Water Futures Data and Analytics (WFDA)

Permanent URI for this collectionhttps://hdl.handle.net/10568/140565

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Clarity tubes as effective citizen science tools for monitoring wastewater treatment works and rivers
(Journal Article, 2024-09) Graham, P. M.; Pattinson, N. B.; Lepheana, A. T.; Taylor, R. J.
Improved freshwater resource management requires the implementation of widespread, effective, and timely water quality monitoring. Conventional monitoring methods are often inhibited by financial, infrastructural, and human capacity limitations, especially in developing regions. This study aimed to validate the citizen-scientist-operated transparency or clarity tube (hereafter “clarity tube”) for measuring water clarity as a proxy for total suspended solids (TSS) concentration, a critical quality metric in river systems and wastewater treatment works (WWTW) effluent in Southern Africa. Clarity tubes provided a relatively accurate and precise proxy for TSS in riverine lotic systems and WWTW effluent, revealing significant inverse log- linear relationships between clarity and TSS with r 2 = 0.715 and 0.503, respectively. We demonstrate that clarity-derived estimates of TSS concentration (TSScde) can be used to estimate WWTW compliance with WWTW effluent TSS concentration regulations. The measurements can then be used to engage with WWTW management, potentially affecting WWTW performance. Overall, these findings demonstrate the usefulness of clarity tubes as low-cost, accessible, and easy-to-use citizen science tools for high spatial and temporal resolution water quality monitoring, not only in rivers in Southern Africa but also in WWTW effluent for estimating compliance, with strong global relevance to the sustainable development goals (SDGs).
WaterCopilot: a water management AI virtual assistant for the Limpopo River Basin Digital Twin - user guide V0 202410
(Report, 2024-12-30) Vickneswaran, Keerththanan; Retief, H.; Padilha, R.; Dickens, Chris; Silva, Paulo; Ghosh, Surajit; Garcia Andarcia, Mariangel
The Limpopo Digital Twin Water Management AI Virtual Assistant User Guide provides a practical guide for users to effectively navigate WaterCopilot, an AIpowered Copilot developed by the International Water Management Institute (IWMI) in collaboration with Microsoft Research. This guide offers clear instructions on using the Copilot to access crucial water-related data for the Limpopo River Basin, including rainfall insights, environmental flow alerts, and water availability. The guide highlights key features such as a userfriendly interface, multilingual support, and interactive data retrieval, making WaterCopilot accessible to a broad range of users, from researchers and policymakers to individuals with limited technical expertise. It also explains the Copilot’s ability to analyze historical and real-time data, helping users identify patterns and make informed decisions. In addition, the user guide includes troubleshooting tips and a frequently asked questions (FAQs) section, ensuring a smooth and efficient user experience. By following this guide, users will be empowered to leverage WaterCopilot for sustainable water management within the Limpopo River Basin.
WaterCopilot: a water management AI virtual assistant for the Limpopo River Basin Digital Twin - technical guide
(Report, 2024-12-30) Vickneswaran, Keerththanan; Retief, H.; Padilha, R.; Dickens, Chris; Silva, Paulo; Garcia Andarcia, Mariangel
The present document provides a comprehensive overview of the development, architecture, and capabilities of the Limpopo Digital Twin Chatbot or Copilot (WaterCopilot). WaterCopilot is an AI-driven virtual assistant designed to enhance data accessibility and support decision-making for water management in the Limpopo River Basin (LRB). It has been developed through collaboration between the International Water Management Institute (IWMI) and Microsoft Research. WaterCopilot integrates advanced natural language processing with real-time data retrieval to address key challenges in water resource management, including fragmented information sources, manual data processing, and delays in response. The document outlines the project's objectives, system architecture, and modular plugin approach, which enables the Copilot to seamlessly connect with various datasets, including real-time environmental data, historical records, and policy documents related to water availability, rainfall patterns, and environmental flow. By leveraging Azure OpenAI services, WaterCopilot interprets user queries and retrieves relevant information. Key features of the Copilot include real-time monitoring of water availability, rainfall patterns, and environmental flow alerts, as well as userfriendly data visualizations and contextual insights. The deployment strategy utilizes Docker containers on AWS infrastructure, ensuring scalability, reliability, and efficient performance of the Copilot. This document also addresses the technical challenges encountered during development, the solutions implemented to create a robust and adaptable system, and outlines future work aimed at further enhancing WaterCopilot's capabilities. This detailed documentation serves as a technical guide to understanding WaterCopilot's capabilities, architecture, and future directions, emphasizing its role in supporting sustainable water management across the LRB.
