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Improving water governance in CentralAsia through application of datamanagement toolsIskandar Abdullaev a , Shavkat Rakhmatullaev a , AlexanderPlatonov b & Denis Sorokin ca Transboundary Water Management in Central Asia Programme,Deutsche Gesellschaft fur Internationale Zusammenarbeit (GIZ)GmbH, Abdullaev Str. 2 A, 100100, Tashkent, Uzbekistanb International Water Management Institute (IWMI) Central AsiaSub-office, Murtazaeva Street, 6, Tashkent, Uzbekistanc Scientific Information Centre of Interstate Coordination WaterCommission, Kara-su 6, Tashkent, Uzbekistan

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To cite this article: Iskandar Abdullaev, Shavkat Rakhmatullaev, Alexander Platonov & Denis Sorokin(2012): Improving water governance in Central Asia through application of data management tools,International Journal of Environmental Studies, 69:1, 151-168

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Improving water governance in Central Asiathrough application of data management tools

ISKANDAR ABDULLAEV*y, SHAVKAT RAKHMATULLAEV*y, ALEXANDERPLATONOVzAND DENIS SOROKINx

yTransboundary Water Management in Central Asia Programme, Deutsche Gesellschaft fur Interna-tionale Zusammenarbeit (GIZ) GmbH, Abdullaev Str. 2 A, 100100Tashkent, Uzbekistan; zInterna-tional Water Management Institute (IWMI) Central Asia Sub-office, Murtazaeva Street, 6Tashkent,Uzbekistan; xScientific Information Centre of Interstate Coordination Water Commission, Kara-su 6,

Tashkent, Uzbekistan

Contemporary water management decisions use many sources and forms of data. The paperdiscusses the implementation results of data management activities in the water sector carried outin five countries of the Central Asia region. Geoinformation systems, remote sensing tools anddatabases have been applied worldwide for improving water resources management with differinglevels of success. Water management organisations, equipped with data management tools will havebetter capacities to adapt their decision-making in the changing availability and scarcity of waterresources. Application of data management tools for improving collection, storage and processingof data and information are a first step towards improved water governance.

Keywords: Data management; Transboundary water management; Database; Irrigation

Introduction

According to different international agencies, 40% to 50% of world population will liveunder water stress by 2025 [1–3]. In most cases, however, problems arise not from physi-cal access or scarcity of natural resources but from the malfunctioning of water governance[1,4]. It is likely that old water governance systems based on hierarchical command andcontrol will become less applicable in the future [5,6]. Improved water governance shouldlead to improved accountability of water institutions to the stakeholders. This can beachieved by good data sharing with stakeholders, which ensures effective introduction ofthe Integrated Water Resources Management (IWRM) paradigm [7,8].

Central Asia is home to more than 55 million people. The region is landlocked with anextreme continental climate of 10-fold difference between rainfall (150–300 mm) andevaporation (1200–1600 mm) [9,10]. There have been serious climate change impacts onice caps in mountains. These features combine to make availability of water resources acontentious issue [11].

Five Central Asian countries (Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan andUzbekistan) are sharing two large rivers (Amu Darya and Syr Darya) and a complex

*Corresponding author. Email: iskandar.abdullaev@giz.de, shavkat.rakhmatullaev@giz.de

International Journal of Environmental Studies,Vol. 69, No. 1, February 2012, 151–168

International Journal of Environmental StudiesISSN 0020-7233 print: ISSN 1029-0400 online � 2012 Taylor & Francis

http://www.tandf.co.uk/journalshttp://dx.doi.org/10.1080/00207233.2011.641243

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irrigation system, covering around 8 million ha of irrigated lands (figure 1). Both riversstart in upstream countries where most of the reservoirs and hydropower facilities arelocated, yet irrigation is largely practised in downstream countries [9,12]. Since the col-lapse of the Soviet Union, there is no longer one set of policies for allocation of waterresources; and there have been tensions among the states, which are growing [13,14].

