dc.description.abstract |
Advances in hydrology are dependent on good, reliable and continuous
measurements of the hydrological variables. Hydrologic data collected from various
sources/instruments are generally raw data and cannot be used directly in most
hydrologic analysis work. Thus, the processing of such raw data is the first and major
task which has to be undertaken before drawing any hydrological inferences. Processing
of hydrological data has two major objectives: one to evaluate the data for its accuracy
and the other to prepare the data in a form most valuable to the users. Data processing
using high-speed computers has immense potential for handling large volume of
hydrologic data in a quick and economic way.
Hydrological and meteorological data are observed manually or digitally using a
variety of instruments. HYMOS is a software, which is used for storage, processing and
retrieval of hydro-meteorological data. This surface water data processing system has
been introduced in various agencies in nine southern states of India under the Hydrology
Project. A surface water data entry system (SWDES) has also been developed under the
Hydrology Project and introduced under the project. SWDES is primarily used for data
entry and primary validation.
In the study reported herein, the capabilities of SWDES and HYMOS software
have been utilized for the processing and analysis of rainfall and discharge data in the
Satluj basin. The catchment of river Satluj between Namagia to Bhakra gauging sites is
considered for this study. The rainfall data have been validated using various techniques
of secondary validation, such as multiple time series plots, spatial homogeneity test, and
double mass analysis. Because of higher altitude difference between the stations, the data
have been normalized before processing. Using the spatial correlation analysis, groups of
stations with significant correlation have been identified. For runoff data between
Rampur and Bhakra, the contribution from the intermediate catchment has been
compared with the average rainfall. Time series analysis of the runoff data at Rampur and
Bhakra has been carried out through a time series model. Few suspect values in the
historical record (1977 – 1998) have been identified. Major deviations between observed
and expected values were matched with the original record. Some of the suspected values
were found to be wrongly entered in the database, which confirms the strength and
necessity of data processing. |
en_US |