English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

To design and construct mosthydraulic structures, e.g. dams, it is essential to determine watershed runoff. If a watershed lacks any gaging station, thenhydrologic models can be utilized to estimate runoff. The Soil Water Assessment Tool (SWAT) is one of the most widelyusedcomputerwatershed models. In this model, we need to input meteorological data, such as precipitation, temperature, wind speed, solar radiation, and relative humidity;as well as watershed data, including curvenumberandroughness coefficient, to calculate the watershed runoff. Some watershedshave weather stations, but there is a risk that the recordeddataof a station do not represent the whole watershed and the use of such data may cause error. Consequently, the error of estimated runoff error needs to be determined. This study deals with the sensitivity of runoff estimatedusing the SWAT model to the variations in meteorological parameters, such as precipitation, solar radiation, wind, humidity, and temperature. Results indicate that with a 30% decrease in the average monthly precipitation, sunshine, relative humidity, wind and temperature, we witness,respectively,a 64.27% decrease, 114.67% increase, 45.93% decrease, 126.12% increase, and 39.21% increase in the estimated runoff.. Runoff estimation is found to be most sensitive to wind speed and solar radiation,and least sensitive to temperature.

Sensitivity Analysis of Runoff Model by SWAT to Meteorological Parameters: A Case Study of Kasillian Watershed, Mazandaran, Iran