ET-CEM-MWM

Expertises

  • Earth and Planetary Sciences

    • Model
    • River
    • Investigation
    • Catchment
    • Low Flow
    • Structural Basin
    • Streamflow
    • Climate Change

Organisaties

Publicaties

2024
Increasing the water level accuracy in hydraulic river simulation by adapting mesh level elevation, Article 106135, 106135 (E-pub ahead of print/First online). Khorsandi kuhanestani, P., Bomers, A., Booij, M. J., Warmink, J. J. & Hulscher, S. J. M. H.https://doi.org/10.1016/j.envsoft.2024.106135Real time probabilistic inundation forecasts using a LSTM neural network, Article 131082. Hop, F. j., Linneman, R., Schnitzler, B., Bomers, A. & Booij, M. j.https://doi.org/10.1016/j.jhydrol.2024.131082Satellite rainfall bias correction incorporating effects on simulated crop water requirements, 2269-2288. Omondi, C. k., Rientjes, T. H. M., Booij, M. j. & Nelson, A. D.https://doi.org/10.1080/01431161.2024.2326801Increasing water footprints of flex crops. Mialyk, O., Berger, M. & Booij, M. J.https://doi.org/10.5194/egusphere-egu24-1342Drought index downscaling using AI-based ensemble technique and satellite data, 2379-2397. Behfar, N., Sharghi, E., Nourani, V. & Booij, M. J.https://doi.org/10.1007/s00704-023-04822-5Improving mesh set-up increase accuracy of discharge capacity representation for water level prediction, 62-63. Khorsandi Kuhanestani, P., Bomers, A., Booij, M. J., Warmink, J. J. & Hulscher, S. J. M. H.https://cdn.bullit.digital/kbase/20240227205343/ncr-54-book_of_abstracts_ncrdays_2024_web.pdfModel identification and accuracy for estimation of suspended sediment load, 18520-18545. Khosravi, K., Golkarian, A., Saco, P. M., Booij, M. J. & Melesse, A. M.https://doi.org/10.1080/10106049.2022.2142964Water footprints and crop water use of 175 individual crops for 1990–2019 simulated with a global crop model, Article 206 (E-pub ahead of print/First online). Mialyk, O., Schyns, J. F., Booij, M. J., Su, H., Hogeboom, R. J. & Berger, M.https://doi.org/10.1038/s41597-024-03051-3Flood process types and runoff coefficient variability in climatic regions of Iran, 241-258. Jahanshahi, A. & Booij, M. J.https://doi.org/10.1080/02626667.2024.2302420
2023
Comparison between statistical and dynamical downscaling of rainfall over the Gwadar‐Ormara basin, Pakistan, Article e2151. Attique, R., Rientjes, T. & Booij, M.https://doi.org/10.1002/met.2151Key trends and opportunities in water footprints of crop production. Mialyk, O., Booij, M. J., Hogeboom, R. J. & Berger, M.https://doi.org/10.5194/egusphere-egu23-1556Exploring controls on rainfall–runoff events: spatial dynamics of event runoff coefficients in Iran, 954-966. Jahanshahi, A. & Booij, M. J.https://doi.org/10.1080/02626667.2023.2193297Uncertainty analysis of risk-based flood safety standards in the Netherlands through a scenario-based approach, 559-574. Westerhof, S. G., Booij, M. J., van den Berg, M. C. J., Huting, R. J. M. & Warmink, J. J.https://doi.org/10.1080/15715124.2022.2060243Improving mesh set-up to increase discharge capcity accuracy for water level prediction, 54-55. Khorsandi Kuhanestani, P., Bomers, A., Booij, M. J., Warmink, J. J. & Hulscher, S. J. M. H.https://cdn.bullit.digital/kbase/20230411204005/ncr-51-book_of_abstracts_ncrdays_2023_web.pdfImproving mesh set-up to increase cross-sectional-area accuracy for water-level prediction. Khorsandi Kuhanestani, P., Bomers, A., Booij, M. J., Warmink, J. J. & Hulscher, S. J. M. H.Simulated annealing coupled with a Naïve Bayes model and base flow separation for streamflow simulation in a snow dominated basin, 89-112. Tongal, H. & Booij, M. J.https://doi.org/10.1007/s00477-022-02276-1
2022
Evaluation of MODIS-Landsat and AVHRR-Landsat NDVI data fusion using a single pair base reference image: a case study in a tropical upstream catchment on Java, Indonesia, 164-197. Rustanto, A. & Booij, M. J.https://doi.org/10.1080/17538947.2021.2018057Innovative polygon trend analysis of monthly precipitation (1952–2015) in the Hindukush‐Karakoram‐Himalaya river basins of Pakistan, 9967-9993. Ahmed, N., Lü, H., Booij, M. J., Wang, G., Marhaento, H., Bhat, M. S. & Adnan, S.https://doi.org/10.1002/joc.7875Variations in hydrological variables using distributed hydrological model in permafrost environment, Article 109609. Ahmed, N., Wang, G., Booij, M. J., Marhaento, H., Pordhan, F. A., Ali, S., Munir, S. & Hashmi, M. Z.-u.-r.https://doi.org/10.1016/j.ecolind.2022.109609Use of machine learning and geographical information system to predict nitrate concentration in an unconfined aquifer in Iran, Article 131847. Gholami, V. & Booij, M. j.https://doi.org/10.1016/j.jclepro.2022.131847Influences of reservoir operation on terrestrial water storage changes detected by GRACE in the Yellow River basin, Article 127924. Xie, J., Xu, Y.-p., Booij, M. J. & Guo, Y.https://doi.org/10.1016/j.jhydrol.2022.127924Satellite rainfall bias assessment for crop growth simulation: a case study of rainfed maize growth, 1-12. Omondi, C. K., Rientjes, T. H. M., Booij, M. J. & Nelson, A. D.Inventing a hydraulic river modelling approach to simulate high flow and low flow conditions, 58-59. Khorsandi Kuhanestani, P., Bomers, A., Booij, M. J., Warmink, J. J. & Hulscher, S. J. M. H.Effect of data length, spin-up period and spatial model resolution on fully distributed hydrological model calibration in the Moselle basin, 759-772. Ekmekcioğlu, Ö., Demirel, M. C. & Booij, M. J.https://doi.org/10.1080/02626667.2022.2046754Historical simulation of crop water and land footprints. Mialyk, O., Schyns, J. F. & Booij, M. J.https://doi.org/10.5194/egusphere-egu22-2022

Onderzoeksprofielen

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