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Current problems of hydrological networks design and optimization.
Introduction
A hydrological network is composed of a group of stations (gauges) that are designed and operated to
make observations under special observation programs and address a single objective or a set of interrelated
objectives. Observation data collected in the network can be used, for example, only for a water resources
assessment, a development plan, a project design, or for designing flood protection measures including flood
forecasting. In most cases, however, a hydrological network is designed for addressing a set of interrelated
objectives. In this case, a network usually consists of several types of gauges and stations. For example, a
flood-warning network might include both stream and stage gauges, meteorological stations, precipitation
network, snow courses and agrometeorological stations and posts providing information on the state of soil
cover (soil water storage at various horizons, soil freezing depth, etc.).
Today, more than ever before, the range of hydrological networks’ objectives and the uses of
collected data has extended. Along with conventional uses of hydrological information, such as water
resources assessment, project design, water resources planning, hydrological forecasting and water quality
control, such applications of hydrological data as environmental monitoring, flow accounting and monitoring
of water quality in transboundary water bodies, development of local hydrological forecasting and flood-
warning systems, monitoring of water allocation processes and provision of data for management of water
utilization systems are gaining in importance.
Hydrological network optimization is a slow and evolutionary process, starting with a minimum
number of stations, and increasing gradually (as necessary) until an optimum network is attained. An
optimum network is achieved when the amount and quality of data collected and information processed is
economically justifiable and it meets the users’ needs.
1. Evolution of methods for hydrological network design and optimization
Most consideration to the issues of hydrological network design and optimization was given in the
USA, Russia and Canada. The most comprehensive review of the history of network design since the 1930’s
up to the present was provided by the scientists from Trent University (Watershed Science Centre)( Richard
S. Pyrce, 2004), some of which is cited here.
Initially, the design of early hydrological network was governed almost exclusively for some specific
2
project, for example, flood mitigation, irrigation or dam construction. The increased need for data during the
Second World War, for economic efforts in support of the war or for military operations, led to the
realization that something more was needed than an ad hoc series of hydrological stations installed without
much reference to one another. This led to the development of a rationale for the design of hydrological
networks based on a quasi-uniform areal coverage to take account of the particular characteristics of the
element being measured. However, much of the literature on network design at that time concentrated on
offering practical advice based on experience. Nemec and Askew (1986) referred to this as the “basic
pragmatic approach”.
As early as the late 1930’s, the first attempts were made to use statistical estimates of error in
computing areal precipitation as a basis for choosing optimum gauge density (Wilm et al., 1939).
In Russia, the first attempts at network design were made at the State Hydrological Institute (SHI). In
1934, the Director of SHI V. Glushkov proposed an approach based on a so-called geographic-hydrological
method (Glushkov, 1933). One of the principles for network design was to satisfy spatial and linear
interpolation of hydrological regime elements. This approach was further developed by I. Karasev (1968,
1972, 1980,1988).
Main principles and criteria for establishing an optimum network suggested by Karasev are based on
continuous representation of fields of hydrological elements. Optimum network design on rivers with natural
or slightly disturbed regimes is based on continuous representation of a field of hydrological elements which
can be assessed by zonal stream-flow characteristics. This can be achieved by establishing most of the
stations so that they close zonal-representative areas of watersheds (Azr). Density of stations, i.e. distance
between central points of the basins, should offer a possibility to accurately estimate discharge characteristics
in ungauged basins. At the same time, stations should be located far enough from each other so as to detect
changes (gradient) of a norm of a hydrological element. On the assumption of homogeneity of the field of
elements within a hydrological region, two main criteria, correlation and gradient, for watershed area closed
by a station were suggested. Optimum watershed area Ao covered by one station should satisfy the
following relation:
Аgr ≤ Ao < Ac,
Where Agr и Ac are the gradient and correlation criteria satisfying correspondingly the smallest and the
largest distance between the centres of the basins under consideration.
On rivers with watershed area A < Ao (small azonal) and for large rivers with A > Ao, networks are
designed depending on the aims of studying conditions of formation and forecasting.
In most cases, optimum value of Aо corresponds to medium watersheds for which zonal type of
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discharge formation is characteristic. For small (azonal) rivers with watershed area A < Aо, large
(polyzonal) rivers, with A > A î , and rivers with human-affected discharge, a site by site principle depending
on the structure river systems would be justifiable. Most early approaches to planning and optimization of
hydrological networks were based on a conclusion that a network should be comprised of two parts: a group
of base stations including those with continuous time-series, and a group of secondary stations to be operated
for relatively short periods (5 to 10 years) until sufficient data are collected to provide reliable correlation
with factors observed at base stations. Optimum networks should also provide methods for determining with
any required accuracy streamflow characteristics at any ungauged point.
