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Nibedita Bisoyi Harish Gupta Narayan Prasad Padhy Govind Joseph Chakrapani 《国际泥沙研究》2019,34(2):125-135
Most of the studies on Artificial Neural Network (ANN) models remain restricted to smaller rivers and catchments. In this paper, an attempt has been made to correlate variability of sediment loads with rainfall and runoff through the application of the Back Propagation Neural Network (BPNN) algorithm for a large tropical river. The algorithm and simulation are done through MATLAB environment. The methodology comprised of a collection of data on rainfall, water discharge, and sediment discharge for the Narmada River at various locations (along with time variables) and application to develop a threelayer BPNN model for the prediction of sediment discharges. For training and validation purposes a set of 549 data points for the monsoon (16 June-15 November) period of three consecutive years (1996–1998) was used. For testing purposes, the BPNN model was further trained using a set of 732 data points of monsoon season of four years (2006–07 to 2009–10) at nine stations. The model was tested by predicting daily sediment load for the monsoon season of the year 2010–11. To evaluate the performance of the BPNN model, errors were calculated by comparing the actual and predicted loads. The validation and testing results obtained at all these locations are tabulated and discussed. Results obtained from the model application are robust and encouraging not only for the sub-basins but also for the entire basin. These results suggest that the proposed model is capable of predicting the daily sediment load even at downstream locations, which show nonlinearity in the transportation process. Overall, the proposed model with further training might be useful in the prediction of sediment discharges for large river basins. 相似文献
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Simanchal Padhy 《Physics of the Earth and Planetary Interiors》2005,148(1):1-12
The attenuation characteristics of Indian lithosphere and its comparison with different tectonic settings in the world are determined from the observations of the Q for Lg(QLg)-, and S(QS)-waves in the 1-30 Hz frequency range. The scattering is approximated with a Gaussian distribution of spherical scatterers. To approximate single scattering, we use Dainty's [Geophy. Res. Lett. 8 (11) (1981) 1126] model that attenuation is given by 1/Q(ω) = 1/Qi + g(ω)v/ω, where Qi is intrinsic Q due to anelastic attenuation, v is shear wave velocity, ω is angular frequency, g = ∫n(a)σ da is the total scattering coefficient for S-to-S scattering, n(a) da is the number of scattering spheres of radius a per unit volume, and σ is the scattering cross-section for the sphere. We find that if n(a) is described by a simple two parameter (a0 and c) Gaussian of amplitude c and standard deviation and mean a0, the attenuation data for different regions of the world are well approximated over the frequency band of seismic observations. Our major findings are: (1) the maximum effect of scattering on attenuation occurs at 0.84 Hz or a wavelength of 4.16 km; (2) the values of g are frequency dependent. Values of g are of the order of 10−3 km−1 at 1-30 Hz, varying from 0.0031 to 0.01 and 0.001 to 0.0083 km−1 for tectonically active and stable regions, respectively; (3) regions of active tectonics and seismicity generally have lower Qi values (1000) than that in stable regions (2000); and (4) regions of high Qi value exhibit low intensity of scattering. 相似文献
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Cyclone-generated surface waves are simulated using state-of-art SWAN (Simulating WAves Nearshore) model coupled with hydrodynamic
model inputs. A severe cyclonic storm passed over the Arabian Sea during 4–9th November 1982 is selected from UNISYS track
records. The cyclone lasted for nearly 6 days and subsided with a land fall at Gujarat coast, west coast of India. In this
study, cyclonic wind fields are generated using a well-established relationship suggested by Jelesnianski and Taylor (1973). The associated water level variations due to storm surge and surge generated currents are simulated using POM (Princeton
Ocean Model). The outputs are one-way coupled with the wave model SWAN for simulating wave parameters off Gujarat, north-east
basin of Arabian Sea. An extensive literature review is carried out on the progress and methodology adopted for storm wave
modelling and analysis. The results presented in this paper reveal the severity of the storm event and would be highly useful
for assessing the extreme wave event/climate especially for the south coast of Gujarat. 相似文献