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A preliminary water balance model for the Tigris and Euphrates River System

Authors:
A Preliminary Water Balance Model for the Tigris and Euphrates River
System
Alan L. Flint
1
, Lorraine E. Flint
1
, Jennifer A. Curtis
2
, and David C. Buesch
3
1
U.S. Geological Survey, Sacramento, CA
2
U.S. Geological Survey, Eureka, CA
3
U.S. Geological Survey, Henderson, NV
Introduction
The Tigris and Euphrates Rivers have made Iraq into the “Breadbasket of the Mideast” and allowed the
development of Sumeria, the world's earliest known civilization (figure 1). Though irrigation canals were
used earlier, an irrigation network including diversion dams and a 70-km aqueduct was in place by 690
B.C. (Krasny and others, 2006). Archaeologists believe that the high point in the development of the
irrigation system occurred about 500 A.D., when a network of irrigation canals permitted widespread
cultivation that made the river basin into a regional granary (Metz, 1988). Successive invasions and
neglect led to the deterioration and partial abandonment of the irrigation and drainage system. Not until
the twentieth century did Iraq make a concerted effort to restore the irrigation and drainage network and
to control seasonal flooding (Metz, 1988). In 2006, about 25 percent of Iraq was irrigated by surface
water (Krasny and others, 2006).
About half of Iraq’s total cultivated area is in the northeastern plains and mountain valleys, where
sufficient rain falls to sustain agriculture via surface and groundwater use. The remainder of the cultivated
land is in the valleys of the Euphrates and Tigris Rivers, which in Iraq receive scant rainfall and rely
instead on irrigation water diverted from the rivers. Both rivers are fed by snowpack and rainfall in
eastern Turkey and in northwest Iran. The rivers' discharge peaks in March and in May, too late for winter
crops and too early for summer crops. The flow of the rivers varies considerably every year. Destructive
flooding, particularly of the Tigris, is not uncommon, and conversely, years of low flow make irrigation
and agriculture difficult.
The majority of the water that flows through the Tigris and Euphrates River basins originates outside the
borders of Iraq. Therefore, the calculation of the water balance of these river systems necessitates an
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understanding of the climate and environmental conditions of the entire system that extends from Turkey
in the headwaters of both rivers, to Syria and Saudi Arabia in the south west, and to Iran where the Karun
flows into the Shatt al Arab near the mouth at the Persian Gulf (figure 2). Although much of the
waterways flowing in Turkey and Syria are dammed, an understanding of the natural, unimpaired water
balance for the extent of the Tigris Euphrates River systems (TERS) serves to provide an understanding
of the long term impacts of climate. This information also provides recognition of recent changes
throughout the system that may highlight locations that are more or less sensitive to changes in climate,
and help to lay a foundation for long term plans for water-resource management.
Climate
Average annual precipitation in the TERS ranges from 50 to over 1,000 mm/year (figure 3), with roughly
90 percent of the annual rainfall occurring between November and April, and most of it in the winter
months from December through March. However, potential evapotranspiration ranges from about 800 to
over 1,400 mm/year (figure 4) and the remaining six months, particularly the hottest ones of June, July,
and August, are very dry. Mean annual minimum air temperatures range from below freezing in the north
and northeast and > 15° C in the southern desert (figure 5). Mean minimum air temperatures in the winter
range from near freezing in the northern and northeastern foothills and the western desert to 2-3° C and 4-
5° C in the alluvial plains of southern Iraq. They rise to a mean annual maximum of 3-10° C in the
mountainous north and northeast to over 30° C in the southern deserts (figure 5). In the summer mean
minimum temperatures range from about 22° C to about 29° C and rise to maximums of over 40
o
C.
Temperatures sometimes fall below freezing and have fallen as low as -14.4° C in the western desert.
They are more likely, however, to go over 46° C in the summer months, and several stations have records
of over 48° C (Hijmans and others, 2005).
Low precipitation and extreme heat makes much of Iraq a desert. Because of very high rates of
evapotranspiration, soil and plants rapidly lose the little moisture obtained from the rain, and agricultural
crops could not survive without extensive irrigation. In contrast, higher precipitation in the Zagros
Mountains in northeastern Iraq provides permanent vegetation, such as oak trees, and date palms are
found in the southern regions.
Snowfall plays a large part in maintaining flows that can extend into the dry season and provide irrigation
and drinking water in the summer. Snowmelt helps to create conditions conducive to recharge into the
subsurface where less water is lost to evapotranspiration. The majority of snow that feeds runoff and
recharge in the TERS occurs in the mountains of Turkey and Iran, although there is a portion that
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provides some runoff to the headwaters of the Tigris in northern Iraq (figure 6). The presence of snow and
the resulting timing and patterns of snowmelt is controlled by air temperature, and thus is very sensitive
to changes in air temperature. As a result snow accumulation and melt processes tend to amplify the
effects of changing climate that are dominated by increases in air temperature and often accompanied by
decreases in precipitation. These effects are manifested by less snow accumulation and earlier springtime
snowmelt.
StudyArea
The study area is 1,035,000 km
2
and covers portions of Turkey, Iran, Iraq, Syria, and Saudi Arabia (with a
minor section in Jordan) (figures 1 and 2). The desert zone, an area lying west and southwest of the
Euphrates River, is a part of the Arabian Desert, which covers sections of Syria, Jordan, and Saudi
Arabia. The region consists of a wide, stony plain interspersed with rare sandy stretches. A widely
ramified pattern of wadis--watercourses that are dry most of the year--runs from the Syrian border to the
Euphrates. Some wadis are over 400 kilometers long and carry brief but torrential floods during the
winter rains.
The uplands region, between the Tigris north of Samarra and the Euphrates north of Hit, is known as Al
Jazirah (the island) and is part of a larger area that extends westward into Syria between the two rivers
and into Turkey. Water in the area flows in deeply cut valleys, and irrigation is much more difficult than
it is in the lower plain. Much of this zone is classified as desert.
The northeastern highlands begin just south of a line drawn from Mosul to Kirkuk and extend to the
borders with Turkey and Iran. High ground, separated by broad, undulating steppes, gives way to
mountains ranging from 1,000 to nearly 4,000 meters near the Iranian and Turkish borders. The alluvial
plain begins north of Baghdad and extends to the Persian Gulf. Here the Tigris and Euphrates Rivers lie
above the level of the plain in many places, and the whole area is a delta interlaced by the channels of the
two rivers and by irrigation canals. Intermittent lakes, fed by the rivers in flood, also characterize
southeastern Iraq. A fairly large area (15,000 square kilometers) just above the confluence of the two
rivers at Qurnah and extending east of the Tigris beyond the Iranian border is marshland, the result of
centuries of flooding and inadequate drainage. Although much of the marshland has been drained or has
diminished as a result of drought, there are still large areas of permanent marsh, with additional areas
becoming marshland only in years of great flooding.
Page 3 of 44
The Euphrates originates in Turkey, is augmented by the Nahr River in Syria, and enters Iraq in the
northwest. Here it is fed only by the wadis of the western desert during the winter rains. It then winds
through a gorge, which varies from two to sixteen kilometers in width, until it flows out on the plain at
Ramadi, where it flows to join the Tigris at Qurnah.
The Tigris also originates in Turkey but is significantly augmented by several rivers in Iraq, all of which
join the Tigris above Baghdad, and the Diyala, which joins it below the city. Both the Tigris and the
Euphrates break into a number of channels in the marshland area, and the flow of the rivers is
substantially reduced by the time they come together at Qurnah. Moreover, the marshes act as silt traps,
and the Shatt al Arab is relatively silt free as it flows south. Below Basra, however, the Karun River
enters the Shatt al Arab from Iran, carrying large quantities of silt.
Methods
Application of the Basin Characterization Model
Watershed hydrology in the TERS drainages is the result of interactions between precipitation,
evapotranspiration, surface water runoff, channel infiltration, and areally distributed infiltration, including
direct recharge or groundwater interaction with rivers and lakes. Runoff, recharge, and changes in soil
moisture conditions can be estimated using a simple monthly water balance approach. The Basin
Characterization Model (BCM) is a physically-based model that calculates water balance fractions based
on data inputs for topography, soil properties and depth, underlying bedrock geology, and spatially-
distributed values (measured or estimated) of air temperature and precipitation (Flint and Flint 2007a, b).
The BCM calculates recharge and runoff monthly (figure 7) using a mathematical deterministic water-
balance approach based on the distribution of precipitation and the estimation of potential
evapotranspiration (Flint and Flint 2007a, b). The BCM relies on a rigorous hourly energy balance
calculation using topographic shading and applies available spatial maps of elevation, bedrock
permeability estimated from geology, soil water storage from soil databases, and precipitation and air
temperature maps. The BCM can be used to identify locations and climatic conditions that generate
excess water, quantifying the amount of water available either as runoff or as in-place recharge on a
monthly basis.
Page 4 of 44
The BCM has been calibrated regionally in the southwest United States, with climate very similar to the
Middle East. Regional calibration compares simulated solar radiation and potential evapotranspiration to
measured values, and simulated snow cover to MODIS snow cover data (Flint and Flint 2007b). Locally
the model is calibrated to measured unimpaired streamflow data. The determination of whether excess
water becomes recharge or runoff is governed in part by the underlying bedrock permeability. In locations
with limited soil water storage, the higher the bedrock permeability, the higher the recharge and the lower
the runoff generated for a given grid cell. In small gaged basins that generate unimpaired flows, the
bedrock permeability can be adjusted to calculate a total basin discharge that matches the measured basin
discharge. In the TERS, four stream gages with unimpaired flows were available (figure 2; table 1) and
were used for model calibration. Properties adjusted during calibration were correspondingly distributed
throughout the study area of the TERS and spatially distributed estimates of recharge and runoff were
calculated for 50 years of available climate records, 1949-1999.
