Results
Model calibration and validation
results
The raster-based Xin’anjiang model captured the seasonal trend of
discharge and extreme flows in heavy rainfall events (Fig. 2). Discharge
in Hengtangcun was well simulated with a correlation coefficient
(R2 ) and Nash-Sutcliffe efficiency coefficient
(NS ) value of 0.90 and 0.81 in calibration period and withR2 and NS value of 0.93 and 0.81 in
validation period respectively. Several discharge peaks (e.g., on Aug.
10, 2009 and Jun. 14, 2011) were well described.
Fig. 2 Daily observed and
simulated discharge at Hengtangcun station during model calibration
(2009-2011) and validation periods (2012).
Simulated water level from NDP model has been verified using data from a
typical polder close to the study area, which performances were
acceptable with the NS value of 0.73 and 0.50 for the calibration
and validation periods (Huang et al.,
2018a). More details can be found in the Supporting Information.
The different hydrological responses to climate change and
land use between mountain and lowland artificial
watersheds
We compared the simulated hydrological processes between mountain and
lowland artificial watersheds under current and each future climatic and
land use conditions. To quantify the influence of future climate change,
we changed temperature and precipitation parameters corresponding to
climate change scenarios from CMIP6 for the 2030s, 2050s, 2070s and
2090s, and kept the other parameters of the two models unchanged. To
quantify the influence of future land use, we evaluated discharge
variations for the 2050s under the developed land use scenarios with the
current change rate, using the identical climate data from 2009 to 2012.
Hydrological responses to climate
variability
Monthly discharge and evaporation calculated from the 2009-2012 basic
data were used to compare the different hydrological responses to
climate variability between mountain and lowland artificial watersheds.
Fig. 3(a) showed the slope (4.75) of evaporation-temperature linear
correlation in lowland watersheds was larger than in mountain watersheds
(2.61), accounting for the same growth in temperature would cause larger
evaporation increment in lowland. Fig. 3(b) showed anR2 of 0.65 in mountain watersheds was larger
than that in lowland watersheds (0.12). This may because precipitation
was the unique water resource in mountain watersheds while irrigation
also controlled discharge in lowland artificial watersheds.
Fig. 3 The linear correlation of
evaporation-temperature (a) and discharge-precipitation (b) in mountain
watersheds (blue points) and lowland artificial watersheds (orange
points).
In case that temperature and precipitation changed simultaneously in
future climate change scenarios, the mean annual runoff change was more
significant in mountain (10~200%) than in lowland
(10~60%) (Fig. 4). In terms of season,
autumn
and winter were significantly related to the increment in mountain
watersheds, and summer and autumn (rice seasons) had a largest
contribution in lowland watersheds. The R2between precipitation variability and mean annual runoff change was 0.78
in mountain, comparing to 0.96 in lowland. TheR2 between annual average temperature and
runoff variability was negligible (0.05) in mountain comparing with that
(0.33) in lowland. Therefore, the dominated factor for runoff variation
under climate change scenarios was precipitation.
Fig. 4 The annual and seasonal
runoff variation under future climate scenarios. RCP2.6_20, RCP4.5_20,
RCP8.5_20 were the simulations for the 2030s; RCP2.6_40, RCP4.5_40,
RCP8.5_40 were the simulations for the 2050s; RCP2.6_60, RCP4.5_60,
RCP8.5_60 were the simulations for the 2070s; RCP2.6_80, RCP4.5_80,
RCP8.5_80 were the simulations for the 2090s.
Hydrological responses to land
use
In order to learn the hydrological processes response to the different
land use conditions, we subdivide the mountain watersheds into several
sub-watersheds based on DEM, and the lowland artificial watersheds into
several polders based on satellite images. Different metrics and
thresholds have been used to characterize discharge regimes
(Berihun et al., 2019). The annual mean
runoff coefficient (α) is the average value of the ratio of annual
runoff depth to annual precipitation depth. In lowland artificial
watersheds, discharge is the total amount of seepage, culvert drainage
and flood drainage, excluding the inflowing irrigation. A higher value
of α correlates with the difficulty in absorption of precipitation by
soil. The coefficient of variation (CV) is the ratio of standard
deviation to average value. Here it estimates the variation extent of
daily discharge in each sub-watershed (polder) as results of different
land use conditions.
It can be found that α in mountain watersheds (0.41) was generally
larger than that in lowland watersheds (0.36). It had a relatively weak
negative correlation with the ratio of cultivate land in mountain
(R2 =-0.28), compare to the relatively strong
negative correlation in lowland (R2 =-0.85). In
addition, the CV of discharge was generally larger in lowland watersheds
(2.39) than in mountain watersheds (1.02), which was positively related
to the ratio of cultivate land in the former
(R2 =0.55) while negatively related to the ratio
in the latter (R2 =-0.37). This is probably
because in lowland artificial watersheds, the surface runoff flowing in
or out of the cultivate land were controlled by pumping stations,
generating sharper discharge hydrograph with higher peak-values and
lower minimum-values (Yan et al., 2018).