Remote sensing estimations of water quality dynamics in the Asian mega deltas
(Abstract, 2024-05-07) Jampani, Mahesh
In the Asian Mega Deltas, Mekong, Irrawaddy, and Ganges, millions of people depend on the aquatic environments for livelihoods. Inhabitants in these delta systems often face health risks that are amplified by anthropogenic pollution loads from terrestrial environments and tidal incursions from coastal environments. The water quality deterioration in these delta systems is complex, often due to a lack of wastewater treatment capacities, upstream activities, climate change implications, and inefficient water management practices. These impacts often lead to the contamination of both riverine and coastal ecosystems, adversely affecting local livelihoods and economies. Therefore, there is an urgent need to understand water quality dynamics within these deltas. The current research leverages multi-sensor satellite imagery in combination with predictive 20modelling to address these challenges. Overall, this research aims to evaluate the spatial and temporal variations of water quality and provide an essential understanding of contaminant plume extent, seasonal dynamics, and pollution occurrence based on events. This research and analysis provide insights into pollution dynamics, evaluating impacts, and developing robust strategies to improve water management in delta systems, thereby mitigating public health risks.
Integrated socio-hydrological dynamics and stakeholder views to develop conceptual water flows and salinity patterns for a polder system in coastal Bangladesh
(Abstract, 2024-12-12) Jampani, Mahesh; Mizan, Syed Adil; Hasib, Md. R.; Nesaruddin, Md.; Mondal, M. K.; Sena, Dipaka Ranjan; Mazid-UL Haque, T.; Alam, R.; Matheswaran, Karthikeyan
Polder systems in the Ganges delta in Bangladesh sustain intensive agricultural production and the livelihoods of about eight million people. These low-lying islands, composed mainly of alluvial sediment deposits, are critical in reducing environmental vulnerabilities against coastal erosion, flood inundation, and saltwater intrusion. The anthropogenic pressures from humans have significantly altered natural hydrological processes in this delta system, leading to numerous emerging problems. These challenges include the evolution of river channels and floodplains, water logging, sea-level rise, tidal surges, and salinity intrusion, all of which impact crop yields, agricultural productivity, and freshwater availability. With more than 160 polders spread across the region, they are predominantly used for rice cultivation in the wet season and rabi crop cultivation in the dry season. Our research aims to understand these complex dynamics of the polder system by appraising the stakeholders’ perspectives and socio-hydrological characteristics of a polder near Khulna in coastal Bangladesh. We employed a range of primary and secondary data sources, including hydrological and water quality data, inputs from government stakeholders through a workshop, and farmers' views via semi-structured surveys, and reviewed relevant literature to analyze polder heterogeneity and social dynamics. Our findings highlight the complex interplay of water availability, water use, seasonal variability, and farmers' and government stakeholder perceptions within the polder system. These insights provide a foundation for implementing a comprehensive socio-hydrological framework, which is crucial for addressing the challenges faced by the Ganges delta region. Furthermore, the results provide valuable insights into mechanisms influencing water balance, saline water intrusion or intake, crop production, livelihood and seasonal cropping practices, and dependency on groundwater during the dry season. These results can aid decision-makers in enhancing water and salinity management in these polders.