Temperature and precipitation are two primary drivers of physical processes acting at the watershed scale.
BCM hydrologic variables sensitive to temperature include potential evapotranspiration (PET) and actual
evapotranspiration (AET). BCM variables sensitive to quantities of precipitation include runoff and
recharge.
ModelDomain
The study area defines the limits of the model domain (figure 2) and is bounded by the topographic
surface hydrology of the Tigris and Euphrates River system. As a result, all input parameters must be
developed for this domain. Map inputs are all developed to correspond to the 180-m spatial resolution of
the digital elevation model.
DevelopmentofInputParametersUsedintheWaterBalanceModel
Climate
Page 5 of 44
Recharge and runoff are non-linearly related to precipitation and snow accumulation and melt (Flint, and
others, 2004; Flint and Flint, 2007b). Therefore transient climate data are required for developing an
understanding of that relation and developing an estimate of long term recharge and runoff for the region.
Global climate data is available from several sources on the web in gridded format in various spatial and
temporal resolutions. The following data was used for this study.
Precipitation,minimumandmaximumairtemperature
Steady-state data from WorldClim (http://worldclim.org/
; Hijmans and others, 2005) is a global climate
set of monthly grids and is readily available via the web. The data layers are generated through
interpolation of average monthly climate data from weather stations on a 30 arc-second resolution grid (1-
km), on the basis of major climate databases. Average monthly data is available for precipitation, and
minimum and maximum air temperature. Although these data are steady-state they are at a fine-scale
spatial resolution and were found to be useful for correcting the coarse scale data described below.
Transient precipitation and air temperature data was available through the Climatic Research Unit (CRU)
and the Tyndall Centre for Climate Change Research (http://www.cru.uea.ac.uk/cru/data/hrg/
) of the
University of East Anglia, Norwich, U.K. The data used were CRU TS 2.1, with a spatial resolution of
0.5 degrees (51.6 km, Mitchell and Jones, 2005). Transient monthly data is available for precipitation, and
minimum and maximum air temperature from 1901 to 2000.
These climate data sets are too coarse a resolution to be used directly in the BCM and therefore required
downscaling to the 180-m spatial resolution for the model domain. Downscaling refers to the calculation
of fine-scale information on the basis of coarser-scale information using various methods of statistical and
spatial interpolation. Spatial downscaling was performed on the coarse resolution grids (1-km and 51.6-
km) to produce fine resolution grids (180-m) using a model developed by Nalder and Wein (1998)
modified with a “nugget effect” specified as the length of the coarse resolution grid (Flint and Flint, in
review).
This technique combines a spatial Gradient and Inverse Distance Squared (GIDS) weighting to monthly
point data using multiple regressions that are calculated for every grid cell for every month. Using the
coarse-scale resolution digital elevation model (1-km or 51.6-km), parameter weighting is based on the
location and elevation of the new fine resolution grid relative to existing coarse resolution grid cells (in
this example we start with the WorldClim data) using the following equation:
Page 6 of 44
(1)
where Z is the estimated climatic variable at a specific location defined by easting (X) and northing (Y)
coordinates, and elevation (E) respectively; Z
i
is the climate variable from the 1-km grid cell i; X
i
, Y
i
, E
i
are easting and northing coordinates and elevation of 1-km grid cell i; N is number of 1-km grid cells in a
specified search radius; C
x
, C
y
, C
e
are regression coefficients for easting, northing, and elevation; D
i
is
distance from the 180-m site to 1-km grid cell i and is specified to be equal to or greater than 1-km (the
nugget) so that the regional trend of the climatic variable with northing, easting, and elevation within the
search radius does not cause the estimate to interpolate between the closest 1-km grid cells, which causes
a bull’s-eye effect around any 180-m fine resolution grid cell that is closely associated or co-located in
space with an original 1-km grid cell. This 180-m gridded data for average monthly precipitation and air
temperature are the baseline data used to correct the transient coarse scale data from the CRU data base.
The CRU data was downscaled in stages to reduce the bull’s-eye effect of GIDS downscaling. The 51.6-
km data was downscaled to 20-km, then those grids were downscaled to 5-km, then 1-km then 180-m.
Resultant grids were smoothly blended into the 180-m grid and still maintained the spatial and elevational
trends of the original coarse-scale data. These transient data were averaged in monthly values to develop a
simple ratio between the CRU data and the originally finer scale WorldClim data. Once the ratio was
developed for each month, it was multiplied across the transient monthly grids to “correct” those grids so
that the long term average would exactly match the more data intensive high resolution WorldClim data
that had been downscaled to 180-m .
To illustrate fine-scale patterns in historical changes in climate, we analyzed average annual values and
the magnitude and direction of observed changes in climate and hydrology over the last century using the
downscaled climate maps by applying a regression through annual averages for every grid cell to
calculate the slope (rate of change) over the 50-yr time period.
PotentialEvapotranspiration
Grids of potential evapotranspiration (PET) were available via the PET Early Warning and Environmental
Monitoring Program of the USGS (http://earlywarning.usgs.gov/fews/middleeast/index.php
) that
endeavors to operate at national, regional, and international scales to support investigations in the areas of
climate change, natural resource management, environmental change detection, food security monitoring,
water resource assessments, and hazard identification/mitigation. The Middle East Data Portal provides
data via the Famine Early Warning Systems Network for the Iraq/Tigris-Euphrates region.
N
i
i
N
i
i
eiyixii
dd
CEECYYCXXZ
Z
1
2
1
2
1
/
)()()(
Page 7 of 44
The daily global PET is calculated from climate parameter data that is extracted from Global Data
Assimilation System (GDAS-PET) analysis fields. The GDAS data are generated every 6 hours by the
National Oceanic and Atmospheric Administration (NOAA). The GDAS fields used as input to the PET
calculation include air temperature, atmospheric pressure, wind speed, relative humidity, and solar
radiation (long wave, short wave, outgoing and incoming). PET is computed for each 6-hour period and
then summed to obtain daily totals. A day is defined as beginning at 00 hours GMT.
The daily PET is calculated on a spatial basis using the Penman-Monteith equation (the formulation of
Shuttleworth (1992) for reference crop evaporation is used). These equations were standardized in
accordance with the FAO publication 56 for the 6-hourly calculations (Allen and others, 1998). The PET
data have a 1 degree ground resolution (63-km) and are global in spatial extent. The transient monthly
GDAS-PET data grids were available from 1948-2006. A USGS fine scale PET (Fine-PET) model (Flint
and Flint, 2007a) was used to model clear sky steady-state monthly PET using the 180-m WorldClim
temperature data and the 180-m DEM for the study area. This provides the fine scale influence of slope,
aspect, and influence of the surrounding mountainous terrain on blocking direct beam solar radiation and
diffuse radiation. The resulting average monthly Fine-PET grids were upscaled to match the average
monthly GDAS-PET grids (63-km). The ratio of average monthly Fine-PET to the transient monthly
GDAS-PET was calculated at the 63-km grid scale. Those grids were then downscaled in steps (similar
to the precipitation) to 180-m grid resolution. The fine scale ratio of Fine-PET to GDS-PET was then
multiplied by the average monthly Fine-PET grids. This approach honors the transient nature of the
GDAS-PET data, which accounts for the transient climate (temperature, solar radiation, and cloudiness)
but also redistributes that data over the landscape to correctly account for slope, aspect, and blocking
ridges.
Geology
The purpose of compiling geologic information for application to the BCM is to estimate the saturated
hydraulic conductivity (Ksat) of the surficial bedrock underlying soils. This attribute is scaled during the
calibration process to partition the relative volume of water that either becomes runoff or recharge to
match streamflow data in unimpaired basins, and the resulting Ksat values are used throughout the model
domain. Whereas detailed geologic information was available for Iraq, the corresponding detail for the
surrounding countries of Turkey, Iran, and Syria were scant, and general extrapolation on the basis of
geologic age and proximity to known geology were used.
Page 8 of 44
BedrockGeology
A total of 144 formations for the country of Iraq that range in age from Paleozoic to Pliocene and
lithologic features in Quaternary deposits were compiled from various reports or maps (Wayne Belcher,
USGS, written commun., 2010). Only 87 formations or features are displayed on the 1:1,000,000 scale
geologic map compiled by the Geological Survey of Iraq (GEOSURV, 2000) and documented in an
accompanying ArcGIS file, however, some of the map units consist of groups of two or more formations.
There is a wide range in types of hydrogeologic data described for formations and lithologic features that
includes porosity, permeability, hydraulic conductivity, transmissivity, storage coefficient, yield, specific
capacity, spring discharge, borehole discharge, groundwater recharge, and the estimated percentage of
rainfall that becomes recharge (Jassim and Al-Gailani, 2006; Krasny and others, 2006). The amounts of
each type of data are quite varied. Properties such as porosity, permeability, hydraulic conductivity, and
transmissivity are preferred for inferring Ksat; however, the other properties were examined to establish
equivalency or relative relations between units with different types of data. Of the map units that are also
described in Jassim and Goff (2006), 24 map units have quantitative values for hydrogeologic properties,
17 map units have only qualitative values (such as “low” or “high”, etc.), and 13 map units have both
quantitative and qualitative values.
