PROBABILISTIC APPROACH TO WATER, SEDIMENT, AND NUTRIENT CONNECTIVITY FOR ADVANCING WATERSHED MODELLING

The goal of this dissertation is to represent the spatial and temporal domains of water, sediment, and nutrient flux and pathways within fluvial and watershed settings. To complete this goal, we integrate connectivity theory into watershed model structures to simulate water, sediment, and nutrient movement at the fundamental unit they occur. Fluvial-based sediment and nutrient flux is an important driver of global sediment and nutrient budgets, and the quantification of which serves as an ongoing challenge to limnologists, engineers, and watershed managers. Watershed models have been richly developed over the past century, but are currently restrained by problems related to omission of physical transport and detachment processes as well ambiguous representation of active non-point sources and their transport pathways. To overcome limitations such as these, geomorphologists introduced connectivity theory, which has garnered popularity from watershed managers and modelers due perhaps to its ability to explain the non-linearity of system response and explicitly detail non-point sources, sinks, and transport pathways. Connectivity is defined herein as, “the integrated transfer of material from source to sink facilitated by the continuum of material generation, loss, and transport in three dimensions and through time.” Connectivity theory has matured such that we now have a holistic view of phenomena controlling connectivity, however, the connectivity community has not yet adopted a unified conceptual framework with the goal of connectivity quantification. Existing connectivity models have varying approaches to quantify connectivity such as: (1) index-based connectivity assessments; (2) effective catchment area estimation; and (3) network-based connectivity simulations. While these models often adequately represent the structural connections of landscape elements, few frameworks are able to represent the variability of connectivity from dynamic hydrologic forcings. We argue that explicit coupling of watershed models with a unified connectivity framework will help to improve the basis of watershed modelling in physics while avoiding problems that current watershed models possess: namely due to spatial and temporal lumping and empirical estimations of non-point source generation and fate. This dissertation seeks to fulfill this objective through of six studies that advance formulation of the tenets of connectivity including the magnitude, extent, timing, and continuity of connectivity with respect to water, sediment, and nutrients

Hillslope Hydrology in Global Change Research and Earth System Modeling

Earth System Models (ESMs) are essential tools for understanding and predicting global change, but they cannot explicitly resolve hillslope-scale terrain structures that fundamentally organize water, energy, and biogeochemical stores and fluxes at subgrid scales. Here we bring together hydrologists, Critical Zone scientists, and ESM developers, to explore how hillslope structures may modulate ESM grid-level water, energy, and biogeochemical fluxes. In contrast to the one-dimensional (1-D), 2- to 3-m deep, and free-draining soil hydrology in most ESM land models, we hypothesize that 3-D, lateral ridge-to-valley flow through shallow and deep paths and insolation contrasts between sunny and shady slopes are the top two globally quantifiable organizers of water and energy (and vegetation) within an ESM grid cell. We hypothesize that these two processes are likely to impact ESM predictions where (and when) water and/or energy are limiting. We further hypothesize that, if implemented in ESM land models, these processes will increase simulated continental water storage and residence time, buffering terrestrial ecosystems against seasonal and interannual droughts. We explore efficient ways to capture these mechanisms in ESMs and identify critical knowledge gaps preventing us from scaling up hillslope to global processes. One such gap is our extremely limited knowledge of the subsurface, where water is stored (supporting vegetation) and released to stream baseflow (supporting aquatic ecosystems). We conclude with a set of organizing hypotheses and a call for global syntheses activities and model experiments to assess the impact of hillslope hydrology on global change predictions. Plain Language Summary Hillslopes are key landscape features that organize water availability on land. Valley bottoms are wetter than hilltops, and sun-facing slopes are warmer and drier than shaded ones. This hydrologic organization leads to systematic differences in soil and vegetation between valleys and hilltops, and between sunny and shady slopes. Although these patterns are fundamental to understanding the structures and functions of water and terrestrial ecosystems, they are too fine grained to be represented in global-scale Earth System Models. Here we bring together Critical Zone scientists who study the interplay of vegetation, the porous upper layer of the continental crust from vegetation to bedrock, and moisture dynamics deep into the weathered bedrock underlying hillslopes and Earth System Model scientists who develop global models, to ask: Do hillslope-scale processes matter to predicting global change? The answers will help scientists understand where and why hillslopes matter, and to better predict how terrestrial ecosystems, including societies, may affect and be affected by our rapidly changing planet.National Science Foundation [NSF-EAR-1528298, NSF-EAR-0753521]6 month embargo; published online: 27 February 2019This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Transit times – the link between hydrology and water quality at the catchment scale

