Hydro-climatic change in irrigated world regions
Hydro-climatic changes in irrigated world regions
Shilpa Muliyil Asokan
Department of Physical Geography and Quaternary Geology
Stockholm University
Stockholm 2013
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Shilpa Muliyil Asokan
© 2013 Shilpa Muliyil Asokan
ISSN: 1653-7211
ISBN: 978-91-7447-641-5
Paper I © 2008 John Wiley & Sons, Ltd.
Paper II © 2010 American Geophysical Union
Paper III© 2010 American Geophysical Union
Paper IV © 2013 Springer Science + Business Media Dordrecht
Paper V © 2012 Shilpa Muliyil Asokan
Cover: Top panel: Irrigation water diversion in Mahanadi River Basin (Photo: Orissa Economy); Bottom panel:
The effect of irrigation water diversion in Aral Sea Drainage Basin - the desiccated Aral Sea (Photo: Olov Johansson)
Layout: Shilpa Muliyil Asokan, Susanne Ingvander (except Paper I, II, III and V)
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Hydro-climatic change in irrigated world regions
Abstract
Understanding of hydro-climatic changes in the world’s river basins is required, for instance towards
ensuring future food security. Different regional basins experience different levels of hydro-climatic
change and different water resource impacts of climate change depending on the endorheic (discharging
into terminal inland water) or exorheic (discharging into the ocean) nature of a hydrological basin, along
with the climatic conditions and human land-use and water-use practices (for instance for agriculture and
its irrigation) within the basin. This thesis has analyzed long-term hydro-climatic changes in two main
irrigated regions of the world: the Mahanadi River Basin (MRB) in India and the Aral region in Central
Asia, including the terminal Aral Sea and the hydrological basin draining into it. The thesis applies a
basin-wise, data-driven water balance-constrained approach to understanding and quantifying the
hydro-climatic changes, and to distinguish their main drivers in the past century and for future scenario
projections. Results point at human water-use and water re-distribution for irrigation within a basin as
a major driver of water balance and water resource changes, which also affect surface temperature in the
region.
Cross-regional comparison for the two different study basins clarifies the importance of different
perspectives on hydro-climatic change. One perspective may for instance focus on the climatically
important changes of water, vapor and latent heat fluxes at the land surface, while another may focus on
changes to water resource availability in the landscape, with different change drivers then being dominant
from these different perspectives on continental water change. Thesis results show that irrigationdriven changes in evapotranspiration and latent heat fluxes and associated temperature changes at the
land surface may be greater in regions with small relative irrigation impacts on water availability in the
landscape (here represented by MRB) than in regions with severe such impacts (here represented by the
Aral region). This implies that one cannot from the knowledge about only one aspect of hydro-climatic
change (such as temperature and precipitation changes at the land surface as given from climate modeling)
simply extrapolate the impact importance of those changes for other types of water changes (such as on
availability of water resources) in a region.
Climate model projections from General Circulation Models (GCMs) used in the fourth assessment
report (AR4) of the Intergovernmental Panel on Climate Change (IPCC) were also studied in the thesis
regarding their performance against hydrologically important, basin-scale observational temperature and
precipitation datasets. Results show lack of consistency in individual GCM performance with regard to
temperature and to precipitation, implying difficulties to identify well-performing GCMs with regard
to both of these variables in a region. For the example case of the Aral region, the thesis shows that
consideration of the ensemble mean of different GCM outputs may instead provide robust projection of
future hydro-climate changes in a regional hydrological basin.
Keywords: Climate change, hydro-climatic change, evapotranspiration, irrigation, water demand,
water balance, land-use, water-use, hydrological catchment, Aral Sea, India, Mahanadi River Basin
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Shilpa Muliyil Asokan
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Hydro-climatic change in irrigated world regions
Svensk sammanfattning
Förståelse av förändringar i hydroklimatet inom olika avrinningsområden i världen krävs, till exempel
för att säkra livsmedelsförsörjningen i framtiden. Beroende på avrinningsområdets karaktär, som om det
är endoreiskt (dränerar till inlandsvatten) eller exoreiskt (dränerar till havet), samt på klimatförhållandena
och den mänskliga användningen av mark och vatten (t.ex. för jordbruk och bevattning) inom området,
påverkas hydroklimatet och vattenresurserna olika av motsvarande klimatförändring i olika regionala
områden. Denna avhandling har analyserat långsiktiga förändringar i hydroklimatet inom två olika
bevattnade regioner i världen: Mahanadi-flodens avrinningsområde (MRB) i Indien och Aral-regionen
i Centralasien, som omfattar Aralsjön och hela det endoreiska avrinningsområde som dräneras in till
den. Avhandlingen tillämpar en datadriven vattenbalansbaserad metod på avrinningsområdesskalan
för att förstå och kvantifiera förändringarna i hydroklimat, samt identifiera och särskilja de viktigaste
drivkrafterna för dessa förändringar under det senaste århundradet och för framtida modellprojektioner.
Resultaten pekar på den mänskliga användningen och omfördelningen av vatten för bevattningsändamål
som en viktig drivkraft för förändringar i vattenbalans och vattenresurstillgång, vilka i sin tur också
påverkar temperaturen i regionen.
Jämförelse av förändringarna i hydroklimat mellan de två studerade avrinningsområdena visar
betydelsen av olika perspektiv på dessa förändringar. Ett perspektiv kan exempelvis fokusera på
förändringar i flödena av vatten, vattenånga och latent värme vid markytan, som är viktiga för området
klimat, medan ett annat perspektiv fokuserar på förändringar i vattentillgång i landskapet. Olika
drivkrafter till förändring blir då viktiga ur dessa olika perspektiv på det kontinentala vattnet. Resultaten
i avhandlingen visar att bevattningsdrivna förändringar i evapotranspiration och latent värmeflöde, samt
relaterade temperaturförändringar vid markytan kan vara större i regioner där bevattningens effekt på
vattentillgången i landskapet är relativt liten (som i MRB) än i regioner med stor bevattningspåverkan
på vattentillgången (som i Aral-regionen). Detta innebär att man inte kan från kunskap om endast en
vattenförändringsaspekt (till exempel förändringar i nederbörd och temperatur vid markytan, givna från
atmosfärisk klimatmodellering) enkelt dra slutsatser om effekter på andra vattenaspekter (till exempel på
vattentillgången i landskapet) inom en region.
Avhandlingen jämför också projektioner av globala klimatmodeller (GCM:er) i den internationella
klimatpanelens (IPCC) fjärde utvärderingsrapport (AR4) med hydrologiskt viktiga observationsdata
för temperatur och nederbörd i de studerade avrinningsområdena. Resultaten visar inkonsekventa
jämförelseresultat för temperatur och nederbörd från enskilda GCM:er, som innebär att det är svårt att
hitta en enskild GCM som ger bra resultat i relation till data för båda dessa variabler i en region. För Aralregionen visar avhandlingen att medelvärdesbildade resultat från många olika GCM:er kan i stället ge mer
rättvisande projektioner av förändringar av hydroklimat inom regionala avrinningsområden.
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Shilpa Muliyil Asokan
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Hydro-climatic change in irrigated world regions
Hydro-climatic change in irrigated world regions
Shilpa Muliyil Asokan
Department of Physical Geography and Quaternary Geology, Stockholm University, Sweden
LIST OF APPENDED PAPERS
This doctoral thesis consists of a summary and six papers. The papers are referred to as Paper I-VI in the
summary text.
