An asynchronous solver for systems of ODEs linked by a directed tree structure

Small, Scott J.; Jay, Laurent O.; Mantilla, Ricardo; Curtu, Rodica; Cunha, L.; Fonley, Morgan; Krajewski, Witold F.

doi:10.1016/j.advwatres.2012.10.011

Cited by 58 publications

(37 citation statements)

References 17 publications

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“…Each channel link and the associated hillslopes (drainage area on the two sides of the channel link) are assigned a Strahler order. For more information about this hillslope-link based representation of the landscape, please refer to our previous papers (e.g., Mantilla, 2007;Mandapaka et al, 2009;Small et al, 2013). As in the works of Clark et al (2009) andHarman et al (2009), our model assumes a linear drainage process at the hillslope scale…”

Section: Structure Of the Distributed Drainage Modelmentioning

confidence: 98%

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Recession analysis across scales: The impact of both random and nonrandom spatial variability on aggregated hydrologic response

Chen

Krajewski

2015

Journal of Hydrology

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Section: Structure Of the Distributed Drainage Modelmentioning

confidence: 98%

“…The recession processes at the hillslope scale are aggregated to those at larger scales through channel routing (Mantilla, 2007;Small et al, 2013) …”

Section: Structure Of the Distributed Drainage Modelmentioning

confidence: 99%

Recession analysis across scales: The impact of both random and nonrandom spatial variability on aggregated hydrologic response

Chen

Krajewski

2015

Journal of Hydrology

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“…However, the computational demands of simulating large areas ($ 10 5 km 2 ) while preserving a sub-hillslope partitioning required by these models becomes a practical limitation. ODEs, on the other hand, can be solved very efficiently using parallel integrators [25].…”

Section: Introductionmentioning

confidence: 99%

An integral-balance nonlinear model to simulate changes in soil moisture, groundwater and surface runoff dynamics at the hillslope scale

Curtu

Mantilla

Fonley

et al. 2014

Advances in Water Resources

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“…Refer to Cunha [] for a complete description of the model equations, and Small et al . [] for a description of the model numeric. CUENCAS has also been used by Mantilla and Gupta [], Mandapaka et al .…”

Section: Hydrological Simulationmentioning

confidence: 99%

Uncertainty in radar‐rainfall composite and its impact on hydrologic prediction for the eastern Iowa flood of 2008

Seo

Cunha

Krajewski

2013

Water Resources Research

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[1] This study addresses a significant potential source of error that exists in radar-rainfall maps that are combined using data from multiple WSR-88D radars of the Next Generation Radar (NEXRAD) national network in the United States. This error stems from different radar calibration offsets that create a border within discontinuous rainfall fields at the equidistance zone among radars. The discontinuity in rainfall fields could lead to misestimation of rainfall over basins and subsequently, to significant errors in streamflow predictions through a hydrologic model. In this study, we produce enhanced radar-rainfall estimates (HN3) based on a novel approach that allows us to reduce the effects of the relative radar calibration bias. We use the relative bias information previously presented in a radar reflectivity comparison study. To investigate the effects of the relative bias adjustment, we evaluate the HN3 and Stage IV radar-rainfall by comparing them with rain gauge data and analyzing their ability to simulate streamflow for an extreme flood case. While the HN3 estimates are statistically comparable to the Stage IV estimates in the rain gauge data comparison, the borderline that identifies discontinuous rainfall fields disappears in the HN3 estimates. We performed hydrological simulations using a physically based, data-intensive, calibration-free, hillslope-link hydrologic model called CUENCAS and demonstrated CUENCAS's ability to accurately simulate flows by comparing results with observed and predicted streamflow generated by the Sacramento (SAC) model. SAC is the operational flood forecast model that has been used by the National Weather Service since 1969, and it was extensively calibrated based on historical data. The simulation results show that the adjustment improves streamflow predictions in the regions where the misestimation of rainfall quantity is considerable. We conclude that systematic error arising from different calibration offsets in rainfall fields can significantly affect hydrologic predictions.

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An asynchronous solver for systems of ODEs linked by a directed tree structure

Cited by 58 publications

References 17 publications

Recession analysis across scales: The impact of both random and nonrandom spatial variability on aggregated hydrologic response

Recession analysis across scales: The impact of both random and nonrandom spatial variability on aggregated hydrologic response

An integral-balance nonlinear model to simulate changes in soil moisture, groundwater and surface runoff dynamics at the hillslope scale

Uncertainty in radar‐rainfall composite and its impact on hydrologic prediction for the eastern Iowa flood of 2008

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