About SPHY
The SPHY model (short for Spatial Processes in Hydrology) leverages components from well tested simulation models like HydroS, SWAT, PCR-GLOBWB, SWAP, and HimSim, to simulate terrestrial hydrology at varying scales, land use and climatic conditions. Operating on a cell-by-cell basis, SPHY is a spatially distributed leaky bucket type water balance model. It is written in Python and uses the PCRaster dynamic modelling framework. To reduce the number of input parameters, level of complexity and model run times, it does not include energy balance calculations.
Developed by FutureWater, with the support of national and international partners, SPHY has emerged as a robust, user-friendly tool for undertaking operational and strategic water resource management decisions. It stands out for its physical consistency, enabling detailed assessments of hydrological storage and flux changes over space and time.
Applications
Climate Change Assessment
SPHY quantifies the future impacts of climate change on water resources and helps to evaluate the effectiveness of adaptation strategies in a precise, sector-specific manner across different spatial and temporal scales.
Hydropower Evaluation
From assessing long-term projections of water availability, scoping regional and local hydropower potential to enabling forecasting services for operational reservoir inflow, SPHY has proven its usefulness for exploring hydropower potential.
Water Allocation and Planning
SPHY’s ability to forecast various hydrological flows under different climate scenarios provides evidence for improved water resources allocation and planning. In many countries, SPHY has also been coupled with WEAP to assess water availability and manage supply-demand gaps across different sectors in an equitable and sustainable manner.
Operational Services
The SPHY model contributes to a wide array of decision support systems with its operational services. These include stream flow forecasting for hydropower production, and soil water content and groundwater level predictions for irrigation guidance. SPHY is also capable of assimilating data from remote sensing, Unmanned Aerial Vehicles (UAVs) and in-situ sensors.
Irrigation Management
SPHY serves as a valuable tool in precision irrigation management. It has been used to provide field-specific irrigation advice for different types of crops and has also been used to evaluate the irrigation potential at larger scales.
Snow and Glacier-fed River Basins
With its ability to quantify the impacts of climate change on glacier and snow melt contributions, SPHY has been instrumental in forecasting flow regime changes and assessing water availability for energy, agriculture and other sectors in snow and glacier-fed river basins. Moreover, given its versatility, SPHY seamlessly integrates with various other hydrological models such as WEAP, SWAT and MIKE Basin.
Functionalities & Key Features
SPHY stands out as compared to other models due to its wide range of functionalities such as:
Spatial scale
SPHY can be applied to flexible ranges of spatial scales such as small-scale farm, medium scale sub-catchment and catchment, and large scale regional and global applications. The model helps users better understand the spatial differences and variability of key hydrological process. Furthermore, the model can run on different spatial scales for different processes within the same simulation. For instance, the glacier can run on 50 meters resolution while the model resolution is 1000 meters.
Temporal scale
The model can be set up at sub-daily to daily, weekly, monthly and yearly time steps depending on the daily variations of the key hydrological processes and data availability.
Adaptability
SPHY can be easily adapted for different climatic conditions around the world. This is particularly useful if the user is studying hydrological processes in regions where not all hydrological processes are relevant.
Data requirement
A user can use any ground-based observations such as hydrological data (discharge), cryospheric data (snow cover, glacier mass balance), crop data (crop coefficients static, leaf area index), lake and reservoir information, if available, to better represent and enhance the accuracy of the model. The model can be supplied with data on a parsimonious or data hungry approach, depending on the data availability in the region.
User friendliness
SPHY is a user-friendly model and can be applied by anyone having an understanding of key hydrological processes. From static constant or stochastic time series to more complex raster maps, users can provide different inputs to the model. It then processes and generates a wealth of output data, in the form of spatial maps and time series, that can be selected based on the preference of the user.
Other key features
- Robust scientific basis
- Combines strengths of existing de facto hydrological models
- Modular setup in order to switch on/off irrelevant processes for computation efficiency
- Wide range of applicability in terms of regions, climates, modeling purposes, spatial and temporal scales
- Performs under data scarcity
- Linkable to remote sensing data
- Easy adjustment and application
- Graphical User Interface for QGIS
- Open source
Video: Latest Developments
Meet FutureWater
FutureWater is a global research and consulting organization dedicated to combining scientific research with practical solutions for water management. Our work spans across global, national, and local levels, partnering on projects that address crucial issues such as water for food, irrigation, water excess and shortage, climate change impacts, and comprehensive river basin management.
At the heart of FutureWater lies our key expertise in quantitative methods. We specialize in advanced simulation models, geographic information systems, and satellite observations, providing insights into complex water management challenges. Our diverse range of clients and collaborators includes the World Bank, Asian Development Bank (ADB), various national and local governments, river basin organizations, science foundations, universities, and research organizations.
With our main offices located in Wageningen, The Netherlands, and Cartagena, Spain, FutureWater maintains a strong international presence.