Paper I
Asokan, S. M. and Dutta, D, 2008, Analysis of water resources in the Mahanadi River Basin, India under
projected climate conditions, Hydrological Processes, 22: 3589-3603. doi: 10.1002/hyp.6962
Paper II
Asokan, S. M., Jarsjö, J. and Destouni, G, 2010, Vapor flux by evapotranspiration: effects of changes in
climate, land-use and water-use, Journal of Geophysical Research – Atmospheres, 115, D24102. doi:
10.1029/2010JD014417
Paper III
Destouni, G., Asokan, S. M. and Jarsjö, J, 2010, Inland hydro-climatic interaction: Effects of human water
use on regional climate, Geophysical Research Letters, 37, L18402. doi: 10.1029/2010GL044153
Paper IV
Asokan, S. M. and Destouni, G, Irrigation effects on hydro-climatic change: Basin-wise water balanceconstrained quantification and cross-regional comparison, manuscript accepted for publication in the
Surveys in Geophysics. doi: 10.1007/s10712-013-9223-5
Paper V
Jarsjö, J., Asokan, S. M., Prieto, C., Bring, A. and Destouni, G, 2012, Hydrological responses to climate
change conditioned by historic alterations of land-use and water-use, Hydrology and Earth System
Sciences, 16, 1335 – 1347. doi: 10.5194/hess-16-1335-2012
Paper VI: Appendix to Paper V
Asokan, S. M. and Destouni, G, Climate model performance versus basin-scale hydro-climatic data.
CO-AUTHORSHIP
The co-authorship of the papers reflects the collaborative nature of the underlying research. For Papers
I, II, IV and VI, I was the main responsible for writing the papers and for most of the computations and
analysis, with all co-authors collaborating on and contributing to study design, analysis and some computations. For Papers III and V, I did many of the included computations, and participated in the design and
analysis of the papers.
LIST OF RELATED PAPERS NOT APPENDED IN THE THESIS
Järsjo, J., Asokan, S. M., Shibuo, Y. and Destouni, G, 2008, Water Scarcity in the Aral Sea Drainage Basin:
Contributions of Agricultural Irrigation and a Changing Climate, NATO Science for Peace and Security
Series C: Environmental Security. Dordrecht: Springer, Pages: 99-108.
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Shilpa Muliyil Asokan
ABBREVIATIONS AND SYMBOLS
AR4
AS
ASDB
CAWATERinfo
CRU TS
DEM
DHM
DS
E
Ep
ET
F
FAO
GCM
GDP
IISDHM
IPCC
km2
km3 yr-1
MCM
mm season-1
mm yr-1
MODIS
MRB
msl
P
R
RCM
RGI
SRTM
T
TAR
UNEP
WHO
W m-2
°C
ΔET
ΔP
ΔR
ΔT
ΔTcl
ΔTDS
ΔTDS-irr
ΔTirr
ΔTirr-gs
ΔTirr-ngs
ΔTshr
ΔTWS
ΔTWS-irr
8
Fourth Assessment Report
Aral Sea
Aral Sea Drainage Basin
Central Asia Water Information database
Climate Research Unit time-series
Digital Elevation Model
Distributed Hydrologic Model
Water storage change
Evaporation
Potential evapotranspiration
Evapotranspiration
Latent heat flux
Food and Agriculture Organization
General Circulation Model
Gross Domestic Product
Institute of Industrial Science Distributed Hydrological Model
Intergovernmental Panel on Climate Change
Square kilometer
Cubic km per year
Million cubic meter
Millimeter per season
Millimeter per year
Moderate Resolution Imaging Spectrometer
Mahanadi River Basin
Mean Sea Level
Precipitation
Runoff
Regional Climate Model
Registrar General Method of India
Shuttle Radar Topography Mission
Temperature
Third Assessment Report
United Nations Environment Programme
World Health Organization
Watts per squared meter
Degrees Celsius
Changes in evapotranspiration
Changes in precipitation
Changes in runoff
Changes in temperature
Temperature change representing the regional manifestation of global climate change
Temperature change in the dry season
Temperature change component due to irrigation in the dry season
Annual average change in temperature due to irrigation
Average change in temperature due to irrigation in the growing season
Average change in temperature due to irrigation in the non-growing season
Temperature change component of Aral Sea shrinkage
Temperature change in the wet season
Temperature change component due to irrigation in the wet season
Hydro-climatic change in irrigated world regions
1 INTRODUCTION
Regional land use changes affect the Earth’s hydrological cycle, as the land surface is an interface to the atmosphere that interacts with climate in regulating the
partitioning of precipitation on land into evapotranspiration (ET) and runoff (R) (Gordon et al., 2005;
Douglas et al., 2006; Donohue et al., 2007; Shibuo
et al., 2007; Destouni et al., 2013). Human activities
that have affected vegetation and changed land- and
water-uses, for instance by irrigation, have therefore
considerably impacted the water cycle (Foley et al.,
2005; Shibuo et al., 2007; Piao et al., 2007; Weiskel et
al., 2007; Wisser et al., 2010; Destouni et al., 2013).
Hydro-climatic impacts of land-use and water-use
changes have been quantified as increases or decrease
of ET. For instance, deforestation may decrease ET
and increase R, while opposite impacts may result
from new forest establishment on previously sparsely vegetated land (Vanlill et al., 1980; Gordon et al.,
2005; Loarie et al., 2011). Furthermore, conversion of
natural unplowed land to cultivated land may often
increase ET (Loarie et al., 2011; Destouni et al., 2013),
but such conversions may under some conditions also
decrease it (Schilling et al., 2008). Change from agriculture to forest may further initially decrease ET
(Qiu et al., 2011) and later increase it (Donohue et al.,
2007). Regarding irrigation of agricultural areas, human re-distribution of water for irrigation, in addition to the actual land irrigation itself, (Shibuo et al.,
2007; Lobell et al., 2009; Lee et al., 2011; Törnqvist
and Jarsjö, 2012) has been estimated to increase net
water fluxes from the land surface to the atmosphere
by about 2000 km3 per year (Foley et al., 2005; Gordon et al., 2005), constituting a considerable part of
the total human freshwater withdrawals and losses
through total ET from land (Destouni et al., 2013).
Human modifications through non-irrigated agriculture and hydropower (Destouni et al., 2013), and
deforestation (Gordon et al., 2005) have also been
shown to increase ET, possibly each of them by as
much as the ET increase by irrigation.
The role of irrigated areas in modifying regional
climate through enhanced ET has been investigated
by several researchers. The first investigations along
these lines considered relative ET flux as a constant
across the global irrigated areas (for instance, the flux
was considered as 40% of the total irrigation water use
by Boucher et al., 2004). Later on, researchers modeled the ET flux using land surface models based on
the area equipped for irrigation (Sacks et al., 2009),
however the modeled water quantity used in the irrigated fields was then mostly considered unlimited.
Also, irrigation water was applied to entire grid cells
even if only a part of the cell was irrigated. These simplifications led to overestimation of vapor and associated latent heat flux to the atmosphere. A more recent
study by Lobell et al. (2009) on the irrigation-induced
climate change over eight major irrigated regions of
the world described a more developed climate modeling approach by taking into account soil saturation thresholds. Nevertheless, the modeled water-use
quantity can also in this approach be higher than actual regional water use, for instance in the case of Aral
Sea region of Central Asia, for which actual water use
has been quantified in a hydrological modeling study
by Shibuo et al. (2007).
