HESSHydrology and Earth System SciencesHESSHydrol. Earth Syst. Sci.1607-7938Copernicus PublicationsGöttingen, Germany10.5194/hess-21-2579-2017Hydrology of inland tropical lowlands: the Kapuas and Mahakam wetlandsHidayatHidayathidayat@limnologi.lipi.go.idTeulingAdriaan J.https://orcid.org/0000-0003-4302-2835VermeulenBartTaufikMuhKastnerKarlhttps://orcid.org/0000-0003-2096-2242GeertsemaTjitske J.BolDinja C. C.HoekmanDirk H.HaryaniGadis SriVan LanenHenny A. J.https://orcid.org/0000-0001-9226-3921DelinomRobert M.DijksmaRoelAnshariGusti Z.NingsihNining S.UijlenhoetRemkohttps://orcid.org/0000-0001-7418-4445HoitinkAntonius J. F.Hydrology and Quantitative Water Management Group, Wageningen University, Wageningen, the NetherlandsResearch Center for Limnology, Indonesian Institute of Sciences, Cibinong, IndonesiaEarth System Science and Climate Change Group, Wageningen University, the NetherlandsResearch Center for Geotechnology, Indonesian Institute of Sciences, Bandung, IndonesiaSoil Science Department, Tanjungpura University, Pontianak, IndonesiaFaculty of Earth Sciences and Technology, Bandung Institute of Technology, Bandung, IndonesiaDepartment of Water Engineering and Management, University of Twente, Enschede, the NetherlandsDepartment of Geophysics and Meteorology, Bogor Agricultural University, Bogor, IndonesiaHidayat Hidayat (hidayat@limnologi.lipi.go.id)24May2017215257925941August201623August201614March201725April2017This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://hess.copernicus.org/articles/21/2579/2017/hess-21-2579-2017.htmlThe full text article is available as a PDF file from https://hess.copernicus.org/articles/21/2579/2017/hess-21-2579-2017.pdf
Wetlands are important reservoirs of water, carbon and
biodiversity. They are typical landscapes of lowland regions that have high
potential for water retention. However, the hydrology of these wetlands in
tropical regions is often studied in isolation from the processes taking
place at the catchment scale. Our main objective is to study the hydrological
dynamics of one of the largest tropical rainforest regions on an island using
a combination of satellite remote sensing and novel observations from
dedicated field campaigns. This contribution offers a comprehensive analysis
of the hydrological dynamics of two neighbouring poorly gauged tropical
basins; the Kapuas basin (98 700 km2) in West Kalimantan and the Mahakam
basin (77 100 km2) in East Kalimantan, Indonesia. Both basins are
characterised by vast areas of inland lowlands. Hereby, we put specific
emphasis on key hydrological variables and indicators such as discharge and
flood extent. The hydroclimatological data described herein were obtained
during fieldwork campaigns carried out in the Kapuas over the period
2013–2015 and in the Mahakam over the period 2008–2010. Additionally, we used
the Tropical Rainfall Measuring Mission (TRMM) rainfall estimates over the
period 1998–2015 to analyse the distribution of rainfall and the influence
of El-Niño – Southern Oscillation. Flood occurrence maps were obtained
from the analysis of the Phase Array type L-band Synthetic Aperture Radar (PALSAR)
images from 2007 to 2010. Drought events were derived from time series of
simulated groundwater recharge using time series of TRMM rainfall estimates,
potential evapotranspiration estimates and the threshold level approach. The
Kapuas and the Mahakam lake regions are vast reservoirs of water of about
1000 and 1500 km2 that can store as much as 3 and 6.5 billion m3 of water, respectively. These storage capacity values can be
doubled considering the area of flooding under vegetation cover. Discharge
time series show that backwater effects are highly influential in the wetland
regions, which can be partly explained by inundation dynamics shown by flood
occurrence maps obtained from PALSAR images. In contrast to their nature as
wetlands, both lowland areas have frequent periods with low soil moisture
conditions and low groundwater recharge. The Mahakam wetland area regularly
exhibits low groundwater recharge, which may lead to prolonged drought events
that can last up to 13 months. It appears that the Mahakam lowland is more
vulnerable to hydrological drought, leading to more frequent fire occurrences
than in the Kapuas basin.
Introduction
Lowland rivers are of major importance for mankind not only due to their
extensive uses for many purposes such as food production, drinking water and
navigation, but they are also important ecosystems that thrive from a regular
supply of nutrients from sediment deposited during floods. Since the very
beginning of agricultural activities, most of the worlds' population has been
concentrated on fertile alluvial floodplains that support food production as
well as access to waterways for transport . Envisioning
the fate of lowland rivers and the adjacent wetlands in response to current
threats, including those stemming from natural processes as well as those of
anthropogenic origin, will likely remain a challenge in the coming years.
Measures to mitigate flood, drought and loss of biodiversity add to elements
that keep lowland rivers a dynamic theme .
Typically, lowlands are located in the downstream part of a river basin in
the form of deltas. However there are also lowlands that are located in more
upstream parts of the basin. The absence of topographical gradients often
leads to the formation of (seasonal) wetlands. The Congo and Amazon are the
best known examples of tropical rainforest regions characterised by vast
areas of lowlands and wetlands . Besides permanent open water
lakes, the Congo basin contains an extensive wetland system with diffuse water
shorelines, which in some areas are inundated under thick vegetation cover,
forming one of the largest swamp forest in the world known as the Cuvette
Centrale . However, there is a lack of knowledge regarding
processes involved in seasonal flooding in tropical lowland areas. Inundation
extent, water depth, groundwater and the storage volume of the wetland are
not well known as few hydrological studies have been conducted in this area
. The floodplain of the Amazon River also contains lakes
that are temporally or permanently connected to the main river by several
channels . Water from the Amazon flows into the floodplain
lakes at the beginning of the rising tide, but by mid-level tide, lake
water gradually flows out into the river . Along with these
processes, groundwater regulates the seasonal dynamics of the Amazon surface
waters . recently assessed the impact of
hydrodynamics on flood wave propagation of the Amazon by coupling a global
hydrologic model with a hydrodynamic model. They found that, although the
coupled runs simulate discharge better than hydrology-only runs, some peak
flows are overestimated due to the lack of a feedback loop to hydrological
processes on floodplains, such as evaporation and groundwater infiltration.
