Evaluation of surface water dynamics for water-food security in seasonal wetlands, north-central Namibia

Abstract

Agricultural use of wetlands is important for food security in various regions. However, land-use changes in wetland areas could alter the water cycle and the ecosystem. To conserve the water environments of wetlands, care is needed when introducing new cropping systems. This study is the first attempt to evaluate the water dynamics in the case of the introduction of rice-millet mixed-cropping systems to the Cuvelai system seasonal wetlands (CSSWs) in north-central Namibia. We first investigated seasonal changes in surface water coverage by using satellite remote sensing data. We also assessed the effect of the introduction of rice-millet mixed-cropping systems on evapotranspiration in the CSSWs region. For the former investigation, we used MODIS and AMSR-E satellite remote sensing data. These data showed that at the beginning of the wet season, surface water appears from the southern (lower) part and then expands to the northern (higher) part of the CSSWs. For the latter investigation, we used data obtained by the classical Bowen ratio-energy balance (BREB) method at an experimental field site established in September 2012 on the Ogongo campus, University of Namibia. This analysis showed the importance of water and vegetation conditions when introducing mixed-cropping to the region.

Evaluation of the Surface Water Distribution in North-Central Namibia Based on MODIS and AMSR Series

“…Researchers have looked for ways to make farming more robust in this region despite the unstable water supply, e.g., [6,7]. The results suggested that a combination of pearl millet farming with rice (Oryza spp.)…”

Does GRACE see the terrestrial water cycle “intensifying”?

“…This endorheic basin is characterized by highly variable rainfall, ranging from 250 to 830 mm/yr, leading a system of shallow ephemeral streams originating in Angola and spreading over flat planes [ Mendelsohn et al , ]. Widespread surface water variability of unclear origin was detected by Hiyama et al [], using NDVI (Normalized Difference Vegetation Index) derived from the MODIS (Moderate Resolution Imaging Spectroradiometer) instrument. For this region, Ahmed et al [] report a distinct positive trend in TWSA, without identifying a clear increase in precipitation.…”

Trends in use of remotely sensed data in wetlands assessment and monitoring in Zimbabwe

“…Just like in Zimbabwe, most (44.4%) of the EO applications in the SADC region are on LULCC compared to other wetland parameters such as water quantity monitoring (3.7%) and flood regimes monitoring (7.4%). Examples of wetland components assessed using EO data in the SADC region include but are not limited to the following: wetland mapping (De Roeck et al., 2008; Bwangoy et al., 2010; Grundling et al., 2013; Landmann et al, 2013; Pullanikkatil et al., 2016), land use land cover change analysis (LULCC; De Roeck et al., 2008; Grundling et al., 2013; Kashaigili & Majaliwa, 2010; Landmann et al, 2013; Leemhuis et al., 2017; Msofe et al., 2019; Munyati, 2000; Pullanikkatil et al., 2016; Schneibel et al., 2017), vegetation monitoring (Hansen et al., 2008; Mutanga et al., 2012; Naidoo et al., 2019), water quantity monitoring (Grundling et al., 2013; Hiyama et al., 2014), flood regimes monitoring (Meier & Kinzelbach, 2010; Talukdar, 2004) and identification of wetland features (Ringrose et al., 2003; Talukdar, 2004).…”

“…A range of satellite imageries from low resolution to high resolution are utilised. These satellite imageries include but are not limited to the following: National Oceanic and Atmospheric Administration (NOAA; Milzow et al., 2006; Ringrose et al., 2003), Advanced Microwave Scanning Radiometer (AMSR; Hiyama et al., 2014), Satellite Pour l'Observation de la Terre (SPOT; Talukdar, 2004), Environmental satellite (ENVISAT; De Roeck et al., 2008; Milzow et al., 2006), aerial photography (Ringrose et al., 2003), Landsat (Awadallah & Tabet, 2015; Bwangoy et al., 2010; Grundling et al., 2013; Hansen et al., 2008; Kashaigili & Majaliwa, 2010; Msofe et al., 2019; Munyati, 2000; Pullanikkatil et al., 2016; Schneibel et al., 2017), Sentinel (Leemhuis et al., 2017; Naidoo et al., 2019), MODIS (Hansen et al., 2008; Hiyama et al., 2014; Hu et al., 2013) and Worldview (Mutanga et al., 2012; Naidoo et al., 2019).…”

“…Costs related to satellite images processing are not only purchasing costs but they also involve hardware, software, qualified specialists and training especially when dealing with large data sets (Masocha et al, 2017). The implication of costs on choice and effective utilisation of EO data in wetlands assessments are also widely documented in the SADC region (Klerk & Buchanan, 2017;Di Martino et al, 2007;Hiyama et al, 2014;Meier & Kinzelbach, 2010;Thamaga & Dube, 2018).…”