Aminova and Abdullaev have discussed Uzbekistan’s management of water, noting thatdifferent water control types are applied at different levels of water management in CentralAsia by different players [15]. There is therefore great potential for political conflict at var-ious levels. The recent land reforms in Central Asian states have increased the number ofirrigation water users, and there has also been an increased flow of information into thedecision-making process on water matters [16,17].

While socio-economic and political controls were applied across all hierarchical levels,technical and managerial controls were mainly observed at the middle level: water man-agement organisation (WMO) and water users’ association (WUA). But water control strat-egies take effect at the grassroots levels. Here, on the one hand, WMOs make operationalwater management decisions; and on the other hand, individual farmers using modern sys-tems and those in the normal peasant agriculture tradition apply water control measures foreveryday water management [17]. Physical, organisational, socio-economic, politicaleffects merge with the actual delivery and use process.

Data for all these users and decision-makers come from different sectors. The raw dataare still kept at the lower levels of water management with restricted access to the higherwater management hierarchies and to the public. Old ways of collection, storing and pro-cessing of the data and information do not work in the new context of post-Soviet contextof efforts towards democracy and a market economy by Central Asian states [18].

Figure 1. Location of the intervention sites for data management for IWRM activities of the TWMP CA.

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According to Garcia [19], water governance and management can be divided into threeinterlinked levels i) constitutional, ii) associative and iii) operational. The real time dataare produced at the operational level of water management. At this level, complex interac-tions between different actors (WMO, WUAs, farmers, industry, local government authori-ties, etc.) on water management take place to define water rights (limits), waterdistribution and water control with application of different water control strategies [12].Therefore, improving of data management at this level is crucial for improving water gov-ernance at this and higher levels (national and regional) of water management (figure 2).

Modern water governance and management decisions rely on many forms of data. Theseare often dispersed, heterogeneous, incomplete, and not comparable [7]. Application ofmodern information tools is necessary for decisions in a modernising Central Asian con-text: for example, geographical information systems (GIS), mobile and Internet communi-cation technologies, remote sensing (RS) tools, modelling and databases. Such tools havebeen employed elsewhere in the world, under a variety of environmental conditions andlevels of engineering complexity and with differing levels of success [20–23]. There havebeen many applications of information tools in water sector research in the last two dec-ades in Central Asia [24–34]. Yet the impact of these apparent advantages on the opera-tional level of water management has been very limited.

The aim of this paper is to review current application of information management toolsin the water sector and results of data management intervention by the German- fundedTransboundary Water Resources Management in Central Asia (TWMCA) Programme. Thepaper studies shortfalls and instances of good practice, and provides practical informationfor designing intervention strategies for international donor community for improvingexisting gaps in Central Asia.

History of data management in water sector of Central Asia

During Soviet times information on water management and use was handled through anadministrative reporting system from the lowest water management organisations towards

Figure 2. Improving water governance through data management.

Improving water governance in Central Asia through application of data management tools 153

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the higher ones. Central Asian countries continue to meet very high requirements ofreporting and documentation. The reports produced by WMOs were mostly in formatswhich were not accessible or understandable by the general public [35]. Annual reports(paper format) were produced by each WMO and stored in the archives for at least for fiveyears. Based on annual reports of WMOs and statistical data collected by departments ofthe statistics, yearly books were published for each Soviet republic. The yearly statisticalsurveys included data on water resources management: water use per sector, per capita andper administrative units (province) [36].

In Central Asia, since the mid-1990s, regional organisations (Scientific Information Cen-tre of Interstate Commission for Water Coordination (SIC ICWC), International Funds forAral Sea, (IFAS)) with support of international donor community have been trying, withvarying success, to improve data generation, collection, systematisation and application ofmodern tools (GIS, models, etc.) for depicting the water management situation at differentlevels (see table 1) [37].

