The increasing global demand on freshwater is resulting in nations improving their terrestrial water monitoring and reporting systems to better understand the availability, and quality, of this valuable resource. A barrier to this is the inability for stakeholders to share information relating to water observations data: traditional hydrological information systems have relied on internal custom data formats to exchange data, leading to issues in data integration and exchange. Organisations are looking to information standards to assist in data exchange, integration and interpretation to lower costs in use, and re-use, of monitoring data. The WaterML2.0 Standards Working Group (SWG), working within the Open Geospatial Consortium (OGC) and in cooperation with the joint OGC-World Meteorological Organisation (WMO) Hydrology Domain Working Group (HDWG), has developed an open standard for the exchange of water observation data. The focus of the standard is time-series data, commonly used for hydrological applications such as flood forecasting, environmental reporting and hydrological infrastructure, where a lack of standards inhibits efficient re-use and automation. This paper describes the development methodology and principles of WaterML2.0, key parts of its information model, implementation scenarios, evaluation and future work. WaterML2.0 was adopted by the OGC as an official standard in September 2012.

Droughts have severely affected Afghanistan over the last four decades, leading to critical food shortages where two-thirds of the country’s population are in a food crisis. Long years of conflict have lowered the country’s ability to deal with hazards such as drought which can rapidly escalate into disasters. Understanding the spatial and temporal distribution of droughts is needed to be able to respond effectively to disasters and plan for future occurrences. This study used Standardized Precipitation Evapotranspiration Index (SPEI) at monthly, seasonal and annual temporal scales to map the spatiotemporal change dynamics of drought characteristics (distribution, frequency, duration and severity) in Afghanistan. SPEI indices were mapped for river basins, disaggregated into 189 sub-catchments, using monthly precipitation and potential evapotranspiration derived from temperature station observations from 1980 to 2017. The results show these multi-dimensional drought characteristics vary along different years, change among sub-catchments, and differ across temporal scales. During the 38 years, the driest decade and period are 2000s and 1999–2022, respectively. The 2000–01 water year is the driest with the whole country experiencing ‘severe’ to ‘extreme’ drought, more than 53% (87 sub-catchments) suffering the worst drought in history, and about 58% (94 sub-catchments) having ‘very frequent’ drought (7 to 8 months) or ‘extremely frequent’ drought (9 to 10 months). The estimated seasonal duration and severity present significant variations across the study area and among the study period. The nation also suffers from recurring droughts with varying length and intensity in 2004, 2006, 2008 and most recently 2011. There is a trend towards increasing drought with longer duration and higher severity extending all over sub-catchments from southeast to north and central regions. These datasets and maps help to fill the knowledge gap on detailed sub-catchment scale meteorological drought characteristics in Afghanistan. The study findings improve our understanding of the influences of climate change on the drought dynamics and can guide catchment planning for reliable adaptation to and mitigation against future droughts.

Water resources are under growing pressures globally, and better basin planning is crucial to alleviate current and future water scarcity issues. Communicating the complex interconnections and needs of natural and human systems is a significant research challenge. With advances in cyberinfrastructure allowing for new innovative approaches to basin planning, this same technology can also facilitate better stakeholder engagement. The potential benefits of using digital basin planning platforms for stakeholder engagement are immense; yet, there is limited guidance on how to best use these platforms for more effective stakeholder engagement in water-related issues and projects. We detail our digital platform, Basin Futures, and highlight the potential uses for stakeholder engagement through an integrative framework across different assessment levels. Basin Futures is a web application that is an entry-level modelling tool that aims to support rapid and exploratory basin planning globally. As a cloud-based tool, it brings together high-performance computing and large-scale global datasets to make data analysis accessible and efficient. We explore the potential use of the tool through three case studies exploring agricultural development, transboundary water-sharing agreements and allocating water for environmental flows.