Model overview

SPHY (Spatial Processes in Hydrology) is a conceptual, spatially distributed (raster-based) “leaky-bucket” type water balance model.  The model is based on the principle of mass conservation and integrates dominant hydrological processes like (i) rainfall–runoff; (ii) lake/reservoir outflow, (iii) cryospheric processes (snow, ice, glaciers) (iv) evapotranspiration and (v) soil hydrological processes. These processes are defined by a physical set of equations and parameters. The SPHY model has been developed and updated overtime by combining the best components of existing and well tested simulation models: SRM, VIC, HydroS, SWAT, PCR-GLOBWB, SWAP and HimSim. It includes relevant terrestrial hydrological processes at flexible scales (local, regional and global), under various land use change, extreme weather and climate scenarios.

An overview of the SPHY model concepts is shown in the Figure 1. The model uses a sub grid variability approach for depicting the processes acting at finer spatial scales. For instance, a cell can be glacier-free, partially glacierized, or completely covered by glaciers. The non-glacierized cell can be of different landuse type. Sub-grid variability is mainly determined by the fractional vegetation coverage, which affects processes such as interception, effective precipitation, and potential evapotranspiration.

The soil/land column is divided in two upper soil stores and a third groundwater store, with their corresponding drainage components: surface runoff, lateral flow and base flow. The model simulates the dynamic behavior of the glaciers by incorporating key processes such as accumulation, ablation and ice mass transfer from accumulation to ablation zone. If glacier is losing mass, ice from the ablation zone will be redistributed over the ablation zone according to the volume ice redistribution.

Further, SPHY includes lake module which keeps track of the lake level height and storage at each time step of the model simulation. The lake module uses an advance scheme to route the flow from lake cells to the downstream regions. There is also an erosion module which calculates the soil erosion due to the impact of raindrops, overland flow, and river flow.

Routing principle

Melting of glacier ice contributes to the river discharge by means of a slow and fast component, being (i) percolation to the groundwater reservoir that eventually becomes base flow, and (ii) direct runoff.

  • Without lake(s): The cell-specific runoff, which becomes available for routing, is the sum of surface runoff, lateral flow, base flow, snow melt and glacier melt. If no lakes are present, then the user can choose for a simple flow accumulation routing scheme: for each cell the accumulated amount of material that flows out of the cell into its neighboring downstream cell is calculated. This accumulated amount is the amount of material in the cell itself plus the amount of material in upstream cells of the cell. For each cell, the following procedure is performed: using the local drain direction network, the catchment of a cell is determined which consists of the cell itself and all cells that drain to the cell.
  • With lake(s): If lakes are present, then the fractional accumulation flux routing scheme is used: depending on the actual lake storage, a fraction of that storage becomes available for routing and is extracted from the lake, while the remaining part becomes the updated actual lake storage. The flux available for routing is routed in the same way as in the simple flow accumulation routing scheme.
Inputs

As inputs, SPHY requires data on state variables as well as dynamic variables. For state variables the most relevant are:

  • Digital Elevation Model (DEM)
  • Land use type
  • Glacier cover
  • Reservoirs
  • Soil characteristics

The main dynamic variables are climate data such as:

  • Precipitation
  • Temperature
  • Reference evapotranspiration

Since SPHY is grid-based, optimal use of remote sensing data and global data sources can be made. For example, the Normalized Difference Vegetation Index (NDVI) can be used to determine the Leaf Area Index (LAI) in order to estimate the growth-stage of land cover. For setting-up the model, streamflow inputs are not necessary. However, to undertake a proper calibration and validation procedure, flow data is required. The model could also be calibrated using actual evapotranspiration, soil moisture contents, or snow coverage.

Outputs

The SPHY model provides a wealth of output data that can be selected based on the preference of the user. Spatial output can be presented as maps of all the hydrological processes. Maps often displayed as output include actual evapotranspiration, runoff generation (separated by its contributors), and groundwater recharge. These maps can be generated on daily basis; however, users usually prefer to aggregate over monthly or annual time periods. Time-series can be generated for each location in the study area. Most commonly, stream flow under current and future conditions, actual evapotranspiration and recharge to the groundwater are subject to time series analyses.

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

  1. Robust scientific basis
  2. Combines strengths of existing de facto hydrological models
  3. Modular setup in order to switch on/off irrelevant processes for computation efficiency
  4. Wide range of applicability in terms of regions, climates, modeling purposes, spatial and temporal scales
  5. Performs under data scarcity
  6. Linkable to remote sensing data
  7. Easy adjustment and application
  8. Graphical User Interface for QGIS
  9. Open source

Modules

SPHY enables users to turn on/off modules that are not required. This concept is very useful if the user is studying hydrological processes in regions where not all hydrological processes are relevant. A user may, for example, be interested in studying irrigation water requirements in central Africa. For this region, glacier and snow melting processes are irrelevant, and can thus be switched off. Another user may only be interested in simulating moisture conditions in the first soil layer, allowing the possibility to switch off the routing and groundwater modules. The advantages of turning off irrelevant modules are two-fold: (i) decrease model run-time, and (ii) decrease the amount of required model input data.

The figure represents an overview of the six modules available: glaciers, snow, groundwater, dynamic vegetation, simple routing, and lake/reservoir routing. All modules can run independently from each other, except for the glacier module. If glaciers are present, then snow processes are relevant as well, meaning that the snow module is turned on automatically if the glacier module is turned on. Since melting glacier water percolates to the groundwater store, the glacier module cannot run with the groundwater module turned off. For routing two modules are available, being (i) a simple flow accumulation routing scheme, and (ii) a fractional flow accumulation routing scheme used when lakes/reservoirs are present. The user has the option to turn off routing, or to choose between one of these two routing modules.

All hydrological processes incorporated in the SPHY model are described in detail in the peer-reviewed publication introducing the SPHY model.

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