Preventing damages from flooding is critically important for city managers and planners.Efforts in protecting infrastructure from flooding are often coupled with building hydrologicmodels to provide predictions of what is likely to happen during storm events. As land usechanges, these models must be updated, which is more challenging with sophisticated models. Ateam of researchers from universities in Utah and Wyoming have been developing tools forwater management in the Intermountain West as part of a collaborative NSF research grantcalled CI-WATER. In particular, a free and open source web platform called Tethys has beendeveloped to support the development and hosting of hydrologic web applications. Tethys wasused to develop a prototype application that uses a GSSHA runoff model and allows users tochange land-use inputs to simulate the impact on a watershed for any type of land use change.The application also provides a method to run the edited model and produces a comparisonreport of before-and-after runoff and water depth as part of a decision-support framework.

Advances in water resources modeling are improving the information that can be supplied to support decisions that affect the safety and sustainability of society, but these advances result in models being more computationally demanding. To facilitate the use of cost- effective computing resources to meet the increased demand through high-throughput computing (HTC) and cloud computing in modeling workflows and web applications, I developed a comprehensive Python toolkit that provides the following features: (1) programmatic access to diverse, dynamically scalable computing resources; (2) a batch scheduling system to queue and dispatch the jobs to the computing resources; (3) data management for job inputs and outputs; and (4) the ability for jobs to be dynamically created, submitted, and monitored from the scripting environment. To compose this comprehensive computing toolkit, I created two Python libraries (TethysCluster and CondorPy) that leverage two existing software tools (StarCluster and HTCondor). I further facilitated access to HTC in web applications by using these libraries to create powerful and flexible computing tools for Tethys Platform, a development and hosting platform for web-based water resources applications. I tested this toolkit while collaborating with other researchers to perform several modeling applications that required scalable computing. These applications included a parameter sweep with 57,600 realizations of a distributed, hydrologic model; a set of web applications for retrieving and formatting data; a web application for evaluating the hydrologic impact of land-use change; and an operational, national-scale, high- resolution, ensemble streamflow forecasting tool. In each of these applications the toolkit was successful in automating the process of running the large-scale modeling computations in an HTC environment.

The interactive nature of web applications or “web apps” makes it an excellent medium for conveying complex scientific concepts to lay audiences and creating decision support tools that harness cutting edge modeling techniques. However, the technical expertise required to develop them represents a barrier for would-be developers. The barrier can be characterized by the following hurdles that developers must overcome: (1) identify, select, and install software that meet the spatial and computational capabilities commonly required for water resources modeling; (2) orchestrate the use of multiple FOSS and FOSS4G projects and navigate their differing application programming interfaces (APIs); (3) learn the multi-language programming skills required for modern web development; and (4) develop a web-safe and fully featured web site to host the app. This research has resulted in two primary products that effectively lower the barrier to water resources web app development: (1) a literature review of free and open source software (i.e. software review) and (2) Tethys Platform. The software review included earth science web apps that were published in the peer-reviewed literature in the last decade and it was performed to determine which FOSS4G and FOSS web software has been used to develop such web apps. The review highlights 11 FOSS4G software projects and 9 FOSS projects for web development that were used to develop 45 earth sciences web apps, which constitutes a significantly reduced list of possible software projects that could be used to meet the needs of water resources web app development—greatly lowering the barrier for entry to water resources web development. While the software review addresses the hurdle of identifying FOSS software to provide a web framework and spatial data capabilities for water resources web apps, there are still other hurdles that needed to be overcome to make development more viable. Tethys Platform was developed to address these other hurdles and streamline the development of water resources web apps. It includes (1) a suite of free and open source software that address the unique data and computational needs common to water resources web app development, (2) a Python software development kit for incorporating the functionality of each software element into web apps and streamlining their development, and (3) a customizable web portal that is used to deploy the completed web apps. Tethys Platform has been used to develop a broad array of web apps for water resources modeling and decision support.