The interactive processes between the land surface and the climate regime in the atmosphere vary
between regions (e.g., Koster et al., 2004). Major factors that govern the geographic variability of irrigation-induced regional climate change have been assumed to depend on the extent of irrigated land area
by Lobell et al. (2009), who reported temperature
biases for climate simulations that neglected irrigation. For the Aral Sea region in Central Asia, lack of
agreement between observed temperature records
and climate model simulation results, which did also
account for irrigation, was attributed to inaccuracy
with regard to the quantity of water being applied for
irrigation in that region. This indicates an effect of
human water-use, and not only land-use, in modifying the regional water cycle. Furthermore, regarding
the linkage between the climate regime and the land
surface processes, Schär et al. (2004) and Seneviratne
et al. (2006) have identified a soil moisture precipitation feedback to regional climate, even in regions
with assumed weak soil moisture-atmosphere coupling (Koster et al., 2004). However, the fact that soil
moisture change is not only a climate change feedback, but also depends on human water use, such as
the applied quantity of irrigation water on land, again
indicates an important direct role of humans in altering regional water cycles, which needs to be further
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Shilpa Muliyil Asokan
investigated.
Regionally, the impacts on water resources from
changes in global atmospheric circulation and climate overlap with the impacts from land-use and
water-use changes (Lobell and Field, 2007). The
overlap makes it hard to distinguish between different hydrological cause-effect relations and impacts
(Milly et al., 2002; Piao et al., 2007; Destouni et al.,
2008). Although recent technological possibilities,
such as Moderate Resolution Imaging Spectrometer [MODIS] (King et al., 1992) and ET algorithm
techniques based on satellite remote sensing (Zhang
et al., 2010), provide more tools, for instance for ET
change distinction and quantification, they have the
limitation of only reflecting changes in relatively recent time periods that overlap with the accessibility
to these technologies (Douglas et al., 2006; Cheng et
al., 2011; Loarie et al., 2011). For more general and
relevant understanding of the hydrological effects
of both global climate change and regional land and
water use changes there is a need for distinguishing
and quantifying irrigation and other change drivers
across different times and relevant water management scales; the latter are commonly those of regional drainage basins. The topographical water divides
that define the regional drainage basins constrain the
flows of water and waterborne substances through the
landscape, and so does the associated environmental
impacts of manmade changes to these flows (Jarsjö
and Destouni 2004; Darracq et al., 2005; Shibuo et al.,
2007; Destouni and Darracq 2009; Törnqvist et al.,
2011; Visser et al., 2012; Destouni et al., 2013). Yet,
also on those scales, several scientific questions are
open and in need of further investigation in the context of hydro-climatic change history and projection,
where the latter perspective also includes the large
spatial scale discrepancy between typical hydrological
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drainage basins and the coarse resolution of general
circulation models (GCMs) (Milly et al., 2005; Groves
et al., 2008).
This thesis aims to understand, distinguish and
quantify hydro-climatic changes caused by irrigation, with particular focus on two geographically and
hydro-climatically different main irrigated regions
of the world: India, with the Mahanadi River Basin
(MRB) as case study, and Central Asia, with the Aral
Sea Drainage Basin (ASDB) as case study. The thesis compiles data and quantifies historic to present
hydrological conditions for the MRB case (Papers
I-II), and utilizes and extends previous such compilations and quantifications for the ASDB case (Jarsjö
and Destouni, 2004; Shibuo et al., 2007). With this
hydrological quantification basis, the thesis develops
and uses a data driven, water-balance constrained approach to understanding and quantifying long-term
hydrological changes and their drivers historically
(Papers II-IV) and in future change scenarios (Paper
V). This approach honors the fundamental water balance constrains within each hydrological basin, taking also into account human use, re-distribution and
export/import of water, in addition to the hydrology
of each basin. Furthermore, the thesis quantifies and
compares regional climate implications, in terms of
the temperature change contributions of historic
changes to ET induced by irrigation and other change
drivers in the two regional basins (Papers III-IV). As
a benchmarking assessment for future hydro-climatic
change projections, and projection comparison with
the soon forthcoming 5th IPCC report, the Appendix
to Paper V contain a compilation and comparison
for both the regional case studies the available basinscale hydro-climatic data with corresponding results
from different General Circulation Models (GCMs),
as reported in Assessment Report Four (AR4) of the
Intergovernmental Panel on Climate Change (IPCC)
(IPCC, 2007).
Hydro-climatic change in irrigated world regions
2 METHODOLOGY
2.1 Case Study Areas
Figure 1 shows the two case study basins considered in
this study: the Mahanadi River Basin (MRB) in India
(Figure 1a) and the Aral Sea Drainage Basin (ASDB)
in Central Asia (Figure 1b). MRB is located in East
Central India within geographical co-ordinates of
80º30’ to 86º50’ E and 19º20’ to 23º35’ N. ASDB is
located in Central Asian region within geographical
co-ordinates of 54º30’ to 78º30’ E and 34º30’ to 52º30’
N. Major land use and associated water use changes
that have taken place in both these basins in the 20th
century are related to intense irrigation of agricultural
areas, with Figure 1 showing the irrigation distribution
within the basins.
Figure 1. Location map and irrigated area percentage within the investigated basins. (a) Mahanadi River Basin (MRB) in
India and (b) Aral Sea Drainage Basin (ASDB) in Central Asia. The red line shows the boundary (water divide) of the basins
and the green scale shows the percentage of irrigated area within the basins (according to Siebert et al., 2007). The blue lines
seen within the basins are the major rivers. The light and dark shades of blue in (b) illustrate the outline of Aral Sea before
(pre-1950) and after (in 2005) its major shrinkage.
MRB is an exorheic basin that drains into Bay of
Bengal, which eventually joins the Indian Ocean. The
basin covers an area of about 135 084 km2 within the
Orissa and Chhattisgarh provinces. The Mahanadi
River with a total length of 851 km originates at an
elevation of about 442 m above Mean Sea Level (msl).
The Hirakud dam with its reservoir, built in 1956 with
a gross water storage capacity of 8136 × 106 m3, is an
engineered water storage structure that facilitates
different human water uses, including water use for
irrigation in the basin. Agricultural areas in MRB are
cultivated throughout the year. The cropping seasons
are broadly classified into Kharif (rainfed cultivation)
and Rabi (irrigated cultivation) seasons. The Kharif
season extends from June till November and the Rabi
season spans from December till May. Out of the total
annual irrigation water demand of 11km3 in MRB, the
Kharif season utilizes 7km3 and Rabi season demands
4km3.
ASDB is an endorheic basin with its two major
rivers Amu Darya and Syr Darya draining into the
terminal Aral Sea. The total basin area is about 1 854
534 km2 (towards the end of the 20th century) which
spreads almost the entire region of Central Asia,
occupying 1.3% of the Earth’s land surface. Major land
and water use changes in the Aral Sea region were
initiated during the 1960s with the commencement
of extensive water diversion and irrigation schemes
leading to dramatic shrinkage of the Aral Sea (Shibuo
et al., 2007). Several irrigation canals were constructed,
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Shilpa Muliyil Asokan
the largest of which is the Karakum canal, reported
to export about 8–12 km3 of water from the ASDB
to other areas annually (Glantz, 2005). Along with
the water diversion from the two major rivers, the
irrigation of land in the ASDB (furrow irrigation has
been, and is still the predominant irrigation method in
the basin) has increased regional evapotranspiration
and dramatically decreased the river runoff into the
Aral Sea (Figure 2), leading to the equally dramatic
shrinkage of the latter (Shibuo et al., 2007).
