Hydrological Information System, Basic Tool in Water Management and
Decision Making
Dr. Eram Artinyan, Dr. Dobri Dimitrov
Eram.Artinian@meteo.bg; Dobri.Dimitrov@meteo.bg
National Institute of Meteorology & Hydrology, Sofia
Abstract
The design, set-up and operation of water related information and
forecasting systems is of primary importance for the river basin
management. The issue is especially valid for the basins shared by two or
more countries, as mentioned in the EU Water Framework Directive. The
paper deals with the Bulgarian experience in design, setting up and
operating of some Information/Forecasting Systems at different Bulgarian
river basins as follows:
Modeling and forecast of the Maritza river flow and river basin water
and energy budget; the system consists of coupled surface scheme and a
distributed hydrological model. It can be provided with historical, real time
and forecast input meteorological data. The system is set-up for a large
region in Bulgaria – about 34000 km2.
Struma/Strymonas Flood forecasting and warning system; this is
Bulgarian – Greek research project targeting detailed investigation on
flood formation and flood forecasting due to heavy rainfall phenomena as
well as mixed rainfall – snowmelt phenomena. The project includes also
installation and operating a system of automatic telemetric hydrometeorological observation stations. Warning system set-up and operation
will follow the research project to ensure better management and safety
operation of the Kerkini Lake.
Short-range forecasting of some mountain reservoirs daily inflow; the
system is serving the peak energy production using water accumulated at
the Southwest part of the Maritza river basin. The system is in operation
since late 2000 and uses coupled meteorological-hydrological forecasting
models. The use of Limited Area High Resolution meteorological
forecasting makes possible two days lead time of the hydrological forecast.
Iskar and Yantra River flows real time monitoring; this project covers
two main Danube basin rivers in Bulgaria as a part of the cooperation
between Romania and Bulgaria in the field of hydrology.
System for automatic hydro-meteorological data processing, archiving
and presentation via Internet/Intranet: It covers mostly the conventional
hydro-meteorological data from the Bulgarian territory and presents data in
the NIMH intranet environment. Hydro-meteorological data are stored in a
database server and made accessible through a web server. This system
presents the data in tabular, graphical and mapped views. It was developed
in the frame of the Med-Hycos and WOISYDES projects.
Keywords:
database
Hydrology, forecasting, modeling, hydro-meteorological
2
Introduction
River basin management is a complex issue comprising variety of tasks and activities of
different spatial and temporal scale. Information and forecasting systems are serving the short-term
tasks of the river basin management, providing timely information about the development of the
phenomena, facilitating water management and decision-making. The tasks become much more
complex, when the trans-boundary issue is concerned, because of the necessity to consider in
addition different legislation of the countries sharing the basin, different information polices and
networks, culture and others.
1. Modeling and forecast of the Maritza river flow and of the river basin water and energy
budget.
1.1.
Description of the region
The region under consideration takes one-third part of the territory of Bulgaria – 34000 km2. It
covers the central part of South Bulgaria, between the chain of Stara Planina Mountain and the
state borders with Greece and Turkey at the south (Figure 1). The climate is continental to
Mediterranean in the valleys depending on the dominant atmospheric circulation. It has pronounced
altitude variability as the elevation is going from 50 m up to 2925 m at the pick of Mussala in Rila
Mountain.
Figure 1: Map of the Maritza, Arda and Tundja River basins in Bulgaria
1.2.
Objectives of the project
1.2.1.




Real time monitoring of the natural water balance components and river
flow forecast at predefined locations
One to two days river flow forecast for the most endangered locations.
To provide real time diagnosis of the river flow over a large region of the country.
To evaluate the snow height and snow water content in real time
Soil moisture evaluation for hydrological and agronomical purposes
1.2.2.
Real time monitoring of reservoirs and channels water balance, and of
water table level

To analyze and predict reservoirs water inflow in order to help the decisions of water
supply authorities
3

1.3.
Long term forecast of the underground water level and low-level river flow in order to
prevent the shortage of water for irrigation and water supply.
Short description of the models used
1.3.1.
High precision short-range numerical weather prediction model –
ALADIN
Aladin short-range NWP model has been operating at the NIMH since May 1999. The
numerical weather prediction model ALADIN (http://www.cnrm.meteo.fr/aladin/) - has been used
as operational model in Bulgaria since June 1999. The weather forecast for 48 hours over the
Balkan Peninsula is computed twice a day using as initial conditions the predictions for 12 and 00
UTC of the French global model ARPEGE (Action de Recherche Petite Echelle Grande Echelle).
