├── AUGFloodedArea_TIFF18.tif ├── AUGFloodedArea_TIFF20.tif ├── AUGFloodedArea_TIFF22.tif ├── AUGFloodedArea_TIFF24.tif ├── NOVFloodedArea_TIFF18.tif ├── NOVFloodedArea_TIFF20.tif ├── NOVFloodedArea_TIFF22.tif ├── OCTFloodedArea_TIFF18.tif ├── OCTFloodedArea_TIFF24.tif ├── SEPFloodedArea_TIFF20.tif ├── SEPFloodedArea_TIFF22.tif ├── SEPFloodedArea_TIFF24.tif ├── OCTFloodedArea_2020_TIFF.tif ├── OCTFloodedArea_2022_TIFF.tif ├── SEPFloodedArea_2018_TIFF.tif ├── NOVFloodedArea _2024_TIFF.tif ├── impact.py ├── water-level-heights-Benue-State.csv ├── water-level-heights in-Kogi State.csv ├── README.md ├── water-level-heights-Rivers-State.csv └── water-level-heights-Bayelsa-State.csv /AUGFloodedArea_TIFF18.tif: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Otutu11/The-impact-of-dam-management-and-rainfall-patterns-on-flooding-in-the-Niger-Delta-Using-Sentinel-1/main/AUGFloodedArea_TIFF18.tif 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/impact.py: -------------------------------------------------------------------------------- 1 | var aoi = ee.Geometry.Polygon([ 2 | [ 3 | [3.03125, 4.5], 4 | [8.03125, 4.5], 5 | [8.03125, 7.5], 6 | [3.03125, 7.5], 7 | [3.03125, 4.5] 8 | ] 9 | ]); 10 | // Define the time period for analysis 11 | var startDate = '2022-09-20'; 12 | var endDate = '2022-10-28'; 13 | 14 | // Load Sentinel-1 SAR dataset 15 | var sentinel1 = ee.ImageCollection('COPERNICUS/S1_GRD') 16 | .filterBounds(aoi) 17 | .filterDate(startDate, endDate) 18 | .filter(ee.Filter.eq('instrumentMode', 'IW')) 19 | .filter(ee.Filter.eq('orbitProperties_pass', 'DESCENDING')) 20 | .filter(ee.Filter.eq('resolution_meters', 10)) 21 | .filter(ee.Filter.listContains('transmitterReceiverPolarisation', 'VV')) 22 | .select('VV'); 23 | 24 | // Create a median composite image for the period 25 | var medianImage = sentinel1.median().clip(aoi); 26 | 27 | // Threshold to identify flood areas (adjust the threshold value based on your AOI) 28 | var floodThreshold = -11; 29 | var floodedArea = medianImage.lt(floodThreshold).selfMask(); 30 | var nonFloodedArea = medianImage.gte(floodThreshold).selfMask(); 31 | 32 | // Display the results 33 | Map.centerObject(aoi, 10); 34 | Map.addLayer(floodedArea, {palette: ['red'], min: 0, max: 1}, 'Flooded Area'); 35 | Map.addLayer(nonFloodedArea, {palette: ['blue'], min: 0, max: 1}, 'Non-Flooded Area'); 36 | 37 | // Calculate flood area statistics 38 | var floodArea = floodedArea.multiply(ee.Image.pixelArea()).reduceRegion({ 39 | reducer: ee.Reducer.sum(), 40 | geometry: aoi, 41 | scale: 10, 42 | maxPixels: 1e10 43 | }); 44 | 45 | var nonFloodArea = nonFloodedArea.multiply(ee.Image.pixelArea()).reduceRegion({ 46 | reducer: ee.Reducer.sum(), 47 | geometry: aoi, 48 | scale: 10, 49 | maxPixels: 1e10 50 | }); 51 | 52 | // Print the results 53 | print('Flooded Area (m^2): ', floodArea.get('VV')); 54 | print('Non-Flooded Area (m^2): ', nonFloodArea.get('VV')); 55 | 56 | // Create a chart to visualize the flood and non-flood areas 57 | var chart = ui.Chart.array.values({ 58 | array: [floodArea.get('VV'), nonFloodArea.get('VV')], 59 | axis: 0 60 | }) 61 | .setChartType('PieChart') 62 | .setOptions({ 63 | title: 'Flood vs Non-Flood Areas', 64 | slices: [{color: 'red'}, {color: 'blue'}], 65 | labels: ['Flooded Area', 'Non-Flooded Area'] 