mountainhydroclimate / snowcloudhydro Goto Github PK
View Code? Open in Web Editor NEWHydrologic model that uses snow cover frequency to predict streamflow
License: GNU General Public License v3.0
Hydrologic model that uses snow cover frequency to predict streamflow
License: GNU General Public License v3.0
%% Model description %% This Snow Cover Runoff (SCR) model uses monthly calculations of snow cover frequency (SCF) from the Modis instrument along with previous monthly streamflow to predict monthly streamflow with a one month lead time. This code requires MATLAB. Octave is an open-source option, though this code has only been tested in Matlab. The SCR model is based upon the paper: Sproles, E.A., Kerr, T., Orrego Nelson, C. Water Resources Management (2016) 30: 2581. doi:10.1007/s11269-016-1271-4 SCF is calculated using Google Earth Engine, and the code can be found on this same github site. This sample code is set up to run for the La Laguna sub-watershed of the r?o Elqui in northern central Chile. The model has also been tested on the John Day (easten Oregon, USA) and the r?o Aragon in northern Spain. %% Model structure %% The DOI for this code is: 10.5281/zenodo.582652 The model has seven parameters that are calibrated using this model based upon Monte Carlo simulations and Dotty Plots. The data that accompanies this code has four columns (Year, Month, Q , N) The inputs are Q is a monthly time series of stream flow N is the snowcover frequency for the basin, and should be a decimal value. nr is the number of realizations for the monte carlo simulation. A good number to start with is 1000. The model has seven parameters based upon the formula: Qpredicted = a*((tsSnow(m-1)).^b) + c*tsQshort(m-1) + d*(tsQlong(m-1)); tsSnow is the moving timeseries for SCF. The model optimizes the # of months for the time series. tsQshort is the moving timeseries for Q in the short term. The model optimizes the # of months for the time series. tsQlong is the moving timeseries for Q in the long term, and conceptually reresents baseflowconditions The model optimizes the # of months for the time series. a, c, and d are scaling coefficients specific to each model forcing. b is an exponential scaling parameter and represents the tapering effect of snowpack contributions to streamflow as it melts (Leibowitz et al. 2012).
A declarative, efficient, and flexible JavaScript library for building user interfaces.
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. ๐๐๐
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google โค๏ธ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.