Although definitions of wetlands are based on hydrologic conditions
, hydrology is the aspect of wetlands that is the
most poorly described due to technical, cost and time constraints of field
measurements in this area . Determining an average or specific
hydroperiod, the period in which a soil area is waterlogged, or on the contrary, a
period with below-normal water storage for wetland sites, subsequently
remains a major technical challenge. Piezometers are commonly used to analyse
water levels in studies at the plot scale in peatlands. However, maintaining
them is labour intensive . The
application of satellite remote sensing techniques is one approach which
addresses this scarcity of information. Data from optical sensors such as Landsat
imagery can be used for this purpose in areas with little cloud cover
e.g.. However, it is hard to satisfy the
preferred limit of cloud cover for such images covering the humid tropics.
For this reason, radar remote sensing is considered to be the most suitable
technique for land and water observation in tropical regions.
demonstrate that flood occurrence information and the
corresponding extent of open water, as well as areas under vegetation cover,
can be extracted from a series of images from the Phase Array type L-band
Synthetic Aperture Radar (PALSAR) covering a humid tropical lowland site.
Using images from an L-band SAR sensor, exhibit the
capabilities of radar remote sensing technique for mapping tropical wetland
extent and inundation over large regions. Other approaches that try to
overcome at-site data scarcity involve simulation modelling using large-scale
data sets as input e.g..
Lowland regions are typified by certain hydrological properties, e.g. small
hydraulic gradients, shallow groundwater, a flat topography and a high
potential for water retaining in wetlands . Intensive
groundwater–stream water interactions as well as soil moisture–groundwater
interactions occur in these areas as a result of shallow groundwater
conditions . The hydrology of lowlands is complicated by
backwater effects, lake–river interactions, possible tidal
effects, hydrological extremes, etc. Backwater effects result in an ambiguous
stage–discharge relation such
that, at any given discharge, falling river stages are much higher than
rising stages. Tides have a significant impact on the river flow farther away
from the river mouth in lowland regions by means of subtidal water level
variations controlled by river–tide interactions
. Therefore, hydrological tools, such as the use
of rating curves, rainfall–runoff models and flood prediction, may fall short
if they are applied without a proper adaptation. Novel measurement and
modelling methods such as continuous flow measurements
and neural networks can
be promising means concerning the complex interactions of peat areas,
lakes, runoff and tides in this region. Although tropical wetlands are more
prone to high water, they also regularly suffer from drought
. This requires approaches that consider both hydrological
extremes.
The Kapuas and Mahakam river basins on Kalimantan represent two large
tropical lowland areas. Figure shows the location of the Kapuas
(total catchment area of 98 700 km2) in West Kalimantan and the Mahakam
(77 100 km2) in East Kalimantan. Both rivers are among the longest rivers
worldwide, are found on one island and are characterised by vast areas of inland
lowlands. The size of the rivers, the complex geomorphology of their lowland
channel networks and the hydrological links with the adjacent peat bogs and
inland wetlands, which are prone to drought and forest fires during dry
years, render the Kapuas and the Mahakam basins a scientific challenge. The Kapuas and Mahakam rivers exemplify data-poor environments in the
tropical region, with catchments that comprise vast areas of rainforest. Few
hydrological studies have been conducted in the region despite the rivers'
importance to environment and the people. Parts of these catchments can be
considered relatively pristine, offering a view of a natural hydrological
regime which serves both scientific and engineering purposes. Compared to
their mid- and high-latitude counterparts, a few studies have addressed the
hydrological dynamics of large tropical rivers. This is mainly caused by the
fact that most tropical rivers are poorly gauged. Over the past decade, many
hydrological studies have focussed on the problem of ungauged basins under
the Prediction in Ungauged Basins initiative of
the International Association of Hydrological Sciences. Growing
international research connections attempt to holistically study the
terrestrial system and the development of globally consistent databases,
including those from remote sensing observations, climate stations,
downscaled bias-corrected output from climate models. This gap is now
gradually changing ,
contributing to this trend. By combining field measurements of key
hydrological variables over two large tropical catchments using modelling and
different sources of satellite remote sensing, we can quantify flooding both
in terms of water level, inundated area and volume, and we reveal the impacts
of important processes such as backwater effects.
Our central objective is to study the hydrological dynamics in the Kapuas and
Mahakam river basins, located in of one of the largest tropical rainforest
regions outside the Congo and Amazon using a combination of satellite remote
sensing and novel observations from dedicated field campaigns. Hereby, we put
specific emphasis on key hydrological variables and indicators such as
discharge and flood extent. Resolving hydrological processes is essential to
understand the impact of changes in terrestrial hydrological and
biogeochemical cycles including land degradation on water level dynamics,
water quality and ecology of these important yet vulnerable wetland regions.
The interactions between wetlands and the river have implications for
geomorphology, governing sediment retention and modulating peak discharges,
and for estuarine processes, controlling salinity intrusion during low flow.
The data set will offer a solid database which will find use in future
research and engineering. Section 2 of this paper describes the two study
catchments. Section 3 presents field data gathering to measure water levels,
soil moisture and discharge. This section also describes satellite-based
data that cover the entire catchments and the method used for obtaining
inundation maps. Section 4 presents the results in the form of a hydrological
comparison between the two lowlands. Section 5 presents the discussion, and
conclusions are drawn in Sect. 6.
Map of the research area. Outlined are the Kapuas catchment upstream
of Sanggau (left) and the Mahakam catchment upstream of its delta region
(right), indicated by the black line. Red boxes indicate the focus regions
encompassing the Kapuas and Mahakam lowlands. Red circles indicate the
locations of point rainfall, soil moisture and groundwater observations.
Discharge monitoring stations are located in the city of Sanggau (the Kapuas)
and in the city of Melak (the Mahakam).