Most of the data and information tools are of restricted access and only contain retro-spective data sets. Yet, the primary level of information collection and data generation is atoperational level (the lowest levels of water management) where data are collected, keptwith no access for higher water policy-makers or the general public. Therefore, it is impor-tant that data management at the operational level of water management is improved, withmore access for both policy-makers and the public.

The application of information systems at the operational level in the region has hadlimited success. The reasons are i) hesitancy of the WMOs to allow public access to thecrucial operational information; ii) existing interventions (both internal and internationaldonor programs) on data management were focused on national or regional levels withoutconsideration of operational levels, where all data and information are generated; iii) insuf-ficient capacities in the WMOs to use data management (DM) tools. Therefore, tediousmanual data management practices persist in everyday operation of WMOs, for gathering,storage and reporting the data [18,35].

But because of the Internet and cell phones, data democratisation is taking place inCentral Asia – just as in the rest of the world. Thus, data management tools will have tobe widely used in the water sector.

Intervention locations

As intervention locations for pilot testing of the data management tools, seven sites withintransboundary river basins were selected in consultation with partner states for up-scalingthe results to national levels. The size of the intervention areas range from a small irriga-tion scheme like Garauti (Tajikistan) with an area of 250 km² up to large basins such asAral-Syrdarya Basin (Kazakhstan) with an area of approximately 80,000 km² (figure 1) .

Materials and methods

Conceptual framework

The data management at the lowest water management level has to face some outstandingissues related to the water governance. The first issue is the accuracy of the data (qualitycontrol). The second is absence of the indicators for water management performance

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Table1.

Pastandcontinuing

water

managem

entdatabasesandinform

ationsystem

sin

Central

Asia

Database

Project/donor

Level

ofdata

collection

Sourceor

linkanddata

accessibility

Relevance

tothewater

governance

Water Managem

ent

Inform

ation

System

(WARMIS)

Water

Resou

rces

Managem

entand

Agricultural

Produ

ction

(WARMAP)

project,

Europ

eanUnion

Six

them

essuch

aswater,water

quality,

econom

y,administration,

etc.The

data

are

attributed

toprovinces,

districtsof

five

Central

Asian

states

No

access,Pow

erPoint

presentatio

nis

available

at:http://www.caw

ater-

info.net/carew

eis/warmis_e.htm

Itreflects

only

situationfortheselected

sitesand

time

series

onwhich

data

have

been

collected.

Mostly

retrospective

data,access

tothe

data

islim

ited;

notpu

blicly

available.

Water

Use

and

Farm

Managem

ent

(WUFMAS)

Water

Resou

rces

Managem

entand

Agricultural

Produ

ction

(WARMAP)

project

phase

2,Europ

ean

Union

Totalof

91farm

sin

1996–199

9,located

inthe

five

repu

blics

inthe

AralSea

basin

No

access,Pow

erPoint

presentatio

nis

available

at:http://www.caw

ater-

info.net/carew

eis/wufmas_e.htm

Itreflects

only

situationfortheselected

farm

sand

time

series

onwhich

data

have

been

collected.

Mostly

retrospective

data,access

tothe

data

islim

ited;

notpu

blicly

available.

Cop

ernicus

database

Europ

eanUnion

Selected

households,

and

onfield

operations

No

access,Pow

erPoint

presentatio

nis

available

at:http://www.caw

ater-

info.net/carew

eis/copernicus_e.htm

Itreflects

only

situation

for

the

selected

households

and

fields

and

timeseries

onwhich

data

have

been

collected.Mostly

retrospective

data,access

tothedata

islim

ited;

notpu

blicly

available.

River

Twin

Project

data

base

EuropeanUnion

Chirchik-Akhangaran-Keles

subbasin

Noaccess

Itreflects

only

situation

forthe

selected

basin.

Dataaccess

islim

ited;

notpublicly

available.

Central

Asia

Regional

Water

Inform

ation

Base

(CAREWIB)

SDC,EU,GIZ

Region,

states

ofCentral

Asia,

main

riverbasins

Partial

access

throug

hon

line

registratio

nat

www.caw

ater-info.net.

