{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Evapotranspiration - exercises\n", "\n", "- toc: true \n", "- badges: true\n", "- comments: false\n", "- categories: [jupyter]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will calculate the evapotranspiration using two methods: Thornthwaite and Penman.\n", "\n", "## Download data from the IMS\n", "\n", "Go to the Israel Meteorological Service website, and download the following data:\n", "1. [hourly data](https://ims.data.gov.il/he/ims/1)\n", " * on the first page, choose all options and press continue.\n", " * on the next page, choose the following date range: 01/01/2020 to 01/01/2021, then press continue.\n", " * Choose station Bet Dagan (בית דגן 2523), then select (בחר), then continue.\n", " * Choose option \"by station\" (לפי תחנות), then produce report.\n", " * Download report as csv, call it \"bet-dagan-3h.csv\".\n", "2. [daily data](https://ims.data.gov.il/he/ims/2)\n", " * on the first page, choose all options and press continue.\n", " * on the next page, choose the following date range: 01/01/2020 to 01/01/2021, then press continue.\n", " * Choose station Bet Dagan Meuyeshet (בית דגן מאוישת 2520), then select (בחר), then continue.\n", " * Choose option \"by station\" (לפי תחנות), then produce report.\n", " * Download report as csv, call it \"bet-dagan-day-pan.csv\".\n", "3. [radiation data](https://ims.data.gov.il/he/ims/6)\n", " * on the first page, choose all options, **then on the bottom right option \"radiation\" (קרינה), choose kJ/m2**, and then press continue.\n", " * on the next page, choose the following date range: 01/01/2020 to 01/01/2021, then press continue.\n", " * Choose station Bet Dagan Krina (בית דגן קרינה 2524), then select (בחר), then continue.\n", " * Choose option \"by station\" (לפי תחנות), then produce report.\n", " * Download report as csv, call it \"bet-dagan-radiation.csv\".\n", " \n", "## Import relevant packages " ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "#collapse-hide\n", "\n", "import matplotlib.pyplot as plt\n", "import matplotlib\n", "import numpy as np\n", "import pandas as pd\n", "from pandas.plotting import register_matplotlib_converters\n", "register_matplotlib_converters() # datetime converter for a matplotlib\n", "import seaborn as sns\n", "sns.set(style=\"ticks\", font_scale=1.5)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## import hourly data" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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station namestation numberDateLST timeTwet-bulb temperature (°C)dew_point_Trelative humidity (%)wind_speedwind direction (degrees)...pressure at sea level (hPa)ëîåú òððéí ëåììú(÷åã)ëîåú òððéí ðîåëéí(÷åã)âåáä áñéñ òððéí ðîåëéí(÷åã)ñåâ äòððéí äðîåëéí(÷åã)ñåâ äòððéí äáéðåðééí(÷åã)ñåâ äòððéí äâáåäéí(÷åã)îæâ àååéø ðåëçé(÷åã)îæâ àååéø ùçìó(÷åã)øàåú àô÷éú(÷åã)
timestamp
2020-01-01 02:00:00áéú ãâï ...252301-01-202002:007.97.26.4901.7117.0...1018.8NaNNaNNaNNaNNaNNaNNaNNaNNaN
2020-01-01 05:00:00áéú ãâï ...252301-01-202005:007.57.06.4931.2116.0...1018.1NaNNaNNaNNaNNaNNaNNaNNaNNaN
2020-01-01 08:00:00áéú ãâï ...252301-01-202008:008.68.38.0961.1107.0...1018.2NaNNaNNaNNaNNaNNaNNaNNaNNaN
2020-01-01 11:00:00áéú ãâï ...252301-01-202011:0015.913.110.6712.4196.0...1017.4NaNNaNNaNNaNNaNNaNNaNNaNNaN
2020-01-01 14:00:00áéú ãâï ...252301-01-202014:0018.114.010.4612.8264.0...1015.3NaNNaNNaNNaNNaNNaNNaNNaNNaN
..................................................................
2021-01-31 11:00:00áéú ãâï ...252331-01-202111:0019.013.78.9525.6235.0...1017.3NaNNaNNaNNaNNaNNaNNaNNaNNaN
2021-01-31 14:00:00áéú ãâï ...252331-01-202114:0019.214.711.0594.6252.0...1016.7NaNNaNNaNNaNNaNNaNNaNNaNNaN
2021-01-31 17:00:00áéú ãâï ...252331-01-202117:0018.214.812.2680.8203.0...1017.0NaNNaNNaNNaNNaNNaNNaNNaNNaN
2021-01-31 20:00:00áéú ãâï ...252331-01-202120:0013.112.311.7911.279.0...1018.2NaNNaNNaNNaNNaNNaNNaNNaNNaN
2021-01-31 23:00:00áéú ãâï ...252331-01-202123:0010.810.610.3971.7111.0...1018.9NaNNaNNaNNaNNaNNaNNaNNaNNaN
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3172 rows × 21 columns

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" ], "text/plain": [ " station name \\\n", "timestamp \n", "2020-01-01 02:00:00 áéú ãâï ... \n", "2020-01-01 05:00:00 áéú ãâï ... \n", "2020-01-01 08:00:00 áéú ãâï ... \n", "2020-01-01 11:00:00 áéú ãâï ... \n", "2020-01-01 14:00:00 áéú ãâï ... \n", "... ... \n", "2021-01-31 11:00:00 áéú ãâï ... \n", "2021-01-31 14:00:00 áéú ãâï ... \n", "2021-01-31 17:00:00 áéú ãâï ... \n", "2021-01-31 20:00:00 áéú ãâï ... \n", "2021-01-31 23:00:00 áéú ãâï ... \n", "\n", " station number Date LST time T \\\n", "timestamp \n", "2020-01-01 02:00:00 2523 01-01-2020 02:00 7.9 \n", "2020-01-01 05:00:00 2523 01-01-2020 05:00 7.5 \n", "2020-01-01 08:00:00 2523 01-01-2020 08:00 8.6 \n", "2020-01-01 11:00:00 2523 01-01-2020 11:00 15.9 \n", "2020-01-01 14:00:00 2523 01-01-2020 14:00 18.1 \n", "... ... ... ... ... \n", "2021-01-31 11:00:00 2523 31-01-2021 11:00 19.0 \n", "2021-01-31 14:00:00 2523 31-01-2021 14:00 19.2 \n", "2021-01-31 17:00:00 2523 31-01-2021 17:00 18.2 \n", "2021-01-31 20:00:00 2523 31-01-2021 20:00 13.1 \n", "2021-01-31 23:00:00 2523 31-01-2021 23:00 10.8 \n", "\n", " wet-bulb temperature (°C) dew_point_T \\\n", "timestamp \n", "2020-01-01 02:00:00 7.2 6.4 \n", "2020-01-01 05:00:00 7.0 6.4 \n", "2020-01-01 08:00:00 