Figure 2. River discharge from the ASDB into the Aral Sea
during the 20th century. The grey line indicates the discharge
into the Aral Sea through the principal rivers Amu Darya and
Syr Darya (Mamatov, 2003, Shibuo et al., 2007). Running
average (30 years) is shown in thin black line.
2.2 Basin-scale hydro-climatic data
The time series plots of basin-scale annual average (a)
temperature and (b) precipitation in MRB and Aral
region for the 20th century is illustrated in Figure
3. The observation data is obtained from the CRU
T S 2.1 database by Mitchell and Jones (2005). This
figure clearly illustrates the significant difference in
the climatic settings of the two basins. The average
rainfall in MRB during the 20th century is about five
times higher than that of the average ASDB rainfall.
The average temperature in Aral region is about onethird of the MRB average temperature during the last
century.
In order to understand the change effects of
the main Hirakud dam and water reservoir, and
associated irrigation water-use changes in MRB, we
compared in Papers II and IV the hydro-climatic
conditions during the time period 1956–2000 with
those in the pre-reservoir time period of 1901–1955.
Similarly, in the case of Aral region, we compared
in Paper III the hydro-climatic conditions during
the time period 1983–2002 with the relatively
undisturbed hydrological conditions during the time
period 1901–1950, before the commencement of the
major irrigation schemes in that basin. The available
hydro-climatic data show then directly an increase in
temperature by 0.26°C, and a decrease in precipitation
by 60 mm/year from (1901–1955) to (1956–2000) in
MRB. For Aral region, the hydro-climatic data show
an increase in temperature by 1.1°C, and an increase
in precipitation by 11 mm/year from (1901–1950) to
(1983–2002).
In addition to temperature and precipitation
data, runoff data is also needed to close, assess and
interpret basin-scale water balances and changes
to them over longer, historic time periods like the
whole 20th century. For Aral region, river discharge
data was obtained for most part of the 20th century
(even though on different time aggregation scales
for different time periods in the century; Figure 2) as
reported by Shibuo et al. (2007). For MRB, however,
river discharge data was obtained only for the limited
time period from 1990 to 2000 from the Central Water
Commission, New Delhi. This data was compiled
and reported in detail by Asokan (2005), and Paper
I summarized and utilized it for some first scoping
calculations and assessments of present seasonal
hydrological conditions and their possible future
changes due to climate change in the region.
The limited time period of runoff data for MRB
implied that longer-term changes to annual average
hydro-climatic and water balance conditions in the
basin could not be directly assessed based only on
data. A different type of hydrological modeling, with
focus on longer-term changes to annual average
hydro-climatic conditions and basin-scale water
Figure 3. Annual average temperature (a) and precipitation (b) within the Mahanadi River Basin (color red) and the Aral
Region (color blue); based on data from Mitchell and Jones [2005]. Running averages (10 years) are shown in black thin lines.
12
Hydro-climatic change in irrigated world regions
balance, rather than the short-term, intra-annual
fluctuation modeling used in Paper I, was needed
to bridge the historic data gaps in the MRB, and
address its long-term change similarly as for the Aral
region. Even though more runoff data was available
for the latter, such a modeling approach had been
developed and used also for the Aral region by Shibuo
et al. (2007). A similar approach to historic data gap
bridging and interpretation was then also developed
for the MRB in Paper II, and used there and further in
Paper IV for assessment and interpretation of historic
hydro-climatic changes, drivers and impacts in that
basin, and for consistent cross-regional comparison
with corresponding long-term Aral region results in
Paper IV.
2.3 Data driven water-balance constrained
quantification of hydro-climatic change
A drainage basin is a basic hydrological spatial unit
that naturally (topographically) confines the different
water flow components of the hydrological system,
and hence the perturbations of hydro-climatic
change can be best captured and understood at this
scale. The understanding of and distinction between
different hydrological change components, and their
drivers and effects can be greatly aided and improved
by honoring and accounting for the water flux
constraints implied by the fundamental water balance
quantification ET=P−R−DS (where P is precipitation,
R is runoff and DS is water storage change) which
applies to all hydrological drainage basins, with the
effects of water storage change, DS, often being small
on larger than annual temporal scales (Destouni et al.,
2013). The basin-scale water balance constraints imply
that the commonly difficult to measure and quantify
ET term can be derived from directly measured P data
across the basin surface and R data at the basin outlet;
the latter should then ideally be measured data over
the same time period as the P data, but if that is not
available over the whole period, model interpolation/
extrapolation of R has to be used to bridge the R data
gaps, as done here for the MRB case.
The hydrological modeling approach can then
be lumped (consider average water flows and their
balance over a whole drainage basin) or distributed
(resolve water fluxes also in grid cells within the
basin) depending on the aim of the investigation.
In this thesis, both approaches have been used for
different study aims across the Papers II−V, and have
also been compared in Paper IV for the case of MRB.
In the distributed hydrological modeling approach,
the basin area is divided into grid cells of equal (in the
present work) or variable size, with the climate and
land use data as input across the grid cells to generate
output precipitation surplus at each individual cell
and routed along different hydrological pathways (the
runoff and water balance in the catchments of which
must then be separately honored and checked against
different local data) and ultimately in total towards
the outlet of the basin. This methodology provides
a thorough understanding of the spatial variability
of hydrological processes, in addition to the integral
hydrological change that is reflected by the total
runoff at the outlet of a whole basin. For instance,
the intensity of ET at different parts of a drainage
basin (say, at irrigated versus non-irrigated parts)
can be well represented through such a distributed
hydrological modeling approach. Furthermore, also
larger-scale comparisons, for instance with climate
model results, can be facilitated by this approach
considering only or mostly the total quantity of water
flows, including total ET from the land surface to the
atmosphere, through a whole hydrological basin.
2.4 Using temperature change seasonality
to distinguish irrigation and other drivers
of hydro-climatic change
Hydro-climatic changes, not least those in the two
regional cases of this thesis, are driven by both global
climate change and regional land-water-use changes,
including irrigation (Shibuo et al., 2007; Paper II).
It is then important to distinguish, understand
and quantify the drivers and impacts of different
contributions to total observed hydro-climatic
change. Papers III and IV develop and apply a novel
methodology to distinguishing irrigation from
other drivers of hydro-climatic change, based on the
seasonality of observed temperature changes, along
with hydrological and water-use data (Paper III for
the Aral region) combined with scenarios (to analyze
implications of data gaps; Paper IV for the MRB) for
the different irrigation conditions in different seasons.
Calculations of temperature change contributions
from irrigation in regional hydrological basins can
use straightforward physical relations (described
in detail in Papers III-IV) between observed
seasonal temperature changes, and hydrologically
determined seasonal changes in ET and associated
changes in latent heat flux over each regional basin.
Furthermore, the latent heat flux and temperature
change contributions from the regional manifestation
of global climate change can then also be calculated as
the difference between the observed annual average
temperature change, and the calculated temperature
change contribution from irrigation in each basin.
2.5 Linking climate model outputs with
hydro-climatic change quantification
After development of a relevant, water-balance
constrained hydrological model based on data for
historic, multi-decadal hydro-climatic dynamics and
changes in a regional basin (Paper II), one can also
further use that model development for projections
of possible future hydrological changes in the basin.
