Nie Qiyang (Nie7yang)

Nie7yang

Geek Repo

Company:Hokkaido

Location:Earth

Github PK Tool:Github PK Tool

Nie Qiyang's repositories

EFDCtool

This tool aims to assist users in constructing models with EFDC+ source code more conveniently.

Language:FortranStargazers:1Issues:1Issues:0

CDRM

CDRMV3 -Distributed hydrological model

Language:FortranStargazers:0Issues:0Issues:0

DTVGM

Distributed Time-Variant Gain hydrological Model

Language:PascalStargazers:0Issues:0Issues:0

FlowDirection

DEM to DIR; DIR to ACC; ACC to Basin; ACC to Network

Language:FortranStargazers:0Issues:0Issues:0

Hydrological-data-processing-applet

Automatic extraction of river network thresholds

Language:FortranStargazers:0Issues:1Issues:0
Language:Jupyter NotebookStargazers:0Issues:0Issues:0

M3O-Multi-Objective-Optimal-Operations

M3O is a Matlab toolbox for designing the optimal operations of multipurpose water reservoir systems

Language:MATLABLicense:GPL-2.0Stargazers:0Issues:0Issues:0

MC-CDRM

Tuning CDRMV3 parameters using Monte Carlo methods

Language:FortranStargazers:0Issues:0Issues:0
Language:FortranStargazers:0Issues:0Issues:0

water_environment_data_process

Code related to water environment data acquisition and processing

Language:PythonLicense:Apache-2.0Stargazers:0Issues:1Issues:0

MODIS_statistics

Used for MODIS snow cover zoning statistics

Language:FortranLicense:GPL-3.0Stargazers:0Issues:0Issues:0
Language:HTMLStargazers:0Issues:0Issues:0

Python-Hydrology-Tools

:droplet: This repository holds a list of open source Python packages interesting to Hydrologists

Stargazers:0Issues:0Issues:0

Python-Practical-Application-on-Climate-Variability-Studies

This tutorial is a companion volume of Matlab versionm but add more. Main objective is the transference of know-how in practical applications and management of statistical tools commonly used to explore meteorological time series, focusing on applications to study issues related with the climate variability and climate change. This tutorial starts with some basic statistic for time series analysis as estimation of means, anomalies, standard deviation, correlations, arriving the estimation of particular climate indexes (Niño 3), detrending single time series and decomposition of time series, filtering, interpolation of climate variables on regular or irregular grids, leading modes of climate variability (EOF or HHT), signal processing in the climate system (spectral and wavelet analysis). In addition, this tutorial also deals with different data formats such as CSV, NetCDF, Binary, and matlab'mat, etc. It is assumed that you have basic knowledge and understanding of statistics and Python.

License:MITStargazers:0Issues:0Issues:0