Precipitation Modeling in Mountainous Areas for the National Weather Service River Forecast System

Larson, Lee W.; Monro, John C.

doi:10.1029/sp004p0189

Cited by 11 publications

(13 citation statements)

References 2 publications

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“…The available temperature-index method in the HEC-HMS software [53] was used for the three aforementioned HEC-HMS-based models. The simple degree-day snowmelt module (DDM) [58] was added to the SMARG and GR4J models, while the SACSMA and MACHBV models were combined with the more complex SNOW17 snowmelt estimation method [60,61] for snow-rainfall discrimination and quantifying snowpack changes over the simulation period.…”

Section: Hydrological Modelsmentioning

confidence: 99%

Inter-Comparison of Different Bayesian Model Averaging Modifications in Streamflow Simulation

Darbandsari

Coulibaly

2019

Water

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Bayesian model averaging (BMA) is a popular method using the advantages of forecast ensemble to enhance the reliability and accuracy of predictions. The inherent assumptions of the classical BMA has led to different variants. However, there is not a comprehensive examination of how these solutions improve the original BMA in the context of streamflow simulation. In this study, a scenario-based analysis was conducted for assessment of various modifications and how they affect BMA results. The evaluated modifications included using various streamflow ensembles, data transformation procedures, distribution types, standard deviation forms, and optimization methods. We applied the proposed analysis in two data-poor watersheds located in northern Ontario, Canada. The results indicate that using more representative distribution types do not significantly improve BMA-derived results, while the positive effect of implementing non-constant variance on BMA probabilistic performance cannot be ignored. Also, higher reliability was obtained by applying a data transformation procedure; however, it can reduce the results’ sharpness significantly. Moreover, although considering many streamflow simulations as ensemble members does not always enhance BMA results, using different forcing precipitation scenarios besides multi-models led to better BMA-based probabilistic simulations in data-poor watersheds. Also, the reliability of the expectation-maximization algorithm in estimating BMA parameters was confirmed.

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Section: Hydrological Modelsmentioning

confidence: 99%

Inter-Comparison of Different Bayesian Model Averaging Modifications in Streamflow Simulation

Darbandsari

Coulibaly

2019

Water

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“…Through the analysis of daily flow observations at the Jiangka hydrometric station, it has been concluded that situations with "one day, one peak" and even "one day, multiple peaks" occur due to the melting of mountain snow [22,23]. Many models with snowmelt modules have been developed [24][25][26][27][28][29], including empirical models, conceptual models, physically based models, and distributed hydrological models. Calculation methods range from complex energy balance [30] to degree-day and water balance [31][32][33].…”

Section: Introductionmentioning

confidence: 99%

Inclusion of Modified Snow Melting and Flood Processes in the SWAT Model

Duan

Meng

et al. 2018

Water

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Flooding, one of the most serious natural disasters, poses a significant threat to people’s lives and property. At present, the forecasting method uses simple snowmelt accumulation and has certain regional restrictions that limit the accuracy and timeliness of flood simulation and prediction. In this paper, the influence of accumulated temperature (AT) and maximum temperature (MT) on snow melting was considered in order to (1) reclassify the precipitation categories of the watershed using a separation algorithm of rain and snow that incorporates AT and MT, and (2) develop a new snow-melting process utilizing the algorithm in the Soil and Water Assessment Tool Model (SWAT) by considering the effects of AT and MT. The SWAT model was used to simulate snowmelt and flooding in the Tizinafu River Basin (TRB). We found that the modified SWAT model increased the value of the average flood peak flow by 43%, the snowmelt amounts increased by 45%, and the contribution of snowmelt to runoff increased from 44.7% to 54.07%. In comparison, we concluded the snowmelt contribution to runoff, flood peak performance, flood process simulation, model accuracy, and time accuracy. The new method provides a more accurate simulation technique for snowmelt floods and flood simulation.

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“…For instance, the current snow forecasting model SNOW-17 [61] uses a parameter to represent the maximum possible snow melt rate. The parameter is typically determined from historical temperature data.…”

Section: Implications Of This Studymentioning

confidence: 99%

“…Another area for enhancement is developing new snow accumulation and ablation processes and incorporating them to the operational forecasting model. The current model is built on snow measurements available about four decades ago [61] when anthropogenic change of climate was not as substantial and the stationarity assumption may still have been sound. In the past several decades, significant changes in snowpack volume have been recorded in the Sierra Nevada Mountains [62][63][64] and are projected to continue to change in the future [65].…”

Section: Implications Of This Studymentioning

confidence: 99%

Changes in Extremes of Temperature, Precipitation, and Runoff in California’s Central Valley During 1949–2010

He¹,

Russo²,

Anderson³

et al. 2017

Hydrology

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This study presents a comprehensive trend analysis of precipitation, temperature, and runoff extremes in the Central Valley of California from an operational perspective. California is prone to those extremes of which any changes could have long-lasting adverse impacts on the society, economy, and environment of the State. Available long-term operational datasets of 176 forecasting basins in six forecasting groups and inflow to 12 major water supply reservoirs are employed. A suite of nine precipitation indices and nine temperature indices derived from historical (water year 1949-2010) six-hourly precipitation and temperature data for these basins are investigated, along with nine indices based on daily unimpaired inflow to those 12 reservoirs in a slightly shorter period. Those indices include daily maximum precipitation, temperature, runoff, snowmelt, and others that are critical in informing decision making in water resources management. The non-parametric Mann-Kendall trend test is applied with a trend-free pre-whitening procedure in identifying trends in these indices. Changes in empirical probability distributions of individual study indices in two equal sub-periods are also investigated. The results show decreasing number of cold nights, increasing number of warm nights, increasing maximum temperature, and increasing annual mean minimum temperature at about 60% of the study area. Changes in cold extremes are generally more pronounced than their counterparts in warm extremes, contributing to decreasing diurnal temperature ranges. In general, the driest and coldest Tulare forecasting group observes the most consistent changes among all six groups. Analysis of probability distributions of temperature indices in two sub-periods yields similar results. In contrast, changes in precipitation extremes are less consistent spatially and less significant in terms of change rate. Only four indices exhibit statistically significant changes in less than 10% of the study area. On the regional scale, only the American forecasting group shows significant decreasing trends in two indices including maximum six-hourly precipitation and simple daily intensity index. On the other hand, runoff exhibits strong resilience to the changes noticed in temperature and precipitation extremes. Only the most southern reservoir (Lake Isabella) shows significant earlier peak timing of snowmelt. Additional analysis on runoff indices using different trend analysis methods and different analysis periods also indicates limited changes in these runoff indices. Overall, these findings are meaningful in guiding reservoir operations and water resources planning and management practices. IntroductionClimatic and weather-induced hazards including excessive heat, flooding, and drought are often economically, environmentally, and societally disruptive [1][2][3]. Previous studies have suggested that such hazards are typically caused by changes in the frequency and intensity rather than the mean of hydro-climatic variables including precipita...

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Precipitation Modeling in Mountainous Areas for the National Weather Service River Forecast System

Cited by 11 publications

References 2 publications

Inter-Comparison of Different Bayesian Model Averaging Modifications in Streamflow Simulation

Inter-Comparison of Different Bayesian Model Averaging Modifications in Streamflow Simulation

Inclusion of Modified Snow Melting and Flood Processes in the SWAT Model

Changes in Extremes of Temperature, Precipitation, and Runoff in California’s Central Valley During 1949–2010

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