The

registratio

nhave

tobe

approved

byProject

Managem

ent

Itis

avery

useful

tool

foranalysis

andresearch.

Mainshortcom

ingis

absenceof

operationaldata

onwater

managem

ent.

Water

inCentral

Asia(CAWa)

data

base

AA

Germany

Region,

selected

prov

inces,

irrigatio

nsystem

sPartial

access:

http://www.caw

a-project.n

et/

Source:Caw

ater-InfoWeb

portal

(2011)

[37].

Improving water governance in Central Asia through application of data management tools 155

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assessment. The third issue is concern of the water professionals to collect regular and reli-able data. If there are shortfalls in water management, then data may show this, and thedefaulting water professionals may be held responsible for water mismanagement; assum-ing that the data are publicly accessible! In this paper, we highlight related measures todeal with these three issues. Data management for IWRM activities is part of the TWMCAProgramme and was designed with four interlinked intervention pathways: i) principles,ii) data, iii) hardware and iv) software (figure 3).

Strategic approach

The data management activities were designed with a bottom-up approach with fullinvolvement of the partner WMO in the activities from the very beginning (pre-assessmentand planning stages). Partner WMOs decided on type, structure, content, interface and for-mat of the data management tools which created an ownership of a process by the partnerWMO.

The data management activities of the TWMCA programme were carried out in threestages:

Stage 1:� The activities were structured to accomplish the following objectives: a) pre-assess-

ment of hardware and capacity building needs of local WMO; b) presentation anddiscussions of data management concept with local decision-makers, technical staffof WMO; c) establishment of workplaces on database and GIS, providing

Figure 3. Main components of data management activities of TWMCA programme.

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up-to-date hardware and software to partner WMO; d) implementation of capacitybuilding measures on data management tools for experts of partner WMO; (e)increasing awareness of local decision-makers through two types of training: centra-lised and on the job. The topics of such training were introductory courses on GIS,GPS (Global Positioning System), satellite imageries (Google Earth, Digital Eleva-tion Models) and remote sensing tools application in the water sector. Russian ver-sions of software were provided to the partner WMO to strengthen and simplify useof data management tools.

Stage 2� The measures were focused on development and implementation of the database

system architecture with full ownership by local WMO experts in terms of content,format, and interface. In this stage, WMO partners prepared algorithms for reportingon daily water information. Users’ manuals on database operation and GIS werebeing prepared as supportive documentation for users.

Stage 3� The activities were concerned with putting in the database both retrospective and oper-

ational data on water discharge, use, abstractions, population dynamics and irrigation.The last step was to prepare river basin plans based on the stored and generated data.

Organisational measures

Capacity building

Capacity building activities were carried out to educate experts of partner WMOs in allseven selected sites on data management. The partner WMOs had nominated one waterprofessional involved in daily data handling and one expert/scientist from local researchorganisations or universities with knowledge of data management. The two nominatedexperts participated at a two-week training course on GIS and GPS. The capacity buildingactivities continued with a series of on the job training sessions in all seven selected sites.During these, supplemental training needs were indentified, for example, use of Internetand GPS receivers.

Technical support

The programme assessed needs for hardware to establish data management workplaces atthe study locations within premises of the WMO. The seven sets of computers, A3 formatprinters and scanners, two GPS-receivers and other auxiliary hardware were provided. GISand general software ArcGIS 9.3.1, MS Office Package and antivirus were installed intothe computers. The computers in data management workplaces were linked with variousunits of the WMO such as dispatch centre, water planning unit and other relevantdepartments through a local network. These networks helped to improve accessibility andoperation, adding data to the database.

Expert inputs to the data management activities

Short-term professional experts from the regional Scientific Information Centre of theInterstate Coordination Water Commission (SIC ICWC) and the International WaterManagement Institute (IWMI) were recruited to help partner WMOs for the development

Improving water governance in Central Asia through application of data management tools 157

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and application of Data Management tools. Both organisations are experienced in thedevelopment of regional databases and GIS development, and have knowledge of regionalwater management problems in Central Asia; and their experts speak Russian. Thus, inter-action with partner WMOs was good.

