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Ryan J. MacDonald, James M. Byrne, Stefan W. Kienzle, and Robert P. Larson

( Barnett et al. 2005 ; Lapp et al. 2005 ). Numerous studies have already shown hydrological changes in snow-dominated regions, with the earlier onset of melt ( Cayan et al. 2001 ; Mote et al. 2005 ; Stewart et al. 2004 , 2005 ; Stewart 2009 ) and decreases in mean annual streamflow ( Zhang et al. 2001 ; Rood et al. 2005 ). This study investigates the potential effects of climate change on mountain snowpack in the St. Mary River watershed, Montana. The International Joint Commission, a cooperative

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Julie Rose N. Javier, James A. Smith, Katherine L. Meierdiercks, Mary Lynn Baeck, and Andrew J. Miller

1. Introduction The utility of distributed hydrologic models in combination with high-resolution Weather Surveillance Radar-1988 Doppler (WSR-88D) rainfall estimates is examined in this paper for flash flood forecasting in small urban watersheds. The hydrologic model ( Morrison and Smith 2001 ; Giannoni et al. 2003 ; Smith et al. 2005a ) consists of a simple infiltration model (see Ogden and Saghafian 1997 ) and a geomorphological instantaneous unit hydrograph (GIUH)-based representation of

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Brianne K. Smith, James Smith, and Mary Lynn Baeck

1. Introduction Flash flooding in urban watersheds causes fatalities ( Mooney 1983 ; Ashley and Ashley 2008 ), damages ( Ogden et al. 2000 ), and degradation of stream channel health ( Booth 1990 ; Paul and Meyer 2001 ). These impacts can be mitigated through better flash flood forecasting and urban storm water infrastructure design, which is often based on design storm calculations. In this study, we seek to characterize storms that cause flash flooding in a prototypical flash flood

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Jason A. Hubbart and Chris Zell

1. Introduction Urban waterways and resident aquatic communities are exposed to several anthropogenic stressors or risks that may occur less frequently or be entirely absent in watersheds that have predominantly rural but mixed land uses ( Walsh et al. 2005 ; Wenger et al. 2009 ). Hydrogeomorphic impacts stemming from reapportionment of freshwater supplies in urbanizing environments include (but are not limited to) channel incision, streambed sedimentation, increased contaminant transport

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Guoxiang Yang, Laura C. Bowling, Keith A. Cherkauer, Bryan C. Pijanowski, and Dev Niyogi

researchers have also examined urban effects on biological systems. Poff and Allan (1995) and Clausen and Biggs (1997) identified that hydrologic variability is a significant environmental variable influencing lotic ecosystems. Thus, increasing impervious cover in a watershed has a substantial influence on biological degradation ( Booth and Jackson 1997 ; Wang et al. 2001 ; Booth et al. 2004 ). Much of the previous research on hydrologic response to urbanization relies on empirical studies of daily

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Brianne K. Smith and James A. Smith

into the spatial distribution of flash flooding across the United States. O’Connor and Costa (2004) investigated the largest rainfall-induced floods across the United States using the U.S. Geological Survey (USGS) streamflow record. Michaud et al. (2001) investigated flooding in small watersheds for the median and 25-yr flood and exceptional flood events. Maddox et al. (1979) looked at 5 years of flash flood events based on the NOAA Storm Data publication. A U.S. flash flood database has been

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Dawit A. Zeweldi, Mekonnen Gebremichael, and Charles W. Downer

such large scales, hydrologic model simulations driven by the existing rain gauge network, albeit sparse in some regions, perform well. However, studies on the capabilities and limitations of satellite precipitation products for hydrological applications in small watersheds are still lacking. The objectives of this study were to assess the use of high-resolution satellite precipitation product as input to a hydrologic model for streamflow simulation and to assess the impact of model calibration

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Kathleen D. Holman

–Southern Oscillation, Pacific decadal oscillation), variations in watershed conditions, and channel and floodplain morphology ( Jain and Lall 2000 ; Alila and Mtiraoui 2002 ; Merz and Blöschl 2003 ). Some studies utilize time of year as a metric for flood mechanisms ( Burn 1997 ; Pizarro and Lall 2002 ; Sivandran 2002 ; De Michele and Rosso 2002 ; Todhunter 2012 ). However, using flood seasonality as a metric for a mechanism can be problematic in watersheds where multiple processes act during the same time

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Sarah A. Baker, Andrew W. Wood, and Balaji Rajagopalan

aversion ( Callahan et al. 1999 ; Kirchhoff et al. 2013 ; Rayner et al. 2005 ; White et al. 2017 ). Baker et al. (2019) sought to address some of these hurdles by translating and bias-correcting S2S climate forecasts to a watershed spatial unit—U.S. Geological Survey (USGS) hydrologic unit code 4 (HUC4) watersheds—for biweekly, monthly, and seasonal prediction periods. This aggregated forecast product was made available in real time on the S2S Climate Outlooks for Watersheds web-based tool ( http

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Lu Yi, Bin Yong, Junxu Chen, Ziyan Zheng, and Ling Li

elements. Section 4 will give the conclusions and highlight the limitations of this study. 2. Data and methods a. Study area and event 1) Study area This research was carried out in the Wangjiaba (WJB) watershed, covering an area of 30 630 km 2 . It is an upstream subbasin of the Huaihe River basin (HRB), which is one of the seven major basins in China and lies between the Yellow River and the Yangze River ( Fig. 1a ). The HRB is in the climate transition zone between north and south China; it has a

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