little_hope.ipynb

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    "# Little Hope Creek :: Peak Flow Analysis\n",
    "\n",
    "This workflow demonstrates an application of event detection to generate a distribution of peak discharges from [Little Hope Creek](https://waterdata.usgs.gov/nc/nwis/inventory/?site_no=02146470&agency_cd=USGS) in North Carolina.\n",
    "\n",
    "## Preparing the environment\n",
    "\n",
    "The included `Makefile` will build the python environment and run the `little_hope.py` script. This script retrieves one year of streamflow data for Little Hope Creak and caches it in a local sqlite database. The script cleans and resamples the data before applying event detection. This workflow applies event detection using time series decomposition as found in the [HydroTools](https://github.com/NOAA-OWP/hydrotools) package. For each event, the script computes peak discharge. The final output are two figures: a histogram of peak discharges and a streamflow hydrograph depicting the start times of all events. Below we step through each part of the `little_hope.py` script and explain the process."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "exceptional-territory",
   "metadata": {},
   "source": [
    "## 1. Import dependencies\n",
    "Import the `nwis_client` tool to retrieve USGS streamflow measurements, `event_detection` to look for hydrological events in a time series of streamflow measurements, and `matplotlib` to plot the results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "instrumental-feature",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import tools to retrieve data and detect events\n",
    "from hydrotools.nwis_client.iv import IVDataService\n",
    "from hydrotools.events.event_detection import decomposition as ev\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "sixth-singapore",
   "metadata": {},
   "source": [
    "## 2. Retrieve data\n",
    "Use the `nwis_client` tool to retrieve one year of streamflow measurements from Little Hope Creek."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "miniature-description",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jregina/.pyenv/lint/lib/python3.8/site-packages/hydrotools/nwis_client/iv.py:283: FutureWarning: In a future version, `df.iloc[:, i] = newvals` will attempt to set the values inplace instead of always setting a new array. To retain the old behavior, use either `df[df.columns[i]] = newvals` or, if columns are non-unique, `df.isetitem(i, newvals)`\n",
      "  dfs.loc[:, \"value\"] = pd.to_numeric(dfs[\"value\"], downcast=\"float\")\n"
     ]
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>value_time</th>\n",
       "      <th>variable_name</th>\n",
       "      <th>usgs_site_code</th>\n",
       "      <th>measurement_unit</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-09-30 23:00:00</td>\n",
       "      <td>streamflow</td>\n",
       "      <td>02146470</td>\n",
       "      <td>ft3/s</td>\n",
       "      <td>0.72</td>\n",
       "      <td>['A']</td>\n",
       "      <td>0</td>\n",
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       "      <th>1</th>\n",
       "      <td>2019-09-30 23:05:00</td>\n",
       "      <td>streamflow</td>\n",
       "      <td>02146470</td>\n",
       "      <td>ft3/s</td>\n",
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       "      <th>2</th>\n",
       "      <td>2019-09-30 23:10:00</td>\n",
       "      <td>streamflow</td>\n",
       "      <td>02146470</td>\n",
       "      <td>ft3/s</td>\n",
       "      <td>0.79</td>\n",
       "      <td>['A']</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-09-30 23:15:00</td>\n",
       "      <td>streamflow</td>\n",
       "      <td>02146470</td>\n",
       "      <td>ft3/s</td>\n",
       "      <td>0.72</td>\n",
       "      <td>['A']</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-09-30 23:20:00</td>\n",
       "      <td>streamflow</td>\n",
       "      <td>02146470</td>\n",
       "      <td>ft3/s</td>\n",
       "      <td>0.72</td>\n",
       "      <td>['A']</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "           value_time variable_name usgs_site_code measurement_unit  value  \\\n",
       "0 2019-09-30 23:00:00    streamflow       02146470            ft3/s   0.72   \n",
       "1 2019-09-30 23:05:00    streamflow       02146470            ft3/s   0.79   \n",
       "2 2019-09-30 23:10:00    streamflow       02146470            ft3/s   0.79   \n",
       "3 2019-09-30 23:15:00    streamflow       02146470            ft3/s   0.72   \n",
       "4 2019-09-30 23:20:00    streamflow       02146470            ft3/s   0.72   \n",
       "\n",
       "  qualifiers series  \n",
       "0      ['A']      0  \n",
       "1      ['A']      0  \n",
       "2      ['A']      0  \n",
       "3      ['A']      0  \n",
       "4      ['A']      0  "
      ]
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     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "# Retrieve streamflow observations for Little Hope Creek\n",
    "client = IVDataService()\n",
    "observations = client.get(\n",
    "    sites='02146470', \n",
    "    startDT='2019-10-01', \n",
    "    endDT='2020-09-30'\n",
    "    )\n",
    "\n",
    "# Look at raw data\n",
    "observations.head()"
   ]
  },
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   "cell_type": "markdown",
   "id": "characteristic-marsh",
   "metadata": {},
   "source": [
    "## 3. Preprocess streamflow measurements\n",
    "Let's reduce the size of the data and make sure the data is consistent. This means dropping extra columns, checking for duplicate data, filling missing data, resampling the data to a consistent frequency, and indexing the data by datetime."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "junior-windsor",
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   "outputs": [
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      "text/plain": [
       "                     value\n",
       "value_time                \n",
       "2019-09-30 23:00:00   0.72\n",
