A comprehensive approach to analyze discrepancies between land surface models and in-situ measurements: a case study over the US and Illinois with SECHIBA forced by NLDAS

The purpose of this study is to test the ability of the Land Surface Model SECHIBA to simulate water budget and particularly soil moisture at two different scales: regional and local. The model is forced by NLDAS data set at 1/8th degree resolution over the 1997–1999 period. SECHIBA gives satisfying results in terms of evapotranspiration and runoff over the US compared with four other land surface models, all forced by NLDAS data set for a common time period. The simulated soil moisture is compared to in-situ data from the Global Soil Moisture Database across Illinois by computing a soil wetness index. A comprehensive approach is performed to test the ability of SECHIBA to simulate soil moisture with a gradual change of the vegetation parameters closely related to the experimental conditions. With default values of vegetation parameters, the model overestimates soil moisture, particularly during summer. Sensitivity tests of the model to the change of vegetation parameters show that the roots extraction parameter has the largest impact on soil moisture, other parameters such as LAI, height or soil resistance having a minor impact. Moreover, a new evapotranspiration computation including bare soil evaporation under vegetation has been introduced into the model. The results point out an improvement of the soil moisture simulation when this effect is taken into account. Finally, soil moisture sensitivity to precipitation variation is addressed and it is shown that soil moisture observations can be rather different, depending on the method of measuring field capacity. When the observed field capacity is deducted from the observed volumetric water profiles, simulated soil wetness index is closer to the observations

3. Eventos hidrológicos extremos en la cuenca amazónica peruana: presente y futuro

Recientemente, severos eventos hidrológicos extremos han ocurrido en el Río Amazonas, como intensas sequías e inundaciones, las cuales han perjudicado a las principales ciudades amazónicas y a las zonas rurales. Esos eventos hacen parte de una tendencia hacia estiajes siempre más bajos. Mientras que el caudal más bajo fue observado en septiembre de 2010 (8 300m3/s) en la estación hidrométrica de Tamshiyacu, una rápida transición hacia uno de los caudales más altos fue observado en abril 2011 (45 000 m3/s). Finalmente en abril de 2012, durante el siguiente periodo de aguas altas, el Río Amazonas experimentó su caudal histórico más elevado (55 400m3/s). Los modelos climatológicos e hidrológicos permiten prever caudales futuros. Para la mitad del siglo 21 se calcula un aumento de 7% de los caudales de crecida, lo que significa extremos aún mayores que los actuales e inundaciones más amplias.La région du fleuve Amazone a récemment connu de sévères événements hydrologiques extrêmes: des inondations et des sécheresses qui ont porté préjudice tant aux villes amazoniennes qu’aux zones rurales. Ces événements s’inscrivent dans une tendance vers des étiages toujours plus prononcés. Alors que le débit le plus bas a été observé en septembre 2008 (8 300 m3/s) a la station hydrométrique de Tamshiyacu, celui-ci a été rapidement suivi d’une rapide transition vers l’un des débits les plus hauts en avril 2011 (45 000 m3/s). Finalement en avril 2012, lors de la saison suivante de hautes eaux, le fleuve Amazone a présenté un débit historique très élevé (55 400 m3/s). Les modelés climatologiques et hydrologiques permettent de prévoir les débits futurs. D’ici la moitié du 21ème siècle, on estime qu’il y aura une augmentation de 7% des débits de crue, ce qui signifie des extrêmes encore plus élevés qu’actuellement et des inondations de plus grande ampleur.The Amazon River has recently experienced severe extreme hydrological events -such as floods and droughts- that have harmed both the main Amazonian cities as rural areas. These events are part of a continuous trend towards low flow. While the lowest rate was observed in September 2008 (8,300 m3/s) at the Tamshiyacu hydrometric station, it was observed a rapid transition to one of the highest rates in April 2011 (45,000m3/s). In April 2012, during the next period of high water, the Amazon River experienced it highest flow in its history (55 400 m3/s). Climatological and hydrological models are used to predict future rates. An increase of 7% of flood flows is calculated by the middle of the 21st century, which means even greater extreme floods than the current ones and larger

Evaluation of ORCHIDEE-MICT-simulated soil moisture over China and impacts of different atmospheric forcing data

Soil moisture is a key variable of land surface hydrology, and its correct representation in land surface models is crucial for local to global climate predictions. The errors may come from the model itself (structure and parameterization) but also from the meteorological forcing used. In order to separate the two source of errors, four atmospheric forcing datasets, GSWP3 (Global Soil Wetness Project Phase 3), PGF (Princeton Global meteorological Forcing), CRU-NCEP (Climatic Research Unit-National Center for Environmental Prediction), and WFDEI (WATCH Forcing Data methodology applied to ERA-Interim reanalysis data), were used to drive simulations in China by the land surface model ORCHIDEE-MICT(ORganizing Carbon and Hydrology in Dynamic EcosystEms: aMeliorated Interactions between Carbon and Temperature). Simulated soil moisture was compared with in situ and satellite datasets at different spatial and temporal scales in order to (1) estimate the ability of ORCHIDEE-MICT to represent soil moisture dynamics in China; (2) demonstrate the most suitable forcing dataset for further hydrological studies in Yangtze and Yellow River basins; and (3) understand the discrepancies of simulated soil moisture among simulations. Results showed that ORCHIDEE-MICT can simulate reasonable soil moisture dynamics in China, but the quality varies with forcing data. Simulated soil moisture driven by GSWP3 and WFDEI shows the best performance according to the root mean square error (RMSE) and correlation coefficient, respectively, suggesting that both GSWP3 and WFDEI are good choices for further hydrological studies in the two catchments. The mismatch between simulated and observed soil moisture is mainly explained by the bias of magnitude, suggesting that the parameterization in ORCHIDEE-MICT should be revised for further simulations in China. Underestimated soil moisture in the North China Plain demonstrates possible significant impacts of human activities like irrigation on soil moisture variation, which was not considered in our simulations. Finally, the discrepancies of meteorological variables and simulated soil moisture among the four simulations are analyzed. The result shows that the discrepancy of soil moisture is mainly explained by differences in precipitation frequency and air humidity rather than differences in precipitation amount.</p

Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models

This is the final version of the article. Available from Wiley via the DOI in this record.Understanding the processes that determine above-ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs.This paper is a product of the European Union's Seventh Framework Programme AMAZALERT project (282664). The field data used in this study have been generated by the RAINFOR network, which has been supported by a Gordon and Betty Moore Foundation grant, the European Union's Seventh Framework Programme projects 283080, ‘GEOCARBON’; and 282664, ‘AMAZALERT’; ERC grant ‘Tropical Forests in the Changing Earth System’), and Natural Environment Research Council (NERC) Urgency, Consortium and Standard Grants ‘AMAZONICA’ (NE/F005806/1), ‘TROBIT’ (NE/D005590/1) and ‘Niche Evolution of South American Trees’ (NE/I028122/1). Additional data were included from the Tropical Ecology Assessment and Monitoring (TEAM) Network – a collaboration between Conservation International, the Missouri Botanical Garden, the Smithsonian Institution and the Wildlife Conservation Society, and partly funded by these institutions, the Gordon and Betty Moore Foundation, and other donors. Fieldwork was also partially supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico of Brazil (CNPq), project Programa de Pesquisas Ecológicas de Longa Duração (PELD-403725/2012-7). A.R. acknowledges funding from the Helmholtz Alliance ‘Remote Sensing and Earth System Dynamics’; L.P., M.P.C. E.A. and M.T. are partially funded by the EU FP7 project ‘ROBIN’ (283093), with co-funding for E.A. from the Dutch Ministry of Economic Affairs (KB-14-003-030); B.C. [was supported in part by the US DOE (BER) NGEE-Tropics project (subcontract to LANL). O.L.P. is supported by an ERC Advanced Grant and is a Royal Society-Wolfson Research Merit Award holder. P.M. acknowledges support from ARC grant FT110100457 and NERC grants NE/J011002/1, and T.R.B. acknowledges support from a Leverhulme Trust Research Fellowship

Simulations of Mississippi river basin streamflows by the land surface model ORCHIDEE. Sensitivity to the forcing resolution and parameters.

International audienceThe land surface community had shown motivation in the development of runoff routing schemes during the last decade to simulate streamflow. It is essential for our models because it integrates at large scale all the land surface hydrology processes and it is easily compared to observations for validation. It is a good challenge for the land surface model (LSM) coupled with ocean-atmosphere to close the global water cycle. Before coupling the LSM with a GCM, an evaluation offline of these routing processes is essential to understand them precisely. Therefore, this work explore the sensitivity of the LSM ORCHIDEE (Organising Carbon and Hydrology In Dynamic EcosystEms) integrating a routing scheme, for two atmospheric forcings differing in resolution, spatially (1° to (1/8)°) and temporally (6 hours to 1 hour), through streamflow variations which are compared to observations (River UCAR and USGS). The forcing data used are NCC (NgoDuc & al., 2005) and NLDAS (Cosgrove & al., 2003) over the Mississippi river basin during a common period 1997-1999. First, we have compared the atmospheric inputs between the forcings. Both give similar mean climatic conditions over the basin (precipitation in particular) excepted the solar radiation. In order to have similar input for the model, a comparison of the downward shortwave radiation is performed between the forcings and FLUXNET data. It shows an agreement between NCC data and measurements but a systematic overestimation (spatially and temporally) of about 25% during the year for the NLDAS data comparing to NCC. Therefore, a basic correction of the NLDAS downward shortwave radiation is performed and the result shows its expected decrease and its similarity with NCC. The first result is the response of the streamflow simulated by ORCHIDEE to the decrease of the NLDAS shortwave radiation. The seasonality is not affected by this modification but the magnitude is increased of about 30% at Vicksburg station during all the period. However, the correlation between the streamflow simulated and the observations is very bad. Secondly, the main result points out the high sensitivity of the streamflow seasonality to the spatial resolution (the temporal resolution has not an impact with this hydrological model). With the NCC resolution, the peak of streamflow reaches the period in agreement with the observations whereas it is hugely shifted with the high resolution. We explain this difference by the time constants of routing reservoirs in ORCHIDEE which were only calibrated with the NCC resolution. With a high resolution, we have to put a lower value of time constant for the stream reservoir which should represent a water amount routed more quickly. When we divided by a factor 10 the time constant of this reservoir and the routing time step, the seasonality of the streamflow at Vicksburg is found back and similar to NCC. Furthermore, with this calibration, we show that streamflows are correctly represented over many stations over the basin during the three years, with both forcings. We also compare ORCHIDEE to four other models which have performed the same simulation with NLDAS (Lohmann & al., 2004). For the five stations of the Mississippi river basin studied in this paper, we compare their measured streamflow variations to the simulated ones. We notice a large difference between five models. ORCHIDEE and NOAH are the most similar and able to represent the peaks accurately. Finally, we point out the good ability of the model ORCHIDEE to simulate streamflow but also the incertitude in its seasonality due to calibrated parameters such as time constant and routing time step. Overall, this study shows the necessity to find a general law to switch over spatio-temporal scale to another in a same LSM