Interpretation of Precipitation Data

Precipitation data must be checked for the continuity and consistency before they are analysed for any significant purpose. This is essential when it is suspected that the gauge site (or its surroundings) might have changed appreciably during the period for which the average is being computed.

Estimation of Missing Data

The continuity of a record of precipitation data may have been broken with missing data due to several reasons such as damage (or fault) in a rain gauge during a certain period. The missing data is estimated using the rainfall data of the neighbouring rain gauge stations. The missing annual precipitation Px at a station x is related to the annual precipitation values, P1, P2, P3 ...... Pm and normal annual precipitation, N1, N2, N3 ...... Nm at the neighbouring M stations 1, 2, 3, … M respectively. The normal precipitation (for a particular duration) is the mean value of rainfall on a particular day or in a month or year over a specified 30-year period.

The 30-year normals are computed every decade. The term normal annual precipitation at any station is, therefore, the mean of annual precipitations at that station based on 30-year record.

The missing annual precipitation Px is simply given as

If the normal annual precipitations at various stations are within about 10% of the normal annual precipitation at station x i.e., Nx. Otherwise, one uses the normal ratio method which gives

This method works well when the precipitation regimes of the neighbouring stations and the station x are similar (or almost the same).

Multiple linear regression (amongst precipitation data of M stations and the station x, excluding the unknown missing data of station x and the concurrent (or corresponding) data of the neighbouring M stations) will yield an equation of the form

The regression method allows for some weighting of the stations and adjusts, to some extent, for departures from the assumption of the normal ratio method.

Test for Consistency of Precipitation Data

Changes in relevant conditions of a rain gauge (such as gauge location, exposure, instrumentation or observation techniques and surroundings) may cause a relative change in the precipitation catchment of the rain gauge. The consistency of the precipitation data of such rain gauges needs to be examined. Double-mass analysis, also termed double-mass curve technique, compares the accumulated annual or seasonal precipitation at a given station with the concurrent accumulated values of mean precipitation for a group of the surrounding stations (i.e., base stations). Since the past response is to be related to the present conditions, the data (accumulated precipitation of the station x, i.e., ΣPx and the accumulated values of the average of the group of the base stations, i.e., ΣPav) are usually assembled in reverse chronological order. Values of ΣPx are plotted against ΣPav for the concurrent time periods and is given in Fig. 1. A definite break in the slope of the resulting plot points to the inconsistency of the data indicating a change in the precipitation regime of the station x. The precipitation values at station x at and beyond the period of change is corrected using the relation,

Where,

     Pcx = corrected value of precipitation at station x at any time t

     Px = original recorded value of precipitation at station x at time t.

     Sc = corrected slope of the double-mass curve

     Sa = original slope of the curve

Fig. 1 Double-Mass Curve

Thus, the older records of station x have been corrected so as to be consistent with the new precipitation regime of the station x.

Presentation of Precipitation Data

Precipitation (or rainfall) data are presented as either a mass curve of rainfall (accumulated precipitation v/s time plotted in chronological order, Fig. 2) or a hyetograph (rainfall intensity v/s time). Mass curves of rainfall provide the information on the duration and magnitude of a storm. Intensities of rainfall at a given time can be estimated by measuring the slope of the curve at the specified time. The hyetograph derived from the mass curve is usually represented as a chart. The area of a hyetograph represents the total precipitation received during the period.

Depth – Area - Duration (DAD) Analysis

Depth-area-duration (DAD) curves are plots of accumulated average precipitation versus area for different durations of a storm period. Depth-area-duration analysis of a storm is performed to estimate the maximum amounts of precipitation for different durations and over different areas. A storm of certain duration over a specified basin area seldom results in uniform rainfall depth over the entire specified area. The difference between the maximum rainfall depth over an area P0 and its average rainfall depth (P-bar) for a given storm, i.e., (P0 – P-bar) increases with increase in the basin area and decreases with increase in the storm duration. The depth-area-duration curve is obtained as given in the following example figure.

Fig. 2 Example Figure for DAD Curves