LDAS-Monde, a global land data assimilation system, is applied over Europe and the Mediterranean basin to increase monitoring accuracy for land surface variables. It is able to ingest information from satellite-derived surface soil moisture (SSM) and leaf area index (LAI) observations to constrain the ISBA land surface model coupled with the CTRIP continental hydrological system. Assimilation of SSM and LAI leads to a better representation of evapotranspiration and gross primary production.

Rapidly increasing population and human activities have altered terrestrial water fluxes on an unprecedented scale. Awareness of potential water scarcity led to first global water resource assessments; however, few hydrological models considered the interaction between terrestrial water fluxes and human activities. Our contribution highlights the importance of human activities transforming the Earth's water cycle, and how hydrological models can include such influences in an integrated manner.

Runoff measurements for 966 catchments around the globe were used to assess the quality of the daily runoff estimates of 10 hydrological models run as part of tier-1 of the eartH2Observe project. We found pronounced inter-model performance differences, underscoring the importance of hydrological model uncertainty.

MSWEP (Multi-Source Weighted-Ensem­ble Pre­cip­i­ta­tion) is a new global ter­res­trial pre­cip­i­ta­tion dataset with a high 3-hourly tem­po­ral and 0.25° spa­tial res­o­lu­tion. The dataset is unique in that it takes advan­tage of a wide range of data sources, includ­ing gauge, satel­lite, and reanaly­sis data, to obtain the best pos­si­ble precipitation esti­mates at global scale. The dataset outper­forms existing gauge-adjusted precipitation datasets.

L-band radiometry is considered to be one of the most suitable techniques for estimating surface soil moisture (SSM) by means of remote sensing. Brightness temperatures are key in this process, as they are the main input in the retrieval algorithm which yields SSM. This paper compares brightness temperatures measured by the SMOS mission to two different sets of modelled ones. It shows that models and remote-sensed values agree well in temporal variability, but not in their spatial structures.

The ensemble Kalman filter (EnKF) and simplified extended Kalman filter (SEKF) root-zone soil moisture analyses are compared when assimilating in situ surface observations. In the synthetic experiments, the EnKF performs best because it can stochastically capture the errors in the precipitation. The two methods perform similarly in the real experiments. During the summer period, both methods perform poorly as a result of nonlinearities in the land surface model.

Extreme weather conditions can strongly affect arable crop growth and final yields. Early heat waves over Italy from 1995 to 2013 are identified and characterised, and their impact on durum wheat yields is investigated. Results confirm the impact of the 2003 heat waves and highlight a high percentage of concurrence of early heat waves and significant negative yield anomalies in 13 out of 39 durum wheat production areas. In the most important area of production this percentage exceeds 80%.

This study explores how catchment heterogeneity and variability can be summarized in simplified models, representing the dominant hydrological processes. We apply simple dynamical system approach (Kirchner, 2009) in the Ardèche catchment (south-east France). The simple dynamical system hypothesis works especially well in wet conditions (peaks and recessions are well modelled) and for granite catchments, which are likely to be characterized by shallow subsurface flow.