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.