Coping with water scarcity and growing competition for water among different sectors requires proper water management strategies and decision processes. A pre-requisite is a clear understanding of the basin hydrological processes, manageable and unmanageable water flows, the interaction with land use and opportunities to mitigate the negative effects and increase the benefits of water depletion on society. Currently, water professionals do not have a common framework that links depletion to user groups of water and their benefits. The absence of a standard hydrological and water management summary is causing confusion and wrong decisions. The non-availability of water flow data is one of the underpinning reasons for not having operational water accounting systems for river basins in place. In this paper, we introduce Water Accounting Plus (WA+), which is a new framework designed to provide explicit spatial information on water depletion and net withdrawal processes in complex river basins. The influence of land use and landscape evapotranspiration on the water cycle is described explicitly by defining land use groups with common characteristics. WA+ presents four sheets including (i) a resource base sheet, (ii) an evapotranspiration sheet, (iii) a productivity sheet, and (iv) a withdrawal sheet. Every sheet encompasses a set of indicators that summarise the overall water resources situation. The impact of external (e.g., climate change) and internal influences (e.g., infrastructure building) can be estimated by studying the changes in these WA+ indicators. Satellite measurements can be used to acquire a vast amount of required data but is not a precondition for implementing WA+ framework. Data from hydrological models and water allocation models can also be used as inputs to WA+.

The scarcity of water encourages scientists to develop new analytical tools to enhance water resource management. Water accounting and distributed hydrological models are examples of such tools. Water accounting needs accurate input data for adequate descriptions of water distribution and water depletion in river basins. Ground-based observatories are decreasing, and not generally accessible. Remote sensing data is a suitable alternative to measure the required input variables. This paper reviews the reliability of remote sensing algorithms to accurately determine the spatial distribution of actual evapotranspiration, rainfall and land use. For our validation we used only those papers that covered study periods of seasonal to annual cycles because the accumulated water balance is the primary concern. Review papers covering shorter periods only (days, weeks) were not included in our review. Our review shows that by using remote sensing, the absolute values of evapotranspiration can be estimated with an overall accuracy of 95% (SD 5%) and rainfall with an overall absolute accuracy of 82% (SD 15%). Land use can be identified with an overall accuracy of 85% (SD 7%). Hence, more scientific work is needed to improve the spatial mapping of rainfall and land use using multiple space-borne sensors. While not always perfect at all spatial and temporal scales, seasonally accumulated actual evapotranspiration maps can be used with confidence in water accounting and hydrological modeling.

The paper demonstrates the application of a new water accounting plus (WA+) framework to produce information on depletion of water resources, storage change, and land and water productivity in the Indus basin. It shows how satellite-derived estimates of land use, rainfall, evaporation (E), transpiration (T), interception (I) and biomass production can be used in addition to measured basin outflow, for water accounting with WA+. It is demonstrated how the accounting results can be interpreted to identify existing issues and examine solutions for the future. The results for one selected year (2007) showed that total annual water depletion in the basin (501 km³) plus outflows (21 km³) exceeded total precipitation (482 km³). The water storage systems that were effected are groundwater storage (30 km³), surface water storage (9 km³), and glaciers and snow storage (2 km³). Evapotranspiration of rainfall or "landscape ET" was 344 km³ (69 % of total depletion). "Incremental ET" due to utilized flow was 157 km³ (31% of total depletion). Agriculture depleted 297 km³, or 59% of the total depletion, of which 85% (254 km³) was through irrigated agriculture and the remaining 15% (44 km³) through rainfed systems. Due to excessive soil evaporation in agricultural areas, half of all water depletion in the basin was non-beneficial. Based on the results of this accounting exercise loss of storage, low beneficial depletion, and low land and water productivity were identified as the main water resources management issues. Future scenarios to address these issues were chosen and their impacts on the Indus Basin water accounts were tested using the new WA+ framework.

The Food and Agricultural Organization of the United Nations (FAO) portal to monitor water productivity through open‐access of remotely sensed derived data (WaPOR) offers continuous actual evapotranspiration and interception (ETIa‐WPR) data at a 10‐day basis across Africa and the Middle East from 2009 onwards at three spatial resolutions. The continental level (250 m) covers Africa and the Middle East (L1). The national level (100 m) covers 21 countries and 4 river basins (L2). The third level (30 m) covers eight irrigation areas (L3). To quantify the uncertainty of WaPOR version 2 (V2.0) ETIa‐WPR in Africa, we used a number of validation methods. We checked the physical consistency against water availability and the long‐term water balance and then verify the continental spatial and temporal trends for the major climates in Africa. We directly validated ETIa‐WPR against in situ data of 14 eddy covariance stations (EC). Finally, we checked the level consistency between the different spatial resolutions. Our findings indicate that ETIa‐WPR is performing well, but with some noticeable overestimation. The ETIa‐WPR is showing expected spatial and temporal consistency with respect to climate classes. ETIa‐WPR shows mixed results at point scale as compared to EC flux towers with an overall correlation of 0.71, and a root mean square error of 1.2 mm/day. The level consistency is very high between L1 and L2. However, the consistency between L1 and L3 varies significantly between irrigation areas. In rainfed areas, the ETIa‐WPR is overestimating at low ETIa‐WPR and underestimating when ETIa is high. In irrigated areas, ETIa‐WPR values appear to be consistently overestimating ETa. The relative soil moisture content (SMC), the input of quality layers and local advection effects were some of the identified causes. The quality assessment of ETIa‐WPR product is enhanced by combining multiple evaluation methods. Based on the results, the ETIa‐WPR dataset is of enough quality to contribute to the understanding and monitoring of local and continental water processes and water management.