Related Issues (20)
- Visualize relative humidity over time, and look for any trends or patterns.
- Make correlation matrix to assess the relationship between the different variables in the dataset.
- Analyze the discharge data to determine the average monthly discharge rate
- Identify areas with high and low precipitation
- Identify where water is likely to accumulate during high flow periods, , including variations in elevation and land cover type
- Total precipitation and runoff volume for the Budhi Gandaki and Langtang catchment over a period of time (e.g. 10 years)
- Identify seasonal and annual average precipitation and runoff volume for the Budhi Gandaki and Langtang catchment.
- Visualize runoff over time, and look for any trends or patterns
- Comparison of the hydrological characteristics of the Budhi Gandaki and Langtang catchment with other catchments in the region
- Visualize daily mean temperature, annual mean precipitation and elevation
- Station altitude (temperature and precipitation) plotted against the hypsographic curve
- Compare calibrated WFDE5 simulation with observed discharge
- Compare calibrated ERA5+TopoScale simulation with observed discharge
- Compare calibrated WFDE5+HI-AWARE simulation with observed discharge
- Identify outliers, nans in datasets if any
- Water balance estimation of outputs
- QQ-plots of simulated versus observed discharge
- Compare simulated snow cover with observed (MODIS)
- Visualize 1 year for observed, calibration and validation for the different forcing
- Annual average water balance components (actual evapotranspiration, precipitation calculated by using p_corr_factor) for different forcing datasets
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