This was done for the Aral region in Paper V, using
GCM output for future climate change scenarios,
along with future scenario assumptions also for the
regional land-water-use conditions, as drivers of the
hydrological modeling. The aim of Paper V was to
understand how, and to what extent, future climate
13
Shilpa Muliyil Asokan
change and human re-distributions of water can affect
future hydrology and water resource conditions in the
basin.
Such interactions of climate change and localregional water resource conditions are not well
resolved in current GCMs, or in regional climate
models (RCMs). To quantify these interactions, Paper
V used the climate (temperature and precipitation)
outputs from 14 GCMs in the IPCC AR4 (IPCC,
2007), which are tabulated in Table 1.
For the large Aral region, with typically many GCM
grid cells falling within the basin area, GCM outputs
could be used directly, without any downscaling, as
input data to the hydrological modeling in Paper V.
Furthermore, the same GCM grid cell magnitude and
reasoning for not requiring a particular downscaling
procedure for the Aral region apply also for the follow-
up, benchmarking comparison in the Appendix to
Paper V between basin-scale results of individual
GCMs and corresponding basin-scale observations
(CRU TS 2.1 climate data) of temperature and
precipitation. Also for the much smaller MRB case,
where only some models had relatively many grid
cells within the basin area (as listed in the Appendix
to Paper V), the corresponding comparison was
carried out without any downscaling procedure.
This was done in order to directly compare results
on model performance versus observations between
the two different basin scales, and thereby distinguish
and understand effects of possible GCM bias versus
effects of insufficient GCM grid resolution on
resulting GCM result and observation discrepancies
for the different basins.
Table 1. List of the AR4 GCMs, with their respective agency, used in this thesis.
GCM
CSIRO: Mk3.0
ECHAM5/MPI-OM
GFDL:CM2.0;
GFDL:CM2.1
HadCM3
MIROC3.2
CNRM-CM3
ECHO-G
GISS-ER
HadGEM1
INMCM3.0
IPSL-CM4
MRI-CGCM2.3.2
CCSM3
PCM
14
Center and Location
CSIRO (Australia)
Max Planck institute of Meteorology (Germany)
Geophysical Fluid Dynamics Laboratory, NOAA
Hadley Centre for Climate Prediction and Research, Met Office
(United Kingdom)
Center for Climate System Research, The University of Tokyo;
National Institute for Environmental Studies, and Frontier Research
Center for Global Change (Japan)
Centre National de Recherches Meteorologiques, Meteo France
(France)
Meteorological Institute of the University of Bonn (Germany), Institute
of KMA (Korea), and Model and Data Group
Goddard Institute for Space Studies, NASA (USA)
Hadley Centre for Climate Prediction and Research, Met Office
(United Kingdom)
Institute of Numerical mathematics, Russian academy of Science,
Russia
Institut Pierre Simon Laplace (France)
Meteorological Research Institute (Japan)
National Center for Atmospheric Research (United States)
National Center for Atmospheric Research (United States)
Hydro-climatic change in irrigated world regions
3 RESULTS
3.1 MRB data compilation and scoping
assessments − Paper I
Paper I summarizes the first data compilation
and scoping assessment, particularly of the large
hydrological seasonality in MRB, clarifying and
quantifying the signature, monsoon-dependent
hydro-climatic identity of this regional basin. The
climate in MRB is tropical hot and humid monsoonal,
and its temporal rainfall pattern is dominated by the
monsoon cycles, with about 70% of the precipitation
occurring during the south-west monsoon period
(June to October; Paper I). There are thus only a few
months of heavy rainfall during the Wet Season in
the MRB that can provide the total irrigation water
amount used for irrigation during both the Wet and
the Dry Seasons.
Figure 4 shows the time series plot of Wet Season
and Dry Season precipitation in MRB during the 20th
century. This seasonality, along with that in observed
temperature and that in availability and use of water
for irrigation were further considered in Paper IV, and
used there to distinguish irrigation and other drivers
of hydro-climatic change, with results discussed in
section 3.3 below.
Figure 4. Seasonal plot of observed precipitation in MRB
during the 20th century. Wet Season (color blue) represents
the months from June to November, and Dry Season (color
brown) represents the months from December to May.
Running seasonal averages (10 years) are shown in black
thin lines.
Spatially, the first data compilation in Paper I
clarified that the more upstream part of MRB is
comparatively dry, receiving an average annual
rainfall of about 1000 mm, which then increases
towards the central part of the basin with average
annual rainfall of about 1300 mm, and even more
further downstream in the relatively wet coastal
belt with average annual rainfall of about 1700 mm.
This spatial distribution in precipitation reflects also
the spatial distribution of water availability and use
for irrigation. This distribution pattern was further
considered in Paper II, and used there to distinguish
hydro-climatic change effects of land-use versus
water-use, with results discussed in section 3.2 below.
3.2 Quantification of long-term hydro-climatic change in MRB − Paper II
The spatially distributed modeling of long-term
hydrological change in MRB clarified in particular
the role of human water-use in the long-term change
pattern of ET in the basin. Specifically, the basin’s
map of water-use (for irrigation) is significantly
different from that of land-use (irrigated area), and
the map of greatest modeled ET changes in the
basin corresponds well to the actual water-use map,
rather than to the land-use map (Figure 5). This
finding questions a common assumption in climate
modeling that it is mainly land-use that determines
the climate effects of irrigation. This assumption
implies that, under dry conditions, irrigation is
applied in the modeling to maintain relatively high
soil moisture contents that can in turn sustain some
assumed land-use production of biomass. However,
when/where ever the actual water availability in space
and/or time is insufficient to maintain such high soil
water contents, the modeled water-use for irrigation
and the corresponding ET flux contribution of the
irrigation will be higher than the real quantities.
Furthermore, these model quantities will also tend to
be higher under dry than under humid spatiotemporal
conditions, failing to reflect the quite opposite reality
of the water availability/scarcity relation to the water
use for irrigation at ground level (see discussion for
MRB in section 3.1 above, and results for both regions
in section 3.3.1 below).
15
Shilpa Muliyil Asokan
Figure 5. Distributed maps of (a) water-use for irrigation and (b) evapotranspiration changes from the period 1901−1955 to
the period 1990−2000 in MRB.
3.3 Distinguishing irrigation and other drivers of hydro-climatic change – Papers III−IV
Paper III developed the approach to distinguishing
and quantifying irrigation and other drivers of hydroclimatic change, through the seasonality of changes in
temperature (ΔT) and applied it to the whole ASDB
and Aral Sea region. Paper IV further applied the
same methodology to the MRB, distinguishing and
utilizing also there ΔT differences between the Wet
Season and Dry Season, and also carrying out a crossregional comparison between Aral region and MRB
results in this context.
internal flow in the total land region, including both
the Aral Sea and its drainage basin. The net total
water flow balance in this land region is therefore
quantified as P−ET, which is here still negative and
thus imbalanced at the end of the 20th century, so that
the Aral Sea continued to shrink also after that time.
In contrast, R from the exorheic MRB flows into the
ocean, which is not particularly dependent on just
that basin flow into it, and R is here an external flow
component for the whole MRB land system. The net
total water flow balance in this land region is then
quantified as P−ET−R, which was essentially zero and
thus balanced at the end as in the beginning of the
20th century.
