YX577's repositories
Area-Water-Resources-Optimization
This is a multi-objective optimization with constriant NSGA-2
2DayCourse
My 2-day short course on spatial data analytics and geostatistics. I hope these resources are helpful, Prof. Michael Pyrcz
CA_Electricty_Price_Prediction_Neural_Net
Time series regression models using ARIMA, SARIMAX, and Recursive Neural Network to predict day-ahead and hour-ahead California wholesale electricity prices. Features include demand forecasts, NOAA weather station data, and CA Dept. of Water Resources reservoir water level hourly observation.
Calculate-Precipitation-based-Agricultural-Drought-Indices-with-Python
Precipitation-based indices are generally considered as the simplest indices because they are calculated solely based on long-term rainfall records that are often available. The mostly used precipitation-based indices consist of Decile Index (DI) Hutchinson Drought Severity Index (HDSI) Percen of Normal Index (PNI) Z-Score Index (ZSI) China-Z Index (CZI) Modified China-Z Index (MCZI) Rainfall Anomaly Index (RAI) Effective Drought Index (EDI) Standardized Precipitation Index (SPI).
chaotic-downscaling
Chaotic Statistical Downscaling
courseworkSAWR
System analysis of water resources:methods and applications coursework.
datacourse2018
Data Course Hydrology / Env. Science
DLcoursera
Coursera Deep Learning Specialization
eci273
Code examples from graduate water resources systems engineering class
eecmip5
Download and manipulate CMIP5 climate simulations from Earth Engine
Flood_CrisisManagament
AI pipeline for Flood prediction from rainfall dataand Sentiment Analysis for disaster management
Hydro_Seper
This document is the user manual of codes designed for the hydrograph separation method reported in Mei & Anagnostou (2015. A Hydrograph Separation Method Based on Information from Rainfall and Runoff Records).
hySens
Analysis of uncertainty in hydrological climate change assessment
kalman-filter
Kalman Filter implementation in Python using Numpy only in 30 lines.
lmoments3
Estimate linear moments for statistical distribution functions
local-coastal-flood-risk
Characterizing flood hazard estimates used by decision makers
LSTM-water-table-depth-prediction
Theano implementation of our paper 'Developing a Long Short-Term Memory (LSTM) based Model for Predicting Water Table Depth in Agricultural Areas', Journal of Hydrology.
obsio
obsio is a Python package that provides a consistent generic interface for accessing weather and climate observations from multiple different data providers.
persiann-cdr-eval
Evaluation of PERSIANN-CDR precipitation product.
Precip_MultiPanel
A Jupyter Notebook to visualize precipitation products from a collection of different datasets.
PrecipitationPrediction
Existing precipitation prediction models have high error rates. The goal of this research is to reduce the error rates of the existing prediction models. An ensemble approach has been proposed to develop a New Aggregated Model to predict precipitation based on the dataset of some existing prediction models. This is a part of my master's thesis project.
predict_potential_water_arcgis
Predict potential water resources using ArcGIS & Python
red_river
Python and R code for bias correction and empirical-statistical downscaling of GCM projections for the Red River basin in Vietnam.
SIESD_2018
Process and analyze streamflow data from ftp://hydrology.nws.noaa.gov/pub/gcip/mopex/US_Data/
SOI
Southern Oscillation Index Data
VanDantzig
Model code for Oddo et al. (2017) - Multiobjective adaptation analysis
warsa
Water resources system analysis in python
water-resource-emulation
Supplementary materials for Owen N.E. & Liuzzo L. "Impact of land use on water resources via a Gaussian process emulator with dimension reduction"