Page 62 - CIWA Water Data Revolution Overview Report

trainings on using the product. Therefore, financial constraints may reduce the ability of
organizations to acquire and use water accounting tools which can impact decisions for both
current and future scenarios.

Organizations reported using a variety of tools to capture the measurements described in Figure
7. For example, organizations stated they used GEE, DEA, DHI tools (such as MIKE), U.S. Army
Corps of Engineers Hydrologic Engineering Center (HEC) products, Water Evaluation and Planning
System (WEAP) software, Excel, geographic information systems (GIS), and UNESCO’s Global
Network on Water and Development Information for Arid Lands (G-WADI). Some organizations
also used or have been using tools that were developed for a specific basin and their needs. Data
required by this wide array of tools also ranged greatly. For example, the respondents reported
using the following specific variables: precipitation (current and projected), evapotranspiration,
temperature, discharge, water levels, NDVI, LULC data, soil moisture, water quality parameters,
piezometric data, topography, and dam attributes (levels, inflows, and releases). Although many
of these variables can be collected using RS, several organizations are relying only on ground
observations to utilize analytics.

Many of the analytical tools currently being used by respondents require ground-based data,
which can present limitations in terms of sustainability of water management operations. Often,
limitations in the ability to collect ground-based data and financial constraints associated with
continuous monitoring can result in inability to establish long-term use of tools that require
constant and frequent input data. Additionally, the cost of acquiring the types of tools listed by
respondents can be a prohibitory factor for many organizations. The high cost associated with
many of the mainstream, common tools described by the respondents can push organizations to
prioritize which types of analytics they can afford. Finally, the long-term maintenance and upkeep
of these devices can be challenging for ensuring high-quality data and reliability throughout a
temporal resolution. As all the analytics listed in Figure 7 are highly important for effective and
efficient WRM, prioritizing only certain types of functionality can be immensely problematic for
holistic water management, especially at the basin level. The issues of ground data requirements
and high capital costs can be reduced by organizations moving toward using available RS data in
free or low-cost data products and analytical tools. Majority of organizations recognize that RS
can assist with their data coverage needs and fill the gap when ground data is scarce. From the
interviews, organizations clearly articulated a desire to use RS to fill these data gaps.
Furthermore, increasing the uptake of free or low-cost platforms using RS data allows for
harmonization of tools across Africa despite ground data and financial constraints.
Harmonization of RS data tools can increase transparency among states, foster collaborative
dialogues, and facilitate transboundary cooperation. Moreover, it can allow for knowledge
exchange across regional organizations, thus improving the connectivity of the water sector
across all of Africa.

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