In the late 1970’s and 1980’s, statistical approaches and regression analysis had widespread
application in network design (Moss and Karlinger, 1974; Benson and Matalas, 1967)
Moss and Tasker (1991) compared and tested two U.S. based network design technologies: 1) the
Network Analysis for Regional Information (NARI) (Moss et al., 1982; Moss and Tasker, 1991)) and 2) the
Network Analysis Using Generalized Least Squares (NAUGLS). Both methods have a common objective: to
maximize regional information within a limited budget and time horizon. NARI evolved to fill a need
highlighted by a national study of the U.S. Geological Surveys’s streamflow data collection program (Benson
and Carter, 1973). The NARI method is based on a regional regression approach (Benson and Matalas, 1967)
for the definition of streamflow parameters, and its output is and evaluation of the likelihood of various
levels of improvement in the regression relations that may that may be obtained by the collection of
additional streamflow data. The strength of this approach is that a stream gauge manager can develop a
network strategy based on any one of a combination of stations.
The NAUGLS procedure used a generalized least square estimator proposed by Stediner and Tasker
(1985) to estimate parameters of a regression model of stream flow characteristics on physiographic
characteristics.
Further attempts to design networks applied socio-economic approach and the information theory.
Mawdsley et al. (1990) discussed a design procedure using a simplified Bayesian decision theory model to
examine the economic value of data for the design of flood protection hydrometric network.
Various methodologies have been recently developed for practical application in hydrological
network design. Network design theory continues to develop constantly evolving new approaches making
maximum use of statistical and regression methods.
Hydrological observation data should provide computations and forecast of hydrological
characteristics for certain basins with account of their area and physiographic features. Therefore,
4
hydrological network should represent the impact on hydrological regime of both zonal and azonal factors as
well as natural anomalies of a region.
The existing methods of calculating discharge form ungauged river basins and basins with short
observation periods are based on the method of hydrological analogy. Therefore, the key criterion in solving
the problems of efficiency of a hydrological network is the possibility to select reliable analogues to
ungauged rivers of a region.
As hydrometeorological processes develop within geographical space, it is feasible to use state-of-
the-art GIS-technologies to describe them objectively (Bobrovitskaya et all, 2003; 2004].
A state-of-the-art HYDRONET technology developed in Russia (Bobrovitskaya, Kokorev at all,
2001; Bobrovitskaya, Kokorev at all, 2004, 2009) enables one to:
1) reveal homogeneity in observation series;
2) obtain quantitative estimates of representativeness for each gauging station used in the analysis;
3) explore the “the effective relationships” with correlation coefficients that make it possible to use
them directly in computations to extend observation series;
4) calculate errors of interpolation of a study hydrometeorological characteristic (maximum,
minimum annual water flow and sediment discharge or meteorological characteristics, such as precipitation,
air temperature and others) at each node of a standard network depending on the number of stations and
natural variations of a study characteristic;
5) depict the results of estimation of interpolation errors on a map;
6) analyze the distribution of interpolation errors on a map with account of location of population
centres, motor- and railways, deposits, power lines, pipeline routes etc in order to identify the number and
location of gauging stations to establish or renovate.
Besides, the tool provides a diversity of functions to be used in hydrological computations (annex 1).
Among the basic analytical techniques used in network design in the present time are:
a) cartographic analysis;
b) correlation and regression methods;
c) probabilistic and deterministic modelling;
d) regionalization techniques.
Each method has particular applications and the choice depends on the type of problems to be
addressed, limitations of observation data, planned expenditures, population density and economic potential
of a region, etc. In Russia, a genetic principle making use of cartographic analysis and regionalization
techniques was applied in hydrological network design. Fundamental research into the problem of zoning of
5
the Russian territory with respect to hydrological regime formation, types of river recharge, intra-annual flow
distribution, etc. (Kuzin, 1960) was initiated in the period of the hydrological network formation.
By the late 1940’s and 1950’s, expanding international cooperation led to increased interest for
intergovernmental organizations to offer guidance on technological development. The World Meterological
organization (WMO) responded by the late 1950’s by initiating a program on operational hydrology and by
1965 published the first “Guide to Hydrometeorological Practices” which included a chapter on the “Design
of Networks” (WMO, 1965). In 2008, a revised fifth edition of the Guide was published.
Since it has been recognized that establishment of a full-scale and complete network is either
impossible or impractical in today’s world (Guide, 2008), various surrogate approaches are used instead of
designing a full-scale network providing information for addressing any objectives. For example, a common
substitution is to maximize information content in lieu of optimizing the economic value of the data (Guide,
2008). If information is used properly, it can be expected to contribute to the economic worth resulting from
a decision. It is quite obvious, however, that economic impact of information is not linearly related to its
magnitude. This is not applicable to areas with dense hydrological network but would prove useful in poorly
gauged basins.