66 | }); 67 | 68 | print(chart); 69 | 70 | // Export the flooded area as a TIFF file 71 | Export.image.toDrive({ 72 | image: floodedArea, 73 | description: 'FloodedArea_TIFF', 74 | scale: 10, 75 | region: floodedArea.geometry().bounds(), 76 | maxPixels: 1e8, 77 | fileFormat: 'GeoTIFF' 78 | }); 79 | 80 | // Export the non-flooded area as a TIFF file 81 | Export.image.toDrive({ 82 | image: nonFloodedArea, 83 | description: 'NonFloodedArea_TIFF', 84 | scale: 10, 85 | region: nonFloodedArea.geometry().bounds(), 86 | maxPixels: 1e8, 87 | fileFormat: 'GeoTIFF' 88 | }); 89 | 90 | -------------------------------------------------------------------------------- /water-level-heights-Benue-State.csv: -------------------------------------------------------------------------------- 1 | Lagdo 7.5751 8.0393 2 | category Water Level Water Level Error 3 | Fri Nov 30 2018 47.27228091 0.024758789 4 | Thu Dec 27 2018 46.30519194 0.006142962 5 | Wed Jan 23 2019 45.87200913 0.021922797 6 | Tue Feb 19 2019 45.60924468 0.004094771 7 | Mon Mar 18 2019 45.63749474 0.002372028 8 | Sun Apr 14 2019 45.62467792 0.004057681 9 | Sat May 11 2019 45.88277906 0.018738869 10 | Fri Jun 07 2019 46.97885515 0.003875227 11 | Thu Jul 04 2019 48.63792423 0.006477098 12 | Wed Jul 31 2019 50.2035973 0.008294318 13 | Tue Aug 27 2019 51.16091615 0.005564701 14 | Mon Sep 23 2019 52.39664331 0.009469409 15 | Sun Oct 20 2019 52.38359801 0.0200246 16 | Sat Nov 16 2019 52.08419163 0.000992566 17 | Fri Dec 13 2019 47.48069851 0.01027907 18 | Thu Jan 09 2020 46.51279316 0.01285399 19 | Wed Feb 05 2020 46.0365734 0.02147859 20 | Tue Mar 03 2020 45.76078877 0.027197339 21 | Mon Mar 30 2020 45.73388211 0.003134304 22 | Sun Apr 26 2020 46.03101776 0.002945421 23 | Sat May 23 2020 46.42925258 0.019160159 24 | Fri Jun 19 2020 47.51759998 0.033783887 25 | Thu Jul 16 2020 49.61500853 0.000572188 26 | Wed Aug 12 2020 50.31424871 0.007601795 27 | Tue Sep 08 2020 51.04021082 0.013638392 28 | Mon Oct 05 2020 52.50641195 0.004689823 29 | Sun Nov 01 2020 50.13915223 0.036352454 30 | Sat Nov 28 2020 47.05125698 0.006942647 31 | Fri Dec 25 2020 46.21494241 0.011023985 32 | Thu Jan 21 2021 45.92318564 0.012058152 33 | Tue Mar 16 2021 45.48971358 0.020575782 34 | Mon Apr 12 2021 45.46471711 0.010350287 35 | Sun May 09 2021 45.69094101 0.038869273 36 | Sat Jun 05 2021 46.46394915 0.007893931 37 | Fri Jul 02 2021 47.88225902 0.001604222 38 | Thu Jul 29 2021 49.7641247 0.065667995 39 | Wed Aug 25 2021 51.13728303 0.011949982 40 | Tue Sep 21 2021 51.87777551 0.02102747 41 | Mon Oct 18 2021 49.62822243 0.009392701 42 | Sun Nov 14 2021 48.62666087 0.026477081 43 | Sat Dec 11 2021 46.82914818 0.018453742 44 | Fri Jan 07 2022 46.04531684 0.01826013 45 | Thu Feb 03 2022 45.83180764 0.051424496 46 | Wed Mar 02 2022 45.75478223 0.059351571 47 | Tue Mar 29 2022 45.48701507 0.001764813 48 | Mon Apr 25 2022 46.01346607 0.04096842 49 | Sat Jun 18 2022 46.99684884 0.009062363 50 | Fri Jul 15 2022 48.86546666 0.008139445 51 | Thu Aug 11 2022 50.35993032 0.011513239 52 | Wed Sep 07 2022 52.56792204 0.008811158 53 | Tue Oct 04 2022 53.22925601 0.002813344 54 | Mon Oct 31 2022 51.94105702 0.009590475 55 | Sun Nov 27 2022 47.67201615 0.00662881 56 | Sat Dec 24 2022 46.76431449 0.001875834 57 | Fri Jan 20 2023 46.2015253 0.027267517 58 | Thu Feb 16 2023 46.17088576 0.039773228 59 | Wed Mar 15 2023 45.78589255 0.00835696 60 | Tue Apr 11 2023 45.87581096 0.007463902 61 | Mon May 08 2023 46.1516244 0.016973281 62 | Sun Jun 04 2023 47.08362595 0.002503474 63 | Sat Jul 01 2023 49.47669952 0.012122154 64 | Fri Jul 28 2023 49.83223336 0.015935847 65 | Thu Aug 24 2023 51.09819895 0.005475244 66 | Wed Sep 20 2023 51.769442 0.003439561 67 | Tue Oct 17 2023 52.32219592 0.019214549 68 | Mon Nov 13 2023 49.26966655 0.011059006 69 | Sun Dec 10 2023 47.34393288 0.019458459 70 | Sat Jan 06 2024 46.74413805 0.007402147 71 | Fri Feb 02 2024 46.1286309 0.010949195 72 | Thu Feb 29 2024 45.94802482 0.030835807 73 | Wed Mar 27 2024 45.21930935 0.009305295 74 | Tue Apr 23 2024 46.66715647 0.039647117 75 | Mon May 20 2024 46.8736103 0.016041286 76 | Sun Jun 16 2024 48.16152433 0.003899255 77 | Sat Jul 13 2024 49.31100543 0.008647902 78 | Fri Aug 09 2024 49.92579735 0.014646969 79 | Thu Sep 05 2024 51.33818743 0.005874281 80 | Wed Oct 02 2024 52.94076817 0.00232567 81 | Tue Oct 29 2024 53.15315669 0.018119172 82 | Mon Nov 25 2024 47.75252975 0.001175286 83 | -------------------------------------------------------------------------------- /water-level-heights in-Kogi State.csv: -------------------------------------------------------------------------------- 1 | Kogi State 6.7827 8.0497 2 | category Water Level Water Level Error 3 | Wed Nov 28 2018 40.92290712 0.077367629 4 | Tue Dec 25 2018 39.32639567 0.008415627 5 | Mon Jan 21 2019 39.22095053 0.001112381 6 | Sun Feb 17 2019 39.21545668 0.00967905 7 | Sat Mar 16 2019 39.14228852 0.011902466 8 | Fri Apr 12 2019 38.63395568 0.001262662 9 | Thu May 09 2019 38.95060592 0.004050961 10 | Wed Jun 05 2019 38.94312894 0.021028533 11 | Tue Jul 02 2019 39.30740436 0.020023763 12 | Mon Jul 29 2019 40.76331723 0.002368274 13 | Sun Aug 25 2019 40.77314469 0.016592303 14 | Sat Sep 21 2019 43.61954737 0.010585254 15 | Fri Oct 18 2019 43.25827836 0.005056477 16 | Thu Nov 14 2019 42.07334033 0.00555531 17 | Wed Dec 11 2019 39.81389951 0.005814374 18 | Tue Jan 07 2020 39.1535024 0.00799658 19 | Mon Feb 03 2020 39.25155912 0.008045914 20 | Sun Mar 01 2020 38.6804678 0.000472629 21 | Sat Mar 28 2020 38.9061048 0.004220791 22 | Fri Apr 24 2020 38.62432868 0.022901153 23 | Thu May 21 2020 38.85961322 0.020687789 24 | Wed Jun 17 2020 38.87421745 0.007667466 25 | Tue Jul 14 2020 39.60328791 0.040671601 26 | Mon Aug 10 2020 39.72889685 0.041722386 27 | Sun Sep 06 2020 41.9264767 0.029765198 28 | Sat Oct 03 2020 44.86869009 0.002967152 29 | Fri Oct 30 2020 42.04283913 0.004089869 30 | Thu Nov 26 2020 39.59805384 0.005641208 31 | Tue Jan 19 2021 39.30819539 0.005037758 32 | Mon Feb 15 2021 39.33840164 0.007977362 33 | Sun Mar 14 2021 39.08609851 0.009816312 34 | Sat Apr 10 2021 39.50611707 0.008095358 35 | Fri May 07 2021 39.00245738 0.003090724 36 | Thu Jun 03 2021 38.0789531 0.023866278 37 | Wed Jun 30 2021 39.04888216 0.008992553 38 | Tue Jul 27 2021 39.04211094 0.049703224 39 | Mon Aug 23 2021 41.03047465 0.00065973 40 | Sun Sep 19 2021 42.05530116 0.003771585 41 | Sat Oct 16 2021 40.44562905 0.009237801 42 | Fri Nov 12 2021 39.56583543 0.024939423 43 | Thu Dec 09 2021 39.17582137 0.000708437 44 | Wed Jan 05 2022 39.15403752 0.019200897 45 | Tue Feb 01 2022 38.92891535 