Hydrological Modelling

Hydrological modelling is the use of mathematical models to simulate the movement of water through the Earth’s surface and subsurface. These models can be used to predict water availability, assess the impact of climate change, and manage water resources.

Within the realm of hydrological modelling, a diverse array of models exists, spanning from the simplicity of conceptual models to the intricacy of distributed models like AD2 and DREAM. Conceptual models offer a streamlined portrayal of the hydrological system, while distributed models provide a more comprehensive and detailed representation.

The selection of the appropriate model hinges on the specific application at hand. For instance, when predicting water availability for irrigation, a straightforward conceptual model might suffice, whereas assessing the repercussions of climate change on a river basin could necessitate the use of a complex distributed model.

Beyond model selection, the calibration of these models holds paramount significance. Calibration entails the meticulous adjustment of model parameters to align the model’s output with observed data—a formidable task, particularly in data-limited environments.

In recent years, an increasingly fervent interest has emerged in harnessing remote sensing observations to enhance hydrological modelling. Remote sensing data offer valuable insights into critical factors such as land cover and soil moisture, significantly enriching the precision of hydrological models.

Hydrological Modelling Initiatives

Within the realm of hydrological modelling, numerous dynamic activities are underway, including:

  1. Development of New Hydrological Models
  2. Calibration of Hydrological Models
  3. Utilization of Remote Sensing Data
  4. Application of Hydrological Models

Conclusion

Hydrological modelling stands as a potent and indispensable tool in our quest to comprehend and effectively manage Earth’s invaluable water resources. The continual development of novel models, meticulous calibration of existing ones, and the judicious incorporation of remote sensing data are pivotal endeavors, all working in concert to bolster the accuracy and utility of hydrological models. By advancing our understanding and harnessing the power of these models, we pave the way for more sustainable and resilient water management practices in an ever-changing world.

References

  1. Bancheri, M., R. Rigon and S. Manfreda, The GEOframe-NewAge modelling system applied in a data scarce environmentWater12, 86, (doi: 10.3390/w12010086) 2019. [pdf]
  2. Baldwin, D., S. Manfreda, H. Lin, and E.A.H. Smithwick, Estimating root zone soil moisture across the Eastern United States with passive microwave satellite data and a simple hydrologic modelRemote Sensing11, 2013, (doi: 10.3390/rs11172013), 2019. [pdf]
  3. Manfreda, S., Mita, L., S. F. Dal Sasso, C. Samela, L. Mancusi, Exploiting the Use of Physical Information for the Calibration of a Lumped Hydrological ModelHydrological Processes, 32(10), 1420-1433, (doi: 10.1002/hyp.11501), 2018.  [pdf]
  4. Ruiz-Pérez, G., J. Koch, S. Manfreda, K.K. Caylor, F. Francés, Calibration of a parsimonious distributed ecohydrological daily model in a data scarce basin using exclusively the spatio-temporal variation of NDVIHydrology and Earth System Sciences, 21, 6235-6251, (doi: 10.5194/hess-21-6235-2017) 2017. [pdf]
  5. Manfreda, S., L. Brocca, T. Moramarco, F. Melone, and J. Sheffield, A physically based approach for the estimation of root-zone soil moisture from surface measurementsHydrology and Earth System Sciences, 18, 1199-1212, (doi:10.5194/hess-18-1199-2014), 2014. [pdf
  6. Manfreda, S., T. Lacava, B. Onorati, N. Pergola, M. Di Leo, M. R. Margiotta, and V. Tramutoli, On the use of AMSU-based products for the description of soil water content at basin scaleHydrology and Earth System Sciences, 15, 2839-2852, (doi:10.5194/hess-15-2839-2011), 2011. [pdf
  7. Manfreda, S., T.M. Scanlon, K.K. Caylor, On the importance of accurate depiction of infiltration processes on modelled soil moisture and vegetation water stressEcohydrology, 3, 155-165, (doi: 10.1002/eco.79), 2010. [pdf]
  8. Gigante V., P. Milella, V. Iacobellis, S. Manfreda, and I. Portoghese, Influences of Leaf Area Index estimations on the soil water balance predictions in Mediterranean regionsNatural Hazard and Earth System Sciences, 9, 979-991, (doi:10.5194/nhess-9-979-2009), 2009. [pdf] 
  9. Manfreda, S., Runoff Generation Dynamics within a Humid River BasinNatural Hazard and Earth System Sciences, 8, 1349-1357, (doi:10.5194/nhess-8-1349-2008), 2008. [pdf]
  10. Manfreda, S., M. Fiorentino, A Stochastic Approach for the Description of the Water Balance Dynamics in a River BasinHydrology and Earth System Sciences, 12, 1189-1200, (doi:10.5194/hess-12-1189-2008), 2008.  [pdf]
  11. Fiorentino, M., S. Manfreda, V. Iacobellis, Peak Runoff Contributing Area as Hydrological Signature of the Probability Distribution of FloodsAdvances in Water Resources, 30(10), 2123-2134, (doi:10.1016/j.advwatres.2006.11.017), 2007.  [pdf]
  12. Manfreda, S., M. Fiorentino, V. Iacobellis, DREAM: a Distributed model for Runoff, Evapotranspiration, and Antecedent Soil Moisture SimulationAdvances in Geosciences, 2, 31-39, (SRef-ID: 1680-7359/adgeo/2005-2-31), 2005. [pdf]

Attachments

  • pdf DREAM Model
    DREAM: a Distributed model for Runoff, Evapotranspiration, and Antecedent Soil Moisture Simulation
    Date added: 14 July 2023 07:42 File size: 762 KB Downloads: 52
  • pdf 2017_Guiomar_Ruiz-Perez_HESS
    Calibration of a parsimonious distributed ecohydrological daily model in a data scarce basin using exclusively the spatio-temporal variation of NDVI
    Date added: 14 July 2023 07:43 File size: 5 MB Downloads: 53
  • pdf Calibration of the AD2 Model
    Exploiting the Use of Physical Information for the Calibration of a Lumped Hydrological Model
    Date added: 14 July 2023 07:44 File size: 2 MB Downloads: 63
  • pdf 2009_Gigante_et_al_NHESS
    Influences of Leaf Area Index estimations on the soil water balance predictions in Mediterranean regions
    Date added: 14 July 2023 07:47 File size: 2 MB Downloads: 45