The hydrologic model as a source of nutrient loading uncertainty in a future climate

Kujawa, Haley; Kalcic, Margaret; Martin, Jay F.; Aloysius, Noel; Apostel, Anna; Kast, Jeffrey; Murumkar, Asmita; Evenson, Grey R.; Becker, R. H.; Boles, Chelsie; Confesor, Remegio; Dagnew, Awoke; Guo, Ten-Huei; Muenich, Rebecca Logsdon; Redder, Todd; Scavia, Donald; Wang, Yu-Chen

doi:10.1016/j.scitotenv.2020.138004

Cited by 17 publications

(30 citation statements)

References 68 publications

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“…Kuwaja et al [10] assessed the inherent uncertainty in the capability of climate models and hydrological models to forecast water discharge and nutrient transport in the Maumee River watershed for the period 2046-2065 by forcing five distinct SWAT models with six different climate models from the CMIP5 ensemble. They found out that the hydrologic models can create greater uncertainties than the climate models in water quality forecasts, because hydrologic models created greater uncertainty in total phosphorus and dissolved reactive phosphorus forecast, while the dominant source of uncertainty in total nitrogen forecast was attributed to the climate models.…”

Section: Introductionmentioning

confidence: 99%

Impact of Seasonal Variation in Climate on Water Quality of Old Woman Creek Watershed Ohio Using SWAT

Olaoye

Confesor

Ortiz

2021

Climate

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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.

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Section: Introductionmentioning

confidence: 99%

Impact of Seasonal Variation in Climate on Water Quality of Old Woman Creek Watershed Ohio Using SWAT

Olaoye

Confesor

Ortiz

2021

Climate

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“…Using projected climate from six CMIP5 ESMs under the RCP8.5 scenario, Kujawa et al. (2020) demonstrated that variation among climate models was the dominant source of uncertainty in predicting future total discharge and total N loading in a watershed located in northwest Ohio. This study supports our findings regarding uncertainty sources in projected discharge and N loading in the MARB.…”

Section: Resultsmentioning

confidence: 99%

“…All other input drivers being equal, model simulations indicate that the estimated discharge and N loading show a larger uncertainty under the RCP8.5 scenario than the RCP4.5 scenario (Figures 3a and 3b), corresponding to the divergence among future climate projections. Using projected climate from six CMIP5 ESMs under the RCP8.5 scenario, Kujawa et al (2020) demonstrated that variation among climate models was the dominant source of uncertainty in predicting future total discharge and total N loading in a watershed located in northwest Ohio. This study supports our findings regarding uncertainty sources in projected discharge and N loading in the MARB.…”

Section: Impacts Of Future Precipitation Change On Water Yield and Ni...mentioning

confidence: 99%

Heavy Precipitation Impacts on Nitrogen Loading to the Gulf of Mexico in the 21st Century: Model Projections Under Future Climate Scenarios

et al. 2022

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While spatial heterogeneity of riverine nitrogen (N) loading is predominantly driven by the magnitude of basin‐wide anthropogenic N input, the temporal dynamics of N loading are closely related to the amount and timing of precipitation. However, existing studies do not disentangle the contributions of heavy precipitation versus non‐heavy precipitation predicted by future climate scenarios. Here, we explore the potential responses of N loading from the Mississippi Atchafalaya River Basin to precipitation changes using a well‐calibrated hydro‐ecological model and Coupled Model Intercomparison Project Phase 5 climate projections under two representative concentration pathway (RCP) scenarios. With present agricultural production and management practices, N loading could increase up to 30% by the end of the 21st century under future climate scenarios, half of which would be driven by heavy precipitation. Particularly, the RCP8.5 scenario, in which heavy precipitation and drought events become more frequent, would increase N loading disproportionately to projected increases in river discharge. N loading in spring would contribute 41% and 51% of annual N loading increase under the RCP4.5 and RCP8.5 scenarios, respectively, most of which is related to higher N yield due to increases in heavy precipitation. Anthropogenic N inputs would be increasingly susceptible to leaching loss in the Midwest and the Mississippi Alluvial Plain regions. Our results imply that future climate change alone, including more frequent and intense precipitation extremes, would increase N loading and intensify the eutrophication of the Gulf of Mexico over this coming century. More effective nutrient management interventions are needed to reverse this trend.

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“…Nitrogen was more clearly reduced with conservation in the mid‐century (

Δ {IC}_{MC}

) because the effects of climate alone reduced TN without additional conservation (Kujawa et al. 2020). Therefore, the combined effects of climate change and IC decreased TN loadings further in the mid‐century (Table 4).…”

Section: Discussionmentioning

confidence: 99%

Using a Multi‐Institutional Ensemble of Watershed Models to Assess Agricultural Conservation Effectiveness in a Future Climate

Kujawa

Kalcic

Martin

et al. 2022

J American Water Resour Assoc

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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.

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The hydrologic model as a source of nutrient loading uncertainty in a future climate

Cited by 17 publications

References 68 publications

Impact of Seasonal Variation in Climate on Water Quality of Old Woman Creek Watershed Ohio Using SWAT

Impact of Seasonal Variation in Climate on Water Quality of Old Woman Creek Watershed Ohio Using SWAT

Heavy Precipitation Impacts on Nitrogen Loading to the Gulf of Mexico in the 21st Century: Model Projections Under Future Climate Scenarios

Using a Multi‐Institutional Ensemble of Watershed Models to Assess Agricultural Conservation Effectiveness in a Future Climate

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