Impact of Direct Soil Moisture and Revised Soil Moisture Index Methods on Hydrologic Predictions in an Arid Climate

Milad Jajarmizadeh,Shamsuddin Shahid,Shatirah Akib,Sobri Bin Harun,Mohsen Salarpour

doi:10.1155/2014/156172

Milad Jajarmizadeh, Shamsuddin Shahid + Show 3 more

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https://doi.org/10.1155/2014/156172

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Abstract

The soil and water assessment tool (SWAT) is a physically based model that is used extensively to simulate hydrologic processes in a wide range of climates around the world. SWAT uses spatial hydrometeorological data to simulate runoff through the computation of a retention curve number. The objective of the present study was to compare the performance of two approaches used for the calculation of curve numbers in SWAT, that is, the Revised Soil Moisture Index (SMI), which is based on previous meteorological conditions, and the Soil Moisture Condition II (SMCII), which is based on soil features for the prediction of flow. The results showed that the sensitive parameters for the SMI method are land-use and land-cover features. However, for the SMCII method, the soil and the channel are the sensitive parameters. The performances of the SMI and SMCII methods were analyzed using various indices. We concluded that the fair performance of the SMI method in an arid region may be due to the inherent characteristics of the method since it relies mostly on previous meteorological conditions and does not account for the soil features of the catchment.

Highlights

The soil and water assessment tool (SWAT) is a semiphysical and semiempirical modeling tool developed by the United States Department of Agriculture (USDA) [1]
The first was the Soil Moisture index (SMI), which is based on previous meteorological conditions, and the second was the Soil Moisture Condition II (SMCII), which is based on soil features
The SMCII method is highly sensitive to soil features

Summary

Introduction

SWAT can be developed for rainfall-runoff simulation with different short-term and long-term objectives, for example, prediction of stream flow and sedimentation, identification of best management practices (BMP), and planning water resources of large and complex watersheds [2,3,4]. SWAT uses the soil conservation services’ curve number (SCS-CN) to estimate the volume of stream flow. The SCS-CN method is used extensively for consecutive flow simulation for long-term runoff analysis [8]. It can be used for optimal estimation of surface runoff in ungauged watersheds [9]. SWAT is one such hydrological modeling tool that uses the SCSCN method to predict water flows in large and ungauged watersheds

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Conclusion