Water data science

This quot;Operational SWAT+ Limpopo River Basin Seasonal Forecasting Systemquot; report outlines the development and implementation of an automated hydrological forecasting system using the Soil and Water Assessment Tool Plus (SWAT+). This system leverages publicly available global datasets and open-source modeling tools integrated within a custom developed automated system to predict seasonal water availability in the Limpopo River Basin (LRB). Key components include integrating the CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data.) and ECMWF (European Centre for Medium-Range Weather Forecasts) precipitation data, comprehensive database management, and real-time monitoring scripts. The system provides accurate and timely water availability forecasts within the LRB to support operational decision making. Future directions focus on improving model calibration, incorporating additional weather variables, better representation of large reservoirs and irrigated areas, applying database optimization procedures, and transitioning to a Docker-based deployment on Amazon Web Services (AWS) for improved scalability and reliability. This SWAT+ operational seasonal forecasting system for the LRB marks a significant step towards bridging a key knowledge gap in the basin to support better decision making on multiple water uses and users including provision for environmental flows. This seasonal forecasting system as a part of the larger river basin Digital Twin is designed to influence effective water resource management in the Southern African region.

As part of the CGIAR Initiative on Digital Innovation, GroundTruth, in partnership with the International Water Management Institute (IWMI), investigated the use of Unmanned Aerial Vehicles (UAVs) to aid in performing bathymetric and water quality surveys. A key outcome of the research and development within this collaboration has been the design and construction of a low-cost survey system comprising a survey vessel equipped with multiple sensors that collect water quality and bathymetric data and can be connected to a UAV. Traditional point-sampling methods limit comprehensive assessments of river health over large spatial areas. This challenge was addressed by developing a drone-towed survey vessel for spatially extensive water quality and depth data collection. The aim of developing the survey vessel was to improve the data collection process which could be useful to further develop the linkages between river flow regimes and water quality parameters. The vessel that was built was equipped with temperature sensors to capture thermal variations across a section of the river, a Total Dissolved Solids (TDS) sensor to monitor total dissolved solids, a Sound Navigation and Ranging (SoNAR) device to map variations in the riverbed profile, a turbidity sensor to provide a measure of water clarity and a Global Positioning System (GPS) module for precise geotagging of all sensor readings. The system was tested at the Lions River in KwaZulu-Natal, South Africa, and the drone-tethered data collection vessel enabled a safe and efficient survey of a river segment. The system was used to collect high-resolution data related to water quality along a reach of the river. The depth data acquired from the vessel was integrated with Light Detection and Ranging (LiDAR) data to generate detailed bathymetric maps for the site. This highlights the potential for expansion in terms of data collection capabilities compared to traditional point sampling methods.

Among many other efforts, high spatial and temporal resolution water quality monitoring data are required to help mitigating the ongoing global freshwater crisis. Citizen science is said to have a high potential to contribute valuable water quality monitoring data, while at the same time offering a range of qualitative benefits such as generation of a social fabric, environmental education, and improved relationships between citizenry and authorities. The potential of citizen science is elevated by integration with technology, especially smartphones, which allow for easy data capture and information sharing among a range of other powerful features. ; As part of the CGIAR Initiative on Digital Innovation, we aimed to test some of the most prominent smartphone applications (apps) to investigate their scalability to developing regions for monitoring the Sustainable Development Goal (SDG) target 6.3.2 indicator water quality parameters or other key water quality metrics. We used southern Africa as a case study, since it characterises numerous key challenges to citizen science water quality monitoring using smartphones in developing regions. We evaluated five smartphone apps that are plug-and-play, assessing both their quantitative accuracy as well as their qualitative suitability to a southern African context. We found that the Hydrocolor and EyeOnWater apps showed theoretical promise but would not be useful for typical citizen science monitoring of streams, river, and dams from the banks of those water bodies given their requirement for deep water. The MQuant StripScan App was not useful given that the reference cards required to use the app could not be sourced and that the app did not function to read the Mquant nitrate test strips. The Nutrient App showed some promise but has ceased being supported, illustrating the critical importance of designing and developing tools with sustainable financing and maintenance in mind (as well as the need for funders to support key tools so they remain freely accessible) so that the great efforts that go into research and development are not ultimately wasted. The Aquality app was fairly user friendly, intuitive, and accessible for free via the Play Store and the Apple App Store. The development and support team were helpful and responsive, with ongoing research and development regarding the app showing good potential for upscaled functionality and implementation in the future. However, we found that there were significant qualitative and quantitative issues with the app that should be investigated further and addressed to ensure the app is suitable for global use, especially in the context of developing regions. These included that i) the material requirements for the app (i.e., a reference card mailed directly from Deltares in the Netherlands and Hach nitrate test strips) were difficult to source in South Africa (which is likely to be the case in many other countries), ii) each test carried a significant finan

The water–energy–food–ecosystems (WEFE) provide vital resources that are essential to human existence. Exploring synergies and trade-offs in these systems has been of interest in recent years to increase economic gain while sustaining the environment. The Tana-Beles Sub-basin of Ethiopia is challenged by population density, climate change, and ecosystem degradation that requires a WEFE Nexus thinking. To understand the current WEFE nexus interactions in the basin, a systematic review of 102 scientific research articles published from 1991 to 2021 was undertaken. Additionally, the systematic review is complemented by spatial data analysis to identify synergies and trade-offs among the WEFE nexus indicators. The analysis revealed the dominance of food–water–ecosystem interdependencies in WEFE nexus research for the Tana-Beles Sub-basin. This dominance is driven by extensive food production activities, which lead to substantial water abstraction and hydrological alterations to meet the intensive water demands of crop cultivation. Simultaneously, the energy-ecosystem interactions are critical due to excessive biomass utilization that exceeds the biomass production potential of the area. Furthermore, the available vegetation cover of the area is very limited to supplement the growing fuel wood demands, which is exerting extreme land degradation and threatening the ecosystem in the sub-basin. This study identifies gaps in WEFE understanding, highlights specific challenges and opportunities within the basin, and calls for coordinated stakeholder action for sustainable resource management through a Nexus approach.