diff --git a/book/thesis_projects/BSc/2024_Q2_ElineMol_CEG/Deliverables/1_introduction_emol.ipynb b/book/thesis_projects/BSc/2024_Q2_ElineMol_CEG/Deliverables/1_introduction_emol.ipynb new file mode 100644 index 0000000..89c321a --- /dev/null +++ b/book/thesis_projects/BSc/2024_Q2_ElineMol_CEG/Deliverables/1_introduction_emol.ipynb @@ -0,0 +1,100 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "213a76bd-9423-4331-9d41-42533d04553f", + "metadata": {}, + "source": [ + "# The Impact of Climate Change on the Groundwater Recharge in the Sonoran Desert\n", + "By Eline Mol" + ] + }, + { + "cell_type": "markdown", + "id": "fde7a748-b9e7-4bd0-8256-a52485db06e9", + "metadata": {}, + "source": [ + "## 1 Introduction\n", + "\n", + "Over the last century, the Earth’s climate has warmed more than 1 °C. In some regions more drought will occur, while other regions will be wetter (IPCC, 2021). In times limited of rainfall, groundwater storages will act as a natural buffer. These storages will provide against water scarcity, limiting evaporation in areas with shallow water tables and sustaining river and wetland baseflows which supports ecosystems and biodiversity (de Graaf et al., 2017). The process of water infiltrating into soil layers and replenishing groundwater is called groundwater recharge. Generally, groundwater is recharged through processes that are controlled by: geology, temperature, precipitation, potential evapotranspiration, humidity and land use (Castillo et al., 2021). \n", + "\n", + "Arid regions such as the Sonoran Desert rely on groundwater as a primary water source according to the Arizona Department of Water Resources (ADWR, 2023). However, long-term groundwater over-pumping poses a significant threat to this resource (PPIC, n.d.). In the Sonoran Desert region, groundwater management has been a pressing priority for decades. For instance, Arizona started regulating groundwater in its largest cities under a new law in 1980, the Groundwater Management Code. This law stated a goal of achieving a long-term balance between the amount of groundwater pumping and the amount of replenishing these buffers (James, 2021). In 2014, California adopted a similar law (Sustainable Groundwater Management Act) to manage and regulate its groundwater sources, as attempt to prevent and recover groundwater depleted basins (Mason, 2014). In Mexico, the Law of the Nation’s Water (LAN) is adopted in 1992, stating the management and regulation of water entitlement. It states the appropriation, allocation and concession of groundwater rights (Cruz-Ayala & Megdal, 2020).\n", + "\n", + "Due to growing concerns of the groundwater availability in the future, this report researches what the impact of climate change will be on the groundwater recharge in the Sonoran Desert. The analysis involves determining the threshold for groundwater recharge in the region and projecting future groundwater recharge by simulating three climate scenarios from CMIP6 in the PCR-GlobWB model. \n", + "\n", + "This report consists of five chapters. The first chapter serves as the introduction, outlining the research motivation, the problem analysis and the objectives of this study. Chapter 2 details the methodology of this study, focusing on the eWaterCycle platform and its application of the hydrological model PCR-GlobWB. Chapter 3 contains the results generated by this model. Chapter 4 includes a discussion, evaluating the results and reflecting on possible implications. Finally, chapter 5 concludes the report, gives recommendations for the future and provides the answer to the research question." + ] + }, + { + "cell_type": "markdown", + "id": "c13383fd-cbe8-441f-9b65-5fa4b2a93b1a", + "metadata": {}, + "source": [ + "### 1.1 Problem Analysis\n", + "\n", + "The Sonoran Desert is an arid region with a subtropical climate in the Southwestern