Sub-watershed scale monitoring and modeling of BMPs under current and future climatic conditions
Date
2022-12
Authors
Syed, Areba
Major Professor
Advisor
Soupir, Michelle
Malone, Rob
Mickelson, Steve
Wu, Huaqing
Gassman, Phil
Kanwar, Ramesh
Committee Member
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Abstract
The increasing issues related to water quality in the recent years have exclusively focused more attention on agriculture-based potential for non-point source (NPS) pollution. In addition, it is a well-known fact that managing and controlling NPS from agriculture fields is daunting task for producers and researchers. However, researchers have made efforts in the last few decades to understand the variability of NPS pollution in various climatic conditions. The data for NPS pollution research is still sparse, and the effect of Best Management Practices (BMPs) is not well pronounced across the world.
It is anticipated that farm management operations with the inputs of research communities will positively influence the reduction of agricultural NPS. A better understanding of the strengths and weaknesses of at the watershed-scale NPS through research will lead to better selection of BMPs and help to avoid misinterpretation or misapplication in practice. Therefore, this study is in connection with the anticipation of reducing the research gap of NPS pollution and BMPs data for variable climatic, operational, and cropping conditions. The effect of NPS pollution is evident in water bodies within Iowa, which is also a primary source region for the seasonal hypoxic zone that forms in the northern Gulf of Mexico. This hypoxic zone is one of the world’s largest seasonally hypoxic impacted areas, which has ranged up to 23 000 km2 in size in some years. Around 25% of the croplands in the US and Canada do not have sufficient natural soil drainage to sustain agricultural and other activities. More than two-thirds of the land use in the Midwest is dominated by farmland agriculture that produces almost 65% of U.S. corn and soybean with the help of artificial drainage system; however, the subsurface drainage system also provides an efficient transport mechanism for nutrient export to downstream waters. The mechanisms governing the hydrology and the loss of pollutants from drained soils are complex and vary with land use, management practices, soils, site conditions, and climate. This study focuses these issues at a watershed scale to classify BMPs for the study area.
Water quality management includes many factors: starting from the implementation of the BMPs, temporal and spatial assessment of target pollutants, monitoring and collection of data to have better understanding of the relationships between conservation efforts and resulting water quality. A temporal and spatial evaluation of BMP effectiveness helps to plan for future mitigation strategies.
Ecohydrological models are capable of reducing the time and effort required in evaluating BMPs. Monitoring data and its use in modeling provide a basis for evaluating the most effective BMPs, resulting in better insights into the effectiveness of water quality protection efforts. In addition, ecohydrological models can be used to evaluate environmental impacts of agricultural management scenarios and integrated with other models to provide broader socio-economic assessments. Global climate change predictions for an increased frequency of hydrological extremes has increased the need to study the water balance and pollutant interactions. To reliably address what-if scenarios for future agriculture, the impacts of future climate change should also be accounted for. The frequency and intensity of hydrometeorological events can influence the sediment and nutrient delivery patterns from cropland to downstream water bodies.
In this study, the effect of current BMPs on water quality was evaluated using suitable statistical methods for two sub-watersheds within the Black Hawk Lake (BHL) watershed (sub-watershed).
The overall goal of this study was to test and identify temporal statistically significant trends in stream water quality in the Black Hawk Lake watershed, develop a predictive model using ArcSWAT for assessing the effect of BMPs in the watershed and project their effectiveness in future climatic conditions.
The specific objectives of the research were to:
1. Evaluate statistical trends in the water quality of the watershed after the installation of BMPs to test and identify any temporal statistically significant trends in stream water quality for the years 2014 to 2018. Also, testing for spatial differences in the water quality and hydrological parameters like stream flow and water yield for two monitoring locations within the BHL watershed.
2. Develop a calibrated SWAT model for sub-watershed 11 (BHL11).
3. Simulate the paired sub-watershed (BHL12) using the calibrated parameters from BHL11.
4. Evaluate the effectiveness of the current BMPs in the future using GCM data.
Chapter 2 in this dissertation addresses the in-stream nutrient comparison at upstream and downstream locations of sub-watershed 13, which is characterized by high BMP implementation at Black Hawk Lake (BHL) watershed (5,324 hectares of tile-drained) in Iowa. The objective of this 5-year (2014-2018) monitoring project was to compare the in-stream nutrient concentration and load, upstream and downstream of an area in a the subwatershed with high levels of BMPs implementation. The upstream and downstream watersheds have 80% and 85% BMPs implementation by drainage area, respectively. Automated samplers were used to collect flow-weighted composite samples with bi-monthly grab samples taken at the same locations. The statistical methods including Linear Regression (LR), student's t-test, and ANOVA were used to assess temporal and spatial trends. A significant decreasing trend in monthly NO3-N (upstream and downstream) and OP concentration (only upstream) was detected over the study period. At upstream, there was also a substantial decreasing TP concentration in the pre-planting season; whereas, with an increasing trend in TSS concentration during harvest season. OP concentration showed an increasing trend downstream during the harvest season. The length of the data collected is not sufficient to see statistically significant trends in most of the water quality parameters; however, the monthly nitrate concentration data have shown a significant decreasing trend. Overall, sediment and associated pollutants appear more sensitive to the intensity of rainfall in the late growing and harvest seasons. Chapter 3 describes the Soil and water Assessment Tool (SWAT) model development for a heavily tile drained small agricultural watershed and application to evaluate the performance of BMPs. The main objective of this study was to evaluate if SWAT can simulate the watershed processes in the study area on a sub-watershed scale (< 3 Km2) adequately. The SWAT model was calibrated for 3 years of observed data (2015-2017), and validated for another 3 years (2018-2020) for sub-watershed 11 (BHL11). The specific objective of this study was to assess the applicability of a calibrated SWAT model to the paired sub-watershed 12 (BHL12). Replicating model parameters to the paired watershed yielded satisfactory results for stream flow; however, the results showed an inconsistent annual water balance. Chapter 4 explains coupling the SWAT model with Global Circulation Model (GCM) data to forecast sediment export from an agricultural watershed. The objective is based on identifying the applicable GCMs for the area and coupling the hydrological model SWAT with the GCM data to assess the predicted sediment export for future climatic conditions. The results showed that there is not much change expected in the annual average precipitation amount for either of the RCP scenarios. However, there is a potential risk of increased sediment export because of high intensity rainfall in the future. An increase in the use of management techniques like filter strips and sediment retention ponds/wetlands might be required to offset the effect of increasing sediment export.
Commonly, a higher the number of samples will result in a more, accurate and reliable representation of the load pattern. Moreover, a longer period (more than 5 years) of data sampling is required for better evaluation of the impact of BMPs on water quality parameters like TP, TSS, and OP. Based on the results of this study it is also recommended that certain BMPs that are helpful in managing higher intensity rainfall effects should be employed. It is recommended to conduct a separate calibration exercise for BHL12 and compare the values of the calibrated parameters with the ones for BHL11 to deduce the potential differences and reasons for not achieving proportionately translated results.
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