8.3 8.0 \n", "2020-01-01 11:00:00 13.1 10.6 \n", "2020-01-01 14:00:00 14.0 10.4 \n", "... ... ... \n", "2021-01-31 11:00:00 13.7 8.9 \n", "2021-01-31 14:00:00 14.7 11.0 \n", "2021-01-31 17:00:00 14.8 12.2 \n", "2021-01-31 20:00:00 12.3 11.7 \n", "2021-01-31 23:00:00 10.6 10.3 \n", "\n", " relative humidity (%) wind_speed \\\n", "timestamp \n", "2020-01-01 02:00:00 90 1.7 \n", "2020-01-01 05:00:00 93 1.2 \n", "2020-01-01 08:00:00 96 1.1 \n", "2020-01-01 11:00:00 71 2.4 \n", "2020-01-01 14:00:00 61 2.8 \n", "... ... ... \n", "2021-01-31 11:00:00 52 5.6 \n", "2021-01-31 14:00:00 59 4.6 \n", "2021-01-31 17:00:00 68 0.8 \n", "2021-01-31 20:00:00 91 1.2 \n", "2021-01-31 23:00:00 97 1.7 \n", "\n", " wind direction (degrees) ... \\\n", "timestamp ... \n", "2020-01-01 02:00:00 117.0 ... \n", "2020-01-01 05:00:00 116.0 ... \n", "2020-01-01 08:00:00 107.0 ... \n", "2020-01-01 11:00:00 196.0 ... \n", "2020-01-01 14:00:00 264.0 ... \n", "... ... ... \n", "2021-01-31 11:00:00 235.0 ... \n", "2021-01-31 14:00:00 252.0 ... \n", "2021-01-31 17:00:00 203.0 ... \n", "2021-01-31 20:00:00 79.0 ... \n", "2021-01-31 23:00:00 111.0 ... \n", "\n", " pressure at sea level (hPa) ëîåú òððéí ëåììú(÷åã) \\\n", "timestamp \n", "2020-01-01 02:00:00 1018.8 NaN \n", "2020-01-01 05:00:00 1018.1 NaN \n", "2020-01-01 08:00:00 1018.2 NaN \n", "2020-01-01 11:00:00 1017.4 NaN \n", "2020-01-01 14:00:00 1015.3 NaN \n", "... ... ... \n", "2021-01-31 11:00:00 1017.3 NaN \n", "2021-01-31 14:00:00 1016.7 NaN \n", "2021-01-31 17:00:00 1017.0 NaN \n", "2021-01-31 20:00:00 1018.2 NaN \n", "2021-01-31 23:00:00 1018.9 NaN \n", "\n", " ëîåú òððéí ðîåëéí(÷åã) âåáä áñéñ òððéí ðîåëéí(÷åã) \\\n", "timestamp \n", "2020-01-01 02:00:00 NaN NaN \n", "2020-01-01 05:00:00 NaN NaN \n", "2020-01-01 08:00:00 NaN NaN \n", "2020-01-01 11:00:00 NaN NaN \n", "2020-01-01 14:00:00 NaN NaN \n", "... ... ... \n", "2021-01-31 11:00:00 NaN NaN \n", "2021-01-31 14:00:00 NaN NaN \n", "2021-01-31 17:00:00 NaN NaN \n", "2021-01-31 20:00:00 NaN NaN \n", "2021-01-31 23:00:00 NaN NaN \n", "\n", " ñåâ äòððéí äðîåëéí(÷åã) ñåâ äòððéí äáéðåðééí(÷åã) \\\n", "timestamp \n", "2020-01-01 02:00:00 NaN NaN \n", "2020-01-01 05:00:00 NaN NaN \n", "2020-01-01 08:00:00 NaN NaN \n", "2020-01-01 11:00:00 NaN NaN \n", "2020-01-01 14:00:00 NaN NaN \n", "... ... ... \n", "2021-01-31 11:00:00 NaN NaN \n", "2021-01-31 14:00:00 NaN NaN \n", "2021-01-31 17:00:00 NaN NaN \n", "2021-01-31 20:00:00 NaN NaN \n", "2021-01-31 23:00:00 NaN NaN \n", "\n", " ñåâ äòððéí äâáåäéí(÷åã) îæâ àååéø ðåëçé(÷åã) \\\n", "timestamp \n", "2020-01-01 02:00:00 NaN NaN \n", "2020-01-01 05:00:00 NaN NaN \n", "2020-01-01 08:00:00 NaN NaN \n", "2020-01-01 11:00:00 NaN NaN \n", "2020-01-01 14:00:00 NaN NaN \n", "... ... ... \n", "2021-01-31 11:00:00 NaN NaN \n", "2021-01-31 14:00:00 NaN NaN \n", "2021-01-31 17:00:00 NaN NaN \n", "2021-01-31 20:00:00 NaN NaN \n", "2021-01-31 23:00:00 NaN NaN \n", "\n", " îæâ àååéø ùçìó(÷åã) øàåú àô÷éú(÷åã) \n", "timestamp \n", "2020-01-01 02:00:00 NaN NaN \n", "2020-01-01 05:00:00 NaN NaN \n", "2020-01-01 08:00:00 NaN NaN \n", "2020-01-01 11:00:00 NaN NaN \n", "2020-01-01 14:00:00 NaN NaN \n", "... ... ... \n", "2021-01-31 11:00:00 NaN NaN \n", "2021-01-31 14:00:00 NaN NaN \n", "2021-01-31 17:00:00 NaN NaN \n", "2021-01-31 20:00:00 NaN NaN \n", "2021-01-31 23:00:00 NaN NaN \n", "\n", "[3172 rows x 21 columns]" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#collapse-hide\n", "\n", "df = pd.read_csv('bet-dagan-3h.csv', encoding = 'unicode_escape', na_values=[\"-\"])\n", "# find out what hebrew gibberish means: http://www.pixiesoft.com/flip/\n", "name_conversion_dictionary = {\"ùí úçðä\": \"station name\",\n", " \"îñôø úçðä\": \"station number\",\n", " \"úàøéê\": \"Date\",\n", " \"ùòä-LST\": \"LST time\",\n", " \"èîôøèåøä(C°)\": \"T\",\n", " \"èîôøèåøä ìçä(C°)\": \"wet-bulb temperature (°C)\",\n", " \"èîôøèåøú ð÷åãú äèì(C°)\": \"dew_point_T\",\n", " \"ìçåú éçñéú(%)\": \"relative humidity (%)\",\n", " \"îäéøåú äøåç(m/s)\": \"wind_speed\",\n", " \"ëéååï äøåç(îòìåú)\": \"wind direction (degrees)\",\n", " \"ìçõ áâåáä äúçðä(hPa)\": \"Pressure\",\n", " \"ìçõ áâåáä ôðé äéí(hPa)\": \"pressure at sea level (hPa)\",\n", " \"\"\"äúàãåú éåîéú îâéâéú ñåâ à'(î\"î)\"\"\": \"pan evaporation (mm)\",\n", " \"ñåâ ÷øéðä()\": \"radiation type\",\n", " }\n", "# units\n", "# T = temperature (°C)\n", "# dew_point_T = dew point temperature (°C)\n", "# wind_speed = wind speed (m/s)\n", "# Pressure = pressure at station height (hPa = 0.1 kPa)\n", "\n", "df = df.rename(columns=name_conversion_dictionary)\n", "df['timestamp'] = df['Date'] + ' ' + df['LST time']\n", "df['timestamp'] = pd.to_datetime(df['timestamp'], dayfirst=True)\n", "df = df.set_index('timestamp')\n", "df" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## import daily data with pan evaporation" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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station namestation numberèîôøèåøú î÷ñéîåí(C°)èîôøèåøú îéðéîåí(C°)èîôøèåøú îéðéîåí ìéã ä÷ø÷ò(C°)îùê æäéøú ùîù(ã÷åú)pan evaporation (mm)÷åã äúàãåú éåîéú()
Date
2020-01-01áéú ãâï îàåéùú ...2520NaNNaNNaNNaN0.80.0
2020-01-02áéú ãâï îàåéùú ...2520NaNNaNNaNNaNNaNNaN
2020-01-03áéú ãâï îàåéùú ...2520NaNNaNNaNNaNNaNNaN
2020-01-04áéú ãâï îàåéùú ...2520NaNNaNNaNNaNNaNNaN
2020-01-05áéú ãâï îàåéùú ...2520NaNNaNNaNNaN2.40.0
...........................