Modeling groundwater flow and salinity dynamics for developing polder management strategies in coastal Bangladesh
(Abstract, 2024-12-11) Mizan, Syed Adil; Jampani, Mahesh; Rahman, Md. A.; Hasib, Md. R.; Sena, Dipaka Ranjan; Mondal, M. K.; Alam, R.; Matheswaran, Karthikeyan
Coastal Bangladesh in the Ganges Delta is comprised of polders, which are unique hydrological boundaries that are crucial for the livelihoods of farmers and local dwellers. These polder systems are facing severe water scarcity for agricultural use in the dry season, and the shallow aquifer system is often saline because of sea level rise, tidal impacts, and incremental groundwater use during Rabi for irrigation. Integrated management options are needed for the polder systems to optimize the salinity conditions. In this context, a comprehensive groundwater flow and salinity transport model was developed for a polder near Khulna City in Bangladesh. Water and salinity dynamics were assessed to develop alternate polder management scenarios. The modeling framework involved coupling MODFLOW and SEAWAT models to evaluate salinity ingress to the aquifer due to tidal interactions and groundwater abstraction. The polder landscape in the Ganges delta system is aligned with a natural hydrological river boundary. The interplay between the polders and the surrounding river system is essential for maintaining the ecological balance of the delta. The controlled water levels within the polders support rice cultivation, aquaculture, and other agricultural activities, while the natural rainfall and tidal hydrology aid in replenishing the local aquifers. Aquifer parameters and geometry, water flows in the polder, climate, hydrology, and water quality data were collected from the field and also obtained from secondary sources. The model encompassed a detailed conceptualization of the polder aquifer system, including the dynamics of surface water-groundwater interactions with tidal intrusion induced salinity gradient. The calibrated model showed good agreement with observed or adopted and simulated groundwater levels within the polder. These findings highlight the significant influence of tidal dynamics in the peripheral rivers on seasonal variations in groundwater flow patterns and salinity dynamics. This model, with its robustness, can serve as a reliable tool for stakeholders and policymakers to design sustainable groundwater management strategies for the polder systems.
Securing water for all: managing physical and economic scarcity in the Anthropocene poster
(Abstract, 2024-12-11) Jampani, Mahesh; Müller, A. B.; Gebrechorkos, S. H.
The Anthropocene, characterized by significant human impacts, raises unprecedented water management challenges due to physical and economic water scarcity. Climate change exacerbates the problem by altering the hydrological cycle and increasing extreme events' frequency. Physical water scarcity concerns insufficient water to meet human and environmental needs, while economic scarcity results from infrastructure and financial deficiencies. This session explores the complex dynamics of water scarcity and its interconnectedness with hydrology, climate, pollution, health, and resource allocation, highlighting solutions and research gaps.
REHYDRATE - an international HELPING working group to REtrieve historical HYDRologic dATa and Estimates
(Abstract, 2024-04-14) Bertola, M.; Mazzoglio, P.; Gelebo, A. H.; Shobha, A. R.; Jampani, Mahesh; Singh, S.; Prieto, C.; Panda, S.; Zaifoglu, H.; Bhowmik, A.; Guesri, M.; Dietrich, S.; Tegegn, Z.; Viglione, A.; Bonaccorso, B.; Claps, P.; Manfreda, S.; Koren, G.; Moulds, S.; Ganapathy, A.; Pizarro, A.; Lešcešen, I.; Jorquera, J.; Morbidelli, R.; Nearing, G.; Treppiedi, D.; Alexander, S.; Gilite, K.; Dallan, E.; Otieno, W.; Houteta, D. K.; Filipova, V.; Rosselló-Geli, J.; Koriche, S.; Faerber, C.; Vidal, J.-P.; Akpoti, Komlavi; Vincent, K.; Aslam, H.; Musau, J.; Domeneghetti, A.; Rahmad, R.; Moccia, B.; Badji, A.; Ceola, S.; Jean-Emmanuel, P.; Roy, T.; Nandikanti, S. S. S.; Zhang, Q.; Chaffe, P.; Mendiondo, E. M.; Cudennec, C.; Fan, X.; Gargouri, E.; Izzeddine, M.; Korichi, A.; Abdessamed, D.; Merheb, M.; Lamia, R.; Slimane, B.; De Smeth, K.; Goody, N.; Newcomer, M.; Slama, F.; Abdeldjabbar, B. S.; Whitaker, A.; Surendran, U.; Chauhan, G.; Montanari, A.; Chen, A.; Tan, X.; Li, Y.; Wu, S.; Yang, Y.; Yao, J.; Payne, T.
