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http://krishi.icar.gov.in/jspui/handle/123456789/21154
Title: | Assessment of spatio-temporal variability and probabilistic prediction of annual rainfalls in a river catchment of Udaipur, Rajasthan |
Other Titles: | Not Available |
Authors: | Deepesh Machiwal Singh, P.K. |
ICAR Data Use Licennce: | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf |
Author's Affiliated institute: | ICAR::Central Arid Zone Research Institute |
Published/ Complete Date: | 2012-12-01 |
Project Code: | Not Available |
Keywords: | Annual rainfall Normal probability plot Probability distribution Spatial and temporal variability |
Publisher: | Indian Association of Hydrologists, Roorkee |
Citation: | Not Available |
Series/Report no.: | Not Available; |
Abstract/Description: | Probabilistic forecasting of one-day maximum annual runoff is essential for safe and cost-effective planning and designing of surface runoff storage systems especially in arid and semi-arid regions of developing countries. In the present study, one-day maximum annual runoff is probabilistically forecasted at selected return periods for eight watersheds of Udaipur, Rajasthan, India. Of the eight selected watersheds in the study, seven are interconnected and one is independent. Total annual runoff from these watersheds for a period of 30 years was estimated by using Soil Conservation Service – Curve Number (SCS-CN) model. The estimated runoff is compared with the observed runoff for one independent reservoir (i.e., Bari) for validating the SCS-CN model for runoff estimation. It is found that SCS-CN model estimates runoff values well. Furthermore, seven kinds of regression models were fitted to annual rainfall and annual runoff values for individual watersheds. Based on coefficient of determination as the best-fit criteria, it is found that linear and polynomial regression models can be used for describing the relationship between annual rainfall and annual runoff for the watersheds of Udaipur. However, use of linear regression model is advantageous over the other models. Moreover, one-day and consecutive 2- and 3-day maximum annual runoff for eight individual watersheds were fitted with three selected probability distributions (i.e., log normal, log Pearson type-III, and Gumbel). The chi-squared test for goodness-of-fit was applied for selecting the best-fit distribution for consecutive days’ maximum runoff from individual watersheds. Based on the results of the Chi-square test, it was found that the best-fit distributions for describing the one-day annual maximum runoff from Bari, Chhota Madar, Lakhawali, Fatehsagar and Udaisagar watersheds is log Pearson type-III distribution. Similarly, the best-fit distribution for one-day annual maximum runoff from Pichhola, Bada Madar, and Chikalwas watersheds is Gumbel. Finally, one-day maximum annual runoff at selected return periods (i.e., 1.05, 1.11, 1.25, 2, 5, 10, 15, and 30 years) were forecasted, which are very useful for safe and economic planning and design of soil and water conservation structures in the watersheds of Udaipur. |
Description: | Not Available |
ISSN: | Not Available |
Type(s) of content: | Research Paper |
Sponsors: | Not Available |
Language: | English |
Name of Journal: | Hydrology Journal |
NAAS Rating: | 8.01 |
Volume No.: | 35(3&4) |
Page Number: | 111-123 |
Name of the Division/Regional Station: | Regional Research Station, Kukma, Bhuj, Gujarat |
Source, DOI or any other URL: | 10.5958/j.0975-6914.35.3X.011 |
URI: | http://krishi.icar.gov.in/jspui/handle/123456789/21154 |
Appears in Collections: | NRM-CAZRI-Publication |
Files in This Item:
File | Description | Size | Format | |
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Machiwal and Singh Krishi_Portal.pdf | 3.04 MB | Adobe PDF | View/Open |
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