3.3.1 Annual hydro-climatic changes and their
cross-regional comparison
Table 2 summarizes data and results from distributed
hydrological modeling for hydro-climatic conditions
and flows, and their changes, in both MRB and
Aral region. Model results include also those from
a hypothetical simulation scenario of only climate
(and no irrigation) change from the beginning
to the end of the 20th century, which quantifies
hydrological flow changes only due to the observed
climate (temperature and precipitation) change.
These simulated climate-induced changes can then
be compared to corresponding observed data and
modeled results for the realistic conditions of both
climate and irrigation change over the same period.
Figure 6 illustrates the cross-regional comparison
between changes in different annual average water
flows in MRB and Aral region. In absolute terms,
all water flow changes are much smaller in Aral
region than in MRB. Yet, the small runoff (R) and
associated other flow changes in Aral region have led
to one of the world’s worst environmental disasters in
modern time: the Aral Sea desiccation and associated
ecosystem collapse (Gaybullaev et al., 2012). With
regard to annual average regional water balance, the
terminal Aral Sea is entirely dependent on R into it
from the endorheic ASDB, and R constitutes here an
16
Figure 6. Water flux changes (for precipitation, ∆P,
evapotranspiration, ∆ET, and runoff, ∆R) in mm per year
from the period 1901−1955 to 1956−2000 for the MRB,
and from 1901−1950 to 1983−2002 for the Aral region.
The magenta error bars for ∆R and ∆ET for the distributed
hydrological modeling of MRB show the possible error range
associated with these results by considering the available
runoff observation data for the 1956-2000 instead of the
modeled runoff result for that period (Table 2) To maintain
basin-scale water balance, the ∆R error range must also be
mirrored as a corresponding ∆ET error range. Black error
bars show 80% confidence intervals (Appendix A, Table A1
of Paper IV) for the other ∆ET and ∆R results, as well as for
∆P, for both regions.
Hydro-climatic change in irrigated world regions
The irrigation-driven contributions to the annual
average water flow changes can be quantified from
the result difference between the realistic ClimateIrrigation scenario and the hypothetical Climate
scenario in Table 2. In both MRB and Aral region, the
irrigation-driven changes are then greater than the
climate-driven ones. In absolute terms, less irrigation
water is used in Aral region than in MRB, even though
the smaller Aral region water use has had much more
dramatic and severe regional impacts (the R decrease
and associated Aral Sea shrinkage) than the larger
water use in MRB. The regional impact differences are
due to the much smaller original (and current) water
availability (in terms of both precipitation and runoff,
Table 2) in Aral region than in MRB. Furthermore,
the differences in regional water use emphasize the
point made in section 3.2 above, regarding the real
water use for irrigation being greater for greater water
availability, rather than the opposite assumption often
made in climate modeling.
3.3.2 Seasonal hydro-climatic change implications and cross-regional comparison
Table 3 summarizes seasonal temperature and
precipitation data and their changes from the
beginning to the end of the 20th century for both
MRB and Aral region. In MRB, there is very large
difference in precipitation and small difference in
temperature between the Wet Season and the Dry
Season. The basis for season differentiation and the
temporal extent of the different seasons is therefore
here determined by precipitation rather than by
temperature. The opposite applies in Aral region,
with much more evenly distributed precipitation
and much larger difference in temperature between
the growing and the non-growing season. The basis
and temporal extents of the different seasons here are
therefore primarily given by temperature rather than
by precipitation differences.
Table 2. Summary of basin scale data and model results for MRB and Aral region.
Pre-reservoir
Climate-
Climate: hypothetical
Irrigation
scenario of only
climate change
Mahanadi River Basin
1901-1955
1956-2000
1956-2000
Data-given average temperature (°C)
25.19
25.45
25.45
Data-given annual average precipitation (mm yr-1)
1334
1274
1274
Total modeled ET (mm yr-1)
668
706
656
-
81
-
Modeled runoff at basin outlet (mm yr-1)
666
568
618
Observed runoff at basin outlet (mm yr-1)
-
515*
-
1901-1950
1983-2002
1983-2002
7.5
8.6
8.6
249
260
260
250
265
260
-
23
-
35
7
36
38
6
-
Data-given irrigation water-use within the basin (mm yr-1)
Aral Region
Data-given average temperature
(°C)
Data-given annual average precipitation (mm
yr-1)
Total modeled ET from whole region – Aral Sea and its drainage
basin (mm
yr-1)
Modeled irrigation water-use within the basin (mm yr-1)
Modeled runoff from drainage basin into Aral Sea (mm
yr-1)
Observed runoff from drainage basin into the Aral Sea (mm yr-1)
*Average runoff from available observations for the period 1990-2000 [Asokan, 2005]
Table 3. Average seasonal temperature and precipitation at the beginning and the end of 20th century for the Mahanadi River
Basin (MRB) and Aral region.
Temperature (oC)
Mahanadi River Basin
Precipitation (mm yr-1)
1901-1955
1956-2000
1901-1955
1956-2000
Dry Season
24.44
24.74
198
190
Wet Season
25.93
26.16
2470
2358
Aral Region
1901-1950
1983-2002
1901-1950
1983-2002
Growing Season
14.7
15.5
192
193
Non-growing Season
-0.1
1.54
354
381
17
Shilpa Muliyil Asokan
Furthermore, Figure 7 illustrates the cross-regional
comparison of seasonal ΔT between MRB and Aral
region. In MRB, the basin-average ΔT during the
Wet Season is an increase of 0.23°C, which is smaller
than the ΔT change (also increase) of 0.30°C during
the Dry Season. In Aral region, the basin-average ΔT
during the growing season is an increase of 0.81°C,
while that during the non‐growing season is an
almost double increase of 1.67°C.
The smaller basin average temperature change
during the Wet Season for MRB (in comparison with
the Dry Season), and during the growing season in
Aral region (in comparison with the non-growing
season) is consistent with more irrigation water
being used during Wet Season in MRB, and the only
irrigation applied in Aral region during the growing
season. Figure 8 summarizes the results obtained
in Papers III-IV by utilizing the different seasonal
temperature changes in Figure 7 to distinguish and
quantify the change contributions to total annual
average ΔT due to irrigation (ΔTirr), and due to the
regional manifestation of global climate change
(ΔTcl) for both MRB and Aral region. Note that the
ΔTcl result then quantifies the total climate‐driven
surface temperature change and not only the latent
heat‐related change contribution, whereas ΔTirr is
entirely due to the latent heat flux change driven by
regional irrigation practices.
Figure 7. Changes in average seasonal surface temperature (ΔT) in degrees Celsius for the Mahanadi River Basin (MRB) and
the Aral region including the Aral Sea Drainage Basin and the Aral Sea. (3a) The change from 1901−1955 to 1956−2000 for
the Wet Season in MRB. (3b) The change from 1901−1955 to 1956−2000 for the Dry Season in MRB. (3c) The change from
1901−1950 to 1983−2002 for the growing season in the Aral region. (3d) The change from 1901−1950 to 1983−2002 for nongrowing season in the Aral region. All these seasonal temperature changes (ΔT) are significant at least at the confidence level
p=0.999 (see Appendix A, Table A1 of Paper IV). Source: Mitchell and Jones [2005].
18
Hydro-climatic change in irrigated world regions
3.4 Assessing climate model applicability to
basin scale hydro-climatic change – Paper V
and its Appendix
Figure 8. Changes in surface temperature (∆T) for the
Mahanadi River Basin (from 1901−1955 to 1956−2000) and
for the Aral Sea region (from 1901−1950 to 1983−2002).
