Improved assessment of nitrogen and phosphorus fate and transport for intensively managed irrigated stream-aquifer systems

2019 Fall.Includes bibliographical references.Nitrogen (N) and Phosphorus (P) are essential elements for animal nutrition and plant growth. However, over the previous decades, excessive loading of fertilizers in agricultural activities has led to elevated concentrations of N and P contaminations in surface waters and groundwater worldwide and associated eutrophication. Therefore, precisely understanding and representation of water movement and fate and transport of N and P within a complex dynamic groundwater-surface water system affected by agricultural practices is of essential importance for sustaining ecological health of the stream-aquifer environment while maintaining high agricultural productivity. Modeling tools often are used to assess N and P contamination and evaluate the impact of management practices. Such models include land surface-based watershed models such SWAT, and aquifer-based models that simulate spatially-distributed groundwater flow. However, SWAT simulates groundwater flow in a simplistic fashion and therefore is not suited for watersheds with complex groundwater flow patterns and groundwater-surface interactions, whereas groundwater models do not simulate land surface processes. This dissertation establishes the modeling capacity for assessing the movement, transformation, and storage of nitrate (NO₃) and soluble P in intensively managed irrigated stream-aquifer systems. This is accomplished by (1) developing a method to apply the SWAT model to such a system, and includes: designating each cultivated field as an individual hydrologic response unit (HRU), crop rotations to simulate the impact of changing crop types for each cultivated field, including N and P mass in irrigation water, and seepage from earthen irrigation canals into the aquifer; (2) simulating land surface hydrology, groundwater flow, and groundwater-surface water interactions in the system using the coupled flow model SWAT-MODFLOW, with the enhanced capability of linkage between SWAT groundwater irrigation HRUs and MODFLOW pumping cells, and the use of MODFLOW's EVT package to simulate groundwater evapotranspiration; and (3) linking RT3D, a widely used groundwater reactive solute transport model, to SWAT-MODFLOW to credibly represent of NO₃-N and soluble P fate and transport processes in irrigated agroecosystems to evaluate best management practices for nutrient contamination. This last phase will also address the uncertainty in system output (in-stream nutrient loads and concentrations, groundwater nutrient concentrations model predictions). Each modeling phase is applied to a 734 km² study region in the Lower Arkansas River Valley (LARV), an alluvial valley in Colorado, USA, which has been intensively irrigated for over 130 years and is threatened by shallow water tables and nutrient contamination. Multiple best management practices (BMPs) are investigated to analyze the effectiveness in reducing NO₃-N and soluble P contamination in the LARV. These strategies are related to irrigation management, nutrient management, water conveyance efficiency, and tillage operations. The most effective individual BMP in most areas is to decrease fertilizer by 30%, resulting in average NO₃-N and soluble P concentrations within the region could be reduced by 14% and 9%, respectively. This individual BMP could lower the average NO₃-N concentrations by 19% and soluble P concentrations by 2%. Combinations of using 30% irrigation reduction, 30% fertilization reduction, 60% canal seepage, and conservation tillage are predicted to have the greatest overall impact that can not only provide a decrease of groundwater concentration in NO₃-N up to 41% and soluble P concentration up to 8%, but also reduce the median of the in-stream NO₃-N and soluble P to meet the Colorado interim standard. As nutrient conditions within the Lower Arkansas River Valley are typical of those in many other intensively irrigated regions, the results of this dissertation and the developed modeling tools can be applied to other watersheds worldwide

Using an Integrated Model to Assess Groundwater Recharge in Martis Valley, CA

Groundwater contributes an essential water supply to several communities and ecosystems in the Truckee River Basin. Water resource investigations were conducted through numerical modeling and comparisons to previous work to assess groundwater recharge in the Martis Valley watershed, which is an essential component to the Truckee River hydrographic region. A baseflow analysis was performed to relate annual baseflow to streamflow and precipitation. Results show that changes in groundwater fluctuations are driven by changes in precipitation, and baseflow response is affected by previous precipitation trends. It was estimated that baseflow is roughly one-sixth of mean annual precipitation. A novel method for constructing a hydrogeologic framework model was developed and applied to an integrated surface water-groundwater hydrologic model, GSFLOW, from which groundwater recharge locations and magnitudes were extracted. Model results supplemented previous work and provided enhanced conceptualizations of surface and groundwater interactions, as well as spatial and temporal recharge trends. Results show that the most significant recharge zones are low to mid-elevation stream channel and alluvial areas. During peak snowmelt periods, upper elevation alluvial areas also contribute significant recharge. The findings herein promote a more detailed understanding of groundwater recharge characteristics in high elevation, snow dependent, alpine catchments

The Role of Bedrock Groundwater in Headwater Catchments: Processes, Patterns, Storage and Transit Time

