Earth and Environmental Sciences

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This is the collection for the University of Waterloo's Department of Earth and Environmental Sciences.

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Forested Watersheds and Water Supply: Exploring Effects of Wildfires, Silviculture, and Climate Change on Downstream Waters
(University of Waterloo, 2023-06-13) Hampton, Tyler; Basu, Nandita
Drinking water supplies for much of society originate in forests. To preserve the capability of these forests to produce clean and easily treatable water, source water supply and protection strategies focus in particular on potential disturbances to the landscape, which include prescribed forest harvesting and wildfires of varying intensity. While decades of work have revealed relationships between forest harvesting and stream flow response, there is a considerable lack of synthesis disentangling the interactions of climate, wildfires, stream flow, and water quality. Revealing the mechanisms for impacts on downstream waters after disturbances of harvesting and wildfire will greatly improve land and water management. In this dissertation, I combined synthesis of previously published or available data, novel mathematical analyses, and deterministic modeling to disentangle various disturbance effects and further our understanding of processes in forested watersheds. I broadly sought to explore how streamflow and water quality change after forest disturbances, and how new methods and analyses can provide insight into the biogeochemical and ecohydrologic processes changing during disturbances. First, I examined the effect of wildfire on hydrology, and developed a novel Budyko decomposition method to separate climatic and disturbance effects on streamflow. Using a set of 17 watersheds in southern California, I showed that while traditional metrics like changes in flow or runoff ratio might not detect a disturbance effect from wildfire due to confounding climate signals, the Budyko framework can be used successfully for statistical change detection. The method was used to estimate hydrologic recovery timescales that varied between 5 and 45 years, with an increase of about 4 years of recovery time per 10% of the watershed burned. Next, in Chapter 3 I used a meta-analysis approach to examine the effect of wildfire on water quality, using data from 121 catchments around the world. Analyzing the changes in concentrations of stream water nutrients, including carbon, nitrogen, and phosphorus, I showed that concentrations generally increased after fire. While a large amount of variability existed in the data, we found concurrent increases in the constituents after fire highlighting tight coupling of the biogeochemical cycles. Most interestingly, we found fire to increase the concentrations of biologically active nutrients like nitrate and phosphate at a greater rate than total nitrogen and phosphorus, with median increases of 40-60% in the nitrate to TN, and SRP to TP ratios. Next, I conducted an analysis of both water quality and hydrology together after fire in Chapter 4, using a set of 29 wildfire-impacted watersheds in the United States. Concentration-discharge relationships can be used to reveal pathways and sources of elements exported from watersheds, and my overall hypothesis was that these relationships change in post-fire landscapes. I developed a new methodology, using k-means clustering, to classify watersheds as chemostatic, dilution, mobilization and chemodynamic, and explored how their position within the cluster changed in post-fire landscapes. I found that the behavior of nitrate and ammonium was increasingly chemostatic after fire, while behavior of total nitrogen, phosphorus, and organic phosphorus was increasingly mobilizing after fire. Finally, I developed a coupled hydrology-vegetation-biogeochemistry model to simulate and elucidate processes controlling the impact of harvesting on downstream waters. I focused on the Turkey Lakes watershed where a significant amount of data has been collected on vegetation and soil nutrient dynamics, in addition to traditional streamflow and water quality metrics, and developed a novel multi-part calibration process that used measured data on stream, forest, and soil characteristics and dynamics. Future work would involve using the model to explore the data driven relationships that have been developed in the earlier chapters of the paper. The work presented in this dissertation highlights new small and large-scale relationships between disturbances in forested watersheds and effects on downstream waters. With more threats predicted to escalate and overlap in the coming years, the novel results and methodologies that I have presented here should contribute to improving land and water management.
