Runoff simulation performance of multi-source precipitation products in small watersheds of different climatic regions in the USA

2020 ◽  
Vol 67 (2/3/4) ◽  
pp. 223
Author(s):  
Kepeng Feng ◽  
Yang Hong ◽  
Juncang Tian ◽  
Guoqiang Tang ◽  
Guangyuan Kan ◽  
...  
Keyword(s):  
Runoff Simulation ◽  
Simulation Performance ◽  
Climatic Regions ◽  
Small Watersheds ◽  
The Usa

Runoff simulation performance of multi-source precipitation products in small watersheds of different climatic regions in the USA

2020 ◽  
Vol 67 (2/3/4) ◽  
pp. 223
Author(s):  
Xiangyu Luo ◽  
Guangyuan Kan ◽  
Guoqiang Tang ◽  
Juncang Tian ◽  
Kepeng Feng ◽  
...  
Keyword(s):  
Runoff Simulation ◽  
Simulation Performance ◽  
Climatic Regions ◽  
Small Watersheds ◽  
The Usa

scholarly journals An improved routing algorithm for a large-scale distributed hydrological model with consideration of underlying surface impact

2020 ◽  
Vol 51 (5) ◽  
pp. 834-853
Author(s):  
Jingjing Li ◽  
Haoyuan Zhao ◽  
Jun Zhang ◽  
Hua Chen ◽  
Chong-Yu Xu ◽  
...  
Keyword(s):  
Large Scale ◽  
Yangtze River Basin ◽  
Poor Performance ◽  
Underlying Surface ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Runoff Simulation ◽  
Temporal And Spatial Distribution ◽  
Simulation Performance ◽  
Routing Method

Abstract Large-scale hydrological models are important tools for simulating the hydrological effect of climate change. As an indispensable part of the application of distributed hydrological models, large-scale flow routing methods can simulate not only the discharge at the outlet but also the temporal and spatial distribution of flow. The aggregated network-response function (NRF), as a scale-independent routing method, has been tested in many basins and demonstrated to have good runoff simulation performance. However, it had a poor performance and produced an unreasonable travel time when it was applied to certain basins due to a lack of consideration of the influence of the underlying surface. In this study, we improve the NRF routing method by combining it with a velocity function using a new routing parameter b to reflect the wave velocity's sensitivity to slope. The proposed method was tested in 15 catchments at the Yangtze River basin. The results show that it can provide better daily runoff simulation performance than the original routing model and the calibrated travel times in all catchments are more reasonable. Therefore, our proposed routing method is effective and has great potential to be applied to other basins.

scholarly journals Deep Learning with a Long Short-Term Memory Networks Approach for Rainfall-Runoff Simulation

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1543 ◽  
Author(s):  
Caihong Hu ◽  
Qiang Wu ◽  
Hui Li ◽  
Shengqi Jian ◽  
Nan Li ◽  
...  
Keyword(s):  
Deep Learning ◽  
Short Term Memory ◽  
Network Models ◽  
Machine Learning Techniques ◽  
Rainfall Runoff ◽  
Ann Model ◽  
Runoff Simulation ◽  
Simulation Performance ◽  
Artificial Neural Network Ann ◽  
Runoff Events

Considering the high random and non-static property of the rainfall-runoff process, lots of models are being developed in order to learn about such a complex phenomenon. Recently, Machine learning techniques such as the Artificial Neural Network (ANN) and other networks have been extensively used by hydrologists for rainfall-runoff modelling as well as for other fields of hydrology. However, deep learning methods such as the state-of-the-art for LSTM networks are little studied in hydrological sequence time-series predictions. We deployed ANN and LSTM network models for simulating the rainfall-runoff process based on flood events from 1971 to 2013 in Fen River basin monitored through 14 rainfall stations and one hydrologic station in the catchment. The experimental data were from 98 rainfall-runoff events in this period. In between 86 rainfall-runoff events were used as training set, and the rest were used as test set. The results show that the two networks are all suitable for rainfall-runoff models and better than conceptual and physical based models. LSTM models outperform the ANN models with the values of R 2 and N S E beyond 0.9, respectively. Considering different lead time modelling the LSTM model is also more stable than ANN model holding better simulation performance. The special units of forget gate makes LSTM model better simulation and more intelligent than ANN model. In this study, we want to propose new data-driven methods for flood forecasting.