Understanding the role of deep aquifer contributions to headwater rainfall-runoff processes, storages and transit times remains a major challenge in hydrology. Bedrock groundwater contributions to the stream channel can significantly augment streamflow, mediate water quality and control the age of water discharging from catchments. Yet, the hydroclimatic and bedrock characteristics that control these dynamics are not fully understood. Direct observation of bedrock groundwater dynamics, storages and surface water connections remain limited, challenging our ability to fully constrain new catchment scale models that are needed to aid future resource management decisions. I undertook a large field campaign at a well-studied research site in New Zealand. Bedrock groundwater dynamics were monitored for one year and combined with bedrock characterization, tritium-based age dating and hydrochemical analysis to constrain a new conceptual model of the headwater aquifer. Findings were used to develop a new index to identify the controls of bedrock permeability and landscape structure on the time scales of catchment storage-release processes. The three major findings of this research were firstly, that unfractured low-permeability bedrock underlying the research catchment limited to deep flowpaths. Minimal bedrock groundwater flux combined with large bedrock storage resulted in significantly older bedrock groundwater that contributed minimally to catchment discharge. Second, unfractured low-permeability bedrock was a primary control on bedrock groundwater recharge seasonality. Groundwater movement occurred as matrix flow, requiring long durations of high catchment-wetness for considerable recharge to occur, a condition that was only attained during cold-season months when evapotranspiration rates were low and catchment wetness was high. Third, permeability contrasts at the soil-bedrock interface and landscape structure were highly correlated with mean transit time for eight catchments in geologically diverse regions, suggesting that subsurface anisotropy is a major control on setting streamwater age. Overall, through the coupled analysis of the processes, patterns, storages and transit times, this research has advanced our understanding of the role of bedrock groundwater in headwaters. The findings presented here offer new insights into the function of deeper hydrologic layers and have implications for future models of headwater catchment function – models that need to better incorporate the influence of deep flowpaths and storages in groundwater-surface water and rainfall-runoff predictions

FROM RECHARGE TO REEF: ASSESSING THE SOURCES, QUANTITY, AND TRANSPORT OF GROUNDWATER ON TUTUILA ISLAND, AMERICAN SAMOA

Ph.D.Ph.D. Thesis. University of Hawaiʻi at Mānoa 201

Catchment Functioning Under Prolonged Drought Stress : Tracer-Aided Ecohydrological Modeling in an Intensively Managed Agricultural Catchment

Acknowledgments Data used in this study are obtained from the Terrestrial Environmental Observatories (TERENO) project and the Modular Observation Solutions for Earth Systems (MOSES) project, both initiated and funded under the Earth and Environment Program of the Helmholtz Association, Germany. The authors highly appreciate efforts of all partners involved in different monitoring activities. Specifically, The authors would like to thank Frido Reinstorf and Florian Pöhlein from University of Applied Sciences Magdeburg‐Stendal for sharing the hydroclimatic and groundwater level data; Kay Knöller, Ralf Merz and Christin Müller, from Department of Catchment Hydrology (UFZ), for sharing the data of stable isotopes of water and for the constructive discussions; Hans‐Jörg Vogel, Holger Rupp and Ralf Gründling, from Department of Soil System Science (UFZ), for sharing the lysimeter soil moisture data. The authors thank the Editor, the Associate Editor, and three reviewers (Trish Stadnyk and two anonymous reviewers) for their constructive comments. The data are presented in the tables, figures, and supplements. The authors would like to thank Marco Maneta for his support and discussion on the modeling. Contributions from C. Soulsby were supported by the Leverhulme Trust's ISOLAND project.Peer reviewedPublisher PD

Predicting stream baseflow using genetic programing

Developing reliable methods to estimate stream baseflow has been a subject of research over the past decades due to its importance in catchment response and sustainable watershed management (e.g. ground water recharge vs. extraction). Limitations and complexities of existing methods have been addressed by a number of researchers. For instance, physically based numerical models are complex, requiring substantial computational time and data which may not be always available. Artificial Intelligence (AI) tools such as Genetic Programming (GP) have been used widely to reduce the challenges associated with complex hydrological systems without losing the physical meanings. However, up to date, in the absence of complex numerical models, baseflow is frequently estimated using statistically derived empirical equations without significant physical insights. This study investigates the capability of GP in estimating baseflow for a small monitored semi-urban catchment (0.021 km2) located in Singapore. A Recursive Digital Filter (RDF) is first adopted to separate the baseflow from observed streamflow. GP is then used to derive an empirical equation to relate the filtered baseflow time series particularly with groundwater table fluctuations which are relatively easy to be measured and are physically related to baseflow generation. The equation is then validated with a longer time series of baseflow data from a groundwater numerical model. These results indicate that GP is an effective tool in determining baseflow.postprin

Integrated Environmental Modelling Framework for Cumulative Effects Assessment

Global warming and population growth have resulted in an increase in the intensity of natural and anthropogenic stressors. Investigating the complex nature of environmental problems requires the integration of different environmental processes across major components of the environment, including water, climate, ecology, air, and land. Cumulative effects assessment (CEA) not only includes analyzing and modeling environmental changes, but also supports planning alternatives that promote environmental monitoring and management. Disjointed and narrowly focused environmental management approaches have proved dissatisfactory. The adoption of integrated modelling approaches has sparked interests in the development of frameworks which may be used to investigate the processes of individual environmental component and the ways they interact with each other. Integrated modelling systems and frameworks are often the only way to take into account the important environmental processes and interactions, relevant spatial and temporal scales, and feedback mechanisms of complex systems for CEA. This book examines the ways in which interactions and relationships between environmental components are understood, paying special attention to climate, land, water quantity and quality, and both anthropogenic and natural stressors. It reviews modelling approaches for each component and reviews existing integrated modelling systems for CEA. Finally, it proposes an integrated modelling framework and provides perspectives on future research avenues for cumulative effects assessment