AQUACROP irrigation synthetic dataset

This example demonstrates how to load and visualize datasets related to evapotranspiration (ETa) and land cover classification (CLC) for a synthetic dataset generated using AQUACROP. The datasets are loaded using Pooch for remote file management. Two visualizations are created: one showing land cover classification (CLC) and another displaying the time series of evapotranspiration (ETa).

import pooch
import xarray as xr 
import matplotlib.pyplot as plt 
from matplotlib.animation import FuncAnimation
from IPython.display import HTML

Step 1: Download datasets using Pooch Pooch is used to manage the dataset downloads from the specified GitHub repository.

pooch_Majadas = pooch.create(
    path=pooch.os_cache("AQUACROP_project"),
    base_url="https://github.com/BenjMy/test_AQUACROP_centum_dataset/raw/refs/heads/main/",
    registry={
        "ds_analysis_EO_0.netcdf": None,
    },
)

AQUACROP_ET_filename = pooch_Majadas.fetch('ds_analysis_EO_0.netcdf')
AQUACROP_ds = xr.load_dataset(AQUACROP_ET_filename)

# AQUACROP_ds = xr.open_dataset(f'../data/synthetic/ds_analysis_EO_0.netcdf')

import numpy as np
_, index = np.unique(AQUACROP_ds['time'], return_index=True)
AQUACROP_ds = AQUACROP_ds.isel(time=index)
AQUACROP_ds['ACT. ETRA'].plot.imshow(x="x", y="y", 
                                        col="time", 
                                        col_wrap=4,
                                        )

Downloading file 'ds_analysis_EO_0.netcdf' from 'https://github.com/BenjMy/test_AQUACROP_centum_dataset/raw/refs/heads/main/ds_analysis_EO_0.netcdf' to '/home/runner/.cache/AQUACROP_project'.

/tmp/ipykernel_2194/1458405863.py:10: FutureWarning: In a future version, xarray will not decode timedelta values based on the presence of a timedelta-like units attribute by default. Instead it will rely on the presence of a timedelta64 dtype attribute, which is now xarray's default way of encoding timedelta64 values. To continue decoding timedeltas based on the presence of a timedelta-like units attribute, users will need to explicitly opt-in by passing True or CFTimedeltaCoder(decode_via_units=True) to decode_timedelta. To silence this warning, set decode_timedelta to True, False, or a 'CFTimedeltaCoder' instance.
  AQUACROP_ds = xr.load_dataset(AQUACROP_ET_filename)

<xarray.plot.facetgrid.FacetGrid at 0x7fd7d1b5efe0>