Results of a research regarding the variability of spring depletion curves

Springs, no recharge periods, discharge process, depletion coefficient

A model-data comparison of gross primary productivity: Results from the North American Carbon Program site synthesis

Accurately simulating gross primary productivity (GPP) in terrestrial ecosystem models is critical because errors in simulated GPP propagate through the model to introduce additional errors in simulated biomass and other fluxes. We evaluated simulated, daily average GPP from 26 models against estimated GPP at 39 eddy covariance flux tower sites across the United States and Canada. None of the models in this study match estimated GPP within observed uncertainty. On average, models overestimate GPP in winter, spring, and fall, and underestimate GPP in summer. Models overpredicted GPP under dry conditions and for temperatures below 0°C. Improvements in simulated soil moisture and ecosystem response to drought or humidity stress will improve simulated GPP under dry conditions. Adding a low-temperature response to shut down GPP for temperatures below 0°C will reduce the positive bias in winter, spring, and fall and improve simulated phenology. The negative bias in summer and poor overall performance resulted from mismatches between simulated and observed light use efficiency (LUE). Improving simulated GPP requires better leaf-to-canopy scaling and better values of model parameters that control the maximum potential GPP, such as ε[subscript max] (LUE), V[subscript cmax] (unstressed Rubisco catalytic capacity) or J[subscript max] (the maximum electron transport rate)

Climate control of terrestrial carbon exchange across biomes and continents

Peer reviewe

Evidence for karstic mechanisms involved in the evolution of Moroccan hamadas

Underground tubular karst features, observed in an arid envinronment of southern Morocco, are described. On the basis of various evidences, it is suggested that such features were originated mainly by condensation water. A computation of the time necessary for their formation supports this hypothesis

A Multi-Scale Approach in Hydraulic Characterization of a Metamorphic Aquifer: What Can Be Inferred about the Groundwater Abstraction Possibilities

Hard-rock aquifers, which constitute a water supply source in many countries, are highly heterogeneous and defining a realistic model of an aquifer can be extremely complex. The objective of this study was to hydraulically characterize a metamorphic aquifer in a representative area of Italy and to identify the most appropriate approach for tapping of groundwater in this challenging environment. The results of surface fracture surveys, injection tests, pumping tests, and a simplified numerical model were compared. From the surface fracture survey, a model of the rock mass characterized by a well-developed discontinuity network and by a high frequency of discontinuities resulted. The injection tests showed the extreme heterogeneity and the lower hydraulic conductivity of the rock mass in comparison with the results of the pumping tests. The independent estimate of the hydraulic parameter resulting from numerical model highlighted a range of values higher than those resulting from the pumping tests. The study demonstrated that the continuum medium approach can be used in the case of hard-rock aquifers with a dense network of discontinuities. The multi-scale approach is recommended for investigating hydraulic heterogeneity and significantly helps to identify the most promising areas for well locations and their characteristics in relation to the style of fracturing

Global estimation of evapotranspiration using a leaf area index-based surface energy and water balance model

Studies of global hydrologic cycles, carbon cycles and climate change are greatly facilitated when global estimates of evapotranspiration (E) are available. We have developed an air-relative-humidity-based two-source (ARTS) E model that simulates the surface energy balance, soil water balance, and environmental constraints on E. It uses remotely sensed leaf area index (Lai) and surface meteorological data to estimate E by: 1) introducing a simple biophysical model for canopy conductance (Gc), defined as a constant maximum stomatal conductance gsmax of 12.2mm s−1multiplied by air relative humidity (Rh) and Lai (Gc = gs max×Rh × Lai); 2) calculating canopy transpiration with the Gc-based Penman–Monteith (PM) E model; 3) calculating soil evaporation from an air relative- humidity-based model of evapotranspiration (Yan & Shugart, 2010); 4) calculating total E (E0) as the sum of the canopy transpiration and soil evaporation, assuming the absence of soil water stress; and 5) correcting E0 for soil water stress using a soil water balance model. This physiological ARTS E model requires no calibration. Evaluation against eddy covariance measurements at 19 flux sites, representing a wide variety of climate and vegetation types, indicates that daily estimated E had a root mean square error = 0.77 mm d−1, bias=−0.14 mm d−1, and coefficient of determination, R2=0.69. Global, monthly, 0.5°-gridded ARTS E simulations from1984 to 1998,whichwere forced using Advanced Very High Resolution Radiometer Lai data, Climate Research Unit climate data, and surface radiation budget data, predicted a mean annual land E of 58.4×103 km3. This falls within the range (58×103–85×103 km3) estimated by the Second Global Soil Wetness Project (GSWP-2; Dirmeyer et al., 2006). The ARTS E spatial pattern agrees well with that of the global E estimated by GSWP-2. The global annual ARTS E increased by 15.5mm per decade from 1984 to 1998, comparable to an increase of 9.9 mm per decade from the model tree ensemble approach (Jung et al., 2010). These comparisons confirm the effectivity of the ARTS E model to simulate the spatial pattern and climate response of global E. This model is the first of its kind among remote-sensing-based PM E models to provide global land E estimation with consideration of the soil water balance