Hot-Moments of Soil CO2 Efflux in a Water-Limited Grassland

The metabolic activity of water-limited ecosystems is strongly linked to the timing and magnitude of precipitation pulses that can trigger disproportionately high (i.e., hot-moments) ecosystem CO2 fluxes. We analyzed over 2-years of continuous measurements of soil CO2 efflux (Fs) under vegetation (Fsveg) and at bare soil (Fsbare) in a water-limited grassland. The continuous wavelet transform was used to: (a) describe the temporal variability of Fs; (b) test the performance of empirical models ranging in complexity; and (c) identify hot-moments of Fs. We used partial wavelet coherence (PWC) analysis to test the temporal correlation between Fs with temperature and soil moisture. The PWC analysis provided evidence that soil moisture overshadows the influence of soil temperature for Fs in this water limited ecosystem. Precipitation pulses triggered hot-moments that increased Fsveg (up to 9000%) and Fsbare (up to 17,000%) with respect to pre-pulse rates. Highly parameterized empirical models (using support vector machine (SVM) or an 8-day moving window) are good approaches for representing the daily temporal variability of Fs, but SVM is a promising approach to represent high temporal variability of Fs (i.e., hourly estimates). Our results have implications for the representation of hot-moments of ecosystem CO2 fluxes in these globally distributed ecosystems

Evidence for global runoff increase related to climate warming

Ongoing global climatic change initiated by the anthropogenic release of carbon dioxide is a matter of intense debate. We focus both on the impact of these climatic changes on the global hydrological cycle and on the amplitude of the increase of global and continental runoff over the last century, in relation to measured temperature increases. In this contribution, we propose an original statistical wavelet-based method for the reconstruction of the monthly discharges of worldwide largest rivers. This method provides a data-based approximation of the evolution of the annual continental and global runoffs over the last century. A consistent correlation is highlighted between global annual temperature and runoff, suggesting a 4% global runoff increase by 1 C global temperature rise. However, this global trend should be qualified at the regional scale where both increasing and decreasing trends are identified. North America runoffs appear to be the most sensitive to the recent climatic changes. Finally, this contribution provides the first experimental data-based evidence demonstrating the link between the global warming and the intensification of the global hydrological cycle. This corresponds to more intense evaporation over oceans coupled to continental precipitation increase or continental evaporation decrease. This process finally leads to an increase of the global continental runoff

Land Surface Verification Toolkit (LVT) - A Generalized Framework for Land Surface Model Evaluation

Model evaluation and verification are key in improving the usage and applicability of simulation models for real-world applications. In this article, the development and capabilities of a formal system for land surface model evaluation called the Land surface Verification Toolkit (LVT) is described. LVT is designed to provide an integrated environment for systematic land model evaluation and facilitates a range of verification approaches and analysis capabilities. LVT operates across multiple temporal and spatial scales and employs a large suite of in-situ, remotely sensed and other model and reanalysis datasets in their native formats. In addition to the traditional accuracy-based measures, LVT also includes uncertainty and ensemble diagnostics, information theory measures, spatial similarity metrics and scale decomposition techniques that provide novel ways for performing diagnostic model evaluations. Though LVT was originally designed to support the land surface modeling and data assimilation framework known as the Land Information System (LIS), it also supports hydrological data products from other, non-LIS environments. In addition, the analysis of diagnostics from various computational subsystems of LIS including data assimilation, optimization and uncertainty estimation are supported within LVT. Together, LIS and LVT provide a robust end-to-end environment for enabling the concepts of model data fusion for hydrological applications. The evolving capabilities of LVT framework are expected to facilitate rapid model evaluation efforts and aid the definition and refinement of formal evaluation procedures for the land surface modeling community

Understanding and Predicting Vadose Zone Processes

Vadose zone hydrologic and biogeochemical processes play a significant role in the capture, storage and distribution of contaminants between the land surface and groundwater. One major issue facing geoscientists in dealing with investigations of the unsaturated zone flow and transport processes is the evaluation of heterogeneity of subsurface media. This chapter presents a summary of approaches for monitoring and modeling of vadose zone dynamics in the presence of heterogeneities and complex features, as well as incorporating transient conditions. Modeling results can then be used to provide early warning of soil and groundwater contamination before problems arise, provide scientific and regulatory credibility to environmental management decision-making process to enhance protection of human health and the environment. We recommend that future studies target the use of RTMs to identify and quantify critical interfaces that control large-scale biogeochemical reaction rates and ecosystem functioning. Improvements also need to be made in devising scaling approaches to reduce the disconnect between measured data and the scale at which processes occur