This dissertation research addresses the tectonism of continental crust during ocean basin closure, suturing between continental landmasses, and collisional orogenesis. The new data and insights presented here were gathered through localized geologic investigations of the Tibetan Plateau of central Asia. This area of central Asia is an ideal location to study these fundamental tectonic processes because it has been the locus of numerous Tethyan ocean basins and terminal collisions between continents during Phanerozoic accretion of Gondwana-derived landmasses onto the southern margin of Eurasia. In this work, I propose, in many orogens, that high-pressure (HP) metamorphism of continental rocks may mark the early stages of the suturing process between continental landmasses rather than the culmination of suturing. This insight has been acquired from a geologic-, geochronologic-, and thermochronologic-based investigation of the HP-near ultrahigh-pressure bearing Triassic metasedimentary metamorphic belt in central Tibet. This work shows near synchronous continent-continent collisions between landmass adjacent to the Paleo-Tethys ocean prior to its final closure in Late Triassic time. In addition, this work shows that Mediterranean-style tectonics may be more widespread during accretionary tectonics than previously thought. A comparison between the distribution of the HP bearing metamorphic belt, autochthonous crystalline basement, and geophysical images of Tibet suggests that a Mesozoic tectonic feature may be controlling the structure and distribution of melt within the middle crust of the Tibetan Plateau. This concept underscores the importance of inherited tectonic frameworks on the evolution of orogenic plateaus. Work in southwest Tibet, along the India-Asia suture zone, highlights the complex behavior of continental crust during collisional orogenesis. This work identifies previously undocumented magmatism, crustal antexis, and high-grade metamorphism along the India-Asia suture. In this work I attribute these observations to the initial interactions between Indian, Asian, and subducting Neo-Tethys oceanic lithosphere.

As satellite and climate modelling technology continues to improve and as climatological disasters and issues continue to impact the global community, climate data will increase in size and relevance. With this new influx of information, it is becoming more and more important for scientists to simply and concisely communicate their findings to both decision makers in governments and disaster preparedness organizations and also to the general public. The Soil and Water Assessment Tool (SWAT) is a powerful modelling tool that allows scientists to simulate essentially all of the physical processes involved in the water cycle. The data that SWAT produces can be valuable information as people strive to better plan for and understand various hydrologic events. The work presented in this thesis represents an effort to overcome some of the limitations of the previously developed SWAT visualization software by creating a set of modular web applications that can be duplicated, customized, and run by any organization or individual interested in visualizing and sharing data from SWAT. By eliminating the technical knowledge barriers that are inherent in running and using SWAT models, this work has the potential to increase SWAT’s impact on non-technically trained stakeholders and decision makers in areas where water and climate management is important.

Earth observation data is increasingly ubiquitous, easily accessible, freely available, and generally usable due to improvements in software, data standards, network infrastructure, and national policies. As a result, greater opportunities arise for using these data in a wider field of application including decision support for local and regional environmental and water resources management efforts. In parts of the world where in situ data are less readily available, global Earth observation data used in such decision support tools can be a boon to underfunded government and private water management agencies. The United Nations Group on Earth Observations Global Water Sustainability initiative (GEOGloWS) works to coordinate such solutions, bringing global water management capabilities to local decision makers. The recent development and deployment of a global hydrologic modelling system based on historical simulations and daily ensemble forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) using Earth observations and streamflow routing on every river of the world results in a highly informative and potentially transformative dataset for users at local scales. However, for this data to reach its full potential at the local level, it needs to be subsetted at a regional or local scale, presented in a local geographic context, and interpreted in terms of local water management challenges. Furthermore, this subsetting allows for customization to support the way information is used and the kinds of decisions that are made. This paper presents the design, development, and experimental testing of the GEOGloWS HydroViewer, which is an open source, web-based software that effectively localizes global ECMWF forecasts to meet the needs of water managers and decision makers through subsetting the mapping and modelling services and supporting other customization as needed. The unique Software-as-a-Service (SaaS) deployment method, developed and tested here, allows for individual water management agencies to automatically generate custom HydroViewer applications that can be managed and/or customized depending on need and capacity in-country without reliance on external software and capacity, removing typical interdependence relationships that often define technology transfer to developing countries.

Warning systems with the ability to predict floods days in advance can benefit tens of millions of people. Because of these potential impacts there have been efforts to improve prediction systems such as the United States’ Advanced Hydrologic Prediction Service and European-developed Global Flood Awareness System. However, these projects are currently limited to relatively coarse resolutions. This thesis presents a method for downscaling and routing global runoff forecasts generated by the European Centre for Medium-Range Weather Forecasts using the Routing Application for Parallel computatIon of Discharge program that make possible orders of magnitude increases in the density of the resolution of stream forecasts. The processing method involves using the Amazon Web Services to distribute execution in a cloud-computing environment to make it possible to solve for large watersheds with high-density stream networks. Using the Amazon Web Services, the number of streams that can be used in the downscaling process in a twelve-hour period is approximated to be close to five million. In addition, an application for visualizing large high-density stream networks has been created using the Tethys Platform of water resources modeling developed as part of the CI-WATER NSF grant. The web application is tested with the HUC-2 Region 12 watershed network with over 67,000 reaches and is able to display analyzed results to the user for each reach.

