Curve Number Method Runoff Estimation in the Kardeh Watershed, Iran

Ebrahimian, Mahboubeh (2009) Curve Number Method Runoff Estimation in the Kardeh Watershed, Iran. Masters thesis, Universiti Putra Malaysia.

[img] PDF
572Kb

Abstract

The major problem in the assessment of the relationship between rainfall and runoff occurs when a study is carried out in ungauged watersheds, in particular, the absence of hydro-climatic data. This study aims to determine the runoff depth using NRCS-CN method with GIS and the effect of slope on runoff generation in the Kardeh watershed, located between 59º 26´ 3˝ to 59º 37´ 17˝ E longitude and 36º 37´ 17˝ to 36º 58´ 25˝ N latitude, about 42 km north of Mashhad, Khorasan Razavi province, Iran. The US Department of Agriculture, Natural Resources Conservation Service Curve Number (USDA-NRCS-CN) method was applied for estimating the runoff depth in the semi-arid Kardeh watershed. Hydrologic soil group, land use and slope maps were generated in GIS environment. The curve number values from NRCS standard tables were assigned to the intersected hydrologic soil groups and land use maps to generate CN values map. The curve number method was followed to estimate runoff depth for selected storm events in the watershed. Effect of slope on CN values and runoff depth was determined. Estimated runoff depth and slope-adjusted runoff depth were statistically compared with the corresponding observed runoff data. Pair wise comparisons by the t-test, Pearson correlation analysis and percent error were used to investigate the accuracy of estimated data and relationship between estimated and observed runoff depth. The results showed that there was no significant difference between the means of observed and estimated runoff depths (P > 0.05). Fairly positive correlations were detected between observed with estimated runoff and slope-adjusted runoff depth (r = 0.55; P < 0.01) and (r = 0.56; P < 0.01), respectively. About 9 % and 6 % of the estimated and slope-adjusted runoff values were within ±10% of the recorded values, respectively. In addition, about 43 and 37 percent of the estimated and slope-adjusted values were in error by more than ±50 %, respectively. Statistical analysis indicated that percent error of estimated slope-adjusted runoff depth was significantly (p < 0.01) lower than the percent error of estimated runoff depth. This decline in percent error can be explained by the role of slope in runoff generation in steep slope watershed. The results of study indicated that the CN is an effective method for homogenous watersheds in terms of land use, soil, and climate rather than heterogeneous ones like Kardeh watershed. In such watersheds it can be employed with about 60 percent accuracy only for management and conservation purposes however and probably not for computation of design floods. Keywords: Curve Number, Geographic Information System, Kardeh watershed, Slope-adjusted runoff depth

Item Type:Thesis (Masters)
Subject:Watersheds - Runoff - Iran - Case studies
Chairman Supervisor:Associate Professor Lai Food See, PhD
Call Number:FH 2009 6
Faculty or Institute:Faculty of Forestry
ID Code:7141
Deposited By: Nur Izzati Mohd Zaki
Deposited On:10 Jun 2010 02:10
Last Modified:27 May 2013 07:33

Repository Staff Only: Edit item detail

Document Download Statistics

This item has been downloaded for since 10 Jun 2010 02:10.

View statistics for "Curve Number Method Runoff Estimation in the Kardeh Watershed, Iran"


Universiti Putra Malaysia Institutional Repository

Universiti Putra Malaysia Institutional Repository is an on-line digital archive that serves as a central collection and storage of scientific information and research at the Universiti Putra Malaysia.

Currently, the collections deposited in the IR consists of Master and PhD theses, Master and PhD Project Report, Journal Articles, Journal Bulletins, Conference Papers, UPM News, Newspaper Cuttings, Patents and Inaugural Lectures.

As the policy of the university does not permit users to view thesis in full text, access is only given to the first 24 pages only.