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Journal ArticleDOI

River flow forecasting through conceptual models part I — A discussion of principles☆

J.E. Nash, +1 more
- 01 Apr 1970 - 
- Vol. 10, Iss: 3, pp 282-290
TLDR
In this article, the principles governing the application of the conceptual model technique to river flow forecasting are discussed and the necessity for a systematic approach to the development and testing of the model is explained and some preliminary ideas suggested.
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This article is published in Journal of Hydrology.The article was published on 1970-04-01. It has received 19601 citations till now. The article focuses on the topics: Conceptual model & Flood forecasting.

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The distributed model intercomparison project (DMIP): Motivation and experiment design

TL;DR: The distributed model intercomparison project was formulated as a broad comparison of many distributed models amongst themselves and to a lumped model used for operational river forecasting in the US to address unresolved questions on the variability of rainfall and its effect on basin response.
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A thermal-based remote sensing technique for routine mapping of land-surface carbon, water and energy fluxes from field to regional scales

TL;DR: In this article, an analytical, light-use efficiency (LUE) based model of canopy resistance within a Two-Source Energy Balance (TSEB) scheme driven primarily by thermal remote sensing inputs was investigated.
Journal ArticleDOI

Skill assessment for coupled biological/physical models of marine systems

TL;DR: The routine application and presentation of rigorous skill assessment metrics will also serve the broader interests of the modeling community, ultimately resulting in improved forecasting abilities as well as helping us recognize the authors' limitations.
Journal ArticleDOI

Automated Web Gis Based Hydrograph Analysis Tool, WHAT

TL;DR: Although base flow separation algorithms in the WHAT system cannot consider reservoir release and snowmelt that can affect stream hydrographs, the Web based WHAT system provides an efficient tool for hydrologic model calibration and validation and demonstrates how remote, distributed resources can be shared through the Internet using Web programming.
Journal ArticleDOI

Application of Long Short-Term Memory (LSTM) Neural Network for Flood Forecasting

TL;DR: In this paper, a Long Short-Term Memory (LSTM) neural network model was used for flood forecasting, where the daily discharge and rainfall were used as input data, and characteristics of the data sets which may influence the model performance were also of interest.
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