of the United States and Northwestern of Mexico. According to the National Park Service (NPS, 2024) the desert covers approximately 260 000 km2 of this region, as shown in Figure 1. In this region, the hydrological system includes many streams and two primary rivers, the Colorado River and the Gila River, Figure 2. A majority of the smaller streams remain dry for most of the year (Kampf et al., 2018). \n", + "\n", + "Groundwater serves as the primary water source in the Sonoran Desert region, supporting both the urban, environmental and agricultural sector. The agricultural sector uses the biggest amount of the available water, about 75% of the available groundwater and surface water (ADWR, 2023; PPIC, n.d.). However, according to the Public Policy Institute of California (n.d.) consistently over pumping is now threatening this resource. \n", + "\t\n", + "The Sonoran Desert receives an average annual precipitation of 76-500 mm. Majority of the rainfall occurs during the summer monsoon thunderstorms. However, it also receives frequent low-intensity winter rains. Precipitation generally increases with elevation, due to orographic effects. A significant amount is occurring as snowfall. Precipitation is an important factor to recharge groundwater. Another critical factor is temperature, which influences the rate of evapotranspiration. High temperatures increase the rate of evapotranspiration, reducing the amount of water available for groundwater recharge (Dimitriadou & Nikolakopoulos, 2021). During the summer, air temperatures exceed 40°C. The temperatures in the winter are mild and mostly free of frost (NPS, 2024). \n", + "\n", + "It is inevitable that climate change will have an impact on the Sonoran Desert region. Changes in precipitation patterns and rising temperatures are likely to influence groundwater recharge processes. Therefore, this research focuses on the impact of climate change on groundwater recharge.\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "e2aec37b-6249-4fc5-a96a-d3335128bf1f", + "metadata": {}, + "source": [ + "### 1.2 Research Objective\n", + "\n", + "It is expected that climate change will have an influence on the hydrological system of the Sonoran Desert. Due to developments and collaborations in hydrological models, more insight can be given on what the impact of climate change will be. This study elaborates on the impact of climate change on groundwater recharge in the Sonoran Desert. This will be done by answering the following main research question:\n", + "\n", + "*“How will climate change influence groundwater recharge in the Gila River basin in the Sonoran Desert over the 21st century?”*\n", + "\n", + "The main research question will be answered by simulating the groundwater recharge using the PCR-GlobWB model. Sub-questions to answer the main research question are as follows:\n", + "\n", + "•\tWhat is the groundwater recharge threshold?\n", + "\n", + "•\tWhat forcings are of importance in the Sonoran Desert?\n", + "\n", + "•\tWhich parameters will have an influence on the groundwater recharge?\n", + "\n", + "•\tFor which climate scenarios will groundwater recharge be simulated, and which scenario will have the biggest impact?\n", + "\n", + "When research questions have been answered by using the PCR-GlobWB model, similar steps will be taken with another model. The wflow model can be used to compare its results with the PCR-GlobWB model. This will give insights into the accuracy of the models and their outcomes.\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "89bc9a84-87bf-450d-ba14-e93d435e7b1a", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "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": "3.12.