Satellite Based Water Intelligence
The Case for the Non-EU Western Balkan states—Albania, Bosnia and Herzegovina, Kosovo, Montenegro, North Macedonia, and Serbia

Summary

The six non‑EU Western Balkan states face accelerating hydrological pressures that require a modern, predictive, and integrated water‑information system, and satellite‑enabled hydrology offers a practical, scalable, and cost‑effective pathway to achieve this. By combining global satellite datasets with national modelling capacity, the region can overcome sparse monitoring networks, strengthen flood and drought forecasting, improve groundwater and environmental oversight, and gain independent visibility across transboundary basins. The proposed architecture, phased implementation roadmap, and costing framework demonstrate that such a system is both technically feasible and financially accessible, with long‑term benefits that far exceed the required investment. With coordinated governance, sustained capacity development, and stable operational funding, the Balkan states can build a resilient, interoperable water‑intelligence framework that enhances national security, supports economic development, and improves climate‑risk management across the region.

Introduction

Water is a strategic national asset across all countries, underpinning energy security, agricultural productivity, public safety, and long‑term economic development. In regions characterised by complex terrain, transboundary river basins, and limited monitoring networks, effective water governance depends on the ability to observe, understand, and predict hydrological behaviour. Climate variability and climate change are amplifying extremes, increasing the frequency of both intense precipitation and prolonged droughts. For countries with constrained observational capacity, the combination of exposure and limited monitoring translates directly into higher disaster risk and greater economic volatility. Conversely, many better‑resourced countries have strengthened their water‑information systems by integrating satellite‑based hydrological data, enabling near‑real‑time monitoring of rainfall, soil moisture, snow cover, surface‑water extent, evapotranspiration, and basin‑scale groundwater storage.

Across the six non‑EU Western Balkan states—Albania, Bosnia and Herzegovina, Kosovo, Montenegro, North Macedonia, and Serbia—these pressures are particularly pronounced. Mountainous and karst landscapes, rapid elevation gradients, and highly variable hydrological regimes create conditions where floods, droughts, and groundwater fluctuations can develop quickly. Major river systems such as the Sava, Drina, Morava, Vardar/Axios, and Neretva cross multiple national borders, making transboundary water management an inherent feature of the region’s hydrology. Monitoring networks remain uneven and often too sparse to capture basin‑scale behaviour, limiting the ability to track evolving risks or understand long‑term trends. Satellite‑enabled water intelligence offers a practical and scalable way to address these gaps by providing continuous, independent, basin‑wide visibility that supports real‑time monitoring, early‑warning capability, and evidence‑based planning.

The region’s hydrological vulnerability is shaped not only by physical characteristics but also by institutional and governance arrangements. Fast‑responding catchments heighten flood risk, while seasonal water scarcity and variable groundwater systems place pressure on agriculture, public supply, and energy production. Forecasting systems must operate with limited lead time, and emergency response depends on timely, accurate information that is not always available. Areas influenced by Mediterranean climate patterns and karst hydrology experience pronounced seasonal variability, yet drought monitoring and groundwater assessment remain limited. Transboundary river systems add further complexity, as upstream conditions frequently determine downstream impacts, while monitoring and data systems remain largely national in scope.

Globally, water‑management policy is shifting toward integrated systems that combine ground observations, numerical models, and satellite‑derived datasets. Many countries now treat satellite rainfall, soil moisture, snow cover, evapotranspiration, surface‑water extent, and groundwater storage as essential components of national forecasting and early‑warning architectures. These datasets are openly accessible, consistent across borders, and available even where in‑situ networks are sparse or difficult to maintain. Flood‑forecasting centres assimilate satellite precipitation and soil‑moisture products; drought‑monitoring systems rely on evapotranspiration and vegetation‑stress indicators; and civil‑protection agencies use radar‑based flood mapping to coordinate emergency response. Satellite‑enabled water intelligence has become a standard element of modern hydrological governance.

The non‑EU Western Balkan region has not yet incorporated satellite‑based hydrological information into its operational water‑management systems. Monitoring still relies mainly on conventional observation networks and numerical weather prediction, while satellite datasets are used only intermittently or within short‑term projects. Satellite rainfall data are not routinely assimilated into hydrological models, and soil‑moisture and evapotranspiration data are not part of formal drought‑assessment procedures. Flood‑extent mapping from satellite radar is generally produced only after major events rather than as part of continuous situational awareness. Groundwater‑storage information from international satellite programmes is also absent from planning and policy processes. These gaps reflect institutional fragmentation, uneven investment in monitoring infrastructure, and the lack of a coordinated policy framework. Responsibilities for hydrometeorology, water management, civil protection, and environmental monitoring are spread across multiple agencies, making it difficult to develop shared data pipelines, common modelling platforms, or unified operational procedures. Technical capacity in remote sensing and data assimilation remains limited, and existing IT systems are not designed for high‑volume, near‑real‑time data processing.

Despite these constraints, the region is well positioned to modernise its hydrological information systems. Global satellite missions now provide continuous, open‑access data across all major components of the water cycle, reducing the need for extensive physical monitoring infrastructure. Integrating these datasets into operational workflows would strengthen forecasting capability, improve seasonal outlooks, and enhance long‑term planning. Satellite‑based observation also provides independent visibility across transboundary river systems, enabling authorities to assess upstream conditions without relying solely on bilateral data‑sharing arrangements. Beyond risk reduction, satellite‑enabled water intelligence can support hydropower optimisation, agricultural advisory services, environmental monitoring, and land‑use assessment. Building such a system requires coordinated investment in data management, modelling capacity, and institutional roles, along with a clear policy mandate that recognises satellite hydrology as a strategic capability. With these elements in place, the region can align with international practice and strengthen its resilience to climate‑driven hydrological change.

Overview of Relevant Satellite Datasets for Water and Hydrological Monitoring

Modern water‑information systems draw on a wide range of satellite datasets that provide continuous, basin‑scale insight into rainfall, soil moisture, snow, surface water, evapotranspiration, groundwater, land conditions, and atmospheric drivers. These datasets are freely available, updated frequently, and used operationally by hydrometeorological agencies, river‑basin authorities, civil‑protection services, and environmental regulators around the world. The following table summarises the major satellite and satellite‑derived products that underpin contemporary hydrological monitoring and forecasting.

Satellite Data Currently Used in the Region

Operational use of satellite data by ministries and agencies in the six non‑EU Western Balkan countries is extremely limited. Current practice is confined to:

  • Basic meteorological satellite imagery (EUMETSAT Meteosat) for cloud cover and weather monitoring
  • Occasional manual downloads of Sentinel‑2 optical images for post‑event inspection
  • Reanalysis datasets such as ERA5 used for climatology and academic analysis

No country in the region uses satellite‑derived hydrological datasets operationally for forecasting, drought monitoring, flood mapping, groundwater assessment, or water‑resource planning.

