3.1.2. Spatial and temporal consistency
The mean ETIa-WPR, SMC and NDVI were plotted for all climate zones for the northern and southern hemisphere. Figure 6 shows some examples of the largest sub-zones per main climate; wet tropical-savanna (Aw), arid-desert-hot (Bwh) and temperate-dry winter-warm summer (Cwb). The average ETIa-WPR (y-axis on the left), and SMC and NDVI (y-axis on the right) are reported from dekad 0901 (2009 - dekad 1) to 1836 (2018 – dekad 36).
The temporal trend for each climate zone is inversed between hemispheres, reflecting the opposite seasons between hemispheres. For example, peak ETIa-WPR values occur around dekad 19 and trough values occur around dekad 01 in the northern hemisphere. Conversely, in the southern hemisphere, peak ETIa-WPR values occur around dekad 01 and trough values occur around dekad 19. The inverse pattern highlights the need to separate climate zones based on hemisphere, as these trends would otherwise cancel out and flatten out temporal trends.
The Aw zones are maintaining the highest ETIa-WPR values and shows the lowest relative variability throughout the year. The BWh zones consistently have lower ETIa-WPR values. The BWh in the southern hemisphere is higher than in the northern hemisphere, and the relative intra-annual variation is greater. The ETIa-WPR in these zones follows a clear seasonal pattern, that is not evident from the NDVI or the SMC. The ETIa-WPR is predominantly governed by evaporation in these arid zones, which is indicated by the low NDVI all-year-round. The temperate zone, Cwb, shows the greatest intra-annual variability in ETIa-WPR, which reflects the more dramatic climatic seasonal variation in these years. ETIa-WPR in Cwb in the northern hemisphere shows two peaks per year. The two seasons are consistent with the zones’ location in the Rift Valley of Eastern Africa. The Rift Valley experiences two wet seasons as influenced by the intertropical convergence zone (Hills, 1978) and the longer wet season.
ETa is either controlled by available energy or available water. All zones, other than BWh and Aw in the northern hemisphere, show a clear relationship between the ETIa-WPR and the NDVI and SMC. The Aw zone in the southern hemisphere, shows two ETIa-WPR peaks a year in the northern hemisphere, while, SMC and NDVI show one. Therefore it is related to net radiation. Although not shown here – ETIa-WPR in BWh in the northern hemisphere follows the same seasonal trend as radiation. In the Aw zone in the northern hemisphere, the net radiation peaks several dekads before the NDVI and SMC, resulting in a double-peaked ETIa-WPR. The ETIa-WPR in BWh zone shows a clear seasonal trend, despite no clear seasonal NDVI or SMC trend. Therefore it is governed by the amount of solar radiation which has a clear yearly trend at the latitudes within the BWh zone.
3.2 Direct validation
The agreement between ETIa-WPR and ETa-EC is shown in Figure 7 and Table 6. Figure 7 shows the time series of ETIa-WPR and ETa-EC for all available in-situ data from all EC stations. Table 6 shows the corresponding metrics for each station, including r, RMSE, bias, the R2 and the average NDVI and LST quality for the comparison period. A good overall correlation (r=0.75) is found between all sites and observations. However, substantial variations existed between sites. Consistency in results is seen between years for most sites. The ETIa-WPR typically captured seasonality well at most sites.
The best-performing sites are SN-DHR and SD-DEM. The SN-DHR and SD-DEM sites are characterised by arid or semi-arid climates and short vegetation. The ETIa-WPR closely follows the ETa-EC at the SN-DHR and SD-DEM site, and both respond quickly to rainfall events. At these sites, the WaPOR SMC and NDVI are well related to both the ETa-EC and ETIa-WPR. For example, the R2 for the SMC or NDVI and ETa-EC or ETIa-WPR ranges between 0.82-0.87 at SN-DHR and 0.69-0.86 at SD-DEM. SD-DEM does overestimate ETIa-WPR when ETa-EC is low and NDVI is low.
