Water Balance Principles: A Review of Studies on Five Watersheds in Iran
S.M.R. Alavi Moghaddam
Originally, water balance models were introduced to evaluate the importance of different hydrologic parameters under a variety of hydrologic conditions but its present applications are the most common studies at water resources management. In spite of the simple concept of water balance equation, specific considerations are need to proper application. With numerous affecting factors on hydrologic processes, the parsimony trait of water balance equation can cause huge errors or complexities throughout study processes. It is beyond a general computation to create an appropriate portrait of water circumstances with a parsimonious equation that should be considered as an art. Practically, water balance computations are used in five separate categories at least: watersheds, groundwater aquifers, farms, urban water distribution networks and particular areas such as glaciers and landfills; totally, they are directed along three main lines: watershed hydrology reconstruction, evaluation of water supply and water demand systems and assessment of climatic changes impacts. This study is to concentrate on some specific hints which their ignorance leads us to less reliability on water balance results and misunderstandings of actual situations. Finally, the methods used in Iran are investigated in five separate watersheds in the north east of the country and their results are compared with two other published results.
January 09, 2011; Accepted: March 21, 2011;
Published: June 07, 2011
Water balance is the base of management and policy making in some critical
matters related to water resources management such as design of water supply
systems, flood estimation, water allocation and use, management of stormwater
and wastewater in urban areas, aquatic ecosystems management, water trading
and virtual water. In all of these fields, the basin managers and policy makers
need to extract information about the volumes of resources, demands and storage
changes in the basin. Based on the results of water balance computations a great
number of important water projects have been planed and constructed such as
CHASM project in Britain (Quinn et al., 2000)
and Doosti complex projects between Iran and Turkmenistan (storage dam, water
pipeline to Mashhad city, Sarakhs irrigation network and etc.). Besides, according
to the general approach which dominates on water balance concepts, it is a valuable
methodology to manage glaciers, snow cover, swamps, estuaries, grasslands, reservoirs
and evaluate activities related to water like the effects of mulches on evaporation
and evapotranspiration from farms, landfill covers, new instruments effects
on nets seepage and etc that have specific analytical conditions (Ghandhari
and Ghahraman, 2010;Alkaeed Matsumoto et al.,
2004; Nurtayev et al., 2004; Sun
et al., 2002; Albright et al., 2004).
The domain of water balance studies can vary from water cycle on the earth to the humidity around a leaf, based on conservation principle. The study targets drive the accuracy rate and the methodology in which computation and application simplicity and reliability are the basses. Because of inherent brevity and parsimony traits of water balance approaches, the water budget models usually focus on prominent aspects of hydrological processes (rainfall-runoff).
The first attempts to develop computer-base models started with SWM (Stanford
Watershed Model) in the years between 1959 and 1966 (Crawford
and Linsley, 1966; Crawford and Burges, 2004), however,
today, numerous models with different assumptions and affecting parameters have
been introduced for water balance computations such as: MOSAZ (Modified Semi
Arid Zone), AWBM, Sacramento and Curve Number, Makhlouf and Michel, Guo, Wandwiele,
Jothityankoon, GR4, PMS, GR2M, VIC-3L, GUI, Wetpass, SESOIL and TOPOG-IRM (Boughton
and Chiew, 2007; Boughton, 2004; Mouelhi
et al., 2006; Cox and Pitman, 2002; Bonazountas
et al., 2005; McCabe and Markstrom, 2007;
Abu-Saleem et al., 2010; Najjar,
1999). WASIM (Singh et al., 1999) and WAVES
(Mingan et al., 2002) models have specialized
for modeling of water balance in a farm. NAM module from MIK-11 is applied to
investigate the statistical importance of various parameters in water balance
equations (Celleri et al., 2000). It is clear
that, the models based on explicit catchment water balance modeling are numbered
in the hundreds and new models are still being presented. A major review of
water balance models was presented by (Boughton, 2004).