Time Series Outlier Detection Based on Sliding Window Prediction

In order to detect outliers in hydrological time series data for improving data quality and decision-making quality related to design, operation, and management of water resources, this research develops a time series outlier detection method for hydrologic data that can be used to identify data that deviate from historical patterns. The method first built a forecasting model on the history data and then used it to predict future values. Anomalies are assumed to take place if the observed values fall outside a given prediction confidence interval (PCI), which can be calculated by the predicted value and confidence coefficient. The use of PCI as threshold is mainly on the fact that it considers the uncertainty in the data series parameters in the forecasting model to address the suitable threshold selection problem. The method performs fast, incremental evaluation of data as it becomes available, scales to large quantities of data, and requires no preclassification of anomalies. Experiments with different hydrologic real-world time series showed that the proposed methods are fast and correctly identify abnormal data and can be used for hydrologic time series analysis

Topographic Influences on Trends and Cycles in Nutrient Export from Forested Catchments on the Precambrian Shield

This dissertation explored topographic controls on spatial and temporal patterns in water yield and nutrient (carbon, nitrogen and phosphorus) export from forested headwater catchments in the Turkey Lakes Watershed in central Ontario, where other factors contributing to differences in water yield and nutrient export, including climate, geology, forest, and soils, are relatively constant. Topographic characteristics, including (a) hydrological flushing potential (expansion of water table into nitrate-N producing areas); (b) hydrological storage potential (area of wetlands, which can alternatively allow water and nutrients to bypass wetlands when storage capacity is filled with water or to trap them when not filled); and (c) hydrological loading potential (differences in precipitation caused by elevation), were considered in deconstructing non-stationary (linear trends) and stationary (oscillating cycles) patterns in water yield and nutrient export data. Topography explained the majority of differences in water yield and nutrient export. For spatial variation, topographic metrics representing hydrologic flushing potential predicted the majority of the spatial variation in nitrate-N export. In contrast, topographic metrics representing hydrologic storage potential explained the majority of the observed spatial variation in dissolved organic carbon, dissolved organic nitrogen and total dissolved phosphorus export. For temporal variation, catchments with low hydrologic loading potential were generally more sensitive to trends and cycles for water and nutrient export. Among these catchments, hydrological storage potential had no significant effect on water export trends, but had a significant effect on water export cycles; namely, the water export range was larger in the catchments with higher hydrological storage potential, even though the water export average was the same as catchments with lower hydrological storage potential. For nutrient export, the non-stationary signals were not consistent among the nutrients, but the amplitude of stationary signals in nutrient export in catchments with high hydrological storage potential compared to those with low hydrological storage potential was higher for organic nutrients and lower for nitrate-nitrogen. Despite many similarities in these headwater catchments, topography influenced the absolute and relative magnitude of hydrological and biogeochemical export from these catchments, which will have implications on the productivity and biodiversity of downstream aquatic systems

Influence of Subsurface Hydrodynamics on the Lower Atmosphere at the Catchment Scale

