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Comparison - SWI - Add Snow-17 outputs.
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Feedback from last round of reviews.
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@jomey
jomey committed Dec 17, 2022
1 parent b626f8c commit 2438a6b
Showing 1 changed file with 126 additions and 63 deletions.
189 changes: 126 additions & 63 deletions comparison/Snobal-SWI_static.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -11,6 +11,55 @@
"from common import *"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "2fdeb03f-e8c0-4262-a6c6-928385ebd1e2",
"metadata": {},
"outputs": [],
"source": [
"# Convert SNOBAL grid cell from meter to square feet\n",
"CELL_AREA = (50.0 * 3.28084)**2\n",
"# MM in one foot\n",
"MM_IN_FT = 304.8\n",
"# Convert to cubic feet\n",
"CELL_AREA_IN_MM = CELL_AREA / MM_IN_FT"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "79bf1112-48e2-445f-84eb-c527cbdfbada",
"metadata": {},
"outputs": [],
"source": [
"# Cubic feet to cubic meter\n",
"FT3_to_M3 = (MM_IN_FT/1000)**3"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "b2f86265-8c13-4b5f-8bb8-6e4bb26728f6",
"metadata": {},
"outputs": [],
"source": [
"wy2018 = dict(time=slice(\"2017-10-01\", \"2018-09-30\"))\n",
"wy2019 = dict(time=slice(\"2018-10-01\", \"2019-09-30\"))\n",
"wy2020 = dict(time=slice(\"2019-10-01\", \"2020-09-30\"))\n",
"wy2021 = dict(time=slice(\"2020-10-01\", \"2021-09-30\"))"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "657177d4-54d8-499e-b7c6-1f9213629f4c",
"metadata": {},
"outputs": [],
"source": [
"zones = cbrfc_zones()"
]
},
{
"cell_type": "markdown",
"id": "bbbf5165-787c-4078-a97d-e83b1cbe368a",
Expand Down Expand Up @@ -38,7 +87,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "cef98708-11c7-4bff-a71c-c8e680fc85a2",
"id": "69101631-83b0-426c-9a39-839566358aac",
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -57,41 +106,77 @@
" **PD_OPTIONS\n",
")\n",
"\n",
"data.Discharge = data.Discharge * 60 * 60 * 24"
"data.Discharge = data.Discharge * 60 * 60 * 24 * FT3_to_M3"
]
},
{
"cell_type": "markdown",
"id": "bb52d74d-463a-4813-be1d-5ead2cfb66f4",
"id": "903647ff-2b1a-476b-886f-b47fd3340a9e",
"metadata": {},
"source": [
"## SNOBAL"
"Area average from iSnobal vs CSV"
]
},
{
"cell_type": "markdown",
"id": "64426da2-be7a-44be-afc0-10f8a862be47",
"metadata": {},
"source": [
"## CBRFC"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a9039ec9-e757-42fa-a4db-98482fe6d46c",
"id": "6db00201-bdf5-4308-9e1f-16516e74c7dd",
"metadata": {},
"outputs": [],
"source": [
"client = start_cluster(5, 16)\n",
"client_ip_and_port(client)"
"PD_OPTIONS = dict(\n",
" comment='#',\n",
" parse_dates=True,\n",
" index_col=0,\n",
" names=['Date', 'SWE'],\n",
" header=0,\n",
" sep=',',\n",
" dtype={'Discharge': np.float64},\n",
")\n",
"cbrfc_HLF = pd.read_csv(\n",
" CBRFC_DIR / 'SWI/ALEC2HLF.RAIM.MA.csv', \n",
" **PD_OPTIONS\n",
")\n",
"cbrfc_HMF = pd.read_csv(\n",
" CBRFC_DIR / 'SWI/ALEC2HMF.RAIM.MA.csv', \n",
" **PD_OPTIONS\n",
")\n",
"cbrfc_HUF = pd.read_csv(\n",
" CBRFC_DIR / 'SWI/ALEC2HUF.RAIM.MA.csv', \n",
" **PD_OPTIONS\n",
")\n",
"cbrfc = cbrfc_HLF + cbrfc_HMF + cbrfc_HUF\n",
"cbrfc = cbrfc[\"2017-10-01\":\"2021-09-30\"]\n",
"cbrfc = (cbrfc.SWE * (INCH_TO_MM / 1000)) * (zones[zones != 0].size * 50**2)"
]
},
{
"cell_type": "markdown",
"id": "bb52d74d-463a-4813-be1d-5ead2cfb66f4",
"metadata": {
"tags": []
},
"source": [
"## SNOBAL"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "2fdeb03f-e8c0-4262-a6c6-928385ebd1e2",
"id": "a9039ec9-e757-42fa-a4db-98482fe6d46c",
"metadata": {},
"outputs": [],
"source": [
"# Convert SNOBAL grid cell from meter to square feet\n",
"CELL_AREA = (50.0 * 3.28084)**2\n",
"# MM in one foot\n",
"FT_IN_MM = 304.8\n",