The dominant interests in water balance modeling vary in different countries:
Estimation of water yield (Australia), flood estimation (USA) (Boughton,
2004) and budget allocation and putting new constrains on groundwater exploitation
(Iran). The wide application of water balance results and decisions which would
be made according to them, especially in Iran, show the importance of water
balance understanding. The first review of catchment water balance in Iran was
done (studied) by Fahmi (1983). This study is an attempt
to shed more light on the water balance computation process and its accuracy
and also is to present some key points for improving the reliability of water
Water balance models have been developed in various time scales (e.g., hourly,
daily, monthly and yearly) and different levels of complexity. Monthly water
balance models were first developed in 1940s by Thornthwaite and later revised
by Thornthwaite and Mather (Xu and Singh, 1998).
At the beginning of computer simulation of catchment water balance, the main
purpose was the estimation of runoff for water yield studies and calculated
monthly totals of runoff were the main interest. Today, a vast range of models
are used in different climates according to the water balance purposes (Xu
et al., 1996; Vandewiele and Elias, 1995;
Vandewiele et al., 1992; Makhlouf
and Michel, 1994; Xiong and Guo, 1999; Legesse
et al., 2010). The calculations for monthly totals were made at daily
time steps; hence daily runoff values soon became a purpose of calculation.
The interest in calculation of daily flows has steadily increased up to the
present. However, the use of sub-daily water balance modeling for flood studies
is necessary. A good review of monthly water balance models was presented by
Xu and Singh (1998) according their applications and
kinds of input parameters.
Practical strategies for calculation of dynamic components of water balance equations depend on the targets, accuracy and the time period in which the equations are assessed. In this regard, a lot of internal processes and events are usually neglected and only the response of the region at the end of the period is considered. This property which is called the parsimony, is in the interests of managers due to presenting simplified results. In Iran, it is customary allocating the financial budgets to water resources policies and projects based on the results of water balance analysis between separate regions. So the researchers and engineers are faced with a complicated situation, they should express the complex processes in the form of a simple equation.
However, modeling purposes, target area, calculation method, temporal and spatial
boundaries, available data and facilities drive the accuracy of water balance
results; generally the degree of accuracy is determined before any computations.
Based on the project situations, some important matters such as, choosing an
appropriate parent model, avoiding unnecessary details in calculations, using
all available data and facilities, model simplification by new scientific achievements
and former experiences; should be considered as main directions in the modeling
(Ghandhari and Ghahraman, 2009).
The success of the paradigm in relating runoff to rainfall is due to the constraint imposed by the need to account for all water entering, leaving and being stored in a catchment. Complex water balance models that contain error term require correct understanding of backgrounds, feedbacks and interactions between different processes, so more complexity don't necessarily lead us to the more accuracy. Correct modeling key is the match between targets, facilities, available data and model complexity.
Some believe when the time steps of a rainfall-runoff model are selected large
enough, the model will be a balance model, in which the ratio of watershed reaction
time to the time step is negligible (Mouelhi et al.,
2006). Sometimes it can be defined water balance from a simple bucket model
to really complex hydrological models according to their resolution (Zhang
et al., 2002). In this case, water balance is a set of equations
in which each process or a part of process is simulated by an equation. Generally,
water budget dominant viewpoints figure out all volumetric components into/out
of a three dimensional space that result in storage changes (Burt,
1999). Actually, for achieving to equilibrium between the complexity of
model structure and the purposes, we are faced with two sources of errors: systematic
errors from simplifier assumptions and calibration errors rising from insufficient
or unreliable data that they are inversely related (Zhang
et al., 2002).
We can define two separate boundaries and scales for water balance equation: 1-spatial boundaries for the region (spatial scale) and 2-temporal boundary for water balance period (time scale). Selecting different spatial or time scales in a specific region change the accuracy, equation elements and methodology according to the reliability of data, financial conditions and facilities.
