{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# 1. Unconfined Aquifer Test - Vennebulten\n", "**This example is taken from Kruseman et al. (1970).**" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Import packages" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "editable": true, "slideshow": { "slide_type": "" }, "tags": [] }, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import pandas as pd\n", "\n", "import ttim as ttm\n", "\n", "plt.rcParams[\"figure.figsize\"] = [5, 3]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Introduction and Conceptual Model" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In aquifer tests in unconfined aquifers, there is also the vertical component to flow to the well. The drawdown data shows the delayed water table response, a distinguishable S-shape in the log-log plot. In the early times of the drawdown, the drawdown behaves as a confined aquifer: when the aquifer releases the elastic storage. However, as pumping continues, the water table storage begins to be released, generating further drawdown and the S-shape.\n", "\n", "This test conducted in Vennebulten, the Netherlands, is reported in Kruseman et al. (1970). The cross-section consists of a first layer up to 6 m depth of very fine and loamy sands, followed by coarse sands until 21 m deep.\n", "\n", "In this example, we will reproduce the work of Xinzhu (2020) that compared different conceptualizations in TTim to various solutions presented in the original report (Kruseman et al., 1970) and in other software, MLU (Carson & Randall, 2012) and AQTESOLV (Duffield, 2007).\n", "\n", "The screen of the pumping well is placed between 10 and 21 meters depth, and pumping has taken place for 25 hours at a rate of 873 m3/d. The available drawdown data comes from two piezometers, a shallow one, screened at 3 m depth, and a deeper one, screened in the depths between 12 to 19 m. Both wells are located 90 m from the pumping well.\n", "\n", "The conceptual model of the aquifer is displayed below:\n", "\n" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "jupyter": { "source_hidden": true }, "tags": [ "hide-input" ] }, "outputs": [ { "data": { "image/png": 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/2NnZwcDAALGxsWLnHTp0SKHyZbW+y/JzkgWfz0efPn3A4/Fw4sQJ7NixA5MmTYKfnx+6desGAFxPVsGZQuvXry8xu8LCwjBhwgTu2i9fvsTVq1cxYMAAmecU9/flR4OcfSng7e2NtWvXYuTIkfD09MSIESNQq1Yt5OTk4Pbt29iwYQNq166NTp06oWbNmhg6dChWr14NLS0ttGvXDvHx8Zg5cyYqVaqE8ePHK339cePGYffu3ejSpQumTp2Khg0b4uvXr4iMjETHjh3h7++P3r17Y8eOHWjfvj3Gjh2Lhg0bQldXF69fv8b58+fRpUsX/PTTT1yZDg4O6Ny5M4KDg1G+fHls374dERERWLx4MYyMjAAAVatWhaGhIXbs2AFXV1eYmJjAwcEBDg4O+OWXX7B+/Xr0798fQ4YMQUpKCpYsWSKxmE2HDh3wxx9/oG/fvhg6dChSUlKwbNkyqVMYi4qDg4NCPQULFy5E69at4e/vj0mTJkFPTw9r1qzB/fv3ERYWxv1wzZgxA4cPH0aLFi0wa9YsGBkZ4e+//8aXL1/EynNycsKcOXMwffp0/PfffwgICICFhQXev3+PmzdvwtjYGCEhIcWmUxb6+vro168fVq9eDcYYFi1aJHZc2XujOFH2M9LT08Py5cvx+fNnNGjQAFevXsW8efPQrl077gGGx+Ohf//+2LJlC6pWrYp69erh5s2bUqcgSqNOnTo4cOAA1q5dC09PT2hpacHLy6vUP6f379/j+vXrEulmZmZwc3MDAMyePRuXLl3C6dOnYW9vj4kTJyIyMhKDBw9G/fr1UaVKFbi4uKBq1aqYOnUqGGOwtLTEkSNHEBERUWy2FiQpKQk//fQThgwZgvT0dMyePRsGBgaYNm2azHNU5fuitpRtfOCPxZ07d1hgYCCrXLky09PTY8bGxqx+/fps1qxZLCkpicvH5/PZ4sWLWY0aNZiuri6ztrZm/fv356aticgfVZ4faRHtHz9+ZGPHjmWVK1dmurq6zNbWlnXo0IE9fvyYy5OTk8OWLVvG6tWrxwwMDJiJiQlzcXFhw4YNY8+ePePyOTo6sg4dOrB9+/axWrVqMT09Pebk5MT++OMPCVvCwsKYi4sL09XVlYh03rZtG3N1dWUGBgbMzc2N7d69W6rtW7ZsYTVr1mT6+vrM2dmZLVy4kG3evFkiSroo0fiykDWT4NKlS6xFixbM2NiYGRoassaNG7MjR45InH/lyhXWuHFjpq+vz+zt7dnkyZPZhg0bJGxmjLHw8HDm7+/PzMzMmL6+PnN0dGTdu3dnZ86c4fKUVDS+iLt37zIATFtbm719+1biuLL3RkEK1o0oyj0qKkosnyha+/z582LpinxGgYGBzNjYmMXGxjI/Pz9maGjILC0t2YgRI8SmmTEmnBr666+/Mjs7O2ZsbMw6derE4uPjFYrGT01NZd27d2flypVjPB5PrF6K+3OSBQqJxm/SpAljjLHTp08zLS0tMT2MMZaSksIqV67MGjRowLKyshhjjD18+JC1bt2amZqaMgsLC9ajRw+WkJAg8XmI7sP8U4Dzf/bS9OT/ronq999//2VjxoxhNjY2TF9fnzVr1ozdunVL7FxZ97wi9wIhCY+x71yZhPjhcHJyQu3atXH06NGyNoUgCDXiwoUL8Pf3x969e9G9e/eyNueHgsIXCYIgCELDIWdPEARBEBoOdeMTBEEQhIZDLXuCIAiC0HDI2RMEQRCEhkPOniAIgiA0HFpUpwACgQBv376Fqamp1DXSCYIgCM2HMYZPnz7BwcFBI9bdJ2dfgLdv36JSpUplbQZBEAShArx69UrunibqADn7Aog2q7h16xVMTMzk5CYIgiA0kc+fM+DlVanMNjAqbsjZF0DUdW9iYgZTU3L2BEEQPzKaMpyr/gMRBEEQBEEUCjl7giAIgtBwyNkTBEEQhIZDzp4gCIIgNBxy9gRBEASh4ZCzJwiCIAgNh5w9QRAEQWg45OwJgiAIQsMhZ08QBEEQGo5GOfvg4GDweDyxl729fVmbRRAEQRBlisYtl1urVi2cOXOGe6+trV2G1hAEQRBE2aNRLXsA0NHRgb29PfeysbEpa5MIQiFGjOiNevXsULOmGVq1qouIiKNlbRJBEBqCxjn7Z8+ewcHBAVWqVEHv3r3x33//FZo/KysLGRkZYi+CKAvGjZuJqKhXePIkA0uXbsLo0f2QmppS1mYRBKEBaJSzb9SoEf755x+cOnUKGzduRGJiInx8fJCSIvsHc+HChTA3N+detJc9UVbUrFkLenp6AIQ9VDk52UhMfFPGVhEEoQlolLNv164dfv75Z9SpUwetWrXCsWPHAADbtm2Tec60adOQnp7OvV69elVa5qo9d+5EYdy4IDRs6IgqVfRRq5YVfvmlA27cuFTi175//zYGDeoKDw8HVK1qhObNXfDnn3Pw9WumWL5x44JQoQJP5is6+vr/l3cHv/zSAQ0aVEbVqoaoVcsSnTp5Y//+7SWuJT+jRvWDs7MBAgI84ePTAq6udcSO8/l81K1riw0b/iy0nOXLg1GhgmZszUkQxPejcQF6+TE2NkadOnXw7NkzmXn09fWhr69filZpBkuWzMTq1Qvg4+OPSZPmoEKFynjzJgEbNvyB7t39sHLlP+jWrV+JXPvp04fo0sUHzs41ERy8ApaW1rhx4yL+/HMOYmOjERp6iMs7btxM/PLLcIkygoI6QU9PH+7uDQAAGRlpcHCohK5d+8DevgIyM7/g4MEdGDPmF7x6FY9x42aUiJaC/PXXDuTmbsOVK+fw7Nkjib20r1+/iJSUZLRv361U7CEIQjPQaGeflZWFR48eoVmzZmVtSqnw5k0CUlM/yM1naWmNChUqF/k6y5bNxsqV8zBz5lIMHz5J7FiXLr3RokUtTJ/+P7Rq1RFmZuZFvo4sDh7ciW/fvmHjxv1wcqoKAGjatAXev3+HHTs2IC3tI8qVswAAODlV5fKIuHYtEqmpHzB27AxutoaPjx98fPzE8rVu3REJCXHYsWNDqTl7QNiF7+vbBps3r0KVKtXRsmV77tixY/tQr54XKlZ0LDV7CIJQfzSqG3/SpEmIjIxEXFwcbty4ge7duyMjIwOBgYFlbVqJ8+ZNAnx9XREQ4Cn35evrijdvEop0nejo61i5ch569AiUcPSAsKekX7+hyMhIx+XLZ79XllR0dXUBQOJBwty8HLS0tLhxb1mEhW0Gj8dD796D5F7L0tIaOjryn4lF3eYPH8Zi6NAecHExR61alggOnoDc3Fw8f/4E/foFoEYNUzRq5IQ1a5bILVMg4CM+/jn3njGGkycPon37n8XynTlzDK1bu6NKFX00blwF69Ytk1s2QRA/FhrVsn/9+jX69OmDDx8+wMbGBo0bN8b169fh6Kj5raDU1A/4+jUTwcHBcHJykpkvPj4ewcHBSE39UKTW/YoVc8Hj8TB58hyZeSpXdgYAvHv3WuIYYwx8Pl+ha8lysj16BGLTphWYOnUEpk9fDCsrG1y7Font29cjKOh/MDIylllmRkY6jh3bh6ZNW6Jy5SoSxwUCAQQCAdLTP+LIkb2IjDyFefP+UsheABg+vCe6deuP/v2H4dKlCKxZswS5uTm4dOkMAgNHYtiwSQgP34n583+Dk1M1rjs+KSkRUVFX4O8fAD09fRw/fgBXr57HtGmLuLJv3bqK9+/fiTn7S5fOYtCgLvD09MaaNbvA5/Oxdu0SJCe/V9hmgiA0H41y9rt27SprE8ocJycnuLi4lEjZGRnpuHjxNHx92xT6oPDly2cAkOp0r12LRI8e/gpd7/r1OFSq5CSRXqmSEw4fvobBg3+Cj09eF/3gwWMQErKi0DLDw8Pw7dtX9OkzWOrxadNGYvv29QAAPT09zJmzCr/8MkwhewGgX7+hGDZsAgCgefNWiIw8jdDQv7Bp0wG0a/cTAOGQwZkzR3Hw4A6xsfdNm1Zg4sRB4PF4qFKlOtat24Natepxx48e3QdX1zpwdq7OpS1ePB02NnYIC4uAgYEBAMDPry0aNXJS2GaCIDQfjXL2RMny+PE95ObmwsWlTqH5oqOvAQBcXetKHKtb1xPHj0cpdD07Owep6a9exSMwsBNsbOywYcM+WFnZ4PbtG1i5ch6+fPmM5cs3yyxz167NsLCwQkDAT1KPjxnzO/r2/RUfPiQhIuIIZswYha9fv0gdspBGq1Ydxd5Xr+6Khw/vwt+/HZemo6MDJ6dqeP36JZdma2uPgwcLn8Vw4sQBsaGHzMwvuHs3CoGBIzlHDwAmJqZo3boT9u6VPQuFIIgfC3L2hMJ8+iRccMjKSvaqhJ8/f8KhQ2GoXLkK6tXzkjhubGyCWrXcFbqerG78BQum4vPnDERE3OF6Dxo3bg5LS2tMmDAI3bsPgLe3r8R5Dx/G4u7dWxg8eKzMGRgVKlTmei1EgXELF05Djx6BheoWYWFhKfZeV1cPhoZGYs4YEPYafP6s+AJOt2/fxJs3CWJd+GlpHyEQCGBjI7n/g60t7QlBEEQeGhWgRxQvqamf8PhJ3roD5ctXBCBsWctizZol+Pz5E8aPny0xbQwQduM7Ouoq9JJ1nQcP7qB6dTeJYYJ69YTT6J48uS/1vF27hC3+vn1/lWl/QerXb4jc3Fy8fFn4SowlzfHj++HsXAMuLrW5tHLlLMDj8ZCcnCiRPylJMo0giB8XatkTMqnjPgIAELZjKpo3qw1X1zpwcqqK8PAwTJ48l5veJmL//u1YvXoBOnXqiZ49pc+AKI5ufDs7Bzx5ch9fvnyGsbEJly4aPhA9lOQnKysL+/dvR/36DcUcpjyuXDkPLS0tODo6K3xOSXD8+H507NhTLM3IyBju7g1x4sQBzJixlOs9+Pz5EyIijpSFmQRBqCjk7H9QunWfC20da4XyDghcik0bx6FVy/pYsmQjBgxojw4dGmDkSGFEeXJyIg4d2oXTpw+jZ88gLFmyQWZZJiamUrv3lWHIkHEYNKgrevdujSFDxsPS0hoxMdfx118LUaOGm9j4uIiTJ8ORlpaKPn2kt+qnTBkKExMzuLs3hI2NHVJTP+Do0b04fHg3RoyYrFAXfklx//4dxMe/QIcOP0scmzJlLvr1C0CfPq0xbNhE8Pl8rFmzGEZGxkhLSy0DawmCUEXI2f+gZGZmAbyvCuXNyeVjytTNiIn6C02a+OPIkRtYtWo+li6diZSUZAgEAlSs6IiwsAg0b96qhC0H2rTpjN27z+Lvvxdh9uyxyMhIh4NDJfTvPwyjRk2TOs9+167NMDIyRpcuvaWW6enpjd27Q7F37zZkZKTB2NgEbm71sGrVv/j55/4lLalQjh/fj4oVHVG3rqfEsebNW2Pz5nAsWTIDI0b0go2NPQIDR+Lbt6/444+QMrCWIAhVhMcYY2VthCqRkZEBc3NzPH6cDlNTs7I2R2Hu3YtBQIAntm7dWujUu8ePHyMoKAjQagfwLGXmK8j0ab0xckRHqcdGj/4FR47sxqFDV7+71U5I4ucn7K2YPXt5WZtCED8Mnz5lwMXFHOnp6TAzUx9fIAtq2f+g/LN1Ilxc6hWap6H3OADA3JABGDSwjcx8Cxb8jaioyxg1qh9OnYopdFEbQnkuXHhY1iYQBKHmkLP/QbG1tUCFCoWP2YcfmIXExI/o1LFRoflMTc1w/XpccZpHEARBFCPk7AmZNPCqUdYmEARBEMUAzbMnCIIgCA2HnD1BEARBaDjUjV+AV6+EK8Y9eHBHbMEWVefZs0cAhLvaFYbouCi/JmBpaV2kHfwIgiB+FGjqXT4SEhLg6uqKzMzMsjaFUAIjIyNcuPCIHD5BEMUGTb3TYD58+IDMzExs374drq6uZW0OoQCPHj1C//79kZr6gZw9QRCEDMjZS8HV1RUeHh5lbQZBEARBFAvk7AmN4Nu3r8jM/FLWZhAEoSFo2u8JOXtCI+jatWlZm0AQBKGy0NQ7giAIgtBwqGWvIPv2AT16ALt2Ab16iR+rVw+IjQVOngTathU/VrUqYG4OxMQofq01awAjIyAo6LvNlsvWrcDAgfLzOToCcmb1IT4eqFIFWLoUmDRJsevGxQFOTgqZWij//jESLlUrfH9BBFEKfDbzkUgzybhaBpYQsvic+Q3+feaWtRnFBjl7BfHzA3g84Px5cWefmgrcuwcYGwuP5Xf2r18D//0HTJig3LXWrAGsrUvH2XfoAFy7Jp7m7Q107w5MnJiXpq9f8rZ8Dwb6ujAylNzaliBUEb6hoUSaUQ7dv6qEQCAoaxOKFXL2CmJtDdSuDVy4IJ4eGQno6ACDBwudfX5E7/39S8XEQmEM+PYNKPgbY2MjfBXEzg5o3Lh0bCMIgiBKFhqzVwJ/f+DJE+Ddu7y0CxeABg2A9u2B6Gjg0yfxY9raQLNmwvchIUCjRoClJWBmBnh4AJs3Cx2xCCcn4MED4UMEjyd85e/mzsgQdpFXqQLo6QEVKgDjxgFfCgSO8njAqFHAunWAq6uwZb5tW9F0JycDI0cCbm6AiQlgawu0aAFcuiQ9v0AAzJ8PVK4MGBgAXl7A2bOKXevMGaBlS+HnY2QENGmi+LkEQRCEdMjZK4GohZ6/dX/+PODrK3RKPJ64Azx/XujQzc2F7+PjgWHDgD17gAMHgG7dgNGjgbn5hoUOHgScnYH69YXd69euCdMAIDNTeK1t24AxY4ATJ4DffhOOf3fuLP7QAADh4cDatcCsWcCpU3kPHcqSmir8O3s2cOwYEBoqtNHPT7KnAwD++ksYv7BiBbB9O6ClBbRrJzlcUJDt24E2bYSOfts24edkaSkcGiGHTxAEUXSoG18JfH2FjuvCBaBPHyAlBbh/XxiQZmIidOznzwtb+a9eCYPPevTIOz80NO9/gUDoLBkDVq4EZs4UPizUry/sajczk+xGX7VKGAh444awtQwIW8EVKgjH2E+eFDpVEZ8/C+MJLCy+T3fNmsI4AhF8vtABx8cLbfLzE8/P5wMREcJWPSDM6+QkfOiIiJB+jcxMYOxYoGPHvIcbQPhZengAv/8u1E0QBEEoD7XslcDCQhh5L2rNRkYKu+mbNBG+9/XNG6eXNl5/7hzQqpWwpa+tDejqCh1gSgqQlCT/+kePCuMG3N2B3Ny8V9u2wgeFgq3sFi2+39GLWLdO6HQNDIQxCrq6wtb2Iyn76XTrlufoAcDUFOjUCbh4UfggII2rV4U9CIGB4toEAiAgAIiKkhyqIAiCIBSDnL2S+PsDT58Cb98KHbqnp7BVDwid/e3bQHq68JiODtD0/9d6uXlT2EUNABs3AleuCB3Y9OnCtK9f5V/7/Xthy15XV/xlairsIfjwQTx/+fLFo/mPP4ARI4TxBvv3A9evC20PCJBut7299LTsbGFvgzTevxf+7d5dUt/ixUJ9ouEEgiAIQjmoG19J/P2Fzu/CBeGrffu8YyLHfvFiXuCe6EFg1y6h4zp6VLzVGx6u+LWtrYVd/Fu2yD6eHx5P8bILY/t2YVf92rXi6fmDEfOTmCg9TU8v7/MoiMj21atlzwKws1PIXIXh8wXQ1v6+593vLUM0vUdLq+hlkI7iK4N0FJ8NxVGGqujQBBRy9hOUnSgOYMaMGbC0tFT6PFWneXNhF/y+fcKo+SVL8o6Zmwu72LdtE45n9+2bd4zHE7b0tbXz0r5+Bf79V/Ia+vrSW8wdOwILFgBWVsJo/NKCx5OcZx8bKwy4q1RJMv+BA8I4BtFDzadPwJEjwgDB/Prz06QJUK4c8PChcBZBSfIl8xvGz/sXV6Ofwc7KDCtmB6JOTSlCCuHek1cYG7INSSkZ8PGsjj9nDoCxoXKLEYTuvYCVW08CAMYNbIeg7r5KnU868iAdeZAOIcWhQ5NQ6HFnxYoVuHHjBm7fvq3Qa/Xq1UhLSyth08sG0ZS58HBhsJ5ovF6Er6/Q2QHi4/UdOgi7sPv2FQap7doldH7SFqupUwe4exfYvVvYXX7vnjB93DhhsFzz5sLehTNngNOngU2bgJ49Sy6ArWNH4XVmzxbGHaxdK4wTkPXAoa0NtG4tDLTbv18YRJiRIZx6KAsTE2Grfv16oHdv4cPUxYvC82fNEg4jFBdrd5zBtZhnYIwhKTUD4+b8o3QZY0O24UPqJzDGcC3mGdbtOKPU+bGPE7Bs4zHk5PCRk8PH0g1Hce/JK6XKIB15kA4hpCOP4tChSSjcjX/w4EHY2toqlNfU1LTIBqkD/v5CJ1y/vtD558fXF/jzT2GXtU++FTFbtBB2vy9eLAxWq1ABGDJEOGd98GDxMkJChHP5hwwRtopFS9UaGwun9i1aBGzYIIz2NzQUzmdv1ap4lp2VxvTpwmj5zZuFPRlubsKAvYMHpU+9GzVKuIDPmDHCwMNatYRT9go+GBWkf3+hliVLhFMUP30Sfj7u7sW7muDb9x+5/wUChvcf0pXq6uPzBUhKyQDLN9fxTaJyAQXvkj5KpL19n6pUy4N0CCEdeZCO/Pm/X4cmoZDq0NBQmIsmiyvA+vXrYVfcA6xKsGbNGlSpUgUGBgbw9PTEJVmrvxQRUcBYVJTksS5dhMeysoSLwuRn4EDg8WOhI3zxApg6FRg0SJg/v6N2dBTOi8/IEB7Lvya9sbFwXv7jx8JrpKUJu9T/+EN8TJsx4Xz3olDwXD09Ybf869fC4YXoaKHOrVvFbXNyEp47ZYqwNf7qldDGmJi84EQRQUGSugFhr8XRo8IZCtnZwmsePSoM3CsumjV0gUDAoKXFg5YWD008ayg1pqetrQUfz+rc+QIBQ7OGLkrZUM/VEcZG+tDW0oK2lhaMjfRRz9WRdJAO0qFCOjQJHmMFl2JRb3bv3o1ffvkFa9asQZMmTbB+/Xps2rQJDx8+ROXKlQs9NyYmBp6enoiOjoaHh0cpWUx8D6I6+/ePiXCpqthTPwPD0bMxuBL9FA52Fvi1lz+MDJQbT8z8loVNu8/j7fuPaOJZAx1beoAH5SIin8W/w/Zw4YNo/67NUN1JuekTpCMPddMhayMcddMhC03QIdwIZyrS09NhVrALVw35Lmf/+fNnic0CyvpDadSoETw8PLA2X+i4q6srunbtioULF0rkz8rKQlZWFgDgzp078PX1JWevRoicPRANgOqMIIjiIgOAucY4e6X7KeLi4tChQwcYGxvD3NwcFhYWsLCwQLly5WBRXCu4FJHs7GxER0ejTYE+4zZt2uDqVenbRy5cuBDm5uYwNzeHr69y0Z4EQRAEoQ4oPc++X79+AIAtW7bAzs4OvOKazF0MfPjwAXw+XyJewM7ODonSJn8DmDZtGje1UNSyJ9SPf//YCZeqxRubQRAlBe1nr/oIu/HL2oriQ2lnHxsbi+joaNSsWbMk7CkWCj6AMMZkPpTo6+tD///nv5nIWvGFUHkM9HNhZJhT1mYQhELwDSUjvY1y6P5VJQQCzaoPpbvxGzRogFevlJvvWFpYW1tDW1tbohWflJRUprMDCIIgCKIsUbplv2nTJgwfPhxv3rxB7dq1oaurK3a8bt26xWacsujp6cHT0xMRERH46aefuPSIiAh06dJF4XIeSdvdhVBJqK4IgiDko7SzT05OxosXLzBw4EAujcfjcV3lfFnbmpUSEyZMwC+//AIvLy94e3tjw4YNSEhIwPDhw+Wea21tDSMjI/Tv378ULCWKC0MDfZQzNy5rMwiCIFQWpZ39oEGDUL9+fYSFhalcgB4A9OrVCykpKZgzZw7evXuH2rVr4/jx43B0lL8gQ+XKlXHz5k3Url0b25aNgJGhXilYXLx8Ma5f6HHjL7dLyZLSo5y5MRxsy3YmCEEQhCqj9Dx7Y2Nj3L17F9WqVSspm8qUjIwMmJub48bBuTAxNpB/gorxyaxZocdNMyhinSDKGmnfU/puqhafv3xDo59masw8e6Vb9i1atNBoZ08QBFEWvE36iLT0L2VtBvH/ZH7NBiCckq2OM7Wsra3FVo1V2tl36tQJ48ePx71791CnTh2JAL3OnTt/v5UEQRA/EImJiejz63J8/ZZV1qYQBVDXtVeMjIzw6NEjzuEr7exFgW5z5syROKYKAXplxb0nr/D2fSrquTrC3qac0udnZ+fiSvRTAEATzxrQ01O6apCYnAbj7+xtUhUddx+9hIOdZZH3nyYdQkhHHqqkw6uteDd+Wloavn7Lwvbt2+Hq6lok2whCxKNHj9C/f398+PCh6M6+4Fr4BBC69wKWbTwGADA20se/f4xETWcHhc/Pzs7FwCnrcOfhSwCAu5sjQpcOh56u4tXz5L+36D9+Dc6d76Sc8flQJR2ZX4UtnMlDOyKou3JP1qRDCOnIQ9V0XG87TGoeV1dX2peDKBE0aw+/MkAgEGDl1pPc+2/fcrB1X6RSZVyJfsr9kAHAnYcvceXWU6XK2LovEllZRV/xSVV1rAg9odQDJunIg3TkoYo6CKI0UcjZr1q1Ct++fVO40HXr1uHTp09FNoogCIIgiOJDIWc/fvx4pZz3lClTkJycXGSj1AktLS2MG9iOe29goKt092ATzxpwd8tbB8DdzRFNvGooVUZQd18YGOjKzygDVdUxbmA7aGkp3gFFOvIgHXmoog6CKE0UmmevpaWF2rVrQ0dHsTGye/fu4cmTJ3B2dv5uA0ubos6z/+7AnZxcrmuyiVcNpcYjRSQmp8G4auFj9vLm8qqKjjIPpCIdHKQjj+LS4VVgzP7x48cICgpCdHR0kcfseTweDh48iK5duxbpfAAICgpCWloawsPDAQB+fn5wd3fHihUrilxmcaOKNqkaMTEx8PT0FLufFPrGzJ49W6kLdenSBZaWlspbqMbUqVmpyD8gAKCnqwN/b7fvssHephy+d/BEVXQU5Yc0P6RDCOnIQ5V0KPs9TUpKwsyZM3HixAm8f/8eFhYWqFevHoKDg+Ht7V1ke9SRAwcOSEz5VkeCg4MRHh6OO3fulMr1SsTZEwRBEMXHzz//jJycHGzbtg3Ozs54//49zp49i9TU1LI2rdT50RqS8sjJyVHo4Yei8QmCIFSYtLQ0XL58GYsXL4a/vz8cHR3RsGFDTJs2DR06dBDL++HDB/z0008wMjJC9erVcfjwYe4Yn8/H4MGDUaVKFRgaGqJmzZpYuXKlUrZ8/PgRAwYMgIWFBYyMjNCuXTs8e/YMAMAYg42NDfbv38/ld3d3h62tLff+2rVr0NXVxefPn6WWHxQUhK5duyIkJAS2trYwMzPDsGHDkJ2dzeXx8/PDuHHjuPfZ2dmYMmUKKlSoAGNjYzRq1AgXLlwQy8/j8SRe8fHxAICEhAR06dIFJiYmMDMzQ8+ePfH+/Xvu/ODgYLi7u2PLli2oXLkyTExMMGLECPD5fCxZsgT29vawtbXF/PnzxbSkp6dj6NChnA7R6rMAsHXrVoSEhODu3bucPVu3bpV7XkF7nJ2doa+vD0VWvSdnTxAEocKYmJjAxMQE4eHhyMoqfIW9kJAQ9OzZE7GxsWjfvj369evHtf4FAgEqVqyIPXv24OHDh5g1axZ+//137NmzR2FbgoKCcOvWLRw+fBjXrl0DYwzt27dHTk4OeDwemjdvzjnajx8/4uHDh8jJycHDhw8BABcuXICnp2ehy8+ePXsWjx49wvnz5xEWFoaDBw8iJCREZv6BAwfiypUr2LVrF2JjY9GjRw8EBARwDyEHDhzAu3fvuFe3bt1Qs2ZN2NnZgTGGrl27IjU1FZGRkYiIiMCLFy/Qq1cvsWu8ePECJ06cwMmTJxEWFoYtW7agQ4cOeP36NSIjI7F48WLMmDED169fByB88OnQoQMSExNx/Phxbuy8ZcuWSE1NRa9evTBx4kTUqlWLs6tXr15yzxPx/Plz7NmzB/v371d4GED5KBeCIAiiWCks2ExHRwdbt27FkCFDsG7dOnh4eMDX1xe9e/dG3bp1xfIGBQWhT58+AIAFCxZg9erVuHnzJgICAqCrqyvmNKtUqYKrV69iz5496Nmzp1wbnz17hsOHD+PKlSvw8fEBAOzYsQOVKlVCeHg4evToAT8/P2zYsAEAcPHiRdSrVw+VK1fGhQsX4ObmhgsXLsDPz6/Q6+jp6WHLli0wMjJCrVq1MGfOHEyePBlz586VmEHx4sULhIWF4fXr13BwEC5wNGnSJJw8eRKhoaFYsGCBWLf/n3/+iXPnzuHGjRswNDREREQEYmNjERcXh0qVhLEY//77L2rVqoWoqCg0aNAAgPBBacuWLTA1NYWbmxv8/f3x5MkTHD9+HFpaWqhZsyYWL16MCxcuoHHjxjh//jzu3buHpKQk6OvrAwCWLVuG8PBw7Nu3D0OHDoWJiQl0dHRgb2/P2Xfu3Dm55wHC3ox///0XNjY2cutNBLXsCYIgypi4uLhCj//88894+/YtDh8+jLZt2+LChQvw8PDgun5F5Hf+xsbGMDU1RVJSEpe2bt06eHl5wcbGBiYmJti4cSMSEhIUsvHRo0fQ0dFBo0aNuDQrKyvUrFkTjx49AiDsMn/w4AE+fPiAyMhI+Pn5wc/PD5GRkcjNzcXVq1flrjVfr149GBkZce+9vb3x+fNnvHr1SiJvTEwMGGOoUaMG1wNiYmKCyMhIvHjxQizviRMnMHXqVOzevRs1atTgNFWqVIlz9ADg5uaGcuXKcZoAwMnJCaamptx7Ozs7uLm5iT182NnZcZ91dHQ0Pn/+DCsrKzG74uLiJOzKj6LnOTo6KuXogSK07OfMmYNJkyaJVQYAfP36FUuXLsWsWbOULZIgCOKH4X+zQvHh8zaUK1cOy5YtAyAcp5WHgYEBWrdujdatW2PWrFn49ddfMXv2bAQFBXF5CgZq8Xg8bqXAPXv2YPz48Vi+fDm8vb1hamqKpUuX4saNGwrZLWtcmDEGHo8HAKhduzasrKwQGRmJyMhIzJkzB5UqVcL8+fMRFRWFr1+/omnTpgpdryCia+RHIBBAW1sb0dHR0NbWFjuWf6jg4cOH6N27NxYtWoQ2bdpItV2WJkD651rYZy0QCFC+fHmx2AER5cqVk6lR0fOMjY1lliELpZ19SEgIhg8fLuHsMzMzERISQs6eIAiiEB49f4P3H9LFWmblypVDWlqaUuW4ublx8+EV4dKlS/Dx8cHIkSO5tMJamdKul5ubixs3bnDd+CkpKXj69Cm3eY9o3P7QoUO4f/8+mjVrBlNTU+Tk5HBDEPlbyNK4e/cuvn79CkNDQwDA9evXYWJigooVK0rkrV+/Pvh8PpKSktCsWTOJ4yIbO3XqhG7dumH8+PESmhISEvDq1Suudf/w4UOkp6d/14ZEHh4eSExMhI6ODpycnKTm0dPTk9g4TpHziorS3fiynoTu3r1LUyIIgiAUJDk5GZ06dUKnTp0KbdmnpKSgRYsW2L59Oze+vHfvXixZsgRdunRR+HrVqlXDrVu3cOrUKTx9+hQzZ85EVFSUwudXr14dXbp0wZAhQ3D58mXcvXsX/fv3R4UKFcTs8PPzw86dO1G3bl2YmZlxDwA7duyQO14PCMejBw8ejIcPH+LEiROYPXs2Ro0aJXXFwxo1aqBfv34YMGAADhw4gLi4OERFRWHx4sU4fvw4AKBbt24wNDREcHAwEhMTuRefz0erVq1Qt25d9OvXDzExMbh58yYGDBgAX19feHl5KfzZFKRVq1bw9vZG165dcerUKcTHx+Pq1auYMWMGbt26BUA4NBAXF4c7d+7gw4cPyMrKUui8oqKws7ewsIClpSV4PB5q1KgBS0tL7mVubo7WrVsrFORBEATxIzOgW14LNDk5GcnJyYVOnTIxMUGjRo3w559/onnz5qhduzZmzpyJIUOG4K+//lL4usOHD0e3bt3Qq1cvNGrUCCkpKWKtfEUIDQ2Fp6cnOnbsCG9vbzDGcPz4cbEubX9/f/D5fDHH7uvrCz6fr9De8C1btkT16tXRvHlz9OzZE506dUJwcHChNg0YMAATJ05EzZo10blzZ9y4cYNrqV+8eBEPHjyAk5MTypcvz71evXoFHo+H8PBwWFhYoHnz5mjVqhWcnZ2xe/dupT6XgvB4PBw/fhzNmzfHoEGDUKNGDfTu3Rvx8fGws7MDIIzDCAgIgL+/P2xsbBAWFqbQeUW2SZHlcgFg27ZtYIxh0KBBWLFiBczNzbljenp6cHJy0oiVnIq6XK6q8MlMeleWCHnL5RIEUfKsP/oKYWFh3PucnBykpaV913K5mkDB5XqJolHk5XIBIDAwEIBwuoaPj49GLFeoKE/+e8ttZxnU3VepPawB4dBHeMQtXLr5GA52FhjRrxWMjZR7kPiS+Q1rd5zB2/cf0ayhC7q29pI6nCKPaUuEPzDqrENT6oN0CPkRdfTt2xd9+/bl3ovWxieIkkLpAD1fX18IBAI8ffoUSUlJEntCN2/evNiMUwUSk9PQf/wabi/ss1cf4PDGSUqtsR0ecQszlu2Blpbwx+dZXCLWL/hVKTvGz/sX12KEi0ScuhgLAPipTQOlygCAY+fuAFBfHZpSH6QjD9JBECWP0gF6169fR7Vq1eDq6ormzZtz8yj9/Pzg7+9fEjaWKXcfvUTm1yzwBQLwBQJ8yczC3UcvlSrj0s3H0NLiQSBgEAgYrkQ/BZ8vkH/i/8PnC3A1+hl3vpYWD5duPlZWirAsNdehKfVBOkgHIcnWrVupC7+EUNrZDx8+HF5eXrh//z5SU1Px8eNH7qWJmzI42EnOMJCWVngZFtz/Wlo82FmbQ1tb8Y9eW1sLdlZmXIsBACrYf//MB3XUoSn1QTry5ycdBFHSKH0nPnv2DAsWLICrqyvKlSsHc3NzsZemUadmJUwe2hG6utrQ1dXG5KEdld7ickS/VvDxqAEejwdbK3OsnD1AaTtWzA6ErZU5tLR48PGogeH9WildBgC116Ep9UE68iAdBFHyKByNL6JFixaYMmUKAgICSsqmMkVWNL4oNkHaXE9F4fMF3/2kL68MedH4xmnCACRV1yEPdakPeZCO4rOhOMooLR0Fv6eiAL0fPRqfKB6KHI0fGxvL/T969GhMnDgRiYmJqFOnjkRUfsGNGTSF7/nyiyiOLr3vLYN0FJ8NxVEG6Sg+G4qjjLLWkX89doIoKtLuI4Wcvbu7O3g8ntjCD4MGDeL+Fx3j8XgSy/8RBEEQhVOuXDkYGuijf//+ZW0KoSEYGRnB2tqae6+Qs5e3IxNBEARRdOzt7XF400SkpX8pa1OI/yfzazYCJ61FZGSk2KY66oK1tTUqV67MvVfI2Ts6OpaYQQRBEATgYGsBB1sL+RmJUuHzl28AhD3bZmZmZWzN96P0ojqHDx+Wms7j8WBgYIBq1aqhSpUq320YQRAEQRDFg9LOvmvXrhLj94D4uH3Tpk25zQVKEycnJ7x8Kb4Qxm+//YZFixaVqh0EQRAEoUooHTYaERGBBg0aICIiAunp6UhPT0dERAQaNmyIo0eP4uLFi0hJScGkSZNKwl65zJkzB+/eveNeM2bMKBM7CIIgCEJVULplP3bsWGzYsAE+Pj5cWsuWLWFgYIChQ4fiwYMHWLFihVi0fmliamoKe3v7Mrk2QRAEQagiSrfsX7x4ITVYwczMDP/99x8AoHr16vjw4cP3W1cEFi9eDCsrK7i7u2P+/PnIzs4uNH9WVhYyMjLEXgRBEAShSSjt7D09PTF58mQkJydzacnJyZgyZQoaNBDuMvXs2TNUrFix+KxUkLFjx2LXrl04f/48Ro0ahRUrVmDkyJGFnrNw4UKx5X4rVVJuiUyCIAiCUHWUdvabN29GXFwcKlasiGrVqqF69eqoWLEi4uPjsWnTJgDA58+fMXPmzGIxMDg4GDwer9DXrVu3AADjx4+Hr68v6tati19//RXr1q3D5s2