Materials and techniques used

Database

The database was designed to collect and store the digital tabular data on water resources,water use, hydro-technical facilities, hydrological conditions, and economic and administra-tive conditions of the location (basin, irrigation system). The database should allow watermanagers to store all operational and daily data in a systematic manner. Datasets which are atpresent available in different formats (MS Excel, Word, Access and etc.) could be trans-formed in the database by import/export commands or manual typing. The database wasdeveloped using open-source PHP script language, which is at present commonly used forweb based databases [38]. The foundation platform was MySQL�, a freely downloadableversion of the world’s most popular open source database [39]. The use of PHP languagemakes it easy to launch an internet-based version of the database; and this gives wider accessto the database for water professionals, policy-makers, academics and the general public.

Geographical Information System (GIS) and Remote Sensing (RS)

The application of GIS tools will allow the assessment of existing irrigated areas, and thewater use situation in different parts of the study areas (basin, irrigation system) [40]. TheGIS tools include satellite based images, Digital Elevation Models (DEMs), different back-ground maps and coordinates of water infrastructure, these being recorded through GPSreceivers. ArcGIS 9.3.1(Russian version) used for image processing and land use mapdevelopment. Application of the GIS and RS tools to assess size and location of theirrigated areas is most important for the improvement of water resources management plan-ning and allocation [22,41,42]. Especially in Central Asia, where irrigation represents upto 90% of water use, irrigated area maps are helpful in identifying both the extent of actu-ally irrigated lands and water use in specific locations.

Results and discussion

Gathering support for data management in water sector: framework condition

The most crucial element for successful implementation of the data management activitiesis the commitment from national water management agencies in each Central Asian coun-try. Therefore, we presented the database concept and structure to the respective nationalauthorities to gain political support. This was also important for the integration of the data-base into the normal business procedures of the partner WMO. The national authorities ofKyrgyzstan, Uzbekistan, Tajikistan and Turkmenistan have issued support letters to theprogramme indicating their desire to support the data management activities. In all fourcountries, special decrees were issued by the respective national water authorities declaringthat use of the database was to be the main tool for reporting within their hierarchicalsystems. The Kazakhstan government is funding the program there on improving data

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management in the water sector. The private company ‘Geobyte’ is implementing the statescheme of water sector data management.

Recent efforts to introduce e-government in all Central Asian states are another reasonfor wider state support of data management tools in the water sector. Moreover, there areattempts by national governments in Central Asia to reduce substantially paper reportingby means of electronic reporting.

Database: progress and issues

Architecture of database

SIC ICWC experts conducted a series of local meetings with staff of partner WMOs atselected sites to discuss type, structure and content of the database. The discussions helpedto indentify the architecture of the database. The major requirement for the database was auser-friendly interface and easy functioning. This could avoid costly upgrading of the data-base. Another prerequisite was that the database should be compatible in all locations, thatis, the database structure in different locations could produce comparable reports or indica-tors, so that in future data exchange would be possible. This was achieved through theapplication of genuine components for databases at all sites (figure 4 and table 2).

Once database structure and interface was prepared, experts from WMOs were trainedon database operation, administration and management. The Help function was built intothe database with users’ manuals. The database structure reflects most of the requirementsof partner WMOs for regular reporting. The database allows the production of a selectedset of regular reports. In order to ease operation by local experts who use a local languagein their daily work the database was made bilingual, with Russian and a local language inevery case.

Figure 4. Configuration of the database for the Serafshan Basin Irrigation Systems Authority, Uzbekistan. A –Sectoral; B – Hydraulic infrastructure; C – Sub-basin WMO; D – Analysis and Reporting; E – Administrationand management.