Generally, water balance development includes three lumping phenomena; 1-Lumping-spatial
basis is related to the averaging of spatial parameters, 2-Lumping-temporal
means that accumulative inputs and outputs are considered in a certain period,
so intermediate events and their consequences are neglected; however, the scale
of the all parameters in a defined model may not be uniform and 3-lumping-conceptual
that contains considerations about separate phenomenon in rainfall-runoff processes.
Physical point of view may suppose that these assumptions violate the conceptions
of modeling; however, the actual modeling results don't approve these judgments.
Parameter reduction procedures are general in hydrology to recognition important
elements in modeling. These manners use sensitivity analysis to identify parameters
with minimum effect on output. One of the general methods is the parameter ratio
(Holvoet et al., 2005; Boughton,
2004). Generally, three different techniques can be applied in order to
evaluate the parameter significance and sensitivity: (1) Evaluation of the parameter
values during the optimization, (2) Checking whether the global minimum is obtained
and (3) Detailed analysis of the variance-covariance matrix (Xu
and Singh, 1998). The influence of the study scales and the importance of
physical characteristics of watershed on water balance equations were studied
by surface and subsurface water tracers (Talamba et al.,
Major classifications of water balance computation methods have performed to look at groundwater interactions with surface waters and water use sorts in atmosphere-water-soil system that cause some operational points.
WATER BALANCE IN WATERSHEDS
Water balance is an efficient means for programming and evaluating in the scale
of watersheds, applying for water supply and water allocation, waste water management
and flood estimation (Anderson et al., 2006;
Boughton and Hill, 1997) specially in the case of ungauged
basins (Boughton and Chiew, 2007; Boughton,
2004). Long-term water storage changes in watersheds, including surface
water and ground water, are expressed in the form of residuals (accumulated
or scattered water) in water balance equation (snow and ice amounts can be removed)
(Berezovskaya et al., 2005) (Eq.
where, dS/dt is total water change in watershed, P is average precipitation,
ET is evapotranspiration and Q is the surface water discharge at the main drain
of basin. This simple expression of water balance is valid where the groundwater
output and its withdrawals are negligible. Correct definition of water balance
period or hydrological year is a very important factor in the simplification
of computations and can be evaluated as a basis for judgment about the hydrological
regime of watershed (Najjar, 1999).
Classification of watersheds according to homogeneity characteristics (single
or multi parametric methods), climate conditions and physiographical situations
(closed or open watersheds), can be evaluated as a basis for using the same
equations for similar catchments (comparison methods). In closed watersheds,
usually, level or volume of the lakes or reservoirs is a controlling factor
for evaluating water balance equations (Ghandhari and Ziaii,
In arid and semi-arid zones, runoff-the basis for calibrating the models as
a spatial integration index and controlling factor-is transient and reduce the
reliability of results (Mazi et al., 2004). In
these zones, it is customary that time series are divided into flooding and
non flooding years. It can help to more accuracy in yearly recharge, evaporation
and evapotranspiration computations. In flood years, all sub-basins contribute
to final discharge that means infiltration, evaporation and evapotranspiration
are influenced significantly because of expanded floodplains and vegetation
cover development. Loss function is the base for short-time models in arid regions.
Dividing a watershed into smaller sub-hydrological systems can improve the results
in these basins (Cohen et al., 2001).
Besides, in these kinds of regions, sink areas (AET≥P) are frequently found
in, or next to, the stream beds of ephemeral rivers and are often characterized
by intensive land use or high conservation values (Ghandhari,
2008). For both types of land use it is important to know if and how much,
AET exceeds P and where the lateral water inputs come from. Thick sedimentary
fills in the stream bed, variable climate conditions and ephemeral flow conditions
pose specific difficulties to the evaluation of the water balance of these sites.