0.029196683 46 | Mon Feb 28 2022 39.07446756 0.001875503 47 | Sun Mar 27 2022 39.0602433 0.008246885 48 | Sat Apr 23 2022 39.32941322 0.011356619 49 | Fri May 20 2022 39.04830058 0.011346614 50 | Thu Jun 16 2022 38.52199847 0.058484093 51 | Wed Jul 13 2022 39.09655278 0.013310841 52 | Tue Aug 09 2022 40.38236206 0.013286055 53 | Mon Sep 05 2022 42.16650731 0.010026496 54 | Sun Oct 02 2022 45.43712858 0.004236445 55 | Sat Oct 29 2022 42.9712798 0.007752142 56 | Fri Nov 25 2022 39.41431562 0.006537446 57 | Thu Dec 22 2022 39.00752053 0.003862484 58 | Wed Jan 18 2023 39.69654468 0.329590824 59 | Tue Feb 14 2023 39.49358282 0.013736783 60 | Mon Mar 13 2023 39.25488813 0.037963279 61 | Sun Apr 09 2023 38.82637835 0.030131836 62 | Sat May 06 2023 38.72892376 0.005158835 63 | Fri Jun 02 2023 39.28557149 0.021499331 64 | Thu Jun 29 2023 40.55015167 0.008334029 65 | Wed Jul 26 2023 41.19748615 0.003003122 66 | Tue Aug 22 2023 41.8487981 0.010471721 67 | Mon Sep 18 2023 42.52220359 0.007629436 68 | Sun Oct 15 2023 42.71947236 0.004617808 69 | Sat Nov 11 2023 40.04603505 0.000154127 70 | Thu Jan 04 2024 39.87140343 0.207763731 71 | Wed Jan 31 2024 38.67153559 0.004670254 72 | Tue Feb 27 2024 38.9699884 0.014954518 73 | Mon Mar 25 2024 38.93619487 0.019837067 74 | Sun Apr 21 2024 39.38303818 0.00569455 75 | Sat May 18 2024 39.73034731 0.003029332 76 | Fri Jun 14 2024 39.69538886 0.008609865 77 | Thu Jul 11 2024 40.40965961 0.001283683 78 | Wed Aug 07 2024 39.88684206 0.032228361 79 | Tue Sep 03 2024 41.80607544 0.018692423 80 | Mon Sep 30 2024 43.77976292 0.011805994 81 | Sun Oct 27 2024 44.03932177 0.017459685 82 | Sat Nov 23 2024 39.96086437 0.000247167 83 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # The Impact of Dam Management and Rainfall Patterns on Flooding in the Niger Delta Using Sentinel-1 2 | 3 | ## Overview 4 | This repository contains the analysis and results of a study examining the interplay between dam management practices, rainfall patterns, and flooding events in the Niger Delta. By leveraging Sentinel-1 satellite data and other hydrological datasets, this project aims to understand the factors contributing to flooding and inform future mitigation strategies. 5 | 6 | ## Data Sources 7 | The analysis is based on the following datasets: 8 | 9 | 1. **Sentinel-1 Imagery (2018-2024):** Used for flood mapping and monitoring water extent changes over time. 10 | 2. **Rainfall Data (2018-2024):** Provides temporal insights into precipitation patterns affecting flooding. 11 | 3. **Water Level Data (2018-2024):** Includes measurements for both upstream and downstream regions, critical for understanding the impact of dam operations. 12 | 4. **Digital Elevation Model (DEM):** Used for terrain analysis and determining flood-prone areas. 13 | 5. **Dam Locations:** Geospatial data of dams influencing water flow within the study area. 14 | 15 | ## Objectives 16 | - Analyze the relationship between dam management practices and flooding events. 17 | - Assess how rainfall patterns contribute to flooding severity and frequency. 18 | - Map flood extents using Sentinel-1 data to identify high-risk zones. 19 | - Provide actionable insights for flood mitigation and dam operation strategies. 