Error bars show 80% confidence intervals for the data-given
total average annual T changes in both regions (Appendix A,
Table A1 of Paper IV).
In summary, the cross-regional comparison in Paper
IV shows that differences in seasonal temperature
changes are exhibited and can be used beyond the
original approach development and application in the
Aral region (Paper III) to distinguish and quantify
irrigation effects on hydro-climatic change across
different land regions. An important insight gained
from the present comparison is that irrigation-driven
absolute changes in the atmospherically important
ET and latent heat (F) fluxes, and through these also
in surface temperature (T), may be greater in land
regions with small relative water resource changes, like
MRB, than in land regions with severe water resource
changes, like the Aral region. Therefore, the regional
climate importance of natural or anthropogenic
climate change drivers, versus that of regional land
and water use drivers cannot simply be judged from
the water resource severity of the latter change drivers.
Conversely, one cannot from just climate modeling of
T, ET and F changes in a region judge the severity of
their water resource effects in the landscape. From
both change assessment perspectives, actual water
balance constraints need to be accounted for in order
to realistically link and accurately assess different
inter-connected hydro-climatic change drivers and
effects in a land region.
Paper V considered future climate change scenarios for
Aral region by using the spatially distributed outputs
of the 14 GCMs from the IPCC AR4 (IPCC, 2007) and
comparing them with corresponding earlier GCM
results from the Third Assessment Report of IPCC
(IPCC, 2001) and CRU TS 2.1 observation records.
The Appendix to Paper V compiles corresponding
AR4 GCM outputs and comparisons with observation
records also for MRB. Figure 9 summarizes and
illustrates individual and ensemble mean results from
AR4 GCMs for temperature (T) and precipitation (P),
and their comparison with CRU TS 2.1 observation
records, for both MRB and Aral region.
The T projections from all the GCMs show an
increasing trend, irrespective of whether they overor under-estimate T compared with observation data.
The ensemble mean results of all the GCMs yields
T and its change trend at comparable range to CRU
observations in both case study regions. However,
with regard to P, some GCMs show an increasing
trend, while others show a decreasing trend. In the
case of MRB, the ensemble mean projection of all the
GCMs underestimates P relative to CRU observations,
while in Aral region, the ensemble mean projection
overestimates P.
Acknowledging such climate model biases and
understanding how to best handle them in hydrological
modeling and assessments is important for relevant
projection of basin-scale hydrological changes in
response to future climate change scenarios. Paper
V develops and applies such a handling approach
to projection of future hydrological change in Aral
region based on the AR4 GCM results shown in Figure
9. Regardless of the uncertainty implied by individual
GCM biases, hydrological model results in Paper V
driven by either bias-corrected or not bias- corrected
ensemble mean GCM results and projections for Aral
region converge in indicating continued decrease in
the regional river discharges, if the present irrigation
practices are maintained also in the future (Figure
10). Note then that both the historic and the projected
future decreases in river discharge in this region
have occurred and are expected to continue in spite
of historic and ensemble-mean projected increases
in P. These divergent R and P changes re-confirm
the concluding assessment in section 3.3 above, that
regional climate changes in T and P alone cannot be
extrapolated to runoff and water condition changes at
the land surface.
Nevertheless, T and P are still important
hydrological drivers, and therefore we have further
assessed the performance of individual GCMs
in simulating these climate drivers T and P on
hydrological basin scales under different geographic
and hydro-climatic settings. The Appendix to Paper
V quantifies and Figure 11 summarizes and illustrates
the relative model bias of GCM results for T (Figure
11a) and P (Figure 11b) relative to corresponding
19
Shilpa Muliyil Asokan
Figure 9. Observed (grey line; with running average in black) and projected (14 AR4 GCMs) temperature in (a) MRB and
(b) Aral region, and precipitation in (c) MRB and (d) Aral region. Thick red line and the corresponding data label show the
uncalibrated ensemble mean values of the GCM projections.
Figure 10. Observed and projected total river discharge to
the Aral Sea. The observed runoff changes so far are primarily
due to irrigation expansion, whereas the future runoff results
assume maintained irrigation practices following the 1984–
1989 period, and quantify the effect of climate change from
the reference period 1961–1990 to 2010–2039. The error
bar indicates the range of runoff projection obtained by
running the hydrological model with the 14 IPCC AR4 GCM
temperature and precipitation projections.
observations for both MRB and Aral region. Relative
model bias is calculated as the difference between
the GCM simulations of basin-average T and P and
the corresponding basin-average T and P based on
observation data from the CRU TS 2.1 database,
normalized with the latter basin-average observation
20
values. The T results in Figure 11 show less GCM
scatter than the P results for both regional basins.
The GCM results for P show greater deviation from
observations than the T results, with general P underprediction bias in MRB, and over-prediction bias in
Aral region, as also indicated by the ensemble mean
results in Figure 9. GCMs with good performance
with respect to the T observations in both basins
(GFDL:CM2.0_2.1, HadCM3, IPSL-CM4, MRICGCM2.3.2 etc.) are not necessarily the best ones
with regard to P observations, making it difficult to
choose one/few best GCMs for hydro-climatic change
projection in a region.
The comparison with observation data in Figure
11 does not indicate greater GCM bias for the small
MRB than for the large Aral region, implying that the
deviations of climate model results from observations
may in both cases depend more on actual model
bias than on scale effects. The Appendix to Paper V
includes also results for relative model performance,
indicating how well a particular GCM performs with
respect to the typical GCM result. It is then only with
this perspective of comparing model results with each
other that there is an apparent difference in GCM
performance between the large Aral region (with
smaller scatter around typical GCM result) and the
small MRB (with greater scatter around typical GCM
result).
Hydro-climatic change in irrigated world regions
Figure 11. Relative model bias of individual GCMs with respect to corresponding CRU TS 2.1 observation data for (a)
temperature and (b) precipitation in MRB and the Aral region.
21
Shilpa Muliyil Asokan
22
Hydro-climatic change in irrigated world regions
4 DISCUSSION
Results in this thesis show that the effect of human
water use on the water balance of a hydrological
basin depends on whether the nature of that basin
is endorheic or exorheic. For an endorheic basin (in
this case the ASDB), the runoff R is an internal flow
component, and therefore the human water diversion
for irrigation which is reflected in the runoff R, has
an impact on the terminal surface water body (here
the Aral Sea) to which it drains. However, for an
exorheic basin (in this case the MRB), where the R
is an external flow component from the hydrological
basin system, the effect of the same human water use
is smaller because it impacts a relatively small fraction
of the total discharge into the ocean. Understanding
the role of the nature of the hydrological basin is
hence important for understanding hydro-climatic
change impacts.
There has been a lack of accounting for the ground
level reality of actual human water use, and water
availability and distribution in the landscape in
climate modeling. For instance, climate models may
assume application of more (unlimited) irrigation
water than is actually available under dry conditions,
which leads to overestimation of ET flux from
the land surface and therefore fails to reflect the
actual regional water status. Furthermore, such an
assumption can also lead to higher modeled ET flux
in relatively dry regions/seasons than in relatively wet
regions/seasons. A basin-wise, data-driven and water
balance-constrained approach to ET quantification
can reflect the actual water resource status of the
basins. Paper II has quantified ET estimation error
with the water balance closure to be around 10-15%,
which is significantly lesser than ET estimation errors
without such water balance constraints, reported to be
around 30-50% (Kite and Droogers 2000). Remotesensing possibilities to estimate ET, such as based on
MODIS (King et al., 1992) and other ET algorithm
techniques (Zhang et al., 2010) represent additional
tools for estimation of large-scale ET, but are limited
to relatively recent time periods (Dougluas et al.,
2006; Cheng et al., 2011; Loarie et al., 2011).