Modelling Legacy Nitrogen Dynamics in the Transboundary Lake Erie Watershed
(University of Waterloo, 2023-01-26) McLeod, Meghan; Basu, Nandita
Lake Erie is a source of drinking water, recreation, and commercial opportunity for both the United States and Canada, making the protection of its water quality essential. In the past decades, Lake Erie's ecosystems have been adversely affected by recurring toxic algal blooms. These algal blooms are attributed to nitrogen (N) and phosphorus pollution from agricultural runoff. Despite recent efforts to reduce N application in the Lake Erie basin, high levels of N concentration persist in surface and groundwater systems. One of the reasons for this apparent stasis in N concentrations is legacy stores of N in landscapes that contribute to lag times in water quality response, even after inputs have ceased. Legacy N is stored in the soil and slow-moving groundwater and makes up a large portion of current N contamination. Quantifying these available legacy N stores is essential for creating nutrient reduction targets. In this thesis, the variance of N inputs and legacy N across different sub-watersheds in the transboundary Lake Erie basin (LEB) are explored. First, I synthesised 2-century-long (1800-2016) N input and output datasets for 45 sub-watersheds across the basin. Specifically, I accounted for manure application, fertilizer, biological N fixation, domestic wastewater N, atmospheric N deposition, and agricultural N uptake. I then used the ELEMeNT modelling framework with these inputs to simulate N loading at the outlet for all 45 sub-watersheds and quantified N retention across the watershed over time. The models performed well overall with a median PBIAS of 1.9% (IQR: 0.7% -3.1%) and a median KGE (Kling Gupta Efficiency) of 0.75 (IQR: 0.66 to 0.88) between modelled and measured N loading across the sub-watersheds. Additionally, the models were able to simulate accumulated soil organic nitrogen (SON) values quite well, with a median PBIAS of 12.6% between modelled and measured SON. The results show that N surplus (the difference between N inputs and non-hydrological N outputs) has been rising across most Lake Erie sub-watersheds since 1950 and has only started to plateau or decrease around 2000. Agricultural inputs from manure, fertilizer, and biological fixation were the lead contributors to N surplus in agricultural watersheds, and domestic N was the lead N contributor in urban sub-watersheds. Since 1950, between 4% and 44% of N has been stored as legacy N (23% median). On average 92% of this N legacy is retained in the soil and 8% is in the groundwater. Through correlation analysis I have found that higher fractions of groundwater N and SON legacy accumulation are correlated with slower travel times and lower tile drainage, while wastewater denitrification emerged as the dominant component in urban sub-watersheds. These results provide insight about drivers of legacy N and N release in sub-watersheds, which could aid in targeted nutrient management across the watershed
The Nitrogen Legacy: Understanding Time Lags in Catchment Response as a Function of Hydrologic and Biogeochemical Controls
(University of Waterloo, 2016-09-23) Van Meter, Kimberly; Basu, Nandita
Global population has seen a more than threefold increase over the last 100 years, accompanied by rapid changes in land use and a dramatic intensification of agriculture. Such changes have been driven by a great acceleration of the global nitrogen (N) cycle, with N fertilizer use now estimated to be 100 Tg/year globally. Excess N commonly finds its way into both groundwater and surface water, leading to long-term problems of hypoxia, aquatic toxicity and drinking water contamination. Despite ongoing efforts to improve water quality in agroecosystems, results have often been disappointing, with significant lag times between adoption of accepted best management practices (BMPs) and measurable improvements in water quality. It has been hypothesized that such time lags are a result of the buildup of legacy N within the landscape over decades of fertilizer application and agricultural intensification. The central theme of my research has been an exploration of this N legacy, including (1) an investigation of the form, locations and magnitudes of legacy N stores within intensively managed catchments; (2) development of a parsimonious, process-based modeling framework for quantifying catchment-scale time lags based on both soil nutrient accumulations (biogeochemical legacy) and groundwater travel time distributions (hydrologic legacy); and (3) use of a statistical approach to both quantifying N-related time lags at the watershed scale, and identifying the primary physical and management controls on these lags. As a result of these explorations I am able to provide the first direct, large-scale evidence of N accumulation in the root zones of agricultural soils, accumulation that may account for much of the ‘missing N’ identified in mass balance studies of heavily impacted watersheds. My analysis of long-term soil data (1957-2010) from 206 sites