In terms of the ratio of water area, the CV of discharge had a negative
relation (R2 =-0.83) with it in lowland
watersheds comparing to non-significance in mountain watersheds, partly
accounting for the capacity of regulating flow of ponds in polders. With
respect to the ratio of residential area, we found that α having an
extremely strong positive correlation (R2 =0.99)
with it in lowland. The other result like α and CV value of discharge in
mountain watersheds were positively correlated to the slope
(R2 =0.73 and 0.82 respectively), implying that
sloping regions more likely lead to the productions and variations of
surface runoff (Fig. 5).
Fig.
5 The description of discharge characteristics and the land use
conditions in mountain watersheds and lowland artificial watersheds
respectively (Left); The different responds of surface runoff to the
ratio of land use types and slope classes between mountain watersheds
and lowland artificial watersheds (Right).
Note: α: the annual mean runoff coefficient; CV: the coefficient of
variation of surface runoff; Farm: cultivated land; W: water area; R:
residential area; For: forest land; G: grass land.
Monthly and annual runoff variations between two watersheds were
compared to evaluate the different effects of future land use
conversions. For the 2050s, keeping the current rate of land use change,
the most dramatic variations of annual runoff in mountain watersheds
were found under the scenarios of converting cultivate land, forestland
or grassland into residential area (increasing 7.8%, 3.5% and 1.7%
respectively). Moreover, under the above three scenarios, seasonal
runoff showed increasing trend especially in May. The most significant
changing of annual runoff in lowland artificial watersheds was found in
the scenarios of converting cultivate land into residential area or into
water area (increasing 22.0% and 2.1% respectively).
The
seasonal runoff showed a dramatic increase except in winter (from Dec.
to Feb.) when converting cultivate land into residential area. It showed
a slight increasing trend except in summer when converting cultivate
land into water area because of the reduced irrigation. Overall, the
effects of land use change on runoff were generally more significant in
lowland artificial watersheds than that in mountain watersheds (Fig. 6).
Fig. 6 The different effects of
land use conversions on monthly (a, b) and annual (c, d) runoff between
mountain watersheds (a, c) and lowland artificial watersheds (b, d). The
value of (c) and (d) represents annual runoff in X axis to that in Y
axis.
Note: Farm: cultivated land; For: forest land; G: grass land; R:
residential area; W: surface water area.
Water balance at mountain and lowland artificial watersheds
under future
scenarios
Land use change scenarios were generated along the same storylines as
climate change scenarios based on RCP 2.6 for the 2050s to assess the
additive impacts of the two stressors. In mountain watersheds, climate
changes itself led to an increase by 0.7 mm and 312.9 mm in annual
evaporation and annual runoff respectively, probably due to the
increment in rainfall. When combined with land use change, the water
balance components varied slightly on the whole. Therefore, water
balance in mountain watersheds were more sensitive to climate change.
The land use change had weak enhancing effects on climate impacts
(Mountain: S1, S2, S3 in Fig. 7).
In lowland artificial watersheds, the water input was larger than water
output in summer, opposite to autumn, which related to the special water
management and drainage rhythm of polders. As to evaporation component,
it sharply declined by 266.6 mm when combining the effect of land use
change, mainly due to the absence of rice evapotranspiration
(Evaporation: S1, S2 in Fig. 7). Irrigation showed a decrease of 77.5
mm when rising 24.4% of annual precipitation (Irrigation: S0, S1 in
Fig. 7), and decline became more apparent with the cultivate land
shrinking (Irrigation: S1, S2 in Fig. 7). Pump drainage notably
increased by 213.8 mm in response to the increment in precipitation
(Pump: S0, S1 in Fig. 7), and when combining land use change, the
capacity of retaining water of increased ponds can mitigate 57.2 mm of
flood discharge (Pump: S1, S2 in Fig. 7). Culvert drainage increased by
25.8 mm with precipitation (Culvert: S0, S1 in Fig. 7). Moreover,
cultivate land shrinking was direct to the reduction of water holding,
consequently the culvert drainage increased another 111.7 mm (Culvert:
S1, S2 in Fig. 7). Seepage increased abruptly by 138.6 mm under future
land use change scenarios (Seepage: S1, S2 in Fig. 7). In summary, the
land use change had strong combined effects on climate factors in
lowland artificial watersheds.
Fig. 7 Water balance simulations
of mountain and lowland artificial watersheds under climate change and
land use scenarios for the 2050s. S0: Historical climate scenario + a
baseline land use scenario. S1: RCP2.6 climate scenario + a baseline
land use scenario. S2: RCP2.6 climate scenario + developed land use
scenario for the 2050s.