*2.2. Technology Appplications*

Traditional investments in water resources in the developing world have seldom been conceived, implemented, or operated from a holistic multi-sectoral basin perspective. They often are based on old technologies and have high operational and maintenance costs that are seldom met, leading to poor service delivery exacerbated by deferred maintenance as they age. Even basic monitoring data are usually not accessible in real-time and require different 'ringfenced' legacy software that are not inter-operable.

**Figure 3.** Typology of 'disruptive' technologies.

One of the main ways in which modern technology is reshaping water resources planning and management is through 'disrupting' the data value chain (Figure 4). This is manifested through new inexpensive sensors for in-situ monitoring (tending towards an expansive 'internet of things'), increasingly powerful Earth observations from satellites and drones/unmanned aerial vehicles (UAVs) to provide synoptic views of topography (including high-resolution digital elevation models to identify flood-prone areas and support hydrodynamic modeling), climate, water levels, flows, snow cover, inundated areas, landcover, watershed status, and even some aspects of water quality and groundwater. Earth observations [22], with near global consistent coverage, is rapidly becoming a game-changer for synoptic observations in large basins, where the resolution of even the free resources from NASA and ESA are often adequate for useful water resources analytics. New unmanned on-water and under-water vehicles show promise; they can be outfitted with sensors and autonomous (single or swarm) capability for surveying large water bodies (e.g., for bathymetry, hydraulic safety, water quality, or fish stock assessments).

New analytical tools, increasingly cloud-based—including at the global level, assimilate available data and generate estimates of a range of critical parameters related to snowmelt estimation, water balance, water accounting (e.g., WA+, WAPOR) [38,39], scenario analysis, and forecasts to create 'digital twins' of basins to facilitate analyses. These enable access to curated archives and real-time estimates of the water status for any basin anywhere in the world to support both strategic planning and tactical operations through data visualization, early alerts/warnings, and the development of interactive packaging for data, analytics, and knowledge. Examples include interactive portals, mobile phone applications, and dynamic e-books. These support decisions at all levels, from simple scoping of water resources development, to detailed planning with stakeholder involvement/outreach, as well as real-time operations. Additional systems related to data/text mining, social media integration, advanced cloud-based modeling, machine learning/AI, or 'bots' can help bring in an additional automation and integrated perspectives to support decision-making.

**Figure 4.** Modernizing the data value chain (Data→Information→Knowledge→Decision Support).

These technologies are helping water managers reimagine the way information-based decisions can be made for smart water resources planning and management and are allowing development of integrated basin/aquifer plans based on both analytical and stakeholder approaches. Technologies have made possible new approaches to use and conserve water and administer usage caps (e.g., using satellite-derived actual evapotranspiration estimates), adopting a systems perspective to improve agricultural water productivity, benchmark systems, and incentivize sustainability. New in-situ and Earth observation monitoring and analytics allow for development and customization of tools for water planning, allocation, and coordinated water infrastructure operations in an integrated multi-sectoral systems perspective. Water infrastructure can now be operated in a more coordinated systems context for multiple objectives ranging from service delivery to climate resilience. Continuous innovation, piloting, and learning from global good practices enables quick scaling-up of new technologies and enables more adaptive management.

3D printing, robotics, automated transport, advanced materials, nanotech, biotech, and cleantech are supporting new operational systems that represent a paradigm shifts away from traditional approaches. Examples include irrigation systems that improve water productivity and field-level water use efficiency (especially when combined with policies such as limits on water abstraction); 3D printed monitoring stations (e.g., 3D-PAWS [40]) that reduce costs for monitoring weather and water levels; and ultrasonic control systems (successfully piloted in Lake Quaroun in Lebanon) that can mitigate algae-related water quality problems.

Platforms are emerging to enable people to work together in new ways in the sharing economy, including fintech, crowdsourcing, crowdfunding, block-chain enabled supply chains, asset sharing systems, Digital ID enabled e-governance, and open learning platforms. Many of these platforms have application in water management in large basins, including online/mobile platforms to support learning or interactions among remote or disperse water user associations, and platforms to help farmers access global marketplaces online, with feedbacks into irrigation water requirements.

#### *2.3. Implications for Large Basins*

The implications of these new technologies, with a focus on digital technologies, for water resources planning and management in large basins, are summarized in Table 1. Major changes in water management around the world are likely in very short timeframes. Ref [41] Many of the initial impacts will come from the plummeting costs of sensors, mobile devices and connectivity, cloud services (including to process increasingly powerful earth observation and other big data), interoperability due to online data standards and protocols, and increasing digital literacy.

Water data could be used primarily for water assessments, evaluations, operations, foresight, design, accountability, and education [42]. Many of these are useful at different scales—from monitoring progress towards the SDG-6 global indicators to helping design a culvert.

Many countries are modernizing their water resources institutions and developing national water resource information systems and analytics to support basin planning and disaster management. Some are also strengthening ties among government, academic, civil society organizations (CSO), and private sector institutions to develop a broad stakeholder base for this transformation. Modern water information systems require integration of data (from global, regional, national, to local sources), data quality management, conversion to interoperable data services, and development of interactive dashboards to help access and visualize data services and associated analytics in appropriate formats to support decisions.

Large basins will especially benefit from these changes given both the challenges (e.g., the need to integrate data across large areas; multiple stakeholders wishing to inform coordinated decisions; large water infrastructure investments) and the opportunities of large basins (e.g., application of free Earth observations in the 10–250 m resolution range; the ability to deliver reach large numbers of remote beneficiaries with valuable data services).

Institutions such as the Mekong River Commission and the various Nile Basin Initiative centers have demonstrated the utility of modern data and analytics in basin planning and hydro-meteorological data integration. Other large basins (e.g., the Congo, Ganges-Brahmaputra-Meghna) are in the nascent stages of this journey given capacity constraints and transboundary cooperation challenges.

Many countries are modernizing their water information systems taking advantage of new technologies. The United States and Australia are improving their already well-established systems facilitated by strong national institutions. Europe is increasingly building on its regional institutions (e.g., European Centre for Medium-Range Weather Forecasts, European Organisation for the Exploitation of Meteorological Satellites, Joint Research Centre of the European Commission) to help countries access better data and analytics. China is utilizing evapotranspiration estimates derived from Earth observations to improve irrigation management [43,44] and India is enhancing its national water resources information system [45].

Estimates based on satellite products or global models are increasingly found to be comparable with those based on in-situ observations [46,47]. These techniques, especially when enhanced by a new generation of artificial intelligence (AI)/machine-learning (ML) algorithms and global models, can revolutionize water resources management even in data-poor environments. When accessed through customized interactive dashboards, this information can be especially useful for estimating parts of the water balance, estimating flooding areas, making customized weather/hydrologic/inundation forecasts, managing large water demands (e.g., agriculture) and system losses, while enhancing and benchmarking water productivity [48,49].


**1.**Summaryofdisruptivetechnologiesrelevanttowatermanagementin