bkZKSIrP8adOmcbEH6enpePXqVZFt/d4drgQCgcSWwWWBKugojt3CSIcQ0lF8NhRHGcXxHVcVHZpSH6rwu1vSKD1mX7NmTTx69AinTp3C06dPwRiDi4sLWrduzS012bVr12IzcNSoUejdu3eheZycnKSmN27cGADw/PlzWFlZSc2jr68PfX3977Lx3pNXGBuyDUkpGfDxrI4/Zw6AsaFyZYbuvYCVW08CAMYNbIeg7r5Knf8l8xvGz/sXy/8qfG38wlAlHVejn8HOygwrZgcqvSEJ6ciDdAhRNR2XLl1R6jwRqqYD0Iz6AIqmQ50o0iLOPB4PAQEBGDNmDMaOHYu2bdsWy5rS0rC2toaLi0uhLwMDA6nn3r59GwBQvnz5ErFNxNiQbfiQ+gmMMVyLeYZ1O84odX7s4wQs23gMOTl85OTwsXTDUdx7olwPw9odZ3At5plS5xRElXQwxpCUmoFxc/5R6nyAdIggHXmomo6iomo6NKU+iqpDnVCoZb9q1SoMHToUBgYGWLVqVaF5x4wZUyyGKcu1a9dw/fp1+Pv7w9zcHFFRURg/fjw6d+4stmRgccPnC5CUkiG27sCbxFSlyniX9FEi7e37VKWedN++lyxDGVRRh0DA8P5DulI7mZGOPEhH/vyqqUNZVFWHptSHsjrUCYU+2T///BNfvnzh/pf1WrFiRUnaWij6+vrYvXs3/Pz84ObmhlmzZmHIkCEICwsr0etqa2vBx7M6tLR40NLiQSBgaNbQRaky6rk6wthIH9paWtDW0oKxkT7quSq3RHGzhi4QCJTarVgMVdMhsqOJZw2ldhEjHaRDHXQUFVXToSn1UVQd6oTS+9lrOrL2sy+ML1+zsG7HGbxJTEWzhi7o2toLPB5Pqes++e8ttu4T7jUf1N0XNZ0dlDqfMYbwiFto1X1CoflMMy7JPKZKOi7dfIwK9pYY3q+V0uNwpCMP0iFE1XT8Pm+NxLHCvpsiVE0HoBn1AUjq+PzlGxr9NBPp6ekasTZ+kZ19dnY24uLiULVqVejoKB3np7IUxdmrEp/MCg/QU+QHhSCIkkXa95S+m6qFpjl7pb10ZmYmRo8ejW3btgEAnj59CmdnZ4wZMwYODg6YOnVqsRup6vD5Aty48xxJKRmoVb0iqldRfgW/9E+ZuBr9FHwBQ7MGNWFuaqR0Gc9fvoddHaVP41AlHfefvIKVhQl8PJTr3gNIR35IRx6qpKNp56LPmlElHZpSH9+jQ11QumU/duxYXLlyBStWrEBAQABiY2Ph7OyMw4cPY/bs2VwEvLpCLXuCIEoaatmrPj98yz48PBy7d+9G48aNxcZH3Nzc8OLFi2I1jiAIgiCI70fpsNDk5GTY2tpKpH/58kXp4AiCIAiCIEoepZ19gwYNcOzYMe69yMFv3LgR3t7exWcZQRAEQRDFgtLd+AsXLkRAQAAePnyI3NxcrFy5Eg8ePMC1a9cQGRlZEjYSBEEQBPEdKN2y9/HxwZUrV5CZmYmqVavi9OnTsLOzw7Vr1+Dp6VkSNhIEQRAE8R0UaYJ8nTp1uKl3BEEQBEGoNkVy9gKBAM+fP0dSUpLE1oDNmzcvFsNUDZHO79nwJ5fPh7aWVpEDGRlj4AsE0NHWLrINpCMP0iGEdORBOvIgHZqF0s7++vXr6Nu3L16+fImCU/R5PB74/KLv6KSK3H/6Cr1GiW/+E7ZyNOq6Kra5DmMMoXsjsXxTXlBjNUc77FgxSuF5/J+/fMOw6Ztw5+FLLm1Y35YYHdhW6Ru4TsBv3P/qqENT6oN0CCEdeZCOPFRCR+Y3hfKpC0ovquPu7o4aNWogJCQE5cuXl6g8c3PzYjWwtMm/qM5/CUnoM3a11Hx7/hqLWjUqyi1v2pJdOHwmWuqx20cXQk+v8Oet7Oxc1O84Teqxbm0bYO7EnmJp8hbVady4sdh7VdUhjdhHCWpXH9IgHXn8qDqkfU8LfjdFqLKOgqhrfRQkvw5NWVRH6b6RZ8+eYcGCBXB1dUW5cuVgbm4u9tIkRDfcnzN/wYPTS/Hg9FL8OfMXAEDPUSvlnp/+KZO74S7smokHp5fi/qklqO4kXNbx33D5K2btOHQZAFCrekXEnliMB6eX4uLu2QCAA6eikP4pUylN6qxDU+qDdJAOWai7Dk2pD5EOTUJpZ9+oUSM8f/68JGxRKfLHIrRpVlfq/wXjFQpyNfopAGBQTz/YWAqfDHk8HrYuGw4A+GPTcbl2/Ln5BADg77kDubWjrSxMMLRPSwDApagncsuQhrrp0JT6IB2kozDUXYem1IdIhyah0Jh9bGws9//o0aMxceJEJCYmok6dOtDV1RXLW7du3YKn/7Dw+cKbUldHPEAlJ0cY16CjwMYPfIGMMnJzAQDaWiUfdEI68pVBOooN0iGJuuvQlPrgy3mgUEcUugvd3d1Rv359uLu74+eff8ajR48waNAgNGjQQOxY/fr1S9reUiN/9OfpS7FS/5cXIdqsoQsAYP3Os0j5+BmA8EYcOXMLAGD84PZy7Rg3qB0AIGjSOi4gMjk1A6F7hQsY+XjWkFuGNNRNh6bUB+kgHYWh7jo0pT5EOjQJhQL0Xr58KS8Lh6Oj43cZVNbkD9B7+eaDzDEiRSNDZyzfg4OnoqQe+96Al86tPLFwSm+xNGUD9FRVhzQePH2tdvUhDdKRx4+qQ5kAPVXWURB1rY+C/LABeo6Ojgq/NIlaNSoibOVoifQ9f41VeArI3Ak9MLxfK7G0+rWccDN8rtwbDgD09HRw4+BcLrhExKQhHbBgci+FbJCFuunQlPogHXmQjjw0QYem1Ieeng7O7piu0LXUBaWn3mk6svazV4XFHRRZpEJey944Tdidpuo65KEu9SEP0pHHj6SjsP3s1UlHYai7jh9+P/sfle+52UR8z00PCCNKv7cM0pEH6RBCOvIgHXmQDs3i+z9JgiAIgiBUGnL2BEEQBKHhFMnZp6WlYdOmTZg2bRpSU1MBADExMXjz5k2xGkcQBEEQxPej9Jh9bGwsWrVqBXNzc8THx2PIkCGwtLTEwYMH8fLlS/zzzz8lYSdBEARBEEVE6Zb9hAkTEBQUhGfPnsHAIC9avV27drh48WKxGkcQBEEQxPejtLOPiorCsGHDJNIrVKiAxMTEYjGKIAiCIIjiQ+lufAMDA2RkZEikP3nyBDY2NsVilLrB5wtwNeYpUj5+Ru2alVDN0U7pMtIyMnE56jG0tbXg41kD5qZGSpfxNO4dytdT+jQOVdLx4Nlr2FmZo5F7NW5DDUUhHXmQjjxUSYfvT4Wvh1EYqqRDU+rje3SoC0o7+y5dumDOnDnYs2cPAOFcyoSEBEydOhU///xzsRuo6ty48xyDpqyXSL+6P0ShG4cxhpl/7JVY2rFzK08smNxLoYUg0j9lwudn4TaS16/L3y9aGqqmIz9blgxDI/dqcs8HSIcI0pGHKuq4/tNYha6bH1XUIULd60OEMjrUDaW78ZctW4bk5GTY2tri69ev8PX1RbVq1WBqaor58+eXhI1lQnKqZO9FQd5/SOduuCZeNTB1RGfumLSbWRqrt53ibrhhfVtiUE8/AMDhM9Hc5hHyUPRaslBFHdNHdUUTL+GmGYOmrEdSSjrpIB0ao6MoqKIOTamPouhQN4q8XO65c+cQExMDgUAADw8PtGrVSv5JaoBoudxG9atiy+LhheYdO2cbzly+j1ljuqFXR28AwifG2m2nAAAOrp+AGlXKF1pGrTaTAQAXd8+GlYUJAOGDhl/vuQCAB6eXFnr+8/hEdBm6HABw/9QSfDZvXmh+0ZKcqq5D9GS9/eBlLFx7CE28amDDgiGFlkE6SIe66ChsuVx10gFoRn1I06Fpy+Uq3bKPj48HALRo0QKTJk3ClClTSsXRz58/Hz4+PjAyMkK5cuWk5klISECnTp1gbGwMa2trjBkzBtnZ2UW63o3bL+TmOXP5PgCgY0sPLo3H42H6qK4AgIfPCl93IJfP5/4X3XAAYGNpJjWPNO4/fQ0AmDqic5G7nlRZR48OjQAAV249LfR8gHRIs5F0qK4OZVBlHZpSH8roUEeUdvbOzs5o2rQp1q9fzy2oUxpkZ2ejR48eGDFihNTjfD4fHTp0wJcvX3D58mXs2rUL+/fvx8SJE4t0vYr2lnLzlDMTjg29epsiln7+2kMAgK1V4U+D2vnWfebzBdz/+TtbtOWsDS26WS9FPZZrryxUWcd/r5IAAJUdrAs9HyAd0mwkHaqrQxlUWYem1IcyOtQRpRXdunUL3t7emDdvHhwcHNClSxfs3bsXWVlZJWEfR0hICMaPH486depIPX769Gk8fPgQ27dvR/369dGqVSssX74cGzdulDp7QB6//6+r3DwrZwUCAH4e8ScevXiDrOwcbD94GVejhU+n8oJNeDwe3N2E2wL3Hr0KySkZSMv4gp+G/QEAqO5kL7e17uMhHO+6cuspdh+9JtdmddHx5WsWHr14g+4jVgAAQsZ3Jx2kQ2N0KIuq6tCU+lBWhzpS5DF7xhguXLiAnTt3Yv/+/eDz+fj555+xZcuW4rZRjK1bt2LcuHFIS0sTS581axYOHTqEu3fvcmkfP36EpaUlzp07B39/f6nlZWVliT2oZGRkoFKlShJb3Mpi0vztOBF5VyI9dOlwNKxXVe75onEhaShqQ/7I1ILTHwcPHoyuXbty72WNC6qajvy0862HZdP7yz0fIB0iSEe+fCqo4/r16xJ5ChuzB1RTh5h9alwfYvb9vw5NG7Mvlv3sY2JiMHjwYMTGxoJfwmMdspz90KFDER8fj9OnT4ul6+vrY+vWrejTp4/U8oKDgxESEiKRruiNCwA3777A7D/3IeHtBzTxqoF5E3vC1spcMUEAsrNzsfPwFfy5+Thy+QKMH9weA35qBj09xWdGvv+QjnZBi5GVnSOWPmbMGPTt2xcA8OHDB+h9fgA99hk2Urq6VEXHorWHcfpSLCzMjbFi5gB41XVW+HzSQTrUQcflK1cljstz9qqoQ1PqQ5oOcvb/z6tXrxAWFoadO3fi3r178Pb2Rr9+/WSOqUtDlqPNT1RUFLy8vLj3hTn7ly9f4tSpU2Lpenp6+Oeff9C7d2+p5X9vy16VaNF3Ht5/SIeWlhasrKwAiLfsO3XqhOTkZNhZm+PczhllaClB/NgoG41PlD6a5uyVXlRnw4YN2LFjB65cuYKaNWuiX79+CA8Ph5OTk9IXHzVqlEwnLELRcu3t7XHjxg2xtI8fPyInJwd2drJXVtLX14e+vr5C11AXrKyscOTIkbI2gyAIglARlHb2c+fORe/evbFy5Uq4u7t/18Wtra1hbS0/+lIRvL29MX/+fLx79w7lywvnWJ4+fRr6+vrw9PQslmsQBEEQhDqitLNPSEgok0jFhIQEpKamIiEhAXw+H3fu3AEAVKtWDSYmJmjTpg3c3Nzwyy+/YOnSpUhNTcWkSZMwZMgQjeiCIQiCIIiiopCzj42NRe3ataGlpYV79+4Vmrdu3brFYlhBZs2ahW3btnHv69evDwA4f/48/Pz8oK2tjWPHjmHkyJFo0qQJDA0N0bdvXyxbtqxE7CEIgiAIdUEhZ+/u7o7ExETY2trC3d0dPB5PbAEC0Xsej1di0fhbt27F1q1bC81TuXJlHD16tESurw44VrCGkaklLC3lLwhEEARB/Dgo5Ozj4uK4+dtxcXElahBRdEKXDpca5UsQBEH82Cjk7B0dHbn/X758CR8fH+joiJ+am5uLq1eviuUlCIIgCKLsUXq5XH9/f6lr4qenp8tcpU6dyc7OxcZd51CrzWTUDfgNoXsvIDs7V6kyklLSMWTaRtRqMxkBQYtw485zpe24FfsfmnSfjVptJmPsnG14/0H+VpCyeP8hXW11aEp9kI48SEcepEOIqujQJJReVEdLSwvv37+XWJb16dOn8PLyKtI69KqEaIvbGweFWx2qwtKQE+dvx0kpS0NuWTJMYh3owrrxRYvqiNmnojqkoSpLdZIOIaQjXz4ldUj7ngb/NkztdEhDHetDGmNDtuHMlfsas6iOwi37bt26oVu3buDxeAgKCuLed+vWDV26dEHbtm3h4+NTkraWOv3G/QVAuDHClX3BuLBrJtyqVQAADJu+Se75fL6Au+F+H9kFMUcXYP/a8QCAE5F3cSv2P7ll3LjznPvi7F87HjcPzcOsMd0AAIOmrBfbtWnKwp0YO3YsZs2aJbWsv/76C9s3LMI/f4xQaR2yULf6IB2kQ1EdADRCh6bUx407z3Hmyn25+dQJhZ29ubk5zM3NwRiDqakp997c3Bz29vYYOnQotm/fXpK2liqMMTx/+R4AcHD9BJQzM4aNpRl2rR4DALjz8CXkdYqIuo2aeNVAv65Noa+nC5eqDti3dhwAYNzcf+TaMXvFPgDCL45LVQcYG+qjV0dvNPES7h51NSZv/+db9/7DjRs3cPv2ballOTo6wq1mFXjWdlZpHdJQx/ogHaRDUR0i1F2HptSHSIcmofCiOqGhoQCEy9dOmjQJxsbGJWaUKsAX5D2B5l9ESFtbSyyPjra2zDLepwjHqfwau4mli/Zs/pj+Ra4doj2bq1QSHzZp6uWCK7eeIuXjZ7llSEPddGhKfZCOPEiHJOquQ1PqQ6RDk1A6QG/27Nka7+gBiN1Myal5cQj5b9bCbjgAqFW9IgBg/l/hYk+jR85EAwDaNJO/AJGPp/CJeN/xvHX/GWNYvO4wAKB2zUpyy5CGuunQlPogHXmQDknUXYem1IdIhyZRpF3v9u3bhz179iAhIQHZ2dlix2JiYorNuLIgf4DenmPXsXzTMQDAwB6+0NXRwYawswCA4f1aYXRgW7nl1Wozmfv/t+GdcfnWY1y5JezKOrdzBuysC9+SMSklHf595gEQ3oD+3m6Y/1c4d/zB6aXc/6Jd72xsbKRuhHPq1Ck8eRCDxFfPce7aA5XVIYstey6oVX2QDtIhTUfP/61EUlqWRBmi4Fl10SENdawPeTo0JUBPaWe/atUqTJ8+HYGBgdi4cSMGDhyIFy9eICoqCv/73/8wf/78krK1VMjv7I2N9PH70t04/P9PhCK6tW2AORN6KLRHQPqnTPj8PFsiXdHIVEB2ZOnV/SEwNzXi3stz9gWj8VVVhywYY2pVH7IgHXn8iDpE31NFUVUdslC3+pDFhesP8b9ZoT+us3dxccHs2bPRp08fmJqa4u7du3B2dsasWbOQmpqKv/76q6RsLRXyO3vRFI/0T5m4Gv0UfAFDswY1FbphC/L85Xvcf/IKVhYm8PGoITYGpQh8vgA37jxHUkoGalWviOpV7CXyKOrszUwNcXLrVJXVIQ91qQ95kI48fiQdwSv24X5cBh49esRNYU5JSYFAIICtlRnmT+qlFjoKQ53qQxaatp+90s7eyMgIjx49gqOjI2xtbREREYF69erh2bNnaNy4MVJS1DuwQZqzVxcUdfZ21uY4t3NGGVhIEAQgOc+evpuqh6Y5e6UD9Ozt7TmH7ujoiOvXrwMQrplfhOF/giAIgiBKGKX3s2/RogWOHDkCDw8PDB48GOPHj8e+fftw69YtdOvWrSRsJAiC0GjatGmDL2lvYWEof9EZgigKSjv7DRs2QPD/cyGHDx8OS0tLXL58GZ06dcLw4cOL3UBCcbq3a4iUHCuYmJiUtSkEQSjB6NGjoZf1EvpZCWVtCqGhKO3stbS0oKWV1/vfs2dP9OzZs1iNIorGyF/a0Ba3BKHiCKfeLYGVlRW2bt1a1uYQPwgKOfvY2FiFC6xbV/EFJAiCIH40Pnz8hOTv2LWSIIqCQs7e3d0dPB5PbgAej8cDn88vFsMIgiAIgigeFHL2cXFxJW2H2sMYk7tmszxEsRD5h0mKEysrK/DAh3U52fNVVUVHLp8PbS0thRbQkAbpyIN05KEKOhgkG029evXCh+Qk2Fqa4OiWKXLLUAUdmlIfJf27qyoo5OwdHR1L2g615fOXbxg2fRPuPHzJpQ3r2xKjA9sqfAPff/oKvUatEksLWzkadV0rK3Q+YwyheyO5JSZlzbPfunWrzCAgVdQBANUc7bBjxSiF1zwgHXmQDiGqrENEZmYmvmR+RaaRnlrq0JT6UEaHulGktfH//fdfrFu3DnFxcbh27RocHR2xYsUKVKlSBV26dCkJO0sN0aI6l/bMhmW5wqPas7NzUb/jNKnHurVtgLkT5Qcuxj5KQJ+xq6Ue2/PXWNSqUVFuGdOW7BJbWlKWswcg1dmrqo783D66EHp6hT+bko48SEceqqoj//dUkUV1VFWHCHWvDxEiHT/8ojpr167FhAkT0L59e6SlpXFj9OXKlcOKFSuK274yY9fRq3Lz7Dh0GYBwl6XYE4vx4PRSXNwtXI/5wKkopH/KlFuG6Ib7c+YveHB6KR6cXoo/Z/4CAOg5aqXc89M/ZXJfHGtLU7n51UHHhV0z8eD0Utw/tQTVnYTLbP4bfol0kA6N0CFvExZ10aEp9VEUHeqI0s5+9erV2LhxI6ZPnw7tfOMkXl5euHfvXrEaV5b8/U+E3Dx/bj4hzDt3ILfmspWFCYb2aQkAuBT1pNDzBfn2bs6/7WL+//PnkcbVaOFOToN6+kG7iGNOqqbDxlL4FM3j8bB1mXDthj82HScdpEOjdCiDKuvQlPpQRoc6ovQ8+7i4ONSvX18iXV9fH1++fCkWo1QBbS354z78/78hdHXEg0NycnMVLuN74fOl2yCNRYsW4fPHd7AwBoLHdc8rQ4V15OQIe450FNjAgnQUH6QjXxmko9jQFB3qiNJNwSpVquDOnTsS6SdOnICbm1tx2KQS/G9AG7l5xg1qBwAImrSOm5aYnJqB0L2RAIT7ORdG/ujP05dipf4vL0K0WUMXAMD6nWflPo1euXIFZyJv4OLNxyqtI+XjZwDCH4aRM7cAAMYPbl/o+aSDdKibDmVQZR2aUh/K6FBHlA7QCw0NxcyZM7F8+XIMHjwYmzZtwosXL7Bw4UJs2rQJvXv3LilbS4XiCtDr3MoTC6fI/ywePH0tc4xI0cjQGcv34OCpKO69srveqaqO/Hxv4A7pyIN05FFWOqZNmwYDAwO0bdsWQN5307KcCdbPHyy1jDXbI3D+2kOpx3auGAVd3cJ793Jy+Og7TvoW5M0bumJ0oPwGzouEJExdHCb12IJJvRTaylZddGR+zUbgpLWIjIxUmyXIra2tUbmy9O9EkaLxN27ciHnz5uHVq1cAgAoVKiA4OBiDB0u/SdUJZbe4/fzlG/qP/xvP4hO5tElDOiCou6/CU0CkRYYqGtkKCKey/PXPaazbcQaA8s5eVXUAQP1aTlg/fzCMjRSfkkM6hJAOIaqoQ7RbqAhRwLMmjhUTpYdoC3ppDr9Izl7Ehw8fIBAIYGtrCwB48+YNKlSoUHRLVYCi7mevCos7FMd+9qqgA9CcxTZIhxDSkYdAIMCXcr5iaQEBAUhLS8P27dvh6upa5LKJH5dHjx6hf//+iI6OhoeHh8RxpQP08mNtbQ0ASExMxPz587Fp0yZ8/fr1e4pUW3g83nf9AACqMU6kKjq+1wbSkQfpyENVdQQFBWHFihVwdXWV+kNNEN+Lwt+etLQ09OvXDzY2NnBwcMCqVasgEAgwa9YsODs74/r169iyZUtJ2krIYdFvfbBixQoEBweXtSkEQcgg7lUS/vvvP7x8mbf6m7u7e9kZRPwQKNyy//3333Hx4kUEBgbi5MmTGD9+PE6ePIlv377hxIkT8PX1lV/IdzB//nwcO3YMd+7cgZ6eHtLS0iTySOuaW7t2LYYPH16itqkKDetVxSezxmVtBkEQhTD4tw2FDrcRREmgsLM/duwYQkND0apVK4wcORLVqlVDjRo1Sm3VvOzsbPTo0QPe3t7YvHmzzHyhoaEICAjg3pubK79aFUEQBEFoEgo7+7dv33Lz6J2dnWFgYIBff/21xAwrSEhICADhZi6FUa5cOdjby5/+QRAEoSrEx8eXtQkqTVBQENLS0hAeHl7WpqgtCo/ZCwQC6Orqcu+1tbVhbGxcIkZ9D6NGjYK1tTUaNGiAdevWyZ3KkpWVhYyMDLGXunLz7gtcv34d0dHSN5lo06YNunbwR3s/99I1jCCIQpHXQxoUFAQejwcejwddXV3Y2dmhdevW2LJlyw8xXW/lypVyG3rqwNatW1GuXLkyubbCLXvGGIKCgqCvrw8A+PbtG4YPHy7h8A8cOFC8FirB3Llz0bJlSxgaGuLs2bOYOHEiPnz4gBkzpE8zA4CFCxdyvQbqztTFYYWOBY4ePVrmFrcEQag2AQEBCA0NBZ/Px/v373Hy5EmMHTsW+/btw+HDh6Gj812Tq0qc7Oxs6OnJ3sK3MGg4Vhw+nw8ej6fUDBWFcwYGBsLW1hbm5uYwNzdH//794eDgwL0XvZQhODiYe1qV9bp165bC5c2YMQPe3t5wd3fHxIkTMWfOHCxdurTQc6ZNm4b09HTuJVooKD9pGZk4ejYGJy7cUWhHJWk8jXuHg6ejcDX6Kbc+tDLw+QJcinqM8NO38Pzl+yLZAABP/3un9jo0pT5IRx6kQz76+vqwt7dHhQoV4OHhgd9//x2HDh3CiRMnxFq96enpGDp0KGxtbWFmZoYWLVrg7t27YmUdOXIEnp6eMDAwgLOzM0JCQpD7/2vLA8Jg57Vr16Jdu3YwNDRElSpVsHfvXrEy3rx5g169esHCwgJWVlbo0qWL2HBEUFAQunbtioULF8LBwQE1akhfxjY4OBju7u5Yv349KlWqBCMjI/To0UMsCFtUlgjGGJYsWQJnZ2cYGhqiXr162Ldvn1h+af7kwoULAICPHz9iwIABsLCwgJGREdq1a4dnz55x54ta4EePHkXNmjVhZGSE7t2748uXL9i2bRucnJxgYWGB0aNHczu/AsIHmilTpqBChQowNjZGo0aNuGteuHABAwcORHp6OmePaOZUYecVtMfNzQ36+vpiszkUQeFHwdDQUKUKVoRRo0bJXV7XycmpyOU3btwYGRkZeP/+Pezs7KTm0dfX53orCsIYw8w/9kostdm5lScWTO6l0MIc6Z8y4fPzbIn0LUuGoZF7NQVUADfuPMegKesl0q/uD4G5qZFCZYg4c+U+Nm3aAUD9dGhKfZCOPEjH99GiRQvUq1cPBw4cwK+//grGGDp06ABLS0scP34c5ubmWL9+PVq2bImnT5/C0tISp06dQv/+/bFq1So0a9YML168wNChQwEAs2fnaZg5cyYWLVqElStX4t9//0WfPn1Qu3ZtuLq6IjMzE/7+/mjWrBkuXrwIHR0dzJs3DwEBAYiNjeVa8GfPnoWZmRkiIiJQ2Pptz58/x549e3DkyBFkZGRg8ODB+N///ocdO3ZIzT9jxgwcOHAAa9euRfXq1XHx4kX0798fNjY28PX1xcqVK7Fo0SIu/6JFixAWFgYXF+Ha/EFBQXj27BkOHz4MMzMz/Pbbb2jfvj0ePnzIDVdnZmZi1apV2LVrFz59+oRu3bqhW7duKFeuHI4fP47//vsPP//8M5o2bYpevXoBAAYOHIj4+Hjs2rULDg4OOHjwIAICAnDv3j34+PhgxYoVmDVrFp48Ee7MJ1qGt7DzqlevztkjWpbeysqKW8xOUcp0FRdra2u4uLgU+jIwUHwVu4Lcvn0bBgYGRR4jWb3tFPcDMKxvSwzq6QcAOHwmmtt0QR75fwCmj+qKJl7Cp9tBU9YjKSVd7vnvP6RzP2RNvGpg6ojOUstWFM86VdRWh6bUB+kgHcWJi4sL16I+f/487t27h71798LLywvVq1fHsmXLUK5cOa7lO3/+fEydOhWBgYFwdnZG69atMXfuXKxfL/7A1KNHD/z666+oUaMG5s6dCy8vL6xeLVzud9euXdDS0sKmTZtQp04duLq6IjQ0FAkJCWItUmNjY2zatAm1atVC7dq1ZWr49u0btm3bBnd3dzRv3hyrV6/Grl27kJiYKJH3y5cv+OOPP7Blyxa0bdsWzs7OCAoKQv/+/TkN5ubmsLe3h729Pa5evYp169Zh//79sLe355z8pk2b0KxZM9SrVw87duzAmzdvxAIAc3JysHbtWtSvXx/NmzdH9+7dcfnyZWzevBlubm7o2LEj/P39cf78eQDAixcvEBYWhr1796JZs2aoWrUqJk2ahKZNmyI0NBR6enowNzcHj8fjbDMxMZF7Xn571qxZAx8fH9SsWVPpmDnVHuTJR0JCAlJTU5GQkAA+n8/tvFetWjWYmJjgyJEjSExMhLe3NwwNDXH+/HlMnz4dQ4cOldlyl8f6nWcBABd3z4aVhfAJbEC3ZvDrPRfLNx3jfhRk8TzfOtr3Ty0Bj8dD385NsP3gZSxcewgzlu/BhgVDCi1jwZpwAMCsMd3Qq6M3AKB/16ao3XYKAGG3YY0q5RXS06tXL3xIToKtpQku7Jqpdjo0pT5IB+koThhjXO9DdHQ0Pn/+DCsrK7E8X79+xYsXL7g8UVFRmD9/Pnecz+fj27dvyMzMhJGRsDfE29tbrAxvb2/udzc6OhrPnz+HqampWJ5v375x1wGAOnXqKDROX7lyZVSsmLfXgbe3NwQCAZ48eSIxu+rhw4f49u0bWrduLZaenZ0tsf367du3MWDAAPz9999o2rQpAOGysjo6OmjUqBGXz8rKCjVr1sSjR4+4NCMjI1StWpV7b2dnBycnJ7FNcezs7JCUlAQAiImJAWNMYrgiKytLoj7yo+h5enp6qFu3rsxy5KE2zn7WrFnYtm0b915UqefPn4efnx90dXWxZs0aTJgwAQKBAM7OzpgzZw7+97//Fel6ufnGYUQ/AABgY2kmlqewpTPvP30NAJg6orNYV2CPDo2wcO0hXLn1VK4dZy7fBwB0bJm3hCaPx8P0UV0x/69wPHz2RmFnn5mZiS+ZX5FppKd2OjSlPkgH6ShuHj16hCpVqgAQzpoqX768WOtahKiHUyAQICQkBN26dZPII68nVaRPIBDA09NTaje7jY0N939RZ2yJriNtCEU0++DYsWMSe7Hkb9glJiaic+fOGDx4sNgmbbKGE/I/NAEQm30mskVamsgegUAAbW1tREdHQ7vA/VLYrnmKnmdoaFjkPR0ANXL2W7duLXTqRUBAgNhiOt+Ldr4oRz5fAG1t4fv8N4q2nEhI0Y/HpajH+OWnZlz6f6+ET4KVHazl2lHOzAhpGZl49TYFLlUduHTRFpG2VmayTi0UddOhKfVBOkjH7tVjkGHcoFjW+j937hzu3buH8ePHAwA8PDyQmJgIHR0dmfFOHh4eePLkCapVKzyW4Pr16xgwYIDYe1Ejy8PDA7t37+aCAL+XhIQEvH37Fg4Owjq8du0atLS0pAb1iQLUEhISZK7c+u3bN3Tp0gUuLi74448/JM7Pzc3FjRs34OPjAwBISUnB06dPv2sTovr164PP5yMpKQnNmjWTmkdPT08soE/R84qDst95RUXh8Xhwd3MEAPQevQrJKRlIy/iCn4YJb5zqTvZyn7J8PIQ36pVbT7H76DV8+ZqFRy/eoPuIFQCAkPHd5dqxclYgAODnEX/i0Ys3yMrOwfaDl3E1WthaKErwj0AgUDsdmlIfpIN02FiZwdbWlttITFGysrKQmJiIN2/eICYmBgsWLECXLl3QsWNHzim3atUK3t7e6Nq1K06dOoX4+HhcvXoVM2bM4GY2zZo1C//88w+Cg4Px4MEDPHr0CLt375aYorx3715s2bIFT58+xezZs3Hz5k2MGjUKANCvXz9YW1ujS5cuuHTpEuLi4hAZGYmxY8fi9evXSukChD0KgYGBuHv3Li5duoQxY8agZ8+eUhdIMzU1xaRJkzB+/Hhs27YNL168wO3bt/H3339zvb/Dhg3Dq1evsGrVKiQnJyMxMRGJiYnIzs5G9erV0aVLFwwZMgSXL1/G3bt30b9/f1SoUAFdunRR2nYRNWrUQL9+/TBgwAAcOHAAcXFxiIqKwuLFi3H8+HEAwoDzz58/4+zZs/jw4QMyMzMVOq84+K4tbjWR/FvcAkCjn2ZKzafoFriyIoXb+dbDsun9FbJp0vztOBF5VyI9dOlwNKyXN6ak6Ba3YvapoA5ZfP7yTa3qQxakI1++H1THJzPxFpxoi1tZ25MGBQVxjkxHRwcWFhaoV68e+vbti8DAQLFegk+fPmH69OnYv38/kpOTYW9vj+bNm2PhwoWoVKkSAODUqVOYM2cObt++DV1dXbi4uODXX3/FkCHC2AIej4e///4b4eHhuHjxIuzt7bFo0SKx2VOJiYn47bffcPz4cXz69AkVKlRAy5YtsWzZMpiZmSm86l1wcDDCw8MxbNgwzJs3D6mpqWjfvj02bdoECwsLTn/+shhjWL16NdasWYP//vsP5cqV46YjNm/eHE5OTlKnpomGfT9+/IixY8fi8OHDyM7O5oICRZHvW7duxbhx48Sm/4nsFMUtSLMrJycH8+bNwz///IM3b97AysoK3t7eCAkJQZ06dQAAI0aMwN69e5GSkoLZs2cjODhY7nnS7ClITEwMPD09Zd5D5OwLUHA/++zsXOw8fAV/bj6OXL4A4we3x4CfmkFPT/ERkPcf0rFo7WGcvhQLC3NjrJg5AF51nZWy6+bdF5j95z4kvP2AJl41MG9iT9haia9roIyzV2UdhaFO9UE6SIcsHQWd/e3btzFixAiZP9SlDY/Hw8GDB8XmtpcU0pwooTzk7JWkoLNXNwr+iORH5OztrM1xbqfsVQUJgig59hy7jo+sAoyMjDhn+vjxYwQFBZGzJ4qMPGevNgF6BEEQmsC6HWe4HrjScKYEAVCAHkEQBFEAxlipPYgEBwdTq74UIGdPEARRxpw8ebKsTSA0HOrG1yDW/HsaKTnRMDExwa+//ipx/LfffgP/82uYaJXs8p0EQSgHOXuipCFnr0HsO3GTGwuU5uybNm1KW9wSBEH8gJCzJwiCUBHyr81OEMog794hZ08QBFHGaGlpQUtLC/37K7aQEEFIw8jISObKjOTsi4Fbsf9h7JxtSMvIRKumtfH7yK6ws1ZuQY9tBy5ixZYT0NbSwvjB7dCvS1OlFvRISknHx/QvheZ5/Pgx2JdXMGYfUKtGRYnjqqJj+rI9uBr9FJUcrBAyrrvSSwKTDtKhyjref5CMmdHW1oZAIIBlOROsnz9YytlCUtM/4+9/IxD7KAF21uYY3rclatespJSOh8/eYOnGo/j85RsaulfFoB5+sCone6OWguTk8HH0XAx2Hr4KLR4P/bo2QTtfd+jqyt4sSB11ZH7NRuCktYiMjCx0IxtVwtraGpUrV5Z6jBbVKYCyi+pMnL8dJ6Us1bllyTCFfkxKYqlOeSvoSVtURxV1iFBm6VTSIYR05Munojryf08VWfBKVXVw9ql5fXD2/b8OUZ709PRi2eynrKGpdzK4/SBebp4bd55zN9z+teNx89A8zBoj3DZy0JT14PMFcsvoN+4vAMINN67sC8aFXTPhVk24beOw6Zvkns/nC7gvjmkRV/xTNR2/j+yCmKMLsH+tcCevE5F3cSv2P9JBOjRCh0dtJ1SpUkVmC0xddGhKfRRFhzpCzl4GU5eEyc0ze8U+AMIbzqWqA4wN9dGrozeaeAl3wboaU/g+1owxPH/5HgBwcP0ElDMzho2lGXatHgMAuPPwpcy9l0XcuPMcANDEqwaMDPULzasuOvp1bQp9PV24VHXAvrXjAADj5v5DOkiHRuj494//ISwsDH///bfca6uyDk2pj6LoUEfI2csgLSNTbp5Xb1MAAFUq2YilN/VyAQCkfPxc6Pl8Qd4TaP5tNEV7ahfMI433KcLxP7/GbnLtlYUq6xDtBS4vHgEgHdJsJB2qq0MZVFmHptSHMjrUEXL2MmjhXUtuHh9P4ZPkvuM3uDTGGBavOwwAcgNOdLTzAlqSUzO4//PfrPnzSKNWdWGg3fy/wuXaKwtV05H/qfrImWgAQJtmdQs9HyAd0mwkHaqrIz81a9ZEHbfqcP3/ruSCqLIOTakPZXSoIxSgVwBRgN6RTZPhXNm20LxJKenw7zMPgPAG9Pd2E3O6D04vlXu9LXsuYPmmYwCAgT18oaujgw1hZwEAw/u1wujAtnLLqNVmMvd/o0aNYG5ujjlz5kjkkxUEpIo6fhveGZdvPcaVW8IuuXM7Z8iNfCYdpENddAybuFgij7wFr1RRh6bUhzQdmhagR86+AMpG48uKLL26PwTmpkZyz2eM4felu3H4/59sRXRr2wBzJvRQqNsv/VMmfH6eDQC4fv26zHyFRfyqmo78KBphC5AOEaQjD1XUIe2hXJ6zV0UdItS9PkTk10HOXsMpyn72fL4AN+48R1JKBmpVr4jqVeyVvm76p0xcjX4KvoChWYOaCt2wBXn+8j3s6nSXeVze9B5V0nH/yStYWZjAx6OG2FiaIpCOPEhHHqqio13QIqR/+ioxRVbRpaxVRYem1IcsHeTsNZyiOHtV4pNZM5nHFJnLSxBEydKi7zxuD4uiOHuidNA0Z08r6BEEQZQxkyZNQnrqe1iZ6eLvOQPL2hxCAyFnr0EMnLwOyRlrYGlpKXUO765du6CblQCD7NdlYB1BELJ48uQJ1+tGECUBOXsN4uWbD3j/IR2fP0ufZ2psbAw9HSPo66jf8ARBEARRdGiePUEQBEFoONSyJwiCKAOSk5PRqVMnAEBKSkoZW0NoOtSy/4HYuXMn1oXuxdZ9kWVtCkH8sAzoljdjJjk5GcnJyRBo4PKshGpBLXsFEX0ZtbSK/nyUy+dDW0uryOtjM8bAFwiKvJRjWFgYkpOTYWtthqDuvkUqAyh7HYBm1AdAOvLzo+gI6u6LLANnhIWJb7alxbJhbWGqNjrkoSk6NAVy9nK4//QVeo1aJZYWtnI06roqtj0lYwyheyO5pRkBoJqjHXasGKXwPP7PX75h2PRNuPPwJZc2rG9LjA5sW6QbOOlDBmq1mayWOjSlPkiHkB9VR9++fdG3b1+xNN67CAybvgm1205RGx3SUMf6kMbnzG8K5VMXaFGdAuRfVOe/hCT0Gbtaar49f41FrRoV5ZY3bckuiSUZRdw+uhB6eoU/b2Vn56J+x2lSj3Vr2wBzJ/bk3starEOEaFGd/KiiDlnEPkpQq/qQBenI40fVIW3xq8aNG0s9X5V1FERd66Mg+XVoyqI6NGZfCKIb7s+Zv+DB6aV4cHop/pz5CwCg56iVcs9P/5TJ3XAXds3Eg9NLcf/UElR3Ei7r+G/4Jbll7Dh0GYBwt6jYE4vx4PRSXNwtXFf6wKkopH+SvxVvQeyszdVSh6bUB+kgHbJQdx2aUh8iHZqEWjj7+Ph4DB48GFWqVIGhoSGqVq2K2bNnIzs7WyxfQkICOnXqBGNjY1hbW2PMmDESeRQlf8BM/m0X8/8vL6jmarRwJ6dBPf1gYyl8MuTxeNi6bDgA4I9Nx+Xa8efmEwCAv+cO5NaOtrIwwdA+LQEAl6KeyC1DGuqmQ1Pqg3SQjsJQdx2aUh8iHZqEWozZP378GAKBAOvXr0e1atVw//59DBkyBF++fMGyZcsAAHw+Hx06dICNjQ0uX76MlJQUBAYGgjGG1auldwmVNHy+8KbU1REPUMnJ4QMAdBTY+IEvkFFGbi4AQFsrbwxseL9W+MgqwMhI+U0pCrWhlHWUFKQjXxmko9goDh0i1F2HptQHX84DhTqiFi37gIAAhIaGok2bNnB2dkbnzp0xadIkHDhwgMtz+vRpPHz4ENu3b0f9+vXRqlUrLF++HBs3bkRGRobMsrOyspCRkSH2AsSjP09fipX6v7wI0WYNXQAA63eeRcpH4ap2fL4AI2duAQCMH9xervZxg9oBAIImrYMovCI5NQOhe4XT53w8a3B5e3ZojL59+6Jr165yy1VlHdJQx/ogHaRDUR0i1F2HptSHSIcmobYBejNmzMDJkydx69YtAMCsWbNw6NAh3L17l8vz8eNHWFpa4ty5c/D395daTnBwMEJCQiTSbxyci5dvPsgcI1I0MnTG8j04eCpK6rHvDXjp3MoTC6f0FktTZNe7/KiqDmk8ePpa7epDGqQjjx9VhzIBeqqsoyDqWh8FoQA9FeHFixdYvXo1hg8fzqUlJibCzs5OLJ+FhQX09PSQmJgos6xp06YhPT2de7169Yo7VqtGRYStHC1xzp6/xio8BWTuhB4Y3q+VWFr9Wk64GT5X7g0HAHp6OrhxcC4XXCJi0pAOWDC5l0I2yELddGhKfZCOPEhHHpqgQ1PqQ09PB2d3TFfoWupCmbbsZbWq8xMVFQUvLy/u/du3b+Hr6wtfX19s2rSJSx86dChevnyJU6dOiZ2vp6eHf/75B717y3+iBGTvZ68KizvIW6QiOSUDGcYNoKWlBWtra4nj3Daapjr4e+6gItkA0GIbIkhHHqQjD0V0SGvZm2YIo8TVSUdhqLsO2s++GBk1apRcJ+zk5MT9//btW/j7+8Pb2xsbNmwQy2dvb48bN26IpX38+BE5OTkSLf6i8D03m4jvuekBYURpYWX0Gr2q0Hn2y5Ytg17WS+hnJXyXHSWtQxHUoT4UgXTkQTqEkI48VEGHplCmzt7a2lpqC1Qab968gb+/Pzw9PREaGipxE3h7e2P+/Pl49+4dypcvD0AYtKevrw9PT89it50gCIIg1AW1mHr39u1b+Pn5oXLlyli2bJlYkJm9vXBsqE2bNnBzc8Mvv/yCpUuXIjU1FZMmTcKQIUM0oguGIAiCIIqKWjj706dP4/nz53j+/DkqVhRfKlEUcqCtrY1jx45h5MiRaNKkCQwNDdG3b19uHj5BEARB/KiohbMPCgpCUFCQ3HyVK1fG0aNHS94gNYUL0DPTxd9zBpa1OQRBEEQpoRbOvjQR9RSo445HAsH/L2KRnIwOHTpIHE9NTQVjDDaWZvj8Rf30EYSm8EX7i0Qaj76TKoXIB6jpUjQSqO2iOiXFf//9h6pVq5a1GQRBEIQK8OrVK4nhY3WEWvYFsLS0BCDcVMfc3LyMrfk+MjIyUKlSJbx69UojghRJj+qiSVoA0qPKlJYWxhg+ffoEBweHErtGaULOvgCiKX3m5uZq/6UQYWZmpjFaANKjymiSFoD0qDKloUXdG3z5UcvlcgmCIAiCUBxy9gRBEASh4ZCzL4C+vj5mz54NfX39sjblu9EkLQDpUWU0SQtAelQZTdJSmlA0PkEQBEFoONSyJwiCIAgNh5w9QRAEQWg45OwJgiAIQsMhZ08QBEEQGg45ewDx8fEYPHgwqlSpAkNDQ1StWhWzZ89Gdna2WL6EhAR06tQJxsbGsLa2xpgxYyTyqBJr1qxBlSpVYGBgAE9PT1y6dKmsTZLLwoUL0aBBA5iamsLW1hZdu3bFkydPxPIwxhAcHAwHBwcYGhrCz88PDx48KCOLFWfhwoXg8XgYN24cl6ZuWt68eYP+/fvDysoKRkZGcHd3R3R0NHdcnfTk5uZixowZ3Pfe2dkZc+bMgUAg4PKosp6LFy+iU6dOcHBwAI/HQ3h4uNhxRWzPysrC6NGjYW1tDWNjY3Tu3BmvX78uRRV5FKYnJycHv/32G+rUqQNjY2M4ODhgwIABePv2rVgZqqRH5WAEO3HiBAsKCmKnTp1iL168YIcOHWK2trZs4sSJXJ7c3FxWu3Zt5u/vz2JiYlhERARzcHBgo0aNKkPLZbNr1y6mq6vLNm7cyB4+fMjGjh3LjI2N2cuXL8vatEJp27YtCw0NZffv32d37txhHTp0YJUrV2afP3/m8ixatIiZmpqy/fv3s3v37rFevXqx8uXLs4yMjDK0vHBu3rzJnJycWN26ddnYsWO5dHXSkpqayhwdHVlQUBC7ceMGi4uLY2fOnGHPnz/n8qiTnnnz5jErKyt29OhRFhcXx/bu3ctMTEzYihUruDyqrOf48eNs+vTpbP/+/QwAO3jwoNhxRWwfPnw4q1ChAouIiGAxMTHM39+f1atXj+Xm5paymsL1pKWlsVatWrHdu3ezx48fs2vXrrFGjRoxT09PsTJUSY+qQc5eBkuWLGFVqlTh3h8/fpxpaWmxN2/ecGlhYWFMX1+fpaenl4WJhdKwYUM2fPhwsTQXFxc2derUMrKoaCQlJTEALDIykjHGmEAgYPb29mzRokVcnm/fvjFzc3O2bt26sjKzUD59+sSqV6/OIiIimK+vL+fs1U3Lb7/9xpo2bSrzuLrp6dChAxs0aJBYWrdu3Vj//v0ZY+qlp6BzVMT2tLQ0pqury3bt2sXlefPmDdPS0mInT54sNdulIe3hpSA3b95kALgGjCrrUQWoG18G6enp3KY4AHDt2jXUrl1bbFOEtm3bIisrS6wbUxXIzs5GdHQ02rRpI5bepk0bXL16tYysKhrp6ekA8jYoiouLQ2Jiopg2fX19+Pr6qqy2//3vf+jQoQNatWollq5uWg4fPgwvLy/06NEDtra2qF+/PjZu3MgdVzc9TZs2xdmzZ/H06VMAwN27d3H58mW0b98egPrpyY8itkdHRyMnJ0csj4ODA2rXrq3y+gDhbwOPx0O5cuUAqL+ekoY2wpHCixcvsHr1aixfvpxLS0xMhJ2dnVg+CwsL6OnpITExsbRNLJQPHz6Az+dL2GtnZ6dythYGYwwTJkxA06ZNUbt2bQDg7Jem7eXLl6Vuozx27dqFmJgYREVFSRxTNy3//fcf1q5diwkTJuD333/HzZs3MWbMGOjr62PAgAFqp+e3335Deno6XFxcoK2tDT6fj/nz56NPnz4A1K9+8qOI7YmJidDT04OFhYVEHlX/nfj27RumTp2Kvn37cpvhqLOe0kCjW/bBwcHg8XiFvm7duiV2ztu3bxEQEIAePXrg119/FTvG4/EkrsEYk5quChS0S5VtlcaoUaMQGxuLsLAwiWPqoO3Vq1cYO3Ystm/fDgMDA5n51EELAAgEAnh4eGDBggWoX78+hg0bhiFDhmDt2rVi+dRFz+7du7F9+3bs3LkTMTEx2LZtG5YtW4Zt27aJ5VMXPdIoiu2qri8nJwe9e/eGQCDAmjVr5OZXdT2lhUa37EeNGoXevXsXmsfJyYn7/+3bt/D394e3tzc2bNggls/e3h43btwQS/v48SNycnIknp7LGmtra2hra0s8zSYlJamcrbIYPXo0Dh8+jIsXL6JixYpcur29PQDhU3z58uW5dFXUFh0djaSkJHh6enJpfD4fFy9exF9//cXNMlAHLQBQvnx5uLm5iaW5urpi//79ANSrbgBg8uTJmDp1KvcbUadOHbx8+RILFy5EYGCg2unJjyK229vbIzs7Gx8/fhRrDSclJcHHx6d0DVaQnJwc9OzZE3FxcTh37pzYFrfqqKc00eiWvbW1NVxcXAp9iVpcb968gZ+fHzw8PBAaGsrtay/C29sb9+/fx7t377i006dPQ19fX+zHXBXQ09ODp6cnIiIixNIjIiJU/qZnjGHUqFE4cOAAzp07hypVqogdr1KlCuzt7cW0ZWdnIzIyUuW0tWzZEvfu3cOdO3e4l5eXF/r164c7d+7A2dlZbbQAQJMmTSSmQT59+hSOjo4A1KtuACAzM1Pie66trc1NvVM3PflRxHZPT0/o6uqK5Xn37h3u37+vkvpEjv7Zs2c4c+YMrKysxI6rm55Sp4wCA1WKN2/esGrVqrEWLVqw169fs3fv3nEvEaKpdy1btmQxMTHszJkzrGLFiio/9W7z5s3s4cOHbNy4cczY2JjFx8eXtWmFMmLECGZubs4uXLggVg+ZmZlcnkWLFjFzc3N24MABdu/ePdanTx+VmQ4lj/zR+Iypl5abN28yHR0dNn/+fPbs2TO2Y8cOZmRkxLZv387lUSc9gYGBrEKFCtzUuwMHDjBra2s2ZcoULo8q6/n06RO7ffs2u337NgPA/vjjD3b79m0uOl0R24cPH84qVqzIzpw5w2JiYliLFi3KbKpaYXpycnJY586dWcWKFdmdO3fEfhuysrJUUo+qQc6eMRYaGsoASH3l5+XLl6xDhw7M0NCQWVpaslGjRrFv376VkdXy+fvvv5mjoyPT09NjHh4e3PQ1VUZWPYSGhnJ5BAIBmz17NrO3t2f6+vqsefPm7N69e2VntBIUdPbqpuXIkSOsdu3aTF9fn7m4uLANGzaIHVcnPRkZGWzs2LGscuXKzMDAgDk7O7Pp06eLOQ9V1nP+/Hmp35XAwEDGmGK2f/36lY0aNYpZWloyQ0ND1rFjR5aQkFAGagrXExcXJ/O34fz58yqpR9WgLW4JgiAIQsPR6DF7giAIgiDI2RMEQRCExkPOniAIgiA0HHL2BEEQBKHhkLMnCIIgCA2HnD1BEARBaDjk7AmCIAhCwyFnTxAEQRAaDjl7glBBeDwewsPDy9qMYicoKIjbcfJ79eXf1XLFihXFYh9BaCrk7AmilMjv6HR1dWFnZ4fWrVtjy5Yt3OYrIt69e4d27dopVK66PRgEBAQopU8WkyZNwrt378R2RSQIQjrk7AmiFBE5uvj4eJw4cQL+/v4YO3YsOnbsiNzcXC6fvb099PX1y9DSkkNfX79Y9JmYmMDe3h7a2trFZBlBaC7k7AmiFBE5ugoVKsDDwwO///47Dh06hBMnTmDr1q1cvvyt9ezsbIwaNQrly5eHgYEBnJycsHDhQgCAk5MTAOCnn34Cj8fj3r948QJdunSBnZ0dTExM0KBBA5w5c0bMFicnJyxYsACDBg2CqakpKleujA0bNojlef36NXr37g1LS0sYGxvDy8sLN27c4I4fOXIEnp6eMDAwgLOzM0JCQsQeWhQhPj4ePB4Pe/bsQbNmzWBoaIgGDRrg6dOniIqKgpeXF0xMTBAQEIDk5GSlyiYIQgg5e4IoY1q0aIF69erhwIEDUo+vWrUKhw8fxp49e/DkyRNs376dc+pRUVEAgNDQULx79457//nzZ7Rv3x5nzpzB7du30bZtW3Tq1AkJCQliZS9fvhxeXl64ffs2Ro4ciREjRuDx48dcGb6+vnj79i0OHz6Mu3fvYsqUKdyQw6lTp9C/f3+MGTMGDx8+xPr167F161bMnz+/SJ/D7NmzMWPGDMTExEBHRwd9+vTBlClTsHLlSly6dAkvXrzArFmzilQ2QfzwlPW2ewTxoxAYGMi6dOki9VivXr2Yq6sr9x4AO3jwIGOMsdGjR7MWLVowgUAg9dz8eQvDzc2NrV69mnvv6OjI+vfvz70XCATM1taWrV27ljHG2Pr165mpqSlLSUmRWl6zZs3YggULxNL+/fdfVr58eZk2SPsMRNuXbtq0iUsLCwtjANjZs2e5tIULF7KaNWtKlOno6Mj+/PNPmdckCIIxnbJ91CAIAgAYY+DxeFKPBQUFoXXr1qhZsyYCAgLQsWNHtGnTptDyvnz5gpCQEBw9ehRv375Fbm4uvn79KtGyr1u3Lvc/j8eDvb09kpKSAAB37txB/fr1YWlpKfUa0dHRiIqKEmvJ8/l8fPv2DZmZmTAyMlJIuzRb7OzsAAB16tQRSxPZRhCEcpCzJwgV4NGjR6hSpYrUYx4eHoiLi8OJEydw5swZ9OzZE61atcK+fftkljd58mScOnUKy5YtQ7Vq1WBoaIju3bsjOztbLJ+urq7Yex6Px3XTGxoaFmqzQCBASEgIunXrJnHMwMCg0HOlkd8W0YNPwbSCsxYIglAMcvYEUcacO3cO9+7dw/jx42XmMTMzQ69evdCrVy90794dAQEBSE1NhaWlJXR1dcHn88XyX7p0CUFBQfjpp58ACMff4+PjlbKrbt262LRpE3edgnh4eODJkyeoVq2aUuUSBFH6kLMniFIkKysLiYmJ4PP5eP/+PU6ePImFCxeiY8eOGDBggNRz/vzzT5QvXx7u7u7Q0tLC3r17YW9vj3LlygEQRtWfPXsWTZo0gb6+PiwsLFCtWjUcOHAAnTp1Ao/Hw8yZM5VuFffp0wcLFixA165dsXDhQpQvXx63b9+Gg4MDvL29MWvWLHTs2BGVKlVCjx49oKWlhdjYWNy7dw/z5s373o+KIIhihKLxCaIUOXnyJMqXLw8nJycEBATg/PnzWLVqFQ4dOiRzvriJiQkWL14MLy8vNGjQAPHx8Th+/Di0tIRf3+XLlyMiIgKVKlVC/fr1AQgfECwsLODj44NOnTqhbdu28PDwUMpWPT09nD59Gra2tmjfvj3q1KmDRYsWcXa2bdsWR48eRUREBBo0aIDGjRvjjz/+gKOj43d8QgRBlAQ8xhgrayMIgvgxCAoKQlpaWrGu+Ofk5IRx48Zh3LhxxVYmQWga1LInCKJUOXr0KExMTHD06NHvKmfBggUwMTGRmGFAEIQk1LInCKLUSEpKQkZGBgCgfPnyMDY2LnJZqampSE1NBQDY2NjA3Ny8WGwkCE2EnD1BEARBaDjUjU8QBEEQGg45e4IgCILQcMjZEwRBEISGQ86eIAiCIDQccvYEQRAEoeGQsycIgiAIDYecPUEQBEFoOOTsCYIgCELD+T+i0pp1woMN2wAAAABJRU5ErkJggg==", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "\n", "##Now printing the conceptual model figure:\n", "\n", "fig = plt.figure()\n", "ax = fig.add_subplot(1, 1, 1)\n", "# sky\n", "sky = plt.Rectangle((-20, 2), width=150, height=5, fc=\"b\", zorder=0, alpha=0.1)\n", "ax.add_patch(sky)\n", "\n", "# Aquifer:\n", "ground = plt.Rectangle(\n", " (-20, -6),\n", " width=150,\n", " height=8,\n", " fc=np.array([209, 179, 127]) / 255,\n", " zorder=0,\n", " alpha=0.9,\n", " hatch=\".\",\n", ")\n", "ax.add_patch(ground)\n", "\n", "# Aquifer 2:\n", "ground2 = plt.Rectangle(\n", " (-20, -21),\n", " width=150,\n", " height=15,\n", " fc=np.array([209, 179, 127]) / 255,\n", " zorder=0,\n", " alpha=0.9,\n", " hatch=\"o\",\n", ")\n", "ax.add_patch(ground2)\n", "\n", "\n", "well = plt.Rectangle(\n", " (-1.5, -21), width=3, height=23, fc=np.array([200, 200, 200]) / 255, zorder=1\n", ")\n", "ax.add_patch(well)\n", "\n", "# Wellhead\n", "wellhead = plt.Rectangle(\n", " (-2, 2), width=4, height=2.5, fc=np.array([200, 200, 200]) / 255, zorder=2, ec=\"k\"\n", ")\n", "ax.add_patch(wellhead)\n", "\n", "# Screen for the well:\n", "screen = plt.Rectangle(\n", " (-1.5, -21),\n", " width=3,\n", " height=11,\n", " fc=np.array([200, 200, 200]) / 255,\n", " alpha=1,\n", " zorder=2,\n", " ec=\"k\",\n", " ls=\"--\",\n", ")\n", "screen.set_linewidth(2)\n", "ax.add_patch(screen)\n", "pumping_arrow = plt.Arrow(x=2, y=3.5, dx=5, dy=0, color=\"#00035b\")\n", "ax.add_patch(pumping_arrow)\n", "ax.text(x=7, y=3.5, s=r\"$ Q = 873$ m$^3$/d\", fontsize=\"large\")\n", "\n", "# Piezometers\n", "piez1 = plt.Rectangle(\n", " (89, -21), width=2, height=23, fc=np.array([200, 200, 200]) / 255, zorder=1\n", ")\n", "screen_piez_1 = plt.Rectangle(\n", " (89, -19),\n", " width=2,\n", " height=7,\n", " fc=np.array([200, 200, 200]) / 255,\n", " alpha=1,\n", " zorder=2,\n", " ec=\"k\",\n", " ls=\"--\",\n", ")\n", "screen_piez_1.set_linewidth(2)\n", "screen_piez_2 = plt.Rectangle(\n", " (89, -3),\n", " width=2,\n", " height=0.5,\n", " fc=np.array([200, 200, 200]) / 255,\n", " alpha=1,\n", " zorder=2,\n", " ec=\"k\",\n", " ls=\"--\",\n", ")\n", "screen_piez_2.set_linewidth(2)\n", "\n", "ax.add_patch(piez1)\n", "ax.add_patch(screen_piez_1)\n", "ax.add_patch(screen_piez_2)\n", "\n", "\n", "# last line\n", "line = plt.Line2D(xdata=[-200, 1200], ydata=[2, 2], color=\"k\")\n", "ax.add_line(line)\n", "\n", "# Water table\n", "line2 = plt.Line2D(xdata=[-200, 1200], ydata=[0, 0], color=\"b\")\n", "ax.add_line(line2)\n", "\n", "ax.text(-18, 0.5, s=\"Water Table\", fontsize=\"large\", color=\"b\", bbox={\"fc\": \"w\"})\n", "ax.text(93, -3, s=\"Shallow piezometer\", bbox={\"fc\": \"w\"})\n", "ax.text(93, -16, s=\"Deeper piezometer\", bbox={\"fc\": \"w\"})\n", "\n", "ax.set_xlim([-20, 130])\n", "ax.set_ylim([-21, 7])\n", "ax.set_xlabel(\"Distance [m]\")\n", "ax.set_ylabel(\"Relative height [m]\")\n", "ax.set_title(\"Conceptual Model - Vennebulten Example\");" ] }, { "cell_type": "markdown", "metadata": { "editable": true, "slideshow": { "slide_type": "" }, "tags": [] }, "source": [ "### Set basic parameters" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "b = -21 # aquifer thickness, m\n", "r = 90 # distance from observation wells to pumping well, m\n", "Q = 873 # constant discharge, m^3/d" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Load data of the two piezometers" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "data1 = np.loadtxt(\"data/venne_shallow.txt\", skiprows=1)\n", "ts = data1[:, 0] / 60 / 24 # convert min to days\n", "hs = data1[:, 1]\n", "\n", "data2 = np.loadtxt(\"data/venne_deep.txt\", skiprows=1)\n", "td = data2[:, 0] / 60 / 24 # convert min to days\n", "hd = data2[:, 1]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Create a conceptual one-layer model\n", "\n", "Both Kruseman et al. (1970) and AQTESOLV solutions that use the Neuman method (Neumann, 1969) assume a one layer unconfined model.