Student Topics

Topics for MSc thesis research


  • Validation of the currently generated ET ensemble product (ETEns1.0) using global flux towers and other data sets with independent estimates of ET such as soil water balances or Large Aperture Scintillometers
  • Improving the core computations for an ensemble ET value for every pixel using maximum 7 individual global scale ET products, and inclusion of rejection criteria by land use type and Leaf Area Index (LAI) of certain products leading to ETEns2.0
  • Inclusion of the Duan model for heat storage in water bodies in ETEns2.0, and the computation of related evaporation fluxes in lakes, reservoirs, rivers and fishponds
  • Validate the automated hot and cold pixel selection of SEBAL3.0 using extra self-calibration data points extracted from special pixels with minimal surface resistance and zero water stress
  • Sensitivity and uncertainty analysis of evapotranspiration estimations (using energy balance models and/or hydrological models)
  • Comparing incoming longwave radiation for Africa using different existing equations including the sets from FAO56, LandSAF, LandSurf-EVAL, ECMWF, GLDAS and more public data sets that are available


  • Preparing high resolution map of maximum root zone storage capacities using global data sets of P (CHRIPS) and ET (ETEns1.0) using the main principles of the Wang-Erlandsson model
  • Assessment of incremental ET due to withdrawals of natural ecosystems using the Budyko curve for green water consumption limitations and ETEns1.0. Developing guidelines of maximum effective precipitation
  • Linking blue water consumption to the withdrawals of surface and groundwater using the WaterPix model and consumed fractions that vary with land use classes
  • Comparison and validation of 5 existing global water withdrawal data sets from various international sources using the new ETBlue maps
  • Linking the surface water withdawals based on maps of ETBlue against water flow in the river, including storage behind reservoirs. While WA makes grid computation and aggregates to catchment scale, the modelling of blue water in the river channel and behind storage reservoirs is still under development
  • Revision of the international standard of bulk environmental flow requirements. This is an oversimplified concept and more ecohydrological concepts need to be involved for reexaming these guidelines
  • Comparison of groundwater recharge from different hydrological models, groundwater databases and from the new WaterPix model for every pixel
  • Evaluate the accuracy of monthly groundwater storage changes computed by Hyongki Lee method based on Grace and GLDAS data

Ecosystem services

  • Mapping of flood prone areas with a particular emphasis of flood risk of urban areas using remote sensing databases to evaluate sites being flooded historically or where near to flooding due to their topographical conditions, very high soil wetness and very intense rainfall rates
  • Estimation of carbon sequestration for various land use classes using spatial information on monthly Net Primary Production (NPP) and the partitioning of NPP into plant organs and soil organic matter. An integration between NPP and AFOLU type of models needs to be developed
  • Quantify the relationship between water consumption and reduction of soil and wind erosion using modified USLE equations and distributed surface runoff from WaterPix
  • Investigate effective methods to mitigate flood risk by reducing peak flows, in particular the role of forests in delaying the flow by modified interception and infiltration processes

Water productivity

  • Develop the minimum and maximum values for climatically corrected Water Productivity for potatoes, sugarcane, sugarbeet, grapes, soybeans and cotton using literature values and existing remote sensing studies
  • Design standard communication pictograms to demonstrate local variabilities in land and water productivity and scope to improve them. Use the WPS concept for a productivity analysis for WEIDAP project in Vietnam
  • Determine analytical relationships between top soil - sub soil moisture and how they change over time
  • Determining vegetation water stress from Sentinel images using estimates of leaf water content and compare them with vegetation water stress from thermal images
  • Development of a standard irrigation information package that computes irrigation performance indicators on the basis of ET, moisture, precipitation and biomass production data. Indicators should be presented by command service areas. Relate remote sensing data also to citizen science on crop type and water levels in irrigation canals

Water accounting

  • Develop a new methodology based on remote sensing data to analyse water scarcity from non-withdrawal data. A direct measurement of vegetation water stress could facilitate the determination of SDG indicator 6.4 on water scarcity
  • Program a standardized drought analysis script in Python from multiple RS products to generate drought status reports for any pixel in a certain management unit
  • Program time series analyses of a set of 10 open access remote sensing variables and convert them to express sustainability, vulnerability and resilience of water and environment at river basin scale in a quantitative way. Use the data to report WA+ sheet 8 and to SDG indicators
  • Prepare global datasets for non-conventional ET values (i.e. water consumption indoor both domestic and industry, respiration of people and animals, greenhouses, other)

Remote sensing

  • Dividing the worlds' lakes, reservoirs and wetlands into 10 different topographic classes with typical relationships between water volumes and water areas using altimeter data in conjunction with water surface data
  • Generate cloud free surface temperature data sets from HANTS and M-SSA algorithms using clouded VIIRS images as input and assess the impact on the accuracy of surface energy balance models
  • Test various existing open-access gapfilling procedures for multi-spectral Landsat-7 data, including the thermal infrared band
  • Inventory of all existing global land cover and land use datasets in 2016 from various databases that have an open-access status and compare the results on consistency
  • Designing machine learning algorithms for global crop classification