What metrics does the skill use to validate groundwater models?

It focuses on Explained Variance Percentage (EVP), Root Mean Square Error (RMSE), and Information Criteria (AIC/BIC) to ensure model accuracy and prevent overfitting.

What is the Pastas library used for in this skill?

Pastas is an open-source Python framework specifically designed for processing, simulating, and analyzing groundwater time series data using transfer function noise models.

Does this skill replace 3D modeling tools like MODFLOW?

No, Pastas is used for site-specific time series analysis and transfer functions, whereas tools like FloPy/MODFLOW are intended for 3D spatially distributed numerical groundwater flow modeling.

Can this skill handle pumping data and river levels?

Yes, the skill provides implementation patterns for adding StressModels like pumping wells or river stages using specialized response functions such as Hantush or Exponential.

Pastas Groundwater Analysis

Name: Pastas Groundwater Analysis
Author: SteadfastAsArt

bySteadfastAsArt

•

Ciencia de Datos y ML

Models and analyzes groundwater time series data using transfer function noise models to understand aquifer behavior and forecast levels.

This skill integrates the Pastas library into Claude's workflow, enabling sophisticated groundwater time series analysis and modeling. It allows users to simulate how well levels respond to external stresses such as precipitation, evaporation, and pumping. By providing domain-specific guidance on transfer function selection (Gamma, Hantush, Exponential) and model diagnostics (EVP, AIC/BIC), it helps geoscientists decompose complex hydrological signals into meaningful components. It is particularly useful for calibrating aquifer parameters, performing long-term forecasts, and generating automated diagnostic plots for residual analysis.

Características Principales

01Generate comprehensive model diagnostics including EVP, RMSE, and residual autocorrelation

0212 GitHub stars

03Calibrate aquifer parameters using predefined response functions like Gamma and Hantush

04Forecast and hindcast groundwater levels based on historical stress data

05Decompose complex hydrological signals into individual stress contributions

06Model groundwater response to precipitation, evaporation, and pumping stresses

Casos de Uso

01Quantifying the impact of climate variability on local groundwater level trends

02Separating the effects of river stage fluctuations from precipitation recharge in riparian wells

03Estimating aquifer drawdown and recovery resulting from industrial pumping operations

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add steadfastasart/geoscience-skills pastas

For use in Claude.ai and ChatGPT

Download Skill