How many ground observations should we aim at?

TWIGA focuses on the combination of remote sensing data and ground-based observations to run models and develop products. The quality and amount of ground-based observations determine the accuracy of data that is used for satellite calibration and modeling, such as crop models. Maintaining monitoring networks requires high resources, thus it is important to assess where […]

Disdro in Kenya – Rain Listening Sensors

In Narok, Kenya there is a unique network of rain sensors on the experiment. We call it the  Disdro Network – a network of acoustic devices that measures the distribution and intensity of rainfall. In December 2020, 10 Disdros were installed on an area spanning 1700km2. A few more are scheduled for installation in early […]

Using drones to get insight into field-scale moisture status

Within the TWIGA project, a student from Wageningen University, Kim Faassen, took up an internship with FutureWater to complete her MSc specialisation Meteorology and Air Quality. We asked Kim to develop a spatial evapotranspiration (ET) product based on a simple method and requiring few data inputs that can be obtained from satellites and drone flights. […]

Transboundary Water Management made easier using the TWIGA platform

Currently, only around 58% of Africans have access to safe drinking water. More than 90% of African freshwater is contained within 63 internationally shared basins. The current freshwater distribution in Africa is expected to change rapidly due to climatic- and socio-economic drivers (IPCC, 2014). In order to guarantee access to freshwater for drinking water or […]

FAO AquaCrop in TWIGA

Crop simulation models are widely used by scientists, policy-makers, and practitioners to understand the response of crop yield to variables including soil fertility, water availability, and atmospheric composition. Among crop simulation models a common drawback is the need for highly detailed input data and parameter values, which are rarely available in data-scarce regions such as […]

Water vapor maps from the integration of GNSS measurements, SAR satellite images and NWP models

Copernicus Sentinel-1 SAR (Synthetic Aperture Radar) acquisitions allow for the generation of high resolution maps containing the variation of atmospheric water vapor content with respect to a reference situation (MASTER). The maps are in fact the product of a processing technique, known as SAR Interferometry (InSAR), which involves the combination of satellite SAR images acquired […]