{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Querying data from the USGS National Water Information System\n",
"\n",
"\n",
"The USGS National Water Information System (NWIS) provides access to surface-water data at approximately 8,500 sites. The data are served online—most in near realtime—to meet many diverse needs. For additional information regarding NWIS, visit the [USGS website](https://waterdata.usgs.gov/nwis)."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"from HydroGenerate.hydropower_potential import calculate_hp_potential\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"##### Use streamflow data from a USGS stream gauge. \n",
"\n",
"The USGS has a Python package (**_dataretrieval_**) designed to simplify the process of loading hydrologic data into the Python environment. **_dataretrieval_** can be pip installed into a Python environment. The example code shows how to donwload data using **_dataretrieval_** and format it for hydropower potential evaluation in **_HydroGenerate_**. The example used, and additional information, is avlaiable as a [HydroShare Resource](http://www.hydroshare.org/resource/c97c32ecf59b4dff90ef013030c54264). Information about **_dataretrieval_** is avaliable directly on the [USGS GitHUb Repository](https://github.com/DOI-USGS/dataretrieval-python)."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"# Install dataretrieval, if it doesn't exist in Python environment, using: \n",
"# !pip install dataretrieval"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"# import data retrieval\n",
"from dataretrieval import nwis"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"# Set the parameters needed to retrieve data\n",
"siteNumber = \"10109000\" # LOGAN RIVER ABOVE STATE DAM, NEAR LOGAN, UT\n",
"parameterCode = \"00060\" # Discharge\n",
"startDate = \"2010-01-01\"\n",
"endDate = \"2020-12-31\"\n",
"\n",
"# Retrieve the data\n",
"dailyStreamflow = nwis.get_dv(sites=siteNumber, parameterCd=parameterCode, start=startDate, end=endDate) "
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
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\n",
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"output_type": "display_data"
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],
"source": [
"# Plot results\n",
"# Columns: discharge_cfs site_id power_kW efficiency energy_kWh\n",
"\n",
"plt.rcParams['figure.figsize'] = [14, 7]\n",
"\n",
"df = hp.dataframe_output.copy()\n",
"fig, ax1 = plt.subplots()\n",
"\n",
"\n",
"color_plot = 'tab:red'\n",
"ax1.set_xlabel('Days')\n",
"ax1.set_ylabel('Flow rate (cfs)', color=color_plot)\n",
"ax1.plot(df['turbine_flow_cfs'], label=\"Flow rate\", color=color_plot)\n",
"ax1.tick_params(axis='y', labelcolor=color_plot)\n",
"\n",
"ax2 = ax1.twinx() # instantiate a second axes that shares the same x-axis\n",
"color_plot2 = 'tab:blue'\n",
"ax2.set_ylabel('Power (kW)', color=color_plot2) # we already handled the x-label with ax1\n",
"ax2.plot(df['power_kW'],'b-',label=\"Power\", color=color_plot2)\n",
"ax2.tick_params(axis='y', labelcolor=color_plot2)\n",
"ax1.grid(True, axis='both', color='k',linestyle='--',alpha=0.4)\n",
"plt.title(\"Yearly flow data from USGS and potential power\")\n",
"fig.tight_layout() # otherwise the right y-label is slightly clipped\n",
"#plt.savefig(os.path.join('..','fig','usgs_twin_falls_flow_power.jpg'))\n",
"plt.show()"
]
}
],
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