20 | 21 | ## Methods 22 | The study employs a combination of geospatial and hydrological analysis techniques, including: 23 | - **Flood Mapping:** Using Sentinel-1 data to detect water extent changes. 24 | - **Rainfall Analysis:** Correlating rainfall patterns with flood occurrences. 25 | - **Hydrological Modeling:** Assessing the impact of dam water levels on downstream flooding. 26 | - **Terrain Analysis:** Utilizing DEM data to identify topographical factors influencing flood behavior. 27 | 28 | ## Tools and Technologies 29 | - **Geospatial Analysis:** Processed using GIS software, including QGIS and Google Earth Engine. 30 | - **Hydrological Analysis:** Conducted with hydrological modeling tools. 31 | - **Satellite Data Processing:** Using tools like SNAP and Python libraries for Sentinel-1 data. 32 | 33 | ## Usage 34 | ### Prerequisites 35 | - Install required Python libraries listed in `requirements.txt`. 36 | - Ensure access to the datasets listed above. 37 | 38 | ### Instructions 39 | 1. Clone this repository: 40 | ```bash 41 | git clone https://github.com/yourusername/The-impact-of-dam-management-and-rainfall-patterns-on-flooding-in-the-Niger-Delta-Using-Sentinel-1.git 42 | ``` 43 | 2. Download the datasets and place them in the `data` folder. 44 | 3. Run the preprocessing scripts to prepare the data. 45 | 4. Execute the analysis notebooks for specific insights. 46 | 47 | ## Results 48 | Key findings from this study include: 49 | - Temporal patterns linking rainfall and flood events. 50 | - Quantitative impacts of dam water level fluctuations on downstream flooding. 51 | - Identification of areas most vulnerable to flooding in the Niger Delta. 52 | 53 | ## Contributions 54 | Contributions are welcome! If you have suggestions or would like to collaborate, please submit a pull request or open an issue. 55 | 56 | ## License 57 | This project is licensed under the MIT License. See `LICENSE` for details. 58 | 59 | ## Acknowledgments 60 | Special thanks to the organizations and individuals who provided the datasets and tools that made this analysis possible. 61 | 62 | --- 63 | For any questions or additional information, feel free to reach out via the issues page or email [desmondeteh@gmail.com]. 64 | 65 | -------------------------------------------------------------------------------- /water-level-heights-Rivers-State.csv: -------------------------------------------------------------------------------- 1 | Rivers State Long Lat 2 | "Niger, River" 6.5043 5.343 3 | 4 | category Water Level Water Level Error 5 | Thu May 12 2016 5.749904605 0.007113931 6 | Wed Jun 08 2016 7.292160718 0.012829885 7 | Tue Jul 05 2016 8.552686657 0.014279693 8 | Mon Aug 01 2016 10.61218094 0.01796557 9 | Sun Aug 28 2016 11.67413889 0.000408551 10 | Sat Sep 24 2016 12.24456409 0.013810727 11 | Fri Oct 21 2016 12.32147702 0.00323359 12 | Thu Nov 17 2016 8.729788874 0.038049875 13 | Wed Dec 14 2016 6.929456673 0.006036406 14 | Tue Jan 10 2017 6.508647632 0.008135108 15 | Mon Feb 06 2017 6.004262226 0.040238991 16 | Sun Mar 05 2017 5.82951978 0.007668935 17 | Sat Apr 01 2017 5.8405872 0.007093415 18 | Fri Apr 28 2017 6.01884901 0.080036444 19 | Thu May 25 2017 5.960818587 0.007975343 20 | Wed Jun 21 2017 7.246245702 0.008604987 21 | Tue Jul 18 2017 9.684332445 0.011249451 22 | Mon Aug 14 2017 10.91474611 0.018257535 23 | Sun Sep 10 