Historical hydrological observations are often stored in printed documents and volumes of archives worldwide. This makes them practically inaccessible and unusable for modern hydrological studies as well as puts them at risk of permanent loss due to the deterioration of their medium. In addition to the intrinsic value of rescuing past observations, having access to historical data is essential for understanding better the complexity and changes in the hydrological cycle and its extremes. Several data rescue initiatives exist, but the efforts are highly fragmented in space and time. Current tools for data digitization include optical character recognition (OCR) software and manual transcription. The latter is often carried out through participatory citizen science projects. The use of OCR software is cheap and fast, but it still requires a considerable amount of manual work due to the diversity of the documents, and its accuracy is, to date, not always acceptable. Manual transcription is more accurate, but extremely resource-intensive. For these reasons, there is a general need for better and less costly methods for hydrological data rescue. New tools are becoming available, and new technologies are developing rapidly. In response to these challenges, the REHYDRATE Working Group has been proposed as part of the IAHS HELPING Science for Water Solutions decade in summer 2023 (https://iahs.info/uploads/HELPING/WG%20Proposal%20REHYDRATE.pdf). The Working Group aims to connect scientists engaged in data rescue, fostering a collaborative community to exchange knowledge, experiences, and best practices in hydrological data rescue and digitization. The ultimate objective is to promote and facilitate hydrologic data digitization initiatives and to ensure their accessibility through open-access repositories. Approximately 80 scientists from diverse geographical regions have joined the Working Group at the time of writing this abstract. Initial meetings were organized in late 2023, and the group is currently working towards its first short-term objective: conducting a comprehensive state-of-theart assessment of methods, initiatives, and articles related to the digitization of historical hydrological data.
Groundwater and urban development
(Abstract, 2024-09-08) Schirmer, M.; Hartog, N.; Nlend, B.; Fallas, H.; Dassargues, A.; Cetinkaya, I. D.; Jampani, Mahesh; Gogu, R.
Urban groundwater is an endangered resource as urban land use exerts enormous and very complex pressures on this resource. This session will provide an overview of urban groundwater studies in the context of urban water management, advances in hydrogeological investigation, monitoring and modelling techniques for urban areas, and highlight the challenges. Techniques for measuring pollutant concentrations, water balancing, and pollutant load estimations will be presented. To fully understand and quantify the complex urban water systems, we need to further develop our methods and combine them with new modelling approaches. In addition, it is essential to enter into an in-depth dialogue with people from urban planning, urban drainage and politics as well as the general public to raise awareness of groundwater. Only in this way will we be able to sustainably manage our water resources in and around our urban areas and incorporate them into future urban planning. For this session we invite especially but not exclusively contributions on the following subtopics: 1. Sustainable management of urban groundwater resource, including water supply from urban groundwater, urban groundwater resource assessment and system analysis, urban groundwater protection, soil and groundwater contamination and remediation, urban water balance, drainage and recharge 2. Groundwater interactions with ecology and the built environment, including dewatering during urban construction, groundwater interactions with urban structures (e.g. subsidence, foundations, infrastructure) 3. Urban groundwater as source and storage for sustainable heating and cooling, including the use of groundwater source heat pump systems, ground source heat pump systems, aquifer thermal energy storage (ATES) systems.