Study area
The Kapuas and the Mahakam are the longest and the second longest rivers in
Indonesia with lengths of about 1140 and 980 km, respectively. The Kapuas
and the Mahakam lowlands are located about 650 and 250 km from their
respective river mouths. Lake Sentarum National Park in the upper Kapuas
River is an important Ramsar site, which represents one of old tropical peat
formations in Late Pleistocene . The Mahakam
River is home to endemic species including the Irrawady dolphin
(Orcaella brevirostris), which is listed as “vulnerable” on the
International Union for Conservation of Nature (IUCN) Red List of Threatened
Species due to entanglement in gillnets, vessel traffic,
sedimentation, habitat loss and degradation from habitat change
, etc. The Kapuas and the Mahakam wetlands are important for their
respective local communities, not only as a source of water for domestic
purposes, but also to sustain the livelihoods of people, especially in the
open water fishery subsector. The Kapuas wetland with its seasonally
inundated lakes produces about 18 000 tons of freshwater fish annually
. The middle Mahakam wetland is the core of inland
fisheries in East Kalimantan and is considered one of the most productive
freshwater fisheries in south-eastern Asia with a current
estimated annual fish production of 33 000 tons . These
fishing industry figures express the high economic value of the wetland areas
we study. The unique tropical wetland ecosystems are rich in biodiversity of
typical aquatic as well as terrestrial flora and fauna, which is why they are
listed as Ramsar sites and designated for conservation. Notwithstanding their
ecological, hydrological and economical importance, the Kapuas and Mahakam
wetlands in particular and the two river basins in general have been
increasingly threatened by a variety of factors including pollution, forest
fires, deforestation and monoculture .
Both the Kapuas and Mahakam rivers originate from the centre of Borneo on the
border between West Kalimantan (Indonesia) and Sarawak (Malaysia). The Kapuas
originates from the Kapuas Hulu mountains, runs westward through mountainous
terrain and descends into a flat plain . At this plain, from
Putussibau until the delta, the river elevation drops by just 50 m over a
length of 900 km . This results in the formation of the
Kapuas floodplain lake area in the upstream part of the river. Figure (top pictures) show conditions of the lake area during wet and
dry periods. The Kapuas lake area, which includes the Lake Sentarum National
Park, is surrounded by mountain ranges; the Upper Kapuas Mountains in the
north, the Muller Mountains in the east, the Madi Plateau in the south and
the Kelingkang mountains in the west . Despite its inland
position, most of this wetland basin lies less than 30 m above sea level
. Downstream of the wetlands, the Kapuas meets a main
tributary, the River Melawi, flows further westward through a low mountain
land, bifurcates into the Kapuas Besar and the Kapuas Kecil, and finally
continues to the Kapuas delta distributaries towards the Karimata Strait.
This strait is connected to the South China Sea, which is very busy and
important to the livelihoods of communities in south-eastern Asia. The capital of
West Kalimantan, Pontianak, which is inhabited by about 600 000 people
estimate from 2014; see, lies right on the equator
along the Kapuas Kecil.
The Mahakam flows from its source through the Pre-Tertiary rocks in
a south-easterly direction and reaches the Tertiary basin of Kutai. The river
then meets the Kedang Pahu River in the middle Mahakam region
. The Mahakam meanders eastward from there through
Quarternary alluvium in the Mahakam lake area. This area is a flat tropical
lowland region circumscribed by wetlands with seasonal flooding (Fig. , bottom left picture). Some 30 shallow lakes, which are
connected to the Mahakam through small channels, are situated in this area.
The Mahakam meets three other main tributaries downstream of the lake area
and flows south-eastward through a Tertiary mountain range before reaching
the Mahakam delta distributaries and debouches into the Makassar Strait.
Samarinda, the capital of East Kalimantan, which is inhabited by over
830 000 people estimate from 2014; see, lies along the
Mahakam just upstream of the delta region.
Photos from a wetland reconnaissance. (a) The Kapuas wetlands during the wet period showing full
inundation and (b) during the dry period showing the exposed lake bed
and the remaining wetted lake channel. (c) The Mahakam at the lake area; flood marks on trees and houses (white arrow) show the highest water
level. (d) Another scene from a drought event in the Kapuas wetlands
with forest/shrub fires in the background.
According to the Köppen climate classification, the climate of the region is
tropical rainforest (Af type), which is characterised by a long-term mean
precipitation higher than 60 mm in the driest month. The regional climate of
Kalimantan is generally influenced by the Indo-Australian monsoon driven by
the Intertropical Convergence Zone (ITCZ) and El-Niño – Southern
Oscillation (ENSO) phenomena . The central and
northern parts of Kalimantan have bimodal rainfall patterns with two peaks of
rainfall (generally from October to November and March to
April) due to the global circulation and the regional climate
. The development of El-Niño in the Pacific, indicated by
an anomalously cold sea surface temperature (SST), surrounds Indonesia.
Warm anomalies develop in the eastern Pacific and western Indian Ocean
, generally triggering drought conditions in the region.
Conversely, the development of a La Niña event indicated by SST anomalies
in contrast to those during an El-Niño event results in increased rainfall
during the dry season. However, the ENSO effect in Indonesia is not uniform
throughout the seasons. Rainfall anomalies tend to persist in the dry season
but not in the wet season .
Methodology
Field data described in this contribution were obtained during fieldwork
campaigns in Mahakam held in 2008–2009 and in the Kapuas held in
2013–2015. Details on field data used in this study are presented in Table . Point measurements of rainfall were conducted using
rain gauges and automatic weather stations. The Tropical Rainfall Measuring
Mission (TRMM) rainfall estimates were acquired from the
NASA's Goddard Earth Sciences Data and Information Services Center
Interactive Online Visualization and Analysis Infrastructure (Giovanni) at
http://giovanni.gsfc.nasa.gov/. We used the TRMM daily 3B42 and monthly 3B43
rainfall products in this study. The daily TRMM rainfall rate was used to
show the spatial rainfall variability in the study area and to be compared
with previous studies with a short period of
observation (about 2 months). The monthly TRMM rainfall rate was
presented along with the publicly available SOI index, which has monthly
values. A comprehensive description of the TRMM rainfall products, which have
been available since 1998, can be found in . Water levels
were measured using pressure transducers, while soil moisture sensors were
used to estimate the volumetric soil moisture contents. Water levels of lakes
were measured at the shore, resulting in an unmeasured water column of the
deeper region. Therefore, a depth of 1 m was added to the water levels for
water volume estimation, based on bathymetry measurements. Discharges were
estimated from measurements using horizontal acoustic Doppler current
profilers (H-ADCP) deployed in middle Mahakam at Melak, which is upstream
of the Mahakam wetland region about 300 km from the river mouth
and in the middle Kapuas at Sanggau, which is situated
about 270 km from the river mouth . The discharge data from
H-ADCP measurements were in half-hourly time step that enable us to see the
hysteretic behaviour of discharge as a result of backwater effects. To
establish water discharge through the river section, boat surveys were
carried out at the cross sections where the H-ADCP was deployed.
