Assessment of Water Level in Dadin Kowa Dam Reservoir in Gombe State Nigeria Using Geospatial Techniques

Year 2019, Volume: 6 Issue: 1, 115 - 130, 12.04.2019

Etido Essien , Ezeikel Jesse Joel Igbokwe

https://doi.org/10.30897/ijegeo.487885

Cited By: 4

Abstract

Reservoirs have been found to
provide a convenient source of water for different purposes to rural
communities and this makes them indispensable, and they are quite important in
improvement of livelihoods of rural community. The study applied Geospatial
techniques in assessing the Dadin Kowa Dam Water level in Gombe State, Nigeria.
To achieve the objectives of this study, two major data were acquired. The
water reservoir level recorded from 1987 till 2013 was collected from Upper
Benue River Basin Development Authority also Landsat satellite imagery from
1987, 2000 and 2015 were acquired. Supervised image based classification was
applied to assess the class of land use land cover in the area of study. The
extents (surface areas) of the Dadin Kowa Dam were delineated from Landsat
satellite images using the Normalized Difference Water Index (NDWI). the water
level record was arranged in Microsoft Excel and the mean of the water level
for 1987, 2000, and 2015 were used to assess the change both in extent and
volume. The result shows that from 1987 to 2000 the water level increased and
decreased from 2000 to 2015 due to the climate change condition and the high
rate consummation of water due to population growth of the area from 266844 in
1991 to 367500 in 2016. Dadin Kowa reservoir may completely dry up by the year
2029 if the climatic condition remains as it is.