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/book/thesis_projects/BSc/2024_Q2_ElineMol_CEG/Deliverables/2_methodology_emol.ipynb b/book/thesis_projects/BSc/2024_Q2_ElineMol_CEG/Deliverables/2_methodology_emol.ipynb new file mode 100644 index 0000000..fa850a3 --- /dev/null +++ b/book/thesis_projects/BSc/2024_Q2_ElineMol_CEG/Deliverables/2_methodology_emol.ipynb @@ -0,0 +1,88 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "560c1047-0b25-4d5d-96ab-0d969180759f", + "metadata": {}, + "source": [ + "# The Impact of Climate Change on the Groundwater Recharge in the Sonoran Desert\n", + "By Eline Mol" + ] + }, + { + "cell_type": "markdown", + "id": "58619540-4ec2-43f0-9f8d-0face55dcd31", + "metadata": {}, + "source": [ + "## 2 Methodology\n", + "\n", + "This study will focus on the impact of climate change on the groundwater recharge in the Sonoran Desert. To assess the impact, the eWaterCycle platform will be used. In eWaterCycle, hydrological models are made FAIR (findable, accessible, interoperable and reproducible) by adding a Basic Model Interface (BMI). These models can be run through the open interface of eWaterCycle and run using Jupyter notebooks provided by the platform. The eWaterCycle platform currently supports the following hydrological models: PCR-GlobWB, wflow, Hype, LISFLOOD, MARRMoT and WALRUS. To predict the effects on the groundwater recharge, the PCR-GlobWB model will be used (Hut et al., 2022). " + ] + }, + { + "cell_type": "markdown", + "id": "bd480fa8-414d-4e21-9ef9-c0fe9665d888", + "metadata": {}, + "source": [ + "### 2.1 PCR-GlobWb\n", + "\n", + "The PCR-GlobWB model is a grid based, global hydrology and water resources model. PCR-GlobWB integrates water use of: sector-specific water demand, groundwater and surface water withdrawal, water consumption and return flows. This model can simulate soil moisture storage, water exchange between the soil, atmosphere and the underlying groundwater reservoir. All of these uses are determined at every time step and are connected to the simulated hydrology. In Figure 3 a simplified overview of a PCR-GlobWB cell can be found to give an impression of all the fluxes in a system. PCR-GlobWB simulates at a spatial resolution of 5 arc-minute, which is ~10x10 km at the equator (Sutanudjaja et al., 2018).\n", + "\n", + "Forcing for models such as PCR-GlobWB in eWaterCycle is accessible through ERA5 datasets (Hut et al., 2022). ERA5 provides detailed recorded data on the global atmosphere, the land surface and ocean waves from 1950 onwards (Hersbach et al., 2020). The ESMValTool in eWaterCycle is used to pre-process the ERA5 dataset, enabling its direct application in the hydrological model. In this research, precipitation and temperature serve as the input for forcing. Additionally, a parameter set including is required as model input, which includes the catchment area and the time period (Hut et al., 2022). Figure 4 presents a flow chart of the PCR-GlobWB model, with ERA5 and a parameter set as input." + ] + }, + { + "cell_type": "markdown", + "id": "f572dad4-fb1b-4e9a-bb25-09b4ebda0f54", + "metadata": {}, + "source": [ + "### 2.2 Climate Projections\n", + "\n", + "To evaluate the potential impact of climate change, the Coupled Model Intercomparison Project Phase 6 (CMIP6) will be used for climate simulations. Three Shared Socioeconomic Pathways (SSPs) are selected for analysis: SSP1-2.6, SSP4-6.0 and SSP5-8.5. These pathways correspond to an optimistic scenario limiting the future warming to 2.0°C, a divided middle road limiting the warming to 4.1°C and the worst-case scenario which limits the future warming to 5.0°C, respectively (Hausfather, 2019). Appendix A explains the narratives of each of the selected SSPs. Figure 5 provides a flowchart of the PCR-GlobWB model with CMIP6 as forcing input." + ] + }, + { + "cell_type": "markdown", + "id": "f110523d-f7d7-4ccc-8e8f-73ff2f6a8f04", + "metadata": {}, + "source": [ + "### 2.3 Groundwater Recharge Threshold\n", + "\n", + "To