Multidimensional Digital Inclusiveness Index: dimensionality reduction for improved applicability in Digital Agri-solutions
(Report, 2024-12-05) Martins, Carolina Iglésias; Opola, Felix; Garcia Andarcia, Mariangel; Joshi, Deepa; Muller, A.; Christen, R.
This report introduces the refined Multidimensional Digital Inclusiveness Index (MDII), developed to assess and promote inclusiveness in digital innovations within agricultural systems. Developed through iterative consultation with experts and stakeholders, the MDII integrates structural and experiential dimensions of digital inclusiveness. It distinguishes between inclusion — ensuring access and usability — and inclusivity — fostering a sense of belonging and meaningful engagement among diverse underserved groups. By applying theoretical frameworks such as the Capability Approach and the Technology Acceptance Model, the MDII captures the multifaceted nature of digital inclusiveness, addressing both tangible and psychological aspects. The revised framework (Version 3.0) evaluates inclusiveness across seven core dimensions, including accessibility, stakeholder relationships, and the social impacts of digital innovations. Significant refinements have been made to reduce complexity, eliminate redundancies, and introduce actionable core and extended indicators. Piloted across multiple regions, the MDII demonstrates adaptability and effectiveness in assessing inclusiveness within varying socio-economic and cultural contexts. The report highlights the importance of user-centric design and culturally responsive approaches to ensure digital tools are accessible, equitable, and relevant. By addressing critical challenges such as digital illiteracy, device affordability, and socio- cultural constraints, the MDII aims to empower underserved communities and foster resilience within agricultural systems. This refined framework provides actionable insights for policymakers, innovators, and development organizations, supporting the creation of inclusive digital ecosystems that bridge the digital divide. Future steps involve expanding the MDII’s application through multi-country pilots, incorporating empirical feedback to refine the framework further, and developing user-friendly tools to enable real-time evaluation and deliver impactful recommendations.
Fostering inclusive water use and productivity in South Africa and Malawi through VIA’s Chameleon Water Sensor
(Report, 2024-12-04) Opola, Felix Ouko; Dyer, S.; Garcia Andarcia, Mariangel
While digital tools and services present an opportunity to address some of the critical challenges facing food and water systems, concerns remain over large groups of people, such as women, elderly people, or people with little formal education, who may be excluded from the development, use, and benefit of digital innovation. In this report we present the outcome of a study that was conducted to assess whether a digital innovation that provides an irrigation service in many African countries was socially inclusive. The assessment was done with the multi-dimensional digital inclusivity index, a tool that is being developed for assessing digital inclusiveness across various dimensions in food, land, and water systems.
MDII Scoring Dashboard (version 1.00): a tool for visualizing digital inclusiveness and innovation performance
(Report, 2024-12-04) Nisansa, Vinuri; Martins, Carolina Iglésias; Opola, Felix; Roberto, C.; Garcia Andarcia, Mariangel
The MDII scoring dashboard was developed as part of a set of tools to assess the social inclusiveness of digital innovations across food, land, and water systems. This tool provides decision-makers with interactive visualizations and key metrics such as accessibility, user engagement, and cultural sensitivity. The dashboard, shaped by collaborative workshops and feedback, incorporates metadata indicators, feedback mechanisms, and customizable data views for portfolio managers. By integrating both quantitative and qualitative data, it allows for monitoring performance, identifying gaps, and aligning digital tools with inclusiveness goals, supporting adaptive learning and sustainability in digital innovations.
