Portability of web applications between web servers of different organizations can be challenging and can complicate sharing and collaborative use of such tools. Given the distributed nature of the web, this lack of portability is usually not a concern because a user in one organization can link to and use a web application hosted by another organization. However, access control or differentiation may be needed by an organization in terms of area of interest, input data, analytical techniques, access control, presentation, branding, and language. This is true for many government organizations, and their associated web sites, and servers. In such cases, there are compelling political, branding, security, and privacy motivations that require each organization or agency to host and manage web applications on their own servers rather than using third party web sites over which they have little or no control. Also, web applications are classically developed by setting up a local software development and testing environment which can be challenging for new developers, be restricted by the software and hardware availability, cost significantly to obtain software development licenses and compatible hardware and is prone to code and data loss due to hardware damage or software corruptions. To simplify the discovery, deployment of web-based applications, I present the design, development, and testing of a system for discovering, installing, and configuring environmental analysis web applications on localized web servers. The system works with applications developed using Tethys Platform, which is an open-source software stack for creating geospatially enabled web-based applications. The developed Tethys App Store includes a Tethys application user interface that allows a server manager to retrieve applications from the central repository and install them on a local server with relatively simplicity, similar to the installation of a mobile application to a mobile device from a mobile application store. Next, I present the design concept of a cloud-based web application development platform, Tethys App Nursery, that attempts to overcome the above hurdles associated with localized development environments. A prototype of this system is developed and presented which is tightly integrated with Tethys platform and various cloud technologies provided by Amazon Web Services. The developed app nursery allows users to register for new Tethys portal instances in the cloud, develop new applications and test existing applications, without installing any local dependencies or development tools. Various cloud components used in this service's development as well as their associated costs are described. These systems were developed to support development of water and environmental analysis web apps for the international Group on Earth Observations (GEO) Global Water Sustainability (GEOGloWS) initiative of the National Aeronautics and Space Administration (NASA) and several partner organizations.

Hydrometeorology researchers use data-products like rainfall maps, quarter-hourly, hourly & daily rainfall accumulation maps, and reflectivity maps to drive their hydrological models. There are many sources available from which to generate such products e.g. (1) Weather-radar scan data, (2) Rain-gauge data and (3) Satellite maps, to name a few. Researchers, however, prefer to deal directly with the data-product, rather than deal with the details of sensor data-collection, data-management, storage, quality-control, processing and format conversion. Many researchers would additionally like a real-time continuous 'feed' of customized hydrometeorology data-products to drive their hydrological models in a real-time continuous fashion. Hydro-NEXRAD II is a new system that is currently being developed at IIHR-Hydroscience and Engineering (at The University of Iowa) to address this need. The system provides rapid and user-friendly access to the aforementioned user-customized hydrometeorology data-products in file formats convenient to researchers. Products are generated using near real-time Weather Surveillance Doppler Radar (WSR-88D) data from the National Weather Service's NEXRAD (NEXt generation RADar) radar-network. The architecture, design and engineering details of Hydro-NEXRAD II are the subject of this thesis.

Water security is defined as a combination of water for achieving our goals as a society, and an acceptable level of water-related risks. Hydrologic modeling can be used to predict streamflow and aid in the decision-making process with the goal of attaining water security. Developed countries usually have their own hydrologic models; however, developing countries often lack hydrologic models due to factors such as the maintenance, computational costs, and technical capacity needed to run models. A global streamflow prediction system (GSPS) would help decrease vulnerabilities in developing countries and fill gaps in areas where no local models exist by providing extensive results that can be filtered for specific locations. The development of a GSPS has been deemed a grand challenge of the hydrologic community. To this end, many scientists and engineers have started to develop large-scale systems to an acceptable degree of success. Renowned models like the Global Flood Awareness System (GloFAS), the US National Water Model (NWM), and NASA's Land Assimilation System (LDAS) are proof that our ability to model large areas has improved remarkably. Even so, during this evolution the hydrologic community has started to realize that having a large-scale forecasting system does not make it immediately useful. New hydroinformatic challenges have surfaced that prevent these models from reaching their full potential. I have divided these challenges in four main categories: big data, data communication, adoption, and validation. I present a description of the background leading to the development of a GSPS including existing models, and the components needed to create an operational system. A case study with the NWM is also presented where I address the big data and data communication challenges by developing cyberinfrastructure and accessibility tools such as web applications and services. Finally, I used the GloFAS-RAPID model to create a forecasting system covering Africa, North America, South America, and South Asia using a service-oriented approach that includes the development of web applications, and services for providing improved data accessibility, and helping address adoption and validation challenges. I have developed customized services in collaboration with countries that include Argentina, Bangladesh, Colombia, Peru, Nepal, and the Dominican Republic. I also conducted validation tests to ensure that results are acceptable. Overall, a model-agnostic approach to operationalize a GSPS and provide meaningful results at the local level is provided with the potential to allow decision makers to focus on solving some of the most pressing water-related issues we face as a society.