2021-01-27áéú ãâï îàåéùú ...2520NaNNaNNaNNaN2.50.0
2021-01-28áéú ãâï îàåéùú ...2520NaNNaNNaNNaN1.20.0
2021-01-29áéú ãâï îàåéùú ...2520NaNNaNNaNNaNNaNNaN
2021-01-30áéú ãâï îàåéùú ...2520NaNNaNNaNNaNNaNNaN
2021-01-31áéú ãâï îàåéùú ...2520NaNNaNNaNNaN2.60.0
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397 rows × 8 columns

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" ], "text/plain": [ " station name station number \\\n", "Date \n", "2020-01-01 áéú ãâï îàåéùú ... 2520 \n", "2020-01-02 áéú ãâï îàåéùú ... 2520 \n", "2020-01-03 áéú ãâï îàåéùú ... 2520 \n", "2020-01-04 áéú ãâï îàåéùú ... 2520 \n", "2020-01-05 áéú ãâï îàåéùú ... 2520 \n", "... ... ... \n", "2021-01-27 áéú ãâï îàåéùú ... 2520 \n", "2021-01-28 áéú ãâï îàåéùú ... 2520 \n", "2021-01-29 áéú ãâï îàåéùú ... 2520 \n", "2021-01-30 áéú ãâï îàåéùú ... 2520 \n", "2021-01-31 áéú ãâï îàåéùú ... 2520 \n", "\n", " èîôøèåøú î÷ñéîåí(C°) èîôøèåøú îéðéîåí(C°) \\\n", "Date \n", "2020-01-01 NaN NaN \n", "2020-01-02 NaN NaN \n", "2020-01-03 NaN NaN \n", "2020-01-04 NaN NaN \n", "2020-01-05 NaN NaN \n", "... ... ... \n", "2021-01-27 NaN NaN \n", "2021-01-28 NaN NaN \n", "2021-01-29 NaN NaN \n", "2021-01-30 NaN NaN \n", "2021-01-31 NaN NaN \n", "\n", " èîôøèåøú îéðéîåí ìéã ä÷ø÷ò(C°) îùê æäéøú ùîù(ã÷åú) \\\n", "Date \n", "2020-01-01 NaN NaN \n", "2020-01-02 NaN NaN \n", "2020-01-03 NaN NaN \n", "2020-01-04 NaN NaN \n", "2020-01-05 NaN NaN \n", "... ... ... \n", "2021-01-27 NaN NaN \n", "2021-01-28 NaN NaN \n", "2021-01-29 NaN NaN \n", "2021-01-30 NaN NaN \n", "2021-01-31 NaN NaN \n", "\n", " pan evaporation (mm) ÷åã äúàãåú éåîéú() \n", "Date \n", "2020-01-01 0.8 0.0 \n", "2020-01-02 NaN NaN \n", "2020-01-03 NaN NaN \n", "2020-01-04 NaN NaN \n", "2020-01-05 2.4 0.0 \n", "... ... ... \n", "2021-01-27 2.5 0.0 \n", "2021-01-28 1.2 0.0 \n", "2021-01-29 NaN NaN \n", "2021-01-30 NaN NaN \n", "2021-01-31 2.6 0.0 \n", "\n", "[397 rows x 8 columns]" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#collapse-hide\n", "\n", "df2 = pd.read_csv('bet-dagan-day-pan.csv', encoding = 'unicode_escape', na_values=[\"-\"])\n", "df2 = df2.rename(columns=name_conversion_dictionary)\n", "df2['Date'] = pd.to_datetime(df2['Date'], dayfirst=True)\n", "df2 = df2.set_index('Date')\n", "df2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## import daily data with radiation" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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daily_radiation_MJ_per_m2_per_day
Date
2020-01-0110.0296
2020-01-024.3128
2020-01-0311.6748
2020-01-041.6452
2020-01-056.8544
......
2021-01-2712.2652
2021-01-287.1640
2021-01-297.2936
2021-01-309.3276
2021-01-3113.5468
\n", "

396 rows × 1 columns

\n", "
" ], "text/plain": [ " daily_radiation_MJ_per_m2_per_day\n", "Date \n", "2020-01-01 10.0296\n", "2020-01-02 4.3128\n", "2020-01-03 11.6748\n", "2020-01-04 1.6452\n", "2020-01-05 6.8544\n", "... ...\n", "2021-01-27 12.2652\n", "2021-01-28 7.1640\n", "2021-01-29 7.2936\n", "2021-01-30 9.3276\n", "2021-01-31 13.5468\n", "\n", "[396 rows x 1 columns]" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#collapse-hide\n", "\n", "df3 = pd.read_csv('bet-dagan-radiation.csv', encoding = 'unicode_escape', na_values=[\"-\"])\n", "df3 = df3.rename(columns=name_conversion_dictionary)\n", "df3['Date'] = pd.to_datetime(df3['Date'], dayfirst=True)\n", "df3 = df3.set_index('Date')\n", "df3 = df3.replace({\"éùéøä\": \"direct\",\n", " \"îôåæøú\": \"diffuse\",\n", " \"âìåáàìéú\": \"global\"})\n", "df3['daily_radiation_MJ_per_m2_per_day'] = df3.iloc[:, 3:].sum(axis=1)/1000\n", "df_radiation = df3.loc[df3[\"radiation type\"] == \"global\", \"daily_radiation_MJ_per_m2_per_day\"].to_frame()\n", "df_radiation" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Part 1: Thornthwaite estimation\n", "\n", "$$\n", "E = 16\\left[ \\frac{10\\,T^\\text{monthly mean}}{I} \\right]^a,\n", "$$\n", "\n", "where\n", "\n", "$$\n", "I = \\sum_{i=1}^{12} \\left[ \\frac{T_i^\\text{monthly mean}}{5} \\right]^{1.514},\n", "$$\n", "\n", "and\n", "\n", "$$\n", "\\begin{align}\n", "a &= 6.75\\times 10^{-7}I^3 \\\\\n", " &- 7.71\\times 10^{-5}I^2 \\nonumber\\\\\n", " &+ 1.792\\times 10^{-2}I \\nonumber\\\\\n", " &+ 0.49239 \\nonumber\n", "\\end{align}\n", "$$\n", "\n", " - $E$ is the monthly potential ET (mm)\n", " - $T_\\text{monthly mean}$ is the mean monthly temperature in °C\n", " - $I$ is a heat index\n", " - $a$ is a location-dependent coefficient\n", "\n", "From df, make a new dataframe, df_th, that stores monthly temperatures means. Use `resample` function." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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T
timestamp
2020-01-1512.484274
2020-02-1514.046983
2020-03-1516.439113
2020-04-1518.512500
2020-05-1523.166532
2020-06-1524.600000
2020-07-1527.353226
2020-08-1528.090323
2020-09-1528.462500
2020-10-1525.120161
2020-11-1519.308475
2020-12-1515.916129
2021-01-1514.123790
\n", "