Since 2002, NASA's GRACE Satellite mission has allowed scientists of various disciplines to analyze and map the changes in Earth's total water storage on a global scale. Although the raw data is available to the public, the process of viewing, manipulating, and analyzing the GRACE data can be difficult for those without strong technological backgrounds in programming or geospatial software. This is particularly true for water managers in developing countries, where GRACE data could be a valuable asset for sustainable water resource management. To address this problem, I have a developed a utility for subsetting GRACE data to particular regions of interest and I have packaged that utility in a web app that allows water managers to quickly and easily visualize GRACE data these regions. Using the GLDAS-Noah Land Surface Model, the total water storage for the regions derived from the raw GRACE data is decomposed into surface water, soil moisture, and groundwater components. The GRACE Groundwater Subsetting Tool is easily deployed, open-source, and provides access to all of the major signal processing solutions available for the total water storage data. The application has been successfully applied to both developed and developing countries in various parts of the world, including the Central Valley region in California, Bangladesh, the La Plata River Basin in South America, and the SERVIR Hindu Kush Himalaya region. The groundwater data in this application has proven capable of monitoring groundwater use based on drought trends as well as agricultural demand in a number of locations and can assist in uniting decision makers and water users in the mission of sustainably managing the world's groundwater resources.

The presented PhD thesis is compiled as a commentary to four published papers, which deal with planktonic assamblages of the Upper Jurassic and Cretaceous, namely with calcareous nannofossils and calpionellids. The first part of the dissertation thesis describes the main characteristics of the studied fossil groups with focus on their morphology, palaeoecology, evolution and systematics. The chapter of calcareous nannoplankton gives special attention to the biostratigraphicaly important genus Nannoconus Kampter 1931. Next chapters describe the methods of the laboratory processing of the sediments and the geological settings of the studied areas. The thesis is focused on two areas. At first the selected localities in the Bohemian Cretaceous Basin, i.e. Upper Turonian and Upper Coniacian, are described. Generally, the Upper Cretaceous platform sediments of the middle European basins are rich in calcareous nannoplankton. These fossils represent important marker for biostratigraphical and palaeoecological interpretations. The second part describes carbonate rocks of the Upper Jurassic and Lower Cretaceous of the Tethyan area. In this case, calcareous nannoplankton and calpionellids are an essential part of the modern multidisciplinary form of the Jurassic- Cretaceous (J/K) boundary interval research....

This dissertation presents the design, development and validation of new data integration methods for mapping the extent of snow cover based on open access ground station measurements, remote sensing images, volunteer observer snow reports, and cross country ski track recordings from location-enabled mobile devices. The first step of the data integration procedure includes data discovery, data retrieval, and data quality control of snow observations at ground stations. The WaterML R package developed in this work enables hydrologists to retrieve and analyze data from multiple organizations that are listed in the Consortium of Universities for the Advancement of Hydrologic Sciences Inc (CUAHSI) Water Data Center catalog directly within the R statistical software environment. Using the WaterML R package is demonstrated by running an energy balance snowpack model in R with data inputs from CUAHSI, and by automating uploads of real time sensor observations to CUAHSI HydroServer. The second step of the procedure requires efficient access to multi-temporal remote sensing snow images. The Snow Inspector web application developed in this research enables the users to retrieve a time series of fractional snow cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) for any point on Earth. The time series retrieval method is based on automated data extraction from tile images provided by a Web Map Tile Service (WMTS). The average required time for retrieving 100 days of data using this technique is 5.4 seconds, which is significantly faster than other methods that require the download of large satellite image files. The presented data extraction technique and space-time visualization user interface can be used as a model for working with other multi-temporal hydrologic or climate data WMTS services. The third, final step of the data integration procedure is generating continuous daily snow cover maps. A custom inverse distance weighting method has been developed to combine volunteer snow reports, cross-country ski track reports and station measurements to fill cloud gaps in the MODIS snow cover product. The method is demonstrated by producing a continuous daily time step snow presence probability map dataset for the Czech Republic region. The ability of the presented methodology to reconstruct MODIS snow cover under cloud is validated by simulating cloud cover datasets and comparing estimated snow cover to actual MODIS snow cover. The percent correctly classified indicator showed accuracy between 80 and 90% using this method. Using crowdsourcing data (volunteer snow reports and ski tracks) improves the map accuracy by 0.7 – 1.2 %. The output snow probability map data sets are published online using web applications and web services.