SaturatedHydraulicConductivityofBedrock
In this text Ksat refers to the estimate of saturated hydraulic conductivity of the surficial bedrock
underlying soils, and is generally lower than deep bedrock due to infilling of materials in fractures,
carbonate deposits and other surficial deposits. This parameter can be approximated on the basis of
several approaches. Measured hydraulic conductivity values, the most relevant to Ksat, were the least
abundant of quantitative values. Most measured hydraulic conductivity values are assumed to be for
lateral flow in the subsurface; however, there are a few values from some of the Quaternary lithologic
features that have both vertical and lateral hydraulic conductivity values. For these detailed studies,
horizontal values are typically 5 to 9 times as large as the vertical values; therefore, most of the values
cited in Krasny and others (2006) might be an order of magnitude greater than what is appropriate for
near-surface Ksat estimates. Initial estimates of Ksat were made on the basis of this information.
Quantitative hydraulic conductivity values are considered the primary data; however, four other types of
hydraulic conductivity values are used in this compilation; (1) hydraulic conductivity calculated from
intrinsic permeability, (2) hydraulic conductivity calculated from transmissivity, (3) estimated hydraulic
conductivity used for qualitative values, and (4) estimated hydraulic conductivity based on
lithostratigraphic similarities.
Page 9 of 44
The calculation of hydraulic conductivity from permeability was based on the relation presented in Freeze
and Cherry (1979, p. 27). The calculation of hydraulic conductivity from transmissivity was based on a
relation for a confined aquifer that includes the thickness of the unit (Freeze and Cherry, 1979, p. 59). The
thickness values used in the calculations are from specific chapters in the Geology of Iraq (Jassim and
Goff, 2006). Usually, the thickness of the "type section" was used; alternatively, a typical thickness (if
described) was used.
Estimated hydraulic conductivity values used for qualitative values (such as very low, low, medium, high,
and wide range) were based on generalizations of statistical summaries of various lithostratigraphic
characteristics in similar formations and lithologic features. Hydraulic conductivity values for many
formations and lithologic features were estimated based on lithostratigraphic similarities. The only
measured hydraulic conductivity values were from the Quaternary deposits; however most lithologic
types have at least some hydraulic conductivity values based on calculations from intrinsic permeability
or transmissivity.
A series of digital bedrock geology maps (Pollastro and others, 1999a; Pollastro and others, 1999b; and
Pawlewicz and others, 2003) were merged with the GEOSURV map of Iraq to develop the geologic map
of the TERS study area. Because no specific information on lithologic properties was available for areas
outside of Iraq, Ksat was extrapolated throughout Turkey (Pawlewicz and others, 2003) and the Arabian
Peninsula and Iran (Pollastro, 1999a; Pollastro and others, 1999b) on the basis of generalized geologic
descriptions and specific lithologic types. In general, measured, calculated, and estimated hydraulic
conductivities are consistent with the ranges of values reported in Bear (1972) and Freeze and Cherry
(1979).
Estimates of hydraulic conductivity are provided in Table 2. These values are likely much higher than the
Ksat, however, the hydraulic conductivity estimates provide the relative magnitudes among the units, that
when adjusted during calibration, maintains a semblance of the relative magnitudes for a reasonable
spatial distribution. The lack of unimpaired streamflow data in basins representing all of the geologic
types introduces uncertainty into the model results that is reduced by the rigor with which the original
hydraulic conductivity numbers were established. The calibrated values of Ksat are shown for the
lithologic units in table 2. They are spatially distributed according to the lithologic descriptions and
illustrated in figure 8.
Page 10 of 44
Soils
A compilation of regional and national soils data presented in the Harmonized World Soil Database V1.1
(FAO/IIASA/ISRIC/ISSCAS/JRC, 2009) was used to derive soil physical properties for the TERS model
domain. The Harmonized World Soil Database (HWSD) consists of a 30 arc-second (~1 km) raster image
and an attribute database in Microsoft Access 2003 format and provides standardized soil parameters for
both topsoil (0 to 30 cm) and subsoil units (30 to 100 cm). Within the HWSD the GIS raster image file is
linked to the attribute database using the harmonized soil mapping unit. Each soil mapping unit consists
of one or more soils identified by a unique database identifier and the percentage of each mapping unit
occupied by a given soil is provided.
DevelopmentofSoilHydraulicPropertiesandDepth
The HWSD raster image was clipped to the study area boundary, a list of study area soil mapping units
created, and a database query performed to extract textural and bulk density data for each soil mapping
unit. The query generated a table of data for each soil mapping unit that included the soil identifier,
percent of mapping unit occupied by each soil, soil depth, and textural and bulk density data for both the
topsoil and subsoil. Weighted average calculations addressed spatial variations of soil properties within
each mapping unit and enabled derivation of representative textural and bulk density values for the entire
soil mapping unit profile. The weighted average textural estimates for each mapping unit were then used
to estimate soil hydraulic properties using Rosetta V1.0 (Schaap and others, 2001), a software program
that utilizes a pedotransfer function method and surrogate soil textural (percent sand, silt and clay) and
bulk density data to estimate water retention parameters according to van Genuchten (1980). Outputs
from Rosetta (residual water content, saturated water content, and van Genuchten curve fit parameters,
and n) were used to estimate weighted average field capacity (water content at 0.03 MPa) and
permanent wilting point (water content at 1.5 MPa) for each mapping unit. Weighted average bulk density
estimates were used to estimate porosity for each soil mapping unit assuming a particle density of 2.65
Mg/m
3
.
Soil depth was also required to calculate the water balance within the study area, however, soil
descriptions within the HWSD database were limited to 1-meter deep profiles. Deep soils and
unconsolidated alluvial units exist throughout the study area, thus accurate depiction of soil water storage
required additional analysis of soil and alluvial thicknesses. Using the geologic map of the study area
Page 11 of 44
described above, Quaternary alluvial units were identified and the database queried to create a map of
alluvial units which was then used to identify soil mapping units underlain by Quaternary sediments.
The study area was separated into four geomorphic providences: Desert Steppe, Mesopotamian Plain,
Foothills, and Mountainous Regions (figure 8) based on average annual precipitation (figure 3) and
topographic relief (figure 1) (Lees and Falcon, 1952; Buringh, 1960; Adnan and others, 2006; Krasny and
others, 2006). There is a strong precipitation gradient across the study area with average annual
precipitation of less than 50 mm/yr in the southern deserts to more than 1,000 mm/yr in the northern
mountains. The Desert Steppe and Mesopotamian Plain receive significantly less precipitation than the
Foothills and Mountainous Regions. The Desert Steppe is characterized by minimal vegetation thereby
enabling wind and water to erode and deflate alluvial surfaces resulting in shallow soils; however thick
aeolian units (35-m high dunes) are common in the Arabian Desert located in the southwestern portion of
the study area. The Mesopotamian Plain and Desert Steppe providences are separated by the Euphrates
Boundary Fault and alluvial thicknesses within the Mesopotamian Plain are further influenced by tectonic
subsidence. Within the Mesopotamian Plain alluvial thicknesses progressively increase eastward of the
boundary fault until the Foothills Region is reached where thick alluvial fans form at the base of the
Mountainous Region. The transition from foothills to mountains is characterized by a significant increase
in topographic relief. Soils in this region are typically shallow and deep alluvial units are limited to
mountain valleys.
The next step in developing the soil depth for each mapping unit was based on geomorphic providence, an
isopach map of alluvial thickness (Figure 15.2;
Adnan and others, 2006), parent material, and soil
profile depths from the HWSD database. If the mapping unit was within the Mesopotamian Plain or the
Arabian Desert and the assigned parent material from the bedrock geology map was Quaternary alluvium,
a soil depth of 6 meters was assigned. Previous studies of infiltration in desert environments (Flint and
Flint, 2007a) indicate 6 meters is a reasonable assumption for the maximum penetration depth of the
wetting front and thus represents a limiting infiltration condition. All other mapping unit soil depths were
estimated using a weighted average calculation. The table of properties for each mapping unit, generated
during the original HWSD database query, shows that many of the mapping units were composed of a
percentage of shallow soils. A weighted average calculation was performed for mapping units with
shallow soils. For example, if the soil depth for 40 percent of a mapping unit was 0.1 meters and the soil
depth for the remaining 60 percent was 1 meter, the estimated soil depth for the mapping unit was 0.68 m.
Page 12 of 44
The final step in producing more discrete spatial resolution for this relatively coarse representation of soil
depth was to use the general relation of soil depth to slope that is reflected in mountainous regions and
described above in general terms. In the mountainous regions of the model domain it was assumed that
the soil was shallower when the slopes were greater. To develop a revised soil thickness map using the
180-m elevation grid, a calculation was made that assumed that if the percent slope was greater than 35
percent the estimated soil thickness was multiplied by 0.4. If the slope was less than 35 percent but
greater than 15 percent, the soil thickness was multiplied by 0.6. This final soil depth map is shown in
figure 9 and illustrates the finer resolution in depth in the mountainous regions, deeper soils in the alluvial
plain, especially in the areas around the Tigris and Euphrates Rivers.