2017 12.35861165 0.00708891 24 | Sat Oct 07 2017 12.60287672 0.008529486 25 | Fri Nov 03 2017 9.936693814 0.146233573 26 | Thu Nov 30 2017 7.26002499 0.003391683 27 | Wed Dec 27 2017 6.221212666 0.007149619 28 | Tue Jan 23 2018 6.016950837 0.001011369 29 | Mon Feb 19 2018 5.666194999 0.066138663 30 | Sun Mar 18 2018 5.651535814 0.019633917 31 | Sat Apr 14 2018 5.62150666 0.00518467 32 | Fri May 11 2018 5.958215721 0.033430414 33 | Thu Jun 07 2018 6.904676142 0.026788835 34 | Wed Jul 04 2018 7.989853405 0.007081023 35 | Tue Jul 31 2018 10.63735459 0.00154077 36 | Mon Aug 27 2018 11.74118969 0.059485561 37 | Sun Sep 23 2018 12.64324847 0.030355237 38 | Sat Oct 20 2018 12.73097334 0.008567483 39 | Fri Nov 16 2018 9.856972005 0.004765555 40 | Thu Dec 13 2018 7.556360205 0.005556722 41 | Wed Jan 09 2019 6.418307318 0.002227145 42 | Tue Feb 05 2019 6.156580253 0.006816012 43 | Mon Mar 04 2019 6.38326181 0.007376032 44 | Sun Mar 31 2019 5.973703595 0.00038592 45 | Sat Apr 27 2019 6.23332291 0.020348039 46 | Fri May 24 2019 6.353172578 0.018483753 47 | Thu Jun 20 2019 8.130005586 0.042022835 48 | Wed Jul 17 2019 9.947067243 0.003843944 49 | Tue Aug 13 2019 11.15054218 0.012424692 50 | Mon Sep 09 2019 12.39094393 0.012530032 51 | Sun Oct 06 2019 12.68356707 0.033735414 52 | Sat Nov 02 2019 12.68028147 0.00807505 53 | Fri Nov 29 2019 10.93436635 0.078205239 54 | Thu Dec 26 2019 7.753754389 0.017675059 55 | Wed Jan 22 2020 6.933115201 0.004234673 56 | Tue Feb 18 2020 6.254388067 0.000245975 57 | Mon Mar 16 2020 6.240151952 0.002353271 58 | Sun Apr 12 2020 6.25034174 0.003945746 59 | Sat May 09 2020 6.162433838 0.023611822 60 | Fri Jun 05 2020 7.050058845 0.003703096 61 | Thu Jul 02 2020 8.484634284 0.000924994 62 | Wed Jul 29 2020 10.73160743 0.018671556 63 | Tue Aug 25 2020 9.996237707 0.002760529 64 | Mon Sep 21 2020 12.52117547 0.011973996 65 | Sun Oct 18 2020 12.93079028 0.0076071 66 | Sat Nov 14 2020 9.919277096 0.001360691 67 | Fri Dec 11 2020 7.148714997 0.014367895 68 | Thu Jan 07 2021 6.550403913 0.053882456 69 | Wed Feb 03 2021 6.699542238 0.079155128 70 | Tue Mar 02 2021 6.212604247 0.041356325 71 | Mon Mar 29 2021 6.393867552 0.031215216 72 | Sun Apr 25 2021 6.617806295 0.007664911 73 | Sat May 22 2021 6.174172758 0.035349791 74 | Fri Jun 18 2021 6.477399379 0.01772288 75 | Thu Jul 15 2021 8.220750446 0.048526821 76 | Wed Aug 11 2021 9.663282278 0.354701157 77 | Tue Sep 07 2021 12.05918761 0.012276469 78 | Mon Oct 04 2021 12.29675932 0.014925469 79 | Sun Oct 31 2021 10.65128057 0.026157257 80 | Sat Nov 27 2021 7.94148463 0.028371998 81 | Fri Dec 24 2021 6.903156739 0.006973845 82 | Thu Jan 20 2022 6.36775771 0.012060623 83 | Wed Feb 16 2022 6.312739439 0.00417312 84 | Tue Mar 15 2022 6.344524697 0.000548177 85 | Mon Apr 11 2022 6.182873179 0.048730247 86 | Sun May 08 2022 6.631946362 0.017573023 87 | Sat Jun 04 2022 6.93558452 0.012526011 88 | Fri Jul 01 2022 8.052878831 0.001124484 89 | Thu Jul 28 2022 9.325176048 0.019033677 90 | Wed Aug 24 2022 11.60665656 0.002274641 91 | Tue Sep 20 2022 12.58042268 0.027460299 92 | Mon Oct 17 2022 13.50004387 0.005271778 93 | Sun Nov 13 2022 11.261647 0.058364666 94 | Sat Dec 10 2022 7.465329022 0.019013101 95 | Fri Jan 06 2023 6.588165934 0.014499862 96 | Thu Feb 02 2023 6.663983552 0.006306753 97 | Wed