ETIa-WPR is also performing well at ES-SCL, ZM-MON, CG-TCH, EG-ZAN, EG-SAA, EG-SAB and SA-SKU. Excluding CG-TCH, these sites have high-quality LST and NDVI layers (the average LST quality for the comparison period is equal to or less than 1). The good performance at this site may be because the variation in CG-TCH station ETa-EC and ETIa-WPR is strongly related to the VDP derived from the EC station and RET, with R2=0.62 and 0.66 respectively. The VDP and RET are derived from GEOS-5 (VDP and RET) and MSG (RET only), as compared to being derived from satellite images. GEOS-5 and MSG are available daily and satellite image gaps do not influence the quality of the VDP and RET quality.
The ETIa-WPR frequently overestimates ETa-EC show good correlations and R2 between ETa-EC and ETIa-WPR at the irrigated agriculture sites, EG-ZAN, EG-SAA and EG-SAB. However, the ETIa-WPR is systematically larger than the ETa-EC during both high and low ETa-EC, as indicated by the average daily bias (Table 6). The seasonal values ETIa-WPR and ETa-EC for the summer maize 2012 crop at EG-ZAN are 682 mm and 424 mm, respectively. Compared to ETa from a lysimeter (ETa-lys), 543mm, as cited in literature (Atta et al. , 2015), at EG-ZAN for the same crop and period. It, therefore, suggests that the ETa at the irrigated sites fall somewhere between the ETa-EC and L1 ETIa-WPR. The overestimation is likely directly related to the net radiation difference between the EC and WaPOR datasets as inferred from the RET estimated from the EC data and compared to the WaPOR RET. The WaPOR RET has a high linear agreement with the EC RET (R2=0.93). However, the bias of WaPOR RET is consistently 50% greater than the EC RET.
ETIa-WPR and ETa-EC show a weak correlation at NE-WAF and NE-WAM. The ETIa-WPR begins increasing earlier in the season, particularly at NE-WAM, and although the ETIa-WPR is capturing the seasonal trend, it is not capturing the magnitude of the ETa-EC summer values. The difference is likely related to the low-quality NDVI and LST layers during the summer (average annual values LST and NDVI gaps appear low in Table 6, however major gaps are concentrated in the summer season). These sites are not highly correlated with the site VDP or RET and therefore the lower quality LST and NDVI is expected to have a great impact on the quality of ETIa-WPR here. The ETIa-WPR is strongly related to the SMC at these sites (e.g. R2=0.73 at NE-WAM); however, the ETa-EC shows no relationship with the WaPOR SMC (R2=0.37 at NE-WAM). Both of these sites are dominated by evaporation (in WaPOR) for most of the year – as indicated by low NDVI all year.
The ETIa-WPR performance at BN-NAL is not capturing the site seasonality well. BN-NAL ETIa-WPR and ETa-EC show annual values ranging from 1.4-4.5mm/day and 0.6-6.9mm/day respectively. The ETIa-WPR at BN-NAL does not appear to capture the rainy period in July-September where the highest gaps in the NDVI exist (low NDVI quality). At this site, the WaPOR SMC and NDVI layers have a stronger relationship with the ETa-EC than the ETIa-WPR. For example, the R2 between the WaPOR NDVI and the ETa-EC and the WaPOR NDVI and the ETIa-WPR are 0.87 and 0.56 respectively. This is, therefore, pointing to an overestimation of the evaporation component when NDVI is low and an underestimation of the transpiration component when the transpiration is high.
The ETIa-WPR has the lowest performance at the GH-ANK and KWSTI in terms of both the regression and the temporal trends. The GH-ANK site is characterised by a tropical climate and high vegetation height (evergreen forest). Further, the ETa-EC is not strongly related to the VDP or the RET. The VDP at this site ranges from 0.07-0.81 with high relative humidity. The KWSTI site is located in the Rift Valley, between the Aberdares Ranges to the east and the Mau escarpment to the west. This setting creates a complex micro-climate with significant diurnal variation in temperature and wind speed, among other meteorological variables. This site has an inferior NDVI quality layer and a very low correlation with VDP. As a result, errors in the input meteorological data may highly influence ETa-EC estimates at the site.
The results improve slightly for all sites on a monthly scale. The Monthly mean daily ETIa-WPR plotted against monthly mean daily ETa-EC is shown in Figure 8. The R2 metric improves the most. The RMSE improves at all stations except EG-SAA, where the RMSE increases by 63%. The correlation and R2 improved slightly at all stations. The correlation and R2 increase on average, across stations – not weight, by 9% and 8% respectively. The absolute bias increases slightly at 5 of the 14 stations.
