This paper presents a new probe that measures soil microwave permittivity in the frequency range of satellite L-band sensors. The probe capacities will allow for validation and calibration of the models used to estimate landscape physical properties from raw microwave satellite datasets. Our results show important discrepancies between model estimates and instrument measurements that will need to be addressed.

We improved the irrigation module in a land surface model ORCHIDEE and developed a dam operation model with the aim to investigate how irrigation and dams affect the streamflow fluctuations of the Yellow River. Results show that irrigation mainly reduces the annual river flow. The dam operation, however, mainly affects streamflow variation. By considering two generic operation rules, flood control and base flow guarantee, our dam model can sustainably improve the simulation accuracy.

With respect to ongoing discussions about the causes of energy imbalance, a method for closing the latent heat flux gap based on lysimeter measurements is assessed at four measurement stations over grassland in humid and semiarid climates. The applied partial closure yields excellent adjustments of eddy covariance data as compared to results found in the literature. The method also allows a distinction between systematic and random deviation of eddy covariance and lysimeter measurements.

A new method to calculate the mass of snow is provided. It is quite simple but gives surprisingly good results. The new approach only requires regular snow depth observations to simulate respective water mass that is stored in the snow. It is called ΔSNOW model, its code is freely available, and it can be applied in various climates. The method is especially interesting for studies on extremes (e.g., snow loads or flooding) and climate (e.g., precipitation trends).

The Swedish hydrological warning service is extending its use of seasonal forecasts, which requires an analysis of the available methods. We evaluate the simple ESP method and find out how and why forecasts vary in time and space. We find that forecasts are useful up to 3 months into the future, especially during winter and in northern Sweden. They tend to be good in slow-reacting catchments and bad in flashy and highly regulated ones. We finally link them with areas of similar behaviour.

Evaporation trends in the stable isotope composition (¹⁸O/¹⁶O, ¹⁷O/¹⁶O, ²H/¹H) of throughflow ponds in a hydrologically complex and seasonally dynamic lake system can be reliably predicted by the classic Craig–Gordon isotope evaporation model. We demonstrate that the novel ¹⁷O-excess parameter is capable of resolving different types of evaporation with and without recharge and of identifying mixing processes that cannot be resolved using the classic δ²H–δ¹⁸O system alone.

Restoration of intertidal wetlands such as mangroves and saltmarshes requires accurate local data on tidal flooding and current velocities. We present the application of a low-cost underwater float equipped with an acceleration data logger, the Mini Buoy, to monitor inundation and tidal currents in intertidal environments. We demonstrate how this tool can be directly applied in hydrological site suitability assessments prior to mangrove restoration in tropical SE Asia.

A long set of operational polarimetric weather radar rainfall accumulations from Estonia and Italy are generated and investigated. Results show that the combined product of specific differential phase and horizontal reflectivity yields the best results when compared to rain gauge measurements. The specific differential-phase-based product overestimates weak precipitation, and the horizontal-reflectivity-based product underestimates heavy rainfall in all analysed accumulation periods.

We present an innovative approach consisting of the statistical analysis and comparison of 15 hydrological descriptors, characterizing catchment response to rainfall events. The distribution of these descriptors is analysed according to the occurrence of karst areas inside 108 catchments. It shows that karst impacts on storm events mainly result in river losses and that interbasin groundwater flows can represent a significant part of the catchment water budget ah the event timescale.

Our research suggests a method that facilitates the inclusion of marginalized stakeholders in model-building activities to address problems in water resources. Our case study showed that knowledge produced by typically excluded stakeholders had significant and unique contributions to the outcome of the process. Moreover, our method facilitated the identification of relationships between societal, economic, and hydrological factors, and it fostered collaborations across different communities.

Certain hydrological processes become more or less relevant when the climate changes. This should also be visible in the models that are used for long-term predictions of river flow as a consequence of climate change. We investigated this using three different models. The change in relevance should be reflected in how the parameters of the models are determined. In the different models, different processes become more relevant in the future: they disagree with each other.

Understanding when, where, and how nitrate is exported from watersheds is the key to addressing the challenges that excess nutrients pose. We analyzed daily nitrate and streamflow data for five nested, agricultural watersheds that export high levels of nitrate over a 4-year time period. Nutrient export patterns varied seasonally during baseflow but were stationary during stormflow. Additionally, anthropogenic and geologic factors drove nutrient export during both baseflow and stormflow.

We estimate the contribution of extreme precipitation, antecedent soil moisture and snowmelt to changes in small and large floods across Europe. In northwestern and eastern Europe, changes in small and large floods are driven mainly by one single driver (i.e. extreme precipitation and snowmelt, respectively). In southern Europe both antecedent soil moisture and extreme precipitation significantly contribute to flood changes, and their relative importance depends on flood magnitude.

