Spatial evapotranspiration, rainfall and land use data in water accounting. Part 2: Reliability of water accounting results for policy decisions in the Awash basin

Water Accounting Plus (WAC) is a framework that summarizes complex hydrological processes and water management issues in river basins. The framework is designed to use satellite-based measurements of land and water variables and processes as input data. A general concern associated with the use of satellite measurements is their accuracy. This study focuses on the impact of the error in remote sensing measurements on water accounting and information provided to policy makers. The Awash Basin in the central Rift Valley in Ethiopia is used as a case study to explore the reliability of WAC outputs, in the light of input data errors. The Monte Carlo technique was used for stochastic simulation of WAC outputs over a period of 3 yr. The results show that the stochastic mean of the majority of WAC parameters and performance indicators are within 5% deviation from the original WAC values based on one single calculation. Stochastic computation is proposed as a standard procedure for WAC water accounting because it provides the uncertainty bandwidth for every WAC output, which is essential information for sound decision-making processes. The majority of WAC parameters and performance indicators have a coefficient of variation (CV) of less than 20 %, which implies that they are reliable and provide consistent information on the functioning of the basin. The results of the Awash Basin also indicate that the utilized flow and basin closure fraction (the degree to which available water in a basin is utilized) have a high margin of error and thus a low reliability. As such, the usefulness of them in formulating important policy decisions for the Awash Basin is limited. Other river basins will usually have a more accurate assessment of the discharge in the river mouth.Water ManagementCivil Engineering and Geoscience

A novel approach to estimate direct and indirect water withdrawals from satellite measurements: A case study from the Incomati basin

The Incomati basin encompasses parts of South Africa, Swaziland and Mozambique, and is a water stressed basin. Equitable allocation of water is crucial to sustain livelihoods and agro-ecosystems, and to sustain international agreements. As compliance monitoring of water distribution by flow meters is laborious, expensive and only partially feasible, a novel approach has been developed to estimate water withdrawals using satellite measurements. Direct withdrawals include pumping from rivers, impoundments and groundwater, for irrigation and other human uses. Indirect withdrawals include evaporation processes from groundwater storage, unconfined shallow aquifers, seepage zones, lakes and reservoirs, and inundations, in addition to evaporation from pristine land surface conditions. Indirect withdrawals intercept lateral flow of water and reduce downstream flow. An innovative approach has been developed that employs three main spatial data layers inferred from satellite measurements: land use, rainfall, and evaporation. The evaporation/rainfall ratio was computed for all natural land use classes and used to distinguish between evaporation from rainfall and incremental evaporation caused by water withdrawals. The remote sensing measurements were validated against measured evaporative flux, stream flow pumping volume, and stream flow reductions. Afforested areas in the whole basin was responsible for an indirect withdrawal of 1241 Mm3/yr during an average rainfall year while the tripartite agreement among the riparian countries specifies a permitted total withdrawal of 546 Mm3/yr. However, the irrigation sector is responsible for direct withdrawals of 555 Mm3/yr only while their allocated share is 1327 Mm3/yr – the long term total withdrawals are thus in line with the tripartite agreement. South Africa withdraws 1504 Mm3/yr while their share is 1261 Mm3/yr. The unmetered stream flow reduction from the afforested areas in South Africa represents the big uncertainty factor. The methodology described using remotely sensed measurements to estimate direct and indirect withdrawals has the potential to be applied more widely to water stressed basins having limited availability of field data.Geoscience & EngineeringCivil Engineering and Geoscience