In November, the annual SPHY Community Session brought together users of the Spatial Processes in HYdrology (SPHY) model. The session provided a platform to share model developments, methodological advances, and applied case studies across different contexts.

The annual SPHY Community Session opened with updates on the new SPHY version 3.1 presented by Tijmen Schults. Dr. Johannes Hunink reflected on the history of SPHY and its use in research-based consultancy, after which Amelia Fernández Rodríguez introduced the new SPHY QGIS 3 plugin, demonstrating how SPHY is now embedded and accessible in the latest version of QGIS. Researchers and practitioners from various institutes then presented their work using SPHY in different contexts. Dr. Faiz Mohammed shared an agent-based socio-hydrology approach to support sustainable and equitable water management investments, while Dr. Joris Eekhout discussed how future changes in irrigation water supply and demand may affect water security in a Mediterranean catchment. Pranisha Pokhrel presented her application of SPHY in the Karnali River Basin in Nepal, and the session concluded with a presentation by Tijmen Schults on simulating spring discharge within the Roadside Spring Protection project in Nepal.

The session reflected the growing and diverse SPHY user community and the importance of continued exchange between research and practice. We thank all speakers and participants for their contributions and engagement, which support the further development of the SPHY model. A next SPHY Community Session will be held in November 2026.

A scientific paper was recently published in Remote Sensing (doi: 10.3390/rs17111855)  presenting the advanced technology developed by the MAGDA project, which integrates multiple sensor platforms and modeling tools to enhance agricultural weather forecasts and irrigation advisories.

This new research offers a breakthrough in precision farming by combining data from European satellites, drones, ground sensors, and GNSS signals for highly localized and accurate weather and soil moisture monitoring.

The MAGDA system provides significant advantages by improving short-term weather predictions and irrigation scheduling at the field scale, addressing challenges posed by climate change and extreme weather. Farmers gain access to precise information that helps optimize water use, reduce waste, and better protect crops from droughts, floods, and hailstorms.

One key component of the MAGDA system is IrriSPHY-1D, an advanced agro-hydrological model empowered by FutureWater embedded in MAGDA’s irrigation advisory service. IrriSPHY-1D accurately simulates soil moisture dynamics within the crop root zone, and compute Irrigation Water Requirement (IWR) more accurately than ever before. This enhanced capability enables farmers to optimize water application rates, and to reduce waste and minimize the environmental impact of irrigation practices.

The integration of MAGDA datasets —including high-resolution atmospheric data from Meteodrones, satellite soil moisture, and soil moisture retrievals via GNSS reflectometry— within IrriSPHY-1D significantly enhances irrigation advisories. This data fusion enables the system to provide more reliable and actionable irrigation forecasts, improving water management and resilience in agriculture.

With this innovative approach and scientific validation mark, FutureWater and MAGDA’s partners have made a significant contribution to advancing sustainable and climate-resilient farming practices across Europe.

I-DIP builds on InfoSequia, an advanced toolbox that integrates satellite data, local observations, and machine learning to monitor and forecast droughts. A new flash drought indicator, tailored to Pakistan’s climate, will be developed and embedded within NDMC’s existing system. The project will enhance early warning capacities, safeguard food and water security, and contribute to national climate adaptation efforts, paving the way for I-DIP’s upscaling across Pakistan.

Beyond monitoring, I-DIP will connect its forecasts to decision-making tools. Impact information will be disseminated through advisory bulletins and the inFarmer app (developed by WaterSprint), already widely used among farming communities. Field facilitators deployed by the Better Cotton Initiative will translate these insights into actionable guidance for farmers, enabling them to adapt irrigation practices, adjust cropping calendars, and mitigate potential losses. This integration of cutting-edge drought science with established communication networks ensures that early warnings are transformed into practical actions at the field level.

By embedding I-DIP within NDMC’s operational system, the project directly strengthens Pakistan’s early warning capacity for droughts, aligns with national climate policies, and supports the country’s commitments under the Sustainable Development Goals. In the longer term, the pilot is expected to catalyse scaling of I-DIP across Pakistan, offering authorities a state-of-the-art tool to anticipate and manage such extreme events.

We invite you to the SPHY Hydrological Model Webinar on 9 October 2025, from 10:00 to 11:00 CET. This event will showcase the latest developments in SPHY, including new tools, features, and workflows, and provide an interactive platform to ask your questions.

A New Era for SPHY

SPHY is undergoing a major transformation to become more powerful and user-friendly. Recent milestones include:

  • QGIS plugin: a redesigned interface that allows users to set up, run, and visualize SPHY entirely within QGIS.
  • SPHY version 3.1: new features such as bias correction for meteorological data, improved snowmelt routines, and more flexible simulation options.
  • New website and resources: updated manuals, tutorials, and datasets are now available at sphymodel.com.