Here, the estimated deficit may be compensated by: (a) infiltration of local
rainfall during extreme events; (b) runon from the surrounding hill slopes and
(c) infiltration of channel flow during flash floods originating from the upper
part of the catchment. However, possibilities (a) and (b) cannot explain the
water deficit. Deep storage of water during floods in the main channel, can
be as much as 60-150 mm per event and may have been 160-400 mm per year in some
cases; that is large enough to replenish the annual deficit (Domingo
et al., 2001).
A missing component in current water balance models is transmission loss in stream channels between the areas where runoff is generated and the catchment outlet where runoff is measured. The importance of transmission loss is increasing as the importance of low flows for both water allocation and aquatic ecosystems increases.
In some regions, the existence of seasonal ice cover can introduce great deal
errors in runoff computations that are why water volume resulted from obstructions
and ice resistance causes inefficiency of usual computational techniques (Hamilton,
2004). Accumulation of snow and ice melting and resulted runoff, previous
soil moistures, evaporation from intermediate snow, traditional methods for
evaporation estimation are the factors affect the results of winter water balances
(Kostka et al., 2000).
Precipitation regimes influence the species plants, quality and quantity of
their water consumptions, root depth and shading conditions (Comstock
and Ehleringer, 1992). Analysis has shown that elderliness is a key factor
for trees water consumptions. Old trees near the permanent currents don't use
surface water but they transpire from deep layers, so they don't have a significant
influenced on surface water balance (Dowson and Ehleringer,
1991). Besides, In some regions, in up to a depth of 1.10 m, shrubs did
not compete with crops for water but preferentially extracted water from the
lower portion of the profile below 1.10 m and even beyond the depth of 3.5 m
(Kizito et al., 2007). However, in arid zones,
according to precipitation regimes and plant age, water balance depends on the
time of the consumptions among the year (Ehleringer et
Overland flow losses, emerged from evaporation and are really more important
than evaporation from open canals. Complexity of interactions between elements
of atmosphere-plant-soil system, spatial and temporal variability of vegetation
cover, amount of available water and dynamic atmosphere conditions are the agents
for complexity of ET computations that take place in the form of water vapor
fluxes, a common parameter in water and energy balance equations; that has been
identified as a key factor in hydrological modeling. For this reason, several
methods have been developed to calculate the potential evapotranspiration (Buttafuoco
et al., 2010). It is clear that potential evapotranspiration (ETp)
in the standard methods takes place when there is enough moisture in the soil
since precipitation is only its source (Najjar, 1999;
Kendy et al., 2003). ETp is an essential parameter
for computation effective recharge and evaporation from ground water. There
are some known methods as Penman-Monteith, FAO56-PM, Thornthwaite and Hargreaves
and Hamon to compute ETp. Actually there are not many differences between them,
so it seems that FAO56-PM is more suitable for computation of ETp because of
its simplicity (Alkaeed et al., 2006). In most
of them, air drying power is computed for estimation of ETp and the differences
between them refer to the formulating procedure of wind function (Hobbins
et al., 2001). Comparison between two common models, AA model (Advection-Aridity)
and CRAE model (Complementary Relationship Area Evapotranspiration), shows that
CRAE is more powerful means for estimation of regional monthly Etp; however,
both of them have present an overestimate values in arid zones. Lidar technique
is also a powerful tool to specification and mapping of water vapor on a heterogynous
surface (Cooper et al., 2000). Most of the hydrological
GIS-based models apply simple interpolation techniques to data measured at few
weather stations disregarding topographic effects for Etp.
Aguilar et al. (2010) apply a topographic solar radiation algorithm
for the generation of detailed time-series solar radiation surfaces using limited
data and simple methods in a mountainous watershed in southern Spain. Results
show the major role of topography in local values and differences between the
topographic approximation and the direct interpolation to measured data (IDW)
of up to + 42% and-1800% in the estimated daily values (Aguilar
et al., 2010).