evaluate which climate scenario will have the greatest impact, a threshold for groundwater recharge must be defined. In arid regions on regional scale, the baseflow discharge of rivers is often indicative of the minimum groundwater recharge that is required to sustain streamflow (Schilling et al., 2021). If the groundwater recharge falls below the threshold, there will not be enough water to sustain the streamflow. \n", + "\n", + "As mentioned in section 1.1, the Gila River spans a greater stretch within the Sonoran Desert compared to the Colorado River. The Colorado River extends to the Rocky Mountains and flows through multiple regions, which can be categorized into the Upper basin and the Lower basin. The discharge in the basins is influenced by several factors, including the amount of precipitation and milder temperatures (Salehabadi et al., 2020). Appendix B provides the mean temperature, mean precipitation and mean runoff of the two basins. Since many factors influencing the discharge of the Colorado river originate outside the Sonoran Desert, this research focuses on the Gila River.\n", + "\n", + "Near the city Yuma, the Gila River converges with the Colorado River. Just before this convergence, the Gila River’s baseflow is a determining factor for assessing the groundwater recharge threshold. Based on the graph provided in Figure 6 by the United States Geological Survey (USGS, n.d.), the baseflow at this point is measured at 0 m3/s. This could serve as the groundwater recharge threshold. However, a threshold of zero implies that no groundwater recharge would be required. To provide a more realistic assessment, the groundwater extraction by sectors such as agriculture will also be take into consideration.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a7b0d7cf-88d8-4325-9107-eb0e8f20bd23", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "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": "3.12.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/book/thesis_projects/BSc/2024_Q2_ElineMol_CEG/Drafts/sonoran_desert/sd_draft.ipynb b/book/thesis_projects/BSc/2024_Q2_ElineMol_CEG/Drafts/sonoran_desert/sd_draft.ipynb new file mode 100644 index 0000000..ce0dfa2 --- /dev/null +++ b/book/thesis_projects/BSc/2024_Q2_ElineMol_CEG/Drafts/sonoran_desert/sd_draft.ipynb @@ -0,0 +1,408 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "31ff7b70-7590-41d7-b650-3b104ab02e46", + "metadata": {}, + "source": [ + "# The Impact of Climate Change on Groundwater Recharge in the Sonoran Desert\n", + "Simulating groundwater recharge with application of the PCR-GLOBWB model. First step is to load all the needed packages." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "1d3a8d02-4a06-429a-a552-dcbcd2a42416", + "metadata": {}, + "outputs": [], + "source": [ + "# This cell is only used to suppress some distracting output messages\n", + "import warnings\n", + "\n", + "warnings.filterwarnings(\"ignore\", category=UserWarning)" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "6f5e5e7a-4f7a-4244-a06d-213f24547a71", + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "from cartopy import crs\n", + "from cartopy import feature as cfeature\n", + "import fiona\n", + "import shapely.geometry\n", + "from pyproj import Geod\n", + "from rich import print\n", + "import pandas as pd\n", + "import xarray as xr\n", + "\n", + "import ewatercycle.forcing\n", + "import ewatercycle.models\n", + "import ewatercycle.parameter_sets" + ] + }, + { + "cell_type": "markdown", + "id": "e685dfd3-1610-4098-a75e-0c95503517cb", + "metadata": {}, + "source": [ + "Next, the forcings and parameterset are computed." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "be67f6f8-2fbd-49a4-a782-ac8053958b4d", + "metadata": {}, + "outputs": [], + "source": [ + "station_latitude = 32.76108802182168 #Gila near Yuma\n", + "station_longitude = -114.41721725761596" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "0cf6a936-2e40-4507-9d53-c0fa2db8edae", + "metadata": {}, + "outputs": [], + "source": [ + "parameter_set = ewatercycle.parameter_sets.ParameterSet(\n", + " name=\"custom_parameter_set\",\n", + " directory=\"/data/shared/parameter-sets/pcrglobwb_global\",\n", + " config=\"./pcrglobwb_sonoran_05min.ini\",\n", + " target_model=\"pcrglobwb\",\n", + " supported_model_versions={\"setters\"},\n", + ")\n", + "#print(parameter_set)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "136fdb1a-9274-4a25-ba21-aa77807a5179", + "metadata": {}, + "outputs": [], + "source": [ + "forcing = ewatercycle.forcing.sources[\"PCRGlobWBForcing\"].load(\n", + " directory=\"/home/emol/forcing/sonoran_desert/work/diagnostic/script\",\n", + ")\n", + "#print(forcing)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "f0560b6d-29a9-4975-94be-cd27ea0802d7", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
PCRGlobWB(\n",
+       "    parameter_set=ParameterSet(\n",
+       "        name='custom_parameter_set',\n",
+       "        directory=PosixPath('/data/shared/parameter-sets/pcrglobwb_global'),\n",
+       "        config=PosixPath('pcrglobwb_sonoran_05min.ini'),\n",
+       "        doi='N/A',\n",
+       "        target_model='pcrglobwb',\n",
+       "        supported_model_versions={'setters'},\n",
+       "        downloader=None\n",
+       "    ),\n",
+       "    forcing=PCRGlobWBForcing(\n",
+       "        start_time='1997-08-01T00:00:00Z',\n",
+       "        end_time='2000-08-31T00:00:00Z',\n",
+       "        directory=PosixPath('/home/emol/forcing/sonoran_desert/work/diagnostic/script'),\n",
+       "        shape=PosixPath('/home/emol/forcing/sonoran_desert/work/diagnostic/script/hysets_09488650.shp'),\n",
+       "        filenames={},\n",
+       "        precipitationNC='pcrglobwb_OBS6_ERA5_reanaly_1_day_pr_1997-2000_hysets_09488650.nc',\n",
+       "        temperatureNC='pcrglobwb_OBS6_ERA5_reanaly_1_day_tas_1997-2000_hysets_09488650.nc'\n",
+       "    )\n",
+       ")\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1;35mPCRGlobWB\u001b[0m\u001b[1m(\u001b[0m\n", + " \u001b[33mparameter_set\u001b[0m=\u001b[1;35mParameterSet\u001b[0m\u001b[1m(\u001b[0m\n", + " \u001b[33mname\u001b[0m=\u001b[32m'custom_parameter_set'\u001b[0m,\n", + " \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/data/shared/parameter-sets/pcrglobwb_global'\u001b[0m\u001b[1m)\u001b[0m,\n", + " \u001b[33mconfig\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'pcrglobwb_sonoran_05min.ini'\u001b[0m\u001b[1m)\u001b[0m,\n", + " \u001b[33mdoi\u001b[0m=\u001b[32m'N/A'\u001b[0m,\n", + " \u001b[33mtarget_model\u001b[0m=\u001b[32m'pcrglobwb'\u001b[0m,\n", + " \u001b[33msupported_model_versions\u001b[0m=\u001b[1m{\u001b[0m\u001b[32m'setters'\u001b[0m\u001b[1m}\u001b[0m,\n", + " \u001b[33mdownloader\u001b[0m=\u001b[3;35mNone\u001b[0m\n", + " \u001b[1m)\u001b[0m,\n", + " \u001b[33mforcing\u001b[0m=\u001b[1;35mPCRGlobWBForcing\u001b[0m\u001b[1m(\u001b[0m\n", + " \u001b[33mstart_time\u001b[0m=\u001b[32m'1997-08-01T00:00:00Z'\u001b[0m,\n", + " \u001b[33mend_time\u001b[0m=\u001b[32m'2000-08-31T00:00:00Z'\u001b[0m,\n", + " \u001b[33mdirectory\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/emol/forcing/sonoran_desert/work/diagnostic/script'\u001b[0m\u001b[1m)\u001b[0m,\n", + " \u001b[33mshape\u001b[0m=\u001b[1;35mPosixPath\u001b[0m\u001b[1m(\u001b[0m\u001b[32m'/home/emol/forcing/sonoran_desert/work/diagnostic/script/hysets_09488650.shp'\u001b[0m\u001b[1m)\u001b[0m,\n", + " \u001b[33mfilenames\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,\n", + " \u001b[33mprecipitationNC\u001b[0m=\u001b[32m'pcrglobwb_OBS6_ERA5_reanaly_1_day_pr_1997-2000_hysets_09488650.nc'\u001b[0m,\n", + " \u001b[33mtemperatureNC\u001b[0m=\u001b[32m'pcrglobwb_OBS6_ERA5_reanaly_1_day_tas_1997-2000_hysets_09488650.nc'\u001b[0m\n", + " \u001b[1m)\u001b[0m\n", + "\u001b[1m)\u001b[0m\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pcrglob = ewatercycle.models.PCRGlobWB(\n", + " parameter_set=parameter_set,\n", + " forcing=forcing\n", + ")\n", + "print(pcrglob)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "111b9f64-1117-4b12-bd2c-74f70d5ec7ce", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "('/home/emol/repos/projects/book/thesis_projects/BSc/2024_Q2_ElineMol_CEG/Drafts/sonoran_desert/pcrglobwb_20241212_091431/pcrglobwb_ewatercycle.ini',\n", + " '/home/emol/repos/projects/book/thesis_projects/BSc/2024_Q2_ElineMol_CEG/Drafts/sonoran_desert/pcrglobwb_20241212_091431')" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cfg_file, cfg_dir = pcrglob.setup(\n", + " start_time=\"1997-08-01T00:00:00Z\",\n", + " end_time=\"1997-12-31T00:00:00Z\",\n", + " max_spinups_in_years=0\n", + ")\n", + "cfg_file, cfg_dir" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "fe81e70f-2a13-4cab-bf6c-29f45f56e863", + "metadata": {}, + "outputs": [], + "source": [ + "pcrglob.initialize(cfg_file)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "4b34ed2b-7565-44b2-b85d-85b2aca712ed", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
PCRGlobWB: Sonoran Desert
time
1997-08-01 00:00:00+00:00NaN
1997-08-02 00:00:00+00:00NaN
1997-08-03 00:00:00+00:00NaN
1997-08-04 00:00:00+00:00NaN
1997-08-05 00:00:00+00:00NaN
\n", + "
" + ], + "text/plain": [ + " PCRGlobWB: Sonoran Desert\n", + "time \n", + "1997-08-01 00:00:00+00:00 NaN\n", + "1997-08-02 00:00:00+00:00 NaN\n", + "1997-08-03 00:00:00+00:00 NaN\n", + "1997-08-04 00:00:00+00:00 NaN\n", + "1997-08-05 00:00:00+00:00 NaN" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "time = pd.date_range(pcrglob.start_time_as_isostr, pcrglob.end_time_as_isostr)\n", + "timeseries = pd.DataFrame(\n", + " index=pd.Index(time, name=\"time\"), columns=[\"PCRGlobWB: Sonoran Desert\"]\n", + ")\n", + "timeseries.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "46327b82-f284-4c4b-867a-4904148c01d6", + "metadata": {}, + "outputs": [], + "source": [ + "while pcrglob.time < pcrglob.end_time:\n", + " pcrglob.update()\n", + "\n", + " # Track discharge at station location\n", + " discharge_at_station = pcrglob.get_value_at_coords(\n", + " \"groundwater_recharge\", lat=[station_latitude], lon=[station_longitude]\n", + " )\n", + " time = pcrglob.time_as_isostr\n", + " timeseries[\"PCRGlobWB: Sonoran Desert\"][time] = discharge_at_station[0]\n", + " #monthly_timeseries = timeseries.resample('A').mean()\n", + " # Show progress\n", + " #print(time,end='\\r') # \"\\r\" clears the output before printing the next timestamp" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "1f4db5c5-7379-400c-b914-772eb680c7b5", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "da = pcrglob.get_value_as_xarray(\"groundwater_recharge\")\n", + "\n", + "fig = plt.figure(dpi=120)\n", + "ax = fig.add_subplot(111, projection=crs.PlateCarree())\n", + "da.plot(ax=ax, cmap=\"GnBu\")\n", + "\n", + "# Overlay ocean and coastines\n", + "ax.add_feature(cfeature.OCEAN)\n", + "ax.add_feature(cfeature.RIVERS, color=\"k\")\n", + "ax.coastlines()\n", + "\n", + "# Add a red cross marker at the location of the Leven River at Newby Bridge\n", + "ax.scatter(station_longitude, station_latitude, s=250, c=\"r\", marker=\"x\", lw=2)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "0a9d2483-476c-476e-89d2-a254bcbfc189", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "timeseries.plot()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "760476a3-95cc-442a-95bd-a0e636b67de4", + "metadata": {}, + "outputs": [], + "source": [ + "pcrglob.finalize()" + ] + } + ], + "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": "3.12.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}