Satellite Data the Region Does Not Routinely Use

Although all six countries have full, free access to major global satellite datasets, none of the hydrology‑relevant products are used in operational workflows. The gaps fall into clear thematic categories:

  • Precipitation (GPM, IMERG, CHIRPS, TRMM): Not used for flood forecasting, drought monitoring, or climate analysis.
    → Ministries lack independent, spatially continuous rainfall information, especially in mountainous and cross‑border basins.
  • Soil Moisture (SMAP, SMOS, ESA CCI): Not used by any national institution.
    → Removes a key early indicator for drought, wildfire risk, and agricultural stress.
  • Flood Mapping (Sentinel 1 radar): Not used in real time.
    → Flood maps are produced only after major events, often manually or by external partners.
  • Snow and Snow Water Equivalent (MODIS, Sentinel 2, passive microwave SWE): No operational snow monitoring system exists.
    → Despite snowmelt being a major driver of spring flooding, ministries have no basin‑wide visibility.
  • Groundwater Storage (GRACE FO): Not used in planning or drought assessment.
    → A major gap given the region’s extensive karst aquifers.
  • Evapotranspiration (MODIS ET, Landsat ET, ECOSTRESS): Not used for drought monitoring, agriculture, or wildfire risk.
    → Limits the ability to quantify water stress.
  • Water Quality (Sentinel 2, Landsat): Not used for turbidity, sediment, or chlorophyll monitoring in reservoirs or rivers.
    → No operational visibility on reservoir health.

Why These Gaps Exist

The absence of satellite hydrology is not due to lack of data — all major datasets are free, global, and continuously updated.

The barriers are institutional and operational:

  • Fragmented responsibilities across hydrometeorology, water management, civil protection, and environmental monitoring prevent shared data pipelines and national‑scale modelling platforms.
  • Limited technical capacity in remote sensing, data assimilation, and hydrological modelling restricts the ability to use satellite datasets operationally.
  • Legacy IT infrastructure is not designed for high volume, near real time satellite data.
  • No national policy mandate recognises satellite hydrology as essential infrastructure, resulting in project based, short term investments.

The Opportunity: Transitioning to a Modern Satellite Enabled System

The limited use of satellite‑based hydrological information across the non‑EU Balkan region creates an unusual advantage: countries can move directly to a modern, integrated water‑information architecture without the burden of legacy systems. Because the key satellite datasets are free and globally accessible, the primary investments required are in data pipelines, modelling capacity, and institutional capability—not in expanding ground‑based sensor networks across difficult terrain.

  • Access to a complete global observing system at zero data cost: The region already has full access to high quality satellite datasets covering rainfall, soil moisture, snow, surface water, evapotranspiration, and groundwater storage. Systems such as GPM, IMERG, CHIRPS, SMAP, Sentinel 1 and Sentinel 2, MODIS, Landsat, GRACE FO, SWOT, ECOSTRESS, and others provide continuous coverage of all major hydrological variables. The marginal cost of accessing these datasets is effectively zero; the real requirement is the institutional and technical capacity to use them operationally.
  • A shift from reactive response to predictive capability: When combined with appropriate hydrological and hydraulic models, satellite datasets can support forecasting systems that provide meaningful lead time for floods, droughts, and seasonal water availability changes. Rainfall and soil moisture products can drive flood forecasting models; evapotranspiration and vegetation stress indicators can support drought early warning; and groundwater storage trends can reveal slow onset risks in karst aquifers. This enables a transition from reactive, event driven response to proactive, risk informed management.
  • Independent visibility across borders: Satellite rainfall, snow, and flood mapping products provide independent insight into upstream basins in neighbouring countries. This is particularly important in the Sava, Drina, Morava, Vardar/Axios, Neretva, and other shared river systems, where upstream conditions strongly influence downstream risk. Satellite based observation allows national authorities to monitor evolving conditions without relying solely on bilateral data sharing arrangements.
  • Hydropower optimisation and energy security: Snow, rainfall, soil moisture, and evapotranspiration datasets can improve inflow forecasts for hydropower reservoirs, enabling more efficient operation and better balancing of flood control and energy generation objectives. Enhanced predictive capability strengthens energy security and supports long term planning under increasing climate variability.
  • Drought early warning and agricultural resilience: Combining satellite rainfall, soil moisture, and evapotranspiration datasets enables the development of drought indices and crop stress maps that can guide irrigation planning, planting decisions, and emergency support to vulnerable agricultural regions.
  • Groundwater and karst system protection: Satellite derived groundwater storage information provides basin scale insight into long term water availability trends, which are otherwise difficult to monitor in complex karst systems. These datasets can help detect emerging depletion patterns and support more sustainable groundwater management.
  • A modern system built on software, data, and people—not hardware: Because these capabilities are driven primarily by data processing, modelling, and institutional capacity, the region can achieve a level of water intelligence comparable to far wealthier countries with relatively modest annual investments. The opportunity lies in building the digital and organisational foundations needed to use satellite data effectively, rather than expanding costly physical monitoring networks.

Requirements for a Modern Satellite‑Enabled Water‑Information System

A satellite‑enabled system depends on a robust data architecture capable of handling continuous, high‑volume, multi‑source inputs. The essential five components are as follows:

1. Data Architecture Requirements

Traditional systems describe work in terms of roles, which bundle many unrelated responsibilities into a single label. The USL instead represents capability at the task level, providing a more precise, portable, and verifiable foundation. The table below highlights the key differences between role‑based and task‑based representations.

  • Automated data ingestion pipelines — Routine acquisition of datasets such as GPM rainfall, SMAP soil moisture, Sentinel 1 flood mapping, MODIS snow and ET, and GRACE FO groundwater without manual downloads.
  • Standardised processing chains — Scripts and workflows that convert raw satellite data into hydrologically meaningful variables (e.g., rainfall grids, soil moisture anomalies, flood extent layers).
  • Centralised data storage — A national repository with versioning, metadata, and consistent naming conventions to ensure interoperability across agencies.
  • APIs and data sharing interfaces — Mechanisms that allow hydromets, water agencies, civil protection, and hydropower operators to access the same datasets in real time.
  • Near real time capability — Infrastructure capable of processing satellite inputs within minutes to hours, enabling operational forecasting and emergency response.

Without these elements, satellite data remains fragmented, manual, and disconnected from decision‑making.

2. Modelling and Forecasting Requirements

Satellite data becomes operationally valuable only when integrated into hydrological and hydraulic models. A modern system requires:

  • Rainfall runoff models capable of ingesting satellite precipitation and soil moisture inputs to generate flood forecasts with meaningful lead time.
  • Hydraulic models for river routing and flood extent prediction, linked to Sentinel 1 flood maps for calibration and validation.
  • Drought monitoring models that combine rainfall, soil moisture, evapotranspiration, and vegetation stress indicators to produce early warning signals.
  • Groundwater trend analysis tools that integrate GRACE FO anomalies with local observations to detect long term changes in karst aquifers.
  • Seasonal outlook models using reanalysis datasets such as ERA5 and MERRA 2 to support agriculture, hydropower, and water resource planning.
  • Model data assimilation frameworks that merge satellite observations with numerical models to improve accuracy and reduce uncertainty.

