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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
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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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Calibration of hydrological model parameters for ungauged catchments

TL;DR: In this paper, a different approach for the transfer of entire parameter sets from one catchment to another is discussed, where parameter sets are considered as tranferable if the corresponding model performance (defined as the Nash-Sutclife efficiency) on the donor catchment is good and the regional statistics: means and variances of annual discharges estimated from catchment properties and annual climate statistics for the recipient catchment are well reproduced by the model.
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A spatially distributed energy balance snowmelt model for application in mountain basins

TL;DR: In this article, a coupled energy and mass-balance model is used to simulate the development and melting of the seasonal snow cover in several mountain basins in California, Idaho, and Utah.
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Evaluation of a low-cost soil water content sensor for wireless network applications

TL;DR: In this article, a low-cost soil water content sensor (ECH2O probe model EC-5, Decagon Devices Inc., Pullman, WA) using laboratory as well as field experiments was evaluated.
Journal ArticleDOI

Using the USLE: Chances, challenges and limitations of soil erosion modelling

TL;DR: In this paper, a review of the most widely used approaches during an 80-year history of erosion modelling are Universal Soil Loss Equation (USLE)-type algorithms which have been applied in 109 countries.
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Rainfall–runoff modeling using artificial neural network coupled with singular spectrum analysis

TL;DR: This paper attempts to eliminate the lag effect from two aspects: modular artificial neural network (MANN) and data preprocessing by singular spectrum analysis (SSA) and shows that MANN does not exhibit significant advantages over ANN, and it is demonstrated that SSA can considerably improve the performance of prediction model and eliminate thelag effect.
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