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Rebecca A. Purvis, Ryan J. Winston, William F. Hunt, Brian Lipscomb, Karthik Narayanaswamy, Andrew McDaniel, Matthew S. Lauffer and Susan Libes
Bioswales are a promising stormwater control measure (SCM) for roadway runoff management, but few studies have assessed performance on a field scale. A bioswale is a vegetated channel with underlying engineered media and a perforated underdrain to promot...
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Li Li and Kyung Soo Jun
River flood routing computes changes in the shape of a flood wave over time as it travels downstream along a river. Conventional flood routing models, especially hydrodynamic models, require a high quality and quantity of input data, such as measured hyd...
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Lilai Jin, Sarah J. Higgins, James A. Thompson, Michael P. Strager, Sean E. Collins and Jason A. Hubbart
Saturated hydraulic conductivity (Ksat) is a hydrologic flux parameter commonly used to determine water movement through the saturated soil zone. Understanding the influences of land-use-specific Ksat on the model estimation error of water balance compon...
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Matina Shakya, Amanda Hess, Bridget M. Wadzuk and Robert G. Traver
The recovery of soil void space through infiltration and evapotranspiration processes within green stormwater infrastructure (GSI) is key to continued hydrologic function. As such, soil void space recovery must be well understood to improve the design an...
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Fazlul Karim, Mohammed Ali Armin, David Ahmedt-Aristizabal, Lachlan Tychsen-Smith and Lars Petersson
Machine learning (also called data-driven) methods have become popular in modeling flood inundations across river basins. Among data-driven methods, traditional machine learning (ML) approaches are widely used to model flood events, and recently deep lea...
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Shiva Gopal Shrestha and Soni M. Pradhanang
The general practice of rainfall-runoff model development towards physically based and spatially explicit representations of hydrological processes is data-intensive and computationally expensive. Physically based models such as the Soil Water Assessment...
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Gabriel B. Senay, Stefanie Kagone, Gabriel E. L. Parrish, Kul Khand, Olena Boiko and Naga M. Velpuri
We enhanced the agro-hydrologic VegET model to include snow accumulation and melt processes and the separation of runoff into surface runoff and deep drainage. Driven by global weather datasets and parameterized by land surface phenology (LSP), the enhan...
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Taylor Joyal, Alexander K. Fremier and Jan Boll
In the humid tropics, forest conversion and climate change threaten the hydrological function and stationarity of watersheds, particularly in steep terrain. As climate change intensifies, shifting precipitation patterns and expanding agricultural and pas...
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Pouya Hosseinzadeh, Ayman Nassar, Soukaina Filali Boubrahimi and Shah Muhammad Hamdi
Streamflow prediction plays a vital role in water resources planning in order to understand the dramatic change of climatic and hydrologic variables over different time scales. In this study, we used machine learning (ML)-based prediction models, includi...
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Randika K. Makumbura, Miyuru B. Gunathilake, Jayanga T. Samarasinghe, Remegio Confesor, Nitin Muttil and Upaka Rathnayake
Hydrologic models are indispensable tools for water resource planning and management. Accurate model predictions are critical for better water resource development and management decisions. Single-site model calibration and calibrating a watershed model ...
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