Limpopo River Basin Digital Twin Open Data Cube Catalog
(Report, 2024-12-04) Afham, Abdul; Silva, Paulo; Ghosh, Surajit; Kiala, Zolo; Retief, H.; Dickens, Chris; Garcia Andarcia, Mariangel
A Limpopo River Basin (LRB) Digital Twin, a significant technological innovation, is being developed to assist water managers to assess and manage the water resources of the basin in sustainable ways. At the core of this innovation, the LRB Digital Twin compiles and serves a variety of raster datasets with unique spatial and temporal resolutions tailored to the basin’s characteristics. These datasets include hydrological variables (e.g., precipitation), climate indicators (e.g., temperature), and land surface characteristics (e.g., vegetation cover, land use). Each data set compromises with advanced preprocessing, fusion, and calibration to ensure consistency, accuracy, and reliability, making it suitable for long-term analysis and immediate decision-making. The Open data cube (ODC) framework was used to organize, visualize and analyze the datasets for different stakeholders of LRB effectively. Automations were built on top of the ODC stack for a smooth workflow, which include steps like creating and indexing the metadata into a database. The present report describes the structure ODC follows in cataloging raster datasets, automations in place for handling ODC tasks and implementation steps taken to get ODC and its components up and running. The available products for the Limpopo region include comprehensive data on irrigated areas and drought index. Additionally, there are environmental flow (E-flow) warnings that provide more insights. These resources collectively support thorough understanding of the region’s water and land management dynamics. This helps policymakers and water managers make informed decisions about resource management and agricultural planning, enabling them to respond more effectively to water-related challenges.
Experimental drought forecast for Limpopo River Basin
(Brief, 2024-11-05) Vigneswaran, Kayathri; Ghosh, Surajit; Dickens, Chris; Garcia Andarcia, Mariangel
This brief focuses on drought forecasting in the Limpopo River Basin (LRB), a transboundary river basin in southern Africa that spans South Africa, Botswana, Zimbabwe, and Mozambique. The study addresses the significant impacts of droughts on agriculture, water resources, and livelihoods in the region, exacerbated by climate variability and change. Utilizing the Standardized Precipitation Index (SPI), derived from both historical and forecasted precipitation data, the study evaluates drought conditions from 2023 to 2024, based on data from the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) dataset and European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal forecasts.
Graph theory applications for advanced geospatial modelling and decision-making
(Journal Article, 2024-12) Ghosh, Surajit; Mallick, A.; Chowdhury, A.; De Sarkar, K.; Mukherjee, J.
Geospatial sciences (GS) include a wide range of applications, from environmental monitoring to infrastructure development, as well as location-based analysis and services. Notably, graph theory algorithms have emerged as indispensable tools in GS because of their capability to model and analyse spatial relationships efficiently. This article underscores the critical role of graph theory applications in addressing real-world geospatial challenges, emphasising their significance and potential for future innovations in advanced spatial analytics, including the digital twin concept. The analysis shows that researchers from 58 countries have contributed to exploring graph theory and its application over 37 years through more than 700 research articles. A comprehensive collection of case studies has been showcased to provide an overview of graph theory’s diverse and impactful applications in advanced geospatial research across various disciplines (transportation, urban planning, environmental management, ecology, disaster studies and many more) and their linkages to the United Nations Sustainable Development Goals (UN SDGs). Thus, the interdisciplinary nature of graph theory can foster an understanding of the association among different scientific domains for sustainable resource management and planning.