" ], "text/plain": [ " T\n", "timestamp \n", "2020-01-15 12.484274\n", "2020-02-15 14.046983\n", "2020-03-15 16.439113\n", "2020-04-15 18.512500\n", "2020-05-15 23.166532\n", "2020-06-15 24.600000\n", "2020-07-15 27.353226\n", "2020-08-15 28.090323\n", "2020-09-15 28.462500\n", "2020-10-15 25.120161\n", "2020-11-15 19.308475\n", "2020-12-15 15.916129\n", "2021-01-15 14.123790" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#collapse-hide\n", "\n", "# monthly data\n", "df_th = (df['T'].resample('MS') # MS assigns mean to first day in the month\n", " .mean()\n", " .to_frame()\n", " )\n", "# we now add 14 days to the index, so that all monthly data is in the middle of the month\n", "# not really necessary, makes plot look better\n", "df_th.index = df_th.index + pd.DateOffset(days=14)\n", "df_th" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Calculate $I$, then $a$, and finally $E_p$. Add $E_p$ as a new column in df_th." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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TEp
timestamp
2020-01-1512.48427420.163427
2020-02-1514.04698327.179636
2020-03-1516.43911340.472053
2020-04-1518.51250054.671821
2020-05-1523.16653296.461219
2020-06-1524.600000112.296873
2020-07-1527.353226146.898516
2020-08-1528.090323157.128632
2020-09-1528.462500162.453109
2020-10-1525.120161118.406386
2020-11-1519.30847560.820862
2020-12-1515.91612937.291178
2021-01-1514.12379027.557481
\n", "
" ], "text/plain": [ " T Ep\n", "timestamp \n", "2020-01-15 12.484274 20.163427\n", "2020-02-15 14.046983 27.179636\n", "2020-03-15 16.439113 40.472053\n", "2020-04-15 18.512500 54.671821\n", "2020-05-15 23.166532 96.461219\n", "2020-06-15 24.600000 112.296873\n", "2020-07-15 27.353226 146.898516\n", "2020-08-15 28.090323 157.128632\n", "2020-09-15 28.462500 162.453109\n", "2020-10-15 25.120161 118.406386\n", "2020-11-15 19.308475 60.820862\n", "2020-12-15 15.916129 37.291178\n", "2021-01-15 14.123790 27.557481" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#collapse-hide\n", "\n", "# Preparing \"I\" for the Thornthwaite equation\n", "I = np.sum( (df_th['T']/5)**(1.514) )\n", "\n", "# Preparing \"a\" for the Thornthwaite equation\n", "a = (+6.75e-7 * I**3 \n", " -7.71e-5 * I**2\n", " +1.792e-2 * I\n", " + 0.49239)\n", "\n", "# The final Thornthwaite model for monthly potential ET (mm)\n", "df_th['Ep'] = 16*((10*df_th['T']/I)**a)\n", "df_th" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Plot the Thornthwaite ET that you calculated." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#collapse-hide\n", "\n", "fig, ax = plt.subplots(1, figsize=(10,7))\n", "ax.plot(df_th['Ep'])\n", "ax.set(xlabel=\"date\",\n", " ylabel=r\"$E_p$ (mm)\",\n", " title=\"Thornthwaite potential evapotranspiration\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Part 2: Penman\n", "\n", "The Penman model is almost entirely a theory based formula for predicting evaporative flux. It can run on a much finer timescale, and requires a much wider variety of data than most models. In addition to temperature, the Penman functions on measurements of radiation, wind speed, elevation above sea level, vapour-pressure deficit, and heat flux density to the ground.\n", "\n", "$$\n", "E = \\frac{1}{\\lambda}\\left[ \\frac{\\Delta}{\\Delta+\\gamma}Q_{ne}+ \\frac{\\gamma}{\\Delta+\\gamma}E_A \\right],\n", "$$\n", "\n", "where $Q_n$ is the available energy flux density\n", "\n", "$$\n", "Q_n = R_n - G,\n", "$$\n", "\n", "and $E_A$ is the drying power of the air\n", "\n", "$$\n", "E_A = 6.43\\cdot f(u)\\cdot\\text{VPD}.\n", "$$\n", "\n", "\n", "$$\n", "\\gamma = \\frac{c_p\\, P}{\\lambda\\cdot MW_\\text{ratio}}\n", "$$\n", " \n", "$$\n", "P = 101.3-0.01055 H\n", "$$\n", "\n", "$$\n", "\\lambda = 2.501 - 2.361\\times 10^{-3}\\,T\n", "$$\n", "\n", "* $MW_\\text{ratio}=0.622$: ratio molecular weight of water vapor/dry air\n", "* $P$: atmospheric pressure (kPa). Can be either measured or inferred from station height above sea level (m).\n", "* $\\lambda$: latent heat of water vaporization (MJ kg$^{-1}$)\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "$$\n", "R_n = (1-\\alpha)R_s\\!\\! \\downarrow -R_b \\!\\! \\uparrow,\n", "$$\n", "\n", "where $\\alpha$ (dimensionless) is the albedo.\n", "The net outgoing thermal radiation $R_b$ is given by\n", "\n", "$$\n", "R_b = \\left( a\\frac{R_s}{R_{so}+b} \\right)R_{bo},\n", "$$\n", "\n", "where $R_{so}$ is the solar radiation on a cloudless day, and it depends on latitude and day of the year.\n", "$R_{bo}$ is given by\n", "\n", "$$\n", "R_{bo} = \\epsilon\\, \\sigma\\, T^4_{Kelvin},\n", "$$\n", "\n", "where $\\sigma=4.903\\times 10^{-9}$ MJ m$^{-2}$ d$^{-1}$ K$^{-4}$, and $\\epsilon$ is net net emissivity:\n", "\n", "$$\n", "\\epsilon=-0.02+0.261 \\exp\\left(-7.77\\times10^{-4}T_{Celcius}^2\\right).\n", "$$\n", "\n", "The parameters $a$ and $b$ are determined for the climate of the area:\n", "* $a=1.0$, $b=0.0$ for humid areas,\n", "* $a=1.2$, $b=-0.2$ for arid areas,\n", "* $a=1.1$, $b=-0.1$ for semihumid areas.\n", "\n", "$$\n", "G = 4.2\\frac{T_{i+1}-T_{i-1}}{\\Delta t}\n", "$$\n", "\n", "$$\n", "\\text{VPD} = e_s - e_d.