TY - JOUR

T1 - Simulation of regional irrigation requirement with SWAT in different agro-climatic zones driven by observed climate and two reanalysis datasets

AU - Uniyal, Bhumika

AU - Dietrich, Jörg

AU - Vu, Ngoc Quynh

AU - Jha, Madan K.

AU - Arumí, José Luis

N1 - Funding Information: This paper is a part of research performed by the corresponding author under the PhD funding provided by Indian Council of Agricultural Research. The authors are grateful to Van Tam Nguyen, Prajna Kasargodu Anebagilu and Jannatul Fardous for providing technical support and for proof reading. Authors wanted to thank the Vietnam Academy of Water Resources (Land Use and Climate Change Interactions in Central Vietnam Project) for providing the necessary data. In addition, the authors acknowledge the free provision of data for German and Chilean catchments provided by the respective authorities. We acknowledge funding of the collaboration between the universities of Hannover and Concepcion by BMBF grant 01DN13016.

PY - 2019/2/1

Y1 - 2019/2/1

N2 - Irrigation water is one of the most substantial water uses worldwide. Thus, global simulation studies about water availability and demand typically include irrigation. Nowadays, regional scale is of major interest for water resources management but irrigation lacks attention in many catchment modelling studies. This study evaluated the performance of the agro-hydrological model SWAT (Soil and Water Assessment Tool) for simulating streamflow, evapotranspiration and irrigation in four catchments of different agro-climatic zones at meso-scale (Baitarani/India: Subtropical monsoon; Ilmenau/Germany: Humid; Itata/Chile: Mediterranean; Thubon/Vietnam: Tropical). The models were calibrated well with Kling-Gupta Efficiency (KGE) varying from 0.74–0.89 and percentage bias (PBIAS) from 5.66–6.43%. The simulated irrigation is higher when irrigation is triggered by soil-water deficit compared to plant-water stress. The simulated irrigation scheduling scenarios showed that a significant amount of water can be saved by applying deficit irrigation (25–48%) with a small reduction in annual average crop yield (0–3.3%) in all climatic zones. Many catchments with a high share of irrigated agriculture are located in developing countries with a low availability of input data. For that reason, the application of uncorrected and bias-corrected National Centers for Environmental Prediction (NCEP) and ERA-interim (ERA) reanalysis data was evaluated for all model scenarios. The simulated streamflow under bias-corrected climate variables is close to the observed streamflow with ERA performing better than NCEP. However, the deviation in simulated irrigation between observed and reanalysis climate varies from −25.5–45.3%, whereas the relative irrigation water savings by deficit irrigation could be shown by all climate input data. The overall variability in simulated irrigation requirement depends mainly on the climate input data. Studies about irrigation requirement in data scarce areas must address this in particular when using reanalysis data.

AB - Irrigation water is one of the most substantial water uses worldwide. Thus, global simulation studies about water availability and demand typically include irrigation. Nowadays, regional scale is of major interest for water resources management but irrigation lacks attention in many catchment modelling studies. This study evaluated the performance of the agro-hydrological model SWAT (Soil and Water Assessment Tool) for simulating streamflow, evapotranspiration and irrigation in four catchments of different agro-climatic zones at meso-scale (Baitarani/India: Subtropical monsoon; Ilmenau/Germany: Humid; Itata/Chile: Mediterranean; Thubon/Vietnam: Tropical). The models were calibrated well with Kling-Gupta Efficiency (KGE) varying from 0.74–0.89 and percentage bias (PBIAS) from 5.66–6.43%. The simulated irrigation is higher when irrigation is triggered by soil-water deficit compared to plant-water stress. The simulated irrigation scheduling scenarios showed that a significant amount of water can be saved by applying deficit irrigation (25–48%) with a small reduction in annual average crop yield (0–3.3%) in all climatic zones. Many catchments with a high share of irrigated agriculture are located in developing countries with a low availability of input data. For that reason, the application of uncorrected and bias-corrected National Centers for Environmental Prediction (NCEP) and ERA-interim (ERA) reanalysis data was evaluated for all model scenarios. The simulated streamflow under bias-corrected climate variables is close to the observed streamflow with ERA performing better than NCEP. However, the deviation in simulated irrigation between observed and reanalysis climate varies from −25.5–45.3%, whereas the relative irrigation water savings by deficit irrigation could be shown by all climate input data. The overall variability in simulated irrigation requirement depends mainly on the climate input data. Studies about irrigation requirement in data scarce areas must address this in particular when using reanalysis data.

KW - Agro-climates

KW - Auto-irrigation

KW - Irrigation water requirement

KW - MODIS

KW - Reanalysis data

KW - SWAT

UR - http://www.scopus.com/inward/record.url?scp=85052665318&partnerID=8YFLogxK

U2 - 10.1016/j.scitotenv.2018.08.248

DO - 10.1016/j.scitotenv.2018.08.248

M3 - Article

C2 - 30176493

AN - SCOPUS:85052665318

VL - 649

SP - 846

EP - 865

JO - Science of the Total Environment

JF - Science of the Total Environment

SN - 0048-9697

ER -