The horizontal resolution of ALADIN is approximately 12 km, with 31 levels vertically. The model
is widely used in Europe.
1.3.2.
Land Surface Scheme – ISBA (Interface Soil Atmosphere Biosphere)
The ISBA surface scheme was developed for the climate, mesoscale and prediction
atmospheric models used at Météo-France (http://www.cnrm.meteo.fr/mc2/). It aims to represent
the main surface processes in a relatively simple way: it solves one energy budget for the soil and
vegetation continuum, and uses the force-restore method (Deardorff, 1978) to compute energy and
water transfers in the soil. Evapotranspiration is computed through four components: interception
by the foliage, bare soil evaporation, transpiration of the vegetation (with a stress function
computed using the method proposed by Jarvis (1976) and sublimation of the snowpack. Two
fluxes of water in the soil are computed: a surface runoff (RO) and drainage (D) (Figure 2). ISBA
was coupled with the distributed hydrological model Modcou (Habets et al. 1999a, 1999b).
Figure 2: ISBA land surface scheme coupled with MODCOU macroscale hydrological
model.
4
1.3.3.
Distributed regional scale hydrological and hydro-geological model –
Modcou
The macro-scale hydrological model MODCOU was used in several applications (Ledoux et
al., 1989). MODCOU takes into account a surface and the underground layers. The surface routing
network is computed from the topography, using a geographical information system (Golaz, 1995).
The surface and underground domains are divided into grid cells of size 1, 2, and 4 km. The
transfer between two grid cells is estimated by using the topography. The surface runoff computed
by ISBA is routed to the river network (Figure 3) and then to the gauging stations using
isochronous zones with a daily time step. The drainage computed from ISBA contributes to the
evolution of the groundwater table, which evolves according to the diffusivity equation. The
exchanges of water between the groundwater table and the river are computed according to simple
relations (Ledoux, 1980). At the end, the flows from the surface layer and from the groundwater
table form the riverflow at the gauging stations.
Figure 3: River network (blue) and area with existing water table (red). Gauging stations are
shown with green squares.
1.4.
Achieved project objectives
1.4.1.
Analysis of the project feasibility
The overall analysis has shown that except the precipitation field estimation, which
contains the higher error, all other fields could be used without special transformation. To correct
the effect of the precipitation field on the water balance the measured precipitations could be used
through sequential update of the soil moisture and other ISBA variables with that ones computed
by using measured precipitations.
1.4.2.
Automated field preparation
For the implementation of the two dimensional surface scheme and the distributed
hydrological and hydro-geological model two-dimensional fields of meteorological variables are
needed. In this case, most of them come from the ALADIN HRM but the precipitation field being
the most critical is also computed on the base of near real time measurements. The real time
processing of all the required fields has to be automated in order to supply the models with the
needed input information.
5
1.4.3.
Adaptation of ISBA-MODCOU coupled system for using Aladin
precipitation fields
The use of Aladin precipitations only was expected to produce largely overestimated
runoff, caused by the overestimated precipitation. That is because the initial conditions (soil
moisture, soil temperature, snow density and height) had to be corrected after one or two days of
surface scheme integration. The values for the re-initialization were taken from another ISBA
integration having a delay of one or two daily steps (Noilhan, 2002), which was using measured
precipitations instead of Aladin outputs.
1.5.



Conclusion
High resolution, short-range outputs from Aladin model can be used for the purpose of
hydrologic modeling.
For the forecast use, it is not possible to avoid inclusion of real and near-real time measured
precipitations.
The update of the ISBA land surface scheme variables (soil moisture, soil temperature, snow
height and density etc.) have to be made at the shortest possible intervals, which is driven by
the availability of new real time 2D precipitation fields.
2. Struma / Strymonas Flood Forecasting and Warning System
Struma is a mountain river flowing from North to South, from Bulgaria through Greece up to
the Aegean Sea. It generates flush floods of snowmelt – rainfall type mainly in the late spring.
Following the strong demand of Greece a project was started aiming to build the basis of a flood
warning system, which should facilitate reservoir management downstream Bulgarian border,
allow secure handling of the floods in Greek territory and generally decrease the flood hazard. The
activities planed include installation of automatic telemetric hydro-meteorological observation
network, review of the results of relevant projects, analysis of historical hydro-meteorological data,
design and calibration of flood forecasting models, prove the possibility to issue flood warnings
with certain lead-time and accuracy.
