YX577

Area-Water-Resources-Optimization

This is a multi-objective optimization with constriant NSGA-2

11

A white

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

SVM-for-Temperature-Prediction

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"