Description of collected field data.
Measurement stationLocationPeriod of dataVariable measuredMahakamRain-gauge at Melintang116.2563∘ E; 0.3016∘ SMay 2008–Mar 2009rainfall, air temperaturePressure transduser at Melintang116.2585∘ E; 0.2932∘ SFeb 2008–May 2009groundwater levelPressure transduser at Jempang116.1884∘ E; 0.4959∘ SMar 2008–May 2009lake levelH-ADCP discharge station at Melak115.8684∘ E; 0.2998∘ SMar 2008–Aug 2009water flow velocity, water level,local bathymetryKapuasAutomatic weather station at Leboyan112.2909∘ E; 1.0830∘ NDec 2013–Mar 2015rainfall, air temperaturePressure transduser at Leboyan112.3094∘ E; 1.0876∘ NDec 2013–Mar 2015groundwater levelPressure transduser at Sentarum112.0636∘ E; 0.8388∘ NMar 2014–Mar 2015lake levelSoil moisture sensor at Leboyan112.2909∘ E; 1.0830∘ NDec 2013–Feb 2014soil moisture contentH-ADCP discharge station at Sanggau110.5889∘ E; 0.1149∘ NOct 2013–Apr 2015water flow velocity, water level,local bathymetry
The Sanggau flow monitoring station is located downstream of the Kapuas
wetland region. Therefore, to evaluate the water surface profile and flow
from this discharge station upstream through the Kapuas wetlands region, a
one-dimensional hydraulic representation of the river was made in HEC-RAS
, an open software river analysis system developed by the US
Hydrological Engineering Centre. Two of the HEC-RAS components were used: the
steady flow surface water computations (to determine average water profiles
and levels for minimum and maximum discharges) and the unsteady flow
simulation (to simulate one-dimensional unsteady flow through a full network
of open channels). Upstream of the Kapuas and the Melawi River (the southern
tributary) a flow hydrograph was given as the boundary condition, based on
characteristics of the upstream subcatchment that drains directly into the
Kapuas River. At the downstream end of the river, a rating curve function
obtained from the stage–discharge relation at Sanggau was provided as
the boundary condition. We used a constant Manning roughness coefficient
n of 0.035, which corresponds to a normal river channel with some
weeds and stones for the entire Kapuas and Melawi reaches. A spatial
discretization of 3 km and a time step of 20 min were chosen for this
model. Spatial resolution of 3 km is considered sufficient for the modelled
river section of 553 km from Putussibau to Sanggau. Regarding time
resolution, flow velocity and cross-sectional distance show that the
resolution in time cannot exceed 25 min. Models runs showed that the
model is stable for δt< 20 min. For δt equal
to 30 min, the model was conditionally stable, and it is unstable for
δt> 1 h. The difference between model outcomes on a 20 min resolution vs. a 1 min resolution was negligible. Model evaluation
was carried out using the Nash–Sutcliffe (NS) efficiency coefficient:
NSE=1-Σt=1T[Qobs(t)-Qsim(t)]2Σt=1T[Qobs(t)-Q‾obs]2,
where Qobs(t) and Qsim(t) correspond to observed and
calculated discharge at time t, Q‾obs is the average observed
discharge, and T is the total number of time steps. The NS coefficient for
water level simulation was calculated in the same way by exchanging Q
with h.
Our HEC-RAS model was not entirely calibrated: literature values were used
for parameters which were not measured. Uncertainty in model parameters can
have an effect on the model outcomes. Therefore, effects of changes in
lateral influx, lake water storage and Manning's roughness coefficient
(n) were investigated (Table ). Water stage and discharge
at Sanggau station and lake water level data were used to validate HEC-RAS
model simulations. An increase in lateral fluxes leads to an increase in peak
flow, lake level fluctuation and river stage fluctuation. An increase in
storage vs. elevation relation decreases the lake water depths, but increases
the outflow as the lake contains more water with the same elevation. A
decrease in n, a decrease in bottom friction, leads to faster and
larger discharges; the discharge at Sanggau increases. The associated river
stages over the entire river profile are lower, as water discharges faster.
Wetland water stages are also lower when Manning's n decreases. Table also shows that an increase in NS in the discharge simulation
at Sanggau is associated with a decrease in NS of the stage simulation at
Sanggau for all scenarios. Figure shows the simulated and
measured water levels of the Kapuas lake. The Kapuas wetland was modelled as
one large reservoir. In fact, it is a complex system of seasonally connected
small lakes and peatland that may cause discrepancies in magnitude and timing
of changes in the water levels of the lake. Our model simulation reflects the
bimodality of the rainfall pattern in the study area, as shown in the
simulated discharge (Fig. ).
Effects of changing lateral influx (Ql) [m3 s-1],
lake storage/elevation (L) [m] and Manning's n
[s m-1/3] on simulated water level (h) and discharge (Q)
at Sanggau.
Simulated (dashed line) and measured (solid line) water levels
(metres above sea level) of the Kapuas lake.
HEC-RAS simulated discharges for different cross sections in the
downstream Kapuas River (a) and the upstream Kapuas River (b) of the
modelled river section.
Inundation maps were obtained from the analysis of PALSAR images available
for the period 2007–2010. Flood occurrences were mapped following the
method for flood mapping of open water and flooding under vegetation
. Crucial in this method is the onset of backscatter for
open water (upper threshold) and for inundation under vegetation cover (the
lower threshold). To determine threshold values for open water flood
occurrence mapping, radar backscatter statistics of regions covering the main
river and lakes known to be permanently inundated were taken. The mean plus
1 standard deviation was chosen as the upper threshold for inundation as
open water. For inundation under vegetation, the mean value of radar
backscatter sampled from floodplain regions known to be frequently flooded
was taken as the lower threshold. Open water inundation occurrence has an
accuracy of about 85 % while the reported accuracy of inundation occurrence
under vegetation is 78 % . From inundation area and lake
water levels, we roughly estimated the total volume of water in the lake regions. Areas of floodplain lakes are following the seasonal inundation
pattern as a result of variable rainfall rates. The period of Mahakam water
level measurements coincided with part of the PALSAR data acquisition dates.