\n", "$$\n", "\n", "For temperatures ranging from 0 to 50 °C, the saturation vapor pressure can be calculated with\n", "\n", "$$\n", "e_s = \\exp \\left[ \\frac{16.78\\, T -116.9}{T+237.3} \\right],\n", "$$\n", "\n", "and the actual vapor pressure is given by\n", "\n", "$$\n", "e_d = e_s \\frac{RH}{100},\n", "$$\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "$$\n", "\\Delta = \\frac{\\text{d} e_s}{\\text{d}T} = e_s(T)\\cdot \\frac{4098.79}{(T+237.3)^2}.\n", "$$\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "$$\n", "f(u) = 0.26(1.0 + 0.54\\, u_2)\n", "$$\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "The various components of the equations above are:\n", "\n", " $$\n", " \\Delta = 0.200 \\cdot (0.00738\\,T + 0.8072)^7 - 0.000116\n", " $$\n", "\n", " $$\n", " \\gamma = \\frac{c_p\\, P}{0.622 \\lambda}\n", " $$\n", " \n", " $$\n", " P = 101.3-0.01055 H\n", " $$\n", "\n", " $$\n", " \\lambda = 2.501 - 2.361\\times 10^{-3}\\,T\n", " $$\n", "\n", " $$\n", " f_e(u) = 1.0 + 0.53\\, u_2\n", " $$\n", " \n", " $$\n", " G = 4.2\\frac{T_{i+1}-T_{i-1}}{\\Delta t}\n", " $$\n", " \n", " $$\n", " e_s = \\exp \\left[ \\frac{16.78\\, T -116.9}{T+237.3} \\right]\n", " $$\n", " \n", " $$\n", " e_d = e_s \\frac{RH}{100}\n", " $$\n", "where $\\Delta t$ is the time *in days* between midpoints of time periods $i+1$ and $i−1$, and $T$ is the air temperature (°C).\n", "\n", "\n", " - $\\Delta$: slope of the saturation water vapor pressure curve (kPa °C$^{-1}$)\n", " - $\\gamma$: psychrometric constant (kPA °C$^{-1}$)\n", " - $c_p=0.001013$: specific heat of water at constant pressure (MJ kg$^{-1}$ °C$^{-1}$)\n", " - $P$: atmospheric pressure (kPa)\n", " - $H$: elevation above sea level (m)\n", " - $\\lambda$: latent heat of vaporization (MJ kg$^{-1}$)\n", " - $R_n$: net radiation (MJ m$^{-2} d^{-1}$)\n", " - $G$: heat flux density to the ground (MJ m$^{-2} d^{-1}$)\n", " - $u_{2}$: wind speed measured 2 m above ground (m s$^{-1}$)\n", " - $e_{s} - e_{d}$: vapor pressure deficit (kPa) \n", " - $e_{s}$: saturation vapor pressure (kPa) \n", " - $e_{d}$: actual vapor pressure (kPa) " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Calculate daily means for the following columns: temperature `T`, wind speed `wind_speed`, atmospheric pressure `Pressure`, and relative humidity `relative humidity (%)`. Remember that pressure data was given in hectopascal, 1 hPa = 0.1 kPa. Store all the calculated values in a new dataframe, called `df_pen`." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Tdew_pointuPRH
timestamp
2020-01-0112.36259.06251.5250101.3087581.500
2020-01-0211.97509.82501.9250101.2012587.000
2020-01-0313.05004.97505.1750101.3712558.500
2020-01-0410.86256.68755.5625101.1550078.375
2020-01-0512.93759.21254.5625101.2362579.125
..................
2021-01-2713.81258.23751.8875100.8375072.375
2021-01-2814.400010.22503.5250101.1275076.750
2021-01-2912.35007.91255.0250101.2212575.250
2021-01-3012.96257.65004.4250101.4950071.375
2021-01-3115.06258.31253.7500101.3250066.000
\n", "

397 rows × 5 columns

\n", "
" ], "text/plain": [ " T dew_point u P RH\n", "timestamp \n", "2020-01-01 12.3625 9.0625 1.5250 101.30875 81.500\n", "2020-01-02 11.9750 9.8250 1.9250 101.20125 87.000\n", "2020-01-03 13.0500 4.9750 5.1750 101.37125 58.500\n", "2020-01-04 10.8625 6.6875 5.5625 101.15500 78.375\n", "2020-01-05 12.9375 9.2125 4.5625 101.23625 79.125\n", "... ... ... ... ... ...\n", "2021-01-27 13.8125 8.2375 1.8875 100.83750 72.375\n", "2021-01-28 14.4000 10.2250 3.5250 101.12750 76.750\n", "2021-01-29 12.3500 7.9125 5.0250 101.22125 75.250\n", "2021-01-30 12.9625 7.6500 4.4250 101.49500 71.375\n", "2021-01-31 15.0625 8.3125 3.7500 101.32500 66.000\n", "\n", "[397 rows x 5 columns]" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#collapse-hide\n", "\n", "# Resampling hourly data over same day and taking mean, to obtain daily averages\n", "df_pen = (df['T'].resample('D')\n", " .mean()\n", " .to_frame()\n", " )\n", "df_pen['dew_point'] = (df['dew_point_T'].resample('D')\n", " .mean()\n", " )\n", "df_pen['u'] = (df['wind_speed'].resample('D')\n", " .mean()\n", " )\n", "df_pen['P'] = (df['Pressure'].resample('D')\n", " .mean()\n", " )/10\n", "df_pen['RH'] = (df['relative humidity (%)'].resample('D')\n", " .mean()\n", " )\n", "df_pen" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "With average $T$ for every day of the year, we can now calculate daily latent heat of vaporization $\\lambda$, the slope of the saturation-vapor pressure-temperature curve $\\Delta$, and the heat flux density to the ground $G$. Add each of these to dataframe `df_pen`. \n", "\n", "Calculate also the wind function using the data for wind speed, and add this to `df_pen`." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Tdew_pointuPRHlambdaDeltaGgammaf_wind
timestamp
2020-01-0112.36259.06251.5250101.3087581.5002.4718120.094385-1.627500.0667501.808250
2020-01-0211.97509.82501.9250101.2012587.0002.4727270.0923001.443750.0666542.020250
2020-01-0313.05004.97505.1750101.3712558.5002.4701890.098185-2.336250.0668353.742750
2020-01-0410.86256.68755.5625101.1550078.3752.4753540.086530-0.236250.0665533.948125
2020-01-0512.93759.21254.5625101.2362579.1252.4704550.0975544.252500.0667393.418125
.................................
