Results 11 to 20 of about 77,303 (305)

Prediction of the Rainfall – Runoff Relationship Using Neuro-Fuzzy and Support Vector Machines. [PDF]

Aerul şi Apa: Componente ale Mediului, 2019
Rainfall- Runoff relationship analyzes are essential for the protection of flood rooting, management of water resources and design of water structures.
Bestami TAȘAR, Fatih UNES, Hakan VARCİN   +2 more
doaj   +1 more source

Uncertainty Estimation with Deep Learning for Rainfall–Runoff Modelling [PDF]

Hydrology and Earth System Sciences, 2021
Abstract. Deep Learning is becoming an increasingly important way to produce accurate hydrological predictions across a wide range of spatial and temporal scales. Uncertainty estimations are critical for actionable hydrological forecasting, and while standardized community benchmarks are becoming an increasingly important part of hydrological model ...
Klotz, Daniel, Kratzert, Frederik, Gauch, Martin, Keefe Sampson, Alden, Brandstetter, Johannes, Klambauer, Günter, Hochreiter, Sepp, Nearing, Grey   +7 more
openaire   +4 more sources

Physics-Informed Data-Driven Model for Predicting Streamflow: A Case Study of the Voshmgir Basin, Iran

Applied Sciences, 2022
Accurate rainfall-runoff modeling is crucial for water resource management. However, the available models require more field-measured data to produce accurate results, which has been a long-term issue in hydrological modeling.
Peiman Parisouj, Esmaiil Mokari, Hamid Mohebzadeh, Hamid Goharnejad, Changhyun Jun, Jeill Oh, Sayed M. Bateni   +6 more
doaj   +1 more source

Rainfall disaggregation for hydrological modeling: is there a need for spatial consistence? [PDF]

Hydrology and Earth System Sciences, 2018
In this study, the influence of disaggregated rainfall products with different degrees of spatial consistence on rainfall–runoff modeling results is analyzed for three mesoscale catchments in Lower Saxony, Germany.
H. Müller-Thomy, H. Müller-Thomy, H. Müller-Thomy, M. Wallner, K. Förster, K. Förster, K. Förster   +6 more
doaj   +1 more source

EVALUATION OF RAINFALL-RUNOFF MODELS FOR MEDITERRANEAN SUBCATCHMENTS [PDF]

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016
The development and the application of rainfall-runoff models have been a corner-stone of hydrological research for many decades. The amount of rainfall and its intensity and variability control the generation of runoff and the erosional processes operating at different scales. These interactions can be greatly variable in Mediterranean catchments with
Cilek, A., Berberoglu, S., Donmez, C.
openaire   +5 more sources

Estimating rainfall and water balance over the Okavango River Basin for hydrological applications [PDF]

, 2006
A historical database for use in rainfall-runoff modeling of the Okavango River Basin in Southwest Africa is presented. The work has relevance for similar data-sparse regions.
Adeyewa, Adler, Brath, Cornelis Vanderpost, Denis Hughes, Dominic Kniveton, Gan, Grimes, Haddad, Julie Wilk, Kummerow, Kummerow, Kummerow, Lebel, Lotta Andersson, Martin C. Todd, McCarthy, Nash, Negri, New, Oki, Russell Layberry, Susan Ringrose, Weber, Wilk   +24 more
core   +2 more sources

The PDM rainfall-runoff model [PDF]

Hydrology and Earth System Sciences, 2007
Abstract. The Probability Distributed Model, or PDM, has evolved as a toolkit of model functions that together constitute a lumped rainfall-runoff model capable of representing a variety of catchment-scale hydrological behaviours. Runoff production is represented as a saturation excess runoff process controlled by the absorption capacity (of the canopy,
openaire   +5 more sources

Incorporating non-uniformity and non-linearity of hydrologic and catchment characteristics in rainfall–runoff modeling using conceptual, data-driven, and hybrid techniques

Journal of Hydroinformatics, 2022
The rainfall–runoff (RR) process in a catchment is non-uniform, complex, dynamic, and non-linear in nature. Although a number of advanced conceptual and data-driven techniques have been proposed in the past, the accurate estimation of daily runoff still ...
Vikas Kumar Vidyarthi, Ashu Jain
doaj   +1 more source

Understanding predictive uncertainty in hydrologic modeling: The challenge of identifying input and structural errors [PDF]

, 2009
Meaningful quantification of data and structural uncertainties in conceptual rainfall-runoff modeling is a major scientific and engineering challenge. This paper focuses on the total predictive uncertainty and its decomposition into input and structural ...
Atger, Benjamin Renard, Beven, Beven, Beven, Bras, Bulygina, Di Baldassarre, Dmitri Kavetski, Dottori, Duan, Eberly, Fenicia, Fenicia, Feyen, Franks, Gelfand, Gelman, George Kuczera, Goldstein, Haario, Hadamard, Hall, Huard, Jacquin, Kavetski, Kavetski, Kavetski, Kavetski, Kennedy, Krzysztofowicz, Kuczera, Kuczera, Kuczera, Laio, Mantovan, Mark Thyer, Marshall, Montanari, Montanari, Moradkhani, Moyeed, Neppel, Oudin, Perrin, Refsgaard, Reichert, Reitan, Renard, Severino, Spiegelhalter, Stedinger, Stewart W. Franks, Tarantola, Thiemann, Thyer, Tonkin, Wagener, Yang, Young   +59 more
core   +3 more sources

Development and Validation of Accumulation Term (Distributed and/or Point Source) in a Finite Element Hydrodynamic Model

Journal of Marine Science and Engineering, 2023
During tropical storms, precipitation and associated rainfall-runoff can lead to significant flooding, in both the upland and coastal areas. Flooding in coastal areas is compounded by the storm surge.
Kendra M. Dresback, Christine M. Szpilka, Randall L. Kolar, Saeed Moghimi, Edward P. Myers   +4 more
doaj   +1 more source