After estimating field capacity, permanent wilting point, porosity and soil depth for each mapping unit
these parameters were incorporated into the attribute table of the HWSD raster image. From this
attributed raster image a series of grid files with a 180-m cell size were generated using ArcGIS.
ModelCalibration
The BCM calculates the water balance in a series of steps. (1) The precipitation is determined to be rain
or snow depending on air temperature. (2) Rain is added to the soil directly and snow is added directly or
to the previous month’s snowpack. (3) If a snow pack exists then snow loss is calculated as sublimation
or snowmelt, again depending on temperature. (4) Rain or snowmelt then fills the available storage in the
soil profile followed by removal of PET. (5) If the total amount of water in the soil profile exceeds the
soil storage the excess water will become runoff. If the total amount of water in the soil profile is less than
the soil storage but greater than field capacity it will be become recharge at a rate equivalent to the bulk
bedrock permeability. (6) Any water remaining above field capacity is added to the runoff. (7) The soil
water at or below field capacity is carried into the next month as soil water storage. To calibrate the model
to measured streamflow all runoff and recharge upstream of a gage is summed and compared to the
measured data. The calculated runoff is always routed to the gage and a proportion of recharge is added to
the runoff as baseflow. Recharge then re-emerges into the river system as baseflow, and determining the
proportion of recharge the re-emerges is part of the calibration process.
Calibrationdata
On the basis of analyses conducted by Saleh (2010) it was determined that four streamflow gages were
available that were considered unimpaired, with no diversions or downstream dams, thus reflecting
appropriate conditions for comparison to the BCM estimates of basin runoff. These gages are shown in
table 1 with their locations, periods of record, elevation, and catchment area, and figures 2 and 8. Two
Page 13 of 44
gages were located in large basins at the headwaters of the Euphrates River in Turkey, and two were in
smaller basins in the headwaters of the Tigris River at the northern Iraq border with Turkey.
Calibrationprocess
Calibration of the BCM is the iterative process of changing the Ksat to alter the proportion of water that
becomes either runoff or recharge to better match streamflow. Ksat of the bedrock is increased to increase
recharge and reduce runoff. Because the BCM is run at a monthly timestep, a recession function was
added to the calibration procedure to allow for a better estimate of the fit. This is an exponent of between
0.8 and 0.92 that is added to the cumulative recharge value that results in a representation of baseflow to
which runoff is added. Calibration results are illustrated in Figure 9 for each of the four gages. Given the
uncertainties in the various components of the input parameters, (climate, geology, and soils data), the
simulated volumes provide a reasonable match to the measured data for these four basins, with slight
underestimates of peaks in the large basins in Turkey and slight overestimates of peaks in the smaller
basins in Iraq.
ResultsandDiscussion
The BCM was run for 1949-1999, the period of record with the most complete climatic records. Results
are shown for monthly trends, annual time series, and average annual spatially distributed maps. Also
included are volume estimates of recharge and runoff for all subbasins in the study area.
Regionalwaterbalanceresults
Monthly trends of climate and water balance parameters averaged for the entire study domain are shown
in figure 11. Average annual air temperature follows the general Mediterranean climate with cold winters
and hot summers (figure 11a). Maximum monthly air temperatures are about 10 to 18 degrees C higher
than minimum monthly air temperatures, with the largest range in midsummer. The percentage of the
total water balance that is represented for each month by snowfall, actual evapotranspiration, runoff, and
recharge (figure 11b) shows that precipitation is the largest component in the winter, whereas
evapotranspiration is the largest in the summer. Snowfall is present as a component from October through
April, with the highest percentage in January, and recharge and runoff follow with a month lag. Recharge
is larger than runoff for all months with the largest percentage in April. These trends follow similar
patterns to many locations in the United States, particularly in California where the areas dominated by
Page 14 of 44
snowfall and springtime snowmelt result in runoff and recharge, with the desert regions having small
components of both runoff and recharge.
Average annual recharge is spatially distributed in figure 12, and supports the interpretation that recharge
is located in regions with higher precipitation and particularly in areas with snowfall. Runoff shows
similar patterns (figure 13) but is in less magnitude than recharge. These results are converted to volume,
in millions of cubic meters per subbasin, in figures 14 and 15, providing a picture of the relative amounts
of precipitation and resulting recharge and runoff in the TERS study area. Again, the majority of the
precipitation is located in the mountains, particularly in the Tigris River basin, and while the majority of
the recharge is in the headwaters of the Tigris, Euphrates, and Karun River basins, most is in the Tigris
River basin. Runoff occurs predominantly in the headwaters of the Tigris, as well. Although precipitation
occurs throughout the TERS with some snowfall occurring within about two-thirds of the area, because of
the high evapotranspiration rates throughout the desert regions little to no recharge or runoff occurs in
about half of the study area.
Average annual values of the water balance components are shown for the Tigris and Euphrates River
basins as well as for each country within the TERS in table 3. To illustrate that the estimates in table 3 are
within reasonable bounds, in the absence of reliable estimates of recharge, a comparison is made to an
estimate of safe yield. Krasny and others (2006) estimate safe yield for the country of Iraq to be
approximately 12,600 million cubic meters. Estimated recharge from the BCM was 7,000 million cubic
meters and stream flow was 6,400 million cubic meters (table 3). Additional runoff generated from other
countries was approximately 14,000 cubic meters. If 15 percent of the runoff from the Tigris and
Euphrates Rivers becomes recharge to the groundwater system in Iraq (15 percent was used in the Great
Basin according to Flint and Flint, 2007b), an additional 3,000 million cubic meters of recharge is added
to the 7,000 for a total of 10,000 million cubic meters. In addition, it is likely that recharge in the
mountains north and east of Iraq will contribute to groundwater recharge in Iraq through subsurface flow
that would increase the estimate of recharge well above the 10,000 million cubic meters. This amount
exceeds that of the estimate of safe yield by Krasny and others (2006), and it is recognized that the two
properties are not equivalent, safe yield should be a percentage of recharge.
The majority of precipitation falls in the Tigris River basin, over twice that of the Euphrates River basin,
yet the Euphrates has the most loss to potential evapotranspiration. The Tigris River basin also receives
the most snowfall, and results in about 30 percent more recharge and 3 times more runoff than the
Euphrates. The majority of the precipitation and resulting recharge and runoff are in Turkey. More
Page 15 of 44
precipitation falls in Iraq than in Syria, Iran, or Saudi Arabia, and more results in runoff, although less of
it results in recharge than in Iran. Within the TERS, Saudi Arabia has little precipitation and no recharge
or runoff.
Changing climate in the Tigris Euphrates River System
Future projections of climate in the Middle East are extremely variable. Simulating the climate of the
region is a challenge for climate models, due in part to the high natural inter-annual variability, the
topography of the region - which includes multiple mountain ranges and inland seas (Hemming and
others, 2010; Evans, 2009). Recent projections from the Intergovernmental Panel on Climate Change
(IPCC) raised fears that storm activity in the eastern Mediterranean would decline this century if global
warming continues on present trends. In turn, that would have reduced rainfall by between 15 and 25 per
cent over a large part of the land encompassing parts of Turkey, Syria, northern Iraq, and north-eastern
Iran and the strategically important headwaters of the Tigris and Euphrates rivers. However, the IPCC
report compared model results from 12 different models using one emission scenario and found that for
much of Iraq, less than two-thirds of the models agreed whether more or less precipitation would occur.
Recent research done by the University of New South Wales Climate Change Research Centre (Evans,
2009) suggests that these projections would result in significant challenges to the region’s agricultural
base, with a longer dry season and changes in the timing of maximum rainfall. However, the researcher
notes that the IPCC projections were based on the results of global modeling of climate change, which
tends to obscure smaller-scale regional effects. As a follow up study, Evans used regional climate
modeling specific to the Middle East, with results that suggest, despite declines in storm activity, that
moisture-bearing winds would be channeled inland more often and diverted by the Zagros Mountains,
bringing an increase of over 50 percent in annual rainfall to the Euphrates-Tigris watershed (Evans and
Smith, 2010). With these widely ranging projections and interpretations that depict future Middle Eastern
climatic conditions, the use of currently measured conditions and trends serves to lay a foundation for
forecasting ongoing changes in climate and hydrology.
Changes in climate are ongoing worldwide and evidence suggests that climate changes in the Middle East
over the last several decades may have been a result of global warming. To illustrate some slight changes
in the climate and resulting recharge and runoff, the water balance results are illustrated as annual time
series for 1949-1999 for both the Tigris and Euphrates River basins (figures 16 and 17). A slight
downward trend is apparent in precipitation for both basins (figure 16a), while slight increases can be
seen in potential evapotranspiration (figure 16b) and air temperature (figure 16c). These are translated
Page 16 of 44
into a larger decrease in snowfall over the 50 year period (figure 17a), and a less noticeable decline in
recharge and runoff (figure 17 b and c). More significant trends can be seen over the last 30 years.
The 50-year time period for which these analyses were done encompasses the time frames within which
large scale climatic cycles occur, most notably the North Atlantic Oscillation (NAO), a dominant mode of
Atlantic sector climate variability, and the Arctic Oscillation, both of which generally vary on decadal
time scales. Positive phases of these indices bring drier conditions to the Middle East, while negative
phases are generally wetter. Generally, since the end of the 1980s, both indices have been systematically
positive, coinciding with relatively warm conditions (Cullen and others, 2002). Interannual to decadal
changes in December through March precipitation and streamflow in the eastern Mediterranean are tied to
the NAO (Cullen and others, 2002; Eshel and Farrell, 2000). Over the past several decades, the NAO
index has steadily strengthened, rising from its low index state in the 1960s to a historic maximum in the
1990s. This trend accounts for a significant portion of the winter temperature increase over Eurasia
(Hurrell and Van Loon, 1997; Hurrell and others, 2001).