To improve the prediction capacity of ETp models for large areas, spatial data
should be used as inputs because their continuous variation may reflect more
appropriately the nature of the ETp in comparison with the measurements made
only at a few weather station locations (Buttafuoco et
In watershed budget, usually ground water resources are not investigated as
a distinct section but they contribute in equations as a kind of water consumptions
(Cohen et al., 2001).
Quantifying noticeable recharges from a vast area due to precipitation, farm irrigations and mountain fronts, especially in arid and semi arid zones is really complicated. Most of the methods that consider the recharge element as a residual component in water balance equations are incorrect because of error margins ranges and inherent uncertainties.
Generally long term groundwater analysis show more desirable results due to the variability of yearly precipitation and volume of irrigation water and not existence appropriate methods to identification of local rising of water table from direct recharges.
Amount of infiltration (recharge) into groundwater depends on vegetation cover
and land use, slope and topography, soil composition and hydraulic, water table
depth, confining beds presence or totally, soil, vegetation and climatic conditions.
There are some known methods which are applied for groundwater budget computations,
physical methods such as lysimetry, Water Flux Meters (WFMs) and Tracers (Rockhold
et al., 2009) other computational methods like inverse modeling,
Richards equation solution, tipping-Bucket models and comparison of water
table fluctuations in humid and dry periods (Kendy et
As inverse modeling doesn't need to unsaturated zone water movement data, it
can be used easily. Although the chemical method and isotropic tracers are very
expensive, they are used successfully for quantifying recharge and identifying
the sources of feeding in various studies (Rockhold et
al., 2009). Richards equation solution for vertical flow component
in unsaturated zone can be time consuming; besides it needs some difficult measurements
such as hydraulic conductivity and soil storage curves but it used successfully
to identify and quantify recharge resources. Infiltration storage-routing routine
is a suitable method for short time modeling. In this method the downward moisture
movement throughout the soil profile is considered providing that moisture is
greater than field capacity. Use of this method in large area based on simple
1D model by crop and soil characteristics, meteorological data and hypothesis
of independency of successive processes, has showed acceptable results (Kendy
et al., 2003).
It is important to know ground water recharge is generally found to be much
higher in no vegetated land-use than in vegetated land use (Gee
et al., 1994). In the area with fine-grained surficial soils and
deep-rooted plants most of the water from direct precipitation is held in the
upper 1 or 2 m of the soil column until it returns to the atmosphere by evapotranspiration
while deep percolation rates in areas with coarse-grained surficial soils and
only shallow rooted plants are greater than in areas with fine grained soils
and deep rooted plants (Prych, 1994).
||Schematic diagram of water balance for a root zone and a catchment
(The box indicates control volume in catchment)
A suitable control volume to estimate recharge from a farm as a part of a watershed is the root zone in which water balance is referred to unit of area (Fig. 1).
Despite of existence of many methods to compute recharge; hydrological conditions and quantity and quality data determine the desirable method. Appropriate control volume for water balance per unit area and estimating irrigation recharge is root zone. Precipitation can be considered effective on groundwater in two forms: direct infiltration and leakage from runoff (Eq. 2):
where, ΔS is soil water storage change in root zone over the time period, P is precipitation, I is interception losses, ET is evaporation and transpiration totally, RO is overland flow or runoff, DD is deep drainage out of root zone, R is recharge to groundwater and SSF is lateral subsurface flow.
Usually piezometric observations are applied to control the calculations in
aquifers. It is very important to consider that the causes of the piezometric
levels variations are not only related to the pumping test and water deductions
intend to supply towns, agricol and industrial sectors. The geometrical configuration
of the aquifer could also play a significant role in the understanding of these
variations (Zouhri et al., 2005).
FARM WATER BALANCE
In the farm water balance, the field measurements are not effective alone.
They are time consuming noticeably and they cost and dont obtain continues
data; however, usually it is essential to trace different parts of total irrigation
water. In farm we usually need to indentifying portion of leaching water and
evapotranspiration as a percent of total irrigation water. Therefore, farm water
balance models need to develop some modules and codes for evaluation of conveyance
budget, root zone moisture and etc. (Zhang, 2002).
