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Comparison of WaPOR RS-based to SWAT+ model water productivity estimates in Lake Naivasha Basin, Kenya

Wanjala, Hellen Vivian Khatundi (2020) Comparison of WaPOR RS-based to SWAT+ model water productivity estimates in Lake Naivasha Basin, Kenya.

Link to full-text:https://ezproxy2.utwente.nl/login?url=https://library.itc.utwente.nl/login/2020/msc/wrem/wanjala.pdf
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Abstract:Many countries face challenges in the water and food sector, especially with the current rapid population growth, and increasing water scarcity due to climate change. Policies and actions have been implemented in order to meet these demands. Kenya is among these countries, and applies various policies to boost the land and water productivity in agriculture; crop or livestock, forestry, fisheries and more. The slogan ‘more food per drop’ is often used. Water productivity (WP) refers to the ratio of mass of agricultural output to the amount of water consumed. Different approaches have been adopted in measuring WP. Food and Agriculture Organization, the United Nations (FAO-UN) plays a leading role in this with the Water Productivity Open-access portal of Remotely-sensed data (WaPOR) that provides land and water productivity information across Africa and the Near East. To ensure that WaPOR datasets are efficient to users, quality assessment via validation and comparative analyses have been (and are still) conducted on different WP data components. This research compares WaPOR level II to SWAT+ model WP estimates in the Lake Naivasha basin located in the Rift Valley in Kenya, over an 11 years period (2009-2019). SWAT+, which is a new version of the SWAT model, is a physical-based, semi-distributed hydrological model that performs simulations on crop growth, hydrological balance (surface and groundwater), water quality, and sediment transportation in a catchment. Fieldwork was first conducted, on 8-25th January 2020, with an aim to collect ground-truth information on the land cover, and crop phenological information with the basic land and water management practices from farmers in the catchment. The SWAT+ model for the Lake Naivasha basin was then established to simulate total biomass production and actual evapotranspiration, after which the WP estimates from SWAT+ could be calculated. These were then compared to the WaPOR WP estimates. As the nature of the datasets from these two approaches is different, only the long term average results were compared. Average annual TBP and ETa values of 23723.5 kg/ha/year and 823.6 mm/year, and 31974.7 kg/ha/year and 800.2 mm/year from WaPOR and SWAT+ respectively were obtained. This gave WP of 3.02 kg/m3 and 3.99 kg/m3 in the entire catchment. In addition, wheat and maize crops were analysed. For WaPOR, the crops WP was estimated from TBP and ETa at the area covered, while for SWAT+, the crops WP were estimated from grain yield and ETa at a few studied hydrological response units levels. WaPOR gave average annual TBP, ETa and WP of 23160.7 kg/ha/year, 779.1 mm/year, and 2.98 kg/m3 respectively for wheat. And, 24018.5 kg/ha/year, 836.2 mm/year, and 2.92 kg/m3 respectively for maize. With SWAT+, wheat gave average annual ETa values of 560.5 mm/year and 563.1 mm/year at two HRUs studied (HRU 1621 and HRU 1584), and maize gave 833.7 mm/year and 788.1 mm/year (HRU 257 and HRU 1614). Average annual wheat crop yields of 1261.7 kg/ha/year and 1530.0 kg/ha/year, and for maize yield, 5444.5 kg/ha/year and 3159.1 kg/ha/year were obtained. Therefore, wheat crop WP of 0.23 kg/m3 and 0.27 kg/m3, and maize crop WP of 0.65 kg/m3 and 0.40 kg/m3 were obtained. Maize gave higher WP components than wheat in both approaches, but with differing crop WP. However, results of this study should caution users concerning SWAT+’s current capacity to accurately simulate biomass time series in a catchment. The model does not implement all calculations, and hence, the output generation on crop yields and land cover management is not fully available. Also, the complex nature of the micro climatic conditions of the study area leading to uncertainty in the weather input data, may have highly influenced the results in both WaPOR and SWAT+.
Item Type:Essay (Master)
Faculty:ITC: Faculty of Geo-information Science and Earth Observation
Programme:Geoinformation Science and Earth Observation MSc (75014)
Link to this item:https://purl.utwente.nl/essays/85135
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