Giter VIP home page Giter VIP logo

gw-predictor's Introduction

GW-predictor - Groundwater Prediction Using Machine Learning

GW-predictor is a research project written in Python that aims to predict the groundwater discharge potential at any coordinate specified. At the moment, the project is trained for Kathmandu Valley and ready to use for predicting discharge within Kathmandu. Training and testing of Gaussian Process Model is implemented in jupyter lab interface with the use of python package GPy. Keeping in mind that very few data is used for training the model, it's relatively low accuracy of prediction is not a surprise.

GW-predictor is a result of work for the 'Code for Nepal Datacrunch Hackathon' by team Lithosphere. Members of team Lithosphere include Nelson Kandel, Samriddhi Ghimire and Prabesh Gyawali. Team Lithosphere succeded to secure the second position in the hackathon.

Gw-predictor is availabe under the MIT license. We'd love to incroporate your changes, so fork us.

Requirements

GW-predictor uses the following Python packages:

Data Description

A sample of original data file is provided in data folder. Each well have their unique well ids. Multiple row entry for with same well id represent data for multiple depth of the soil layer below ground level. First row entry of each well ids have discharge and other hydraulic properties associated with the specific well.

Preprocessing

Following steps are considered for preprocessing process:

  1. Read original data file.
  2. Extract first row for each unique well ids.
  3. Check for no values.
  4. Save the required information.

Model Training

Train test ration = 70%
RBF Kernal:
Input Dimensions = 2 (i.e, x, y UTM coordinates)
Lengthscale = 200
Variance = 5
Optimization Algorithm: Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS)

Results

Scatter Plot of Actual Discharge vs Predicted Discharge
Q_act vs Q_pred

1D Cross section of prediction model along x-axis
Q_act vs Q_pred

Data Courtesy

Kathmandu Upatyaka Khanepani Limited

gw-predictor's People

Contributors

kandeln avatar samriddhighimire avatar

Stargazers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.