21 skills found
utah-geological-survey / WellApplicationTools used to manipulate hydrograph data; Solinst xles to pandas dataframe; hydrograph analysis; hydrology; Gannt Charts; Piper diagrams; hydrogeology; wells; groundwater; USGS data; WQP data;
yousseftfifha / Groundwater Management Under Climate ChangeThis project aims to study the impact of climate change on groundwater level in Mornag plain in Tunisia. Indeed, in the last few decades, aquifers all over the world have experienced notable water level variability due to the spatiotemporal variability of rainfall and temperature. Therefore, for a reliable groundwater management under climate change context, it is mandatory to analyze and estimate its level variability. In this study, we focus on the plain of Mornag, located in the southeast of Tunisia, since it represents 33% of the national agricultural production. From this plain, we have collected historical piezometric and pluviometric data covering the period 2005-2017. Knowing the pluviometric data, our goal is to predict the piezometric one. This issue has been already studied using classical numerical groundwater modeling such as Modflow and Feflow. Despite unsatisfactory results, these techniques are data and time consuming. To overcome all these drawbacks, we propose to use two Artificial Intelligence (AI) approaches: the Extreme Gradient Boosting (XGBoost) approach, that has shown great performances in literature, and the well used one in our context which involves the use of Long-Short Term Memory (LSTM) Neural Network. For better results, we have added supplementary features to our dataset such as the cluster zone (zones with same characteristics) and the Standardized Precipitation Index (SPI) which can identify drought at different time scales. Both approaches have been executed entirely on GPU for time acceleration. Compared with traditional existing methods, they both have shown a high level of accuracy which confirms their adequacy for groundwater level forecasting. The proposed prediction models will be used for evaluating the repercussions of climate change on groundwater levels under the different scenarios RCP 4.5 and RCP 8.5 for the period of 2017-2090. It will be evaluated for three future periods: 2017-2040 (short term), 2041-2065 (medium term) and 2066-2090 (long term). The analysis of the future results using AI will be considered as a new Decision Support System used to optimize the management of our limited resources in order to satisfy the needs of the population in terms of drinking water and agriculture production.
bcgov / Groundwater Levels IndicatorR scripts for an indicator on long-term trends in groundwater levels in B.C. published on Environmental Reporting BC
xjtu-gwdg / GraphFourierNetA Graph Fourier-Based Deep Learning Model to Predict Regional Groundwater Level Variations with Hydrogeological and Spatio-Temporal Interpretability
DOI-USGS / HASPHydrologic AnalySis Package. See official source code: https://doi-usgs.github.io/HASP/
peterson-tim-j / HydroMapMapping of groundwater level for realistic flow flowpaths using semi-automated kriging.
AndreasWunsch / Groundwater Level Forecasting With ANNs A Comparison Of LSTM CNN And NARXNo description available
aleaf / PydrographGet and process stream flows and groundwater levels from NWIS.
inkenbrandt / Earth TidesScripts used to examine time series groundwater level data, including barometric efficiency calculations.
Nelvinebi / Mapping Groundwater Contamination Using GIS MLThis project leverages GIS and machine learning to map groundwater contamination using synthetic data. It identifies spatial pollution trends, predicts contamination levels, and supports sustainable water resource management.
UVAdMIST / Norfolk Groundwater ModelThis repository contains scripts to model and forecast shallow groundwater table level in Norfolk, VA with artificial neural networks.
meresar / Erdos GroundwaterImplementing supervised machine learning models to forecast groundwater levels using surface water and weather data. Final project for the Erdos Institute Data Science Boot Camp, Fall 2023.
UNIGRAC / Global Reporting Groundwater LevelsThis repository contains the programs (and associated reports) that have been developed to report on Groundwater Levels in the State of Global Water Resources report.
calgo-lab / Gwl Forecast Pipelinemodel pipeline for groundwater level prediction in German
mgomezo12 / Performance CnnPerformance assessment of geospatial and time series features on groundwater level forecasting with deep learning.
datadesk / Groundwater AnalysisA Los Angeles Times analysis of well completion, groundwater levels, and water shortages in the San Joaquin Valley
msmahatha / Groundwater Level No description available
CalvnSamwel / Soil Moisture And Groundwater Level Monitoring Using Sentinel 1Extracting Volumetric Soil Moisture and Groundwater level using Radar Remote Sensing
Aqualinc / Auto Groundwater Data ProcessorSoftware tools to automagically process large numbers of groundwater level time series data
wondy30 / GRACE TWSA Downscaling MlR code developed to downscale GRACE TWSA into depth to groundwater level using machine learning