       "2019-10-01 00:00:00   0.72\n",
       "2019-10-01 01:00:00   0.72\n",
       "2019-10-01 02:00:00   0.72\n",
       "2019-10-01 03:00:00   0.79"
      ]
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    "# Drop extra columns to be more efficient\n",
    "observations = observations[['value_time', 'value']]\n",
    "\n",
    "# Check for duplicate time series, keep first by default\n",
    "observations = observations.drop_duplicates(subset=['value_time'])\n",
    "\n",
    "# Resample to hourly, keep first measurement in each 1-hour bin\n",
    "observations = observations.set_index('value_time')\n",
    "observations = observations.resample('H').first().ffill()\n",
    "\n",
    "# Look at preprocessed data\n",
    "observations.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "alternative-activity",
   "metadata": {},
   "source": [
    "## 4. Process streamflow record\n",
    "Run event detection to generate a list of hydrological events with start and end times. This particular method of event detection is suitable for use on small streams dominated by rainfall-driven direct runoff events."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "judicial-memphis",
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   "outputs": [
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       "      <th>0</th>\n",
       "      <td>2019-10-13 10:00:00</td>\n",
       "      <td>2019-10-15 05:00:00</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-10-16 02:00:00</td>\n",
       "      <td>2019-10-18 05:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-10-19 20:00:00</td>\n",
       "      <td>2019-10-22 05:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-10-22 07:00:00</td>\n",
       "      <td>2019-10-23 20:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-10-27 01:00:00</td>\n",
       "      <td>2019-10-28 19:00:00</td>\n",
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      "text/plain": [
       "                start                 end\n",
       "0 2019-10-13 10:00:00 2019-10-15 05:00:00\n",
       "1 2019-10-16 02:00:00 2019-10-18 05:00:00\n",
       "2 2019-10-19 20:00:00 2019-10-22 05:00:00\n",
       "3 2019-10-22 07:00:00 2019-10-23 20:00:00\n",
       "4 2019-10-27 01:00:00 2019-10-28 19:00:00"
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   "source": [
    "# Detect events\n",
    "events = ev.list_events(\n",
    "    observations['value'],\n",
    "    halflife='6H', \n",
    "    window='7D',\n",
    "    minimum_event_duration='6H',\n",
    "    start_radius='6H'\n",
    ")\n",
    "\n",
    "# Look at events\n",
    "events.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "developed-ghost",
   "metadata": {},
   "source": [
    "## 5. Analyze events\n",
    "Here we compare the `events` DataFrame to the original `observations` DataFrame and get the maximum for every period defined by `start` and `end` columns in `events."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "waiting-democracy",
   "metadata": {},
   "outputs": [
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       "      <th>0</th>\n",
       "      <td>2019-10-13 10:00:00</td>\n",
       "      <td>2019-10-15 05:00:00</td>\n",
       "      <td>30.000000</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-10-16 02:00:00</td>\n",
       "      <td>2019-10-18 05:00:00</td>\n",
       "      <td>63.900002</td>\n",
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       "      <th>2</th>\n",
       "      <td>2019-10-19 20:00:00</td>\n",
       "      <td>2019-10-22 05:00:00</td>\n",
       "      <td>217.000000</td>\n",
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       "      <th>3</th>\n",
       "      <td>2019-10-22 07:00:00</td>\n",
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       "      <td>42.799999</td>\n",
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       "      <th>4</th>\n",
       "      <td>2019-10-27 01:00:00</td>\n",
       "      <td>2019-10-28 19:00:00</td>\n",
       "      <td>19.100000</td>\n",
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      "text/plain": [
       "                start                 end        peak\n",
       "0 2019-10-13 10:00:00 2019-10-15 05:00:00   30.000000\n",
       "1 2019-10-16 02:00:00 2019-10-18 05:00:00   63.900002\n",
       "2 2019-10-19 20:00:00 2019-10-22 05:00:00  217.000000\n",
       "3 2019-10-22 07:00:00 2019-10-23 20:00:00   42.799999\n",
       "4 2019-10-27 01:00:00 2019-10-28 19:00:00   19.100000"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Compute peak discharge for each event\n",
    "events['peak'] = events.apply(\n",
    "    lambda e: observations['value'].loc[e.start:e.end].max(), \n",
    "    axis=1\n",
    "    )\n",
    "\n",
    "# Peaks have been added to each event\n",
    "events.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aware-plate",
   "metadata": {},
   "source": [
    "## 6. Visualize the results\n",
    "Below we plot a histogram of peak flows for all events and the entire streamflow hydrograph for Little Hope Creek with points that indicate all the start time events detected."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "secondary-ordinary",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot a histogram of peak discharge values\n",
    "plt.hist(events['peak'], bins=20, density=True)\n",
    "plt.xlim(0.0,2000.0)\n",
    "plt.xlabel('Peak Discharge (cfs)')\n",
    "plt.ylabel('Relative Frequency')\n",
    "plt.title('Distribution of Peak Event Discharges for Little Hope Creek')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "crucial-livestock",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the hydrograph\n",
    "observations.plot(logy=True, legend=False)\n",
    "observations.loc[events['start'], 'value'].plot(\n",
    "    ax=plt.gca(), style='o'\n",
    ")\n",
    "plt.xlabel('Datetime (UTC)')\n",
    "plt.ylabel('Discharge (cfs)')\n",
    "plt.legend(['Streamflow','Event Start'])\n",
    "plt.title('Streamflow Hydrograph for Little Hope Creek with Detected Events')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}