The application of optimization to Water Distribution Systems encompasses the use of computer-based techniques to problems of many different areas of system design, maintenance and operational management. As well as laying out the configuration of new WDS networks, optimization is commonly needed to assist in the rehabilitation or reinforcement of existing network infrastructure in which alternative scenarios driven by investment constraints and hydraulic performance are used to demonstrate a cost-benefit relationship between different network intervention strategies. Moreover, the ongoing operation of a WDS is also subject to optimization, particularly with respect to the minimization of energy costs associated with pumping and storage and the calibration of hydraulic network models to match observed field data. Increasingly, Evolutionary Optimization techniques, of which Genetic Algorithms are the best-known examples, are applied to aid practitioners in these facets of design, management and operation of water distribution networks as part of Decision Support Systems (DSS). Evolutionary Optimization employs processes akin to those of natural selection and “survival of the fittest” to manipulate a population of individual solutions, which, over time, “evolve” towards optimal solutions. Such algorithms are characterized, however, by large numbers of function evaluations. This, coupled with the computational complexity associated with the hydraulic simulation of water networks incurs significant computational overheads, can limit the applicability and scalability of this technology in this domain. Accordingly, this thesis presents a methodology for applying Genetic Algorithms to Water Distribution Systems. A number of new procedures are presented for improving the performance of such algorithms when applied to complex engineering problems. These techniques approach the problem of minimising the impact of the inherent computational complexity of these problems from a number of angles. A novel genetic representation is presented which combines the algorithmic simplicity of the classical binary string of the Genetic Algorithm with the performance advantages inherent in an integer-based representation. Further algorithmic improvements are demonstrated with an intelligent mutation operator that “learns” which genes have the greatest impact on the quality of a solution and concentrates the mutation operations on those genes. A technique for implementing caching of solutions – recalling the results for solutions that have already been calculated - is demonstrated to reduce runtimes for Genetic Algorithms where applied to problems with significant computation complexity in their evaluation functions. A novel reformulation of the Genetic Algorithm for implementing robust stochastic optimizations is presented which employs the caching technology developed to produce an multiple-objective optimization methodology that demonstrates dramatically improved quality of solutions for given runtime of the algorithm. These extensions to the Genetic Algorithm techniques are coupled with a supporting software library that represents a standardized modelling architecture for the representation of connected networks. This library gives rise to a system for distributing the computational load of hydraulic simulations across a network of computers. This methodology is established to provide a viable, scalable technique for accelerating evolutionary optimization applications.

This work explores the use of hydroinformatics tools to provide a user friendly and accessible interface for executing and visualizing the output of distributed hydrological models for Iowa. It uses an IFIS-based web environment for graphical displays and it communicates with the ASYNCH ODE solver to provide input parameters and to gather modeling outputs. The distributed hydrologic models used here are based on the segmentation of the terrain into hillslope-link hydrologic units, for which water flow processes are represented by sets of nonlinear ordinary differential equations. This modeling strategy has shown promising results in in modeling extreme flood events in the state of Iowa – USA. The usage and evaluation of outputs from hillslope-link models (HLM) has been limited to a restrict group of academics due to the demand of high processing capability and the number of customized tools needed to visualize model outputs. HLM-based models provide abundant output information on rainfall-runoff processes of the hydrological cycle, including estimates of discharge for all streams in the state of Iowa, and for all conceptual vertical layers of water storage in soils. The interfaces and methodologies developed in this thesis respond to the constant demand for communicating effectively water-related information from academic communities to the public using hydroinformatics tools to provide an accessible portal to the information generated by complex hydrological models. It also facilitates model development and evaluation by allowing rapid development of what-if scenarios. This work represents a significant advance in this direction, and the results have been made publicly available online under the URL http://ifis.iowafloodcenter.org/ifis/sc/modelplus/.