Amid growing interest in using large-scale hydrological models for flood and drought monitoring and forecasting, it is important to evaluate common assumptions these models make. We investigated the representation of reservoirs as separate (non-coordinated) infrastructure. We found that not appropriately representing coordination and control processes can lead a hydrological model to simulate flood and drought events that would not occur given the coordinated emergency response in the basin.

We used a new and experimental version of the Advanced Scatterometer (ASCAT) soil water index data set and Moderate Resolution Imaging Spectroradiometer (MODIS) C6 snow cover products for multiple objective calibrations of the TUWmodel in 213 catchments of Austria. Combined calibration to runoff, satellite soil moisture, and snow cover improves runoff (40 % catchments), soil moisture (80 % catchments), and snow (~ 100 % catchments) simulation compared to traditional calibration to runoff only.

Crop yield is reduced by heat and water stress, particularly when they co-occur. We quantify the joint effects of (unpredictable) air temperature and soil water availability on crop heat stress via a mechanistic model. Larger but more infrequent precipitation increased crop canopy temperatures. Keeping crops well watered via irrigation could reduce canopy temperature but not enough to always exclude heat damage. Thus, irrigation is only a partial solution to adapt to warmer and drier climates.

The risk of flash flood is of growing importance for populations, particularly in the Mediterranean area in the context of a changing climate. The representation of soil processes in models is a key factor for flash flood simulation. The importance of the various methods for soil moisture estimation are highlighted in this work. Local measurements from the field as well as data derived from satellite imagery can be used to assess the performance of model outputs.

Ecohydrological sensitivity, defined as the response intensity of streamflow to vegetation change, indicates the hydrological sensitivity to vegetation change. The study revealed seasonal ecohydrological sensitivities were highly variable, depending on climate condition and watershed attributes. Dry season ecohydrological sensitivity was mostly determined by topography, soil and vegetation, while wet season ecohydrological sensitivity was mainly controlled by soil, landscape and vegetation.

The rainfall in eastern China is principally concentrated from April–September. Changes are roughly coincident with phase shifts of the El Niño–Southern Oscillation (ENSO) in both the dry (October–March) and wet (April–September) seasons, and the Pacific Decadal Oscillation (PDO) triggers a stronger effect on precipitation in the wet season. The interannual and interdecadal rainfall variability over eastern China is substantially modulated by drivers originating from the Pacific Ocean.

The key innovation of the study is a method to simulate reactive solute transport in the vadose zone within a Lagrangian framework. We extend the LAST-Model with a method to account for non-linear sorption and first-order degradation processes during unsaturated transport of reactive substances in the matrix and macropores. Model evaluations using bromide and pesticide data from irrigation experiments under different flow conditions on various timescales show the feasibility of the method.

Soil salinity is a serious threat in numerous arid and semi-arid areas of the world. Given this threat, efficient field assessment methods are needed to monitor the dynamics of soil salinity in salt-affected lands efficiently. We demonstrate that rapid and non-invasive geophysical measurements modelled by advanced numerical analysis of the signals and coupled with hydrological modelling can provide valuable information to assess the spatio-temporal variability in soil salinity over large areas.

We compare simulated values from 47 models estimating surface water over the USA. Results show that model uncertainty is substantial over much of the conterminous USA and especially high in the west. Applying the studied models to a simple water accounting equation shows that model selection can significantly affect research results. This paper concludes that multimodel ensembles help to best represent uncertainty in conclusions and suggest targeted research efforts in arid regions.

The SMAP L4 dataset has been extensively used in hydrological applications. We innovatively use a machine learning method to analyze how the efficiency of the L4 data assimilation (DA) system is determined. It shows that DA efficiency is mainly related to T_b innovation, followed by error in precipitation forcing and microwave soil roughness. Since the L4 system can effectively filter out precipitation error, future development should focus on correctly specifying the SSM–RZSM coupling strength.

We introduce a daily-scale index, termed the standardized compound drought and heat index (SCDHI), to measure the key features of compound dry-hot conditions. SCDHI can not only monitor the long-term compound dry-hot events, but can also capture such events at sub-monthly scale and reflect the related vegetation activity impacts. The index can provide a new tool to quantify sub-monthly characteristics of compound dry-hot events, which are vital for releasing early and timely warning.

Land surface models are important tools for translating meteorological forecasts and reanalyses into real-world impacts at the Earth's surface. We show that the hydrological predictions, in particular soil moisture, of these models can be improved by combining them with satellite observations from the NASA SMAP mission to update uncertain parameters. We find a 22 % reduction in error at a network of in situ soil moisture sensors after combining model predictions with satellite observations.

This study comprehensively evaluated 11 satellite radar altimetry missions (including their official retrackers) for lake water level retrieval and developed a strategy for constructing consistent long-term water level records for inland lakes. It is a two-step bias correction and normalization procedure. First, we use Jason-2 as the initial reference to form a consistent TOPEX/Poseidon–Jason series. Then, we use this as the reference to remove the biases with other radar altimetry missions.