These modelling capabilities transform raw satellite data into forecasts, alerts, and actionable insights.

3. Institutional and Governance Requirements

A satellite‑enabled water‑information system cannot function without clear institutional roles and coordination mechanisms. The region requires:

  • A designated lead agency responsible for national satellite hydrology operations, including data ingestion, modelling, and dissemination.
  • Formalised inter agency coordination between hydrometeorology, water management, civil protection, environmental authorities, and hydropower operators.
  • A national data sharing framework that defines access rights, responsibilities, and operational procedures for satellite derived products.
  • Standard operating procedures (SOPs) for flood forecasting, drought monitoring, and emergency response that explicitly incorporate satellite datasets.
  • A policy mandate recognising satellite hydrology as essential infrastructure, ensuring continuity beyond project cycles.

4. Human Capacity and Skills Requirements

Satellite‑enabled systems are fundamentally knowledge‑driven. The region needs sustained investment in:

  • Remote sensing specialists to manage satellite data processing and interpretation.
  • Hydrological and hydraulic modellers capable of integrating satellite inputs into forecasting systems.
  • Data engineers and IT specialists to maintain ingestion pipelines, APIs, and cloud or on premise infrastructure.
  • Operational forecasters and analysts trained to use satellite derived products in real time decision making.
  • Cross agency training programmes to ensure consistent understanding and use of satellite based information.

5. IT and Infrastructure Requirements

To support continuous, high‑volume satellite data flows, the region requires:

  • Reliable server or cloud infrastructure capable of storing and processing multi terabyte datasets.
  • High availability systems for operational forecasting and emergency response.
  • Secure data exchange mechanisms for inter agency communication.
  • Scalable architecture that can incorporate new satellite missions such as SWOT or future high resolution sensors.
  • Monitoring and logging systems to ensure reliability and traceability.

With these foundations in place, the region can operationalise satellite hydrology at national scale and align with international best practice.

Proposed System Architecture for a Satellite‑Enabled Water‑Information System

A modern satellite‑enabled water‑information system for the non‑EU Balkan region must be designed as an integrated, end‑to‑end architecture that transforms global satellite observations into operational hydrological intelligence. The system must support continuous data ingestion, automated processing, model integration, real‑time forecasting, and multi‑agency dissemination. This section outlines the proposed architecture, organised into five functional layers: data ingestion, processing and transformation, modelling and assimilation, applications and services, and governance and operations.

Layer 1 — Data Ingestion and Acquisition

The foundation of the system is a set of automated pipelines that continuously acquire satellite, reanalysis, and in‑situ datasets. These pipelines must operate without manual intervention and support near‑real‑time updates. This layer ensures that all relevant datasets enter the system reliably, consistently, and on time. The key components include:

  • Automated satellite ingestion services for datasets such as GPM rainfall, IMERG, SMAP soil moisture, Sentinel 1 radar, Sentinel 2 optical, MODIS snow and ET, GRACE FO groundwater, and SWOT river elevation.
  • Reanalysis ingestion for ERA5 and MERRA 2 to provide atmospheric forcing and long term baselines.
  • In situ integration for rain gauges, stream gauges, snow stations, and groundwater wells, ensuring consistency between satellite and ground observations.
  • Metadata and catalogue services to track dataset provenance, versioning, and quality.

Layer 2 — Data Processing and Transformation

Once ingested, raw satellite data must be transformed into hydrologically meaningful products. This layer provides the computational workflows that convert global datasets into national‑scale operational inputs. This layer transforms diverse satellite inputs into consistent, high‑quality hydrological variables. The core functions include:

  • Spatial and temporal harmonisation — resampling datasets to common grids and time steps suitable for hydrological modelling.
  • Bias correction and quality control — adjusting satellite rainfall, soil moisture, and snow products using available ground observations.
  • Feature extraction — generating flood extent layers from Sentinel 1, snow cover masks from MODIS and Sentinel 2, evapotranspiration fields from ECOSTRESS, and groundwater anomalies from GRACE FO.
  • Anomaly and trend detection — producing soil moisture anomalies, rainfall deficits, snow water equivalent anomalies, and groundwater trends.
  • Data cubes and analysis ready formats — storing processed datasets in formats optimised for modelling and analytics.

Layer 3 — Modelling and Data Assimilation

This layer integrates processed satellite datasets into hydrological and hydraulic models to generate forecasts, risk indicators, and long‑term assessments. This layer converts satellite‑derived variables into actionable hydrological intelligence. The key components include:

  • Rainfall runoff models that ingest satellite precipitation and soil moisture inputs to produce flood forecasts.
  • Hydraulic routing models that simulate river levels and flood extents, calibrated using Sentinel 1 flood maps.
  • Drought monitoring models that combine rainfall, soil moisture, evapotranspiration, and vegetation stress to generate early warning indicators.
  • Groundwater trend models that merge GRACE FO anomalies with local well data to detect depletion or recharge patterns.
  • Seasonal outlook models driven by reanalysis and climate forecast datasets.
  • Data assimilation frameworks that merge satellite observations with numerical models to reduce uncertainty and improve forecast accuracy.

Layer 4 — Applications, Dashboards, and Decision Support Services

This layer provides the operational interfaces used by hydrometeorology, water agencies, civil protection, hydropower operators, and agricultural services. These applications translate complex satellite and model outputs into operational products for decision‑makers. Core applications include:

  • Flood early warning dashboards showing rainfall, soil moisture, river levels, and satellite derived flood extents.
  • Drought monitoring portals integrating rainfall deficits, soil moisture anomalies, evapotranspiration, and vegetation stress.
  • Groundwater trend dashboards displaying basin scale storage changes and long term anomalies.
  • Hydropower inflow forecast tools using snow, rainfall, and soil moisture inputs to support reservoir operations.
  • Transboundary basin monitoring interfaces providing independent visibility into upstream rainfall, snowmelt, and flood conditions.
  • Environmental monitoring tools for turbidity, sediment, and chlorophyll using Sentinel 2 and Landsat.

Layer 5 — Governance, Operations, and Inter Agency Coordination

The final layer ensures that the system functions reliably, sustainably, and consistently across institutions. This layer ensures that the architecture is not just technically sound but operationally viable. The key elements include:

  • A national operations centre responsible for running ingestion pipelines, models, and dashboards.
  • Inter agency data sharing agreements enabling hydromets, water agencies, civil protection, and hydropower operators to access the same datasets and forecasts.
  • Standard operating procedures (SOPs) defining how satellite derived products are used during floods, droughts, and emergencies.
  • Maintenance and update cycles for models, pipelines, and infrastructure.
  • Training and capacity building programmes to ensure long term sustainability.

