Decomposing parameter and input errors in model calibration is a considerable challenge. This study transfers the direct estimation of an input error series to their rank estimation and develops a new algorithm, i.e., Bayesian error analysis with reordering (BEAR). In the context of a total suspended solids simulation, two synthetic studies and a real study demonstrate that the BEAR method is effective for improving the input error estimation and water quality model calibration.

This study investigates the use of hydrometeorological sensors to reconstruct variations in internal vegetation water content of corn and relates these variations to the sub-daily behaviour of polarimetric L-band backscatter. The results show significant sensitivity of backscatter to the daily cycles of vegetation water content and dew, particularly on dry days and for vertical and cross-polarizations, which demonstrates the potential for using radar for studies on vegetation water dynamics.

Ephemeral streams in the western Mediterranean area are driven by the duration, magnitude, and intensity of rainfall events (REs). A detailed statistical analysis showed that the average RE (1.2 d and 1.5 mm) is not enough to generate new flow, which is only guaranteed by events occurring in return periods from 2 to > 50 years. REs explain near to 75 % of new flow, meaning that terrain and lithological characteristics play a fundamental role.

Pesticides continue to pose a threat to surface water quality worldwide. Here, we present a spatial Bayesian belief network (BBN) for assessing inherent pesticide risk to water quality. The BBN was applied in a small catchment with limited data to simulate the risk of five pesticides and evaluate the likely effectiveness of mitigation measures. The probabilistic graphical model combines diverse data and explicitly accounts for uncertainties, which are often ignored in pesticide risk assessments.

Assuming stationarity of hydrological systems is no longer appropriate when considering land use and climate change. We tested the sensitivity of hydrological predictions to changes in model parameters that reflect ecosystem adaptation to climate and potential land use change. We estimated a 34 % increase in the root zone storage parameter under +2 K global warming, resulting in up to 15 % less streamflow in autumn, due to 14 % higher summer evaporation, compared to a stationary system.

Sensitivity analysis can be harnessed to evaluate effects of model uncertainties on planning outcomes. This study explores how observation and parameter uncertainty propagate through a hydrogeologic model to influence the ranking of decision alternatives. Using global sensitivity analysis and evaluation of aquifer management objectives, we evaluate how physical properties of the model and choice of observations for calibration can lead to variations in decision-relevant model outputs.

Due to the widespread salinity in coastal zones, freshwater supplies are now under pressure. This study analyzes the recharge and salinity sources of coastal groundwater (brine, saline, brackish, fresh), as well as salinization and freshening processes, using hydrochemical and isotopic methods. The evolution of saline groundwater is studied using sedimentary characteristics as multiple lines of evidence. This study can be used to better understand groundwater evolution in the coastal zone.

Implementation failure is well known to be a major barrier to the success of water resource plans and policies. The motivations and abilities (MOTA) approach attempts to address this barrier, by providing a multi-stakeholder, multilevel tool to assess triggers, motivations and abilities supporting the implementation feasibility of plans. We review existing MOTA applications in various water management contexts and propose several complementary add-in applications to complement the approach.

Hydrological catchment models are commonly used as the basis for water resource management planning. The HBV model, which is a typical example of such a model, was first applied about 50 years ago in Sweden. We describe and reflect on the model development and applications. The aim is to provide an understanding of the background of model development and a basis for addressing the balance between model complexity and data availability that will continue to face hydrologists in the future.

We explore, together with stakeholders, whether seasonal forecasting of water quantity, quality, and ecology can help support water management at five case study sites, primarily in Europe. Reliable forecasting, a season in advance, has huge potential to improve decision-making. However, managers were reluctant to use the forecasts operationally. Key barriers were uncertainty and often poor historic performance. The importance of practical hands-on experience was also highlighted.

The water balance on river basin scales depends on a number of soil physical processes. Gaining information on these quantities using observations is a key step toward improving the skill of land surface hydrology models. In this study, we use data from the Gravity Recovery and Climate Experiment (NASA-GRACE) to inform and constrain these hydrologic processes. We show that our model is able to simulate the land hydrologic cycle for a watershed in the Amazon from January 2003 to December 2012.

The mid-summer drought (MSD) is common in Mesoamerica. It is a short (weeks-long) period of reduced rainfall near the middle of the rainy season. When it occurs, how long it lasts, and how dry it is all have important implications for smallholder farmers. Studies of changes in MSD characteristics rely on defining characteristics of an MSD. Different definitions affect whether an area would be considered to experience an MSD as well as the changes that have happened in the last 40 years.

We present a new method for quantifying the probability of occurrence of extreme rainfall using radar data, and we use it to examine coastal and orographic effects on extremes. We identify three regimes, directly related to precipitation physical processes, which respond differently to these forcings. The methods and results are of interest for researchers and practitioners using radar for the analysis of extremes, risk managers, water resources managers, and climate change impact studies.

Groundwater discharge into streams plays a major role in the preservation of stream ecosystems. There were two complementary methods, both based on the use of the distributed temperature sensing technology, applied in a headwater catchment. Measurements allowed us to characterize the spatial and temporal patterns of groundwater discharge and quantify groundwater inflows into the stream, opening very promising perspectives for a novel characterization of the groundwater–stream interface.

Climate change impacts on water resources in the Volta River basin are investigated under various global warming scenarios. Results reveal contrasting changes in future hydrological processes and water availability, depending on greenhouse gas emission scenarios, with implications for floods and drought occurrence over the 21st century. These findings provide insights for the elaboration of regional adaptation and mitigation strategies for climate change.

The Budyko curve emerges globally from the behavior of multiple catchments. Single-parameter Budyko equations extrapolate the curve concept to individual catchments, interpreting curves and parameters as representing climatic and biophysical impacts on water availability, respectively. We tested these two key components theoretically and empirically, finding that catchments are not required to follow Budyko curves and usually do not, implying the parametric framework lacks predictive ability.