3.3 Level consistency
The consistency between the evaporation and transpiration data products for the L1 and L2 data products is high. The ETIa-WPR RMSE, between L1 and L2, for each dekad for the 2009-2018 period ranged from 0.01 to 0.11mm/day with a median of 0.03mm/day, while the correlation ranged from 0.95 to 1.00 with a median of 0.98. The median R2 over the period is 0.96 while the median bias is 7%. The consistency between layers dropped slightly after 2014. In 2014 the PROBA-V was introduced for L2, as compared to resampling of MODIS to 100m before 2014. The median correlation dropped from 1.0 to 0.96, and the median RMSE increased from 0.01 mm/day to 0.04 mm/day. A slight positive systematic bias, in favour of L2, is evident after 2013, with median bias increased from 4% to 9%.
The L1 and L3 ETIa-WPR products have a lower consistency as compared to the L1 and L2 products in the four irrigation areas. The mean ETIa-WPR values for all dekads in the Zankalon and Awash schemes are shown in Figure 9. The Awash area has the highest consistency of all scheme areas, reflected in the highest correlation, R2. The ETIa-WPR RMSE between L1 and L3 in the Wonji ranges from 0.42-1.01mm/day, while the correlation ranges from 0.63-0.92. The median correlation for all dekads in the study period is 0.84, and the median R2 is 0.84. The RMSE is highest when the ETIa-WPR is highest. The RMSE temporal trend is in line with the seasonal trend in the Awash and displays the two seasons associated with the intertropical convergence zone. The correlation is above 0.73 on 95% of dekads, and lowest on dekads when the mean ETIa-WPR is highest.
The Koga has the lowest consistency of the schemes. Although the RMSE between L1 and L3 is lower, ranging from 0.26-0.71mm/day, the median correlation is 0.67, and the median R2 is 0.45. Zankalon performed slightly better, with a median correlation of 0.71 and a median R2 of 0.51. The RMSE is higher in Zankalon than the Koga, but this reflects the higher ETIa-WPR values found in the area. The ODN had the same RMSE (0.64mm/day) as Zankalon and the highest range of RMSE (0.15-1.62mm/day). The correlation and R2 are also similar, with median values of 0.73 and 0.53 respectively. All schemes show similar per cent bias medians (9-12%). The only scheme that shows a systematic bias is ZAN, where the L1 is consistently higher ETIa-WPR values than L3.
The 10-daily average ETa-EC and ETIa-WPR for all three spatial resolutions at EG-ZAN are shown in Figure 10. The L1 and L2 ETIa-WPR show high consistency with each other. The L3 ETIa-WPR is consistently sitting between the ETa-EC and the L1 and L2 ETIa-WPR. All levels capture the overall ETa-EC seasonal trends. The L3 data shows a slightly lower R2 (L3=0.66 and L1=0.69) and correlation (L3=0.53 and L1=0.68), but a much lower bias (L3=1.06mm/day and L1=1.68mm/day) and a lower RMSE (L3=0.99mm/day and L1=2.19mm/day) when compared with ETa-EC. The better R2 and correlation reflect the L1 and L2 ETIa-WPR ability to capture the temporal fluctuations of ETa-EC better than L3 ETIa-WPR. An example of this is at dekad 1117, where L1 and L2 ETIa-WPR capture the ETa-EC dip, whereas L3 ETIa-WPR stays flat. The L3 ETIa-WPR have a better seasonal agreement with the ETa-lys for the summer maize crop in 2012 (L3=487mm, L1=682mm and ETa-lys=543mm).
The NDVI and ETIa-WPR for the 250m buffer are shown in Figure 11 for the three spatial resolutions. The 30m level is picking up more spatial variation (standard deviations: L3=0.05, L2=0.02; L1=0.02) at the site and has a lower mean NDVI for the site as compared to L2 and L1 (mean: L3=0.74; L2=0.82 and L1=0.83). This reflects the lower ETIa value for this dekad, which is more similar to the EC – as seen in Figure 10.