Featured Work

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Natural Infrastructure

Flood reduction and water quality mediation capacities of natural infrastructures are largely disregarded in conventional watershed modeling and management practices. We are filling this knowledge gap.

Related publications:

• Rajib et al., 2020. DOI: 10.1029/2019WR026561​
• Golden et al., 2019. DOI:10.1021/acs.est.8b07270

Large-scale Locally Relevant Flood Modeling

There is little practical value in a so-called large-scale model when that model produces streamflow and inundation maps only along the main river channels. We showed the feasibility of "large-scale yet locally relevant" flood predictions.

Related publications:

• Rajib et al., 2020. DOI:10.1016/j.jhydrol.2019.124406  
• Maidment et al., 2016. DOI: 10.4211/technical.20161019

Watershed Modeling with Big Data

Remotely sensed Big Data can limit watershed model's tendency to give "right answers for wrong reasons". We developed an advanced SWAT modeling framework which automatically assimilates these emergent datasets.

Related publications:

• Rajib et al., 2020. DOI: 10.3390/rs12132148 ​ 
• Rajib et al., 2018. DOI:10.1029/2017WR021147

Cyber-infrastructure for Hydrology 

We develop innovative research approaches and classroom instruction modules for web-based access, integration, sharing, and visualization of hydrologic data, metadata, and model results. Our work contributes to Findable, Accessible, Interoperable, and Reproducible (FAIR) hydrologic sciences.

Related publications:​

• Rajib et al., 2016. DOI:10.1016/j.envsoft.2015.10.032 

Last updated: August 19, 2020