RWater – A Cyber Enabled Tool For Hydrologic Modeling And Analysis

Existing distributed hydrologic models are complex and computationally demanding for using as a rapid-forecasting policy-decision tool, or even as a class-room educational tool. In addition, platform dependence, specific input/output data structures and non-dynamic data-interaction with pluggable software components inside the existing proprietary frameworks make these models restrictive only to the specialized user groups. RWater is a web-based hydrologic analysis and modeling framework that utilizes the commonly used R software within the HUBzero cyber infrastructure of Purdue University. RWater is designed as an integrated framework for distributed hydrologic simulation, along with subsequent parameter optimization and visualization schemes. RWater provides platform independent web-based interface, flexible data integration capacity, grid-based simulations, and user-extensibility. RWater uses RStudio to simulate hydrologic processes on raster based data obtained through conventional GIS pre-processing. The program integrates Shuffled Complex Evolution (SCE) algorithm for parameter optimization. Moreover, RWater enables users to produce different descriptive statistics and visualization of the outputs at different temporal resolutions. The applicability of RWater will be demonstrated by application on two watersheds in Indiana for multiple rainfall events

The changing face of floodplains in the Mississippi River Basin detected by a 60-year land use change dataset

Floodplains provide essential ecosystem functions, yet \u3e80% of European and North American floodplains are substantially modified. Despite floodplain changes over the past century, comprehensive, long-term land use change data within large river basin floodplains are limited. Long-term land use data can be used to quantify floodplain functions and provide spatially explicit information for management, restoration, and flood-risk mitigation. We present a comprehensive dataset quantifying floodplain land use change along the 3.3 million km2 Mississippi River Basin (MRB) covering 60 years (1941–2000) at 250-m resolution. We developed four unique products as part of this work, a(n): (i) Google Earth Engine interactive map visualization interface, (ii) Python code that runs in any internet browser, (iii) online tutorial with visualizations facilitating classroom code application, and (iv) instructional video demonstrating code application and database reproduction. Our data show that MRB’s natural floodplain ecosystems have been substantially altered to agricultural and developed land uses. These products will support MRB resilience and sustainability goals by advancing data-driven decision making on floodplain restoration, buyout, and conservation scenarios

SWATShare – A Web-Portal For Hydrology Research And Education Using Soil Water And Assessment Tool

Many hydrologic modelers around the world use Soil Water Assessment and Tool (SWAT) to simulate hydrologic processes, water quality loadings and testing agricultural management scenarios. Once these tasks are complete including publication of results, the models generally are not published or made available to the public for further use and improvement. Although publication or sharing of models is not required for journal publications, sharing of models may open doors for new collaborations, and avoids duplication of efforts if other researchers are interested in simulating a particular watershed for which a model already exists. For researchers, who are interested in sharing models, there are limited avenues to publishing their models to the wider community. Towards filling this gap, a prototype cyberinfrastructure (CI), called SWATShare, is developed for publishing, sharing and running SWAT models in an interactive GIS-enabled web environment. Users can utilize SWATShare to publish or upload their own models, search and download existing SWAT models developed by others, run simulations including calibration using high performance resources provided by XSEDE and Cloud. In addition to research, SWATShare enables sharing and using of SWAT model outputs that can be used for understanding the hydrology of different watersheds within a classroom setting

Design of a Metadata Framework for the Environmental Models with an Example Hydrologic Application in HydroShare

Environmental modelers rely on a variety of computational models to make predictions, test hypotheses, and address specific problems related to environmental science and natural resource management. Scientists and engineers must devote significant effort to preparing these computational models. While significant attention has been devoted to sharing and reusing environmental data, less attention has been devoted to sharing and reusing environmental models. A first step toward increasing environmental model sharing and reuse is to define a general metadata framework for models that is flexible and, therefore, applicable across the wide variety of models used by environmental modelers. This paper proposes a general approach for representing environmental model metadata that extends the Dublin Core metadata framework. The framework is implemented within the HydroShare system and applied for a hydrologic model sharing use case. This example application demonstrates how the metadata framework implemented within HydroShare can assist in model sharing, publication, reuse, and reproducibility

Improved Soil Moisture Accounting in Hydrologic Models

Uncertainty is inherent in any hydrologic prediction; an apparently well-performing model can be pseudo-accurate giving right answers for wrong reasons. Soil Moisture Accounting (SMA), by playing an important role in partitioning water between surface and sub-surface components, regulates the overall physical consistency and predictive skills of a hydrologic model. Given the complex cause-and-effect relationships among soil moisture, surface runoff and evapotranspiration, this dissertation explores multiple avenues to improve SMA with the aim of improving the overall hydrologic model predictability. Specifically, Soil and Water Assessment Tool (SWAT) is used on four U.S. watersheds to accomplish the following three objectives: (1) evaluation of a multi-objective calibration approach for hydrologic models using remotely sensed soil moisture estimates; (2) re-conceptualization of surface runoff mechanism by incorporating a time-dependent, soil moisture-informed Curve Number method; and (3) direct ingestion of spatially distributed remotely sensed potential evapotranspiration in SWAT to improve the overall energy and water balance. To meet the level of interoperability required between a complex hydrologic model and the remotely sensed “big data” (objectives 1 and 3), a key contribution of this dissertation is the development of a new, adaptive tool that can perform rapid extraction and processing of satellite observations at user-defined spatial resolution. The first objective involves evaluating the relative potential of spatially distributed surface and root zone soil moisture estimates in the calibration of SWAT model. Considering two agricultural watersheds in Indiana, USA, the proposed calibration approach is performed using remotely sensed Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) surface soil moisture (~1 cm top soil) estimates in sub-basin/HRU level together with observed streamflow data at the watershed’s outlet. Although application of remote sensing data in calibration improves surface soil moisture simulation, other hydrologic components such as streamflow and deeper layer moisture content remain less affected. An extension of this approach to apply root zone soil moisture estimates from limited field sensor data showed considerable improvement in those cases. Difference in relative sensitivity of parameters and reduced extent of uncertainty are also evident from the proposed method, especially for parameters related to the sub-surface hydrologic processes. The second objective involves incorporating a time-dependent SMA based Curve Number method (SMA_CN) in the SWAT model and compare its performance with the existing CN method by simulating the hydrology of two agricultural watersheds in Indiana, USA. Results show that fusion of the SMA_CN method in SWAT better predicts streamflow in all wetness conditions, thereby addressing issues related to peak and low flow predictions by SWAT in many past studies. Comparison of the calibrated model outputs with field-scale soil moisture observations reveals that the SMA overhauling enables SWAT to represent soil moisture condition more accurately, with better response to the incident rainfall dynamics. While the results from the newly introduced SMA_CN method are promising, functionality of this method would likely to be more pronounced if applied for sub-daily hydrologic forecasting. Source-attribution of evapotranspiration uncertainty in a hydrologic model and evaluation of a remote sensing based solution are the two main aspects of the third objective. Using SWAT for three US watersheds from Indiana and Arkansas, this study first addresses the effects of parameter equifinality, energy related weather input-uncertainty and lack of geo-spatial representation on evapotranspiration simulation. In every case, remotely sensed 8-day total actual evapotranspiration (AET) estimate from Moderate Resolution Imaging Spectroradiometer (MODIS) is used as the reference to evaluate model outcome. Results from these assessments indicate the likelihood of a pseudo-accurate model that invariably shows high streamflow prediction skills despite having severely erroneous spatio-temporal dynamics of AET. As a remedial measure, a hybrid daily PET estimate, derived from MODIS and the North American Land Data Assimilation System phase 2 (NLDAS-2), is directly ingested at each Hydrologic Response Units (HRUs) of the SWAT model to create a new configuration called SWAT-PET. Noticeably increased accuracy of three water balance components (soil moisture, AET and streamflow) in SWAT-PET, being evaluated against completely independent sources of observations/reference estimates (i.e. field sensor, satellite and gauge stations), proves the efficacy of the proposed approach towards improving physical consistency of hydrologic modeling. While the proposed approach is evaluated for a past period, the main motivation here is to serve the purpose of hydrologic forecasting once near real-time PET estimates become available. Although three objectives are accomplished through separate studies, the proposed approaches are designed to function in an integrated way if applied together in a particular hydrologic model. While designing the methodologies, main focus was to ensure replicability such that research results from this dissertation can be readily translated into practice

A Comprehensive Modeling Study on Regional Climate Model (RCM) Application — Regional Warming Projections in Monthly Resolutions under IPCC A1B Scenario

Some of the major dimensions of climate change include increase in surface temperature, longer spells of droughts in significant portions of the world, associated higher evapotranspiration rates, and so on. It is therefore essential to comprehend the future possible scenario of climate change in terms of global warming. A high resolution limited area Regional Climate Model (RCM) can produce reasonably appropriate projections to be used for climate-scenario generation in country-scale. This paper features the development of future surface temperature projections for Bangladesh on monthly resolution for each year from 2011 to 2100 applying Providing Regional Climates for Impacts Studies (PRECIS), and it explains in detail the modeling processes including the model features, domain size selection, bias identification as well as construction of change field for the concerned climatic variable, in this case, surface temperature. PRECIS was run on a 50 km horizontal grid-spacing under the Intergovernmental Panel on Climate Change (IPCC) A1B scenario and it was found to perform reasonably well in simulating future surface temperature of Bangladesh. The linear regression between observed and model simulated results of monthly average temperatures, within the 30-year period from 1971 to 2000, gives a high correlation of 0.93. The applied change field in average annual temperature shows only 0.5 °C–1 °C deviation from the observed values over the period from 2005 to 2008. Eventually, from the projected average temperature change during the years 1971–2000, it is apparent that warming in Bangladesh prevails invariably every month, which might eventually result in an average annual increase of 4 °C by the year 2100. Calculated anomalies in country-average annual temperature mostly remain on the positive side throughout the period of 2071–2100 indicating an overall up-shift. Apart from these quantitative analyses of temporal changes of temperature, this paper also illustrates their spatial distribution with a view to identify the most vulnerable zones under consequent warming through future times

Streamflow response to potential land use and climate changes in the James River watershed, Upper Midwest United States

Study region: North and South Dakotas, United States Study focus: Changes in watershed hydrology are mainly driven by changes in land use and climate. This study evaluated the impacts of climate and land use changes on streamflow in an agricultural watershed in the Upper Midwest. Three projected climate change scenarios (A1B, A2 and B1) of three general circulation models (CGCM3.1, GFDL-CM2.1, and HADCM3) were developed for mid (2046â2065) and end (2080â2099) of the 21st century. Corresponding land use maps for years 2055 and 2090 were obtained from the FOREcasting SCEnarios of Land-Cover (FORE-SCE) model. The scenarios were designed in a way that land use was changed while climate conditions remain constant, land use was then held constant under a changing climate, and finally both land use and climate were changed simultaneously to reflect possible future land use and climate conditions. New hydrological insights for the region: Potential land use and climate changes would result in 12â18% % and 17â41% increases in annual streamflow, respectively, by end of the century. The combined effects of land use and climate changes would intensify future streamflow responses with 13â60% increases in the region. This study provides a broad perspective on plausible hydrologic alterations in the region, prompting individual and collective opportunities to engage with this topic for sustainable planning and management of watersheds. Keywords: Watershed modeling, Precipitation, Agricultural land, Grassland, Dakota, SWA

Toward a Common Metadata Framework for Representing Water Models as Resources

A large variety of water models exist, each tailored to address specific challenges related to hydrologic science and water resources management. When scientists and engineers apply one of these models to address a specific question, they must devote significant effort to set up, calibrate, and evaluate that model instance built for some place and time. In many cases, there is a benefit to sharing these computer models and associated datasets with the broader scientific community. Core to model reuse in any context is well-defined metadata for describing the model. A standardized metadata framework applicable across models will foster interoperability and encourage reuse and sharing of existing resources. This paper reports on the development of a metadata framework for sharing water models. We also discuss steps taken to implement the resources and metadata framework in the HydroShare system. As an example of the potential benefit of a common model metadata framework, we will present the prototype of a SWAT Model Instance resource type that can used to provide interoperability between the HydroShare system and an external system called SWATShare that is tailored for running SWAT models in the cloud, but lacks the general resource sharing capabilities and goals present in HydroShare. This example is a demonstration of our long-term vision: to establish a common metadata framework for water models that enables interoperability across cyberinfrastructure systems