Therefore, we were able to derive a lake depth (h) – area
(A) relationship that was used to estimate the lakes' water levels
beyond the period of our measurements (Fig. ). For the Kapuas, our
water level measurement did not coincide with the PALSAR observation period.
With an assumption of uniform distribution of depths, we develop a
depth–rainfall relationship. Correlation analysis reveals that the depth of
the lakes is well correlated with the two-month moving average of areal
rainfall (P2m). We obtained a linear depth–rainfall relation
that was applied to approximate water levels of the Kapuas lakes, reading
h=0.021⋅P2m-2.4.
Relationship between measured depth of the middle Mahakam lakes and
area of open water inundation from PALSAR images.
For a drought study in the two basins, we simulated the transient water
balance using rainfall estimates from TRMM and potential
evapotranspiration from the Climate Research Unit (CRU) as input data to derive groundwater
recharge for the period from 1998 to 2014. The spatial resolution of the gridded potential evapotranspiration
obtained from CRU is 0.5∘. Our measured data were used to validate the
TRMM product. Therefore, the difference in the period of field campaigns in
the Kapuas and Mahakam basins has little effect on the overall results.
Different land uses were used simulate the actual evapotranspiration in the wetland
area and were identified from the Borneo land-use and land cover map
. Drought events are derived from time series of groundwater
recharge using the threshold level approach. This approach defines drought as
a period in which the recharge is below a certain threshold value
. As in previous studies
e.g., we applied the 80 percentile from the
duration curve as a threshold. We applied monthly variable thresholds that
were identical for both river basins, which were derived from the Mahakam
basin, being the driest. Drought duration is considered as the period from the
start to the end of an uninterrupted drought.
Hydrological characterisationClimate and climate variability
Rainfall rates are generally higher in the Kapuas than in the Mahakam. The
spatial distribution of rainfall as TRMM daily rainfall rate (mm) averaged
over January 1998–December 2014 is shown in Fig. . The lowest
average rainfall rate of about 5 mm day-1 was found in the Mahakam wetland
region, while the highest rainfall rate of about 11 mm day-1 was found in the
upper Kapuas region. As the spatial resolution of the TRMM data is very
rough, small-scale variation cannot be observed. Spatial variability of
rainfall is obvious in a subcatchment-scale daily field observation.
and reported that most high intensity
showers in Bika, a subcatchment in the upper Kapuas region, can differ quite
significantly over a short distance. Due to this large variation, rain gauges
will have a small representative area. As TRMM measures the total rainfall
over an area of 0.25∘× 0.25∘, the measured amounts are expected
to represent the average rainfall over that area. The 17-year record
of TRMM rainfall estimates confirms the rainfall pattern over the Kapuas and
the Mahakam catchments to be bimodal with the average annual rainfall of
approximately 3630 and 3000 mm, respectively. Zoomed into the lowland
areas, the Kapuas wetlands receives an average annual rainfall of 3700 mm,
while the Mahakam wetlands receives an average annual rainfall of 2690 mm.
The peak of rainfall usually occurs in December–January, with the second peak
in March–April and the driest month is around June–August. This pattern is
always shifting backwards and forwards due to the ENSO influence.
Spatial distribution of rainfall as TRMM daily rainfall rate (mm)
averaged over January 1998–December 2014. Bold black lines indicate
catchment boundaries and thin lines indicate approximate coast lines.
The influence of ENSO in the region results in significant annual variation
of rainfall. Rainfall is generally low in Indonesia during the warm period of
ENSO and is indicated by a negative Southern Oscillation Index (SOI). The
opposite trend occurs when the SOI is positive. Figure shows the
relationship between SOI and monthly rainfall depth in the Kapuas and Mahakam
wetland regions (red boxes in Fig. 1) with correlation coefficients
(r) of 0.212 and 0.358, respectively. This correlation, however, is
not uniform throughout the season. For the Kapuas wetlands the highest
r value of 0.725 is found in August, while for the Mahakam wetlands
the highest r value of 0.732 is found in October. These r
coefficient values show that the Mahakam wetland is more affected by the
ENSO, which is also confirmed by its rainfall rate and drought duration
described in the respective subsection. From the figure, an increasing trend
in the peak of rainfall in the two catchments is also observed, while the
trends of the mean and minimum rainfall are hardly detected from the
available TRMM rainfall estimates.
Monthly rainfall of the Kapuas (dashed line) and the Mahakam
(continuous line) lowlands from January 1998 to December 2015 plotted
along with the Southern Oscillation Index (bars). Box plots show the
variability of monthly rainfall in the two lowland regions.
Groundwater and soil moisture respond relatively quickly to rainfall events.
Figure (top panel) shows the increase/decrease of water level and
soil moisture as the results of rainfall/no rainfall events at one of our
monitoring stations in the upper Kapuas area. A similar result was found in
the upper Kapuas peat-dominated Bika subcatchment as reported by
. This subcatchment is a fast-responding system characterised
by shallow groundwater levels and rapid groundwater fluctuations; the
increase in groundwater levels is clearly visible after precipitation events.
Soil was saturated during the first period of our measurement in
December–January, which is the peak period of rainfall (Fig. ),
followed by reasonably dry conditions in February that led to the drying-out of
the lakes in the Kapuas wetlands in March 2014 (Fig. , bottom
right). Groundwater and soil moisture are well correlated. Although the
location of measurements are about 5 km apart, soil moisture was measured in
a mineral soil while groundwater level was measured in a peat soil. No soil
moisture observation was carried out in the Mahakam. Figure
(bottom panel) shows hourly rainfall and groundwater level measured at a peat
forest site next to Lake Melintang. During a normal period, groundwater level
response to rainfall events is rather lenient due to the presence of the lake
nearby. The response is slightly faster during dry conditions as the lake's
water level is also low. As the Melintang peat forest is part of the Mahakam
lowlands, groundwater level is not only a function of local rainfall but it
is also influenced by upstream conditions. River bank overtopping upstream of
the lake region causes a sudden increase in water level observed during the
peak of the wet period.