The WMO advocated that an optimum network should not be attempted until a minimum number of
stations had not been established. This minimum network is intended as a first step to satisfy the most serious
gaps, from the perspective of water resources development. Because of the small density of the minimum
network, it is important that the records at all stations be of good quality.
Major indicator of adequacy is the area covered by observations from each gauge in a network.
According to the WMO recommendations, the density of hydrological network should provide reliable
determination of hydrological characteristics within a certain region. Recommended minimum network
densities for various physiographic regions are given in the Guide (2008).
Most recently, Perks et al. (1996) studied the adequacy of hydrometeorological observations in six
physiographic regions identified by WMO. It was found that the WMO recommendations for minimum
density were not reached in all the regions. Network densities of polar, arid and coastal regions are close to
the recommended ones, while mountainous and inland regions have densities 3 to 5 times lower than those
recommended by WMO.
On the whole, different countries and regions use different approaches to network planning, which
will be illustrated here by several examples.
2. Principles of hydrological network optimization with regard to economic and geographical
conditions of individual countries
2.1 Recent approaches to network design
6
The United States hydrometric network.
Since 1889, the U.S. Geological Survey (USGS) has operated a multi-purpose stream-gauging network.
Today the USGS operates and maintains more than 85% of the U.S. stream gauging operations, including
over 7,000 continuous-record stream gauging stations in the United States, Puerto Rico, and the Trust
Territories of the Pacific Islands. The principles that have guided the USGS network are that:
• many partners contribute funding for the operation of gauging stations to collaboratively achieve
federal mission goals and the individual goals of the funding agencies;
• all data is freely available to all partners and the public;
• the USGS operates the network on behalf of all partners to achieve economy and standardization of
the availability and quality of data.
Five key categories of federal purposes of the stream gauging network are:
1. Interstate and international transfers – measures the ability of the network to provide accepted,
neutral data for the U.S. to use in the allocation of water transferred across the lines or
international borders.
2. Water budgets – the goal is to be able to account for the contribution of water from each river
basin to water resources of the country and playing a fundamental role in national water
policies and planning.
3. Flooding – the goal is to provide streamflow information for populations at risk from
flooding. Real-time information is needed to provide current streamflow conditions to guide
emergency decisions and to provide information critical to produce accurate and timely flood
forecasts and flood zoning maps.
4. Water quality.
5. Long-term changes – the goal is to monitor and characterize trends in streamflow in
representative streams within each of the nation’s ecoregions.
At the end of the last century the USGS developed a national NSIP program (The National
Streamflow Information Program).
At the core of the NSIP is a set of the USGS-funded stream gauges that are continuously operated to
fulfill five Federal Goals:
1. Interstate and International Waters (506 stations);
2. Streamflow Forecasts (3,245 stations);
3. River Basin Outflows (445 stations);
4. Sentinel Watersheds (874 stations);
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5. Water Quality (210 stations).
The proposed NSIP network would have approximately 5,280 stream monitoring gauges, of which
approximately 1,350 would be new or reactivated gauges. Under full NSIP implementation stream gauges in
the network will have:
• real-time data delivery;
• the ability to withstand the impact of a 200-year flood and still be operational;
• provide accurate data fro the full range of anticipated flows.
An original approach was used for the Maryland’s stream gauging network modernization (Cleaves
and Doheny, 2000). The network plan had been guided by discussions and recommendations of a
stream-gauging workshop and by 102 responses to a questionnaire sent to 500 users of streamgauge
data in 1998. Recommendations in November 1999 included that Maryland’s streamgauging
network be increased from 97 gauges to 157 gauges.
The additional gauges were to be activated in stages according to six priority
management goals:
1. Core network (20 gauges to be reactivated, 2 new gauges)
2. Small watersheds (11 gauges to be reactivated, 10 new gauges)
3. Coastal plain harmful algal blooms (7 stations to be reactivated, 1 new gauge)
4. Flood Hazard (2 stations to be reactivated, 3 new stations)
5. Clean Water Action Plan (2 new gauges)
6. Unmet Coverage (2 new gauges).
The Canadian hydrometric network. The Canadian Federal Hydrometric Network was established in the
1890’s. Since the mid-1960’s up to the mid-1970’s, global concern was raised of the needs of hydrometric
data which led to a substantial increase in the number of hydrological stations. By 1975, the Canadian
hydrometric network expanded to 3,300 stations, and then during the 1980’s the number of stations remained
relatively stable. A national survey of users of hydrometric data (Environment Canada, 1989) found that
there was a shortage of stream gauges in Canada. It was determined that 2,000 new stations would meet the
current and future information needs. However, instead of continued growth of the Canadian hydrometric
network, cuts to the network were beginning to appear by the early 1990’s due to increased budget pressure.