2021-01-2713.81258.23751.8875100.8375072.3752.4683890.1025514.777500.0665322.000375
2021-01-2814.400010.22503.5250101.1275076.7502.4670020.106028-3.071250.0667602.868250
2021-01-2912.35007.91255.0250101.2212575.2502.4718420.094317-3.018750.0666913.663250
2021-01-3012.96257.65004.4250101.4950071.3752.4703960.0976945.696250.0669113.345250
2021-01-3115.06258.31253.7500101.3250066.0002.4654370.1100708.820000.0669332.987500
\n", "

397 rows × 10 columns

\n", "
" ], "text/plain": [ " T dew_point u P RH lambda Delta \\\n", "timestamp \n", "2020-01-01 12.3625 9.0625 1.5250 101.30875 81.500 2.471812 0.094385 \n", "2020-01-02 11.9750 9.8250 1.9250 101.20125 87.000 2.472727 0.092300 \n", "2020-01-03 13.0500 4.9750 5.1750 101.37125 58.500 2.470189 0.098185 \n", "2020-01-04 10.8625 6.6875 5.5625 101.15500 78.375 2.475354 0.086530 \n", "2020-01-05 12.9375 9.2125 4.5625 101.23625 79.125 2.470455 0.097554 \n", "... ... ... ... ... ... ... ... \n", "2021-01-27 13.8125 8.2375 1.8875 100.83750 72.375 2.468389 0.102551 \n", "2021-01-28 14.4000 10.2250 3.5250 101.12750 76.750 2.467002 0.106028 \n", "2021-01-29 12.3500 7.9125 5.0250 101.22125 75.250 2.471842 0.094317 \n", "2021-01-30 12.9625 7.6500 4.4250 101.49500 71.375 2.470396 0.097694 \n", "2021-01-31 15.0625 8.3125 3.7500 101.32500 66.000 2.465437 0.110070 \n", "\n", " G gamma f_wind \n", "timestamp \n", "2020-01-01 -1.62750 0.066750 1.808250 \n", "2020-01-02 1.44375 0.066654 2.020250 \n", "2020-01-03 -2.33625 0.066835 3.742750 \n", "2020-01-04 -0.23625 0.066553 3.948125 \n", "2020-01-05 4.25250 0.066739 3.418125 \n", "... ... ... ... \n", "2021-01-27 4.77750 0.066532 2.000375 \n", "2021-01-28 -3.07125 0.066760 2.868250 \n", "2021-01-29 -3.01875 0.066691 3.663250 \n", "2021-01-30 5.69625 0.066911 3.345250 \n", "2021-01-31 8.82000 0.066933 2.987500 \n", "\n", "[397 rows x 10 columns]" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#collapse-hide\n", "\n", "def lambda_latent_heat(T):\n", " \"\"\"daily latent heat of vaporization (MJ/kg)\"\"\"\n", " return 2.501 - 2.361e-3*T\n", "\n", "def Delta(T):\n", " \"\"\"slope of saturation-vapor curve (kPa/°C)\"\"\"\n", " return 0.2000*(0.00738*T + 0.8072)**7 - 0.000116\n", "\n", "def G(T):\n", " \"\"\"heat flux density to the ground, G (MJ/m2/d)\"\"\"\n", " return 4.2*np.gradient(T.values)\n", "\n", "cp = 0.001013 # (MJ kg−1 °C−1) \n", "df_pen['lambda'] = lambda_latent_heat(df_pen['T'])\n", "df_pen['Delta'] = Delta(df_pen['T'])\n", "df_pen['G'] = G(df_pen['T'])\n", "df_pen['gamma'] = (cp*df_pen['P'])/(0.622*df_pen['lambda'])\n", "df_pen['f_wind'] = 1.0 + 0.53 * df_pen['u']\n", "df_pen" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It's time to calculate net radiation $R_n$. The monthly mean solar radiation $R_{so}$ for latitude 30 degrees is \n", "`[17.46, 21.65, 25.96, 29.85, 32.11, 33.20, 32.66, 30.44, 26.67, 22.48, 18.30, 16.04]` (MJ m$^{-2}$ d$^{-1}$) \n", "(Israel's latitude is ~ 31 degrees).\n", "\n", "* Add a new column `Rso_monthly` to `df_pen`, where each day has the appropriate $R_{so}$ given by the data above. \n", "* Add a new columns `Rs` with the global radiation data imported in the 3rd file." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, '$R_{so}$ (MJ m$^{-2} d^{-1}$)')" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#collapse-hide\n", "\n", "# Rso: mean solar radiation from a cloudless sky (based on latitude)\n", "# MJ/m2/d\n", "Rso_monthly = np.array([17.46, 21.65, 25.96, 29.85,\n", " 32.11, 33.20, 32.66, 30.44,\n", " 26.67, 22.48, 18.30, 16.04])\n", " \n", "# create empty columns\n", "df_pen[\"Rso_monthly\"] = \"\"\n", "\n", "# every day in the month will have the same values for Rso\n", "for i in range(12):\n", " df_pen.loc[df_pen.index.month==(i+1), \"Rso_monthly\"] = Rso_monthly[i]\n", "\n", "df_pen[\"Rs\"] = df_radiation[\"daily_radiation_MJ_per_m2_per_day\"]\n", "\n", "fig, ax = plt.subplots(1, figsize=(10,7))\n", "ax.plot(df_pen['Rso_monthly'])\n", "plt.gcf().autofmt_xdate()\n", "ax.set_ylabel(r\"$R_{so}$ (MJ m$^{-2} d^{-1}$)\")" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, '$R_{so}$ (MJ m$^{-2} d^{-1}$)')" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#collapse-hide\n", "\n", "middle = pd.date_range(start='1/1/2020', periods=13, freq='MS') + pd.DateOffset(days=14)\n", "new = df_pen.loc[middle, 'Rso_monthly'].astype('float')\n", "new\n", "df_i = (pd.DataFrame(data=new, index=new.index) #create the dataframe\n", " .resample(\"D\") #resample daily\n", " .interpolate(method='time') #interpolate by time\n", " )\n", "\n", "fig, ax = plt.subplots(1, figsize=(10,7))\n", "ax.plot(df_i, 'o')\n", "ax.plot(df_pen['Rso_monthly'])\n", "plt.gcf().autofmt_xdate()\n", "ax.set_title(\"time interpolation\")\n", "ax.set_ylabel(r\"$R_{so}$ (MJ m$^{-2} d^{-1}$)\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "from: Ward & Trimble, \"Environmental Hydrology\", 2nd Edition, page 99.\n", "\n", "* Calculate \n", " $$\n", " R_{bo} = \\epsilon\\, \\sigma\\, T^4_{Kelvin},\n", " $$\n", " where\n", " $$\n", " \\epsilon=-0.02+0.261 \\exp\\left(-7.77\\times10^{-4}T_{Celcius}^2\\right),\n", " $$ \n", " $$\n", " \\sigma=4.903\\times 10^{-9} \\text{ MJ m$^{-2}$ d$^{-1}$ K$^{-4}$},\n", " $$\n", " and\n", " $$\n", " T_{Kelvin}=T_{Celcius}+273.15\n", " $$\n", "* Calculate \n", " $$\n", " R_b = \\left( a\\frac{R_s}{R_{so}+b} \\right)R_{bo},\n", " $$\n", " where \n", " - for humid areas, $a=1.0$ and $b=0$, \n", " - for arid areas, $a=1.2$ and $b=-0.2$, \n", " - for semihumid areas, $a=1.1$ and $b=-0.1$\n", "* Finally, calculate \n", " $$\n", " R_n = (1-\\alpha)R_s\\!\\! \\downarrow -R_b \\!\\! \\uparrow,\n", " $$\n", " where \n", " - $\\alpha= 0.23$ for most green crops with a full cover\n", " - $\\alpha= 0.04$ for fresh asphalt\n", " - $\\alpha= 0.12$ for worn-out asphalt\n", " - $\\alpha= 0.55$ for fresh concrete\n", "\n", "Add a new column `Rn` to `df_pen` dataframe." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Tdew_pointuPRHlambdaDeltaGgammaf_windRso_monthlyRsRn