(a) Hourly groundwater level and surface level (5 cm deep) and 10 cm-deep soil moisture response as results of rainfall (and no rainfall) events
in the Kapuas. The scatter plot shows the relation between soil moisture and
groundwater level. Note that while rainfall and soil moisture were measured
at the same location (mineral soil), groundwater level was measured about 5 km apart (peat soil). (b) Hourly rainfall and groundwater level of the
Mahakam peat forest near Lake Melintang.
Discharge series from flow monitoring stations of the Kapuas at
Sanggau (a) and the Mahakam at Melak (b) with scatter plots
showing stage–discharge relations. Water stages are with respect to the
pressure gauge positions.
Streamflow and flood hydraulics
Consistent with the local humid climate, the Kapuas and the Mahakam are
rainfall driven rivers. Figure shows discharge series of the Kapuas
at Sanggau and the Mahakam at Melak flow monitoring stations. Hydrograph
behaviour of the Kapuas at Sanggau and the Mahakam at Melak generally
corresponds to monthly average precipitation behaviour with a small delay in
time. The Kapuas mean discharge at Sanggau is about 5000 m3 s-1, while
that of the Mahakam at Melak is about 2000 m3 s-1. During low flows in
July–August, both discharge time series show subdaily fluctuations, which
correspond to tidal signals. Tidal energy can reach that far upstream because
the terrain of the middle and lower regions of the Kapuas and that of the
Mahakam are relatively flat.
The Kapuas flow monitoring station at Sanggau is located downstream of the
wetlands area and lies in relatively steeper terrain that marks the
transition between the middle and the lower Kapuas regions. This results in
an almost unambiguous stage–discharge relation due to the absence of
backwater effects. The opposite condition was observed in the discharge
series from the Mahakam discharge station at Melak, which was located upstream
of the wetlands area in a relatively mild topography. Variable backwater
effects from floodplain impacts, lakes and tributaries and effects of
river–tide interaction are apparent in the ambiguous stage–discharge
relation. Water level fluctuations of about 10 m were recorded during our
observation at Melak station. Discharge at this location is highly
hysteretic, and is extensively discussed in . From water
level records, they show that wetlands, including some 30 lakes in the
middle Mahakam area, play a role in water level peak attenuation via a lake
filling and emptying mechanism.
Water levels also fluctuated with a range of about 10 m at our discharge
monitoring station of the Kapuas at Sanggau. No significant hysteresis occurs
in the stage–discharge relation at this flow monitoring station. As it is the
case of the middle Mahakam region, backwater effects are likely to occur
upstream of the Kapuas wetlands area, which was investigated using the
HEC-RAS river analysis system . Figure (left) shows
the falling limb of the hydrograph from the Kapuas HEC-RAS model simulation.
When the water levels drop, a smooth surface water profile develops. In the
upper half of the Kapuas a water hump is formed where the maximum water depth
of 13.1 m occurs about 280 km upstream of Sanggau. The rising limb of the
hydrograph is displayed in Fig. (right). At about 350 km upstream
of Sanggau, the Tawang channel meets the Kapuas, connecting the wetland to the
river. Directly upstream of this wetland a backwater curve arises during the
rising limb of the hydrograph. observed hysteresis loops in
the stage–discharge relation of the Bika River, a tributary debouching to the
Kapuas upstream of the wetland area. She found that, due to backwater effects
from the main Kapuas as well as from ponding of the lower Bika region, low
water levels can imply both a low and a high discharge, which also holds for
high water levels.
Longitudinal surface water profile over the Kapuas river reach from
Sanggau to Putussibau; z is bed elevation. (a) Water stages are
plotted for 30 January and 1 August, displaying the falling limbs of the
hydrograph. (b) The rising limbs, when the water levels are
increasing, are shown for 3 December 2014 and 6 January 2015.
Inundation dynamics
Both catchments are characterised by vast wetland areas. Figure
shows the inundation occurrence in the upper Kapuas and Mahakam lake area
derived from 20 PALSAR images available in the period from 2007 to 2010.
Estimates of the total volumes of the lakes in the Kapuas and the Mahakam
lake area are shown in Fig. . As these estimates were derived
without incorporating the lake's bathymetry, which is generally flat as shown
on Fig. (bottom right), the value presented herein should be
merely considered a rough estimate of storage capacity. The highest
estimated total volume of water in the Kapuas lakes is about 3 billion m3
during the PALSAR data acquisition on 8 April 2009, while that of the Mahakam
lakes is about 6.5 billion m3 during the PALSAR data acquisition on
12 May 2010. Considering the extent of flooding under vegetation cover
(Fig. ), the maximum total volume of water stored in these
wetlands could be twice as much as the abovementioned values. This partly
explains why such a large discharge variation occurred at a given water stage
as shown in the scatter plot of Fig. (bottom panel) at the discharge
station upstream of the wetland region.
Inundation occurrence in the upper Kapuas (a) and
Mahakam (b) lake area derived from 20 PALSAR images of 2007–2010
as open water (light green – dark blue) and flooding under vegetation (light
– dark brown). Vertical legend on the right: Lake flood count in open
water; vegetated flood count in flooding under vegetation.
Estimates of total volume of lakes in the Kapuas (a) and
the Mahakam (b) lowlands derived from flooded pixel areas in PALSAR
images. Note that stream network was not removed during the flood count
assessment, which renders the area of inundation somewhat
overestimated.
Drought occurrence and fire vulnerability
Groundwater tables in the lowlands of Borneo are typically shallow; capillary
rise from groundwater normally feeds soil water in the topsoil to (partially)
compensate for the high evapotranspiration losses. Groundwater recharge
reflects soil hydrological processes well, including capillary rise and
evapotranspiration. During the dry season, low recharge is common and it can
even become negative, meaning topsoil moisture is too low to compensate for
the evapotranspiration flux and capillary rise occurs, which is not always
enough to keep the evapotranspiration at the potential rate. The two lowlands
under study show a different hydroclimatic regime. In the Kapuas, a high
median monthly groundwater recharge (161 mm month-1) occurs, which is
twice as high that of Mahakam lowland (Fig. , left panel). The
Kapuas lowlands have few periods with low groundwater recharge during the dry
season. Prolonged drought is rarely found in the Kapuas (only few events last
up to 3 months (Fig. , right panel). In contrast, the Mahakam
wetland area regularly exhibits low groundwater recharges, which may lead to
prolonged drought events that can last up to 13 months. It appears that the
Mahakam lowland is more vulnerable to hydrological drought, leading to higher
fire risk.