An initial federal government budget reduction of 35% was anticipated to result in the closure of 1,100
hydrometric stations across Canada over a three year period starting in 1995/96. A Water Monitoring
Program Re-Engineering Strategy was developed by the Federal Government (Yuzyk et al., 1995) to focus
8
on seven key items: rationalization, integrated planning, harmonization, modernization, commercial services,
organization, and people. It was decided that all future monitoring would emphasize information production,
be results driven, client focused, and minimize net costs, thus the strategy applied a business approach to
monitoring based on the true costing of services. The actual stream gauge rationalization resulted in a total
network reduction of 21% or 724 gauging stations; the provinces experienced similar pressures resulting in a
19% reduction in provincially operated stations between 1990-1998. Federal funding for the network had
declined since the mid-1970’s; in 1975, the federal funding proportion was 60%, by 1989 it was 48%, and by
1998 it was only 41%, ultimately contributing to a reduction of stations within the network.
The intent was to “moth-ball” stations, rather than decommission them. Environment Canada initiated
a series of cooperative ventures to rationalize the network including consultations with federal departmental
managers, provincial partners, improved management approaches, expanded partnerships, and alternative
delivery mechanisms (Pilon et al., 1996). The rationalization process was also aimed at establishing which
sites would continue to be important from an environmental perspective. The key issues facing the future of
the Canadian hydrometric network were identified as:
I) flow prediction capabilities,
II) climate change,
III) water export,
IV) ecosystem health.
Strengthened partnership would be necessary to sustain and enhance the network, and a comprehensive
evaluation of the economic value of Canada’s hydrometric value would be necessary. Environment Canada
decided to focus its attention on national and international levels of ecosystem health, to be pursued through
a strong support for long-term studies that contribute to the prediction of climate change impacts on
Canadian hydrology.
Generally, about 80% of the active hydrometric stations were initially constructed to serve a specific
water management purpose, however over time the data from these stations also served other interests. The
remaining 20% of the hydrometric stations were strategically located to document hydrological
characteristics and processes required to understand the regional hydrology. Currently there are 2,500 water
level and streamflow stations being operated under the Federal-Provincial and Federal-Territorial CSA; more
than 720 are designated as federal stations, about 980 as provincial or territorial stations, and 781 as federal-
provincial or federal-territorial stations. A further 92 stations are fully cost-recovered from other parties, and
another 302 stations are contributed by other organizations, bringing the total number of active stations to
~2,870. An additional 5,500 hydrometric stations are no longer active, although their data are stored in the
accessible HYDAT database (Water Survey Branch, 2002).
9
Most of the hydrometric stations are located in the southern half of the country where population and
economic pressures are the greatest; as a result, the adequacy of the network to describe hydrologic
characteristics decreases significantly to the north. The federal Canadian hydrometric network was fully
modernized with employment of new field methods and technologies, advanced data management, and real-
time on-line access to hydrometric information.
The European Union. The overall objective of the European Environmental Agency (EEA) is to “obtain
timely, quantitative and comparable information on the status of inland waters from all EEA member states
so that valid temporal and spatial comparisons can be made and so that key environmental problems
associated with Europe’s inland waters can be defined, quantified and monitored”. The primary focus of the
EEA is water quality, however the network also addresses surface water and groundwater quantity. Europe
has a dense network of approximately 19,000 flow measurement stations at an average density of one station
per 270 km2, which is justifiable considering Europe’s wide physical diversity, the anthropogenic factors of
population density and land use, and river types and hydrograph regimes.
Two broad categories of water quantity monitoring stations are considered:
1. Statutory monitoring arising from national or international obligations, or to provide
information for the business and operational needs of the regulators, suppliers, users and
reclaimers of water;
2. Surveillance monitoring to characterize and allow appraisals to be carried out on the state of
water resources, and in conjunction with water quality measures and biodiversity, and the state of
the water environment.
A general surveillance network to obtain information on the general quality of rivers within the EEA
would consist of:
1. A basic network made up of approximately 1,425 (80%) Representative (or Index) rivers that
are a subset of the network and ideally provide long-term summary estimates of the regional or
national picture (selected on the basis of 1 gauge/2,000 km2), and about 355 (20%) Reference
rivers which characterize hydrologic regimes in undisturbed catchments (selected on the basis of
1 gauge/2,000 km2).
2. An Impact network to record and characterize the effects of anthropomorphic interference with
natural hydrological regimes, consisting of approximately 1,590 rivers selected, where for < 50
inhabitants/km2, there would be one river per 10,000 km2 and for >100 inhabitants/km2 there
would be one river per 1,000 km2.