In last decades, the importance of flood damage and loss estimation systems has increased significantly because of its social and economic outcomes. Flood damage and loss estimation systems are useful to understand possible impacts of flooding and prepare better resilience plans to manage and allocate resources for emergency decision makers. Recent web-based technologies can be utilized to create a system that can help to analyze flood impact both on the urban and rural area. With taking advantage of web-based systems, decision makers can observe effects of flooding considering many different scenarios with requiring less effort. Most of the emergency management plans have been created using paper-based maps or GIS (Geographical Information System) software. Paper-based materials generally illustrate floodplain maps and give basic instructions about what to do during flooding event and show main roads to evacuate people from their neighborhood. After the development of GIS (Geographic Information System) software, these plans have been prepared with giving more detail information about demographics, building, critical infrastructure etc. With taking advantage of GIS, there are several software have been developed for the understanding of disaster impacts on the community. One of the widely-used GIS-based software called Hazus-MH (Multi-Hazard) which is created by FEMA (Federal Emergency Management Agency) can analyze disaster effects on both urban and rural area. Basically, it allows users to run a disaster simulation (earthquake, hurricane, and flood) to observe disaster effects. However, its capabilities are not broad as web-based technologies. Hazus-MH has some limitations in terms of working with specific software requirements, the ability to show a limited number of flood scenarios and lack of representing real time situation. For instance, the software is only compatible with Windows operated computers and specific version of ArcMap rather than other GIS software. Users must have GIS expertise to operate the software. In contrast, web-based system allows use to reduce all these limitations. Users can operate the system using the internet browser and do not require to have GIS knowledge. Thus, hundreds of people can connect to the system, observe flood impact in real time and explore their neighborhood to prepare for flooding. In this study, Iowa Flood Damage Estimation Platform (IFDEP) is introduced. This platform is created using various data sources such as floodplain maps and rasters which are created by IFC (Iowa Flood Center), default Hazus-MH data, census data, National Structure Inventory, real-time USGS (United States Geological Survey) Stream gage data, real time IFC bridge sensor data, and flood forecast model which created by IFC. To estimate damage and loss, damage curves which are created by Army Corps of Engineers are implemented. All of these data are stored in PostgreSQL. Therefore, hundreds of different flood analyses can be queried with making cross-sectional analyses between floodplain data and census data. Regarding to level analyses which are defined by FEMA as three level, Level 3 type analysis can be done on the fly with using web-based technology. Furthermore, better and more accurate results are presented to the users. Using real-time stream gauge data and flood forecast data allow to demonstrate current and upcoming flood damage and loss which cannot be provided by current GIS-based desktop software. Furthermore, analyses are visualized using JavaScript and HTML5 for better illustration and communication rather than using limited visualization selection of GIS software. To give the vision of this study, IFDEP can be widened using other data sources such as National Resources Inventory, National Agricultural Statistics Service, U.S. census data, Tax Assessor building data, land use data and more. This can be easily done on the database side. Need to address that augmented reality (AR) and virtual reality (VR) technologies can enhance to broad capabilities of this platform. For this purpose, Microsoft HoloLens can be utilized to connect IFDEP, real-time information can be visualized through the device. Therefore, IFDEP can be recruited both on headquarters for emergency managers and on the field for emergency management crew.

This paper documents the design and creation of an App Library for HydroShare water resources data and software discovery and sharing system. This App Library was developed to simplify the discovery process for using environmental web applications and to lower hosting requirements for such a repository. To accomplish this goal, I created the HydroShare App Library as a standalone web application using the React JavaScript framework. The App Library application uses the existing HydroShare resource connectors to allow the registration of all web applications within the App Library without having external software requirements. This allows the HydroShare App Library to be a centralized location for web app developers to register their tools and models using their preferred software while allowing water resources managers, engineers, scientists, and decision-makers to find these tools in a single location. The developed HydroShare App Library allows the discovery of all web applications that are included in the HydroShare ecosystem and not just CUAHSI-owned web apps. This is done by using a dynamic table with React that automatically updates the user interface without having to reload entire pages. This approach allows this web app to reduce processing for the App Library by only rendering web app entries that are relevant to the current user. This allows the App Library to grow and continue to be effective as more web applications are registered in HydroShare and are discoverable within the App Library.

Hydrologic Information Systems (HIS) have emerged as a means to organize, share, and synthesize water data. This work extends current HIS capabilities by providing additional capacity and flexibility for marine physical and chemical observations data and for freshwater and marine biological observations data. These goals are accomplished in two broad and disparate case studies – an HIS implementation for the oceanographic domain as applied to the offshore environment of the Chukchi Sea, a region of the Alaskan Arctic, and a separate HIS implementation for the aquatic biology and environmental flows domains as applied to Texas rivers. These case studies led to the development of a new four-dimensional data cube to accommodate biological observations data with axes of space, time, species, and trait, a new data model for biological observations, an expanded ontology and data dictionary for biological taxa and traits, and an expanded chain-of-custody approach for improved data source tracking. A large number of small studies across a wide range of disciplines comprise the “Long Tail” of science. This work builds upon the successes of the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) by applying HIS technologies to two new Long Tail disciplines: aquatic biology and oceanography. In this regard this research improves our understanding of how to deal with collections of biological data stored alongside sensor-based physical data. Based on the results of these case studies, a common framework for water information management for terrestrial and marine systems has emerged which consists of Hydrologic Information Systems for observations data, Geographic Information Systems for geographic data, and Digital Libraries for documents and other digital assets. It is envisioned that the next generation of HIS will be comprised of these three components and will thus actually be a Water Information System of Systems. / text