2.1.
Introduction
Struma is collecting waters from four countries (Yugoslavia, Bulgaria, Macedonia and Greece),
flowing from North to South up to the Aegean Sea. Considerable part of the river basin is situated
in northwest Bulgaria (fig. 4.), having an area of more than 10000 km2 and average elevation about
900 m a.s.l. It is a mountain basin with steep slopes and relatively small concentration time,
generating flush floods of snowmelt – rainfall type mainly in the late spring. Flood warnings are
needed generally for the Greek lowlands to facilitate reservoir management downstream, allow
secure handling of the floods in Greek territory and generally decrease the flood hazard.
Some real steps in organizing flood forecasting/warning system for the Struma river basin started in
early 1990, when project briefs prepared by one of authors of this paper were presented to the
Greek side. The WMO expert Dr. Alesh Svoboda during his advisory mission in 1992 prepared a
project document related to flood forecasting for the Bulgarian-Greek border basins of Mesta and
Struma, calling for UNDP support. The AUA Greek experts Prof. Karakatsoulis and Dr. Mimidis
prepared in 1990 project proposal for Struma/Strymonas Flood Warning System. As a result the
joint Bulgarian-Greek Intereg II – Phare CBC Committee found the problem as important one and
gave start to research activities to be implemented by Bulgaria and Greece, which should prove the
possibility to issue flood forecasts and warnings with acceptable for the practice lead-time and
accuracy. For that purpose, the Bulgarian Phare CBC Program organized an international tender
(project BG9803-030202) for delivery and installation of equipment for the Struma Flood Warning
and Forecasting System in late 1999. The Greek company ScientAct SA was selected and
successfully installed the equipment in early 2001 with the assistance of the National Institute of
Meteorology and Hydrology, which is beneficiary of the project.
6
It should also be noted that the development of the WMO Med-Hycos project significantly
facilitated the above one providing guidance, practices and the first automatic telemetric station in
the basin (Figure 4).
The present paper is giving information on the activities of the side in the design and
establishment of the telemetric hydro-meteorological observation network, analysis of historical
hydro-meteorological data, design of hydrological forecasting model, first practical results, etc.
Figure 4: Telemetric observation network
2.2.
First Results
The first results achieved by the Bulgarian team include:
 The telemetric observation network set-up and the operational data collection system.
The system started functioning and collecting hourly averages of all the observed
hydrological and meteorological parameters in January 2001;
 Analysis of relevant historical data set was completed. It includes review of 30 years
series of daily averages of discharges, daily precipitation totals, snow heights, air
temperature daily means and maximums observed at certain stations in the region.
Different type of descriptive information, important for the design and calibration was also
collected. That is valid for the hydrographic characteristics of the basin, information about
the major soil classes in the basin, major anthropogenic impacts of the hydrological
regime, etc. Examples of the work carried out in that direction are presented below.
Separately the pluviograph data (rainfall intensity – Figure 8) were processed, which are
unfortunately available for a few stations situated in the lowland and working only during
the warm season. Relevant single flood waves (Figure 7) (using hourly discharges from
limnigraph records) were analyzed as well, to determine more precisely the concentration
7
Altitude in m.
time and flood peak discharge. The most important result here is that the southern parts of
the basin usually start working first, due to the intensive snowmelts and rainfalls, caused by
Mediterranean cyclones moving from South to North.
Catchment area in km2
Razhdavitca
5,3
60,5
1,5
1,4
1,8
1,3
3,4
2,9
1,9
1,2
1,4 4,1 1,9 2,2
1,7
4,0 0,9
5,6
5,1
2,8
1,6
1,68
P. Bistritca r.
0,0 62,5
6,7
13,8 82,0
24,5 100,0 Lebnitca r.
24,4 99,8 S. Bistritca r.
37,7 121,0 Tcarevska r.
59,1 193,0 Dyavolska r.
53,9 166,5 Vlahinska r.
82,5 300,4 Stara reka r.
78,7 285,1 Gradevska r.
73,3 272,3 Sushichka r.
69,4
115,4 364,0 Dzherman r.
111,0 357,0 Kopriven r.
2,64
103,9 340,7 Rilska r.
99,2 331,7 Lisiiska r.
93,3 318,0 Bl. Bistritca r.
157,0 459,0 Bistritca r.
147,5 441,3 Grashtitca r.
142,2 435,0 Eleshnitca r.