This trend is apparent in the temperature and evapotranspiration data shown in figures 16 b and c, and the
decline of BCM-simulated recharge and runoff throughout the 90s (figure 17 b and c). Additionally, links
have been established between changes in Middle Eastern water supply associated with natural variations
in the climate system and sea surface temperature variations in the Atlantic Ocean and eastern
Mediterranean Sea. These links suggest that if the NAO, influenced by increased greenhouse gases,
continues its upward trend, then future amounts of December through March precipitation and streamflow
can be expected to be lower (Cullen and others, 2002).
The spatial variation in how the water balance changes over time within a region may indicate locations
that are more or less sensitive to changes in climate, for reasons such as topographic influences on climate
resulting in localized refugia, or regional influences on climatic patterns, or elevational gradients. An
analysis was done of climatic data that evaluated the trend in climate and hydrology over the 50-yr period
1949-1999 by developing regressions of 50 yearly values for every 180-m gridcell, resulting in the
spatially distributed change in the value over the time period. This is shown for snowfall, encompassing
most of the changes in precipitation and air temperature, in figure 18. This illustrates an increase over the
50-yr period at the highest elevations in the TERS in Turkey, at the headwaters of both the Tigris and
Euphrates rivers. All other locations have declined in snowfall. Corresponding changes in recharge for
this period are shown in figure 19 and illustrate the differences in recharge in higher elevation areas that
have snow from those that do not. There is evidence in regions with warm snowpack that the highest
Page 17 of 44
elevation locations may be receiving increases in moisture with warming climates that are being
translated into increases in snow at elevations that are still below freezing in the winter. As a result, and
despite the increases in potential evapotranspiration, there are increases in recharge in these regions. This
is more pronounced in the Euphrates River basin than the Tigris, however, whereas the increases in runoff
that have occurred over the 50-yr period are centered over the location with increases in snowfall. There
are also differences in northern Iraq where recharge has been increasing and runoff has been declining, as
well as in the Karun River basin. The change in snowfall and subsequent springtime snowmelt causes
changes in the timing of runoff, and rain on snow events that cause increases in peak flows. Decreases in
snowpack, such as in the northwestern portion of the Euphrates River basin, may provide the opportunity
for recharge to occur during the winter when evapotranspiration is low, whereas runoff occurs more
predominantly as a function of snowmelt.
SummaryandConclusions
To support and encourage economic development and stability in Iraq, scientists with the U.S. Geological
Survey are providing information, expertise, and technological assistance in regard to Iraq's water
resources, and creating the necessary infrastructure to enable easy access and sharing of national
geospatial data. As part of this endeavor, the unimpaired flows in the Tigris and Euphrates Rivers have
been assessed using regional water balance modeling to provide an understanding of the historical
hydrologic conditions, how they are currently changing, and to provide the basis for evaluating the effects
of upstream development on Iraq’s current and projected surface water supplies.
Regional water balance modeling was applied to the Tigris Euphrates River system, necessitating the
development and downscaling of mostly global datasets for this data poor region. Transient climate data
obtained from coarse scale CRU datasets, interpolated and scaled to fine scale monthly average
WorldClim patterns, were downscaled further for model application at 180-m spatial resolution. Very
coarsely mapped soils data was further developed to reflect fine scale geomorphic and topographic
features. Geologic maps of the region were combined and interpreted to provide a starting point for model
calibration. The model, calibrated to four available unimpaired streamflow records, was then applied to
the region to establish a monthly hydrologic record for 1949-1999.
Results of the Basin Characterization Model for 1949-1999 illustrate the importance of snowfall to
recharge and runoff in the TERS, with the majority of recharge and runoff in the mountainous regions
Page 18 of 44
where snow occurs. The decline of snowfall over the 50-yr period is apparent, but these preliminary
results suggest inconclusively that runoff is being impacted more by the decline in snowfall than in
recharge.
The Tigris River basin receives the majority of precipitation and the least potential evapotranspiration,
resulting in 30 percent more recharge and three times more runoff. Although a more rigorous analysis that
includes the last 10 years of record (1999-2009) is warranted, climate changes over the past few decades
are translating into slight changes in hydrology. These are illustrated as declines in precipitation and
increases in potential evapotranspiration and air temperature, resulting n decreases in snow. These trends
are more obvious since the late 1980s. The spatial distribution of how the water balance has changed over
the 50-yr period illustrates that although snowfall has declined over the region, locations with the highest
elevations have had increases in snow and thus increases in recharge and runoff. These trends have
implications for shorter term management considerations.
Page 19 of 44
References
Adnan, A., Domas, J., and Jassim, S.Z., 2006, Quaternary Deposits: Chapter 15 in Geology of Iraq, S. Z.
Jassim and J. C.Goff. (eds), Dolin, Hlavni Publishers, Brno, Czech Republic, p.185 – 198.
Allen, R.G., Pereira, L.S., Raes, D., 1998, Crop evapotranspiration-Guidelines for computing crop water
requirements: FAO Irrigation and drainage paper 56, Rome, Italy, 300 p.
Bear, J., Shamir, U., and Hefez, E.A., 1972, Numerical modeling of groundwater systems: Technion-
Israel Institute of Technology, 76 p.
Buringh, P., 1960, Soils and Soil Conditions in Iraq: Ministry of Agriculture, Baghdad, Iraq, 214 p.
http://library.wur.nl/isric/index2.html?url=http://library.wur.nl/WebQuery/isric/648
Cullen, H.M., Kaplan, A., Arkin, P.A., and Demenocal, P.B., 2002, Impact of the north Atlantic
oscillation on middle eastern climate and streamflow: Climatic Change 55:315-338.
Eshel, G., Farrell, C. M., and Farrell, B., 2000, Forecasting eastern Mediterranean droughts: Mon.
Weather Rev. 128:3618–3630.
Evans, J.P., 2009, 21
st
century climate change in the Middle East: Climatic Change 92:417-432.
Evans, J. P., and Smith, R.B., 2006, Water vapor transport and the production of precipitation in the
eastern Fertile Crescent: J. Hydrometeor, 7, 1295–1307.
FAO/IIASA/ISRIC/ISS-CAS/JRC, 2009. Harmonized World Soil Database (version 1.1). FAO, Rome,
Italy and IIASA, Laxenburg, Austria.
http://www.iiasa.ac.at/Research/LUC/External-World-soil-database/HTML/index.html?sb=1
Flint, A.L., Flint, L.E., Hevesi, J.A., and Blainey, J.M., 2004, Fundamental concepts of recharge in the
Desert Southwest: a regional modeling perspective, in Groundwater Recharge in a Desert Environment:
The Southwestern United States, edited by J.F. Hogan, F.M. Phillips, and B.R. Scanlon, Water Science
and Applications Series, vol. 9, American Geophysical Union, Washington, D.C., 159-184.
Flint, L.E., and Flint, A.L., 2007a, Regional analysis of ground-water recharge, in Stonestrom, D.A.,
Constantz, J., Ferré, T.P.A., and Leake, S.A., eds., Ground-water recharge in the arid and semiarid
southwestern United States: U.S. Geological Survey Professional Paper 1703, p. 29-59.
Flint, A.L., and Flint, L.E., 2007b, Application of the basin characterization model to estimate in-place
recharge and runoff potential in the Basin and Range carbonate-rock aquifer system, White Pine County,
Nevada, and adjacent areas in Nevada and Utah: U.S. Geological Survey Scientific Investigations Report
2007-5099, 20 p.
Page 20 of 44
Flint, L.E., and Flint, A.L., Downscaling future climate scenarios to fine scales for hydrologic and
ecologic modeling and analysis. (In review)
Freeze, R.A., and Cherry, J.A., 1979, Groundwater: Prentice-Hall, 604 p.
GEOSURV, 2000, Geological map of Iraq, 1:1,000,000: 3
rd
revision, State Company of
Geological Survey and Mining, Baghdad.
Hemming, D., Buontempo, C., Burke, E., Collins, M, and Kaye, N., 2010, How uncertain are climate
model projections of water availability indicators across the Middle East?: Phil. Trans. R. Soc. A,
368(1931): 5117-5135.
Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G., and Jarvis, A., 2005 Very high resolution
interpolated climate surfaces for global land areas: Int. J. of Climatology 25:1965-1978.
Hurrell, J. and Van Loon, H., 1997, Decadal variations in climate associated with the North
Atlantic Oscillation: Climatic Change 36:301–326.
Hurrell, J., Kushnir, Y., and Visbeck, M., 2001, The North Atlantic Oscillation: Science 291:603–605.
Jassim, S.Z. and Al-Gailani, M., 2006, Hydrocarbons: Chapter 18 in Geology of Iraq,
S. Z.
Jassim and Buday, T. (eds), Dolin, Hlavni Publishers, Brno, Czech Republic, p. 232-249.
