Like in all ancient civilisations, the need to manage water propelled the growth of hydrological science in ancient India also. In this paper, we provide some fascinating glimpses into the hydrological, hydraulic, and related engineering knowledge that existed in ancient India, as discussed in contemporary literature and recent explorations and findings. Many interesting dimensions of early scientific endeavours emerge as we investigate deeper into ancient texts, including Indian mythology.

Diatoms (microscopic algae) are regarded as useful tracers in catchment hydrology. However, diatom analysis is labour-intensive; therefore, only a limited number of samples can be analysed. To reduce this number, we explored the potential for a time-integrated mass-flux sampler to provide a representative sample of the diatom assemblage for a whole storm run-off event. Our results indicate that the Phillips sampler did indeed sample representative communities during two of the three events.

Proper water availability for the right place and time in a changing climate requires analysis of complex scientific, technical, socioeconomic, regulatory, and political issues. A Water-Energy-Food Nexus Phosphate (WEF-P) Tool, based on integrating supply chain processes, transportation, and water–energy footprints could assess the various scenarios to offer an effective means of ensuring sustainable management of limited resources to both agricultural areas and the phosphate industry.

This paper investigates the variability of past flooding by applying a numerical model coupled with historical records of regional climate and anthropogenic activity under the deficiency of observations. We conclude that trends in flooding frequency were predominantly modulated by the intensity and frequency of extreme rainfall events, which highlights the need for the implementation of effective river engineering measures to counteract increasing flood risks as a result of the future.

Wild salmon numbers in Nova Scotia, Canada, have been plummeting in recent decades. In 2014, we launched an ionic aluminium monitoring program in Nova Scotia to see if this toxic element was a threat to salmon populations. We found that all 10 monitored rivers had ionic aluminium concentrations that exceeded the threshold for aquatic health. Our results demonstrate that elevated aluminium still threatens aquatic ecosystems and that delays in recovery from acid rain remains a critical issue.

In socio-hydrology, human–water interactions are investigated. Researchers have two major methodologies in socio-hydrology, namely mathematical modeling and empirical data analysis. Here we propose a new method for bringing the synergic effect of models and data to socio-hydrology. We apply sequential data assimilation, which has been widely used in geoscience, to a flood risk model to analyze the human–flood interactions by model–data integration.

Our objective is to investigate how satellite microwave sensors, particularly Soil Moisture and Ocean Salinity (SMOS), may help to reduce errors and uncertainties in soil moisture simulations with a large-scale conceptual hydro-meteorological model. We assimilated a long time series of SMOS observations into a hydro-meteorological model and showed that this helps to improve model predictions. This work therefore contributes to the development of faster and more accurate drought prediction tools.

Soil mass and heat transfer processes were represented in three levels of model complexities to understand soil freeze–thaw mechanisms. Results indicate that coupled mass and heat transfer models considerably improved simulations of the soil hydrothermal regime. Vapor flow and thermal effects on water flow are the main mechanisms for the improvements. Given the explicit consideration of airflow, vapor flow and its effects on heat transfer were enhanced during the freeze–thaw transition period.

We analysed how and to which extent changes in water storage on continents had an effect on global ocean mass over the period 1948–2016. Continents lost water to oceans at an accelerated rate, inducing sea level rise. Shrinking glaciers explain 81 % of the long-term continental water mass loss, while declining groundwater levels, mainly due to sustained groundwater pumping for irrigation, is the second major driver. This long-term decline was partly offset by the impoundment of water in dams.

Groundwater use changes the availability of groundwater, especially during droughts. This study investigates the impact of groundwater use on groundwater droughts. A methodological framework is presented that was developed and applied to the UK. We identified an asymmetric impact of groundwater use on droughts, which highlights the relation between short-term and long-term strategies for sustainable groundwater use.

The paper performs the most comprehensive European-scale evaluation to date of satellite rainfall products for river flow prediction. In doing so, how errors transfer from satellite-based rainfall products into flood simulation is investigated in depth and, for the first time, quantitative guidelines on the use of these products for hydrological applications are provided. This result can represent a keystone in the use of satellite rainfall products, especially in data-scarce regions.

Snow is a critical contributor to our water and energy budget, with impacts on flooding and water resource management. Measuring the amount of snow on the ground each year is an expensive and time-consuming task. Snow models and gridded products help to fill these gaps, yet there exist considerable uncertainties associated with their estimates. We demonstrate that machine learning techniques are able to reduce biases in these products to provide more realistic snow estimates across Ontario.

Our research studies whether science depoliticizes water conflicts or instead conflicts politicize science–policy processes. We analyze a water conflict due to the development of large infrastructure. We interviewed key actors in the conflict and replicated the results of water resources models developed to solve the conflict. We found that knowledge produced in isolation has no positive effect in transforming the conflict; instead, its potential could be enhanced if produced collaboratively.

Here we examine the effect of evaporative cooling across different vegetation types. Evaporation cools surface temperature significantly in short vegetation. In the forest, the high aerodynamic conductance explains 56 % of the reduced surface temperature. Therefore, the main cooling agent in the forest is the high aerodynamic conductance and not evaporation. Additionally, we propose the diurnal variation in surface temperature as being a potential indicator of evaporation in short vegetation.

The mechanistic Couvreur root water uptake (RWU) model that is based on plant hydraulics and links root system properties to RWU, water stress, and crop development can evaluate the impact of certain crop properties on crop performance in different environments and soils, while the Feddes RWU approach does not possess such flexibility. This study also shows the importance of modeling root development and how it responds to water deficiency to predict the impact of water stress on crop growth.

It is still challenging to apply the quantitative and comprehensive global sensitivity analysis method to complex large-scale process-based hydrological models because of variant uncertainty sources and high computational cost. This work developed a new tool and demonstrate its implementation to a pilot example for comprehensive global sensitivity analysis of large-scale hydrological modelling. This method is mathematically rigorous and can be applied to other large-scale hydrological models.

Due to climate and population evolution, increased pressure is put on the groundwater resource, which calls for better understanding and models. In this paper, we describe a novel workflow to model the geological heterogeneity of coastal aquifers and apply it to the Roussillon plain (southern France). The main strength of the workflow is its capability to model aquifer heterogeneity when only sparse data are available while honoring the local geological trends and quantifying uncertainty.