Priority Use Cases for a Satellite‑Enabled Water‑Information System

A modern satellite‑enabled water‑information system must deliver clear operational value across the full spectrum of hydrological risks and water‑management needs in the non‑EU Western Balkan region. The following priority use cases represent the most immediate and high‑impact applications of satellite‑derived datasets, numerical models, and integrated decision‑support tools. Each use case addresses a specific regional challenge and demonstrates how satellite hydrology can strengthen forecasting, early warning, planning, and cross‑border coordination.

To provide a clear overview before the descriptions that follow, the table below summarises these priority use cases, the satellite inputs that enable them, and the operational benefits they deliver to national agencies.

Flood Forecasting and Early Warning

Floods are among the most frequent and damaging hazards in the region, driven by steep terrain, rapid runoff, and transboundary river systems. Satellite datasets can significantly enhance flood forecasting capability by providing continuous, basin‑wide visibility. Key components include:

  • Satellite rainfall inputs from GPM and IMERG to drive rainfall runoff models.
  • Soil moisture conditions from SMAP to improve antecedent wetness estimates.
  • Real time flood extent mapping from Sentinel 1 radar to validate and calibrate hydraulic models.
  • Transboundary basin monitoring using satellite rainfall and snowmelt to track upstream conditions in neighbouring countries.

A satellite‑enabled water‑information system delivers clear operational benefits, providing earlier and more accurate flood warnings, improved situational awareness during emergencies, reduced dependence on sparse ground‑gauge networks, and independent visibility across borders. Together, these advantages strengthen national forecasting capability, support coordinated emergency response, and ensure that all agencies operate from a shared, reliable, region‑wide picture of hydrological conditions.

Drought Early Warning and Agricultural Advisory Services

Droughts in the region develop quickly, especially in Mediterranean‑influenced and karst landscapes. Satellite datasets provide the continuous monitoring needed to detect emerging deficits before impacts occur. The core elements include:

  • Rainfall deficits from CHIRPS and IMERG
  • Soil moisture anomalies from SMAP and ESA CCI
  • Evapotranspiration and vegetation stress from MODIS ET and ECOSTRESS
  • Seasonal outlooks using ERA5 and MERRA 2

Applications, include drought severity indices, crop stress maps, irrigation advisory tools, and early warning bulletins for farmers and water managers. Together, these capabilities provide a continuous picture of agricultural conditions, enabling earlier interventions, more efficient water use, and better planning during dry seasons.

Hydropower Inflow Forecasting and Reservoir Optimisation

Hydropower is a major component of the region’s energy systems. Satellite datasets can improve inflow forecasts and support more efficient reservoir operations. The key inputs include:

  • Snow cover and snowmelt from MODIS snow and Sentinel 2
  • Rainfall and soil moisture from GPM, IMERG, and SMAP
  • Evapotranspiration from MODIS and ECOSTRESS
  • Seasonal climate drivers from ERA5

A satellite‑enabled system delivers major operational gains by providing more accurate inflow prediction, giving operators earlier insight into changing basin conditions. This, in turn, enables more effective balancing of flood‑control and energy‑generation objectives, allowing reservoirs to store or release water with greater confidence. It also strengthens energy‑security planning by offering a clearer view of seasonal water availability. Taken together, these improvements reduce operational uncertainty during extreme events, supporting safer, more efficient, and more resilient water‑resource management.

Groundwater and Karst System Monitoring

Karst aquifers dominate large parts of the region and are difficult to monitor using conventional methods. Satellite‑derived groundwater storage provides basin‑scale insight into long‑term trends. The core components include:

  • Groundwater storage anomalies from GRACE FO
  • Integration with local well data for calibration
  • Trend analysis to detect depletion or recharge patterns

The applications include long‑term groundwater‑resource planning, drought‑impact assessment, early detection of unsustainable withdrawals, and improved management of transboundary aquifers.

Transboundary Basin Monitoring and Regional Coordination

Most major rivers in the region cross national borders. Satellite datasets provide independent, consistent, basin‑wide visibility that supports cooperation and reduces reliance on bilateral data sharing. Key capabilities are:

  • Upstream rainfall and snowmelt monitoring using GPM, IMERG, MODIS, and Sentinel 2
  • Flood extent mapping from Sentinel 1 across entire basins
  • Surfacewater dynamics from SWOT
  • Consistent cross-border datasets unaffected by national boundaries

The benefits include improved situational awareness during regional flood events, harmonised data for river‑basin authorities, and stronger evidence base for transboundary water agreements.

Environmental Monitoring and Water Quality Assessment

Satellite optical datasets provide continuous spatial coverage of lakes, reservoirs, and rivers, supporting environmental oversight and regulatory compliance. The most relevant datasets are:

  • Water turbidity, sediment, and chlorophyll from Sentinel 2 and Landsat
  • Surface water extent from Sentinel 1 and MODIS
  • Land use and land cover change from Sentinel 2

The benefits include improved situational awareness during regional flood events, harmonised data for river‑basin authorities, and stronger evidence base for transboundary water agreements.

Governance and Institutional Model

A satellite‑enabled water‑information system can only function effectively when supported by clear institutional roles, coordinated operational procedures, and a governance framework that ensures long‑term sustainability. Technical capability alone is not enough; forecasting, early warning, and water‑resource management depend on the ability of multiple agencies to access, interpret, and act on shared information. For the non‑EU Western Balkan region, this requires a governance model that enables integrated, cross‑sectoral operation of a modern satellite‑based hydrology system.

A successful system must be anchored by a single national institution with the mandate and capacity to operate the satellite‑hydrology platform. This lead agency is responsible for running data‑ingestion pipelines for datasets such as GPM rainfall, SMAP soil moisture, and Sentinel‑1 flood mapping; maintaining hydrological and hydraulic models, including calibration, validation, and data assimilation; producing national‑scale forecasts and bulletins for floods, droughts, groundwater trends, and seasonal outlooks; coordinating with civil‑protection authorities during emergencies; and managing the national data repository while ensuring data quality. In most countries, the national hydrometeorological service is the natural lead agency due to its operational mandate, forecasting responsibilities, and existing technical infrastructure.

Because satellite‑enabled hydrology spans water management, civil protection, hydropower, agriculture, and environmental monitoring, structured inter‑agency coordination is essential. Effective operation requires a national water‑information coordination group that brings together hydrometeorological services, water agencies, civil‑protection authorities, environmental institutions, and hydropower operators. Shared operational procedures for floods, droughts, and groundwater events ensure that all institutions work from the same datasets and forecasts. Joint situation reports during emergencies, based on common satellite‑derived products, help maintain a unified national picture. Regular technical working groups are needed to review model performance, data quality, and system updates. These mechanisms prevent satellite‑derived information from becoming siloed and instead embed it within a unified national decision‑making framework.

