mike-rain

MIKE+ Rain

MIKE+ rainfall boundaries read a .dfs0 of Rainfall Intensity, mm/h, mean-step-backward: exactly the shape of DHI's own example rain files (Sirius_IDF_1year_rainfall.dfs0). This skill produces that file from a CSV.

Tool

• mike_rain_to_dfs0 — {csv, out_dfs0, time_col?, value_col?, unit?, item_name?}
  • unit: 'mm/h' (intensity, default) or 'mm' (depth per step, converted with each step's own duration; the conversion is reported).
  • Returns {dfs0, item, n_steps, start, end, timestep_s, uniform_step, total_depth_mm, peak_intensity_mm_h, peak_time, conversion} after reading the file back.

Conventions

• Time column first, value column second by default; name them if the CSV differs.
• Rejects negative values, non-numeric cells, unsorted duplicates, fewer than two steps: fix the CSV, do not silently clean it.
• Report total_depth_mm and peak_intensity_mm_h; if uniform_step is false say so (MIKE 1D accepts irregular steps, but the user should know).
• The tool never touches the model. To make a MIKE 1D model use the new rain, edit its rainfall boundary with mike-params on a COPY. The boundary lives in table msm_BBoundary (the rainfall row has TypeNo = 1; in Sirius_RTC its MUID is Rainfall) with columns
  • TSConnection = dfs0 path relative to the model folder (DHI's example: Sirius_IDF_1year_rainfall.dfs0), so write the new file into the model copy folder,
  • TimeseriesName = the dfs0 item name (must match: pass item_name to mike_rain_to_dfs0, or set this column to Rainfall),
  • DataTypeName = Rainfall Intensity. mike_get_values {table: msm_BBoundary, columns: [TypeNo, TSConnection, TimeseriesName, DataTypeName]} first, then mike_set_values on that MUID, then run and check mike_results_summary.
• The same .dfs0 is what mike_plot_rain_flow / mike_plot_compare take as rain_dfs0, so use it for the figure of the run it drove.

Orchestration

mike_rain_to_dfs0 {csv, out_dfs0: runs/<case>/00_model/storm.dfs0, item_name: <existing TimeseriesName or 'Rainfall'>}
mike_get_values  {sqlite: <copy>, table: msm_BBoundary, columns: [TypeNo, TSConnection, TimeseriesName]}
mike_set_values  {sqlite: <copy>, table: msm_BBoundary, muids: [<rain row>], values: {TSConnection: storm.dfs0, TimeseriesName: ...}}
mike_run -> mike_results_summary (skip_hours) -> mike_plot_rain_flow {rain_dfs0: storm.dfs0}
mike_manifest_write {inputs: [csv, storm.dfs0], ...}