These innovations make SPHY more accessible and relevant for a wide range of hydrological and water resources applications.

What to Expect at the Webinar

  • Tijmen Schults will introduce SPHY and its latest features.
  • Amelia Fernández Rodríguez will give a live demonstration of the new QGIS plugin.

This is the perfect opportunity to see SPHY in action and get direct input from the experts.

Who Should Attend

The webinar is open to hydrologists, water managers, GIS practitioners, researchers, students, and anyone interested in open-source hydrological modelling.

Practical Info & Registration

  • Date & Time: 9 October 2025, 10:00–11:00 CET
  • Format: Online webinar
  • Cost: Free
  • Register here

Nepal offers an ideal testing ground due to strong government support for climate-smart agriculture, a large population of vulnerable smallholders, and active engagement from organisations like Climate Resilience Research Centre (CRRC) and International Centre for Integrated Mountain Development (ICIMOD). Results from this feasibility will support national policy goals and can be scaled to similar mountain regions across South Asia.

This project focuses on Syangja District, Gandaki Province, which faces growing water scarcity and unpredictable rainfall, especially on hillside farms reliant on spring-fed irrigation and rain-fed agriculture. These conditions make traditional irrigation unworkable and create a need for low-pressure, affordable, and locally adaptable solutions. The Smart Sprayer combines practical hardware with a digital advisory tool to optimise limited water use — a frugal innovation tailored for smallholder needs.

Croptimal combines of crop, field and irrigation characteristics with weather station and satellite data to provide irrigation advice.

The project entails the feasibility of an integrated, low-cost “Smart Sprayer” irrigation system based on Croptimal but tailored for hillside farming that delivers practical WhatsApp/SMS irrigation advice. The main innovation is the Smart Sprayer, a gravity-fed, low-pressure micro-pivot irrigation device paired with a tailored Smart Irrigation Tool. The digital platform delivers daily, data-driven irrigation advice to farmers’ phones. Together, these offer a scalable and cost-effective package for precise and efficient water use on remote hillside farms.

The main objective is to improve water security and agricultural productivity for mid-hill smallholders during the dry season in Nepal. More specifically, to demonstrate the technical, economic and social feasibility of a low-pressure irrigation solution in combination with irrigation advisory based on remote sensing data and weather forecasts. This includes market research and development of business cases for both farmers and local suppliers.

The Croptimal app is available at Croptimal.app. Get in touch with us if you would like more information or to request your own account.

Video: Croptimal – Smart Irrigation Advice Powered by Data

 

To further advance our hydrological model SPHY, we are proud to announce four major milestones for the SPHY modelling community. Since SPHY is widely used by FutureWater in capacity building programs, our goal has always been to make the model and its data as accessible and user-friendly as possible.

Until now, Graphical User Interfaces (GUIs) for SPHY were only available in QGIS for version 2.0. This project has upgraded those plugins to ensure full compatibility with the latest versions of SPHY, QGIS, and Python. The updated plugins also integrate new functionalities to handle cutting-edge data sources as model inputs. With these new QGIS plugins, running SPHY no longer requires programming skills—opening the door for a much broader audience to set up, run, and analyze hydrological simulations with ease.

1. Introducing the SPHY QGIS plugin

SPHY is now directly integrated into QGIS, allowing users to set up, run, and visualize SPHY simulations through an intuitive graphical interface. This plugin streamlines workflows, improves accessibility for new users, and enhances integration with geospatial datasets. Features include

  • Complete SPHY workflow integrated in QGIS
  • Streamlined preprocessing of model inputs
  • Intuitive, no-code interface
  • Results visualized directly in QGIS
  • Modular setup for diverse applications
  • Open-source and fully reproducible

2. New SPHY website

The new SPHY website offers easier navigation, updated documentation, and a central hub for resources, downloads, and training materials. Visit www.sphymodel.com to explore a fresh, modern platform for all SPHY matters.

3. SPHY model version 3.1 released

The latest SPHY release on Github introduces new features, performance improvements, and enhanced capabilities for hydrological and cryospheric modelling. This version builds on the robust foundations of previous releases, integrating feedback from the community and advancing the model’s flexibility and accuracy. It can be downloaded completely free and is open source. New in this version are:

  • Added bias-correction procedure for meteorological forcing
  • Increased flexibility and options for defining simulation periods
  • Enhanced snow melt calculation

4. Updated manuals, tutorials and datasets

Manuals of the new SPHY version and QGIS plugin are now available, as well as new datasets to make your model work. For the new QGIS plugin a video tutorial was made to explain all the ins and outs of the tool.

More to come soon!