3. Approximately 450 Baseline rivers with catchment areas greater than 2,500 km2, to characterize
10
the general runoff behavior of a region. Additional important rivers/canals in each country
should also be included bringing the total up to 650 rivers. The results can be extrapolated to
characterize other ungauged sites.
4. Approximately 100 Flux rivers to assess sediment loads or contaminants entering Europe’s seas
or crossing international boundaries in conjunction with other quality measurements.
Nixon (1996) described a stream gauge network design for the EEA. He suggested a so-called
stratification technique. For example, a statistical population of all rivers (e.g. all rivers in Europe) can be
subdivided in to sub-populations (e.g., all the small, high altitude streams in Europe) and random site
allocation can be applied to each sub-population (strata) separately. Stream order was suggested as an
indicator of a river size. Using this approach the number of river reaches/river lengths meeting the criteria
associated with each of the matrix cells would have to be defined, likely involving a GIS database of the river
network.
The Finnish surface water monitoring network. During the late 90’s, the monitoring objectives and
structure of the Finnish network were clarified to improve cost-efficiency (Puupponen, 1998). A decision
was made to concentrate on water balance stations, spatial estimation stations for the transfer of discharge
data to small natural catchments, and operational stations for the daily operation of water resources projects.
The evaluation recommended a remarkable network reduction of 321 stations out of the existing 721 to be
either closed or removed from the national network. However the number of closed stations was only 50
stations and the remainder continued operating primarily outside the Water Resources Administration.
The third step comprised of statistical analyses of the spatial estimation stations and a decision was
made on the future extent of this sub-network. Cluster analysis and the Network Analysis Using Generalized
Least Squares NAUGLS (see Moss and Tasker, 1991) were applied to mean discharge and various extreme
discharge parameters. The resulting conclusion was to reduce the network down to 397 stations. The annual
costs of the Water Resources Administration for the operation of the new modernized national hydrometric
network decreased by approximately 32%.
2.2. The Russian hydrological network.
Federal Service for Hydrometeorology and Environmental Monitoring of the Russian Federation
(Roshydromet) is the federal executive body that provides state services in the field of environmental
monitoring, including hydrological regime of surface water bodies (river, lake and reservoir water regime). In
order to study water regimes and monitor hydrological processes, a network of hydrological stations and
posts was established in the Russian Federation. Roshydromet operates 24 Interregional Territorial Branches
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(UGMS).
The Russian hydrological network began to develop as early as the 1874’s-1884’s. By 1914, the
network expanded to 1,134 stations, of which 202 performed monitoring of stream flow. Initially, as in many
other countries, the Russian hydrological network was designed to address specific objectives. At the first
stage, it was intended for monitoring hydrological regimes for the purposes of construction of railways,
railway river crossings, dams, etc. It was only in 1908 when a hydrological service was organized in Russia
after a devastating flooding of the Ob River which hit all central provinces and caused extensive damage and
loss of life. A number of stations were put into operational regime in order to produce regular hydrological
forecasts.
By 1929, all stations were integrated into a basic observation network, and the number of stations
increased to 2,708 (863 for streamflow monitoring).
By 1940, the number of stations in the former USSR network was 4,247 including 2,021 for
streamflow monitoring. However, this number still did not meet the demands of practical hydrology and the
developing economy, and a new network development plan was adopted in 1940 envisaging expanding of the
network to more than 10,000 stations.
During the Second World War, many stations were destroyed, and their total number somewhat
decreased compared with 1940, but immediately after the end of the war, a second prospective development
plan was adopted in 1946 which was completed by 1962 bringing the total number of stations to 6,143, of
which 4,766 performed monitoring of stream flow.
The third development plan adopted in 1974-1975 outlined further development of the network.
Although the plan was to be fully implemented by 1990, the network expanded to 7,083 hydroposts (5,478
for streamflow monitoring) already in 1980, resulting in an optimum number of stations envisaged by the
first development plan.
In the period after 1990, the former USSR experienced substantial economic difficulties which led to
a drastic reduction of the observation network. In the end of the 1980’s, the network reduced severely by
31%. During the last decade, the reduction ceased, and the Russian hydrological network is currently
gradually recovering (see Table 1).
Table 1 Changes in total number of hydrological stations and posts in 1986-2010
YearNumber of active Type
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stations river lake
1986 4481 3967 514
1992 3670 3262 408
1995 3423 3037 386
1997 3114 2752 362
1998 3089 2733 356
1999 3053 2703 350
2000 3059 2708 351
2010 3069 2715 354
Table 2 shows current quantitative and qualitative characteristics of the Russian network by UGMS.
