Ecohydrological Controls on Grass and Shrub Above-ground Net Primary Productivity in a Seasonally Dry Climate

Seasonally dry, water‐limited regions are often co‐dominated by distinct herbaceous and woody plant communities with contrasting ecohydrological properties. We investigated the shape of the above‐ground net primary productivity (ANPP) response to annual precipitation (Pa) for adjacent grassland and shrubland ecosystems in Southern California, with the goal of understanding the role of these ecohydrological properties on ecosystem function. Our synthesis of observations and modelling demonstrates grassland and shrubland exhibit distinct ANPP‐Pa responses that correspond with characteristics of the long‐term Pa distribution and mean water balance fluxes. For annual grassland, no ANPP occurs below a ‘precipitation compensation point,’ where bare soil evaporation dominates the water balance, and ANPP saturates above the Pawhere deep percolation and runoff contribute to the modelled water balance. For shrubs, ANPP increases at a lower and relatively constant rate across the Pa gradient, while deep percolation and runoff account for a smaller fraction of the modelled water balance. We identify precipitation seasonality, root depth, and water stress sensitivity as the main ecosystem properties controlling these responses. Observed ANPP‐Paresponses correspond to notably different patterns of rain‐use efficiency (RUE). Grass RUE exceeds shrub RUE over a wide range of typical Pa values, whereas grasses and shrubs achieve a similar RUE in particularly dry or wet years. Inter‐annual precipitation variability, and the concomitant effect on ANPP, plays a critical role in maintaining the balance of grass and shrub cover and ecosystem‐scale productivity across this landscape

Not Like Everybody Else:Essays in Honor of Kees Mandemakers

This collection of essays pays tribute to Kees Mandemaker's great contribution to the data infrastructure of social science history, in the Netherlands and elsewhere. Several essays discuss (the future of) historical databases. Yet other provide examples of research on topics covering important life course transitions. All demonstrate the scale, scope and variation of research based on well-constructed databases

Application of a Hillslope-Scale Soil Moisture Data Assimilation System to Military Trafficability Assessment

Soil moisture is an important environmental variable that impacts military operations and weapons systems. Accurate and timely forecasts of soil moisture at appropriate spatial scales, therefore, are important for mission planning. We present an application of a soil moisture data assimilation system to military trafficability assessment. The data assimilation system combines hillslope-scale (e.g., 10s to 100s of m) estimates of soil moisture from a hydrologic model with synthetic L-band microwave radar observations broadly consistent with the planned NASA Soil Moisture Active–Passive (SMAP) mission. Soil moisture outputs from the data assimilation system are input to a simple index-based model for vehicle trafficability. Since the data assimilation system uses the ensemble Kalman Filter, the risks of impaired trafficability due to uncertainties in the observations and model inputs can be quantified. Assimilating the remote sensing observations leads to significantly different predictions of trafficability conditions and associated risk of impaired trafficability, compared to an approach that propagates forward uncertainties in model inputs without assimilation. Specifically, assimilating the observations is associated with an increase in the risk of “slow go” conditions in approximately two-thirds of the watershed, and an increase in the risk of “no go” conditions in approximately 40% of the watershed. Despite the simplicity of the trafficability assessment tool, results suggest that ensemble-based data assimilation can potentially improve trafficability assessment by constraining predictions to observations and facilitating quantitative assessment of the risk of impaired trafficability

A weather generator for hydrological, ecological, and agricultural applications

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95112/1/wrcr11029.pd

Physically based modeling of rainfall-triggered landslides: a case study in the Luquillo forest, Puerto Rico

This paper presents the development of a rainfall-triggered landslide module within an existing physically based spatially distributed ecohydrologic model. The model, tRIBS-VEGGIE (Triangulated Irregular Networks-based Real-time Integrated Basin Simulator and Vegetation Generator for Interactive Evolution), is capable of a sophisticated description of many hydrological processes; in particular, the soil moisture dynamics are resolved at a temporal and spatial resolution required to examine the triggering mechanisms of rainfall-induced landslides. The validity of the tRIBS-VEGGIE model to a tropical environment is shown with an evaluation of its performance against direct observations made within the study area of Luquillo Forest. The newly developed landslide module builds upon the previous version of the tRIBS landslide component. This new module utilizes a numerical solution to the Richards' equation (present in tRIBS-VEGGIE but not in tRIBS), which better represents the time evolution of soil moisture transport through the soil column. Moreover, the new landslide module utilizes an extended formulation of the factor of safety (FS) to correctly quantify the role of matric suction in slope stability and to account for unsaturated conditions in the evaluation of FS. The new modeling framework couples the capabilities of the detailed hydrologic model to describe soil moisture dynamics with the infinite slope model, creating a powerful tool for the assessment of rainfall-triggered landslide risk.United States. National Aeronautics and Space Administration (Project NNX07AD29G

Rainfall-runoff as spatial stochastic processes : data collection and synthesis.

Thesis. 1975. Sc.D.--Massachusetts Institute of Technology. Dept. of Civil Engineering.Vita.Bibliography: leaves 213-221.Sc.D

Investigating the interstellar dust through the Fe K-edge

The chemical and physical properties of interstellar dust in the densest regions of the Galaxy are still not well understood. X-rays provide a powerful probe since they can penetrate gas and dust over a wide range of column densities (up to $10^{24}\ \rm{cm}^{-2}$). The interaction (scattering and absorption) with the medium imprints spectral signatures that reflect the individual atoms which constitute the gas, molecule, or solid. In this work we investigate the ability of high resolution X-ray spectroscopy to probe the properties of cosmic grains containing iron. Although iron is heavily depleted into interstellar dust, the nature of the Fe-bearing grains is still largely uncertain. In our analysis we use iron K-edge synchrotron data of minerals likely present in the ISM dust taken at the European Synchrotron Radiation Facility. We explore the prospects of determining the chemical composition and the size of astrophysical dust in the Galactic centre and in molecular clouds with future X-ray missions. The energy resolution and the effective area of the present X-ray telescopes are not sufficient to detect and study the Fe K-edge, even for bright X-ray sources. From the analysis of the extinction cross sections of our dust models implemented in the spectral fitting program SPEX, the Fe K-edge is promising for investigating both the chemistry and the size distribution of the interstellar dust. We find that the chemical composition regulates the X-ray absorption fine structures in the post edge region, whereas the scattering feature in the pre-edge is sensitive to the mean grain size. Finally, we note that the Fe K-edge is insensitive to other dust properties, such as the porosity and the geometry of the dust.Comment: 11 pages, 10 figures. Accepted for publication in Astronomy and Astrophysic