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KINEROS2

Runs and calibrates a lumped daily KINEROS2 watershed hydrology model with Green-Ampt infiltration.

155|6|Updated Mar 31, 2026
Search Tags:#calibration#hydrology#rainfall-runoff#kineros2#watershed modeling#green-ampt#discharge simulation
One-click install
npx skills add https://github.com/lzwei196/KISS-Knowledge-Infrastructure-for-Scientific-Simulation --skill kineros2-lzwei196
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: KINEROS2
Source: https://github.com/lzwei196/KISS-Knowledge-Infrastructure-for-Scientific-Simulation/tree/main/models/KINEROS2
Command: npx skills add https://github.com/lzwei196/KISS-Knowledge-Infrastructure-for-Scientific-Simulation --skill kineros2-lzwei196

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires numpy, pandas, xarray, geopandas, scipy, shapely, matplotlib, and includes scripts (resource) and references (resource) components.

What problem does it solve? It enables an AI agent to correctly prepare inputs, execute, calibrate, and validate the KINEROS2 watershed hydrology model while avoiding silent unit-conversion failures that corrupt discharge simulations. ## Core Features & Use Cases - Forcing and soil preparation: Converts CMFD/ERA5 NetCDF precipitation and temperature into daily basin-average forcing and derives Green-Ampt parameters from USDA texture classes or HWSD/SoilGrids data. - Simulation and calibration: Runs the lumped Green-Ampt plus dual-reservoir kinematic-wave model and calibrates 8 parameters against observed discharge via differential evolution. - Diagnostics and validation: Provides 26 symptom-diagnosis-remedy triplets, a preflight environment check, and cited NSE/PBIAS validation bands for judging run quality. - Use Case: Simulate daily streamflow at the Bengbu station on the Huai River from CMFD forcing, calibrate 1981-1985, and validate against observed gauge discharge with NSE and PBIAS metrics. ## Quick Start Ask the agent to run the KINEROS2 preflight check and then simulate daily discharge for your basin by providing CMFD forcing data, a basin shapefile, and a soil texture class.

Frequently Asked Questions about KINEROS2

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run the KINEROS2 watershed model with CMFD forcing data?▼

Convert CMFD NetCDF files with convert_forcing_to_kineros2.py using a basin shapefile, generate parameters with convert_soil_to_kineros2.py, then execute run_kineros2.py in simulate mode. Parse results with parse_output_kineros2.py to compute NSE, KGE, and PBIAS.

How do I calibrate KINEROS2 parameters against observed discharge?▼

Run run_kineros2.py in calibrate mode with forcing data, observed discharge CSV, basin area, and a calibration window. It uses scipy differential evolution over 150 iterations, optimizing a combined KGE and NSE objective while excluding the spinup year.

Why is my simulated discharge 86400 times too low?▼

CMFD precipitation is in kg/m2/s and must be multiplied by 86400 to get mm/d. Without this conversion, precipitation appears near zero and produces almost no runoff, a silent failure documented as diagnostic triplet dt_001.

Can KINEROS2 be used for large basins or continuous daily simulation?▼

KINEROS2 was designed for event-based simulation on watersheds under 100 km2. This lumped daily reimplementation supports continuous runs but loses distributed routing physics, so peak-timing errors are inherent on large basins.

What Python packages does the KINEROS2 pipeline require?▼

The pipeline requires numpy, pandas, xarray, geopandas, scipy, and shapely for forcing conversion, masking, and calibration. Matplotlib is optional and only needed for validation plots.

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