In spite of trying to understand processes in the same spatial domain, the catchment hydrology and water quality scientific communities are relatively disconnected and so are their respective models. This is emphasized by an inadequate representation of transport processes, in both catchment-scale hydrological and water quality models. While many hydrological models at the catchment scale only account for pressure propagation and not for mass transfer, catchment scale water quality models are typically limited by overly simplistic representations of flow processes. With the objective of raising awareness for this issue and outlining potential ways forward we provide a non-technical overview of (1) the importance of hydrology-controlled transport through catchment systems as the link between hydrology and water quality; (2) the limitations of current generation catchment-scale hydrological and water quality models; (3) the concept of transit times as tools to quantify transport and (4) the benefits of transit time based formulations of solute transport for catchment-scale hydrological and water quality models. There is emerging evidence that an explicit formulation of transport processes, based on the concept of transit times has the potential to improve the understanding of the integrated system dynamics of catchments and to provide a stronger link between catchment-scale hydrological and water quality models

Hillslope Hydrology in Global Change Research and Earth System Modeling

Earth System Models (ESMs) are essential tools for understanding and predicting global change, but they cannot explicitly resolve hillslope‐scale terrain structures that fundamentally organize water, energy, and biogeochemical stores and fluxes at subgrid scales. Here we bring together hydrologists, Critical Zone scientists, and ESM developers, to explore how hillslope structures may modulate ESM grid‐level water, energy, and biogeochemical fluxes. In contrast to the one‐dimensional (1‐D), 2‐ to 3‐mdeep, and free‐draining soil hydrology in most ESM land models, we hypothesize that 3‐D, lateral ridge‐to‐valley flow through shallow and deep paths and insolation contrasts between sunny and shady slopes are the top two globally quantifiable organizers of water and energy (and vegetation) within an ESM grid cell. We hypothesize that these two processes are likely to impact ESM predictions where (and when) water and/or energy are limiting. We further hypothesize that, if implemented in ESM land models, these processes will increase simulated continental water storage and residence time, buffering terrestrial ecosystems against seasonal and interannual droughts. We explore efficient ways to capture these mechanisms in ESMs and identify critical knowledge gaps preventing us from scaling up hillslope to global processes. One such gap is our extremely limited knowledge of the subsurface, where water is stored (supporting vegetation) and released to stream baseflow (supporting aquatic ecosystems). We conclude with a set of organizing hypotheses and a call for global syntheses activities and model experiments to assess the impact of hillslope hydrology on global change predictions

Hillslope Hydrology in Global Change Research and Earth System Modeling

Earth System Models (ESMs) are essential tools for understanding and predicting global change, but they cannot explicitly resolve hillslope‐scale terrain structures that fundamentally organize water, energy, and biogeochemical stores and fluxes at subgrid scales. Here we bring together hydrologists, Critical Zone scientists, and ESM developers, to explore how hillslope structures may modulate ESM grid‐level water, energy, and biogeochemical fluxes. In contrast to the one‐dimensional (1‐D), 2‐ to 3‐m deep, and free‐draining soil hydrology in most ESM land models, we hypothesize that 3‐D, lateral ridge‐to‐valley flow through shallow and deep paths and insolation contrasts between sunny and shady slopes are the top two globally quantifiable organizers of water and energy (and vegetation) within an ESM grid cell. We hypothesize that these two processes are likely to impact ESM predictions where (and when) water and/or energy are limiting. We further hypothesize that, if implemented in ESM land models, these processes will increase simulated continental water storage and residence time, buffering terrestrial ecosystems against seasonal and interannual droughts. We explore efficient ways to capture these mechanisms in ESMs and identify critical knowledge gaps preventing us from scaling up hillslope to global processes. One such gap is our extremely limited knowledge of the subsurface, where water is stored (supporting vegetation) and released to stream baseflow (supporting aquatic ecosystems). We conclude with a set of organizing hypotheses and a call for global syntheses activities and model experiments to assess the impact of hillslope hydrology on global change predictions

Modelling in ungauged catchments using PyTOPKAPI : a case study of Mhlanga catchment.

