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1 |
Hydrological modelling of karst catchment using lumped conceptual and data mining models
مدل سازی هیدرولوژیکی حوضه کارست با استفاده از مدلهای مفهومی و داده کاوی بهم چسبیده-2019 Hydrological modelling is a challenging and significant issue, especially in nonhomogeneous catchments in
terms of geology, and it is an essential part of water resources management. In this study, daily rainfall-runoff
modelling was carried out using the lumped conceptual model, the artificial neural network (ANN), the deepneural
network (DNN), and regression tree (RT) data mining models for the nonhomogeneous karst Ljubljanica
catchment and four of its sub-catchments in Slovenia with different geological characteristics. Model performance
was evaluated using several performance criteria and additional investigation of low and high flows was
carried out. The results of the study indicate that the Génie Rural à 4 paramètres Journalier (GR4J) lumped
conceptual model yielded better modelling performance compared to the data-driven models, namely ANN, DNN
and RT models. Moreover, the enhanced version of the GR4J model (i.e. GR6J) also yielded good performance in
terms of the recession part. The RT model yielded the worst performance regarding runoff forecasting among the
examined models in the case of all five investigated catchments. However, ANN and DNN data-driven models
were slightly more successful in modelling the hydrograph recession in the case of karst sub-catchments compared
to the GR4J lumped conceptual model structure. Inclusion of additional meteorological variables to ANN
and DNN does not significantly improve modelling results. Keywords: Hydrological model | Lumped conceptual model | Data mining | Karst | Nonhomogeneous catchment | Ljubljanica River |
مقاله انگلیسی |
2 |
OpenMP Parallelization of a Gridded SWAT (SWATG)
OpenMP Parallelization of a Gridded SWAT (SWATG)-2017 Large-scale, long-term and high spatial resolution simulation is a common issue
in environmental modeling. A Gridded Hydrologic Response Unit (HRU)-based Soil
and Water Assessment Tool (SWATG) that integrates grid modeling scheme with
different spatial representations also presents such problems. The time-consuming
problem affects applications of very high resolution large-scale watershed modeling.
The OpenMP (Open Multi-Processing) parallel application interface is integrated with
SWATG (called SWATGP) to accelerate grid modeling based on the HRU level. Such
parallel implementation takes better advantage of the computational power of a shared
memory computer system. We conducted two experiments at multiple temporal and
spatial scales of hydrological modeling using SWATG and SWATGP on a high-end
server. At 500-m resolution, SWATGP was found to be up to nine times faster than
SWATG in modeling over a roughly 2,000 km2 watershed with 1 CPU and a 15 thread
configuration. The study results demonstrate that parallel models save considerable
time relative to traditional sequential simulation runs. Parallel computations of
environmental models are beneficial for model applications, especially at large spatial
and temporal scales and at high resolutions. The proposed SWATGP model is thus a
promising tool for large-scale and high-resolution water resources research and
management in addition to offering data fusion and model coupling ability.
Keywords: grid | parallel | SWAT | hydrological model | OpenMP |
مقاله انگلیسی |