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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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Models for estimating daily rainfall erosivity in China.

TL;DR: In this article, the authors used one-minute resolution rainfall data recorded in sixteen stations over the eastern water erosion impacted regions of China to parameterize models suitable for estimating erosivity from daily rainfall data, which are more widely available.
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Predicting the spatial patterns of hillslope sediment delivery to river channels in the Murrumbidgee catchment, Australia

TL;DR: In this paper, a spatially distributed soil erosion and sediment delivery model (WATEM/SEDEM) was used to predict sediment delivery in the Murrumbidgee River basin.
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Runoff and Sediment Yield Modeling using Artificial Neural Networks: Upper Siwane River, India

TL;DR: In this article, Artificial Neural Network (ANN) models were developed, to predict both runoff and sediment yield on a daily and weekly basis, for a small agricultural watershed for proper watershed management.
Journal ArticleDOI

Evaluation of ensemble streamflow predictions in Europe

TL;DR: In this article, the current status of the monitoring and evaluation framework of the European Flood Awareness System (EFAS) is presented, where 10-day ensemble streamflow predictions are evaluated against a reference simulation which uses observed meteorological fields as input to a calibrated hydrological model.
Journal ArticleDOI

Comparison of Noah simulations with eddy covariance and soil water measurements at a winter wheat stand

TL;DR: In this article, the performance of the Noah land surface model (LSM) for energy partitioning and soil water dynamics on a winter wheat stand in southwest Germany was evaluated using a set of eddy covariance (EC) data collected in the 2009 season.
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