timestamp
2020-01-0112.36259.06251.5250101.3087581.5002.4718120.094385-1.627500.0667501.80825017.4610.02964.346568
2020-01-0211.97509.82501.9250101.2012587.0002.4727270.0923001.443750.0666542.02025017.464.31282.653905
2020-01-0313.05004.97505.1750101.3712558.5002.4701890.098185-2.336250.0668353.74275017.4611.67484.854942
2020-01-0410.86256.68755.5625101.1550078.3752.4753540.086530-0.236250.0665533.94812517.461.64521.871722
2020-01-0512.93759.21254.5625101.2362579.1252.4704550.0975544.252500.0667393.41812517.466.85443.415474
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2021-01-2713.81258.23751.8875100.8375072.3752.4683890.1025514.777500.0665322.00037517.4612.26525.060995
2021-01-2814.400010.22503.5250101.1275076.7502.4670020.106028-3.071250.0667602.86825017.467.16403.534995
2021-01-2912.35007.91255.0250101.2212575.2502.4718420.094317-3.018750.0666913.66325017.467.29363.537119
2021-01-3012.96257.65004.4250101.4950071.3752.4703960.0976945.696250.0669113.34525017.469.32764.152687
2021-01-3115.06258.31253.7500101.3250066.0002.4654370.1100708.820000.0669332.98750017.4613.54685.513874
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397 rows × 13 columns

\n", "
" ], "text/plain": [ " T dew_point u P RH lambda Delta \\\n", "timestamp \n", "2020-01-01 12.3625 9.0625 1.5250 101.30875 81.500 2.471812 0.094385 \n", "2020-01-02 11.9750 9.8250 1.9250 101.20125 87.000 2.472727 0.092300 \n", "2020-01-03 13.0500 4.9750 5.1750 101.37125 58.500 2.470189 0.098185 \n", "2020-01-04 10.8625 6.6875 5.5625 101.15500 78.375 2.475354 0.086530 \n", "2020-01-05 12.9375 9.2125 4.5625 101.23625 79.125 2.470455 0.097554 \n", "... ... ... ... ... ... ... ... \n", "2021-01-27 13.8125 8.2375 1.8875 100.83750 72.375 2.468389 0.102551 \n", "2021-01-28 14.4000 10.2250 3.5250 101.12750 76.750 2.467002 0.106028 \n", "2021-01-29 12.3500 7.9125 5.0250 101.22125 75.250 2.471842 0.094317 \n", "2021-01-30 12.9625 7.6500 4.4250 101.49500 71.375 2.470396 0.097694 \n", "2021-01-31 15.0625 8.3125 3.7500 101.32500 66.000 2.465437 0.110070 \n", "\n", " G gamma f_wind Rso_monthly Rs Rn \n", "timestamp \n", "2020-01-01 -1.62750 0.066750 1.808250 17.46 10.0296 4.346568 \n", "2020-01-02 1.44375 0.066654 2.020250 17.46 4.3128 2.653905 \n", "2020-01-03 -2.33625 0.066835 3.742750 17.46 11.6748 4.854942 \n", "2020-01-04 -0.23625 0.066553 3.948125 17.46 1.6452 1.871722 \n", "2020-01-05 4.25250 0.066739 3.418125 17.46 6.8544 3.415474 \n", "... ... ... ... ... ... ... \n", "2021-01-27 4.77750 0.066532 2.000375 17.46 12.2652 5.060995 \n", "2021-01-28 -3.07125 0.066760 2.868250 17.46 7.1640 3.534995 \n", "2021-01-29 -3.01875 0.066691 3.663250 17.46 7.2936 3.537119 \n", "2021-01-30 5.69625 0.066911 3.345250 17.46 9.3276 4.152687 \n", "2021-01-31 8.82000 0.066933 2.987500 17.46 13.5468 5.513874 \n", "\n", "[397 rows x 13 columns]" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#collapse-hide\n", "\n", "# Stefan-Boltzmann constant\n", "sigma = 4.903e-9\n", "emissivity = -0.02 + 0.261 * np.exp(-7.77e-4 * df_pen['T']**2)\n", "\n", "# Rbo: net longwave radiation for clear skies, otherwise known as diffuse radiation or emitted radiation from the\n", "# atmosphere - 'how hot is it?'\n", "Rbo = emissivity*sigma*((df_pen['T']+273.15)**4)\n", "\n", "# net outgoing long-wave radiation (note: Rs/Rso = proportion of how clear the day is)\n", "# for humid areas, a=1.0 and b=0\n", "# for arid areas, a=1.2 and b=-0.2\n", "# for semihumid areas, a=1.1 and b=-0.1\n", "a = 1.2\n", "b = -0.2\n", "Rb = (a*df_pen['Rs']/df_pen['Rso_monthly'] + b)*Rbo \n", "\n", "# α is the albedo, or short-wave reflectance (dimensionless)\n", "alpha = 0.23\n", "\n", "# net radiation\n", "Rn = (1 - alpha) * df_pen['Rs'] - Rb # (MJ/m2/d)\n", "df_pen['Rn'] = Rn\n", "df_pen" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Calculate the vapor pressure deficit, VPD, add a new column to `df_pen`.\n", "\n", "$$\n", "e_d = e_s\\cdot \\frac{RH}{100}\n", "$$\n", "\n", "$$\n", "e_s = \\exp\\left(\\frac{16.78\\,T-116.9}{T+237.3}\\right)\n", "$$" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Tdew_pointuPRHlambdaDeltaGgammaf_windRso_monthlyRsRnesedVPD
timestamp
2020-01-0112.36259.06251.5250101.3087581.5002.4718120.094385-1.627500.0667501.80825017.4610.02964.3465681.4371481.1712760.265872
2020-01-0211.97509.82501.9250101.2012587.0002.4727270.0923001.443750.0666542.02025017.464.31282.6539051.4009351.2188130.182122
2020-01-0313.05004.97505.1750101.3712558.5002.4701890.098185-2.336250.0668353.74275017.4611.67484.8549421.5034240.8795030.623921
2020-01-0410.86256.68755.5625101.1550078.3752.4753540.086530-0.236250.0665533.94812517.461.64521.8717221.3013831.0199590.281424
2020-01-0512.93759.21254.5625101.2362579.1252.4704550.0975544.252500.0667393.41812517.466.85443.4154741.4923991.1808600.311538
...................................................
