Journal ArticleDOI
River flow forecasting through conceptual models part I — A discussion of principles☆
J.E. Nash,J.V. Sutcliffe +1 more
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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.About:
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.read more
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A review of validation methodologies and statistical performance indicators for modeled solar radiation data: Towards a better bankability of solar projects
TL;DR: In this paper, the authors present guidelines for successful validation of solar radiation data, not only from the standpoint of solar scientists but also of non-experts with limited knowledge of radiometry or solar radiation modeling.
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Deep solar radiation forecasting with convolutional neural network and long short-term memory network algorithms
TL;DR: It is ascertained that a proposed hybrid model based on a convolution network framework can accurately predict GSR and enable energy availability to be regularly monitored over multi-step horizons when coupled with a low latency Long Short-Term Memory network.
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Water Erosion Prediction Project (WEPP): Development History, Model Capabilities, and Future Enhancements
TL;DR: The Water Erosion Prediction Project (WEPP) as discussed by the authors was initiated in 1985 to develop new-generation water erosion prediction technology for use by federal action agencies involved in soil and water conservation and environmental planning and assessment.
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A comparative study of Markov chain Monte Carlo methods for conceptual rainfall‐runoff modeling
TL;DR: In this paper, Markov chain Monte Carlo (MCMCMC) sampling of the posterior distribution has been used to estimate parameter uncertainty in hydrological models, where prior knowledge about the parameter is combined with information from the available data to produce a probability distribution (the posterior distribution) that describes uncertainty about the parameters and serves as a basis for selecting appropriate values for use in modeling applications.
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Identification and Prioritisation of Critical Sub-watersheds for Soil Conservation Management using the SWAT Model
TL;DR: In this article, a calibrated Soil and Water Assessment Tool (SWAT) model was verified for a small watershed (Nagwan) and used for identification and prioritisation of critical sub-watersheds to develop an effective management plan.