Water 2018, 10(2), 212; https://doi.org/10.3390/w10020212
Calibration of Spatially Distributed Hydrological Processes and Model Parameters in SWAT Using Remote Sensing Data and an Auto-Calibration Procedure: A Case Study in a Vietnamese River Basin
Lan Thanh Ha 1,2,*
, Wim G. M. Bastiaanssen 1,3, Ann Van Griensven 4,5, Albert I. J. M. Van Dijk 6 and Gabriel B. Senay 7
, Wim G. M. Bastiaanssen 1,3, Ann Van Griensven 4,5, Albert I. J. M. Van Dijk 6 and Gabriel B. Senay 7
1
Faculty of Civil Engineering and Geosciences, Delft University of Technology, 2628 CN Delft, The Netherlands
2
Department of Training and International Cooperation, Institute of Water Resources Planning, Hanoi 100000, Vietnam
3
Integrated Water Systems and Governance Department, IHE Delft Institute for Water Education, 2611 AX Delft, The Netherlands
4
Water Science & Engineering Department, IHE Delft Institute for Water Education, 2611 AX Delft, The Netherlands
5
Hydrology and Hydraulic Engineering Department, Free University of Brussels (VUB), 1050 Brussel, Belgium
6
Fenner School of Environment & Society, Australian National University, Canberra, ACT 2601, Australia
7
U.S. Geological Survey Earth Resources Observation Science Center, North Central Climate Science Center, Fort Collins, Colorado, CO 80526, USA
*
Author to whom correspondence should be addressed.
Received: 14 December 2017 / Revised: 2 February 2018 / Accepted: 13 February 2018 / Published: 16 February 2018
Abstract
In this paper, evapotranspiration (ET) and leaf area index (LAI) were used to calibrate the SWAT model, whereas remotely sensed precipitation and other climatic parameters were used as forcing data for the 6300 km2 Day Basin, a tributary of the Red River in Vietnam. The efficacy of the Sequential Uncertainty Fitting (SUFI-2) parameter sensitivity and optimization model was tested with area specific remote sensing input parameters for every Hydrological Response Units (HRU), rather than with measurements of river flow representing a large set of HRUs, i.e., a bulk calibration. Simulated monthly ET correlations with remote sensing estimates showed an R2 = 0.71, Nash–Sutcliffe Efficiency NSE = 0.65, and Kling Gupta Efficiency KGE = 0.80 while monthly LAI showed correlations of R2 = 0.59, NSE = 0.57 and KGE = 0.83 over a five-year validation period. Accumulated modelled ET over the 5-year calibration period amounted to 5713 mm compared to 6015 mm of remotely sensed ET, yielding a difference of 302 mm (5.3%). The monthly flow at two flow measurement stations were adequately estimated (R2 = 0.78 and 0.55, NSE = 0.71 and 0.63, KGE = 0.59 and 0.75 for Phu Ly and Ninh Binh, respectively). This outcome demonstrates the capability of SWAT model to obtain spatial and accurate simulation of eco-hydrological processes, also when rivers are ungauged and the water withdrawal system is complex. View Full-Text
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Ha, L.T.; Bastiaanssen, W.G.M.; Van Griensven, A.; Van Dijk, A.I.J.M.; Senay, G.B. Calibration of Spatially Distributed Hydrological Processes and Model Parameters in SWAT Using Remote Sensing Data and an Auto-Calibration Procedure: A Case Study in a Vietnamese River Basin. Water 2018, 10, 212.
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