throughout the Mississippi River Basin (MRB) revealed N accumulation in cropland of 25-70 kg ha-1 y-1, a total of 3.8 ± 1.8 Mt y-1 at the watershed scale. A simple modeling framework was then used to show that the observed accumulation of soil organic N (SON) in the MRB over a 30-year period (142 Tg N) would lead to a biogeochemical lag time of 35 years for 99% of legacy SON, even with a complete cessation of fertilizer application. A parsimonious, process-based model, ELEMeNT (Exploration of Long-tErM Nutrient Trajectories), was then developed to quantify catchment-scale time lags based on both soil N accumulation (biogeochemical legacy) and groundwater travel time distributions (hydrologic legacy). The model allowed me to predict the time lags observed in a 10 km2 Iowa watershed that had undergone a 41% conversion of area from row crop to native prairie. The model results showed that concentration reduction benefits are a function of the spatial pattern of implementation of conservation measures, with preferential conversion of land parcels having the shortest catchment-scale travel times providing greater concentration reductions as well as faster response times. This modeling framework allows for the quantification of tradeoffs between costs associated with implementation of conservation measures and the time needed to see the desired concentration reductions, making it of great value to decision makers regarding optimal implementation of watershed conservation measures. To better our understanding of long-term N dynamics, I expanded the ELEMeNT modeling framework described above to accommodate long-term N input trajectories and their impact on N loading at the catchment scale. In this work, I synthesized data from a range of sources to develop a comprehensive, 214-year (1800-2104) trajectory of N inputs to the land surface of the continental United States. The ELEMeNT model was used to reconstruct historic nutrient yields at the outlets of two major U.S. watersheds, the Mississippi River and Susquehanna River Basins, which are the sources of significant nutrient contamination to the Gulf of Mexico and Chesapeake Bay, respectively. My results show significant N loading above baseline levels in both watersheds before the widespread use of commercial N fertilizers, largely due to 19th-century conversion of natural forest and grassland areas to row-crop agriculture. The model results also allowed me to quantify the magnitudes of legacy N in soil and groundwater pools, thus highlighting the dominance of soil N legacies in the MRB and groundwater legacies in the SRB. It was found that approximately 85% of the annual N load in the MRB can be linked to inputs from previous years, while only 47% of SRB N loading is associated with “older” N. In addition, it was found that the dominant sources of current N load in the MRB are fertilizer, atmospheric deposition, and biological N fixation, while manure and atmospheric deposition account for approximately 64% of the current loads in the SRB. Finally, long-term N surplus trajectories were paired with long-term flow-averaged nitrate concentration data to as means of quantifying N-related lag times across an intensively managed watershed in Southern Ontario. In this analysis, we found a significant linear relationship between current flow-averaged concentrations and current N surplus values across the study watersheds. Temporal analysis, however, showed significant nonlinearity between N inputs and outputs, with a strong hysteresis effect indicative of decadal-scale lag times between changes in N surplus values and subsequent changes in flow-averaged nitrate concentrations. Annual lag times across the study watersheds ranged from 15-33 years, with a mean lag of 24.5 years. A seasonal analysis showed a distribution of lag times across the year, with fall lags being the shortest and summer lags the longest, likely due to differences in N delivery pathways. Multiple linear regression analysis of dominant controls showed tile drainage to be a strong determinant of differences in lag times across watersheds in both fall and spring, with a watershed’s fractional area under tile drainage being significantly linked to shorter lag times. In summer, tile drainage was found to be an insignificant factor in driving lag times, while a significant relationship was found between the percent soil organic matter and longer N-related lag times. By moving beyond the traditional focus on nutrient concentrations and fluxes, and instead working towards quantification of the spatio-temporal dynamics of non-point source nutrient legacies and their current and future impacts on water quality, we make a significant contribution to the science of managing human impacted landscapes. Due to the strong impacts of nutrient legacies on the time scales for recovery in at-risk landscapes, my work will enable a more accurate assessment of the outcomes of alternative management approaches in terms of both short- and long-term costs and benefits, and the evaluation of temporal uncertainties associated with different intervention strategies.