Keywords

Dam management, Water level, Landsat, NDW, land use

References

• Abdullaev, I., De Fraiture, C., Giordano, M., Yakubov, M., Rasulov, A. (2009). Agricultural water use and trade in Uzbekistan, Situation and potential impacts of market liberalization. Water Resources Development 25(1): 47–63.
• Alsdorf, D., Rodriguez, E., Lettenmaier, D. (2007). Measuring surface water from space. Rev. Geophys, 45.Baup, F., Frappart, F., Maubant, J. (2014). Combining high-resolution satellite images and altimetry to estimate the volume of small lakes. Hydrol. Earth Syst. Sci. 18, 2007–2020.
• Baup, F., Frappart F., Maubant. (2014). Combining high-resolution satellite images and altimetry to estimate the volume of small lakes Hydrol. Earth Syst. Sci., 18, 2007–2020.
• Birkett, C. (1995). The contribution of topex/poseidon to the global monitoring of climatically sensitive lakes. J. Geophys. Res. Oceans, 100, 25179–25204.
• Calmant, S., Seyler, F., Cretaux, J. (2008). Monitoring continental surface waters by satellite altimetry. Surv. Geophys. 29, 247–269.
• Congalton R., Green, K. (2009) Assessing the accuracy of remotely sensed data: Principles and practices, 2nd edn. Taylor & Francis, Baco Raton
• Calvet, J.C., Wigneron, J.-P., Walker, J., Karbou, F., Chanzy, A., Albergel, C. (2011). Sensitivity of passive microwave observations to soil moisture and vegetation water content: L-band to w-band. IEEE Trans. Geosci. Remote Sens. 49, 1190 1199.
• Cihlar, J., Beaubien, J., Latifovic, R., Simard, G. (2005). Land cover of Canada version CD-ROM. Natural Resources Canada, Ottawa
• CHEN, Y., XU, Y., YIN, Y. (2009). Impacts of land use change scenarios on storm-runoff generation in Xitiaoxi basin, China. Quaternary Int. 208 (1–2) 121–128.
• Crétaux, F., Birkett, C. (2006). Lake studies from satellite radar altimetry. C. R. Geosci. 338, 1098–1112.
• Crétaux, F., Jelinski, W., Calmant, S., Kouraev, A., Vuglinski, V., Bergé-Nguyen, M., Gennero, C., Nino, F., Del Rio, A., Cazenave, A. (2011). Sols: A lake database to monitor in the near real time water level and storage variations from remote sensing data. Adv. Space Res. 47, 1497–1507.
• Daily, G. (1997). Nature’s Services: Societal Dependence on Natural Ecosystems; Island Press: Washington, DC, USA, 329.
• Desmet, P., Govers, G. (1996). A GIS procedure for automatically calculating the USLE LS factor on topographically complex landscape units. J. Soil Water Conserv. 51, 427–433.
• Duan, Z., Bastiaanssen, W. (2013). Estimating water volume variations in lakes and reservoirs from four operational satellite altimetry databases and satellite imagery data. Remote Sens. Environ. 134, 403–416.
• Duan, Z., Bastiaanssen, W. (2013). Estimating water volume variations in lakes and reservoirs from four operational satellite altimetry databases and satellite imagery data. Remote Sens. Environ. 134, 403–416.
• Dukhovny, A. (2003). The Aral Sea Basin – Rumors, realities, prospects. Irrig.and Drain. 52: 109 120.Food & Agriculture Organization of United
• Nations. (2007). http://www.fao.org.
• Frappart, F., Seyler, F., Martinez, M., Leon, G., Cazenave, A. (2005). Floodplain water storage in the Negro river basin estimated from microwave remote sensing of inundation area and water levels. Remote Sens. Environ. 99, 387–399.
• Frappart, F., Calmant, S., Cauhopé, M., Seyler, F., Cazenave, A. (2006). Preliminary results of ENVISAT RA-2-derived water levels validation over the Amazon basin. Remote Sens. Environ. 100, 252–264.
• Frappart, F., Papa, F., Güntner, A., Werth, S., Da Silva, S., Tomasella, J., Seyler, F., Prigent, C., Rossow, B., Calmant, S. (2011). Satellite-based estimates of groundwater storage variations in large drainage basins with extensive floodplains. Remote Sens. Environ. 115, 1588–1594.
• Heaven, S., Koloskov, B., Lock, C., Tanton, W. (2002). Water resources management in the Aral Basin: a river basin management model for the Syr Darya. Irrigation and Drainange. 51(2) 109-118.
• Hundecha, Y., Bardossy. A. (2004). Modeling of the effect of land use changes on the runoff generation of a river basin through parameter regionalization of a watershed model, J. Hydrol. 292, 281–295.
• Hu, Z., Gong, H. and Zhu, L. (2007) Fast Flooding Information Extraction in Emergency Response of Flood Disaster. Proceedings of the ISPRS Workshop on Updating Geo-Spatial Databases with Imagery and the 5th ISPRS Workshop on DMGISs, Urumchi, 28-29 August 2007, 173-177.
• Iclei, (2012). Sea Level Rise Adaptation Strategy for San Diego Bay. 133 pp., ICLEI-Local Governments for Sustainability USA, San Diego, CA.
• Jawak, D., Kulkarni, K., Luis, J. (2015). A review on extraction of lakes from remotely sensed optical satellite data with a special focus on cryospheric lakes. Adv. Remote Sens. 4, 196 213.
• Jensen, R. (2009). Remote Sensing of the Environment: An Earth Resource Perspective 2/e; Pearson Education: Delhi, India, 15–17.
