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Analysis of Rainfall Data

Before using rainfall records at a station for any analysis, the data has to be checked for

  • Continuity
  • Consistency

Missing rainfall data can be estimated using the rainfall data at neighbouring stations.

Estimation of Missing Rainfall Data

Required to find the missing annual precipitation clip_image001 at station X (not included in the m neighbouring stations), given the annual precipitation values at m neighbouring raingauge stations clip_image002. Let the normal annual precipitation at the m+1 stations be clip_image003

If the normal precipitations at the different stations are within 10% of the normal annual precipitation at station X, then


If the normal precipitation at any of the m stations vary by more than 10% from the normal annual precipitation at station X, then is estimated by the normal ratio method as


Test for Consistency of Record

Inconsistency would arise in the rainfall data at a raingauge station if conditions relevant to recording of rainfall at the station undergoes significant change during the period of record. It would be felt from the time a significant change took place.

Some common causes for inconsistency of record

  • Shifting of the raingauge to a new location
  • Neighbourhood of the station is undergoing significant changes
  • Change in the ecosystem due to natural calamities such as forest fires, landslides etc
  • Errors in observation from a certain date

Check for inconsistency of record is done by the double mass curve technique (based on the principle that when each recorded data comes to same parent population, they will be consistent.

  • Let X be the station where inconsistency in rainfall records is observed.
  • Select a group of about 5 to 10 base stations in the neighbourhood of station X.
  • Data of annual or monthly mean rainfall of station X as well as the average rainfall of the group of base stations over a long time period is arranged in reverse chronological order ie. the latest record is the first entry and the oldest record is the last entry in the list.
  • Accumulated precipitation at station X clip_image006 and the accumulated values of the average precipitation of the group of base stationsclip_image007 are computed from the latest records.
  • A plot of clip_image006[1] vs clip_image007[1] for various consecutive time periods is prepared.
  • A break in the slope of this plot indicates a change in the precipitation regime of station X.
  • Precipitation values at X beyond the period of change of regime is corrected as



Double mass curve

Figure: Double mass curve

Thus older records are brought to the new regime at X.

  • The more homogeneous the base station records are, the more accurate will be the corrected values at station X.
  • A change in slope is taken as significant only if it persists for more than 5 years.
  • The double mass curve technique is also useful in checking arithmetical errors in transferring rainfall data from one record to another.

Presentation of Rainfall Data

Mass Curve of Rainfall

  • It is a plot of accumulated precipitation against time, plotted in chronological order.
  • Records of float type, weighing bucket type etc raingauges are of this form.
  • It gives information on duration and magnitude of a storm.Intensity at various time intervals in a storm = slope of the curve.
  • It can be prepared for non-recording raingauges also if the approximate start and end of a storm are known.

Mass curve of rainfall

Figure: Mass curve of rainfall


  • It is a plot of rainfall intensity against time interval.
  • Time interval depends on the purpose (urban drainage problems – small durations, flood flow computations from large catchments~ 6h).
  • It can be derived from the mass curve of rainfall.
  • It is represented as a bar chart.
  • It is useful in developing design storms to predict extreme floods.
  • Area under a hyetograph = total precipitation received in that time period.

Hyetograph of a storm

Figure: Hyetograph of a storm