This thesis introduces 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. WA+ is a simple, yet comprehensive and understandable water accounting framework that provides a standardized way of data collection and a presentation system that describes the overall land and water management situation in complex river basins. WA+ tracks water depletions rather than withdrawals and it goes past flow and run-off accounting. Rainfall is a recognized key hydrological process in WA+, and only a portion of total rainfall translates to stream flows and ground water recharge. A significant portion of the rainfall is directly depleted by natural processes such as ET from natural vegetation or rainfed plantations and crops. These natural water depletions bring about economic benefits and provide many services. Hence, by accounting only for run-off these benefits and uses of water will be discounted and the full picture on water flows and the gains will be distorted. WA+ explicitly recognizes the influence of land use on the water cycle and provides the link between water balance, land use and water use as well as management options to modify it, by grouping land use classes with common management characteristics. Information on water supply, water depletion processes, beneficial and non-beneficial depletion, biomass production, water and land productivity, and water withdrawals and reuse are presented in WA+. Land use is also central in reducing greenhouse gas emissions and other new approaches related to climate smart agriculture. In an effort to reduce greenhouse gas emissions, many countries also study the carbon accounts of rural areas. The WA+ framework improves understanding of the current state of a basin, issues, future challenges, and improvement opportunities. It provides the information that will help managers to make the basin more climate secure and to adapt to periods of droughts and floods. It can be used to monitor changes in a basin’s water resources situation and to assess the impacts of future interventions such as large scale land use change and expanding irrigated agriculture. To ensure global applicability of WA+ the framework is designed to primarily use data from open access satellite measurements. To showcase WA+ application, this thesis presents a case study from the Indus Basin. This pilot study demonstrates how the WA+ framework can be implemented to provide much-needed explicit information on the water resources situation, depletion, and productivity, in a systematic way by using minimum ground measured data and how the accounting results can be used to identify weaknesses, strengths, and opportunities. The accounting results show that the Indus basin is nearly a closed basin in which more than 95% of the available water is depleted while half of the water depletion is through processes that produce very little or no benefits, i.e. non-beneficial depletion. The majority of these non-beneficial depletion occurs via excessive soil evaporation of shallow water table areas. Hence, large amounts of valuable groundwater resources are vaporized non-beneficially into the atmosphere. The results also show that total annual water depletion in the basin plus outflows exceeds total precipitation. This situation has resulted in reduction in storage, especially groundwater storage. Such a fast decline in groundwater storage may have major implications for the sustainability of the basin. Not only it becomes an environmental crisis, also the food security is at danger. Scenario analysis show - based on a single year analysis - that through decreasing wasteful soil evaporation in agricultural areas, particularly in irrigated land an amount of 37.8 km3 can be saved. If interventions are not timely implemented, retirement of irrigated land seems unavoidable. The WA+ sheets were deemed useful to understand the impact of certain interventions. WA+ uses satellite measurements of land and water use data. All satellite data parameters have some level of uncertainty and error that needs to be taken into account because satellites are measuring hydrological processes indirectly. The errors in large water volumes (i.e. rainfall and ET) may result in large errors in river and aquifer flows. Thus the reliability of satellite measurements of land and water use data is investigated in this thesis. A comprehensive literature review on accuracy of the main satellite based estimates used in WA+, namely ET, rainfall, and land use land cover was conducted. For each parameter an error probability distribution function (PDF) is fitted from peer reviewed articles. The results show that the mean absolute error for satellite-based estimates of ET, rainfall, and land use classification are 5.4%, 18.5 %, 14.6% respectively. The largest error is thus associated with rainfall. Bias correction and local calibration of global and regional rainfall products seem to improve the quality of the data layers. In contrast to rainfall, the error in satellite-based ET is relatively small. ET is a vital component of the hydrological cycle. Results show that remotely sensed ET is reliable enough to be used both as input into distributed hydrological models, and as a means to calibrate the simulations. Nonetheless, despite the existing potential and accuracy, satellite-based ET is under-utilized in hydrological studies. Contributing factors are presumably the difficulty to access and acquire reliable ET data through the public domain, and the difficulty to compare it with reliable field data. The land use classifications come with an overall error of 14.6%. This level of accuracy, although acceptable, calls for improvements given the wide use of these maps. Another important issue is the need for a new type of land use mapping dedicated to agricultural and river basin water management issues. Currently, most legends are meant to describe ecosystems, instead of classes with differences in water management. Furthermore this thesis explores the impact of the uncertainty of the satellite measurement on the reliability of WA+ outputs. Predictive uncertainty of WA+ outputs was studied for the Awash River basin in Ethiopia. The Monte Carlo (MC) technique that is based on selecting numbers randomly from a pre-defined probabilistic distribution was used for stochastic simulation of WA+ outputs. The simulation was repeated 1,000 times for three years (2009, 2010, and 2011). The results of this exercise show that the stochastic mean of the majority of WA+ parameters and performance indicators are within 1% deviation from the original value. This shows that stochastic simulation can be used as part of a standard procedure to produce water accounts with WA+. There are two main advantages pertaining to the MC technique. Firstly, incorporation and acknowledgement of input data errors in producing water accounts. Secondly, the possibility to estimate and report on the error band width that surrounds every WA+ output. The latter is of essential value to informed decision making, as it enables users to better understand the error margin that is associated with the generated information. The goal is to separate reliable information from those that have low reliability. In such a way, outputs with a high error margin, low reliability, will be identified and it is recommended that they should not be used to formulate policy decisions. WA+ has triggered a wider discussion on using the framework for analyzing complex river basins, especially when data is scarce. This holds true especially for developing countries where the required data collection and archiving processes are insufficient for creating clearly defined alterative solutions for decision makers. A simple WA+ system based on earth observation data is thus a good first step in the right direction. A multi-institutional water accounting data repository is under development that is endorsed by IWMI, UNESCO-IHE and FAO. This platform, WaterAccounting.org, will be based on routine satellite data, data from hydrological models, and other open access global and regional data sources. The platform will provide information by sectors (i.e. agriculture, environment) on the sources of water use (i.e. surface water and groundwater), geographical water scarcities (i.e. local demand and supply), utilizable water flows (i.e. local actual flows and reserved flows), and the sustainability of the water services to environment, food security, energy, economy and domestic use.