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Filling of data

The WMOs had the task of filling the databases with retrospective and actual data. Someinnovative approaches were applied; for example, in Kyrgyzstan (Isfara–Khojabakirgan,Chu–Talas basins) a group of professional experts from the research organisation in Bish-kek with previous experience on filling up regional database, Central Asian Research Envi-ronmental and Water Information Base (CAREWIB) were involved. In Serafshan BasinIrrigation Systems Authority (Uzbekistan) local students from Samarkand State Universitywere recruited to transform paper data into the database. It turned out to be a difficult taskto collect long-term retrospective data due to the loss of the data in the paper forms whichwere stored in poor conditions at the offices of district (rayon) and provincial (oblast)water management organisations. Therefore, it is urgent to transfer all retrospective infor-mation and datasets into the databases. Due to the limited availability of retrospective datafor seven WMOs in seven locations, it was decided to collect and enter data for the lastfive years (2005–2010) only.

Access/connection

Access to the database has been a crucial issue. It will be difficult to convince WMOs togive open access to the public or to ‘outsiders’. Only one partner agreed during the initialmeetings to post a database on the internet. After a few rows in the meetings, otherWMOs agreed to launch an internet database with the provision of access only to theirstaff from branches/units. In order to give access to WMO branches (hydro unit, district,irrigation systems, etc.) mobile internet devices, offered by the local mobile phone compa-nies were used (figure 5). Widespread use of mobile phones and mobile internet connec-tions everywhere makes this option viable.

Another important issue is sustainable operation and maintenance of the database. Itrequires expert knowledge to be transferred from trained staff to other personnel: institu-tional learning. But the internal structure of partner WMOs does not support such learningeasily. Therefore, more on-the-job training series were conducted to build more capacities.

GIS and RS tools: too high-tech to be easy?

The application of GIS tools for water resources management has been successful from theresearch and business point of view [22]. But, due to high prices and high learning

Table 2. Functionality of main components of developed database used by Serafshan Basin Irrigation SystemsAuthority, Uzbekistan

Component Functionality

A Sectoral General statistics on different sectors of the river basin such as socio-economicsettings, land resources, agriculture and industry

B Hydraulicinfrastructure

General information and data for flows, discharge from surface and groundwaterresources

C Sub-basin WMO Information and data for water use, delivery, abstraction and irrigationD Analysis and

reportingCompilation of existing reporting formats according to national water managementsystem

E Administration andmanagement

Administration and management of the DB content and format wise. Granting accessto data

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requirements for GIS tools, there has been limited application in practical water manage-ment [41]. Recent changes in GIS approaches, automation of operations in GIS environ-ment, free of charge or low cost satellite images, open source software have made GIStools more attractive for the water sector [43].

Downloading and processing of Landsat satellite images

The free Landsat-5 satellite images were downloaded from the Internet (http://glovis.usgs.gov/) for all study areas (table 3). Cloud free images for 2009’s growing season(July–September) with maximum vegetation with seven spectral bands were provided in tifformat. But, only three main bands (3, 4, 2) were used in ArcGIS for visualisation ofnatural colours.

Delineation of irrigated areas

For each study area the GIS layers of irrigated area polygons were manually digitised,using Landsat satellite images as background. The rectangular shapes of the irrigated fieldswere used to distinguish irrigated areas from none-irrigated zones. The cities and villagesalso were included in irrigated areas, because the vegetation inside the populated arearequires water for irrigation. In some cases, when the spatial resolution of Landsat images(30 m) was not enough to distinguish the irrigated fields from natural vegetation of wet-lands (mainly along the Syrdarya river for Aral-Syrdarya basin), the pictures from GoogleEarth, which have a spatial resolution of 5–6 m, were georeferenced to Landsat imagesand used for precise delineation of irrigated areas.

Figure 5. Linking different branches of WMOs for database.