Masters Degree. University of KwaZulu-Natal, Durban.Hydrological modeling of rainfall-runoff processes is a powerful tool used in various water resources applications, including the simulation of water yield from ungauged catchments. Many rivers in developing countries are poorly gauged or fully ungauged. This gives rise to a challenge in the calibration and validation of hydrological models. This study investigated the applicability of PyTOPKAPI, a physically based distributed hydrological model, in simulating runoff in ungauged catchments, using the Mhlanga River as a case study. This study is the first application of the PyTOPKAPI model to simulate daily runoff on an ungauged catchment in South Africa. The PyTOPKAPI model was parameterised using globally available digital elevation data (DEM), satellite-derived land cover, soil type data and processed hydro-meteorological data collected from various sources. Historical 30-year (1980-2009) quaternary monthly streamflow (from a well-tested and calibrated model) and daily meteorological variables (rainfall, temperature, humidity and so on) were obtained. The rainfall data were subjected to double mass curve test to check for consistency. The monthly streamflow was transposed to the catchment and disaggregated to daily streamflow time step. The PyTOPKAPI model was calibrated using an average runoff ratio as an alternative to matching streamflow data that is usually used for model calibrations. The simulated results were thereafter compared with the disaggregated monthly quaternary data. The model results show good overall performance when compared with the average runoff ratio, monthly disaggregated streamflow and the expected mean annual runoff in the catchment. In general, PyTOPKAPI can be used to predict runoff response in ungauged catchments, and thus may be adopted for water resources management applications

Evaluating Conceptual Numerical Models of Boreal Plains Hydrology

The Boreal Plains (BPs) ecoregion spans the northern potions of Alberta, Saskatchewan, and Manitoba and is an area of high ecological sensitivity. With large industrial developments in the region, including the Athabasca Oil Sands extraction projects, informed decision making and reclamation is critical. Hydrologic models are tools which are often used to inform such tasks. The BPs are characterized by their deep soils, their mosaic of forests and wetlands and their corresponding complicated hydrology. This complicated hydrology, including variable hydrologic connectivity, fill and spill mechanisms, and variable annual moisture deficit make selecting or developing appropriate hydrologic models a challenge. Current fixed model approaches have thus far been unable to demonstrate good representation of the hydrology of the BPs. To address this gap in the literature for BPs hydrologic representation, three model structures were developed which attempt to capture the complicated physical nature of the BPs. This was achieved by utilizing an iterative, step-wise, and flexible model development approach within the Raven Hydrologic Modelling Framework (Raven). Additionally, physical realism was checked throughout the development process using multiple model diagnostic criteria and hydrologic signatures. Three study basins in the Athabasca River Basin were used to calibrate and validate the model structures. The results were compared to a baseline model which employed standard fixed modelling approaches. The model development process faced numerous challenges including limited data availability, limited understanding of the physical environment at large scales, accurately representing wetland functional groups, representing the variable contributing area, equifinality of calibrated data sets, and limiting available winter algorithms in Raven. For the three data-limited basins examined here, it was found that lack of sufficient data made it difficult to properly constrain model structure and parameterization. Due to the complexity of BPs hydrology, it was found that while inclusion of additional BPs-specific hydrologic structures generally improved model performance in calibration, similar performance was unattainable in validation. This indicates that basins in the BPs will likely required additional data sources, beyond hydrographs, to properly inform and constrain local models

Comparative Analysis of Water Storage Dynamics and Storage-Discharge Relations among Variably Urbanized Catchments within South River Watershed, DeKalb County, GA

The study of watershed storage is critical for understanding watershed hydrologic functions, ecosystem dynamics, and biogeochemical processes. However, few studies have quantified how much water lies in the subsurface in urban watersheds. In this study, dynamic storage was estimated, and storage-discharge relations evaluated in Atlanta, GA among variably urbanized watersheds. Streamflow data from 2012-2016 was utilized and the simple dynamical systems model employed. Dynamic storage values in these watersheds are small: ~3mm to ~9mm. The small dynamic storage values observed across the watersheds are linked to watershed urbanization; however, other subsurface properties of the watersheds may also account for this small storage values. Storage-discharge relations across all the watersheds are non-linear, except the most developed sub-watershed (35% impervious surface area). Two less urbanized sub-watersheds (21% and 26% impervious surface area), showed high streamflow sensitivity. Overall, this study shows that the simple dynamical system model performs well in urbanized watersheds and the South River Watershed can be regarded as a dynamical system