As for qualitative characteristics, there are 2,715 (88.5%) river stations and 354 (11.5%) lake stations. Stream
flow is observed at 2,165 (70.5 %) stations (GP1), and sediment discharge at 688 (22.4%). The Russian
hydrological network now comprises 1,283 reference stations and 1,433 basic (noncontinuous) stations
funded from the Federal budget. There are also 354 supplementary stations (SS) fully cost-recovered from
various organizations.
The structure, composition and methodologies applied in the Russian hydrological network are
regulated by prescriptive guidance (or guides) providing uniformity and compatibility of observation data.
Division of stations into reference and noncontinuos (or basic) ones enables one to initiate or cease
observations in one sites ensuring their continuity in others.
Reference hydroposts are the most essential having long observation series which may be used in
various generalizations, national water resources assessments, water regime studies, as well as for developing
techniques of hydrological forecasting, including hydrological models. These amount to only 42% of the
total number of stations.
Table 2 Composition of the Russian hydrological network as of 01.10.2010
Number of active
stations in 2010 Information Reference Basic Suppl. UGMS
total GP SS GP1
Sediment
discharge GP SS GP SS GP SS GP SS
13
1 2 3 4 5 6 7 8 9 10 11 12 13 14
Bashkiria 68 58 10 50 17 46 5 21 5 36 5 1 -
Upper-Volga 110 93 17 83 21 85 17 27 1 53 13 13 3
Far East 158 153 5 88 21 112 5 65 70 5 18 -
Transbaikalia 185 174 11 147 51 91 3 114 8 58 1 2 2
West Siberia 222 197 25 169 72 101 8 80 5 74 13 43 7
Irkutsk 181 136 45 98 36 87 37 69 26 57 18 11 1
Kaliningrad
CGMS 15 15 - 13 - 5 - 7 - 5 - 3 -
Kamchatka 80 80 - 74 25 46 - 46 - 9 - 25 -
Kolyma 42 38 4 25 8 28 - 12 1 25 3 1 -
Murmansk 55 40 15 40 1 30 14 19 9 21 6 -
Ob’-Irtysh 162 147 15 96 36 92 62 2 69 6 16 7
Volga 102 83 19 73 48 60 16 26 6 37 11 20 2
Maritime 74 71 3 55 15 66 3 41 1 26 2 4 -
Sakhalin 41 41 0 37 3 25 - 17 - 24 - - -
North 228 216 12 173 6 180 10 94 10 105 1 17 1
North-West 218 175 43 154 5 83 31 70 17 82 18 23 8
North Caucasus 254 238 16 199 135 126 11 87 4 117 12 34 -
Mid Siberia 219 195 24 158 74 128 14 74 8 120 16 1 -
Tatarstan 33 21 12 21 7 18 12 5 4 15 8 1 -
Ural 144 115 29 94 0 99 23 38 11 58 13 19 5
Central 192 160 32 115 25 106 21 57 8 90 20 13 4
Central
Chernozem 87 84 3 76 27 67 2 33 - 42 3 9 -
Chukotka 18 18 - 12 7 15 - 9 - 7 - 2 -
Yakutsk 181 167 14 115 48 117 6 79 5 52 7 36 2
Total: 3069 2715 354 2165 688 1813 238 1152 131 1252 181 312 42
As it was already defined, major indicator of a network adequacy is the average area served by one
hydrological station, which is also referred to as hydrological network density. As of 1.10.2010, the Russian
hydrological network density was 1 station per 5,250 km2, with 1 station per 7,860 km2 for information
14
network solely (Table 3). Fifteen years ago the network density was 1 stations per 3,400 km2 in comparison
with the US network density of 1 station per 1,338 km2, the Canadian per 3,691 km2, the French per 203
km2, and the Japanese per 67 km2.
Table 3. Hydrological network density by UGMS
Area served by one
station, km2
№ UGMS Populatio
n density,
inh/km2
Total
number of
stations
Number
of
informatio
n stations
informatio
n network
whole
network
1 Bashkiria 28.5 68 51 2813 2110
2 Upper-Volga 30.0 110 102 2577 2390
3 Far East 2.12 158 117 10290 7620
4 Transbaikalia 2.73 185 94 8148 4140
5 West Siberia 11.1 222 109 7892 3875
6 Irkutsk 3.36 181 124 6123 4195
7 Kaliningrad CGMS 63.2 15 5 3000 1000
8 Kamchatka 0.76 80 46 9130 5250
9 Kolyma 0.40 42 28 16095 10730
10 Murmansk 6.16 55 44 3238 2590
11 Ob’-Irtysh 3.5 162 92 27047 15360
12 Volga 30.5 102 76 4711 3510
13 Maritime 12.5 74 69 2402 2240
14 Sakhalin 6.28 41 25 3485 2125
15 North 3.15 228 190 5969 4974
16 North-West 23.0 218 114 3136 1640
17 North Caucasus 44.0 254 137 4357 2350
18 Mid Siberia 0.85 219 142 23843 15460
19 Tatarstan 55.6 33 30 2409 2190
20 Ural 25.7 144 122 3925 3325
15
21 Central 63.0 192 127 4452 2945
22 Central Chernozem 44.8 87 69 2459 1950
23 Chukotka 0.07 18 15 49180 40983
24 Yakutsk 0.3 181 123 25090 17050
Total: 3069 2051 7860 5250
In 2006, Roshydromet began to implement a project “Modernization and technical re-equipment of
Roshydromet’s institutions and organizations”. The project is aimed to improve the level of services in the
field of hydrometeorology and other related fields provided to the government of the Russian Federation,
other authorities, and population through re-equipment of its technical and technological facilities and
strengthening of institutional and management structure. Three pilot network modernization projects are
being currently implemented in the Kuban, Oka and Ussuri river basins.