2021-01-2713.81258.23751.8875100.8375072.3752.4683890.1025514.777500.0665322.00037517.4612.26525.0609951.5800541.1435640.436490
2021-01-2814.400010.22503.5250101.1275076.7502.4670020.106028-3.071250.0667602.86825017.467.16403.5349951.6414141.2597850.381629
2021-01-2912.35007.91255.0250101.2212575.2502.4718420.094317-3.018750.0666913.66325017.467.29363.5371191.4359671.0805650.355402
2021-01-3012.96257.65004.4250101.4950071.3752.4703960.0976945.696250.0669113.34525017.469.32764.1526871.4948431.0669440.427899
2021-01-3115.06258.31253.7500101.3250066.0002.4654370.1100708.820000.0669332.98750017.4613.54685.5138741.7131061.1306500.582456
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397 rows × 16 columns

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" ], "text/plain": [ " T dew_point u P RH lambda Delta \\\n", "timestamp \n", "2020-01-01 12.3625 9.0625 1.5250 101.30875 81.500 2.471812 0.094385 \n", "2020-01-02 11.9750 9.8250 1.9250 101.20125 87.000 2.472727 0.092300 \n", "2020-01-03 13.0500 4.9750 5.1750 101.37125 58.500 2.470189 0.098185 \n", "2020-01-04 10.8625 6.6875 5.5625 101.15500 78.375 2.475354 0.086530 \n", "2020-01-05 12.9375 9.2125 4.5625 101.23625 79.125 2.470455 0.097554 \n", "... ... ... ... ... ... ... ... \n", "2021-01-27 13.8125 8.2375 1.8875 100.83750 72.375 2.468389 0.102551 \n", "2021-01-28 14.4000 10.2250 3.5250 101.12750 76.750 2.467002 0.106028 \n", "2021-01-29 12.3500 7.9125 5.0250 101.22125 75.250 2.471842 0.094317 \n", "2021-01-30 12.9625 7.6500 4.4250 101.49500 71.375 2.470396 0.097694 \n", "2021-01-31 15.0625 8.3125 3.7500 101.32500 66.000 2.465437 0.110070 \n", "\n", " G gamma f_wind Rso_monthly Rs Rn \\\n", "timestamp \n", "2020-01-01 -1.62750 0.066750 1.808250 17.46 10.0296 4.346568 \n", "2020-01-02 1.44375 0.066654 2.020250 17.46 4.3128 2.653905 \n", "2020-01-03 -2.33625 0.066835 3.742750 17.46 11.6748 4.854942 \n", "2020-01-04 -0.23625 0.066553 3.948125 17.46 1.6452 1.871722 \n", "2020-01-05 4.25250 0.066739 3.418125 17.46 6.8544 3.415474 \n", "... ... ... ... ... ... ... \n", "2021-01-27 4.77750 0.066532 2.000375 17.46 12.2652 5.060995 \n", "2021-01-28 -3.07125 0.066760 2.868250 17.46 7.1640 3.534995 \n", "2021-01-29 -3.01875 0.066691 3.663250 17.46 7.2936 3.537119 \n", "2021-01-30 5.69625 0.066911 3.345250 17.46 9.3276 4.152687 \n", "2021-01-31 8.82000 0.066933 2.987500 17.46 13.5468 5.513874 \n", "\n", " es ed VPD \n", "timestamp \n", "2020-01-01 1.437148 1.171276 0.265872 \n", "2020-01-02 1.400935 1.218813 0.182122 \n", "2020-01-03 1.503424 0.879503 0.623921 \n", "2020-01-04 1.301383 1.019959 0.281424 \n", "2020-01-05 1.492399 1.180860 0.311538 \n", "... ... ... ... \n", "2021-01-27 1.580054 1.143564 0.436490 \n", "2021-01-28 1.641414 1.259785 0.381629 \n", "2021-01-29 1.435967 1.080565 0.355402 \n", "2021-01-30 1.494843 1.066944 0.427899 \n", "2021-01-31 1.713106 1.130650 0.582456 \n", "\n", "[397 rows x 16 columns]" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#collapse-hide\n", "\n", "# vapor pressure deficit = VPD\n", "def vp_sat(T):\n", " return np.exp((16.78*T - 116.9)/(T + 237.3)) \n", "df_pen['es'] = vp_sat(df_pen['T'])\n", "df_pen['ed'] = df_pen['es'] * df_pen['RH'] / 100\n", "df_pen['VPD'] = df_pen['es'] - df_pen['ed']\n", "df_pen" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now that all variables have been defined, daily E_penman can be calculated. \n", "\n", "$$\n", "E_{tp} = \\frac{\\Delta}{\\Delta+\\gamma}Q_{ne}+ \\frac{\\gamma}{\\Delta+\\gamma}E_A\n", "$$\n", "\n", "$Q_n$ is the available energy flux density:\n", "\n", "$$\n", "Q_n = R_n - G,\n", "$$\n", "\n", "and $E_A$ is the drying power of the air:\n", "\n", "$$\n", "E_A = f_e(u)\\cdot\\text{VPD}\n", "$$\n", "\n", "Add a new column `E_penman` to `df_pen`." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, '$ET_{penman}$ (mm d$^{-1}$)')" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#collapse-hide\n", "\n", "def E_penman(df):\n", " T = df['T']\n", " Delta = df['Delta']\n", " gamma = df['gamma']\n", " Rn = df['Rn']\n", " G = df['G']\n", " EA = 6.43*df['f_wind'] * df['VPD']\n", " lambd = df['lambda']\n", " return ((Delta / (Delta + gamma))*(Rn - G) + ((gamma / (Delta + gamma))*EA)) / lambd\n", "\n", "# daily_data\n", "df_pen['E_penman'] = E_penman(df_pen)\n", "\n", "fig, ax = plt.subplots(1, figsize=(10,7))\n", "ax.plot(df_pen['E_penman'])\n", "plt.gcf().autofmt_xdate()\n", "ax.set_ylabel(r\"$ET_{penman}$ (mm d$^{-1}$)\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Make a plot with the following: \n", "1. the Penman (daily) estimate of the potential evapotranspiration.\n", "2. the Thornthwaite (monthly) estimate of the potential ET.\n", "3. daily evaporation pan data." ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#collapse-hide\n", "\n", "fig, ax = plt.subplots(1, 1, figsize=(10,7))\n", "ax.plot(df_pen['E_penman'], color=\"tab:red\", label=\"Penman\", linewidth=2)\n", "ax.plot(df_th['Ep']/30, color=\"tab:blue\", label=\"Thornthwaite\", linewidth=2)\n", "ax.plot(1*df2['pan evaporation (mm)'], color=\"black\", label=\"pan\", linewidth=2)\n", "\n", "ax.set(xlabel=\"date\",\n", " ylabel=\"evaporation (mm)\")\n", "ax.legend();" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Plot the mean temperatures used in the Penman calculation (daily mean) and in the Thornthwaite calculation (monthly mean)." ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#collapse-hide\n", "\n", "fig, ax = plt.subplots(1, 1, figsize=(10,7))\n", "ax.plot(df_pen['T'], color=\"tab:blue\", label=\"Penman\", linewidth=2)\n", "ax.plot(df_th['T'], color=\"tab:orange\", label=\"Thornthwaite\", linewidth=2)\n", "ax.set(xlabel=\"date\",\n", " ylabel=\"temperature (°C)\")\n", "ax.legend();" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.7.4" } }, "nbformat": 4, "nbformat_minor": 4 }