Processes (e.g., groundwater flow, evapotranspiration, precipitation) in different compartments of the hydrological cycle (e.g., subsurface, land surface, and atmosphere) show characteristic variability at different space-time scales and interact with each other through complex non-linear feedback mechanisms. In the hydrologic cycle, subsurface hydrodynamics that may be expressed through the presence of a free water table, interact with land surface mass and energy balance components (e.g., shallow soil moisture and evapotranspiration), which may significantly affect atmospheric processes (e.g., atmospheric boundary layer height and convective precipitation). This thesis aims to understand and quantify the feedback mechanisms between groundwater dynamics and the atmosphere via land surface processes at the catchment scale by analyzing the space-time variability of the fluxes and states of the coupled water and energy cycles. Both modeling and observations of various mass and energy balance components of the hydrological cycle are applied in order to achieve this goal. A coupled simulation platform consisting of a subsurface model (ParFlow), a land surface model (CLM3.5), and an atmospheric model (COSMO-DE) is applied over a model domain encompassing the Rur catchment, Germany, to simulate the fluxes from the subsurface across land surface into the atmosphere over multiple years. The coupled model continuously simulates the mass and energy fluxes over space and time for all three compartments of the hydrological cycle. A comprehensive comparison between the model results and observations demonstrates the model’s capability to reproduce the dynamics as well as the absolute values of the mass and energy fluxes (e.g., shallow soil moisture, groundwater table depth, latent heat flux, sensible heat flux, near-surface temperature). Statistical, geostatistical, and spectral analysis techniques are used to explore the inherent variability of the compartmental mass and energy fluxes, which reveals the interconnections of the compartmental processes at various space-time scales. In this thesis, a novel concept of a dual-boundary forcing is introduced to represent and quantify the interactions between the compartmental mass and energy balance components at the relevant space and time scales. According to this concept, atmosphere and groundwater act as the upper and lower boundary conditions, respectively, for the land surface. The dominating boundary condition controlling the variability of land surface processes is determined by space and time localized moisture and energy availability. This concept states that the space-time patterns of land surface processes can be explained by the variability of the dominating boundary condition, which is corroborated by applying continuous wavelet transform and variogram techniques on the model results and observations. In the ensuing step, the proposed dual-boundary forcing concept is tested considering different lower boundary conditions based on groundwater dynamics in a coupled subsurface-land surface model. The results show that there are significant and predictable differences in the variability of land surface processes at monthly to multi-month time scales from the model configurations with different lower boundary conditions, which indicates that the representation of groundwater dynamics in a numerical simulation platform affects the temporal variability of land surface processes. For example, it was demonstrated that the temporal variability of evapotranspiration simulated by a coupled subsurface-land surface model is reduced at monthly to multi-month time scales in case of a simplified representation of groundwater dynamics. Finally, fully integrated simulations of the terrestrial hydrological cycle are performed considering different groundwater dynamics in a subsurface-land surface-atmosphere model of the larger Rur catchment to study the influence of subsurface hydrodynamics on local weather generating processes. The results show that differences in groundwater dynamics in the model affect shallow soil moisture, evapotranspiration, and sensible heat transfer, which influences atmospheric boundary layer height, convective available potential energy, and precipitation especially under strong convective conditions. These results suggest that groundwater dynamics may generate systematic uncertainties in atmospheric simulations in a fully-coupled model. This thesis reveals that the presence of groundwater dynamics is important to take into account in atmospheric simulations and water resources assessments, such as, drought prediction.Die Prozesse (z.B. Grundwasserströmung, Evapotranspiration, Niederschlag), die in den verschiedenen Kompartimenten des hydrologischen Kreislaufs (z.B. Boden, Landoberfläche und Atmosphäre) stattfinden, zeigen eine charakteristische Variabilität auf verschiedenen Zeit- und Raumskalen. Sie interagieren miteinander durch komplexe nicht-lineare Feedback-Mechanismen. Die Hydrodynamik des Bodens kann beispielsweise durch einen frei beweglichen Grundwasserspiegel formuliert werden und interagiert mittels Komponenten der Massen- und Energiebilanz mit der Landoberfläche (z.B. oberflächennahe Bodenfeuchte und Evapotranspiration). Der Einfluss der Hydrodynamik auf die Landoberfläche kann wiederum signifikante Auswirkungen auf die atmosphärischen Prozesse herbeiführen (z.B. die Höhe der atmosphärischen Grenzschicht und konvektiven Niederschlag). Diese Arbeit fokussiert sich auf diese Feedback-Mechanismen, die zwischen Grundwasserdynamik und Atmosphäreneigenschaften via Landoberflächenprozesse auf der Einzugsgebietsskala entstehen können. Das Verständnis und die Bewertung dieser Mechanismen wird durch die Analyse der Raum-Zeitvariabilität der Zustände und Flüsse des gekoppelten Wasser- und Energiekreislaufes erzielt. Die Verwendung