Krupnik
Marino Pole
Hydrological
station
164,9 479,0
169,9
190,8 585,0
217,1 624,0 Arkata r.
206,0 607,0 Svetlya r.
201,0 595,0 Orolachka r.
239,4 655,0 Konska r.
249,4
289,8 2180
Absolute elevation
of the river bed in m.
Distance in km. (Beginning from the border)
268,7
267,0 800,0
Pernik
Altitude in m.
Studena dam
Figure 5: Struma river basin hydrographic curve
1,41
400
Struma river 1972
Marino Pole
Krupnik
Rajdavitza
Strumeshnitza
Rila
6
4
3
200
2
1
0
ct
-O
30
ct
-O
28
ct
-O
26
ct
-O
24
ct
ct
-O
22
-O
20
ct
-O
18
16
-O
ct
Days - hours
Figure 7: Single flood wave analysis (hourly)

Station Blagoevgrad
confidence level
0.01
0.1
1%
3%
5%
5
Intensity [mm/min]
600
Discharge [m3/s]
Figure 6: Struma river basin longitudinal profile
Duration [min]
0
0
20
40
60
80
Figure 8: Rainfall intensity/duration curves
The first modeling was elaborated (Sosedko et al, 1990; Dimitrov, 2001). It is not
practical to relay on the telemetric data as an input for the hydrological forecasting model
because of the short concentration time (for some flood events less than 24 hours). Two
8


days ahead meteorological forecast is used as first approximation of the precipitation and
air temperature fields. Experiments were made with two types of simulation models using
daily values: the Ukrainian SNEG2 (Sosedko et al, 1992; Dimitrov and Stanev, 1994); the
Norwegian version of HBV (Stanev and Saelthun, 1993, 1994). Example of the results is
presented below (fig. 10).
It is foreseen that the real time rainfall/snowfall telemetric data will not be used directly as
an input for the hydrological forecasting model. Meteosat satellite data and elevation
gradients will be used for the spatial analysis of the precipitation fields. The analysis of the
historical data set shows that the density of the observation network is not sufficient
because of the mountain landscape conditions.
Finally, the real time observations of the river levels will be used for dynamic adaptation of
the discharge forecast using Kalman filtering or other stochastic approach.
3. Short Range Forecasting of Mountain Reservoirs Inflow
With the developing of the marketing economy in Bulgaria, the demand for more reliable
hydrological information and forecast is continuously increasing. First, the energy production
decided to finance the development and set-up of a system for short range forecasting of the daily
reservoirs inflow. Four cascades located at the southwest mountain part of Bulgaria were found
important for such kind of forecasting services. The reservoirs of those cascades are not big and
have relatively complex system of operation, producing only peak energy at certain time in the
morning and evening. Most of them are equipped with powerful pumps reversing water at night
using cheap energy produced by “Kozloduy” nuclear power plant. The project has been started at
late 1998 with the following objectives:
 At least two days ahead forecasts of daily reservoir inflow is issued every day, to facilitate
the optimal planning of their operation.
 Improving the management of the reservoirs and cascades operation by optimal planning of
peak energy production and reverse pumping.
 Making the exploitation of the reservoir cascades more secure by optimal planning the
retention volumes in case of floods.
Hydrological forecast with increased lead
time, two days ahead meteorological
forecast:
Limited Area High Resolution
Meteorological Forecasting Model
“ALADIN”
Two days ahead meteorological forecasts of
air temperature and precipitation
Adjustment of flood forecast by real
time hydro-meteorological
observations
Spatial analysis of the precipitation
fields applying METEOSAT data
Uses the hourly data obtained from
the telemetric stations, elevation
profiles and satellite data about the
entire river basin
Hydrological Rainfall/Snowmelt - Runoff
Forecasting Model
Takes into account snowmelt processes, interception, evapotranspiration, infiltration, uses
simple routing procedures and gives one day ahead forecast, according to basin
concentration time
Final adjustment of hydrological forecast using
dynamic adaptation stochastic models
Figure 9:Principle scheme of the modeling concept
9
One of the first tasks of the project (Dimitrov, 2001) was inventory of derivation channels and
pumping facilities to clarify the water collection schemes at each complex and its corresponding
watershed (example of that type of information is given in Fig.11). The historical hydrometeorological information in the reservoirs watersheds was also reviewed as well as the
availability of real time hydro-meteorological data, which could be used for the verification of the
meteorological forecasts and adaptation of the hydrological forecasts. Certain operational data
collection system was designed and set-up, comprising:
 Daily inflow/outflow of 11 reservoirs;
 Air temperature/humidity, wind speed/direction, observed three times per day as well as
daily precipitation totals and snow heights at 12 meteorological stations (collected daily);
 Daily precipitation totals and snow heights, weekly snow water content and coverage at 24
precipitation gauges (collected weekly);
 Daily instantaneous discharges at 42 water level gauges located at rivers that are more
important and derivation channels (collected weekly for the dynamic calibration of the subbasin forecasting hydrological model).