A national data‑sharing and information‑management framework is also required to support seamless exchange of satellite‑derived datasets, forecasts, and alerts. This framework must guarantee open access to core datasets—such as rainfall, soil moisture, snow, flood extent, and groundwater anomalies—for all relevant agencies. Automated data exchange should be enabled through APIs and machine‑to‑machine interfaces, supported by standardised metadata, naming conventions, and version control. Clear data‑licensing rules must define which products are public, restricted, or internal. Together, these elements ensure that all institutions operate from a single, authoritative source of truth.

Operational procedures and emergency protocols must formally embed satellite‑derived information into national workflows. Flood procedures should specify how satellite rainfall, soil moisture, and flood‑extent maps feed into warnings and alerts. Drought procedures must define how rainfall deficits, evapotranspiration, and soil‑moisture anomalies trigger early‑warning stages. Groundwater procedures should guide interpretation of GRACE‑FO anomalies and their integration into planning. Civil‑protection protocols must define how satellite‑derived situational awareness is used during emergencies. These procedures ensure that satellite data is not merely available but operationally embedded.

Long‑term sustainability requires legal and policy alignment. Satellite hydrology must be recognised as part of national water‑information infrastructure through a formal policy mandate. Alignment with EU and international frameworks—including the Water Framework Directive, Floods Directive, Sendai Framework, and UNECE water conventions—ensures coherence with regional and global standards. Integration into national disaster‑risk‑reduction strategies and climate‑adaptation plans provides the legal foundation for sustained investment and inter‑agency cooperation.

Finally, a sustainable system requires stable funding for operations, maintenance, and staffing. This includes dedicated annual budgets for data pipelines, modelling, IT infrastructure, and personnel; multi‑year investment plans aligned with national water‑management and climate‑adaptation strategies; cost‑sharing mechanisms between hydrometeorological services, water agencies, civil‑protection authorities, and energy operators; and partnerships with international organisations for capacity building and system enhancement. Because satellite datasets are free, the primary costs relate to people, infrastructure, and governance rather than data acquisition.

Stakeholder Matrix

Implementation Roadmap

Building a satellite‑enabled water‑information system requires a phased, structured approach that balances technical development, institutional coordination, and capacity building. The roadmap below outlines a realistic three‑year pathway for the non‑EU Western Balkan region to move from minimal satellite use to a fully operational, integrated system. Each phase builds on the previous one, ensuring that early investments create the foundation for more advanced capabilities.

Phase 1 — Foundation and System Setup (0–12 months)

The first year focuses on establishing the core data and technical infrastructure required for satellite hydrology to function reliably.

Key Actions
  • Establish a national satellite hydrology operations team within the designated lead agency.
  • Deploy automated data ingestion pipelines for GPM/IMERG, SMAP, Sentinel 1, Sentinel 2, MODIS, GRACE FO, ERA5, and MERRA 2.
  • Create a centralised data repository with metadata, versioning, and analysis ready formats.
  • Develop initial processing chains for rainfall, soil moisture, snow cover, evapotranspiration, flood extent, and groundwater anomalies.
  • Integrate in situ data (gauges, snow stations, groundwater wells) to support calibration and validation.
  • Launch basic dashboards for rainfall, soil moisture, snow cover, and flood mapping.
  • Begin staff training in remote sensing, data engineering, and hydrological modelling.

By the end of Phase 1, the system achieves a fully operational foundation for national satellite‑enabled hydrology. Continuous satellite‑data ingestion is running reliably, ensuring that key datasets flow into the system without manual intervention. Core products are automatically processed and stored in a national repository, creating a single authoritative source of hydrological information. Basic internal visualisation tools are in place, allowing technical staff to explore rainfall, soil moisture, snow, and flood‑mapping layers. Institutional roles and responsibilities for satellite hydrology are formally defined, establishing the governance structure needed for the next phases of system expansion.

Phase 2 — Operationalisation and Early Services (12–24 months)

The second year focuses on integrating satellite datasets into hydrological models and delivering the first operational services.

Key Actions
  • Integrate satellite rainfall and soil moisture into rainfall runoff models for flood forecasting.
  • Develop hydraulic models calibrated using Sentinel 1 flood extent maps.
  • Operationalise drought monitoring tools combining rainfall deficits, soil moisture anomalies, and evapotranspiration.
  • Launch groundwater trend dashboards using GRACE FO and local well data.
  • Deploy transboundary basin monitoring interfaces showing upstream rainfall, snowmelt, and flood conditions.
  • Establish SOPs for using satellite products in flood and drought operations.
  • Expand training programmes for hydromets, water agencies, civil protection, and hydropower operators.

By the end of Phase 2, the system moves from foundational capability to full operational use across key hydrological domains. Satellite‑driven flood and drought products are incorporated into routine workflows, providing national authorities with timely, spatially consistent intelligence for early warning and response. Transboundary monitoring becomes available, giving agencies continuous visibility across shared basins and upstream catchments. Groundwater‑trend analysis, derived from satellite observations, is integrated into planning processes, supporting long‑term water‑resource management. Most importantly, agencies begin using satellite‑derived information in real‑time decision‑making, marking the transition from experimental use to operational reliance across the national water‑management system.

Phase 3 — Full Integration and Advanced Services (24–36 months)

The third year focuses on scaling the system, improving accuracy, and embedding satellite hydrology into national governance frameworks.

Key Actions
  • Implement data assimilation frameworks to merge satellite observations with hydrological and hydraulic models.
  • Deploy seasonal outlook tools for agriculture, hydropower, and water resource planning.
  • Integrate SWOT derived river elevation data into surface water monitoring.
  • Expand environmental monitoring services (turbidity, sediment, chlorophyll) using Sentinel 2 and Landsat.
  • Establish a national multi agency operations centre for satellite enabled forecasting and early warning.
  • Formalise long term governance arrangements including data sharing agreements and maintenance budgets.
  • Develop public facing dashboards for transparency and risk communication.

By the end of Phase 3, satellite hydrology becomes fully embedded within national forecasting, planning, and operational systems. Satellite‑derived products are integrated directly into hydrological models, seasonal outlooks, and long‑term water‑resource strategies, ensuring that ministries and agencies rely on them as core operational inputs. Multi‑agency coordination is institutionalised, with established procedures, shared platforms, and routine joint decision‑making across hydrometeorology, water management, civil protection, energy, agriculture, and environmental authorities. Advanced services are operational, supporting hydropower optimisation, agricultural drought management, groundwater planning, and environmental oversight. At this stage, the region achieves a modern, predictive, satellite‑enabled water‑information system aligned with international best practice, providing a durable foundation for climate resilience and integrated water‑resource management.

Cross Cutting Requirements Across All Phases

Some elements must be developed continuously throughout the roadmap:

  • Capacity building — ongoing training in remote sensing, modelling, and data engineering.
  • IT infrastructure scaling — ensuring storage, compute, and network capacity grow with system demands.
  • Quality assurance and validation — routine comparison of satellite products with ground observations.
  • Stakeholder engagement — regular coordination with hydromets, water agencies, civil protection, hydropower, agriculture, and environmental authorities.
  • Sustainability planning — long term budgeting, staffing, and governance.