Hydroclimatological regimes and drought in the Kapuas and Mahakam
lowlands: (a) violin and box plots showing the distribution of
monthly groundwater recharge over the period of the TRMM data set
(1998–2014); (b) drought in groundwater recharge showing different
durations.
Discussion
Tropical rivers exhibit a fairly direct response to rainfall input with
strong seasonality as a dominant feature . This is also the
case in the Kapuas catchment, which generally reacts very quickly and behaves
as a straightforward system. In a lowland region, the presence of wetlands
locally averts the river system from this general principle. Our HEC-RAS
model simulations shows that lakes and adjacent wetlands have a delaying
effect on river discharges and diminish water levels and flow fluctuations.
The average lake level fluctuation of 7.3 m for the entire wetland area is
in the same range as previously documented ranges of 8 and 11 m
. During the rising limb of the hydrograph, as
could be seen in Fig. , a backwater curve arises just upstream of
the Tawang channel, which connects the lake area to the Kapuas. Next to
discharge, backwater influences river flow velocities, which is an important
factor in river meander growth. From an analysis using a series of Landsat
images, found a clear transition between a more active
channel migration of the Kapuas upstream of the lake area and a less active
migration downstream. The border between these two regimes was found 10 km
upstream of the Tawang channel. At this border, a clear transition between
river flow velocities is observed. Erosion and transport of the eroded
material can take place during bankfull discharge, while during low flows,
when flow velocities fall below the settling velocity of sediment particles,
sediments can be deposited. The distinct changes in flow velocities and the
accelerating and decelerating behaviour could also explain why the
Kapuas is very actively meandering in its upper reaches. During the rising
limb of the hydrograph no distinct effect of the wetland can be seen at
the Sanggau discharge station. The peak flows occur at the same moment in time
and the discharge rises with the same speed. During the falling limb, effects
of the wetland can be seen. The falling limb occurs more gradually and the
minimum flow changes due to the supply of water from the lake.
Tree cover (green) forest loss (red) forest gain (blue) with loss
and gain (purple) between 2000–2012 in the Kapuas and the Mahakam. Data
source: Global Forest Change .
Next to the effect on the river discharges, the wetland also gave rise to a
backwater curve, rising upstream of the Tawang channel. This backwater curve
affects the flow velocities and can influence the meandering behaviour of the
Kapuas river. Processes of lake filling and emptying contribute to
accelerating and retarding the river flow velocity. Due to the backwater
effect from the lake, when lake level is high, the stage upstream of the
lake area is relatively high for a relatively low discharge. This effect is
reduced when the lake level dropped and the discharge increased while the
water level keeps decreasing, pending sufficiently high discharge that
renders water level to follow the discharge trend. During the lake-filling
process, the contrasting mechanism took place. These mechanisms play a key
role in regulating water level and discharge downstream .
Vast areas of lowland wetlands in the middle Kapuas as well as in the middle
Mahakam region form a massive water storage that eliminates sudden and large
river discharge changes downstream. The moderation of discharge and water
level fluctuations in the lower reaches of the river by the filling and
emptying mechanisms of the lake, as shown by water level records as well as river–tide
interactions, results in a relatively mild discharge variation in the
downstream region .
The accurate, continuous discharge estimates from the H-ADCP allow for a
discussion on the difference between runoff and discharge in the backwater
affected region, in our case upstream of the wetland/lake regions. ADCP flow
measurements are costly and time consuming. Nevertheless, there is no simple
alternative to monitoring discharge dynamics in rivers with backwater. Too
often, water agencies rely on rating curves that fail to capture the
hysteresis effects. Hydrologists may not always be sufficiently critical
about the accuracy of discharge estimates from rating curves. The data series
presented in this contribution is relatively short, but we would like to
point to the fact that regarding discharge data, long data series available
elsewhere are always based on rating curve information, whereas our
observations are made independent for discharge (using an H-ADCP) and water
level. The rainfall data period is extended by the availability of TRMM
products and potential evapotranspiration from CRU. Here we use data from
1998 to 2015. We concur that the analysis presented can be improved in
the future, when longer data series are available, but the present data
series are long enough to support the conclusions drawn. Further, the
influence of ENSO on the Kapuas and Mahakam is not equally significant. This
knowledge could be used to develop different consequences and policies.
The present study makes a systematic inventory of the existing studies of
inland tropical lowlands, which have received relatively little attention,
including gathering continuous flow data to accurately estimate river
discharge, one of the key hydrological variables. Concerning discharge in the
Kapuas, we are the first to record water discharge on the Kapuas River based
on H-ADCP flow monitoring. Once a representative length of flow measurements
is obtained, a model can be constructed to relate discharge data with other
simpler to measure parameters such as stage, known as the rating curve
technique. However, rating curves are subject to uncertainties concerning
interpolation and extrapolation errors and seasonal plants variations
and may fail to capture discharge dynamics in lowland
river reaches affected by backwater effects due to the inapplicability of the
kinematic wave equation to handle the surface gradient term in the
non-inertial wave equation . A novel technique, such as
neural networks, can be applied to model discharge in this hydrologically
complex region. demonstrate that discharge in a tide-dominated
river reach can be well modelled even without at-site stage records
given that a representative discharge time series is available for training and
validating the model. This implies that an H-ADCP can be installed
temporarily in one location, e.g. 1 year of flow measurements, to obtain
discharge estimates that can later on be used to train and validate the
model. Once the model is established, it can be used for discharge prediction
whilst the H-ADCP can be installed in another location, optimising investment
in monitoring instrumentation, even though a permanent H-ADCP station would
be ideal. Similarly to that of the traditional rating curve technique, however,
occasionally updating it with new data is required to adjust the neural network
model to account for changes in the river system.