Assessing El Niño-induced drought in Zambia and its effects using earth observation data
(Journal Article, 2024-10) Ghosh, Surajit; Kour, Sneha; Taron, Avinandan; Kaywala, Karyn; Rajakaruna, Punsisi
Southern Africa faces significant impacts of El Niño primarily in the form of droughts. Zambia is not an exception. Standardized Precipitation Index (SPI), rainfall anomaly and Vegetation Condition Index (VCI) are robust indicators for drought studies due to their distinct and complementary roles. Our results reveal severe meteorological drought conditions in Zambia using SPI and rainfall anomaly. VCI values have declined in the cropping season due to vegetation stress induced by water deficit conditions. Low rainfall leads to widespread deterioration of crop production, with approximately 40.46% of the country experiencing drought conditions in 2023–2024. The Central, Eastern, Southern, Lusaka, and Copperbelt provinces showed lower VCI values in March and April 2024, indicating poor crop health and drought-like conditions. On the other hand, low rainfall has substantially influenced hydropower reservoirs. Significant surface water loss is observed in the hydropower reservoirs such as Itezhi Tezhi Dam (117.40 sq. km), Mita Hills Dam (25.72 sq. km) and in parts of Lake Kariba (58.72 sq. km) between December 2023 and April 2024. This loss has disrupted industries relying on water resources and hindered hydropower generation, leaving substantial portions of the population without electricity for extended periods. The present study aims to explore the power of open access Earth Observation data and cloud analytics to evaluate the extent and multi-sectoral impact of the recent drought in Zambia. Results highlight the upcoming challenges the country might face in food and nutrition and the critical need for stakeholder involvement and policy design to mitigate future crises and strengthen vulnerable communities.
Performance evaluation of ECMWF monthly rainfall forecasts in the Limpopo River Basin
(Report, 2024-10-30) Vigneswaran, Kayathri; Ghosh, Surajit; Retief, H.; Garcia Andarcia, Mariangel; Dickens, Chris
This study evaluates the performance of the European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal rainfall forecasts provided by Limpopo River Basin's (LRB) Digital Twin using Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) dataset as a reference for the period of 2017 to 2024. The primary aim is to assess forecast skill across different climate zones within the LRB, characterized by varying climatic conditions from semi-arid to temperate.
A description of recent drought prevalence in the Limpopo River Basin
(Brief, 2024-10-30) Ghosh, Surajit; Vigneswaran, Kayathri; Dickens, Chris; Retief, H.; Garcia Andarcia, Mariangel
This report provides an in-depth analysis of drought conditions in the Limpopo River Basin (LRB), with a focus on drought frequency, meteorological patterns, and agricultural impacts. Historical drought data and earth observation (EO) datasets are used to monitor and forecast drought severity. Key indices such as the Standardized Precipitation Index (SPI), Vegetation Condition Index (VCI), and rainfall anomalies derived from advanced EO technologies offer valuable insights into the basin's drought dynamics. • Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) datareveals a persistent pattern of dry conditions from March 2023 to the end of theyear, which can be exacerbated by the El Niño phenomenon. Notably, thenorthern and southeastern regions of the basin show the highest concentration ofdry days, critically impacting water availability and agricultural activities. • Vegetation health declined across the basin in the short term because of El Niño,which started in May 2023 and resulted in less than normal rainfall.Approximately 37% of the basin experienced drought during the 2023-2024cropping season, affecting ecosystems and crop yields. • The analysis of the water balance (difference between precipitation andevapotranspiration) for the basin's croplands in 2023 highlights significantfluctuations, with both surplus (Oct 2023 to Feb 2024) and deficit (Jan to Sep in2023) months. This variability underscores the challenges in managing waterresources for agriculture and food security. This data feeds into the IWMI Digital Twin platform for the Limpopo Basin, which provides near real-time hydrological data, supporting informed decision-making for water management and agricultural planning. The platform integrates multiple datasets, allowing policymakers to visualize and assess the evolving drought conditions across the basin.
Operational SWAT+ model: advancing seasonal forecasting in the Limpopo River Basin
(Report, 2024-10-23) Chambel-Leitão, P.; Santos, F.; Barreiros, D.; Santos, H.; Silva, Paulo; Madushanka, Thilina; Matheswaran, Karthikeyan; Muthuwatta, Lal; Vickneswaran, Keerththanan; Retief, H.; Dickens, Chris; Garcia Andarcia, Mariangel
This "Operational SWAT+ Limpopo River Basin Seasonal Forecasting System" 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.
Design, construction and evaluation of a drone-tethered river survey vessel
(Report, 2024-10-15) Maharaj, U.; Singh, K.; Pike, T.; Pike, C.
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.

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