A
A. van Griensven
Researcher at UNESCO-IHE Institute for Water Education
Publications - 59
Citations - 5909
A. van Griensven is an academic researcher from UNESCO-IHE Institute for Water Education. The author has contributed to research in topics: Environmental science & Soil and Water Assessment Tool. The author has an hindex of 25, co-authored 44 publications receiving 4946 citations. Previous affiliations of A. van Griensven include Vrije Universiteit Brussel & University of California, Riverside.
Papers
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Journal ArticleDOI
SWAT: Model Use, Calibration, and Validation
Jeffrey G. Arnold,Daniel N. Moriasi,Philip W. Gassman,Karim C. Abbaspour,Michael J. White,Raghavan Srinivasan,C. Santhi,R. D. Harmel,A. van Griensven,M. W. Van Liew,Narayanan Kannan,Manoj Jha +11 more
TL;DR: The SWAT-CUP tool as discussed by the authors is a semi-distributed river basin model that requires a large number of input parameters, which complicates model parameterization and calibration, and is used to provide statistics for goodness-of-fit.
Journal ArticleDOI
A global sensitivity analysis tool for the parameters of multi-variable catchment models
A. van Griensven,Thomas Meixner,Sabine Grunwald,Thomas F. A. Bishop,M. Diluzio,Raghavan Srinivasan +5 more
TL;DR: In this article, a sampling strategy that is a combination of latin-hypercube and one-factor-at-a-time sampling that allows a global sensitivity analysis for a long list of parameters with only a limited number of model runs is described.
Journal ArticleDOI
Sediment management modelling in the Blue Nile Basin using SWAT model
G.D. Betrie,G.D. Betrie,Yasir A. Mohamed,Yasir A. Mohamed,A. van Griensven,Raghavan Srinivasan +5 more
TL;DR: In this paper, the authors presented daily sediment yield simulations in the Upper Blue Nile under different Best Management Practice (BMP) scenarios, such as maintaining existing conditions, introducing filter strips, applying stone bunds (parallel terraces), and reforestation.
Journal ArticleDOI
Methods to quantify and identify the sources of uncertainty for river basin water quality models
A. van Griensven,Thomas Meixner +1 more
TL;DR: The total model uncertainties are assessed by four components: the sum of the squares of the residuals (SSQ), parameter uncertainties, input data uncertainties, and an additional predictive uncertainty that is expressed when the model appears to be biased when it is applied for data other than the data used for calibration.
Journal ArticleDOI
Sensitivity analysis for hydrology and pesticide supply towards the river in SWAT
TL;DR: In this article, the authors used the Latin Hypercube (LH) samples as initial points for an OAT design and performed a sensitivity analysis on the Nil catchment in Belgium.