von Beobachtungsdaten und die Modellierung der verschiedenen Komponenten der Massen- und Energiebilanz des hydrologischen Kreislaufs sollen dabei helfen, die entsprechenden Erkenntnisse zu liefern. Eine gekoppelte Simulationsplattform, die aus einem Boden-Grundwassermodell (ParFlow), einem Landoberflächenmodell (CLM3.5) und einem Atmosphärenmodell (COSMO-DE) besteht, wird über das Einzugsgebiet der Rur (Deutschland) angewendet. In diesem gekoppelten System werden die Massen- und Energieflüsse von den untersten Bodenschichten über die Landoberfläche bis in die Atmosphäre über einen Zeitraum von mehreren Jahren durchgängig in Zeit und Raum simuliert. Ein umfassender Vergleich zwischen den Resultaten des Modells und den Beobachtungsdaten demonstriert die Eigenschaft des Modells, die Dynamik und die absoluten Werte des Massen- und Energieflusses (z.B. oberflächennahe Bodenfeuchte, Grundwasserspiegel, latenten und fühlbaren Wärmefluss, bodennahe Temperaturen) zu reproduzieren. Statistische, geostatistische und spektrale Analysetechniken werden genutzt, um die inhärente Variabilität der Massen- und Energieflüsse der entsprechenden Kompartimente zu identifizieren. Durch diese Analysetechniken lassen sich die Zweiwegekopplungen der Prozesse der entsprechenden Kompartimente in verschiedenen Zeit- und Raumskalen bestimmen. In dieser Arbeit wird ein neues Konzept des dual-boundary forcings eingeführt, um die Interaktion zwischen den Komponenten der Massen- und Energiebilanz der entsprechenden Bereiche in den relevanten Raum- und Zeitskalen zu repräsentieren und quantifizieren. Die Atmosphäre und das Grundwasser agieren diesem Konzept entsprechend als obere, respektive untere Randbedingung für die Landoberfläche. Die zeitliche und räumliche Verfügbarkeit von Feuchte und Energie bestimmt hierbei die dominierende Randbedingung bezüglich der Variabilität der Landoberflächenprozesse. Das Konzept des dual-boundary forcings konstatiert im weiteren Verlauf, dass die zeitlichen und räumlichen Strukturen der Landoberflächenprozesse durch die Variabilität der dominierenden Randbedingung erklärt werden kann. Dieser Einfluss der Randbedingung auf die Landoberfläche wird durch die Anwendung der Kontinuierliche Wavelet-Transformation und Variogrammanalysen der Modellresultate und der Beobachtungsdaten gezeigt. Im darauffolgenden Schritt wird unter der Betrachtung verschiedener unterer Randbedingungen, basierend auf der Grundwasserdynamik des gekoppelten Boden-Landoberflächenmodells, das aufgestellte dual-boundary forcing Konzept getestet. Die Ergebnisse der Simulationen mit den verschiedenen unteren Randbedingungen zeigen, dass es signifikante vorhersagbare Unterschiede in der Variabilität von Landoberflächenprozessen im Bereich von monatlichen bis hin zu Zeitskalen von mehreren Monaten gibt. Dies zeigt, dass das Vorhandensein der Grundwasserdynamik in einer numerischen Simulationsplattform die zeitliche Variabilität der Landoberflächenprozesse beeinflußt. Zum Beispiel wurde gezeigt, dass die zeitliche Variabilität der Evapotranspiration durch ein gekoppeltes Boden-Grundwassermodell simuliert wird monatlich zu mehrmonatigen Zeitskalen bei einer vereinfachten Darstellung der Grunddynamik verringert. In einem letzten Schritt werden unter der Berücksichtigung verschiedener Randbedingungen der Grundwasserdynamik im Boden-Landoberflächen-Atmosphären Modell des erweiterten Rur-Einzugsgebiets komplett integrierte Simulationen des terrestrischen, hydrologischen Kreislaufs durchgeführt, um den Einfluss der Hydrodynamik des Bodens auf lokale, wetterbestimmende Prozesse zu analysieren. Die Ergebnisse zeigen, dass unterschiedliche Grundwasserdynamiken des Modells einen signifikanten Einfluß auf die landoberflächennahe Bodenfeuchte, die Evapotranspiration und fühlbaren Wärmeströme ausüben. Diese weisen wiederum einen Einfluss auf die Grenzschichthöhe, CAPE (convective available potential energy) und den Niederschlag, besonders unter stark konvektiven Konditionen auf. Diese Resultate lassen den Schluß zu, dass die Grundwasserdynamik in vollgekoppelten Modellen systematische Unsicherheiten in atmosphärischen Simulationen generieren können. Unter der Berücksichtigung von Modellresultate und Beobachtungen zeigt diese Arbeit auf, dass das Vorhandensein der Grundwasserdynamik in numerischen Simulationsplattformen die Variabilität der Prozesse durch Massen- und Energieflüsse der entsprechenden Kompartimente an der Landoberfläche beeinflusst. Aufgrund dieser Ergebnisse ist es wichtig, das Vorhandensein der Grundwasserdynamik bei atmosphärischen Simulationen und Anwendungen in der Wasserbewirtschaftung, wie zum Beispiel Vorhersagen von Dürreperioden, zu berücksichtigen

Hydrologic modelling

Advances in computational tools and modeling techniques combined with enhanced process knowledge have, in recent decades, facilitated a rapid progress in hydrologic modeling. From the use of traditional lumped models, the hydrologic science has moved to the much more complex, fully distributed models that exude an enhanced knowledge of hydrologic processes. Despite this progress, uncertainties in hydrologic predictions remain. The Indian contribution to hydrologic science literature in the recent years has been significant, covering areas of surface water, groundwater, climate change impacts and quantification of uncertainties. Future scientific efforts in hydrologic science in India are expected to involve better, more robust observation techniques and datasets, deeper process-knowledge at a range of spatio-temporal scales, understanding links between hydrologic and other natural and human systems and integrated solutions using multidisciplinary approaches

Methods to improve neural network performance in daily flows prediction

Author name used in this publication: K. W. Chau2009-2010 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe