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Abstract
The current influx of climate related information required scientists to communicate their findings to decision makers in governments, disaster preparedness organizations, and the general public. The Soil and Water Assessment Tool (SWAT) is a powerful modelling tool that allows scientists to simulate many of the physical processes involved in the water cycle. This article presents the design, methods and development efforts to overcome some of the limitations of the previously developed SWAT visualization software programs by creating a set of modular web applications that can be duplicated, customized, and run. Moreover, this article features a web application development tool for climate data retrieval. The NASAaccess fetches, extracts and reformats climate data from the National Aeronautics and Space Administration servers and outputs data compatible with hydrological models. This work has the potential to increase the SWAT's model impact on non-technically trained stakeholders and decision makers charged with water and climate management.
Highlights
Over the last several years the issue of climate change has come to the forefront of many political and economic issues
The Soil and Water Assessment Tool (SWAT) is a powerful modelling tool that allows scientists to simulate many of the physical processes involved in the water cycle (Arnold and Fohrer, 2005; Arnold et al, 2012; Douglas-Mankin et al, 2010; Gassman et al, 2007)
Data used in the land use land cover and soil layers examples are obtained from the SWAT model described by Mohammed et al, (2018)
Summary
Over the last several years the issue of climate change has come to the forefront of many political and economic issues. The emergence of better technologies to access, analyze, and share climate information can greatly improve the efforts of governments around the world and people in disaster-prone areas to prepare for, and respond to changes in climate and the increasing frequencies of disasters Earth observations, both from space and ground, when supplemented with climate models and statistical data assimilation methods have already proven to be powerful tools in forecasting future events, analyzing past events, and performing various scenario analyses to assist in disaster preparedness and future infrastructure planning. The people responsible for making decisions based on the information from these climate data and models generally do not have the infrastructure, the time, or the technical expertise to sift through and analyze the raw data to make the informed decisions for which the data was produced in the first place (Dahlhaus et al, 2015) For this reason, the full potential of the SWAT model and other climate data sources has yet to be realized. This means that the apps provided and presented in this work can be replicated, customized, and implemented anywhere (Ames et al, 2016; Croney et al, 2007) for any watershed with the SWAT model output data
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