The implementation roadmap provides a clear, structured pathway for moving from foundational data pipelines to fully operational, multi‑agency satellite‑enabled services. By progressing through phased development, the region can build capacity gradually, ensuring that institutions develop the technical and operational skills required for long‑term sustainability. This approach also minimises risk by allowing systems to be tested, refined, and validated before scaling. It strengthens institutional alignment by embedding roles, responsibilities, and coordination mechanisms early in the process. Most importantly, it delivers operational value from the outset, ensuring that agencies begin benefiting from satellite‑derived information well before the full system is completed.

The implementation of this roadmap is expected to be supported primarily through EU IPA funding—most likely through a 36‑month project aligned with the three phases described above, which represents the most suitable mechanism for regional digital‑water and climate‑resilience investments. An illustrative example of what such a project could look like is provided in Annex A — Example Only: Potential Structure for an EU IPA Project ToR.

Additional technical support, financing, and regional coordination can be provided by several key organisations. The Regional Cooperation Council (RCC) can facilitate political alignment and regional policy coherence, while the International Sava River Basin Commission (ISRBC) can support harmonisation of standards and cross‑border basin management. The UNECE Water Convention bodies offer guidance on transboundary data sharing and legal frameworks. International partners such as the World Bank, UNDP, WMO, and EEA can contribute funding, capacity building, and technical oversight. Together, these institutions help ensure that the system is interoperable, regionally coherent, and aligned with international best practice.

Costing and Resource Requirements

The implementation of a regional satellite‑enabled water‑intelligence system across the six non‑EU Western Balkan states requires a structured financial plan that reflects the region’s diverse institutional arrangements, varying technical capacities, and phased development approach. Because hydrometeorological and water‑management responsibilities are distributed differently across Albania, Bosnia and Herzegovina, Kosovo, Montenegro, North Macedonia, and Serbia, the costing model must be flexible enough to accommodate national budgeting processes while still supporting a coherent regional architecture. This section provides a realistic costing framework based on international benchmarks, regional project experience, and the technical requirements outlined in earlier sections. Costs are presented as ranges rather than fixed values, recognising that procurement pathways, staffing models, and cloud‑infrastructure choices can significantly influence total expenditure.

A key principle of the costing framework is that satellite‑based systems are inherently more cost‑efficient than traditional monitoring networks. Satellite data are free, globally available, and require no physical infrastructure in the field. As a result, the majority of costs relate to cloud processing, modelling infrastructure, personnel, and institutional coordination rather than hardware. This makes the system financially accessible even for countries with limited capital budgets. The cost structure is therefore dominated by software engineering, data‑pipeline development, hydrological modelling, and long‑term operational staffing.

To support decision‑makers, three implementation options are presented: a Minimal Viable System, a Standard Regional System, and a Full‑Spectrum Advanced System. These options differ in scope, modelling depth, automation level, and institutional integration. Each option is viable, but they deliver different levels of predictive capability and operational maturity.

1. Minimal Viable System (MVS)

The Minimal Viable System represents the fastest and least resource‑intensive pathway for the region to adopt satellite‑enabled hydrological prediction. It focuses on establishing essential data pipelines and deploying a limited set of operational models that immediately improve flood and drought preparedness. This option is designed for rapid deployment, low institutional disruption, and early demonstration of value to hydrometeorological services and civil‑protection agencies.

  • Core satellite data ingestion and harmonisation. The system establishes automated ingestion for precipitation, soil moisture, snow cover, and flood mapping datasets. These pipelines form the backbone of all later modelling and ensure that national hydrometeorological services across the region have access to a unified, continuously updated data cube.
  • Basic flood and drought models. The MVS includes simplified rainfall runoff models, satellite enhanced flood extent mapping, and basic drought indices derived from CHIRPS, IMERG, SMAP, and MODIS. These models provide immediate operational value, especially for flash flood prone basins and drought sensitive Mediterranean influenced regions.
  • Lightweight civil protection dashboard. A simple web based interface delivers flood alerts, rainfall maps, and drought indicators to national civil protection agencies. This dashboard prioritises clarity and speed over advanced analytics, ensuring rapid adoption by operational staff.
  • Minimal staffing footprint. The system can be operated with a small team of hydrologists, data engineers, and remote sensing specialists. This makes the MVS financially accessible and institutionally feasible even before long term staffing programmes are established.

2. Standard Regional System (SRS)

The Standard Regional System is the recommended configuration for the non‑EU Western Balkan region. It provides a complete, multi‑model prediction environment that integrates all major satellite datasets, supports all hydrological processes relevant to the region, and delivers a unified dashboard for operational decision‑making. This option balances cost, capability, and institutional complexity, making it suitable for long‑term adoption across multiple countries.

  • Full spectrum satellite ingestion and harmonisation. The SRS includes ingestion pipelines for precipitation, soil moisture, snow, evapotranspiration, groundwater, water quality, and flood mapping datasets. These pipelines are harmonised across national institutions, ensuring that hydromets, river basin authorities, and civil protection agencies operate on a shared information base.
  • Comprehensive hydrological modelling suite. The system deploys rainfall runoff models, 2D hydraulic models, snowmelt models, drought prediction models, groundwater trend analysis, evapotranspiration estimation, and water quality monitoring. This multi model environment enables the region to address floods, droughts, snowmelt, karst recharge, and reservoir management within a single integrated platform.
  • Regional water intelligence dashboard. A unified dashboard provides forecasts, risk maps, groundwater trends, snowmelt indicators, and water quality assessments. It serves as the operational interface for civil protection, hydropower operators, water management agencies, and environmental authorities, enabling shared situational awareness during extreme events.
  • Institutional integration and shared standards. The SRS formalises data sharing protocols, modelling standards, and alerting procedures across national institutions. Regional coordination bodies support interoperability without requiring structural reform.
  • Moderate staffing and training requirements. The system requires dedicated teams of hydrologists, data scientists, and remote sensing specialists in each country. Universities across the region play a central role in training and capacity development, ensuring long term sustainability.

3. Full Spectrum Advanced System (FSAS)

The Full‑Spectrum Advanced System represents the highest level of capability and aligns the region with the most advanced water‑prediction systems in Europe. It builds on the Standard Regional System but adds high‑resolution modelling, machine‑learning‑based data assimilation, reservoir‑operation optimisation, and advanced environmental‑monitoring modules. This option is suitable for long‑term regional modernisation and for institutions seeking to position the Balkans as a leader in satellite‑enabled hydrology.

