Please use this identifier to cite or link to this item: http://117.252.14.250:8080/jspui/handle/123456789/5220
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dc.contributor.authorGoel, M. K.-
dc.contributor.authorAgarwal, P. K.-
dc.contributor.authorJain, Sharad K.-
dc.date.accessioned2020-11-02T14:25:55Z-
dc.date.available2020-11-02T14:25:55Z-
dc.date.issued2002-
dc.identifier.urihttp://117.252.14.250:8080/jspui/handle/123456789/5220-
dc.description.abstractAdvances 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
dc.language.isoenen_US
dc.publisherNational Institute of Hydrologyen_US
dc.subjectSWDESen_US
dc.subjectHYMOSen_US
dc.subjectTime series analysisen_US
dc.subjectTime series modelen_US
dc.subjectBhakra-Runoff dataen_US
dc.subjectRampur-Runoff dataen_US
dc.titleProcessing of Hydrological Data of Bhakra System Using HYMOSen_US
dc.typeTechnical Reporten_US
Appears in Collections:Special Reports

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