"# Convert to area\n",
"CELL_AREA_IN_MM = CELL_AREA / FT_IN_MM"
"client = start_cluster(8, 24)\n",
"client_ip_and_port(client)"
]
},
{
Expand All @@ -106,7 +191,7 @@
" data_vars=['SWI'],\n",
" parallel=True,\n",
")\n",
"snobal_em.coords['mask'] = (('y', 'x'), cbrfc_zones())\n",
"snobal_em.coords['mask'] = (('y', 'x'), zones)\n",
"snobal_em['time'] = snobal_em.time + np.timedelta64(2,'h')"
]
},
Expand All @@ -118,7 +203,7 @@
"outputs": [],
"source": [
"swi = (\n",
" snobal_em.where(snobal_em.mask != 0).SWI * CELL_AREA_IN_MM\n",
" (snobal_em.where(snobal_em.mask != 0).SWI / 1000) * 50**2\n",
").sum(['x', 'y']).compute()"
]
},
Expand All @@ -132,22 +217,6 @@
"client.shutdown()"
]
},
{
"cell_type": "markdown",
"id": "e474c2ec-0647-4bac-aea6-1f8a7271841c",
"metadata": {},
"source": [
"### Calculate added/removed daily SWE "
]
},
{
"cell_type": "markdown",
"id": "c18a16bc-2735-48bb-becf-a1aba0fc2c08",
"metadata": {},
"source": [
"### SNOBAL "
]
},
{
"cell_type": "markdown",
"id": "2be3f669-3a91-4929-bfda-df2429596a65",
Expand All @@ -156,54 +225,48 @@
"### Moving 7-day average SNOBAL vs. USGS"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "de3cc2ee-b6e4-4adf-8c56-240476c73e3e",
"metadata": {},
"outputs": [],
"source": [
"x_axis_fmt = mdates.DateFormatter('%d-%b-%y')"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "911be6cc-0b01-463c-a63e-fb863f365174",
"metadata": {},
"outputs": [],
"source": [
"plt.figure(dpi=300, figsize=(9,2.5))\n",
"figure = plt.figure(dpi=300, figsize=(10,3))\n",
"ax = plt.gca()\n",
"\n",
"swi.rolling(time=7, center=True).mean().plot(ax=ax, label='iSnobal Runoff', color='peru', alpha=0.7, lw=1)\n",
"data.rolling(7, center=True).mean().Discharge.plot(ax=ax, label='USGS Discharge', color='cadetblue', alpha=0.7, lw=1)\n",
"swi.rolling(time=7, center=True).mean().plot(ax=ax, label='HRRR-iSnobal SWI', color='peru', alpha=0.8, lw=1)\n",
"cbrfc.rolling(28, center=True).mean().plot(ax=ax, label='SNOW-17 SWI', color='olivedrab', alpha=0.8, lw=1.2, ls=(0, (5, 1)))\n",
"data.rolling(7, center=True).mean().Discharge.plot(ax=ax, label='Stream Discharge', color='cadetblue', alpha=0.8, lw=1)\n",
"\n",
"locator = mdates.AutoDateLocator(maxticks=20)\n",
"\n",
"ax.xaxis.set_major_locator(locator)\n",
"ax.xaxis.set_minor_locator(mdates.MonthLocator())\n",
"\n",
"formatter = mdates.ConciseDateFormatter(locator)\n",
"ax.xaxis.set_major_formatter(formatter)\n",
"\n",
"ax.xaxis.set_major_formatter(x_axis_fmt)\n",
"ax.set_xlim(left=data.index.min(), right=data.index.max())\n",
"index = 0\n",
"for label in ax.get_xticklabels(which='major'):\n",
" label.set(rotation=0, horizontalalignment='center')\n",
" if index in [1, 5, 9, 13]:\n",
" label.set(fontstyle='italic', fontweight=600)\n",
" index += 1\n",
"\n",
"ax.set_xlim(left=data.index.min(), right=swi.time.max().values)\n",
"ax.set_ylim(bottom=-1000)\n",
"ax.ticklabel_format(axis='y', useMathText=True)\n",
"\n",
"plt.ylabel('7-Day Mean Output (mm)')\n",
"plt.legend();"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "b2f86265-8c13-4b5f-8bb8-6e4bb26728f6",
"metadata": {},
"outputs": [],
"source": [
"wy2018 = dict(time=slice(\"2017-10-01\", \"2018-09-30\"))\n",
"wy2019 = dict(time=slice(\"2018-10-01\", \"2019-09-30\"))\n",
"wy2020 = dict(time=slice(\"2019-10-01\", \"2020-09-30\"))\n",
"wy2021 = dict(time=slice(\"2020-10-01\", \"2021-09-30\"))"
"plt.xlabel('')\n",
"plt.ylabel(r'Mean Volume ($\\frac{m^3}{7 \\ days}$)')\n",
"plt.legend(loc='upper center', ncol=3, bbox_to_anchor=(0.55, 1.14), frameon=False);"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a25a860b-cde2-42bd-b673-6cbacdb07636",
"id": "b673175f-6cd7-4eee-8853-e2c9f2455ac1",
"metadata": {},
"outputs": [],
"source": []
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