The modeling concept is very similar to that given at Fig. 9 (Dimitrov, 2001). The difference
is that the sub-basins along the derivation channels and reservoirs are much smaller (with area
varying from 40–60 to 200-300 km2), their concentration time is several hours, no automatic
telemetric observation network is available, so some reasonable lead-time of the hydrological
forecast might be obtained only using the high resolution meteorological forecast of air temperature
and precipitation.
Figure 10: Simulation of the daily discharges (1986, 1983)
The hydrological forecasting model is calibrated for the most important sub-basins, where
observations of air temperature, precipitation and discharges are available and for each of the
reservoirs’ watersheds. The final product – two days ahead hydrological forecast is available in
several competitive variants:
 Direct forecast of the reservoirs inflow, considering it as discharge at certain river cross
section;
 Composed forecast of the reservoirs inflow obtained by separated forecasting of the
derivation channels and their sub-basins contributions;
 Adaptive scheme adjusting the above two variants.
The project implementation has faced a number of difficulties as follows:
10



It was difficult to find suitable historical data for the calibration of the sub-basins at the
higher elevation zone, because of the lack of meteorological observations there and the low
quality hydrometric data during the winter;
The calibration faced another difficulty, due to the considerable difference between the
meteorological forecasts and meteorological observations at the high mountain zone,
which is especially valid for the precipitation;
The operational evaluation of the reservoirs inflow is performed based on the produced
energy and overall water balance of the respective reservoir/cascade. That was very
often source of errors, existence of false peaks of the inflow, etc.
The operational exploitation of the forecasting system started in early 2001. The evaluation of
the system performance and accuracy is promising. The general conclusions are that many
improvements should be done both in the meteorological and hydrological forecasting models to
increase the forecasting accuracy and reliability as well as to meet the demands of the practice.
Figure 11: Principle scheme of “Batak” cascade (reservoirs “Batak” “Golyam Beglik”, “Shiroka Plyana”)
11
Figure 12: Hydro-meteorological data and hydrological forecasts visualization software
4. Iskar and Yantra River flows real time monitoring
4.1.
Objectives
Installation of automatic system for observation the level of main tributaries of the Danube in
Bulgaria and creation of public information system for hydrological information through
publishing in the Internet and, on this basis to provide free access in real time to the data for a wide
circle of interested authorities, business and civil organization, population and relevant subject
from the Republic of Romania
4.2.
Outputs/Results
In the project framework, an investigation was made for the choice of the places for installation
of two automatic hydrometric stations in the lower reaches of the major tributaries of the Danube in
Bulgaria – Iskar River and Yantra River. The places had been prepared in advance and automatic
stations for water level, water temperature, precipitation and air temperature were installed. The
information is transmitted through GSM modem to branch Pleven of NIMH, where it is stored in a
database and is published in (Figure 13) Internet (www.pleven.meteo.bg). Computer equipment
was bought and proper software for the project requirements was installed.
Figure 13: Web site images of the real time water level data - Belyanovo and Orehovitsa
hydrological stations
12
5. System for automatic hydro-meteorological data processing, archiving and presentation
via Internet/Intranet
For the purpose of hydro-meteorological data monitoring within an Intranet environment a
special technology was developed. The system (Figure 14) consists of three main parts:
5.1.
Access database file
The Access database stores:
 Vectorial geographical information of the hydro-meteorological objects: basins,
watersheds, rivers, stations
 Metadata about the objects: coordinates, relationship between objects, addresses etc.
 Description of different variables used to create data series, documents and tables
 Links to documents, pictures, tables related to the above mentioned objects
 Data Series of any variable type and time step attached to them
Figure 14: Information system structure
5.2.
Data Manager application tool
The tool serves:
 To create and maintain the database structure and administrative access
 For adding, updating and deleting geographical objects
 To create new variables
 For editing the objects metadata
 To insert and update Data Series and other documents attached to the objects
 As a tool for graphical and tabular presentation of the data
 For data import and export in ASCII format
13
5.3.