Mar 01 2023 6.525072885 0.02710399 98 | Tue Mar 28 2023 5.936458343 0.030956885 99 | Mon Apr 24 2023 6.251904591 0.099224176 100 | Sun May 21 2023 6.659960719 0.039895787 101 | Sat Jun 17 2023 8.703232318 0.033945365 102 | Fri Jul 14 2023 10.72548436 0.018026352 103 | Thu Aug 10 2023 10.50983321 0.005853157 104 | Wed Sep 06 2023 12.41301828 0.000612841 105 | Tue Oct 03 2023 12.54494721 0.025895464 106 | Mon Oct 30 2023 12.12383579 0.002284511 107 | Sun Nov 26 2023 8.614149579 0.008080544 108 | Fri Jan 19 2024 6.63587514 0.008069309 109 | Thu Feb 15 2024 6.220237447 0.027842109 110 | Wed Mar 13 2024 6.637188866 0.005004782 111 | Tue Apr 09 2024 6.356423281 0.007914085 112 | Mon May 06 2024 6.570262652 0.024729748 113 | Sun Jun 02 2024 6.687850662 0.037450694 114 | Sat Jun 29 2024 8.155110364 0.001079303 115 | Fri Jul 26 2024 10.11205453 0.010964628 116 | Thu Aug 22 2024 9.03223089 0.044829084 117 | Wed Sep 18 2024 11.91953427 0.107094565 118 | Tue Oct 15 2024 12.44539233 0.091681625 119 | Mon Nov 11 2024 12.5594144 0.00430578 120 | -------------------------------------------------------------------------------- /water-level-heights-Bayelsa-State.csv: -------------------------------------------------------------------------------- 1 | Delta 6.0588 5.0074 2 | category Water Level Water Level Error 3 | Fri May 06 2016 1.273688955 0.001574678 4 | Thu Jun 02 2016 3.406982027 0.012436734 5 | Wed Jun 29 2016 1.886756392 0.021673246 6 | Tue Jul 26 2016 2.892055407 0.0029886 7 | Mon Aug 22 2016 4.254295732 0.015747815 8 | Sun Sep 18 2016 5.772672769 0.008646884 9 | Sat Oct 15 2016 5.799272015 0.012107826 10 | Fri Nov 11 2016 2.845658836 0.02658071 11 | Thu Dec 08 2016 1.144974723 0.029495828 12 | Wed Jan 04 2017 0.84341667 0.019808909 13 | Tue Jan 31 2017 0.959644864 0.006470575 14 | Mon Feb 27 2017 1.196408952 0.011792685 15 | Sun Mar 26 2017 1.196656016 0.001957801 16 | Sat Apr 22 2017 0.898297215 0.056307979 17 | Fri May 19 2017 0.75384552 0.00011964 18 | Thu Jun 15 2017 1.266414067 0.011857117 19 | Wed Jul 12 2017 2.23300664 0.04861738 20 | Tue Aug 08 2017 3.582053067 0.030580289 21 | Mon Sep 04 2017 5.004488108 0.008739105 22 | Sun Oct 01 2017 5.763331838 0.019440825 23 | Sat Oct 28 2017 5.022609475 0.001020249 24 | Fri Nov 24 2017 1.328492292 0.023593182 25 | Thu Dec 21 2017 1.120136169 0.008080485 26 | Wed Jan 17 2018 1.025207132 4.18665E-05 27 | Tue Feb 13 2018 1.067910353 0.011082035 28 | Mon Mar 12 2018 0.633489395 0.004074432 29 | Sun Apr 08 2018 0.544077314 0.03068272 30 | Sat May 05 2018 0.622037555 0.010666266 31 | Fri Jun 01 2018 1.551628418 0.032852862 32 | Thu Jun 28 2018 1.621327594 0.010511663 33 | Wed Jul 25 2018 2.849151783 0.023319299 34 | Tue Aug 21 2018 4.107050114 0.002953258 35 | Mon Sep 17 2018 5.866015331 0.003021717 36 | Sun Oct 14 2018 6.47782985 0.00577094 37 | Sat Nov 10 2018 4.270791882 0.004648458 38 | Fri Dec 07 2018 1.537365124 0.032998931 39 | Thu Jan 03 2019 1.016103916 0.050947102 40 | Wed Jan 30 2019 0.931336088 0.017275998 41 | Tue Feb 26 2019 0.764699917 0.024410799 42 | Mon Mar 25 2019 0.960819707 0.007564265 43 | Sun Apr 21 2019 1.169184783 0.00586392 44 | Sat May 18 2019 1.191589173 0.00380795 45 | Fri Jun 14 2019 1.256080442 0.051876218 46 | Thu Jul 11 2019 2.53282279 0.031754204 47 | Wed Aug 07 2019 3.930276179 