Water shortages, water rights, project developments, irrigation system efficiency,
common water resources around the farm (as springs) and returned water from
adjacent farms are arguments that result in serious legal challenges in many
catchments and plains. These challenges have created a basis for a new definition
as beneficial or intelligent use of water allocation among different sectors
and users, according to water balance approaches (Burt,
1999). In this way it can be define the irrigation efficiency as the ratio
of benefitted irrigation water (consumed by crops) to irrigation water minus
soil storage increasing (Isidoro et al., 2004).
In the case of the farm managements there are a great number of modes as aforementioned.
THE IMPACTS OF HUMAN ACTIVITIES AND CLIMATE CHANGE ON WATER BALANCE
Land cover change, associated with the intensification of agriculture, cattle
rising and urbanization, could have a profound influence on the hydrological
processes in small watersheds and at a regional level (Mendoza
et al., 2010). Developing water balance formulations, especially
when the targets contain future programming based on forecasts, significantly
depend on human activities and climate change; however, a lot of models have
a disability to incorporate these effects.
Human activity has the potential to indirectly and directly affect water quantity and the natural flow regime of a river system. Indirect impacts to the hydrologic cycle can result from land-use changes. Direct impacts can result from water diversions, withdrawals and discharges and from dams (flow regulation and water storage).
Urban and rural developments and followed physical changes in a part of the
catchment can have significant quantitative and qualitative effects on streams
and currents. All kinds of structures such as roads, fences, asphalted areas
and etc can change the natural river regimes and increase accidental hydrological
events. In fact, changes to the landscape caused by urban structures development
can affect hydrologic systems in two major ways, termed closed circuited and
non-closed circuited land use. Closed circuited areas include areas where the
impacted land is hydrological isolated from the original drainage area and no
longer contributes flow to the river system. Non-closed circuited land change
includes areas that still contribute flows to the river systems but where vegetation
has been removed or other changes affecting water flow havWatsone occurred.
Some artificial surface nets create closed circuited in some processes as flow
and pollution conveyances solution and absorption on soil particles, delayed
feedback mechanisms, surface maintenance and biological degradations in unsaturated
In small basins, small-scale forest management activities increase total discharge,
direct runoff, groundwater recharge and base flows (Bent,
2001). Environmental degradation and native vegetation removals or change
the type of the forest trees cause changes in soil compositions and its hydraulic
properties (Wahl et al., 2003) and after that
changes the situation of ground water recharge components (Zhang
et al., 2002).
There are some models such as Macaque model, TOPOG, ANTHROPOG, MM5 and SWAT
which have been used effectively to investigate some effects of human activates
on local water cycle components (Watson, 1999; Fohrer
et al., 2001; Ghandhari and Ghahraman, 2010).
Dam construction with big reservoirs that can store considerably volume of
yearly discharges, in some countries such as Iran produced significant effects
on watershed water budget and hydrologic conditions (Ghandhari
and Ghahraman, 2010).
Climate change can cause significant impacts on water resources through changes
in the hydrological cycle. The change in temperature and precipitation components
of the cycle can have a direct consequence on the quantity of evapotranspiration
and runoff components. Consequently, the water balance can be significantly
affected (Legesse et al., 2010). PDO and ENSO
are two natural known phenomena affecting water balance parameters. In some
countries such as US, climate change has been identified as critical key for
water sustainability (Hansen et al., 2004). The
water balance models have proven to be a valuable tool not only for assessing
the hydrologic characteristics of diverse watersheds but also for evaluating
the hydrologic consequences of climatic change. In the last 10 years, monthly
water balance models have been used to explore the impact of climatic change
(Xu and Singh, 1998). For the purpose of water resources
assessment and climate change impact study, a semi distributed monthly water
balance model is proposed and developed to simulate and predict the hydrological
process and water resources in macro scale basins in China with (Guo
et al., 2001).