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Downloading and processing of DEM (Digital Elevation Model) raster layers

The free Aster Digital Elevation Model-DEM layers (spatial resolution 30 m) were down-loaded from the Internet (https://wist.echo.nasa.gov) for intervention locations. But theShuttle Radar Topography Mission (SRTM) Digital Elevations Model (spatial resolution90 ms) was used only for the Aral-Syrdarya basin, due to the large size of the basin. The1� tiles of Aster DEM were provided in the geographical coordinate system. The tiles fullycovered study areas and were mosaiced and projected to the WGS-84 coordinate system.

Delineation of basin boundaries

The subsets of projected DEM and calculated raster layers from DEM were used for man-ual delineation of the basin boundaries in the water formation zones (watersheds) of studyareas. The basin boundaries at low altitudes were further corrected, when local partnersprovided the GIS layers of canal infrastructure for each study area (figure 6).

Downloading and processing of MODIS satellite image products

The free products (MOD13Q1) of MODIS satellite images which represent the NormalisedDifference Vegetation Index (NDVI) values with spatial resolution 250 m and temporalresolution 16 days were downloaded from the Internet (http://glovis.usgs.gov/) in tif for-mat. All study areas were covered by four tiles (h22v04, h22v05, h23v04, h23v05), pro-vided in Sinusoidal projection, Spheroid – WGS84 and Datum – WGS84 of year 2009.The NDVI raster layers (for each 16 days created 23 layers) of each tile were stacked in 4img format and were mosaiced in one file. The file was huge in size, and so subsets weremade. These include all study areas and the NDVI image file and these subsets werere-projected to the Universal Transverse Mercator coordinate system (UTM).

Table 3. List of used Landsat-5 satellite images for all study areas

Study area List of Landsat-5 satellite images

Aral-Syrdarya river basin L5_155030_2009_0720,L5_155031_2009_0720,L5_156029_2009_0812,L5_157029_2009_0819,L5_158029_2009_0911,L5_159028_2009_0902,L5_160028_2009_0723

Khodjabakirgan river basin L5_153032_2009_0823Isfara river basin L5_153032_2009_0823Zerafshan river basin (Bad-Bad canal) L5_155032_2009_0821,

L5_155033_2009_0720,L5_156032_2009_0727

Vakhsh river basin (massive Garauti) L5_153033_2009_0823,L5_153034_2009_0823,L5_154034_2009_0830

Karakum canal basin (massive Hanhowuz) L5_158034_2009_0826Chu and Talas rivers basin L5_150030_2009_0701,

L5_150031_2009_0701,L5_151030_2009_0708,L5_152030_2009_0816,L5_153030_2009_0706

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Land use/land cover classification

Land use/land cover maps were prepared with 16 land use/land cover classes. The file con-tents are 23 NDVI bands (each 16 days). Each study area has a unique combination ofdominated classes, and so there was a problem of combining the set of classes for eachstudy area in one set. Where the amount of land use/land cover classes inside the studyareas is unknown, the typical solution is to apply unsupervised classification with a prede-fined number of classes. Usually the number of classes is twice more than expected. Toovercome this problem, the unsupervised classification with 16 classes was applied to theimage file, which includes all study areas. Figure 7 presents the temporal profiles of NDVIchanges for 16 land use/land cover (LULC) classes.

Table 4 presents the parameters of LULC classes and the preliminary, assigned namesfor each class. Some classes can be combined; for example, classes 3–6 represent the baresoil, but before combining classes (grassland and shrub land), there must be ground truthdata and a check of the accuracy of LULC classification. At present, only preliminary landuse/land classification maps are produced and handed over to the WMO experts to analyseand to provide their expert assessments on GIS maps (figure 8).

WMO experts have collected and digitised different maps for GIS layers of irrigatedareas such as topographic maps, administrative borders, irrigation system borders, etc. Themaps were manually digitised, using as background layer Landsat satellite images. The rect-angular shape of irrigated fields was used to distinguish irrigated areas from none-irrigatedareas. The settlements (cities, towns, villages) were included in the LULC maps.