Runoff Simulation Model for Small Watersheds

1989 ◽  
Vol 32 (3) ◽  
pp. 0881-0886 ◽  
Author(s):  
D. K. Borah
Keyword(s):  
Simulation Model ◽  
Runoff Simulation ◽  
Small Watersheds

scholarly journals Comparison of Hourly and Daily SWAT Results for the Evaluation of Runoff Simulation Performance

2016 ◽  
Vol 58 (5) ◽  
pp. 59-69
Author(s):  
Sun Sook Jang ◽  
Seong Joon Kim
Keyword(s):  
Runoff Simulation ◽  
Simulation Performance

scholarly journals National and regional seasonal dynamics of all-cause and cause-specific mortality in the USA from 1980 to 2016

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Robbie M Parks ◽  
James E Bennett ◽  
Kyle J Foreman ◽  
Ralf Toumi ◽  
Majid Ezzati
Keyword(s):  
Mortality Data ◽  
Age Group ◽  
Limited Information ◽  
Death Rates ◽  
Local Climate ◽  
Climatic Regions ◽  
All Cause Mortality ◽  
The Usa ◽  
Group Sex ◽  
June July

In temperate climates, winter deaths exceed summer ones. However, there is limited information on the timing and the relative magnitudes of maximum and minimum mortality, by local climate, age group, sex and medical cause of death. We used geo-coded mortality data and wavelets to analyse the seasonality of mortality by age group and sex from 1980 to 2016 in the USA and its subnational climatic regions. Death rates in men and women ≥ 45 years peaked in December to February and were lowest in June to August, driven by cardiorespiratory diseases and injuries. In these ages, percent difference in death rates between peak and minimum months did not vary across climate regions, nor changed from 1980 to 2016. Under five years, seasonality of all-cause mortality largely disappeared after the 1990s. In adolescents and young adults, especially in males, death rates peaked in June/July and were lowest in December/January, driven by injury deaths.

scholarly journals Technical note: Long-term persistence loss of urban streams as a metric for catchment classification

2018 ◽  
Vol 22 (6) ◽  
pp. 3551-3559 ◽  
Author(s):  
Dusan Jovanovic ◽  
Tijana Jovanovic ◽  
Alfonso Mejía ◽  
Jon Hathaway ◽  
Edoardo Daly
Keyword(s):  
Negative Relationship ◽  
Technical Note ◽  
Annual Rainfall ◽  
Fluctuation Analysis ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Climatic Regions ◽  
Catchment Size ◽  
The Usa ◽  
The Impact

Abstract. Urbanisation has been associated with a reduction in the long-term correlation within a streamflow series, quantified by the Hurst exponent (H). This presents an opportunity to use the H exponent as an index for the classification of catchments on a scale from natural to urbanised conditions. However, before using the H exponent as a general index, the relationship between this exponent and level of urbanisation needs to be further examined and verified on catchments with different levels of imperviousness and from different climatic regions. In this study, the H exponent is estimated for 38 (deseasonalised) mean daily runoff time series, 22 from the USA and 16 from Australia, using the traditional rescaled-range statistic (R∕S) and the more advanced multifractal detrended fluctuation analysis (MF-DFA). Relationships between H and catchment imperviousness, catchment size, annual rainfall and specific mean discharge were investigated. No clear relationship with catchment area was found, and a weak negative relationship with annual rainfall and specific mean streamflow was found only when the R∕S method was used. Conversely, both methods showed decreasing values of H as catchment imperviousness increased. The H exponent decreased from around 1.0 for catchments in natural conditions to around 0.6 for highly urbanised catchments. Three significantly different ranges of H exponents were identified, allowing catchments to be parsed into groups with imperviousness lower than 5 % (natural), catchments with imperviousness between 5 and 15 % (peri-urban) and catchments with imperviousness larger than 15 % (urban). The H exponent thus represents a useful metric to quantitatively assess the impact of catchment imperviousness on streamflow regime.

