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Cambridge University Press, Journal of Agricultural Science, 3(153), p. 481-496, 2014

DOI: 10.1017/s0021859614000422

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Soil water content, runoff and soil loss prediction in a small ungauged agricultural basin in the Mediterranean region using the Soil and Water Assessment Tool

Journal article published in 2014 by M. C. Ramos, J. A. Martínez-Casasnovas ORCID
This paper is available in a repository.
This paper is available in a repository.

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Abstract

SUMMARYThe aim of the present work was to evaluate the possibilities of using sub-basin data for calibration of the Soil and Water Assessment Tool (SWAT) model in a small (46 ha) ungauged basin (i.e. where the water flow is not systematically measured) and its response. This small basin was located in the viticultural Anoia-Penedès region (North-east Spain), which suffers severe soil erosion. The data sources were: daily weather data from an observatory located close to the basin; a detailed soil map of Catalonia; a 5-m resolution digital elevation model (DEM); a crop/land use map derived from orthophotos taken in 2010 and an additional detailed soil survey (40 points) within the basin, which included properties such as texture, soil organic carbon, electrical conductivity, bulk density and water retention capacity at −33 and −1500 kPa. A sensitivity analysis was performed to identify and rank the sensitive parameters that affect the hydrological response and sediment yield to changes of model input parameters. A 1-year calibration and 1-year validation were carried out on the basis of soil moisture measured at 0·20-m intervals from depths of 0·10 to 0·90 m in two selected sub-basins, and data related to estimations of runoff and sediment concentrations in runoff collected in the same sub-basins. The present paper shows a methodological approach for calibrating SWAT in small ungauged basins using soil water content measurements and runoff samples collected within the basin. The SWAT satisfactorily predicted the average soil water content, runoff and soil loss for moderate intensity events recorded during the study periods. However, it was not satisfactory for high-intensity events which would require exploring the possibilities of using sub-daily information as an input model parameter.