\n", "To compare TTim with both, we begin by modelling a one-layer aquifer.\n", "\n", "For the unconfined test, the preferred method for modelling is to use the ```Model3D``` class. ```Model3D``` assumes the system is a vertical stacking of aquifer layers. Vertical flow is computed between layers by calculating the vertical resistance between layers. Vertical resistance between the aquifer layers is determined as the resistance from the middle of one layer to the middle of the next layer. The vertical anisotropy can be specified for each layer.\n", "\n", "Model construction is similar to the ```ModelMaq``` class. We detail it below:\n", "\n", "For our Model3D model, we have to set:\n", "\n", "- The hydraulic conductivity: ```kaq```. It is a list/array with a float element for every aquifer, for example: ```[kaq0,kaq1]```. We can also set a float value. In this case, the same ```kaq``` is assumed for every layer.\n", "- The top and bottom of each aquifer: ```z``` defined by a list/array ```[zt0,zb0,zt1,zb1,...]```, where the inputs are a sequence of top and bottoms of the aquifer layers.\n", "- The specific storage: ```Saq```. It is a list/array with a float element for every aquifer, for example: ```[Saq0, Saq1]```. We can also set a float value. In this case, the same ```Saq``` is assumed for every layer.\n", "- The minimum time for which TTim solve the groundwater flow: ```tmin```, a float.\n", "- And the maximum time: ```tmax```, float.\n", "- TTim automatically assumes the ```topboundary``` is confined. In this case, we also assume the ```topboundary``` is confined, so we do not need to set this parameter. In the code example, the parameter is set for clarity.\n", "- The vertical anisotropy, defined by the parameter: ```kzoverkh```, which means the vertical hydraulic conductivity divided by the horizontal conductivity. This parameter is a list/array with a float element for every aquifer, for example: ```[kzoverkh0,kzoverkh1]```. We can also set a float value. In this case, the same ```kzoverkh``` is assumed for every layer. If one does not set this parameter, a isotropic model is considered: ```kzoverkh = 1```\n", "- ```phreatictop```: Is a boolean (True/False). If ```True```, the first element in ```Saq``` is considered phreatic storage (Specific Yield) and is not multiplied by the layer thickness. The default value is ```True```. This parameter is relevant for the unconfined aquifer test, and we will show underneath how to set it." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To reproduce the one-layer aquifer model in Kruseman et al. (1970), we will build a two-layer Model3D model. The first layer is a very thin (0.1 m thick) layer with phreatic storage, followed by the 21 m thick aquifer layer. This thin layer is how TTim accounts for the water table storage in the unconfined situation. The first conceptual model is represented in the image below.\n" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "jupyter": { "source_hidden": true }, "tags": [] }, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Model Figure - One - layer model\n", "fig = plt.figure()\n", "ax = fig.add_subplot(1, 1, 1)\n", "\n", "\n", "# Aquifer:\n", "ground = plt.Rectangle(\n", " (-20, -21), width=150, height=23, fc=\"w\", zorder=0, alpha=0.9, hatch=\".\"\n", ")\n", "ax.add_patch(ground)\n", "\n", "well = plt.Rectangle((-1.5, -21), width=3, height=23, fc=\"w\", zorder=1, ec=\"k\")\n", "ax.add_patch(well)\n", "\n", "# Wellhead\n", "wellhead = plt.Rectangle((-2, 2), width=4, height=2.5, fc=\"w\", zorder=2, ec=\"k\")\n", "ax.add_patch(wellhead)\n", "\n", "# Screen for the well:\n", "screen = plt.Rectangle(\n", " (-1.5, -21), width=3, height=11, fc=\"w\", alpha=1, zorder=2, ec=\"k\", ls=\"--\"\n", ")\n", "screen.set_linewidth(2)\n", "ax.add_patch(screen)\n", "\n", "# Piezometers\n", "piez1 = plt.Rectangle((89, -21), width=2, height=23, fc=\"w\", zorder=1, ec=\"k\")\n", "screen_piez_1 = plt.Rectangle(\n", " (89, -19), width=2, height=7, fc=\"w\", alpha=1, zorder=2, ec=\"k\", ls=\"--\"\n", ")\n", "screen_piez_1.set_linewidth(2)\n", "screen_piez_2 = plt.Rectangle(\n", " (89, -3), width=2, height=0.5, fc=\"w\", alpha=1, zorder=2, ec=\"k\", ls=\"--\"\n", ")\n", "screen_piez_2.set_linewidth(2)\n", "\n", "ax.add_patch(piez1)\n", "ax.add_patch(screen_piez_1)\n", "ax.add_patch(screen_piez_2)\n", "\n", "\n", "# last line\n", "line = plt.Line2D(xdata=[-200, 1200], ydata=[2, 2], color=\"k\")\n", "ax.add_line(line)\n", "\n", "# Water table\n", "line2 = plt.Line2D(xdata=[-200, 1200], ydata=[0, 0], color=\"b\")\n", "ax.add_line(line2)\n", "\n", "ax.text(-18, 0.5, s=\"Water Table\", fontsize=\"large\", color=\"b\", bbox={\"fc\": \"w\"})\n", "ax.text(93, -3, s=\"Shallow piezometer\", bbox={\"fc\": \"w\"})\n", "ax.text(93, -16, s=\"Deeper piezometer\", bbox={\"fc\": \"w\"})\n", "\n", "ax.set_xlim([-20, 130])\n", "ax.set_ylim([-21, 7])\n", "ax.set_xlabel(\"Distance [m]\")\n", "ax.set_ylabel(\"Relative height [m]\")\n", "ax.set_title(\"Conceptual Model 1 - Vennebulten Example\");" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "self.neq 1\n", "solution complete\n" ] } ], "source": [ "ml_1 = ttm.Model3D(\n", " kaq=10,\n", " z=[0, -0.1, b],\n", " Saq=[0.1, 1e-4],\n", " tmin=1e-4,\n", " tmax=1.1,\n", " kzoverkh=1,\n", " phreatictop=True,\n", ")\n", "w_1 = ttm.Well(ml_1, xw=0, yw=0, rw=0.1, tsandQ=[(0, Q)])\n", "ml_1.solve()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Calibrate the one layer model with the shallow piezometer" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We begin the initial model by adding the shallow observation well as the observation for the residuals calibration. And we calibrate hydraulic conductivity, specific yield and specific storage of our one layer unconfined aquifer:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ ".....................................................................................................................................................\n", "Fit succeeded.\n" ] } ], "source": [ "# calibrate with data of shallow piezometer\n", "# unknown parameters: kaq, Saq\n", "ca_1 = ttm.Calibrate(ml_1)\n", "ca_1.set_parameter(name=\"kaq0_1\", initial=10)\n", "ca_1.set_parameter(name=\"Saq0\", initial=0.2)\n", "ca_1.set_parameter(name=\"Saq1\", initial=1e-4, pmin=0)\n", "ca_1.set_parameter(name=\"kzoverkh0_1\", initial=1, pmin=1e-5)\n", "ca_1.series(name=\"obs\", x=r, y=0, t=ts, h=hs, layer=0) # shallow piezometer\n", "ca_1.fit()" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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optimalstdperc_stdpminpmaxinitialparray
kaq0_1132.4979475.8501324.415262-infinf10.0000[132.49794744095647, 132.49794744095647]
Saq0-0.0261760.046748178.594011-infinf0.2000[-0.026175550379415664]
Saq10.0021080.002176103.2057880.00000inf0.0001[0.002108316392783749]
kzoverkh0_13.3453793.739321111.7757060.00001inf1.0000[3.3453791717676915, 3.3453791717676915]
\n", "