These developments mark a significant step forward in making SPHY more accessible, powerful, and user-friendly for researchers, practitioners, and decision-makers worldwide. Soon we will organize a webinar to explain all the new features and later this year we plan on hosting a user day to discuss future model developments with the SPHY community.

Video

On June 25, we celebrated the successful closure of the RoSPro project with a national workshop held in Nepal. The event brought together key stakeholders to reflect on the project’s positive outcomes, including improved spring water access, road resilience, and community engagement in water management.

A key highlight of the project was the Decision Support System (DSS) developed by FutureWater. This system integrated hydrological (as an outcome of the SPHY hydrological model), geospatial, and socioeconomic data into a user-friendly platform, enabling data-driven decisions for sustainable water management. Moreover, the system provides a simple Cost&Benefit Calculator to assist stakeholders in evaluating the potential of proposed management measures for mountain springs.

The workshop underscored the potential for scaling up the approach in other regions, using the DSS to guide future spring protection and water resource management efforts. We look forward to continue this work in the future!

An open access version of the DSS is available here

Cover picture of the DSS

The approach of FutureWater and Galayr is designed to be both scientifically rigorous and contextually grounded, ensuring that the developed drought model is locally relevant, sustainable, and fully integrated into existing national systems such as those of SODMA and NADFOR. The model will merge top-down (data-driven, machine learning-enabled) and bottom-up (stakeholder-informed) approaches, combining satellite data, climate indices, and indigenous knowledge to co-develop impact-based forecasts and consensus-based triggers for anticipatory action.

For the development of the drought forecasting model and the knowledge transfer we will focus on the following pillars:

  • A phased work plan that spans institutional capacity assessments, model development, validation, stakeholder consultations, and hands-on capacity building.
  • Application of state-of-the-art forecasting models ranging from ARIMA and regression to more advanced machine learning techniques, while maintaining focus on usability and institutional adoption.
  • A strong emphasis on knowledge transfer, including training programs and the establishment of a collaborative knowledge-sharing platform using the FutureWater Academy platform
  • A robust risk management plan, including mitigation strategies for data scarcity, stakeholder disengagement, and institutional turnover.

 

The BUCRA (Building Unity for Climate Resilient Agriculture) project aims to strengthen agricultural resilience in Qahbunah, a farming community in Egypt’s Nile Delta. Local farmers face growing pressures from water scarcity, climate change, and land fragmentation, creating an urgent need for innovative and practical solutions to safeguard their livelihoods.

At the core of BUCRA is Croptimal, developed by FutureWater. Croptimal bridges advanced data-driven technologies with local agricultural knowledge to support farmers in making smarter, climate-resilient decisions.

Croptimal is a climate suitability analysis tool that combines climate projections, geospatial data, and agricultural expertise to assess the suitability of crops under both current and future climate conditions. By identifying which crops and locations are most resilient to stressors such as heat, salinity, and water scarcity, Croptimal provides farmers with clear, data-driven recommendations for crop selection and planting strategies. The tool delivers detailed maps and actionable insights, helping farmers adapt to climate change while improving productivity and reducing risk.

Complementing Croptimal, BUCRA also applies smart irrigation advice through digital tools that improve water-use efficiency. Using open-source satellite data, real-time weather information, and local soil conditions, farmers receive precise, daily irrigation recommendations. These are delivered directly via WhatsApp, ensuring the service is accessible, practical, and cost-effective. This approach reduces water and energy use while maintaining or improving crop yields—an essential benefit in the water-stressed Nile Delta.

Beyond digital tools, BUCRA includes demonstration plots that showcase climate-smart practices such as efficient irrigation, improved soil management, and crop rotation. Farmers take part in a blended learning programme, combining hands-on field training with simple digital applications designed for easy adoption.

A strong emphasis is placed on empowering youth and women, strengthening market linkages, and promoting sustainable land-use practices. By aligning Dutch expertise with local needs, BUCRA seeks to increase productivity, stabilise incomes, and build a more sustainable agricultural future for Qahbunah.

The project’s long-term vision is to encourage wider adoption of these tools and practices across the region, contributing to improved food and water security while addressing the growing challenges of climate change.

The Croptimal app is available at Croptimal.app. Get in touch with us if you would like more information or to request your own account.

Video: Croptimal – Smart Irrigation Advice Powered by Data

Graphical User Interfaces are available for QGIS but only for SPHY v2.0 at the moment. This project will upgrade these plugins in order to make them compatible with the latest versions of SPHY (v3.0 and v3.1), QGIS and Python available. The updated plugins will also incorporate the additional functionalities to process state of the art new data sources as inputs.

As SPHY is used by FutureWater in several capacity building programs, our aim is to make the access to the data and the model as easy and intuitive as possible. With updated QGIS Plugins, no programming skills will be required to run the model, so a broader audience can use SPHY for their own purposes.

More information can be found at the SPHY website.