As radar is unrestricted by cloud cover, radar remote sensing technology
presents an alternative to detecting changes in inundation states of wetlands in
the humid tropics. From its dark signature, a fully inundated region can be
easily recognised on radar images. From combining images produced by taking
the minimum, mean and maximum backscatter values of radar images, a clear
signature of flooding under vegetation can be obtained and from such images
floodplain delineation can be performed . The results
presented herein provide a basis for a better understanding of the role of
the Kapuas and the Mahakam inland wetlands, in buffering the discharge
towards the downstream coastal regions. Radar-based floodplain observations
may be used in future work to calibrate hydrodynamic models, simulating the
filling and emptying processes of the lake area. This work has also
contributed to the understanding of tropical lowlands. We find two important
features, namely (1) widespread flooding and strong surface water-groundwater
linkage and (2) strong backwater effects that form a dramatic multiple
discharge hysteresis as shown in the Q-h plot. We reveal the impacts of
backwater effects, which proves the kinematic wave approach adopted in many
hydrological studies unsuitable. These findings imply that many hydrological
models will fail to describe the hydrology correctly if they do not account
for the presence of standing water or high groundwater tables, and that many
simple routing routines will fail to describe the discharge dynamics.
Climate extremes, both wet and dry, can have devastating impacts in tropical
regions. Such impacts are well documented for the Amazon basin, but have
received less attention for tropical rainforests in Asia, in particular those
in Kalimantan. An exception forms the large-scale drought-induced wildfires
that have occurred over the past decades and which are associated with the
El Niño Southern Oscillation (ENSO) phase . Before the
1980s, it was believed that tropical rainforests were resilient to drought.
During the 1982/1983 El Niño, it became clear that prolonged drought
could cause large-scale damage to rainforests and peat soils due to
widespread wildfires . Wildfires spread more easily due
to an accumulation of leaf litter , which becomes extremely dry
during drought conditions. This factor, along with those of anthropogenic
origin; e.g. the conversion of forests to other land uses is the main
contributor to loss of rainforest in Kalimantan's lowlands (Fig. ).
72–85 % of the middle Mahakam peatlands were burned between 1997 and 2000
. Fires mostly occurred within this period during the
1997/1998 extremely dry El Niño-induced conditions. Another study by
reported that more than 2 million Ha of forest were burned
in lowland Mahakam. At present, large-scale wildfires occur almost every year
during the dry season, raising the questions of whether climate variability and
circulation changes can amplify anthropogenic land use changes, and how this
will impact the hydrological functioning of the study area.
Conclusions
Alluvial floodplains of lowland rivers have become the centre of past and
present human settlements due to their fertile soil which supports food
production and easy access for transportation. With the ever-increasing water
demands and threat from water-related disasters, hydrological prediction, on
the one hand, is crucial to support a resilient society inhabiting the area.
On the other hand, hydrological predictions in lowland rivers, especially in
tropical regions, are difficult because of the scarcity of
hydrometeorological data and flow regime complexity resulting from lake–river interactions, backwater and tidal effects, etc. This study
offers a comprehensive view of the hydrological characteristics of two
poorly gauged tropical inland lowland rivers: the Kapuas and the Mahakam in
Kalimantan, Indonesia. Based on TRMM data, it was shown that both river
basins experience strong seasonal fluctuations in precipitation. The Kapuas
basin receives considerably more precipitation than the Mahakam. The Kapuas
wetland area receives an average annual rainfall of 3700 mm, while the
Mahakam wetland area receives an average annual rainfall of 2690 mm. In
response to the strong seasonal variations in water input, both basins showed
strong seasonal variability in inundation extent as derived from PALSAR
images. The Kapuas and Mahakam lake regions are vast reservoirs of water
that can store as much as 3 billion m3 and 6.5 billion m3 of water,
respectively, which can be doubled when the area of flooding under vegetation
cover is considered. We found the seasonally varying storage in both wetlands
to exhibit an important role in regulating the discharge regime of the
downstream parts of the rivers. Directly downstream of the wetland, the river
discharges are most clearly affected. Based on discharge observations made by
H-ADCP during dedicated field campaigns over multiple seasons, we found
strong dynamics in both discharge and water levels. The seasonal amplitude in
water levels was found to be around 10 m for both basins. Strong backwater
effects in the Mahakam prohibited the use of a traditional rating curve for
discharge estimation, calling into question the quality of historical
discharge records in many lowland basins. Contrary to the moist nature of
wetlands, the two lowlands are vulnerable to drought, especially during the
warm period of ENSO, yet prolonged drought rarely occurs in the Kapuas under
current climate conditions in line with observations of shallow groundwater
tables and a strong coupling between groundwater and soil moisture
observations. We found that the Mahakam lowland area is more vulnerable to
hydrological drought, leading to the occurrence of fire. It is expected that the
hydrological characterisations of the Kapuas and the Mahakam facilitates
a better prediction of fire-prone conditions in these regions.
Our observations and analysis reveal a region dominated by highly dynamic
hydrological processes, such as seasonal inundation over vast areas
(>1000 km2), strong backwater effects, shallow groundwater tables and a
high seasonal amplitude of river stages (∼10 m). Most of these processes
are currently not or only crudely represented in hydrological models. We
believe our study can contribute to the use of data from poorly gauged
catchments to improve the next generation of models in areas that were
traditionally a “blind spot” for model evaluation, but where strong changes
in land use and climate provide an urgent need for better models.
Data sets are provided in the Supplement.
The Supplement related to this article is available online at doi:10.5194/hess-21-2579-2017-supplement.
The authors declare that they have no conflict of
interest.
Acknowledgements
This research has been funded by The Royal Netherlands Academy of Arts and
Sciences (KNAW) through the Scientific Programme Indonesia–Netherlands
SPIN3-JRP-29 and by the Netherlands Organization for Scientific Research (NWO
grant number WT76-268). ALOS PALSAR data have been provided by JAXA EORC
within the framework of the ALOS Kyoto and Carbon Initiative. TRMM data
analysis and visualisation used in this paper were produced with the Giovanni
online data system and developed and maintained by the NASA GES DISC. We thank
the reviewers and the editor for their comments and suggestions, which helped
to improve the manuscript.
Edited by: S. Uhlenbrook
Reviewed by: K. Hassaballah and M. C. Westhoff
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