" ], "text/plain": [ " optimal std perc_std pmin pmax initial \\\n", "kaq0_1 132.497947 5.850132 4.415262 -inf inf 10.0000 \n", "Saq0 -0.026176 0.046748 178.594011 -inf inf 0.2000 \n", "Saq1 0.002108 0.002176 103.205788 0.00000 inf 0.0001 \n", "kzoverkh0_1 3.345379 3.739321 111.775706 0.00001 inf 1.0000 \n", "\n", " parray \n", "kaq0_1 [132.49794744095647, 132.49794744095647] \n", "Saq0 [-0.026175550379415664] \n", "Saq1 [0.002108316392783749] \n", "kzoverkh0_1 [3.3453791717676915, 3.3453791717676915] " ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "RMSE: 0.0030 m\n" ] } ], "source": [ "display(ca_1.parameters)\n", "print(f\"RMSE: {ca_1.rmse():.4f} m\")" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "hs_1 = ml_1.head(r, 0, ts)\n", "hd_1 = ml_1.head(r, 0, td)\n", "plt.semilogx(ts, hs, \".\", label=\"shallow obs\")\n", "plt.semilogx(ts, hs_1[0], label=\"shallow ttim\")\n", "plt.semilogx(td, hd, \".\", label=\"deep obs\")\n", "plt.semilogx(td, hd_1[0], \"--\", label=\"deep ttim\")\n", "plt.xlabel(\"time [d]\")\n", "plt.ylabel(\"drawdown [m]\")\n", "plt.title(\"TTim Unconfined Model Results - Shallow Piezometer\")\n", "plt.legend()\n", "plt.grid()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Calibrate the one layer model with the deeper piezometer" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this second approach, we adjust the model to the deeper piezometer, as done by Kruseman and de Ridder (1970)." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "..................................................................................................................................................................................................................\n", "Fit succeeded.\n" ] } ], "source": [ "# calibrate with data of deeper piezometer\n", "# unknown parameters: kaq, Saq, kzoverkh\n", "ca_2 = ttm.Calibrate(ml_1)\n", "ca_2.set_parameter(name=\"kaq0_1\", initial=10, pmin=1e-8)\n", "ca_2.set_parameter(name=\"Saq1\", initial=1e-4, pmin=1e-5)\n", "ca_2.set_parameter(name=\"Saq0\", initial=0.2, pmin=1e-8)\n", "ca_2.set_parameter(name=\"kzoverkh0_1\", initial=1, pmin=1e-5)\n", "ca_2.series(name=\"obs\", x=r, y=0, t=td, h=hd, layer=0) # deep piezometer\n", "ca_2.fit()" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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optimalstdperc_stdpminpmaxinitialparray
kaq0_1136.8451595.769378e+004.2159901.000000e-08inf10.0000[136.84515923564663, 136.84515923564663]
Saq10.0000109.560501e-080.9560161.000000e-05inf0.0001[1.0000356947981182e-05]
Saq00.0000444.479922e-0610.2541351.000000e-08inf0.2000[4.368892779782474e-05]
kzoverkh0_10.0045365.683402e-0412.5291321.000000e-05inf1.0000[0.004536150130718286, 0.004536150130718286]
\n", "
" ], "text/plain": [ " optimal std perc_std pmin pmax initial \\\n", "kaq0_1 136.845159 5.769378e+00 4.215990 1.000000e-08 inf 10.0000 \n", "Saq1 0.000010 9.560501e-08 0.956016 1.000000e-05 inf 0.0001 \n", "Saq0 0.000044 4.479922e-06 10.254135 1.000000e-08 inf 0.2000 \n", "kzoverkh0_1 0.004536 5.683402e-04 12.529132 1.000000e-05 inf 1.0000 \n", "\n", " parray \n", "kaq0_1 [136.84515923564663, 136.84515923564663] \n", "Saq1 [1.0000356947981182e-05] \n", "Saq0 [4.368892779782474e-05] \n", "kzoverkh0_1 [0.004536150130718286, 0.004536150130718286] " ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "RMSE: 0.0059183857395334405\n" ] } ], "source": [ "display(ca_2.parameters)\n", "print(\"RMSE:\", ca_2.rmse())" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "hd_2 = ml_1.head(r, 0, td)\n", "hs_2 = ml_1.head(r, 0, ts)\n", "plt.semilogx(td, hd, \".\", label=\"deep obs\")\n", "plt.semilogx(td, hd_2[0], label=\"deep ttim\")\n", "plt.semilogx(ts, hs, \".\", label=\"shallow obs\")\n", "plt.semilogx(ts, hs_2[0], \"--\", label=\"shallow ttim\")\n", "plt.xlabel(\"time [d]\")\n", "plt.ylabel(\"drawdown [m]\")\n", "plt.title(\"TTim Unconfined Model Results - Deeper Piezometer\")\n", "plt.legend();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Create a conceptual model with n-layers\n", "\n", "As we can see in the examples of step 5, the single-layer simplification does not represent the system well as we have a vertical component to flow, shown in the head difference between both piezometers.\n", "\n", "We now explore the feature of TTim to create a multi-layer model to represent better the unconfined system and simulate the vertical flow component. We will discretize the aquifer in a 21 layer model, with 1 m thick each." ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "jupyter": { "source_hidden": true }, "tags": [] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Model Figure - One - layer model\n", "fig = plt.figure()\n", "ax = fig.add_subplot(1, 1, 1)\n", "\n", "\n", "# Aquifer:\n", "for i in range(21, -2, -1):\n", " ground = plt.Rectangle(\n", " (-20, -i),\n", " width=150,\n", " height=1,\n", " fc=\"w\",\n", " zorder=0,\n", " alpha=0.9,\n", " hatch=\"..\",\n", " ec=\"k\",\n", " ls=\"--\",\n", " )\n", " ax.add_patch(ground)\n", "\n", "\n", "well = plt.Rectangle((-1.5, -21), width=3, height=23, fc=\"w\", zorder=1, ec=\"k\")\n", "ax.add_patch(well)\n", "\n", "# Wellhead\n", "wellhead = plt.Rectangle((-2, 2), width=4, height=2.5, fc=\"w\", zorder=2, ec=\"k\")\n", "ax.add_patch(wellhead)\n", "\n", "# Screen for the well:\n", "screen = plt.Rectangle(\n", " (-1.5, -21),\n", " width=3,\n", " height=11,\n", " fc=\"w\",\n", " alpha=1,\n", " zorder=2,\n", " ec=\"k\",\n", " ls=\"--\",\n", " hatch=\"-\",\n", ")\n", "screen.set_linewidth(2)\n", "ax.add_patch(screen)\n", "\n", "# Piezometers\n", "piez1 = plt.Rectangle((89, -21), width=2, height=23, fc=\"w\", zorder=1, ec=\"k\")\n", "screen_piez_1 = plt.Rectangle(\n", " (89, -19), width=2, height=7, fc=\"w\", alpha=1, zorder=2, ec=\"k\", ls=\"--\", hatch=\"-\"\n", ")\n", "screen_piez_1.set_linewidth(2)\n", "screen_piez_2 = plt.Rectangle(\n", " (89, -3), width=2, height=0.5, fc=\"w\", alpha=1, zorder=2, ec=\"k\", ls=\"--\", hatch=\"-\"\n", ")\n", "screen_piez_2.set_linewidth(2)\n", "\n", "ax.add_patch(piez1)\n", "ax.add_patch(screen_piez_1)\n", "ax.add_patch(screen_piez_2)\n", "\n", "\n", "# last line\n", "line = plt.Line2D(xdata=[-200, 1200], ydata=[2, 2], color=\"k\")\n", "ax.add_line(line)\n", "\n", "# Water table\n", "line2 = plt.Line2D(xdata=[-200, 1200], ydata=[0, 0], color=\"b\")\n", "ax.add_line(line2)\n", "\n", "ax.text(-18, 0.5, s=\"Water Table\", fontsize=\"large\", color=\"b\", bbox={\"fc\": \"w\"})\n", "ax.text(93, -3, s=\"Shallow piezometer\", bbox={\"fc\": \"w\"})\n", "ax.text(93, -16, s=\"Deeper piezometer\", bbox={\"fc\": \"w\"})\n", "\n", "ax.set_xlim([-20, 130])\n", "ax.set_ylim([-21, 7])\n", "ax.set_xlabel(\"Distance [m]\")\n", "ax.set_ylabel(\"Relative height [m]\")\n", "ax.set_title(\"Conceptual Model 2 - Multi-layer Model 3D - Vennebulten Example\");" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "nlay = 21 # number of layers\n", "zlayers = np.linspace(0, b, nlay + 1) # elevation of each layer\n", "Saq = 1e-4 * np.ones(nlay)\n", "Saq[0] = 0.1 # Setting the first storage as specific yield" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The model is created just as in the previous step, however with the new parameters defined above:" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "self.neq 21\n", "solution complete\n" ] } ], "source": [ "ml_2 = ttm.Model3D(\n", " kaq=10, z=zlayers, Saq=Saq, kzoverkh=0.1, phreatictop=True, tmin=1e-4, tmax=1.1\n", ")\n", "w_2 = ttm.Well(ml_2, xw=0, yw=0, rw=0.1, tsandQ=[(0, Q)], layers=range(nlay))\n", "ml_2.solve()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Calibrate multi-layer model with the two piezometers simultaneously" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In the TTim multi-layer model, we can fit the parameters using data from both piezometers simultaneously.\n", "For this initial assumption, we assume the aquifer has one hydraulic conductivity and storage parameter.\n", "\n", "The unknown parameters are kaq, Saq, kzoverkh.\n", "\n", "Now, on the ```series``` method, we have to remember to set a different layer for each piezometer, corresponding to the depth of the screen." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ ".............................................................\n", "Fit succeeded.\n", "[[Fit Statistics]]\n", " # fitting method = leastsq\n", " # function evals = 58\n", " # data points = 48\n", " # variables = 4\n", " chi-square = 0.00243050\n", " reduced chi-square = 5.5239e-05\n", " Akaike info crit = -466.761301\n", " Bayesian info crit = -459.276496\n", "[[Variables]]\n", " kaq0_20: 59.3574445 +/- 2.85482618 (4.81%) (init = 10)\n", " Saq0: 0.03005722 +/- 0.00252459 (8.40%) (init = 0.2)\n", " Saq1_20: 3.3850e-05 +/- 2.1163e-06 (6.25%) (init = 0.0001)\n", " kzoverkh0_20: 0.00152234 +/- 2.5876e-04 (17.00%) (init = 0.1)\n", "[[Correlations]] (unreported correlations are < 0.100)\n", " C(kaq0_20, kzoverkh0_20) = -0.9548\n", " C(kaq0_20, Saq0) = -0.5934\n", " C(kaq0_20, Saq1_20) = -0.5598\n", " C(Saq0, kzoverkh0_20) = +0.5134\n", " C(Saq1_20, kzoverkh0_20) = +0.4769\n", " C(Saq0, Saq1_20) = +0.3186\n" ] } ], "source": [ "ca_3 = ttm.Calibrate(ml_2)\n", "ca_3.set_parameter(name=\"kaq0_20\", initial=10)\n", "ca_3.set_parameter(name=\"Saq0\", initial=0.2)\n", "ca_3.set_parameter(name=\"Saq1_20\", initial=1e-4)\n", "ca_3.set_parameter(name=\"kzoverkh0_20\", initial=0.1, pmin=1e-5, pmax=0.5)\n", "ca_3.series(name=\"obs1\", x=r, y=0, layer=1, t=ts, h=hs)\n", "ca_3.series(name=\"obs2\", x=r, y=0, layer=15, t=td, h=hd)\n", "ca_3.fit(report=True)" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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optimalstdperc_stdpminpmaxinitialparray
kaq0_2059.3574452.8548264.809550-infinf10.0000[59.357444540804096, 59.357444540804096, 59.35...