Accurate assessment of vapor flux to the atmosphere
by ET from irrigated land areas is important for
quantification of associated temperature change at
the land surface, which is an essential component
of local-regional climate change. Thesis results have
distinguished and quantified the irrigation and other
drivers of hydro-climatic change through a novel
data-driven approach based on temperature change
seasonality. We found that the total and the climatedriven land surface T changes are larger in the Aral
region, whereas the net total irrigation effect is much
smaller in this region than in MRB (both in absolute
terms and relative to climate-driven T change). Had
ASDB been an exorheic basin, there would not have
been such irrigation-driven surface water shrinkage
as that of the terminal Aral Sea, and the irrigationdriven temperature change (cooling effect) would
have been much larger (cooling of −0.6°C instead of
−0.1°C) in the Aral region, which would then also be
larger than the cooling effect in the MRB.
Furthermore, thesis results show relatively greater
changes in irrigation-driven ET, latent heat flux
and surface temperature in MRB, which is a region
with relative small water availability changes, in
comparison to the Aral region, which has had severe
such changes. This implies that the severity of changes
to water resource availability in a land region cannot
be directly assessed from the magnitude of climaterelated changes at the land surface, and vice versa.
Actual water balance constraints and hydrological
basin conditions need to be taken into account
for accurate understanding of the interconnection
between different hydro-climatic changes, in
interactions with the atmosphere at the land surface,
and water processes and conditions through the
whole landscape.
The thesis also analyzed basin-scale results of
global climate models in relation to each other and to
available observation data of T and P for the two study
regions. Deviations between observations and climate
model outputs appear to depend more on GCM
biases than on the spatial scale difference between
the two different regional basins. Lack of consistency
between individual GCM performance for T and P
results imply difficulty in identifying one (or more)
generally well-performing GCM(s) for a region, and
hence the ensemble mean of the available GCMs may
be more useful for hydro-climatic change assessment
and projection. Projection results for future changes
in the Aral region further show that climate model
outputs cannot alone judge future changes in water
resource availability and change vulnerability in the
region. Scenarios of future development of human
water use for irrigation and other major water uses
must also be accounted for to accurately understand
and project possible future hydrological and water
resource changes.
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Shilpa Muliyil Asokan
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Hydro-climatic change in irrigated world regions
5 CONCLUSIONS
This thesis has developed and successfully applied
a consistent basin-wise, data-driven water balanceconstrained approach to quantification of long-term
hydro-climatic change in two, hydro-climatically
different irrigated regions in the world. The approach
has distinguished and quantified the role and impacts
of climate and land-water-use (in particular related
to irrigation) changes as drivers of hydro-climatic
change, both historically and in future scenario
projections.
Important results and implications from the
two basin applications and their cross-regional
comparison can be summarized as:
• It is important to account for human water use,
and its change and spatial patterns, in addition
to atmospheric climate change, in order to
understand and accurately interpret past and
future hydro-climatic changes in land regions.
• Human redistribution of water within hydrological
basins can alter both the water balance and the
surface temperature of land regions.
• Climate model results for precipitation in a
region cannot be simply extrapolated to regional
changes in water flow, water balance and water
availability in the landscape.
•
•
•
•
Good GCM performance with regard to regional
T data is not often accompanied by similarly good
performance with regard to P data, and vice versa,
implying difficulties to identify a generally wellperforming GCM for regional hydro-climatic
change assessment.
GCM performance relative to basin-scale T and P
observations is not increasing for the larger land
areas when compared to the smaller land areas,
implying that model-observation differences may
depend more on actual model bias than on scale
effects.
The ensemble mean of available GCM outputs
provide robust projection of future hydroclimatic changes, rather than a particular GCM
as the driver of hydrological modeling.
A basin-scale, water balance-constrained
approach to quantification of long-term hydroclimatic change dynamics can aid in correcting
model biases and bridging resolution gaps in land
surface representations of climate models, by
more accurately accounting for and quantifying
land-water-use effects, such as those of irrigation,
on water and latent heat fluxes, as well as on
temperature change at the land surface.
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Shilpa Muliyil Asokan
26
Hydro-climatic change in irrigated world regions
ACKNOWLEDGEMENTS
I would like to express my sincere gratitude to my principal supervisor Georgia Destouni for providing me the opportunity to pursue my doctoral research at the department. The scientific-discussions with her have always been filled with valuable insights and in-depth expertise which have incrementally improved my perspective on the subject matter in particular, and research in general. The
supervision that I have received from her throughout the research period has been fundamental for the
completion of this thesis. I am grateful to my co-supervisor, Jerker Jarsjö, for his generous advices and discussions. The thesis has greatly benefited from the valuable scientific discussions and contributions by him.
Thanks are also due to Dr. Dushmanta Dutta for guiding me during the initial stages of my research career.
I take this opportunity to thank my colleagues at the department, collaboration with whom has been
invaluable. I extend my thanks to Yoshihiro Shibuo for introducing me to the world of complex hydrologic
modelling and yet making it appear so simple. Thanks are also due to Carmen Prieto, Amelie Darracq, Claudia Teutschbein, Arvid Bring, Rebecka Törnqvist and many other friends for the long scientific and not-so
scientific discussions along the hallway. Many thanks to Peter Jansson and Helle Skånes for their guidance on
all the scientific and administrative follow-up procedures leading towards the disputation. Thanks to Ingrid
Stjernquist for the comments and suggestions during the internal review of my thesis. A special thanks to
Susanne Ingvander for helping me with the formatting of my thesis. Thanks are also due to Susanna Blåndman and Carina Henriksson for providing complete administrative assistance all throughout. Also, I would
like to thank the reviewers of my manuscripts for providing constructive feedback and insightful comments.
I am thankful for the constant support from my family and friends back home. Special thanks to my dear
parents Muliyil Asokan and Sajini Asokan for always believing in me and supporting my idea of pursuing graduate study in an international university at the first place. I would like to thank my elder sister Greeshma for being
patient with me and guiding me through all life situations. Thanks to my younger sister Theertha, I really enjoyed
the competition we had on who will be the first to have the Dr. degree, well you won, and I am happy for you.
Finally, I would like to thank my husband Abhi for the past decade of togetherness – from my friend to my
life partner to the doting papa of our two year old daughter Trisha. Thank you for all these happening years of friendship, family, travelling and parenting, I thoroughly enjoyed it and am looking forward for many more to come. Our
daughter Trisha joined us two years back, and since then she holds the key to my mood swings, when she smiles I smile,
and when she becomes sad, so do I. Thank you my dear, for you are the most wonderful gift that I have ever received.
FINANCIAL SUPPORT
Work in this thesis has been financially supported by the Swedish International Development Cooperation Agency
(SIDA) and the Swedish Research Council (VR; project number 2006-4366). Work has also been carried out within
the frameworks of the Bert Bolin Centre for Climate Research (supported by a Linnaeus grant from the Swedish research councils VR and Formas) and the strategic environmental research project EkoKlim at Stockholm University.
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Hydro-climatic change in irrigated world regions
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