Geographical Information System (GIS) and Remote Sensing (RS) tools requirespecialist knowledge. Without special training and long term experience local experts

Figure 6. Digital Elevation Model of the Serafshan River Basin (Uzbekistan part).

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cannot produce GIS tools. But, LULC maps are not required to be prepared for eachseason or year. Revision every four to five years will be sufficient for basin assessmentand planning purposes. Keeping a professional staff with GIS skills is not feasible incurrent conditions due to the low wages of WMO staff. Therefore, recruiting of a growingnumber of companies or experts on GIS is an option for revision of the LULC maps. In afew Central Asian states National Water Management Authorities are starting to set upGIS units at the national level. These can help WMO to produce LULC on a regular basis.

Figure 7. NDVI changes (each 16 days, 2009) for 16 LULC classes from unsupervised classification of image,which includes all study areas.

Table 4. Parameters of LULC classes and assigned names

Class

Month of NDVI:

Max NDVI Class nameOnset Peak Senescene

1 – – – < 0 Water, Snow2 Jun Aug Oct 0.4 Grassland (alpine)3 Jun Aug Oct 0.12 Bare soil4 Mar May-Sep Nov 0.1 Bare soil5 Apr Jul Nov 0.17 Bare soil6 Mar May Nov 0.15 Bare soil7 Mar May Jun 0.22 Grassland (sparse)8 Feb Apr Jun 0.35 Grassland (early)9 Mar May Jul 0.28 Grassland (late)10 Apr Aug Nov 0.33 Shrubland (sparse)11 Apr Jun Nov 0.41 Shrubland (early)12 Feb May Jul 0.49 Grassland (dense)13 Apr Jun Nov 0.47 Mixed crops14 May Jul Nov 0.67 Shrubland (alpine)15 Feb May Aug 0.70 Shrubland (early and dense)16 Apr Jun Nov 0.70 Forest, orchards

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Conclusion and perspectives

Data management activities in selected sites show that there is a need to use modern infor-mation technologies in the decision-making process and the daily operation of water man-agement organisations for sustainable and efficient water management. Equipped with datamanagement tools WMOs will have better capacities to adapt their decision-making inresponse to changing water resources, availability and scarcity. The data management toolswill also have broader impacts because introducing information systems into any societymeans bringing a new series of institutions, discourses and practices into play [44,45].There is the danger that there may be differential access, that information may not be avail-able to all equally and there have been various critiques of the politics of knowledge [46].

The results presented in this paper show that in Central Asia application of the datamanagement tools could help to develop sustainable water management systems. Yet thereare still many challenges on practical application of data management tools in CentralAsia, including:

– staff of WMOs do not know the full advantages of information technology applica-tions for water management

– staff of WMOs are generally technically inexperienced on database, GIS and RStools

– the sub-basin WMOs are often geographically dispersed and Internet/Intranet logis-tics should be carefully examined

– digital databases should be stored centrally with full access to different users via theInternet

Figure 8. Land Use/land Cover classes of the Serafshan River Basin (Uzbekistan part).

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– Internet infrastructure is poor for acquisition of large size satellite imaginary.The data collection and reporting requirements in the water sector of the Central Asian

countries has not changed much from the Soviet time. A huge effort has been made in thelast decade or so by regional organisations (such as the Scientific Information Centre ofthe Interstate Coordination Water Commission (SIC ICWC), the Executive Council of theInternational Fund for the Aral Sea (EC IFAS), etc.) to systematise data on waterresources. The databases developed during this period cover different levels, aspects andregions of Central Asian water management. Raw data are collected and kept at the lowestwater management levels with limited or no access either for higher water managementhierarchies or the public.

Making informed decisions on water management depends on the availability of the dataat operational levels. Improvement of data management is part of the solution to waterproblems. These are worldwide, and governance issues are central to their resolution [47].Therefore, improving transparency of the management system through data tools couldlead to more sustainable water resources. This is especially significant because of climatechange. Data management in the water sector requires multi-disciplinary knowledge andmethods.

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