Use of a physically based hydrological model integrating all hydrological processes
on basin scale with GIS and RS technologies, to assist the water balance components
simulation, is the best alternative approach for lumped and/or empirical methods
(Abu-Saleem et al., 2010), so now-a-days, RS
and GIS are considered as two basic elements in hydrological modeling and simulation.
Determination of vegetation cover areas and their types, impermeable areas,
river and their bank vegetation conditions that show an intermediate status,
ET, precipitation properties and snow properties can be determine with RS. Satellite
images have more advantages than field images, considering to economic issues
and their accuracy; however, satellite images dont have a lot of restrictions
(Goetz and Jantz, 2004; Wenzhong
and Youjing, 2009; Berezovskaya et al., 2005;
Dewan et al., 2005). In Iran RS can be suppose
the best technique because of insufficient appropriate databases and reliable
enough data especially about the farms (Ghandhari, 2004).
One parameter of special interest for water management applications is the crop
coefficient employed by the FAO-56 model to derive actual crop evapotranspiration
(ET) by RS radiometric measurements. Combinations RS data with daily soil water
balance in the root zone is used to estimate daily evapotranspiration at field
scale (Padilla et al., 2010). Besides, precipitation
radar data are really useful for distributed surface hydrological processes
modeling because of their high resolution and time and space continuity. Guo
et al. (2004) prepared an almost complete list of radar data applications
until 2004 and they showed NEXRAD data receive precipitation special distribution
more effective than rain gages by using their effect on water balance of watershed.
Today, there are Mathematical-GIS based algorithms to extract the hydrological
features such as drainage networks, ridge networks and watersheds accurately
WATER BALANCE EVALUATION STUDIES IN FIVE WATERSHEDS IN THE NORTH EAST OF IRAN
Although, all available information collecting are required for further understanding
of the problem aspects, usually objects and parameter estimation methods lead
to eliminate some insignificant parameters. Despite of relatively simple conceptual
analysis of water balance equations, the number of components, parameter calculation
methods and specific local conditions determine the structure and procedures
of water balance equations. However, it has been tried to choose the simple
method with desirable variability (Ghandhari and Ghahraman,
Practically, water balance computations are based on expert judgments that
are why today there are not enough data and definition data collecting and field
measurement as a part of water balance studies in Iran. Usually ET is computed
according Thornthwaite method, Darcys law is used for water movement in
saturated zones and then recharge from farms, plains, urban and rivers estimated
as a portion of annual precipitation empirically. Because of these percentages
are considered without any data and measuring documents, they are really unreliable.
Here five separate watersheds with different hydrological and geological conditions
are compared briefly and then the results of a modeling according to a simple
form of Richards approach (Kendy model) in one of these watersheds and
the results of two published studies are investigated (Fig. 2).
Comparison shows there are significant deviations between supposal percentages
and actual ones (Table 1).
|| Study results on separate catchments
|| Five catchments in Khorasan Razavi province of Iran
In a region as Khorasan Razvi province of Iran with 250 mm yearly precipitation, water is the main determinative factor for all activities. It means an error about 7% for 54472 ha, 7% for 104 km river with 0.44 L sec-1 mean discharge and 15% for 7852 M^3 of daily domestic water are significant.
Understanding this issue that a lot of common engineering analytic methods (quantitative and qualitative), developed models and softwares which are used for analysis the water problems are based on the water balance equations; can help us to find the best method for modeling.
In some countries such as Iran, most of the models used in water resources planning have been extracted from other countries with different climate conditions. It is very important to concentrate on the basis of these models before using them. Determination of minimum standards, required number of parameters and estimation methods in separate local zones, required reliability, new techniques and tools for reducing costs, field measurements and so on; can help to achieve more effective water management. Already developed methods that are the base for strategic decision making and financial budget allocations dont have reliable basis.
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