Using GIS and Remote Sensing in Assessment of Water Scarcity in Nakuru County, Kenya

• 作者: Arthur W. Sichangi Catherine Changwony Moses Murimi Ngigi
• 来源期刊: 遥感技术进展(英文)
• 学科: 医学
• 关键词: LAND Use LAND COVER (LULC) METEOROLOGICAL DROUGHT Standard Precipitation Index (SPI) Water SCARCITY
• 年，卷（期）: 2017,（1）
• 页码范围: 88-102
• 页数: 15页
• 分类号: R73

摘要

Water is at the core of sustainable development and is critical for socio-economic development, healthy ecosystems and for human survival. This research study has been carried out in Nakuru County, a tropical region in the Rift Valley of Kenya, bounded between latitude 0.28°N and 1.16°S, and longitude 36.27°E and 36.55°E. The objective of the study has been to use GIS and remote sensing in assessment of water scarcity using Land use Land cover area changes, standard precipitation index and crop yields. Landsat satellite images for the year 1985, 1995, 2005 and 2015 were used. Classification was done using maximum likelihood algorithm while classification accuracy assessment entailed the use of confusion matrix method and ground truth data. Post classification change detection results gave percentage cropland areas as 21% in 1985, 29% in 1995, 53% in 2005 and also 53% in 2015. Eleven (11) ground rainfall stations and TRMM satellite rainfall data from 1985 to 2015 has been used to show meteorological drought. Validation of rainfall data done using correlation coefficient (R2) and root mean square (RMS) methods showed that ground rainfall data and TRMM data correlate. Modelling of 3 months SPI for each of the three seasons (MAM, JJA and OND) has been done using interpolation distance weighted method (IDW). 3 months SPI time scales curves gave October 1987 May 1993, and July 2004 as water scarce and dry seasons and were categorized as either Normal, moderately dry, severely dry and extremely dry. Crop yield trends curves showed crop yield decrease in this identified water scarce and dry years. Conclusion reached is that crop yields is not dependent on size of land ploughed only but mostly on rainfall quantities. Therefore, the findings of this research can be used as drought monitoring tools.