water quality lab, Heidelberg University. Land use scenario simulations were conducted by varying percentages of agricultural land from 20% to 40%, 53.5%, 65%, and 80% while adjusting the forest area. A total of 105 simulations was run for the period 2015–2017: one with PRISM data and 20 with CMIP5 model data for each of the five land use classes scenarios. Ten variables were analyzed, including flow, sediment, organic nitrogen, organic phosphorus, mineral phosphorus, chlorophyll a, CBOD, dissolved oxygen, total nitrogen, and total phosphorus. For all the variables of interest, the average of the 20 CMIP5 simulation results show good correlation with the PRISM results with an underestimation relative to the PRISM result. The underestimation was insignificant in organic nitrogen, organic phosphorus, total nitrogen, chlorophyll a, CBOD, and total phosphorus, but was significant in CMIP5 flow, sediment, mineral phosphorus, and dissolved oxygen. A weak negative correlation was observed between agricultural land percentages and flow, and between agricultural land percentages and sediment, while a strong positive correlation was observed between agricultural land use and the water quality variables. A large increase in farmland will produce a small decrease in flow and sediment transport with a large increase in nutrient transport, which would degrade the water quality of the OWC estuary with economic implications.
The effect of the projected 21st century climate change on water quality in Old Woman Creek (OWC) watershed was evaluated using the Soil and Water Assessment Tool (SWAT) and the precipitation and temperature projections from three best Global Climate Circulation Model (GCM)l ensemble downloaded from the Coupled Model Intercomparison Project Phase 5 (CMIP5). These three best GCMs (GFDL-ESM2M, MPI-ESM-MR, EC-EARTH) were identified as those closest to the multivariate ensemble average of twenty different GCM-driven SWAT simulations. Seasonal analysis was undertaken in historical (1985–2014), current to near future (2018–2045), mid-century (2046–2075), and late-century (2076–2100) climate windows. The hydrological model calibration was carried out using a multi-objective evolutionary algorithm and pareto optimization. Simulations were made for stream flow and nine water quality variables (sediment, organic nitrogen, organic phosphorus, mineral phosphorus, chlorophyll a, carbonaceous biochemical oxygen demand, dissolved oxygen, total nitrogen, and total phosphorus) of interest. The average of twenty different CMIP5-driven SWAT simulation results showed good correlation for all the 10 variables with the PRISM-driven SWAT simulation results in the historical climate window (1985–2014). For the historical period, the result shows an over-estimation of flow, sediment, and organic nitrogen from January to March in simulations with CMIP5 inputs, relative to simulations with PRISM input. For the other climate windows, the simulation results show a progressive increase in stream flow with peak flow month shifting from April to March. The expected seasonal changes in each water quality variable have implications for the OWC estuary and Lake Erie water quality.
FoodsecURe: Food security through better sanitation: the case of urine recycling
Human urine contains essential nutrients (e.g., nitrogen and phosphorus) required for plant growth. Hence, urine can serve as a “free” and locally available nutrient source. Successful, low-cost urine-diverting toilets (UDTs) that separately collect urine have been developed in Scandinavia and in Europe and are being manufactured at large-scale in Africa.
Innovative concepts and technologies for ECOlogically sustainable NUTRIent management in agriculture aiming to prevent, mitigate and eliminate pollution in soils, water and air