Jassim, S. Z., and Goff, J.C., 2006, Phanerozoic development of the northern Arabian Plate: Chapter 3 in
Geology of Iraq, S. Z. Jassim and Buday, T. (eds), Dolin, Hlavni Publishers, Brno, Czech Republic, p. 32-
44.
Krasny, J., Alsam, S., and Jassim, S.Z., 2006, Hydrogeology: Chapter 19 in Geology of Iraq,
S. Z. Jassim
and Buday, T. (eds), Dolin, Hlavni Publishers, Brno, Czech Republic, p. 251 – 287.
Lees, G.M. and Falcon, N. L., 1952, The geographical history of the Mesopotamian Plains: The
Geographical Journal, 118(1): 24-39. http://www.jstor.org/stable/1791234
Metz, H.C. (ed.), 1988, Iraq: A Country Study: Washington, GPO for the Library of Congress.
Mitchell, T.D., and Jones, P.D., 2005, An improved method of constructing a database of monthly climate
observations and associated high-resolution grids: Int. J. Climatology 25:693-712.
Nalder, I.A., and Wein, R.W., 1998, Spatial interpolation of climatic normals, test of a new method in the
Canadian boreal forest: Agricultural and Forest Meteorology 92: 211– 225.
Pawlewicz, M.J., Steinshouer, D.W., and Gautier, D.L., 2003, Map showing geology, oil and gas fields,
and geologic provinces of Europe including Turkey: U.S. Geological Survey Open File Report 97-470I,
one CD-ROM.
Page 21 of 44
http://pubs.usgs.gov/of/1997/ofr-97-470/OF97-470I/
Pollastro R.M., Karshbaum A.S, and Viger R.J., 1999a, Map showing geology, oil and gas fields, and
geologic provinces of the Arabian peninsula: U.S. Geological Survey Open File Report 97-470B, one
CD-ROM. http://pubs.usgs.gov/of/1997/ofr-97-470/OF97-470B/
Pollastro R.M., Persits, F.M., Steinhouer, D.W., 1999b, Map showing geology, oil and gas fields, and
geologic provinces of Iran: U.S. Geological Survey Open File Report 97-470G, one CD-ROM.
http://pubs.usgs.gov/of/1997/ofr-97-470/OF97-470G/
Saleh, D.K., 2010, Stream gage descriptions and streamflow statistics for sites in the Tigris River and
Euphrates River Basins, Iraq: U.S. Geological Survey Data Series 540, 146 p.
Schaap, M.G., Leij, F.J., van Genuchten, MTh., 2001. Rosetta: a computer program for estimating soil
hydraulic parameters with hierarchical pedotransfer functions: J. Hydro. 251, 163-176.
http://www.ussl.ars.usda.gov/models/rosetta/rosetta.HTM
Shuttleworth, W.J., 1993, Evaporation: Chapter 4 in Maidment, D.R. (ed.), Handbook of Hydrology: New
York, McGraw-Hill, 53 p.
van Genuchten, M.Th., 1980, A closed-form equation for predicting the hydraulic conductivity of
unsaturated soils: Soil Sci. Am. J. 44:p. 892-898.
Page 22 of 44
50°0'0"E45°0'0"E40°0'0"E
N
Turkey
Armenia
40°0'0"
Elevation
(meters above
mean sea level)
High : 4,363
Iran
Syria
3
5°0'0"N
35°0'0"N
Low : -9
Mosul
Kirkuk
l
ih
Iraq
boundary
Iraq
Jordan
3
Baghdad
Samarra
Ramadi
Hit
Al
Jaz
i
ra
h
Saudi Arabia
Kuwait
30°0'0"N
30°0'0"N
Qurnah
Basrah
Marshes
ArabianDesert
50°0'0"E45°0'0"E40°0'0"E
PersianGulf
Figure1.MapofTigrisEuphratesRiverSystem,includingcountryboundariesand
elevation
010020050 Kilometer
s
elevation
.
Page 23 of 44
50°0'0"E45°0'0"E40°0'0"E
4
0°0'0"N
Study Area Boundary
Eht Ri Bi
4
Tigris and Euphrates Drainage Network
Unimpaired Streamflow Gages
Unimpaired Basins
E
up
h
ra
t
es
Ri
ver
B
as
i
n
Karun River Basin
Shatt al Arab River Basin
Tigris River Basin
35°0'0"N
35°0'0"N
Unimpaired
Basins
Iraq
boundary
N
30°0'0"N
30°0'0"
N
0
100
200
50
Kilometers
50°0'0"E45°0'0"E40°0'0"E
Figure2.MapofTigrisEuphratesRiverSystem(TERS),studyareaboundary,majorriver
basins and
subbasins
calibration basins and unimpaired
streamflow
gages
0
100
200
50
Kilometers
basins
and
subbasins
,
calibration
basins
,
and
unimpaired
streamflow
gages
.
Page 24 of 44
50°0'0"E45°0'0"E40°0'0"E
40°0'0"N
(a)
35°0'0"N
35°0'0"N
A
N
0
°0'0"N
A
verage
Annual
Precipitation
(mm/year)
50 - 100
50°0'0"E45°0'0"E40°0'0"E
30°0'0"
N
3
0
100 - 150
150 - 200
200 - 250
250 - 300
300
400
(b)
50°0'0"E45°0'0"E40°0'0"E
0
°0'0"N
010020050 Kilometer
s
300
-
400
400 - 500
500 - 600
600 - 800
800 - 1,050
4
0
0
'0"N
35°0'0"N
35°
0
Iraq
boundary
30°0'0"N
30°0'0"N
010020050 Kilometer
s
Figure3.MapofaverageannualprecipitationfortheTigrisEuphratesRiverSystemat(a)
180mspatialresolutionusedforBasinCharacterizationModel,and(b)originalspatial
resolutionof51.6kmfromdataavailablefromtheClimaticResearchUnit(Universityof
EastAnglia,Norwich,UK;http://www.cru.uea.ac.uk/cru/data/hrg/
).
50°0'0"E45°0'0"E40°0'0"E
Page 25 of 44
50°0'0"E45°0'0"E40°0'0"E
40°0'0"N
Potential
Evapotranspiration
(mm/yr)
< 800
800 - 1,100
1,100 - 1,300
1,300 - 1,400
1,400 - 1,700
35°0'0"N
35°0'0"N
1,700 - 1,900
>2,000
Iraq
boundary
°
0'0"N
30°0'0"N
30
°
010020050 Kilometer
s
Figure4.MapofannualpotentialevapotranspirationfortheTigrisEuphratesRiver
System(USGSEarlyWarningandEnvironmentalMonitoringProgram;
http://earlywarning.usgs.gov/fews/middleeast/index.php).
50°0'0"E45°0'0"E40°0'0"E
Page 26 of 44
50°0'0"E45°0'0"E40°0'0"E
40°0'0"N
Maximum Air
35°0'0"N
35°0'0"N
Temperature
(degrees C)
3 - 10
10 - 15
15
18
N
0
°0'0"N
15
-
18
18 - 21
21 - 24
24 - 27
27 - 30
50°0'0"E45°0'0"E40°0'0"E
30°0'0"
N
3
0
30 - 33
50°0'0"E45°0'0"E40°0'0"E
'0"N
010020050 Kilometer
s
Iraq
boundary
40°0
"
N
Minimum Air
Temperature
(degrees C)
-
8
-
0
35°0'0"N
35°0'0
"
8
0
0 - 2
2 - 4
4 - 6
6 - 9
30°0'0"N
30°0'0"N
9 - 12
12 - 15
15 - 18
010020050 Kilometer
s
Iraq
boundar
y
Figure5.MapofaverageannualmaximumandminimumairtemperaturefortheTigris
EuphratesRiverSystem(Hijmans andothers,2005;http://worldclim.org/).
50°0'0"E45°0'0"E40°0'0"E
y
Page 27 of 44
50°0'0"E45°0'0"E40°0'0"E
4
0°0'0"N
Average Annual Snowfall
(mm/yr)
4
(mm/yr)
< 5
5 - 10
10 - 20
20 - 40
40 - 70
70
100
35°0'0"N
35°0'0"N
70
-
100
100 - 150
150 - 200
200 - 250
> 250
Iraq
boundary
N
30°0'0"N
30°0'0"
N
010020050 Kilometer
s
Figure6.MapofaverageannualsnowfallfortheTigrisEuphratesRiverSystem.Snowfall
iscalculatedfromairtemperatureandprecipitationdata(Hijmans andothers,2005;
http://worldclim.org/)usingtheBasinCharacterizationModel(FlintandFlint,2007a).
50°0'0"E45°0'0"E40°0'0"E
Page 28 of 44
Figure7.SchematicoftheBasinCharacterizationModelindicatingcomponentsofthe
monthly water balance decision points and how runoff and recharge are calculated
monthly
water
balance
,
decision
points
,
and
how
runoff
and
recharge
are
calculated
.
Page 29 of 44
50°0'0"E45°0'0"E40°0'0"E
40°0'0"N
Bulk Bedrock Permeability
(mm/day)
0 - 0.5
0.5 - 2
2 - 3
3 - 5
5 - 10
10 - 40
35°0'0"N
35°0'0"N
40 - 200
200 – 1,500
1,500 – 2,500
2,500 – 4,000
Iraq
boundary
Unimpaired
basins
boundary
30°0'0"N
30°0'0"N
50°0'0"E45°0'0"E40°0'0"E
Figure8.Mapofsurficialsaturatedhydraulicconductivityderivedfromgeologyforthe
TigrisEuphratesRiverSystem.Geomorphicprovidencesareincluded.