Modernization objectives being addressed under the above mentioned projects include optimum
design and re-equipment of hydrological stations with modern instruments for water level and discharge
observations, including automated hydrological stations for water level, flow velocity and discharge
measurements.
2.3 Hydrological network modernization and optimization: case-study of the Kuban River
Optimization of hydrological networks in each of the above mentioned regions was governed by
general principles developed by the State Hydrological Institute. The principles take account of physiography
and socio-economic features of the regions. Optimum location of reference and basic (noncontinuous)
stations was evaluated to satisfy the requirements of spatial and linear interpolation of the hydrological
regime characteristics with the use of correlation and regression analyses. Optimum location of the
information hydrological network (IHN) was analyzed to meet more extensive set of requirements.
Data observed at the IHN are intended for hydrological forecasting services and providing the
population with timely warnings on the state of water bodies, floods and other extreme hydrological events,
as well as for provision of information for water-economy complexes. The IHN stations are either included in
the basic hydrological network or purposely established.
The whole Kuban basin is divided into upper, middle and lower reaches depending on physiographic
characteristics and the level of economic development.
Stations located in the Kuban upper reaches and the heads of its tributaries should provide data to be
16
used in the models for forecasting discharge formation of small and medium rivers in the basin. Such models
are based on the account of discharge formation factors of a watershed and use large input datasets including
data on snow water content, precipitation, soil moisture, etc. Distributed-parameter models are particularly
sensitive to network densities (1 gauge per 200 to 400 km2) and the content of observations.
Regression models using discharge characteristics of small and medium rivers as predictors are
commonly used for outlets. Usually, such models are well enough provided with data derived from the IHN.
Moreover, an opportunity exists to select just a few the most informative stations depending on the type of a
forecasting model applied.
In order to provide information for flash flood simulation in the Kuban basin the following was
suggested:
• to establish several automated stations in areas with elevation more than 1,500 m, primarily in the
upper reaches of the Ullukam, Uchkulan, Teberda, Aksaut, Bolshaya Laba and Pshish rivers.
• to establish automated meteorological stations at the same sites and simultaneously with the
automated hydrological stations;
• to establish several meteorological, snow and precipitation measuring sites in areas with elevation
more than 1,500 m near the Main and the Lateral Caucasus ranges, and to equip them with either
satellite or radio communication facilities to ensure timely provision of information to data
collecting centres;
• to increase the number of stations on small foothill rivers.
Timely flood forecasting is also critical for the middle Kuban. However, in contrast to the upper
reaches, different type of models enabling calculation of flood wave transformation and movement are
required. In this case, flood forecasting models use data from stations located along the length of rivers. A
chain of such stations makes it possible to forecast flood wave propagation in river systems. There is a
diversity of approaches to solving such tasks. One of the simplest and most common methods is the method
of corresponding levels and discharges which consists in establishing a regression relationship between these
characteristics at adjacent stations. Stations at this reach of a river should be located to meet the requirements
of the lead-time of a forecast which is determined by lag time of a flood wave.
For the middle and upper Kuban, a crucial task to be solved when designing a network is provision of
real-time information (both calculations and forecasts) for water resources utilization systems. One of the
most developed water resources utilization systems – Krasnodarskoye reservoir, with a number of water
distribution units and high regulating storage capacity, is located in the middle and lower Kuban. The
17
hydroposts located in these reaches should meet the objectives of water level monitoring and control and
forecasting flash flood propagation, as well as should ensure reliable calculations and forecasting of inflow to
hydraulic structures and the Krasnodarskoye reservoir.
To meet these needs, 18 new hydrological stations were established, and modernization of already
existing stations was initiated with installation of automated hydrological stations for continuous water level
monitoring and transmission of the observed data to the purposely established data collection centre in
Rostov-on-Don (see Figure 1).
