Abstract.A new global estimate of surface turbulent fluxes, latent heat flux (LE) and sensible heat flux (H ), and gross primary production (GPP) is developed using a machine learning approach informed by novel remotely sensed solarinduced fluorescence (SIF) and other radiative and meteorological variables. This is the first study to jointly retrieve LE, H , and GPP using SIF observations. The approach uses an artificial neural network (ANN) with a target dataset generated from three independent data sources, weighted based on a triple collocation (TC) algorithm. The new retrieval, named Water, Energy, and Carbon with Artificial Neural Networks (WECANN), provides estimates of LE, H , and GPP from 2007 to 2015 at 1 • × 1 • spatial resolution and at monthly time resolution. The quality of ANN training is assessed using the target data, and the WECANN retrievals are evaluated using eddy covariance tower estimates from the FLUXNET network across various climates and conditions. When compared to eddy covariance estimates, WECANN typically outperforms other products, particularly for sensible and latent heat fluxes. Analyzing WECANN retrievals across three extreme drought and heat wave events demonstrates the capability of the retrievals to capture the extent of these events.Uncertainty estimates of the retrievals are analyzed and the interannual variability in average global and regional fluxes shows the impact of distinct climatic events -such as the 2015 El Niño -on surface turbulent fluxes and GPP.

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A new seasonal design flood method based on bivariate joint distribution of flood magnitude and date of occurrence. Hydrol. Sci. J. 55(8), 1264-1280.Abstract Seasonal design floods which consider information on seasonal variation are very important for reservoir operation and management. The seasonal design flood method currently used in China is based on seasonal maximum (SM) samples and assumes that the seasonal design frequency is equal to the annual design frequency. Since the return period associated with annual maximum floods is taken as the standard in China, the current seasonal design flood cannot satisfy flood prevention standards. A new seasonal design flood method, which considers dates of flood occurrence and magnitudes of the peaks (runoff), was proposed and established based on copula function. The mixed von Mises distribution was selected as marginal distribution of flood occurrence dates. The Pearson Type III and exponential distributions were selected as the marginal distribution of flood magnitude for annual maximum flood series and peak-over-threshold samples, respectively. The proposed method was applied at the Geheyan Reservoir, China, and then compared with the currently used seasonal design flood methods. The case study results show that the proposed method can satisfy the flood prevention standard, and provide more information about the flood occurrence probabilities in each sub-season. The results of economic analysis show that the proposed design flood method can enhance the floodwater utilization rate and give economic benefits without lowering the annual flood protection standard.Une nouvelle méthode d'évaluation de crue de projet saisonnière basée sur une distribution jointe bivariée de la magnitude et de la date d'occurrence de la crue Résumé Les crues de projet saisonnières qui tiennent compte d'informations sur la variabilité saisonnière sont très importantes pour l'opération et la gestion des barrages. La méthode d'évaluation de crue de projet saisonnière actuellement utilisée en Chine est basée sur des échantillons de maximum saisonnier et suppose que la fréquence de projet saisonnière est égale à la fréquence de projet annuelle. La période de retour associée aux pics de crue annuels étant le standard en Chine, la crue de projet saisonnière actuelle ne permet pas de satisfaire les objectifs de prévention de crue. Une nouvelle méthode d'évaluation des crues de projet saisonnières, qui considère les dates d'occurrence des crues ainsi que les magnitudes des pics de ruissellement, est proposée et établie sur la base de copules. La distribution mixte de von Mises est choisie pour la distribution marginale de la date d'occurrence de la crue. Les distributions Pearson III et exponentielle sont choisies pour les distributions de la magnitude respectivement de la série du maximum annuel et des échantillons seuillés. La méthode proposée est appliquée au Barrage Geheyan, Chine, puis comparée avec les méthodes d'évaluation de crue de projet saisonnière actuellement utilisées. Les résultats ...