Web site
The Web site allows an Intranet access to the tabular and graphical views on the database. It
has several features:
 An interactive mapping interface to the geographical structures of the database (Figure
15)
 A tree view on the objects relationships
 A tabular representation of the data series
 An interactive graphical presentation of the data series
Figure 15: Web site main application page
The entire system serves to supply historical and real time information of all hydrometeorological data collected by the National Institute of Meteorology and Hydrology. It is planned
to enhance its analytical potential in the future, in order to include automatic creation of thematic
maps :





Real time and historical water production maps
Alarm methods for high flood forecast
Prediction of low water level periods
Real time soil moisture maps
Monitoring and alarm methods for the reservoirs input, storage volume etc.
14
6. Acknowledgements
Several projects funded by PHARE helped the creation and development of Danube AEWS 97-5244.00, 99-0207. Struma Warning System was funded by Phare CBC BG9803.03.02.02 and
Intereg II funds. The Mountain Reservoir Forecasting System was helped by the National
Electricity Company project CDU-9801.
The Maritza River hydrological modeling was developed within the bilateral cooperation
between the National Institute of Meteorology and Hydrology of Bulgaria and Météo-France.
The “System for automatic hydro-meteorological data processing, archiving and presentation
via Internet/Intranet” was developed initially within Med-Hycos project, then enhanced with the
help of a FAO project for Cyprus Water Development Division (WDD) and the WOISYDES
project. The Web Interface is developed by Dipl.-Ing. Dejan Lekic (dlekic@meteo.yu) from
Ministry for Protection of Natural Resources and Environment of Republic of Serbia.
7. References
Deardorff, J.W., 1978: Efficient prediction of ground temperature and moisture with inclusion of a layer of
vegetation. J. Geophys. Res., 83, 1889-1903.
Dimitrov, D. 2001: Short term hydrological forecasting of the reservoirs cascades Arda, Batak, Belmeken,
Dospat. NIMH – Technical report (in Bulgarian), Sofia, 2001.
Dimitrov, D., K. Stanev, 1994: On the possibility for short range forecasting at the Bulgarian mountain part
of the Mesta river basin. UNESCO Conf. on Developments in Hydrology of Mountainous Areas, Stara
Lesna, Slovakia.
Golaz, C., and C. Cavazzi, 1995: Exploitation d’un modèle numérique du terrain pour l’aide á la mise en
place d’un modèle hydrologique distribué. Rapport technique, CIG, Ecole des Mines de Fontainebleau.
DEA d’hydrologie, Université PARIS 6. (in French)
Habets, F., J. Noilhan, C. Golaz, J. P. Goutorbe, P. Lacarrère, E. Leblois, E. Ledoux, E. Martin, C.
Ottlé, D. Vidal-Madjar, 1999a: The ISBA surface scheme in a macroscale hydrological model applied
to the Hapex-Mobilhy area Part 1: Model and database. J. Hydrol., 217, 75-96.
Habets, F., P. Etchevers, C. Golaz, E. Leblois, E. Ledoux, E. Martin, J. Noilhan, and C. Ottlé, 1999b:
Simulation of the water budget and the river flows of the Rhone basin. J. Geophys. Res.104 (D24),
31145-31172
Jarvis, P.G., 1976: The interpretation of leaf water potential and stomatal conductance found in canopies in
the field. Phil. Trans. R. Soc. London, Ser. B, 273, 593-610.
Ledoux E., 1980: Modélisation integrée des écoulements de surface et des écoulements souterrains sur un
bassin hydrologique. Thesis, Ecole Nationale Superieure des Mines de Paris and Université Pierre et
Marie Curie – Paris VI
Ledoux, E., G. Girard, G. de Marsilly, J. Deschenes, 1989: Spatially distributed modeling: conceptual
approach, coupling surface water and ground water, NATO, ASI Series C. In: Morel-Seytoux, X. (Ed.).
Unsaturated Flow Hydrologic Modeling-theory and Practice, 275 pp. Kluwer Academic, Dordrecht pp.
435-454.
Noilhan, J., 2002: GLASS workshop on land – atmosphere interaction, In
http://www.knmi.com/samenw/eldas/GLASS_workshop/workshop.html
Sosedko, M., K. Stanev, D. Dimitrov 1992: Snowmelt–rainfall hydrograph modelling and forecasting. Bulg. J. of Meteorology & Hydrology, v.3, No1 (in Russian).