beach resilience to storm-induced erosion
what contributes to beach profile recovery after significant erosion events.
Currently working on this project. The beach recovery is checked in the 10-day post-storm period. A storm data set of 347 is used.
A lot of content to be updated, more work to be done. Following function was used to check the profile change during a storm event. This is a continuation from the susceptibility quantification approach.
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def prof_change_temp(start,end):
start = pd.to_datetime(start)
end= pd.to_datetime(end)
start,end = (start - timedelta(5)).date(),(end + timedelta(5)).date()
fig, ax = plt.subplots(figsize = (4,2.2), dpi = 300)
x = np.arange(-115.0,386.0,5)
temp = profile.loc[start:end,:'385']
temp_wave = wave.resample('d').max().loc[start:end,'Hs_380']
line, = ax.plot(x, gaussian_filter1d(temp.values[0], sigma=2),
linewidth = 0.4, color = 'k')
time_text = ax.text(-100, -4, '', bbox=dict(facecolor='green', alpha=0.1))
time_text2 = ax.text(-100, -2.5, '', bbox=dict(facecolor='red', alpha=0.1))
def animate(i):
line.set_ydata(gaussian_filter1d(temp.values[i], sigma=2)) # update the data.
time_text.set_text('date = {}'.format(temp.index[i].date()))
time_text2.set_text('max Hs = {:.2f} m'.format(temp_wave[i]))
return line, time_text,
plt.grid(linewidth = 0.2)
plt.axhline(y = 1.25, linewidth = 0.4, color = 'teal', label = 'HWL - 1.252 m')
plt.xlabel('Cross-shore distance')
plt.axvspan(0,150, alpha=0.1, color='r')
plt.ylabel('Elevation (m)')
plt.legend(frameon = True)
ani = animation.FuncAnimation(
fig, animate,frames = len(temp), interval=750, blit=True)
plt.close(ani._fig)
#Call function to display the animation
return HTML(ani.to_html5_video())
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