  • High resolution hydraulic and hydrological modelling. The FSAS includes 2D hydraulic models at 5–10 m resolution, high resolution snowmelt models, and advanced karst recharge simulations. These models provide unprecedented detail for flood risk mapping, reservoir inflow forecasting, and spring discharge prediction.
  • Machine learning based data assimilation. The system incorporates machine learning algorithms to fuse satellite observations with model outputs, improving accuracy during extreme events. This includes assimilation of Sentinel 1 flood masks, SMAP soil moisture, MODIS ET, and GRACE FO groundwater anomalies.
  • Reservoir operation optimisation and hydropower integration. Advanced optimisation modules support hydropower operators across the region. These modules integrate inflow forecasts, sediment transport indicators, and snowmelt predictions to improve energy production and reduce downstream flood risk.
  • Advanced environmental monitoring capabilities. The FSAS includes high resolution water quality modelling, sediment transport analysis, algal bloom prediction, and long term ecological trend monitoring. These capabilities support environmental protection agencies and help countries align with EU Water Framework Directive requirements.
  • Expanded staffing and research integration. The system requires larger specialist teams and deeper collaboration with universities. This creates a regional centre of excellence in satellite hydrology, positioning the Balkans as a leader in predictive water management technologies.

The table below summarises the cost and staffing requirements for each national satellite‑hydrology system configuration, with full‑time equivalent (FTE) staffing levels specified per country.

Beyond capital and operational costs, the system requires sustained investment in human capacity. Hydrometeorological institutions across the region currently operate with limited remote‑sensing and data‑science staffing, making workforce development a critical component of long‑term sustainability. Training programmes at universities in Tirana, Sarajevo, Banja Luka, Pristina, Podgorica, Skopje, and Belgrade will be essential for developing domestic expertise in hydrological modelling, satellite‑data processing, and cloud‑based geospatial analytics. These programmes represent a modest cost relative to the overall system but are indispensable for ensuring that the region can maintain and evolve the platform without long‑term external dependence.

Cloud‑infrastructure costs represent another significant component of the budget. Because satellite datasets are large and updated frequently, the system requires scalable storage, high‑performance compute resources, and automated processing pipelines. Cloud‑based deployment avoids the need for national data centres and reduces capital expenditure, but it introduces recurring operational costs. These costs are manageable and predictable, especially when using tiered storage and scheduled compute workloads, but they must be incorporated into long‑term financial planning.

Institutional coordination also carries a cost, though it is primarily organisational rather than financial. Regional coordination bodies and national ministries will require dedicated staff to manage inter‑agency cooperation, international partnerships, and alignment with EU data‑governance standards. These roles ensure that the system functions as a coherent regional platform rather than a collection of isolated national tools.

The costing and resource requirements presented in this section demonstrate that the non‑EU Balkan region can implement a modern, satellite‑enabled water‑prediction system at a cost that is modest relative to the economic and social benefits it delivers. Flood‑damage reduction, improved drought preparedness, optimised hydropower operations, and enhanced environmental monitoring all generate returns that far exceed the initial investment. The system is therefore not only technically feasible but economically compelling, offering a high‑impact, low‑cost pathway to regional water resilience.

Risks and Mitigation Measures

The development of a satellite‑enabled water‑information system for the non‑EU Western Balkan region carries a set of institutional, technical, operational, and sustainability risks that must be addressed to ensure long‑term success. Although the system is technically feasible and financially accessible, its effectiveness depends on the ability of national institutions to adopt new workflows, maintain data pipelines, and integrate satellite‑derived products into routine decision‑making. The most significant risk arises from institutional fragmentation. Hydrometeorological services, water‑management agencies, civil‑protection authorities, and environmental regulators often operate with separate mandates, data systems, and operational cultures. Without a clear governance framework, satellite‑derived information may remain siloed within individual institutions, limiting its impact. This risk can be mitigated by establishing a national coordination mechanism, formalising data‑sharing agreements, and embedding satellite products into standard operating procedures for floods, droughts, and groundwater management.

A second major risk relates to technical capacity. Many institutions in the region have limited experience with remote sensing, cloud‑based geospatial processing, and hydrological data assimilation. If staffing gaps are not addressed, the system may become dependent on external consultants, reducing national ownership and long‑term sustainability. Mitigation requires sustained investment in training programmes, partnerships with universities, and the creation of dedicated satellite‑hydrology units within national hydrometeorological services. Over time, these teams must be able to operate ingestion pipelines, maintain models, and interpret satellite‑derived indicators without external support.

A third risk concerns IT infrastructure and system reliability. Satellite datasets are large, frequently updated, and computationally demanding. If cloud resources are undersized or poorly configured, the system may experience delays, data gaps, or processing failures during critical events. This risk can be mitigated through scalable cloud architectures, automated monitoring of pipeline performance, and the use of redundant processing pathways to ensure continuity during high‑load periods. Regular stress‑testing during flood and drought seasons will help identify bottlenecks before they affect operations.

Operational integration presents another challenge. Even when high‑quality satellite products are available, forecasters and emergency managers may hesitate to rely on them if they are unfamiliar or perceived as experimental. This risk is common in transitions from traditional gauge‑based systems to blended or satellite‑enhanced approaches. Mitigation requires early engagement with end users, co‑development of dashboards and workflows, and clear documentation of how satellite inputs improve forecast accuracy. Demonstration exercises during flood and drought seasons can build confidence and accelerate adoption.

Financial sustainability also poses a risk. Although satellite data are free, the system requires ongoing investment in staffing, cloud infrastructure, and maintenance. If budgets fluctuate or rely heavily on short‑term projects, the system may degrade over time. This risk can be mitigated by embedding satellite hydrology into national water‑management and disaster‑risk‑reduction strategies, ensuring that operational costs are recognised as essential public‑service expenditures rather than discretionary project items. Multi‑year budgeting and cost‑sharing arrangements between hydromets, water agencies, civil protection, and energy operators can further stabilise funding.

Finally, there is a risk related to regional coordination. Because major river basins such as the Sava, Drina, Morava, Vardar/Axios, and Neretva cross national borders, inconsistent adoption of satellite‑enabled systems could create uneven capabilities and reduce the benefits of shared situational awareness. This risk can be mitigated through regional cooperation platforms, harmonised data standards, and shared training programmes that ensure all countries operate at a comparable level of capability. Over time, regional alignment will strengthen transboundary water governance and improve collective resilience to climate‑driven hydrological extremes.

With appropriate governance, capacity development, infrastructure planning, and financial commitment, the non‑EU Balkan region can implement a robust, reliable, and sustainable satellite‑enabled water‑information system that delivers long‑term operational and strategic benefits.

Conclusion

The non‑EU Western Balkan region faces a convergence of hydrological pressures that demand a more modern, predictive, and integrated approach to water‑information management. Mountainous terrain, rapid runoff, karst aquifers, and transboundary river systems create conditions where floods, droughts, and groundwater fluctuations can develop quickly and with limited warning. Traditional monitoring networks, while essential, are too sparse to provide the basin‑scale visibility required for effective forecasting and long‑term planning. Satellite‑enabled water intelligence offers a practical, scalable, and financially accessible solution to these challenges, providing continuous coverage of rainfall, soil moisture, snow, evapotranspiration, surface water, and groundwater storage across all six countries.

