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The primary effects of droughts on river basins include both depleted quantity and quality of the available water resources, which can render water resources useless for human needs and simultaneously damage the environment. Isolated water quality analyses limit the action measures that can be proposed. Thus, an integrated evaluation of water management and quality is warranted.In this study, a methodology consisting of two coordinated models is used to combine aspects of water resource allocation and water quality assessment. Water management addresses water allocation issues by considering the storage, transport and consumption elements . Moreover, the water quality model generates time series of concentrations for several pollutants according to the water quality of the runoff and the demand discharges. These two modules are part of the AQUATOOL decision support system shell for water resource management. This tool facilitates the analysis of the effects of water management and quality alternatives and scenarios on the relevant variables in a river basin. This paper illustrates the development of an integrated model for the Llobregat River Basin. The analysis examines the drought from 2004 to 2008, which is an example of a period when the water system was quantitative and qualitatively stressed. The performed simulations encompass a wide variety of water management and water quality measures; the results provide data for making informed decisions. Moreover, the results demonstrated the importance of combining these measures depending on the evolution of a drought event and the state of the water resources system.

Satellite Remote Sensing, with both optical and SAR instruments, can provide distributed observations of snow cover over extended and inaccessible areas. Both instruments are complementary, but there have been limited attempts at combining their measurements. We describe a novel approach to produce monthly maps of dry and wet snow areas through application of data fusion techniques to MODIS fractional snow cover and Sentinel-1 wet snow mask, facilitated by Google Earth Engine. The method is demonstrated in a 55,000 km 2 river basin in the Indian Himalayan region over a period of ∼2.5 years, although it can be applied to any areas of the world where Sentinel-1 data are routinely available. The typical underestimation of wet snow area by SAR is corrected using a digital elevation model to estimate the average melting altitude. We also present an empirical model to derive the fractional cover of wet snow from Sentinel-1. Finally, we demonstrate that Sentinel-1 effectively complements MODIS as it highlights a snowmelt phase which occurs with a decrease in snow depth but no/little decrease in snowpack area. Further developments are now needed to incorporate these high resolution observations of snow areas as inputs to hydrological models for better runoff analysis and improved management of water resources and flood risk.

Summary1. According to the European Union Water Framework Directive, river basin management plans must include a programme of measures, with a series of management actions aiming to achieve good ecosystem status of all water bodies within the basin. The design and later prioritization of these management actions is, in theory, done through cost-effectiveness analysis (CEA), which compares management action costs with expected improvements in ecosystem status. However, such an approach does not consider the effects of management actions on human well-being resulting from changes in the provision of ecosystem services. 2. We propose to complement the current CEA approach with a cost-benefit analysis (CBA) integrating the effects of management actions on the provision of ecosystem services, therefore moving from a single-objective to a multiobjective approach. We propose a flexible methodological framework based on a combination of CEA and CBA that can be easily adapted to different case studies. 3. To test the applicability of our approach, we applied it to an impaired basin, the Llobregat River basin (north-eastern Iberian Peninsula). The analysis considers management actions selected from the programme of measures under implementation: establishment of environmental river flows, improvement of river connectivity, treatment of urban wastewater and reduction in saline pollution; and the effects on a series of ecosystem services: water provisioning, waste treatment and habitat for species. 4. Results revealed that management actions designed to improve ecosystem status do not necessarily improve human well-being through changes in the provision of ecosystem services. 5. The implementation of the CEA and CBA allowed the identification of management actions providing the best trade-offs between improvements of ecosystem status and human well-being. For example, the establishment of environmental river flows in the upper Llobregat River was the management action that maximized the balance between gains in ecosystem status and human well-being. 6. Synthesis and applications. Overall, the combination of cost-effectiveness analysis and cost-benefit analysis supports a more informed and transparent decision-making in the implementation of river basin management plans, better assisting stakeholders to prioritize those management actions providing the optimal win-win results.

Demand for water is expected to grow in line with global human population growth, but opportunities to augment supply are limited in many places due to resource limits and expected impacts of climate change. Hydro-economic models are often used to evaluate water resources management options, commonly with a goal of understanding how to maximise water use value and reduce conflicts among competing uses. The environment is now an important factor in decision making, which has resulted in its inclusion in hydro-economic models. We reviewed 95 studies applying hydro-economic models, and documented how the environment is represented in them and the methods they use to value environmental costs and benefits. We also sought out key gaps and inconsistencies in the treatment of the environment in hydro-economic models. We found that representation of environmental values of water is patchy in most applications, and there should be systematic consideration of the scope of environmental values to include and how they should be valued. We argue that the ecosystem services framework offers a systematic approach to identify the full range of environmental costs and benefits. The main challenges to more holistic 2 representation of the environment in hydro-economic models are the current limits to understanding of ecological functions which relate physical, ecological and economic values and critical environmental thresholds; and the treatment of uncertainty.

The need to provide accurate estimates of precipitation over catchments in the Hindu Kush, Karakoram, and Himalaya mountain ranges for hydrological and water resource systems assessments is widely recognized, as is identifying precipitation extremes for assessing hydro‐meteorological hazards. Here, we investigate the ability of bias‐corrected Weather Research and Forecasting model output at 5‐km grid spacing to reproduce the spatiotemporal variability of precipitation for the Beas and Sutlej river basins in the Himalaya, measured by 44 stations spread over the period 1980 to 2012. For the Sutlej basin, we find that the raw (uncorrected) model output generally underestimated annual, monthly, and (particularly low‐intensity) daily precipitation amounts. For the Beas basin, the model performance was better, although biases still existed. It is speculated that the cause of the dry bias over the Sutlej basin is a failure of the model to represent an early‐morning maximum in precipitation during the monsoon period, which is related to excessive precipitation falling upwind. However, applying a nonlinear bias‐correction method to the model output resulted in much better results, which were superior to precipitation estimates from reanalysis and two gridded datasets. These findings highlight the difficulty in using current gridded datasets as input for hydrological modeling in Himalayan catchments, suggesting that bias‐corrected high‐resolution regional climate model output is in fact necessary. Moreover, precipitation extremes over the Beas and Sutlej basins were considerably underrepresented in the gridded datasets, suggesting that bias‐corrected regional climate model output is also necessary for hydro‐meteorological risk assessments in Himalayan catchments.

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Global change is expected to have a strong impact in the Himalayan region. The climatic and orographic conditions result in unique modelling challenges and requirements. This paper critically appraises recent hydrological modelling applications in Himalayan river basins, focusing on their utility to analyse the impacts of future climate and socio-economic changes on water resource availability in the region. Results show that the latter are only represented by land use change. Distributed, process-based hydrological models coupled with temperature-index melt models are predominant. The choice of spatial discretisation is critical for model performance due to the strong influence of elevation on meteorological variables and snow/ice accumulation and melt. However, the sparsity and limited reliability of point weather data, and the biases and low resolution of gridded datasets, hinder the representation of the meteorological complexity. These data limitations often limit the selection of models and the quality of the outputs by forcing the exclusion of processes that are significant to the local hydrology. The absence of observations for water stores and fluxes other than river flows prevents multi-variable calibration and increases the risk of equifinality. The uncertainties arising from these limitations are amplified in climate change analyses and, thus, systematic assessment of uncertainty propagation is required. Based on these insights, transferable recommendations are made on directions for future data collection and model applications that may enhance realism within models and advance the ability of global change impact assessments to inform adaptation planning in this globally important region.