scholarly journals Stepwise prediction of runoff using proxy data in a small agricultural catchment

2021 ◽  
Vol 69 (1) ◽  
pp. 65-75
Author(s):  
Borbála Széles ◽  
Juraj Parajka ◽  
Patrick Hogan ◽  
Rasmiaditya Silasari ◽  
Lovrenc Pavlin ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Model Calibration ◽  
Agricultural Land ◽  
Pearson Correlation ◽  
Hydrologic Model ◽  
State Variables ◽  
Runoff Generation ◽  
Runoff Simulation ◽  
Proxy Data ◽  
Simulation Performance

AbstractIn this study, the value of proxy data was explored for calibrating a conceptual hydrologic model for small ungauged basins, i.e. ungauged in terms of runoff. The study site was a 66 ha Austrian experimental catchment dominated by agricultural land use, the Hydrological Open Air Laboratory (HOAL). The three modules of a conceptual, lumped hydrologic model (snow, soil moisture accounting and runoff generation) were calibrated step-by-step using only proxy data, and no runoff observations. Using this stepwise approach, the relative runoff volume errors in the calibration and first and second validation periods were –0.04, 0.19 and 0.17, and the monthly Pearson correlation coefficients were 0.88, 0.71 and 0.64, respectively. By using proxy data, the simulation of state variables improved compared to model calibration in one step using only runoff data. Using snow and soil moisture information for model calibration, the runoff model performance was comparable to the scenario when the model was calibrated using only runoff data. While the runoff simulation performance using only proxy data did not considerably improve compared to a scenario when the model was calibrated on runoff data, the more accurately simulated state variables imply that the process consistency improved.

scholarly journals Technical note: Long-term memory loss of urban streams as a metric for catchment classification

2017 ◽  
Author(s):  
Dusan Jovanovic ◽  
Tijana Jovanovic ◽  
Alfonso Mejía ◽  
Jon Hathaway ◽  
Edoardo Daly
Keyword(s):  
Negative Relationship ◽  
Memory Loss ◽  
Technical Note ◽  
Annual Rainfall ◽  
Long Term Memory ◽  
Fluctuation Analysis ◽  
Climatic Regions ◽  
The Usa ◽  
The Impact

Abstract. Urbanisation has been associated with a reduction in the long-term correlation within a streamflow series, quantified by the Hurst exponent (H). This presents an opportunity to use the H exponent as an index for the classification of catchments on a scale from natural to urbanised conditions. However, before using the H exponent as a general index, the relationship between this exponent and level of urbanisation needs to be further examined and verified on catchments with different levels of imperviousness and from different climatic regions. In this study, the H exponent is estimated for 38 (deseasonalized) mean daily runoff time series, 22 from the USA and 16 from Australia, using the traditional rescaled-range statistic (R/S) and the more advanced multi-fractal detrended fluctuation analysis (MF-DFA). Relationships between H and catchment imperviousness, catchment size, annual rainfall and specific mean discharge were investigated. No clear relationship with catchment area was found, and a weak negative relationship with annual rainfall and specific mean streamflow was found only when the R/S method was used. Conversely, both methods showed decreasing values of H as catchment imperviousness increased. The H exponent decreased from around 1.0 for catchments in natural conditions to around 0.6 for highly urbanised catchments. Three significantly different ranges of H exponents were identified, allowing catchments to be parsed into groups with imperviousness lower than 5 % (natural), catchments with imperviousness between 5 and 15 % (peri-urban), and catchments with imperviousness larger than 15 % (urban). The H exponent thus represents a useful metric to quantitatively assess the impact of catchment imperviousness on streamflow regime.

scholarly journals A Diffusion Wave Based Integrated FEM-GIS Model for Runoff Simulation of Small Watersheds

2009 ◽  
Vol 01 (06) ◽  
pp. 391-399 ◽  
Author(s):  
Reddy K. VENKATA ◽  
T. I. ELDHO ◽  
E. P. RAO
Keyword(s):  
Runoff Simulation ◽  
Diffusion Wave ◽  
Gis Model ◽  
Small Watersheds
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