The assessment presented in this report demonstrates that the region is starting from a position of minimal satellite integration, but this gap also represents a strategic opportunity. Because satellite datasets are free, globally available, and require no physical infrastructure, the region can leapfrog directly to a modern water‑information architecture without the burden of legacy systems. By investing in data pipelines, modelling capacity, institutional coordination, and operational staffing, the Balkan states can rapidly build a system that aligns with international best practice and delivers immediate operational value. The priority use cases—flood forecasting, drought early warning, hydropower optimisation, groundwater monitoring, transboundary basin oversight, and environmental assessment—reflect real and pressing needs that satellite‑derived information is uniquely positioned to address.

The proposed system architecture and implementation roadmap provide a clear, phased pathway from foundational data ingestion to advanced modelling and multi‑agency decision support. The costing analysis shows that even the most capable system remains financially accessible, with operational expenses dominated by people, cloud infrastructure, and governance rather than hardware. The risks identified—technical capacity, institutional fragmentation, infrastructure reliability, and financial continuity—are all manageable with appropriate planning, training, and policy alignment. With sustained commitment, the region can build a resilient, predictive, and interoperable water‑information system that strengthens national security, supports economic development, and enhances climate resilience.

Ultimately, satellite‑enabled hydrology is not simply a technological upgrade; it is a strategic investment in the region’s future. By adopting a unified, modern water‑intelligence framework, the non‑EU Western Balkan states can reduce disaster losses, improve resource management, support regional cooperation, and ensure that decision‑makers have the information they need to act with confidence. The opportunity is clear, the benefits are substantial, and the pathway is achievable. What is required now is coordinated action to turn this vision into an operational reality.

Annex A — Example Only: Potential Structure for an EU IPA Project ToR (Not a Standard or Official Template)

Project Title: “Regional Satellite Enabled Water Intelligence System for the Non EU Balkan Region”

Estimated Budget Required: €3,000,000
Implementation Period: 36 months

1. Background and Rationale

The six non‑EU Balkan states face increasing hydrological risks driven by climate variability, rapid runoff, snowmelt dynamics, and complex karst groundwater systems. Existing monitoring networks are sparse, fragmented, and insufficient for basin‑scale forecasting. Satellite‑enabled hydrology provides a cost‑effective pathway to modernise water‑information systems by integrating global datasets such as GPM rainfall, SMAP soil moisture, Sentinel‑1 flood mapping, and GRACE‑FO groundwater.

The project will support the development of a regional, interoperable, satellite‑enabled water‑intelligence platform, strengthening forecasting, early warning, and water‑resource planning across Albania, Bosnia and Herzegovina, Kosovo, Montenegro, North Macedonia, and Serbia.

2. Overall Objective

To enhance climate resilience and water‑risk management in the non‑EU Balkan region by establishing a regional satellite‑enabled water‑intelligence system that provides continuous, high‑resolution hydrological monitoring and predictive capability.

3. Specific Objectives

  • Establish automated regional data ingestion pipelines for satellite and reanalysis datasets.
  • Develop harmonised hydrological and hydraulic modelling tools for floods, droughts, snowmelt, and groundwater.
  • Deploy a regional water intelligence dashboard for operational agencies.
  • Strengthen institutional coordination and data sharing across the six countries.
  • Build long term technical capacity in remote sensing, modelling, and cloud based geospatial analytics.

4. Scope of Work

The contractor will deliver a complete operational system, capacity‑building programme, and governance framework. The work is organised into five components.

Component 1 — Regional Data Infrastructure (Budget: €750,000)

The contractor will design and deploy automated data ingestion pipelines for:

  • Precipitation (GPM, IMERG, CHIRPS)
  • Soil moisture (SMAP, ESA CCI)
  • Snow cover and ET (MODIS, Sentinel 2, ECOSTRESS)
  • Flood extent (Sentinel 1)
  • Groundwater anomalies (GRACE FO)
  • Reanalysis datasets (ERA5, MERRA 2)

Outputs include a regional data cube, metadata catalogue, and harmonised gridded datasets for all six countries.

Component 2 — Hydrological and Hydraulic Modelling (Budget: €900,000)

The contractor will develop a harmonised modelling suite including:

  • Rainfall–runoff models
  • Snowmelt models
  • Drought monitoring indices
  • Groundwater trend analysis
  • Hydraulic routing for major basins
  • Model data assimilation using satellite inputs

Models must be calibrated for at least 12 priority river basins across the region.

Component 3 — Regional Water Intelligence Dashboard (Budget: €550,000)

The contractor will build a multilingual, web‑based dashboard providing:

  • Flood forecasts and flood extent maps
  • Drought indicators and soil moisture anomalies
  • Snowmelt and reservoir inflow indicators
  • Groundwater storage trends
  • Training programme and certification
  • Environmental monitoring layers (turbidity, chlorophyll)

The dashboard must include APIs for national hydromets and civil‑protection agencies.

Component 4 — Institutional Coordination and Governance (Budget: €300,000)

The contractor will support:

  • A Regional Water Intelligence Coordination Group
  • Harmonised data sharing protocols
  • Standard operating procedures for floods and droughts
  • Alignment with EU Water Framework and Floods Directives
  • Regional workshops and joint simulation exercises

This ensures interoperability and long‑term sustainability.

Component 5 — Capacity Building and Training (Budget: €500,000)

The contractor will deliver:

  • Training for hydromets, water agencies, civil protection, and universities
  • Certification programmes in remote sensing and hydrological modelling
  • On-the-job training for operational forecasting
  • Regional knowledge exchange events
  • Training programme and certification
  • Training materials, manuals, and e-learning modules

At least 50 staff across the region must be trained.

5. Key Deliverables

  • Regional satellite data ingestion system
  • Harmonised hydrological and hydraulic models
  • Operational regional dashboard
  • Data sharing and governance framework
  • Training programme and certification
  • Final evaluation and sustainability plan

6. Implementation Arrangements

The project will be implemented under Indirect Management with the EU Delegation, with national hydrometeorological services as primary beneficiaries. A regional steering committee will oversee progress and ensure cross‑border alignment.

7. Expected Impact

The project will deliver a fully operational, region‑wide satellite‑enabled water‑intelligence system, improving forecasting accuracy, strengthening disaster‑risk management, supporting hydropower and agriculture, and enhancing climate resilience across the non‑EU Balkan region.

If you’re interested in this initiative, please contact me to discuss.

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Licence: All ideas and concepts shown on this website are shared under the Creative Commons Attribution 4.0 International Licence (CC BY 4.0) . You are free to use, adapt, and build upon them, provided you give appropriate credit to Dr. Patrick Reynolds and include a link to this website.
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