Quantifying the role of reservoirs in altering phosphorus dynamics using a combination of data analysis and process modeling
(University of Waterloo, 2022-04-29) Grootjen, Tori; Basu, Nandita
Excess phosphorus (P) from agricultural watersheds promotes eutrophication in downstream aquatic systems. Reservoirs retain P generated from farm fields and protect downstream waters. Reservoirs also act as hotspots for P transformation, as anoxic conditions can facilitate the release of stored P from the lake sediments. The role of inland reservoirs in P speciation at the watershed scale is relatively unexplored. This problem is growing in importance as approximately half of the global river volume is at least moderately impacted by damming, and is projected to reach 93% with all the planned or proposed dams (Grill et al. 2015). Here we use a decade of soluble reactive P (SRP) and total P (TP) concentration data at the inlet and outlet of two reservoirs, Belwood Reservoir and Conestogo Reservoir, in the Grand River Watershed, Canada. The annual SRP and TP percent retention varied at both reservoirs, showing that the reservoirs acted as a sink in some years and as a source in other years. The percent TP retention in Belwood Reservoir varies from -40% to 32%, while percent TP retention in Conestogo Reservoir is generally lower, between -72% to 25%. The SRP retention in Belwood Reservoir varied between -68% and 43%, while SRP retention in Conestogo Reservoir varied between -71% and 28%. Interestingly, the source-sink behaviour is visible for both SRP and TP and they are similar between years. That is, in years that Belwood Reservoir acts as a source of TP, the reservoir often acts as a source of SRP too. At the seasonal scale, we found that both reservoirs increase the proportion of bioavailable P (SRP:TP ratio) from inlet to outlet between April and October. We then built a process-based model to examine the P cycling and sediment-water interactions controlling this speciation of P in the Belwood Reservoir. The model was able to capture downstream SRP export with NSESRP = 0.57-0.86 and TP export with NSETP = 0.60-0.91. The model had difficulty capturing the SRP:TP magnification from inlet to outlet and sediment P accumulation, especially for the first few years of model simulation (2007 - 2012). Model results highlight the role of internal loading during the summer months. As dam construction is on the rise globally, it is critical to understand the impact of reservoirs on the relative reactivity of P in order to mitigate nuisance and potentially harmful algal blooms.
Spatio-Temporal Patterns in Net Anthropogenic Nitrogen and Phosphorus Inputs Across the Grand River Watershed
(University of Waterloo, 2016-09-23) Zhang, Xiaoyi; Basu, Nandita
Over the last century, human activities have dramatically increased the inputs of nitrogen (N) and phosphorus (P) to land, resulting in increased eutrophication of aquatic systems, and degradation of drinking water quality. Although many changes in management have been adopted to mitigate these impacts, little improvement has been observed in water quality. Multiple N and P mass balance studies have indicated imbalances between inputs and outputs of N and P in anthropogenic landscapes. In this work, historical (1901-2011) N and P budgets for the Grand River Watershed (GRW) in southwestern Ontario were developed using the NANI/NAPI (net anthropogenic N/P input) framework. NANI was calculated as the sum of four different components: commercial fertilizer N application, atmospheric N deposition, net food and feed imports, and biological N fixation. A similar budgeting method was used to estimate NAPI, which includes fertilizer P application, net food and feed imports and detergent P use by humans. Relevant data was obtained from the Canadian agricultural census, Environment Canada, and literature estimates. Our results showed that annual NANI and NAPI values increased approximate 2-fold since 1901, with peak net inputs in 1986 and 1976, respectively. Increases in NANI over time can primarily be attributed to high atmospheric N deposition, fertilizer N application and biological N fixation, while increases in NAPI are primarily due to increased fertilizer P application. Spatially, the hotspots for both NANI and NAPI have since the early 1950s shifted to the central sub-watersheds of the GRW, which can be attributed to greater urbanization and agricultural intensification in the central area. The historical NANI and NAPI estimates obtained for the GRW provide insights into the spatio-temporal patterns in NANI and NAPI, and can facilitate better N and P management strategies.

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