010020050 Kilometer
s
Page 30 of 44
Euphrates at Murat
Euphrates at Bagistas
50°0'0"E45°0'0"E40°0'0"E
40°0'0"N
Khabu at Zakho
Khazir at Manquba
35°0'0"N
35°0'0"N
Soil Depth
(meters)
0
0 - 0.1
0.1 - 0.2
°0'0"N
0.2 - 0.3
0.3 - 0.4
0.4 - 0.5
0.5 - 0.7
0.7 - 1
1
51
50°0'0"E45°0'0"E40°0'0"E
30°0'0"N
30
40°0'0"E
"N
0
'0"N
(a)
(b)
1
-
5
.
1
010020050 Kilometer
s
Unimpaired
basins
40°0'0
40°
0
Euphrates at Murat
0306015 Kilometers
40°0'0"E
Figure9.Mapofsoildepthdevelopedfor(a)theTigrisEuphratesRiverSystemand(b)a
closeupillustratingtheimpactofslopesonderivedsoildepth.
Page 31 of 44
1,400
1,600
1,800
l
ionsof
BCMsimulated Meas ured
RMSE=363
(a)
0
200
400
600
800
1,000
1,200
1975 1976 1977 1978 1979 19 80 1981
BasinDischarge,mil
l
cubi cmeters
1000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
n
Dis charge,millionsof
cubicmeters
BCMsimulated Measured
RMSE=834
(b)
0
500
1
,
000
1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985
Basi
n
800
1,000
m
illionsof
r
s
BCMsimulated Meas ured
RMSE=136
(c)
0
200
400
600
1949 1951 1953 1955 1957 1959 1961 1963 1965 1967 1969 1971 1973 1975 1977
Bas inDischarge,
m
cubicmete
r
(d)
200
400
600
800
1,000
1,200
B
asinDischarge,millionsof
cubicmeters
BCMsimulated Measured
RMSE=181
(d)
0
1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988
B
Figure10.Calibrationresultscomparingsimulatedandmeasuredbasindischargefor
stramflow gagesat(a)EuphratesatBagistas,(b)EuphratesatMurat,(c)Khazir at
Manquba
and (d)
Khabu
at
Zahko
for the period of record for each gage
Manquba
,
and
(d)
Khabu
at
Zahko
,
for
the
period
of
record
for
each
gage
.
Page 32 of 44
35
40
45
e
,C
MaximumMonthly AirTemperature
MinimumMonthlyAirTemperature
(a)
5
10
15
20
25
30
35
A
nnualAirTemperatur
e
0
5
Aveage
A
70%
80%
90%
100%
b
alance
(b)
30%
40%
50%
60%
e
ntageoftotalwa ter
b
Runoff
Recharge
Actual
Evapotranspiration
Snowfall
Precipitation
0%
10%
20%
Perc
e
Precipitation
Figure11.Averagemonthly(a)airtemperatureand(b)BasinCharacterizationModel
resultsofwaterbalancecomponentsdepictedasthepercentageofthetotalwater
balance
balance
.
Page 33 of 44
50°0'0"E45°0'0"E40°0'0"E
4
0°0'0"N
Average Annual Recharge
(mm/year)
4
(mm/year)
0.1 - 1
1 - 2
2 - 10
10 - 20
20 - 50
< 0.1
35°0'0"N
35°0'0"N
50 - 100
100 - 150
150 - 200
200 - 250
250 - 450
Iraq
boundary
N
30°0'0"N
30°0'0"
010020050 Kilometer
s
50°0'0"E45°0'0"E40°0'0"E
Figure12.Mapofaveragerechargefor19491999fortheTigrisEuphratesRiverSystem
usingtheBasinCharacterizationModel.
Page 34 of 44
50°0'0"E45°0'0"E40°0'0"E
4
0°0'0"N
Average Annual Runoff
(mm/year)
4
(mm/year)
0.1 - 1
1 - 2
2 - 10
10 - 20
20 - 50
< 0.1
35°0'0"N
35°0'0"N
50 - 100
100 - 150
150 - 200
200 - 250
250 - 450
Iraq
boundary
N
30°0'0"N
30°0'0"
010020050 Kilometer
s
50°0'0"E45°0'0"E40°0'0"E
Figure13.Mapofaverageannualrunofffor19491999fortheTigrisEuphratesRiver
SystemusingtheBasinCharacterizationModel.
Page 35 of 44
50°0'0"E45°0'0"E40°0'0"E
40°0'0"N
A
vera
g
e annual
35°0'0"N
35°0'0"N
g
precipitation
(millions of cubic meters)
0 - 50
50 - 300
300 - 600
0
"N
30°0'0"N
600 – 1,000
1,000 – 1,500
1,500 – 2,500
2,500 – 4,500
4,500 – 7,000
7 000
10 000
50°0'0"E45°0'0"E40°0'0"E
30°0'
0
50°0'0"E45°0'0"E40°0'0"E
0
'0"N
7
,
000
10
,
000
10,000 – 16,000
010020050 Kilometer
s
Iraq
boundary
Subbasin boundaries
40°
0
"
N
Average annual
snowfall
(millions of cubic meters)
0 - 5
5 - 25
35°0'0"N
35°0'0
"
25 - 65
65 - 120
120 - 250
250 - 650
650 – 1,200
1 200
2 000
30°0'0"N
30°0'0"N
1
,
200
2
,
000
2,000 – 3,000
3,000 – 6,000
010020050 Kilometer
s
Iraq
boundary
Subbasin boundaries
50°0'0"E45°0'0"E40°0'0"E
Figure14.Mapsofaverageannualprecipitationandsnowfallasvolumesforeach
subbasin intheTigrisEuphratesRiversystem.
Page 36 of 44
50°0'0"E45°0'0"E40°0'0"E
40°0'0"N
Recharge
35°0'0"N
35°0'0"N
N
0
°0'0"N
Average annual
recharge and runoff
50°0'0"E45°0'0"E40°0'0"E
30°0'0"
N
3
0
50°0'0"E45°0'0"E40°0'0"E
0
'0"N
(millions of cubic meters)
0 - 10
10 - 50
50 - 100
100 - 200
200 - 350
40°
0
"
N
350 - 600
600 - 900
900 – 1,400
1,400 – 2,000
2,000 – 4,800
Runoff
Sbb i
bdi
35°0'0"N
35°0'0
"
Iraq
boundary
S
u
bb
as
i
n
b
oun
d
ar
i
es
30°0'0"N
30°0'0"N
50°0'0"E45°0'0"E40°0'0"E
Figure15.Mapsofaverageannualrechargeandrunoffasvolumesforeachsubbasin in
theTigrisEuphratesRive rsystem.
Page 37 of 44
500
600
700
m
/year
(a)
0
100
200
300
400
9
1
3
5
7
9
1
3
5
7
9
1
3
5
7
9
1
3
5
7
9
1
3
5
7
9
Precipitation,m
m
EuphratesRiverBasin
TigrisRiverBasin
194
9
195
195
3
195
5
195
7
195
9
196
196
3
196
5
196
7
196
9
197
197
3
197
5
197
7
197
9
198
198
3
198
5
198
7
198
9
199
199
3
199
5
199
7
199
9
1,600
1,700
1,800
1,900
o
transpiration,
/
year
(b)
1,200
1,300
1,400
1,500
1949
1951
1953
1955
1957
1959
1961
1963
1965
1967
1969
1971
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
PotentialEvap
o
mm
/
EuphratesRiverBasin
TigrisRiverBasin
15
20
25
30
T
emperature,C
EuphratesTmax
TigrisTmax
Euphrates Tmin
(c)
5
10
1949
1951
1953
1955
1957
1959
1961
1963
1965
1967
1969
1971
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
Air
T
Euphrates
Tmin
TigrisTmin
Figure16.Annualresultsfor19491999fortheEuphratesRiverBasinandtheTigrisRiver
Basinfor(a)precipitation,(b)potentialevapotranspiration,and(c)maximumand
minimumairtemperature.
Page 38 of 44
140
160
180
a
r
(a)
0
20
40
60
80
100
120
Snowfall,mm/ye
a
EuphratesRiverBasin
TigrisRiverBasin
1949
1951
1953
1955
1957
1959
1961
1963
1965
1967
1969
1971
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
80
100
120
140
m
m/year
(b)
0
20
40
60
80
1949
1951
1953
1955
1957
1959
1961
1963
1965
1967
1969
1971
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
Recharge,
m
EuphratesRiverBasin
TigrisRiverBasin
60
80
100
120
140
o
ff,mm/year
EuphratesRiverBasin
(c)
0
20
40
1949
1951
1953
1955
1957
1959
1961
1963
1965
1967
1969
1971
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
Run
o
TigrisRiverBasin
Figure17.Annualresultsfor19491999fortheEuphratesRiverBasinandtheTigrisRiver
Basinfor(a)snowfall,(b)recharge,and(c)runoff.
Page 39 of 44
50°0'0"E45°0'0"E40°0'0"E
40°0'0"N
Change in Snowfall
(mm)
-75 - -50
-50 - -35
-35 - -20
-20 - -10
-10 - -5
No change
35°0'0"N
35°0'0"N
5 - 10
10 - 20
20 - 35
Iraq
boundary
0
'0"N
30°0'0"N
50°0'0"E45°0'0"E40°0'0"E
30°
0
010020050 Kilometer
s
Figure18.Mapofthe changeinsnowfalloverthe50yearperiodfrom19491999for
theTigrisEuphratesRive rSystem.