Saq00.0300570.0025258.399289-infinf0.2000[0.030057222790710464]
Saq1_200.0000340.0000026.252124-infinf0.0001[3.384998672499465e-05, 3.384998672499465e-05,...
kzoverkh0_200.0015220.00025916.9975960.000010.50.1000[0.001522344436417982, 0.001522344436417982, 0...
\n", "
" ], "text/plain": [ " optimal std perc_std pmin pmax initial \\\n", "kaq0_20 59.357445 2.854826 4.809550 -inf inf 10.0000 \n", "Saq0 0.030057 0.002525 8.399289 -inf inf 0.2000 \n", "Saq1_20 0.000034 0.000002 6.252124 -inf inf 0.0001 \n", "kzoverkh0_20 0.001522 0.000259 16.997596 0.00001 0.5 0.1000 \n", "\n", " parray \n", "kaq0_20 [59.357444540804096, 59.357444540804096, 59.35... \n", "Saq0 [0.030057222790710464] \n", "Saq1_20 [3.384998672499465e-05, 3.384998672499465e-05,... \n", "kzoverkh0_20 [0.001522344436417982, 0.001522344436417982, 0... " ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "RMSE: 0.007115852666850155\n" ] } ], "source": [ "display(ca_3.parameters)\n", "print(\"RMSE:\", ca_3.rmse())" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "hs_3 = ml_2.head(x=r, y=0, t=ts, layers=1)\n", "hd_3 = ml_2.head(x=r, y=0, t=td, layers=15)\n", "plt.semilogx(ts, hs, \".\", label=\"shallow obs\")\n", "plt.semilogx(td, hd, \".\", label=\"deep obs\")\n", "plt.semilogx(ts, hs_3[0], label=\"shallow ttim\")\n", "plt.semilogx(td, hd_3[0], label=\"deep ttim\")\n", "plt.xlabel(\"time [d]\")\n", "plt.ylabel(\"drawdown [m]\")\n", "plt.title(\"TTim Multi - Layer Unconfined Model Results\")\n", "plt.legend()\n", "plt.grid()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We already see significant improvement from the previous single-layer model. The fit is better and the AIC and BIC indicators have also significantly improved.\n", "\n", "What if we take into account the described stratification of the aquifer? In that case, we could try to stratify our model into two: The first 6 m and the deeper layers." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Calibration of the Stratified Model" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this final example, we will assume the storage is distributed according to the sediment stratification in the aquifer. We will adjust two different ```Saq```values, one for the first 6 m of the aquifer and another for the deeper layers. We assume the hydraulic conductivity and the anisotropy is constant." ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "jupyter": { "source_hidden": true }, "tags": [] }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Model Figure - One - layer model\n", "fig = plt.figure()\n", "ax = fig.add_subplot(1, 1, 1)\n", "\n", "\n", "# Aquifer 1:\n", "for i in range(21, 6, -1):\n", " ground = plt.Rectangle(\n", " (-20, -i),\n", " width=150,\n", " height=1,\n", " fc=\"w\",\n", " zorder=0,\n", " alpha=0.9,\n", " hatch=\"oo\",\n", " ec=\"k\",\n", " ls=\"--\",\n", " )\n", " ax.add_patch(ground)\n", "# Aquifer 2:\n", "for i in range(6, -2, -1):\n", " ground = plt.Rectangle(\n", " (-20, -i),\n", " width=150,\n", " height=1,\n", " fc=\"w\",\n", " zorder=0,\n", " alpha=0.9,\n", " hatch=\"..\",\n", " ec=\"k\",\n", " ls=\"--\",\n", " )\n", " ax.add_patch(ground)\n", "\n", "\n", "well = plt.Rectangle((-1.5, -21), width=3, height=23, fc=\"w\", zorder=1, ec=\"k\")\n", "ax.add_patch(well)\n", "\n", "# Wellhead\n", "wellhead = plt.Rectangle((-2, 2), width=4, height=2.5, fc=\"w\", zorder=2, ec=\"k\")\n", "ax.add_patch(wellhead)\n", "\n", "# Screen for the well:\n", "screen = plt.Rectangle(\n", " (-1.5, -21),\n", " width=3,\n", " height=11,\n", " fc=\"w\",\n", " alpha=1,\n", " zorder=2,\n", " ec=\"k\",\n", " ls=\"--\",\n", " hatch=\"-\",\n", ")\n", "screen.set_linewidth(2)\n", "ax.add_patch(screen)\n", "\n", "# Piezometers\n", "piez1 = plt.Rectangle((89, -21), width=2, height=23, fc=\"w\", zorder=1, ec=\"k\")\n", "screen_piez_1 = plt.Rectangle(\n", " (89, -19), width=2, height=7, fc=\"w\", alpha=1, zorder=2, ec=\"k\", ls=\"--\", hatch=\"-\"\n", ")\n", "screen_piez_1.set_linewidth(2)\n", "screen_piez_2 = plt.Rectangle(\n", " (89, -3), width=2, height=0.5, fc=\"w\", alpha=1, zorder=2, ec=\"k\", ls=\"--\", hatch=\"-\"\n", ")\n", "screen_piez_2.set_linewidth(2)\n", "\n", "ax.add_patch(piez1)\n", "ax.add_patch(screen_piez_1)\n", "ax.add_patch(screen_piez_2)\n", "\n", "\n", "# last line\n", "line = plt.Line2D(xdata=[-200, 1200], ydata=[2, 2], color=\"k\")\n", "ax.add_line(line)\n", "\n", "# Water table\n", "line2 = plt.Line2D(xdata=[-200, 1200], ydata=[0, 0], color=\"b\")\n", "ax.add_line(line2)\n", "\n", "ax.text(-18, 0.5, s=\"Water Table\", fontsize=\"large\", color=\"b\", bbox={\"fc\": \"w\"})\n", "ax.text(93, -3, s=\"Shallow piezometer\", bbox={\"fc\": \"w\"})\n", "ax.text(93, -16, s=\"Deeper piezometer\", bbox={\"fc\": \"w\"})\n", "\n", "ax.set_xlim([-20, 130])\n", "ax.set_ylim([-21, 7])\n", "ax.set_xlabel(\"Distance [m]\")\n", "ax.set_ylabel(\"Relative height [m]\")\n", "ax.set_title(\"Conceptual Model 3 - Multi-layer Model 3D - Vennebulten Example\");" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "self.neq 21\n", "solution complete\n" ] } ], "source": [ "ml_3 = ttm.Model3D(\n", " kaq=10, z=zlayers, Saq=Saq, kzoverkh=0.1, phreatictop=True, tmin=1e-4, tmax=1.1\n", ")\n", "w_3 = ttm.Well(ml_3, xw=0, yw=0, rw=0.1, tsandQ=[(0, Q)], layers=range(nlay))\n", "ml_3.solve()" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ ".................................................................................................................\n", "Fit succeeded.\n" ] } ], "source": [ "ca_4 = ttm.Calibrate(ml_3)\n", "ca_4.set_parameter(name=\"kaq0_20\", initial=50)\n", "ca_4.set_parameter(name=\"Saq0\", initial=0.1)\n", "ca_4.set_parameter(name=\"Saq1_7\", initial=1e-4, pmin=0)\n", "ca_4.set_parameter(name=\"Saq7_20\", initial=1e-4, pmin=0)\n", "ca_4.set_parameter(name=\"kzoverkh0_20\", initial=0.1, pmin=1e-5, pmax=0.5)\n", "ca_4.series(name=\"obs1\", x=r, y=0, layer=1, t=ts, h=hs)\n", "ca_4.series(name=\"obs2\", x=r, y=0, layer=15, t=td, h=hd)\n", "ca_4.fit()" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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optimalstdperc_stdpminpmaxinitialparray
kaq0_2073.3714562.9310423.994798-infinf50.0000[73.37145562442105, 73.37145562442105, 73.3714...
Saq00.0212800.0020799.772022-infinf0.1000[0.02128009026680317]
Saq1_70.0004210.00006114.4007140.00000inf0.0001[0.0004206754841473703, 0.0004206754841473703,...
Saq7_200.0000240.0000014.9456120.00000inf0.0001[2.3670441879897197e-05, 2.3670441879897197e-0...
kzoverkh0_200.0004350.00012328.1916600.000010.50.1000[0.0004347006679574145, 0.0004347006679574145,...
\n", "
" ], "text/plain": [ " optimal std perc_std pmin pmax initial \\\n", "kaq0_20 73.371456 2.931042 3.994798 -inf inf 50.0000 \n", "Saq0 0.021280 0.002079 9.772022 -inf inf 0.1000 \n", "Saq1_7 0.000421 0.000061 14.400714 0.00000 inf 0.0001 \n", "Saq7_20 0.000024 0.000001 4.945612 0.00000 inf 0.0001 \n", "kzoverkh0_20 0.000435 0.000123 28.191660 0.00001 0.5 0.1000 \n", "\n", " parray \n", "kaq0_20 [73.37145562442105, 73.37145562442105, 73.3714... \n", "Saq0 [0.02128009026680317] \n", "Saq1_7 [0.0004206754841473703, 0.0004206754841473703,... \n", "Saq7_20 [2.3670441879897197e-05, 2.3670441879897197e-0... \n", "kzoverkh0_20 [0.0004347006679574145, 0.0004347006679574145,... " ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "RMSE: 0.0034378856797220685\n" ] } ], "source": [ "display(ca_4.parameters)\n", "print(\"RMSE:\", ca_4.rmse())" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "hs_4 = ml_3.head(x=r, y=0, t=ts, layers=1)\n", "hd_4 = ml_3.head(x=r, y=0, t=td, layers=15)\n", "plt.semilogx(ts, hs, \".\", label=\"shallow obs\")\n", "plt.semilogx(td, hd, \".\", label=\"deep obs\")\n", "plt.semilogx(ts, hs_4[0], label=\"shallow ttim\")\n", "plt.semilogx(td, hd_4[0], label=\"deep ttim\")\n", "plt.xlabel(\"time [d]\")\n", "plt.ylabel(\"drawdown [m]\")\n", "plt.title(\"TTim Stratified Unconfined Model Results\")\n", "plt.legend()\n", "plt.grid()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here we see that the model fit has significantly improved. AIC and BIC indicators are lower than the previous multi-layer model." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Comparison of results" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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k [m/d]Sy [-]Ss [1/m]kzoverkhRMSE
MLU62.6570.00120.0000280.0025950.013540
ttim-multilayer59.3574450.0300570.0000340.0015220.007116
ttim-stratified Ss73.3714560.021280.0000240.0004350.003438
\n", "
" ], "text/plain": [ " k [m/d] Sy [-] Ss [1/m] kzoverkh RMSE\n", "MLU 62.657 0.0012 0.000028 0.002595 0.013540\n", "ttim-multilayer 59.357445 0.030057 0.000034 0.001522 0.007116\n", "ttim-stratified Ss 73.371456 0.02128 0.000024 0.000435 0.003438" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "t2 = pd.DataFrame(\n", " columns=[\"k [m/d]\", \"Sy [-]\", \"Ss [1/m]\", \"kzoverkh\"],\n", " index=[\"MLU\", \"ttim-multilayer\", \"ttim-stratified Ss\"],\n", ")\n", "t2.loc[\"MLU\"] = [62.657, 0.0012, 2.790e-05, 0.002595]\n", "t2.loc[\"ttim-multilayer\"] = ca_3.parameters[\"optimal\"].values\n", "t2.iloc[2, 0:2] = ca_4.parameters[\"optimal\"].values[0:2]\n", "t2.iloc[2, 2:4] = ca_4.parameters[\"optimal\"].values[3:5]\n", "t2.loc[:, \"RMSE\"] = pd.Series([0.013540, ca_3.rmse(), ca_4.rmse()], index=t2.index)\n", "t2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The multi-layer approach allowed us to fit both piezometers and better represent the vertical component of flow. However, the parameters were sensitive to the conceptualization applied. The stratified model had much larger hydraulic conductivity in comparison to the multi-layer model. In the stratified approach, the fit has significantly improved." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## References\n", "\n", "* Carlson F, Randall J (2012) MLU: a Windows application for the analysis of aquifer tests and the design of well fields in layered systems. Ground Water 50(4):504–510\n", "* Duffield, G.M., 2007. AQTESOLV for Windows Version 4.5 User's Guide, HydroSOLVE, Inc., Reston, VA.\n", "* Kruseman, G.P., De Ridder, N.A., Verweij, J.M., 1970. Analysis and evaluationof pumping test data. volume 11. International institute for land reclamation and improvement The Netherlands.\n", "* Neuman, S.P., Witherspoon, P.A., 1969. Applicability of current theories of flow in leaky aquifers. Water Resources Research 5, 817–829.\n", "* Yang, Xinzhu (2020) Application and comparison of different methodsfor aquifer test analysis using TTim. Master Thesis, Delft University of Technology (TUDelft), Delft, The Netherlands." ] } ], "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": "3.11.4" } }, "nbformat": 4, "nbformat_minor": 4 }