Figure 1 – Location of operating and newly established stations of the North Caucasus UGMS in the
Kuban River basin
Conclusions
It seems obvious that decisions on designing comprehensive observation systems can be made only in each
specific case with due account of socio-economic conditions and attraction of investments of interested
authorities and branches of national economy.
Optimum network design involves, first of all, identification of zonal and azonal elements in the
hydrological process and separation of the specific from the general. This task can be solved through
18
hydrological zoning of an area. Hydrological zoning consists in classifying regions with regard to uniformity
of physiographic and hydrological conditions, which offers a possibility to make a proper generalization of
main regime characteristics within each region and extrapolate them to ungauged basins using methods of
hydrological analogy. Hydrological zoning is based on the homogeneity of discharge formation conditions
which is estimated from interrelations between water balance elements. Hydrological zoning of an area takes
account of medium and small rivers comprising the majority (98-99%) of a channel network. As a result,
each part of an area under consideration should be included into one of the hydrologic regions. Basic
hydrological network should be designed to comply with principles of optimum spatial and temporal
resolution of observations.
As is known, reliability of hydrological characteristics depends not only on the accuracy of
observations, but also on the mathematical background for interpretation of the results. Therefore, a need
arises to optimize not only networks and means and methods of observations, but also procedures and
techniques of data processing, especially with regard to on-line data processing.
Information hydrological network should provide data for flood forecasting models as well as models
for calculation and forecasting of inflow to hydraulic structures and reservoirs. Currently, the Russian
information network does not to a full extent meet the requirements of the communities, water-economy
complexes, agriculture, recreation, and others. Information on the state of a river is transferred first of all to
data collection and forecasting centres, and only after that it returns to local users in the form of forecasts.
That is why development of optimization procedures for data collection and dissemination is of critical
importance.
One of the most important objectives of hydrological networks is provision of observations within the
environmental monitoring system (EMS). In Russia, environmental monitoring of rivers, canals, lakes and
reservoirs is performed by the basic hydrological network and the state water quality observational network,
providing that specific types of observations required for environmental monitoring are included in its
observation program.
Location of the EMS stations is defined by the requirements of water use and water quality
monitoring. Such monitoring is performed on the basis of channel water balances, channel sediment
balances, and estimation of chemical pollutants concentration. Water quality control implies estimation not
only of concentration of contaminants and sediments, but also of their discharge over a certain period, which
enables identification and forecasting trends in hydrochemical regime. The above aspects should also be
addressed in designing optimum hydrological networks.
Summing up the above considered issues, one can mention that, in spite of the variety of requirements
to hydrological network optimization, there are no insoluble contradictions between them. As such, network
19
optimization procedures may require increased network density in some parts of a basin and reduced number
of stations in others.
It should be also noted that economic aspects such as costs to design and maintain a network should
also be taken into account in network planning and optimization. It appears that hydrological network
operation and maintenance should be funded from federal and regional budgets, but, as the analysis has
shown, many countries are now facing the problem of attracting funds from business and other entities using
hydrological information.
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ANNEX 1
FEDERAL STATE-FINANCED ORGANIZATION “The State Hydrological Institute” (FSFO
21
“SHI”)
The Valdai Branch of FSFO “SHI”
Dr. N. N. Bobrovitskaya, A. V. Kokorev, Senior Research Fellow
HYDRONET-2011:
AUTOMATED HYDROLOGICAL NETWORK DATA ANALYSIS TECHNOLOGY
WITH THE AIM OF ITS OPTIMIZATION
ST. PETERSBURG, VALDAI
2011
TABLE OF CONTENTS
22
pgs.
INTRODUCTION
1 THE PRINCIPAL FOUNDATIONS OF THE NETWORK ANALYSIS METHOD USED IN THE PROGRAM
2 INITIAL/INPUT/SOURCE DATA PREPARATION
3 THE PROGRAM STRUCTURE, ITS MAIN MENU, SELECTING THE STUDY AREA AND THE HYDROLOGICAL CHARACTERISTIC
4 THE “DATA CORRELATION” FUNCTIONAL WINDOW
4.1 Implementation of the “Correlation function” task
4.2 Implementation of the “Representativeness” task
4.3 Implementation of the “Effective Correlations” task
4.4 Implementation of the “Interpolation” task
4.5 The “Additional parameters” menu option
4.6 The “Schematic map of the network” menu option
5 THE “ANALOGS” FUNCTIONAL WINDOW OF THE PROGRAM
5.1 The “Select object” menu option
5.2 The “List of analogs” menu option
5.3 The “Correlation graph” menu option
5.4 The “Cross-integral curve” menu option
5.5 The “Chronological graph” menu option
5.6 The “Correlation analysis” menu option
6 THE “STATISTICS” FUNCTIONAL WINDOW
BIBLIOGRAPHY