Page 40 of 44
50°0'0"E45°0'0"E40°0'0"E
40°0'0"N
Recharge
3
5°0'0"N
35°0'0"N
3
0
'0"N
Change over 50 yrs
(mm)
50°0'0"E45°0'0"E40°0'0"E
30°0'0"N
30°
0
-90 - -40
-40 - -20
-20 - -5
-5 - -0.1
No change
50°0'0"E45°0'0"E40°0'0"E
'
0"N
010020050 Kilometer
s
No
change
0.1 - 5
5 - 20
20 - 40
40 - 90
40°0
'
"
N
Runoff
35°0'0"N
35°0'0
"
Iraq
boundary
30°0'0"N
30°0'0"N
010020050 Kilometer
s
Figure19.Mapofthe changeinrechargeandrunoffoverthe50yearperiodfrom1949
1999fortheTigrisEuphratesRiverSystem.
50°0'0"E45°0'0"E40°0'0"E
Page 41 of 44
Table1.UnimpairedstreamflowgagesintheTigrisandEuphratesRiverSystem.
Gagename
Latitude
(decimal
degrees)
Longitude
(deci mal
degrees)
Elevation
(meters)
Catchment
area(km2)
Periodof
record
EuphratesatBagistas 39.450 38.483 1,277 15,562 19751982
Euphrates at Murat
38 692
39 929
1000
25 447
1975 1985
Euphrates
at
Murat
38
.
692
39
.
929
1
,
000

25
,
447

1975
1985
Khazi ratManquba 36.300 43.550 549 2,900 19441994
KhabuatZakho 37.133 42.683 254 3,500 19 581988
Page 42 of 44
[mm/day,millimeterspe rday]
C lib t d ttd
Table2.GeneraldescriptionoflithologicunitsusedintheBasinCharacterizationMode l,includinginitial esti matesof
hydrauli cconductiv ityandfinalcalibratedsaturatedhydraulicconductivity.
Generallithologicdescripti on
C
a
lib
ra
t
e
d
sa
t
ura
t
e
d
hydrauli cconductiv ity
(mm/day)
Initialestimateofhydraulic
conducti vity(mm/day)
Active marsh de
p
osits 100.
0
500
Aeolian 4,000.
0
10,00
0
Ar
g
illaceous marl, ar
g
illaceous limestone, and shale 20.
0
500
Bammu Con
g
lomerate 50.
0
10,00
0
Carbonate 30.
0
10,00
0
Carbonate 30.
0
5,000
Carbonate 30.
0
1,000
Carbonate 30.
0
8
Carbonate, shale 10.
0
500
Chalk
y
and cr
y
stalline limestones with marl and chert 1.0
10
De
p
ression-fill de
p
osits 0.1
500
Dolomite and dolomitic limestone with
gyp
sum and anh
y
drite beds 5.0
1,000
Dolomite and finel
y
recr
y
stallised limestone 20.
0
1
Dolomites, limestone, ar
g
illaceous chalk
y
limestone,
p
hos
p
horite 1.0
500
Dolomitized limestone with shale 10.
0
500
Et i bkh
20
100
E
s
t
uar
i
ne sa
bkh
a
2
.
0
100
Eva
p
orites
(gyp
sum, marl, and limestone
)
5.0
5,000
Eva
p
orites
(gyp
sum, marl, and limestone
)
20.
0
1,000
Eva
p
orites
(gyp
sum, marl, and limestone
)
with
(
im
p
ermeable
)
mudstone 0.5
500
Eva
p
orites
(gyp
sum, marl, and limestone
)
with
(
im
p
ermeable
)
mudstone 1.0
50
Fine-coarse
g
rained sand and sandstone 100.
0
1,000
Flood
p
lain and crevasse s
p
la
y
s 1,000.
0
500
Flood
p
lain and fluvial de
p
osits 2,500.
0
20,00
0
Gravels and sands with var
y
in
g
amounts of cla
y
1,500.
0
10,00
0
Gy p c
r
e
t
e
depos
it
s
1
.0
100
Gypc e e depos s
.0
Horan
g
ravels 1,500.
0
10,00
0
Inland sabkha 5.0
2,400
Intrusive 50.
0
50
Limestone and a
g
illaceous limestone, well-bedded 0.5
1,000
Limestone and chalk
y
limestone 5.0
1,000
Limestone with im
p
ermeable cla
y
and marl 1.0
500
Limestone with im
p
ermeable cla
y
and marl 1.0
5
Limestone, dolomite 5.0
10
Limestone, dolomite, interbedded with marl 10.
0
5,000
10 000
Limes tone,
g
enerall
y
dolomitised and recr
y
stallised 20.
0
10
,
000
Limestone, shale 40.
0
1,000
Limestone, shale 5.0
11
Limestone, shale 50.
0
1
Lower clastic, u
pp
er carbonate 2.0
50
Marl, ar
g
illaceous limestone, siltstone, con
g
lomerate 20.
0
5,000
Marl, marl
y
limestone, limestone, dolomite 10.
0
10,00
0
Metamor
p
hic 10.
0
1,000
Metamor
p
hic 1.0
8
Mudstone
30
1,000
Mudstone
3
.
0
1,000
Mudstones
(
im
p
ermeable
)
0.2
0
Pol
yg
enetic de
p
osits 20.
0
500
Red bed series, shale, sandstone, con
g
lomerate 20.
0
500
Sand,
g
ravel, and con
g
lomerate 200.
0
1,000
Sandstone and shale beds 10.
0
833
Sandstone, shale 1.0
500
Shale 1.0
1
Shale, carbonate 5.0
50
Shale, sandstone 10.
0
167
Sheet-run-off de
p
osits 0.1
0
Sli
g
htl
y
dolomitized limestone 5.0
10,00
0
Sli
g
htl
y
dolomitized limestone 5.0
5,000
Sli
g
htl
y
dolomitized limestone 5.0
10
Tidal flat de
p
osits 0.1
500
Volcanic 20.
0
1,000
Page 43 of 44
Table3.AverageannualwaterbalancecomponentsfortheTigrisandEuphratesRiverbasinsandcountri eswithintheTigris
EuphratesRiverSystem.
Country orRiver
Basin
millimeters
millionsof
cubicmeters
millimeters
millionsof
cubicmeters
millimeters
millionsof
cubicmeters
millimeters
millionsof
cubicmeters
millimeters
millionsof
cubicmeters
TigrisRiverBasin 454 126,703 1,426 398,316 85 23,801 73 20,255 52 14,608
EuphratesRiverBasin 20 4 128,958 1,737 128,958 26 16,692 24 15,261 6 4,039
Turkey 60 0 115,418 1,062 204,181 185 35,435 136 26,110 55 10,601
Precipitation
Potential
Evapotranspiration Snowf al l Recharge Runoff
Syria 207 24,065 1,465 170,146 14 1,602 44 5,127 1 133
Iraq 206 86,909 1,842 777,241 17 7,291 17 6,977 15 6,445
Iran 376 60,158 1,810 289,437 103 16,506 65 10,419 19 3,036
SaudiaArabia 116 16,573 1,914 273,809 0 21 0   
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... This period is also characterised by significantly elevated dust mass accumulation rates (DMAR) reaching almost 800 g m −2 y −1 (Fig. 5e), a reduced fluvial run-off ( Supplementary Fig. S2e) and common occurrence of the mineral celestine (an aridity indicating strontium sulphate, see Supplementary information chapter 3). In contrast to sandstones from 126 ). b Based on data from Rosenthal et al. 37 and Ewing et al. 36 . ...
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The evolution of the present-day African savannah fauna has been substantially influenced by the dispersal of Eurasian ancestors into Africa. The ancestors evolved endemically, together with the autochthonous taxa, into extant Afrotropical clades during the last 5 million years. However, it is unclear why Eurasian ancestors moved into Africa. Here we use sedimentological observations and soluble salt geochemical analyses of samples from a sedimentary sequence in Western Iran to develop a 10-million-year long proxy record of Arabian climate. We identify transient periods of Arabian hyperaridity centred 8.75, 7.78, 7.50 and 6.25 million years ago, out-of-phase with Northern African aridity. We propose that this relationship promoted unidirectional mammalian dispersals into Africa. This was followed by a sustained hyperarid period between 5.6 and 3.3 million years ago which impeded dispersals and allowed African mammalian faunas to endemically diversify into present-day clades. After this, the mid-Piacenzian warmth enabled bi-directional fauna exchange between Africa and Eurasia, which continued during the Pleistocene.
... The TEB bounds two rivers (Tigris and Euphrates), originating in the mountains in eastern Turkey and flowing in Syrian valleys and Iraqi plateaus to the confluence at Shat Al-Arab and then flowing into the Persian Gulf (Fig. 1). The semi-arid climate dominates most of the basin (except the mountains), with precipitation from north to south ranging from 50 to 1000 mm/yr (Al-Ansari and Knutsson, 2011;Flint et al., 2011). During the winter (December to February), snow accumulates in the mountains under freezing temperatures, down to~−11°C, and melts during spring (April to May) to maintain flow in rivers and to recharge aquifers (New et al., 2002) with a lag of~3-5 months (Daggupati et al., 2017). ...
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