Application of Climate Assessment Tool (CAT) to estimate climate variability impacts on nutrient loading from local watersheds

Ouyang, Ying; Parajuli, Prem B.; Feng, Gary; Leininger, Theodor D.; Wan, Yongshan; Dash, Padmanava

doi:10.1016/j.jhydrol.2018.06.017

Cited by 24 publications

(9 citation statements)

References 22 publications

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“…Among various approaches to the climate change impact assessment on hydrology, such as water quality, crop yield, soil erosion etc., the application of hydrological models is the most effective method [6][7][8][9]. A hydrologic and water quality model, Soil and Water Assessment Tool (SWAT) has been extensively used to analyse the impact of climate change on hydrology and water quality by incorporating the climate data on the model [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Climate Change on Streamflow, Sediment, and Nutrient Load at Watershed Scale

Parajuli

Risal

2021

Climate

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This study evaluated changes in climatic variable impacts on hydrology and water quality in Big Sunflower River Watershed (BSRW), Mississippi. Site-specific future time-series precipitation, temperature, and solar radiation data were generated using a stochastic weather generator LARS-WG model. For the generation of climate scenarios, Representative Concentration Pathways (RCPs), 4.5 and 8.5 of Global Circulation Models (GCMs): Hadley Center Global Environmental Model (HadGEM) and EC-EARTH, for three (2021–2040, 2041–2060 and 2061–2080) future climate periods. Analysis of future climate data based on six ground weather stations located within BSRW showed that the minimum temperature ranged from 11.9 °C to 15.9 °C and the maximum temperature ranged from 23.2 °C to 28.3 °C. Similarly, the average daily rainfall ranged from 3.6 mm to 4.3 mm. Analysis of changes in monthly average maximum/minimum temperature showed that January had the maximum increment and July/August had a minimum increment in monthly average temperature. Similarly, maximum increase in monthly average rainfall was observed during May and maximum decrease was observed during September. The average monthly streamflow, sediment, TN, and TP loads under different climate scenarios varied significantly. The change in average TN and TP loads due to climate change were observed to be very high compared to the change in streamflow and sediment load. The monthly average nutrient load under two different RCP scenarios varied greatly from as low as 63% to as high as 184%, compared to the current monthly nutrient load. The change in hydrology and water quality was mainly attributed to changes in surface temperature, precipitation, and stream flow. This study can be useful in the development and implementation of climate change smart management of agricultural watersheds.

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Section: Introductionmentioning

confidence: 99%

Evaluation of Climate Change on Streamflow, Sediment, and Nutrient Load at Watershed Scale

Parajuli

Risal

2021

Climate

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“…As such, previous studies have suggested that pollution management by BMPs will be undermined by changes in watershed hydrology resulting from climate change . In the northeastern United States, terrestrial nutrient losses are expected to rise via an increase in patterns of drought followed by intense rainfalls, which will lead to greater nutrient loads flushed into receiving waters. − Furthermore, it is expected that increased temperatures will lead to a greater amount of nitrogen and phosphorus being released from organic matter both in the landscape and in waterways, which will further increase nutrient levels in waterways . Indeed, a study of a 724 km 2 watershed in Korea showed increased TP loads into waterways under the RCP 4.5 climate scenario .…”

Section: Discussionmentioning

confidence: 99%

Best Management Practices for Diffuse Nutrient Pollution: Wicked Problems Across Urban and Agricultural Watersheds

Lintern

McPhillips

Winfrey

et al. 2020

Environ. Sci. Technol.

125

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Extensive time and financial resources have been dedicated to address nonpoint sources of nitrogen and phosphorus in watersheds. Despite these efforts, many watersheds have not seen substantial improvement in water quality. The objective of this study is to review the literature and investigate key factors affecting the lack of improvement in nutrient levels in waterways in urban and agricultural regions. From 94 studies identified in the academic literature, we found that, although 60% of studies found improvements in water quality after implementation of Best Management Practices (BMPs) within the watershed, these studies were mostly modeling studies rather than field monitoring studies. For studies that were unable to find improvements in water quality after the implementation of BMPs, the lack of improvement was attributed to lack of knowledge about BMP functioning, lag times, nonoptimal placement and distribution of BMPs in the watershed, postimplementation BMP failure, and socio-political and economic challenges. We refer to these limiting factors as known unknowns. We also acknowledge the existence of unknown unknowns that hinder further improvement in BMP effectiveness and suggest that machine learning, approaches from the field of business and operations management, and long-term convergent studies could be used to resolve these unknown unknowns.

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“…The LMRAV is situated in the floodplain of the Mississippi River (MR) beginning from the north at Illinois, continuing through Missouri, Kentucky, Arkansas, Tennessee, and Mississippi, and ending at the Gulf of Mexico (GOM) in South Louisiana. Clearcuttings of bottomland hardwood forests, conversions from forests to agricultural lands with intensive crop production, and intensified and extreme precipitations are the major factors affect river flooding, wetland loss, and water quality degradation in the MR and the adjacent GOM (Munoz and Dee 2017;Ouyang et al 2013Ouyang et al , 2018Ouyang et al , 2020. Three NOAA (National Oceanic and Atmospheric Administration) weather stations, namely the USC00226177 in Natchez, Mississippi; USC00113580 in Grand Chain Dam 53, Illinois; and USC035691 in Williams Junction, Arkansas, were selected to download the daily precipitation data (Figure 1).…”

Section: Study Site and Data Acquisitionmentioning

confidence: 99%

A Hybrid of Copula Prediction and Time Series Computation to Estimate Stream Discharge Based on Precipitation Data

Ouyang

2022

J American Water Resour Assoc

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Stream discharge is a key hydrological factor for water supply planning, wetland loss investigation, ecological service assessment, and climate change impact estimation. Conceptually, stream discharge is expected to be highly and positively related to precipitation. In reality, however, such a relationship may be weaker because precipitation characteristics are affected by local climate of watersheds. For many watersheds around the world, a vast amount of precipitation data are readily available but the stream discharge data are very limited or unavailable. It would be time-saving and cost-effective to predict stream discharge based on precipitation data. Unfortunately, this task is very difficult to achieve using the traditional methods. Although the copula method is able to establish a good relationship (or a good dependence structure) between discharges and precipitations, this relationship does not include the time series process, and thus is impractical for applications. Therefore, a hybrid of copula prediciton and time series computation was developed (with detailed procedures) here to estimate stream discharge based on precipitation data. The method was validated using the measured daily discharges with the good statistical measures, that is, the Kandell's τ (0.42-0.44), normalized root mean square error (2.19-2.28 m 3 /s), and R 2 (0.66-0.84). This study suggests that the hybrid method is a useful tool to predict stream discharges based on precipitation data.

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Application of Climate Assessment Tool (CAT) to estimate climate variability impacts on nutrient loading from local watersheds

Cited by 24 publications

References 22 publications

Evaluation of Climate Change on Streamflow, Sediment, and Nutrient Load at Watershed Scale

Evaluation of Climate Change on Streamflow, Sediment, and Nutrient Load at Watershed Scale

Best Management Practices for Diffuse Nutrient Pollution: Wicked Problems Across Urban and Agricultural Watersheds

A Hybrid of Copula Prediction and Time Series Computation to Estimate Stream Discharge Based on Precipitation Data

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