• Kazbekov, J., Rakhmatullaev, S., Huneau, F., Coustumer, P. (2007). Types & Hydrogeologic Features of surface and groundwater interactions in Uzbekistan. 35th International Association of Hydrogeologists Congress, Lisbon, Portugal, 17 21 September 2007. Conference Proceedings, ISBN978-989-95297-3-1.
• McFeeters, K. (1996). The use of the normalized difference water index (NDWI) in the delineation of open water features. Int. J. Remote Sens.17, 1425–1432.
• Medina, E., Gomez-Enri, J., Alonso, J., Villares, P. (2008). Water level fluctuations derived from ENVISAT Radar Altimeter (RA-2) and in-situ measurements in a subtropical waterbody: Lake Izabal (Guatemala). Remote Sens. Environ.112, 3604–3617.
• Micklin, H., Kluwer. (2004). The Aral Sea crisis. In: Dying and dead Seas-Climatic versus Anthropic causes, Academic Publishers,Netherlands; 49-76.
• Nation Emergency management. (2012). Report.http://nema.gov.ng/south-south-lost-n2-51trn-to-floods-in-2012-says-nema/
• O’Hara, L. (2000). Lessons from the past: water management in Central Asia. Water Policy 2: 365-384
• Phan, H., Lindenbergh, R., Menenti, M. (2012). ICESat derived elevation changes of Tibetan lakes between 2003 and 2009. Int. J. Appl. Earth Obs. Geoinf. 17, 12–22.
• Rakhmatullaev, S. (2006). Geoinformation systems for estimation of reservoir volume Capacities due to sedimentation. Final Proc. IV Conf. Specialis President Foundation ISTEDOD, November 24 25, 40-51.
• Ramillien, G., Frappart, F., Seoane, L. (2014). Application of the regional water mass variations from grace satellite gravimetry to large-scale water management in Africa. Remote Sens. 6, 7379–7405.
• Rokni, K., Ahmad, A., Selamat, A., Hazini, S. (2014). Water feature extraction and change detection using multitemporal Landsat imagery. Remote Sens. 6, 4173–4189.
• Singh, A., Seitz, F., Schwatke, C. (2012). Inter annual water storage changes in the Aral Sea from multi-mission satellite altimetry, optical remote sensing, and GRACE satellite gravimetry. Remote Sens. Environ. 123, 187–195.
• Sharma, O., Mioc, D. and Anton, F. (2007) Feature Extraction and Simplification from Colour Images Based on Colour Image Segmentation and Skeletonization Using the Quad-Edge Data Structure. Proceedings of the International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, Plzen, 29 January-1 February 2007, 225-232.
• Sun, F., Sun, W., Chen, J., Gong, P. (2012). Comparison and improvement of methods for identifying waterbodies in remotely sensed imagery. Int. J. Remote Sens. 33, 6854–6875.
• Snyder, F. (1938). Synthetic Unit Graphs. Trans. Am. Geophys. Union 19 447–454.
• Timawus, M. (2010). Jonathan Needs More Than Good Luck. Daily Trust. 05-23.
• Tourian, M., Elmi, O., Chen, Q., Devaraju, B., Roohi, S., Sneeuw, N. (2015). A spaceborne multisensor approach to monitor the desiccation of Lake Urmia in Iran. Remote Sens. Environ. 156, 349–360.
• UBRB (Upper Benue River Basin). (2015). Rain fall data report in the northeast Nigeria.USACE. (2008). HEC-HMS Hydrologic Modeling System User’s Manual. Hydrologic Engineering Center,
• Davis, CA.Vivoni, R. (2007). Variation of hydro meteorological conditions along a topographic transect in north western Mexico during the North American monsoon. J. Clim. 20 1792–1809.
• Wijesekara, N., Gupta, A., Valeo, C., Hasbani Jg, Y., Delaney, P., Marceau, J., (2012) Assessing the impact of future land-use changes on hydrological processes in the Elbow River watershed in southern Alberta, Canada. J. Hydrol. 412–413 220–232.
• World Bank. (2003). Irrigation in Central Asia: Social, economic and environmental considerations. www.worldbank.org/eca/environment.
• Volpi, M., Petropoulos, P., Kanevski, M. (2013). Flooding extent cartography with Landsat TM imagery and regularized kernel fisher’s discriminant analysis. Comput. Geosci. 57, 24–31.
• United Nations Development Programme, (UNDP). (2007). Water, critical resource for Uzbekistan’s future.UNDP Program, Tashkent, Uzbekistan, 121p.
• Wang, X.W., Gong, P, Zhao, Y, Xu, Y., Cheng, X., Niu, G., Luo, C., Huang, B., Sun, D., Li, W. (2013) Water-level changes in China’s Large Lakes determined from ICESat/GLAS data. Remote Sens. Environ. 132, 134–144.
• Yan, J., Qi, W. (2012). Lakes in Tibetan Plateau extraction from remote sensing and their dynamic changes. Acta Geosci. Sin. 33, 65–74.
• Yang, X. (2002). Satellite monitoring of urban spatial growth in the Atlanta metropolitan area. Photogramm Eng Remote Sens 68:725–734
• Zhang, J., Xu, K., Yang, Y., Qi, L., Hayashi, S., Watanabe, M. (2006). Measuring water storage fluctuations in Lake Dongting, China, by Topex/Poseidon satellite altimetry. Environ. Monit. Assess. 2006, 115, 23–37.
• Zhu,W., Jia, S., Lv, A. (2014). Monitoring the fluctuation of Lake Qinghai using multi-source remote sensing data. Remote Sens. 6, 1045