Page 52 - CIWA Water Data Revolution Overview Report

usage; practices for collecting, storing, managing, and analyzing RS data; and their views on
current and future challenges associated with using RS data in products and tools. Surveys were
distributed in English and French. An example form is provided in Appendix 10.2.

Surveys were comprised of three sections. Section 1 collected general information on the
organization, such as contacts; their organization type (governmental, basin, regional, or
research/academic); and a list of countries, river basins, and aquifers the organization works
within. Sections 2 and 3 evaluated data practices and needs. Section 2 gauged the familiarity,
interest, and capacity of staff at these organizations to work with RS data and data products,
while section 3 focused on analytical tools and applications related to water resources
management. Questions in section 3 were designed to better understand the types of analytics
organizations apply, opportunities to expand their usage of analytical tools requiring only RS data
inputs, and constraints limiting their ability to benefit from fit-for-purpose tools. Additionally,
section 3 assessed needs and levels of interest for various trainings around applying RS tools.

Section 2 included 14 questions to assess the current and past use of RS data, data products, and
familiarity with data platforms. To understand if organizations collect RS data with relevance for
WRM, respondents were asked if they use RS to characterize any of the following water cycle
attributes: precipitation, evapotranspiration, soil moisture, vegetation and land cover,
groundwater, surface water, snow and ice, water quality, and topography. Follow up questions
asked for additional details on the types of RS data used, such as the source, resolution, cost, and
primary use of the data. This information was collected to provide insight on what types of RS
are most commonly used by various institutions across Africa and what types of data are perhaps
the easiest to access. Subsequently, respondents were asked if they used, or were familiar with,
the following data platforms and tools: GEE, DEA, IWMI data and tools, Dartmouth Flood
Observatory Flood Portal, EarthMap.org, Aquastat, Global Flood Monitoring System, Aqueduct
Water Risk Atlas, and World Bank Spatial Agent Hydroinformatics. These platforms were included
in the survey because they can facilitate the use of RS data and assist with water-related
operations, but they have differing utilities for organizations based on their needs. For example,
GEE and DEA primarily provide analysis-ready data from RS, where GEE is a commonly used
product worldwide and DEA is a far newer product catered to the African context. Earth Map
functions as a complimentary tool to GEE by providing access to the GEE data without requiring
coding expertise. Aquastat and the Aqueduct Water Risk Atlas also provide water-related data
and information, whereas the Global Flood Monitoring System and Dartmouth Flood Observatory
enable flood analyses using open-access data. Of the IWMI Digital Data and Tools, the most
applicable tool for using RS in Africa is the water accounting tool. Unlike the other platforms in
the survey, this tool is not open access. And finally, the Spatial Agent Hydroinformatics platform
provides access to information from various providers applicable for harnessing RS data, mainly
through the form of visualization. To further determine the status of using data products and
platforms, follow up questions were given to understand the types of data products organizations
use, as well as the main purpose or application and required input data per product. Lastly,
section 2 included questions to measure the capacity and interest of RBOs and ROs to develop
the WDR capacity building strategy under Pillar B. Questions assessed inhouse expertise with RS

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