0.011301938 48 | Tue Sep 03 2019 4.674920049 0.018804332 49 | Mon Sep 30 2019 5.996944165 0.009459568 50 | Sun Oct 27 2019 6.295269632 0.01110908 51 | Sat Nov 23 2019 6.201164962 0.011647353 52 | Fri Dec 20 2019 1.596054791 0.004134927 53 | Thu Jan 16 2020 0.90778274 0.031140623 54 | Wed Feb 12 2020 1.019743868 0.016747073 55 | Tue Mar 10 2020 1.260659695 0.008816959 56 | Mon Apr 06 2020 1.335366438 0.006084614 57 | Sun May 03 2020 1.064107206 0.009051293 58 | Sat May 30 2020 0.846980623 0.046114819 59 | Fri Jun 26 2020 1.257267213 0.042042039 60 | Thu Jul 23 2020 3.430242009 0.004243682 61 | Wed Aug 19 2020 3.461440362 0.021689111 62 | Tue Sep 15 2020 4.869101202 0.004020802 63 | Mon Oct 12 2020 6.4784878 0.001283424 64 | Sun Nov 08 2020 5.753842876 0.008644227 65 | Sat Dec 05 2020 1.182336956 0.048098658 66 | Fri Jan 01 2021 1.238141575 0.010985541 67 | Thu Jan 28 2021 1.270719233 0.004567722 68 | Wed Feb 24 2021 1.110253787 0.001940485 69 | Tue Mar 23 2021 0.789297419 0.005842167 70 | Mon Apr 19 2021 0.88085147 0.003960821 71 | Sun May 16 2021 0.889706497 0.023555337 72 | Sat Jun 12 2021 1.206738645 0.013327513 73 | Fri Jul 09 2021 1.783656394 0.020075461 74 | Thu Aug 05 2021 1.895632524 0.022863758 75 | Wed Sep 01 2021 4.560171718 0.011902528 76 | Tue Sep 28 2021 5.453896515 0.000268668 77 | Mon Oct 25 2021 3.517770733 0.014013949 78 | Sun Nov 21 2021 2.245972257 0.001261862 79 | Sat Dec 18 2021 1.273765998 0.005779618 80 | Fri Jan 14 2022 1.022245496 0.006646233 81 | Thu Feb 10 2022 0.667572115 0.001272003 82 | Wed Mar 09 2022 0.8815414 0.012225426 83 | Tue Apr 05 2022 1.106065567 0.028123211 84 | Mon May 02 2022 1.290609277 0.002170176 85 | Sun May 29 2022 1.509617622 0.01062723 86 | Sat Jun 25 2022 1.421143794 0.015070565 87 | Fri Jul 22 2022 1.888022464 0.000466692 88 | Thu Aug 18 2022 3.823156254 0.006465082 89 | Wed Sep 14 2022 5.387346703 0.006036211 90 | Tue Oct 11 2022 6.590335115 0.006479603 91 | Mon Nov 07 2022 6.339008503 0.024286257 92 | Sun Dec 04 2022 1.640978884 0.004874756 93 | Sat Dec 31 2022 0.737538448 0.06132916 94 | Fri Jan 27 2023 0.967997632 0.002207958 95 | Thu Feb 23 2023 1.172271108 0.012190602 96 | Wed Mar 22 2023 1.354081209 0.005247993 97 | Tue Apr 18 2023 1.341367977 0.001147793 98 | Mon May 15 2023 1.201393238 0.043191647 99 | Sun Jun 11 2023 1.36027665 0.011539694 100 | Sat Jul 08 2023 3.316319262 0.006775228 101 | Fri Aug 04 2023 3.922290261 0.005907372 102 | Thu Aug 31 2023 4.587773794 0.008928647 103 | Wed Sep 27 2023 5.58903698 0.024073185 104 | Tue Oct 24 2023 5.843824698 0.001450071 105 | Mon Nov 20 2023 2.769629785 0.00412885 106 | Sun Dec 17 2023 1.510088786 0.009019941 107 | Sat Jan 13 2024 1.229833209 0.009548245 108 | Fri Feb 09 2024 1.151783122 0.001244891 109 | Thu Mar 07 2024 1.151595311 0.004346904 110 | Wed Apr 03 2024 0.926003689 0.031770059 111 | Tue Apr 30 2024 0.780834242 0.003358146 112 | Mon May 27 2024 1.074685376 0.037664874 113 | Sun Jun 23 2024 1.678161547 0.015925179 114 | Sat Jul 20 2024 2.911868023 0.005247861 115 | Fri Aug 16 2024 2.492166171 0.01647807 116 | Thu Sep 12 2024 4.310214823 0.054814197 117 | Wed Oct 09 2024 5.630645194 0.010843767 118 | Tue Nov 05 2024 6.184918437 0.003130416 119 | --------------------------------------------------------------------------------