No abstract

Relatively little is currently known about the spatiotemporal variability of land surface conditions during the North American monsoon, in particular for regions of complex topography. As a result, the role played by land-atmosphere interactions in generating convective rainfall over steep terrain and sustaining monsoon conditions is still poorly understood. In this study, the variation of hydrometeorological conditions along a large-scale topographic transect in northwestern Mexico is described. The transect field experiment consisted of daily sampling at 30 sites selected to represent variations in elevation and ecosystem distribution. Simultaneous soil and atmospheric variables were measured during a 2-week period in early August 2004. Transect observations were supplemented by a network of continuous sampling sites used to analyze the regional hydrometeorological conditions prior to and during the field experiment. Results reveal the strong control exerted by topography on the spatial and temporal variability in soil moisture, with distinct landscape regions experiencing different hydrologic regimes. Reduced variations at the plot and transect scale during a drydown period indicate that homogenization of hydrologic conditions occurred over the landscape. Furthermore, atmospheric variables are clearly linked to surface conditions, indicating that heating and moistening of the boundary layer closely follow spatial and temporal changes in hydrologic properties. Land-atmosphere interactions at the basin scale (ϳ100 km 2 ), obtained via a technique accounting for topographic variability, further reveal the role played by the land surface in sustaining high atmospheric moisture conditions, with implications toward rainfall generation during the North American monsoon.

No abstract

Seasonal vegetation changes during the North American monsoon play a major role in modifying water, energy, and momentum fluxes. Nevertheless, most models parameterize plants as a static component or with averaged seasonal variations that ignore interannual differences and their potential impact on evapotranspiration (ET) and its components. Here vegetation parameters derived from remote sensing data were coupled with a hydrologic model at two eddy covariance (EC) sites with observations spanning multiple summers. Sinaloan thornscrub (ST) and Madrean woodland (MW) sites, arranged at intermediate and high elevations along mountain fronts in northwest Mexico, occupy specific niches related to climate conditions and water availability that are poorly understood. We found that simulations with a dynamic representation of vegetation greening tracked well the seasonal evolution of observed ET and soil moisture (SM). A switch in the dominant component of ET from soil evaporation (E) to plant transpiration (T) was observed for each ecosystem depending on the timing and magnitude of vegetation greening that is directly tied to rainfall characteristics. Differences in vegetation greening at the ST and MW sites lead to a dominance of transpiration at ST (T/ET 5 57%), but evaporation-dominant conditions at MW (T/ET 5 19%). Peak transpiration occurred at 5 and 20 days after the full canopy development in the ST and MW sites, respectively. These results indicate that evapotranspiration timing and partitioning varies considerably in the two studied ecosystems in accordance with different modes of vegetation greening. Intermediateelevation ecosystems follow an intensive water use strategy with a rapid and robust transpiration response to water availability. In contrast, higher elevation sites have delayed and attenuated transpiration, suggesting an extensive water use strategy persisting beyond the North American monsoon.

Soil moisture distributions are expected to be closely tied to ecosystem processes in water-limited environments of the southwest United States. Nevertheless, few studies have addressed how soil moisture varies across grassland to forest transitions frequently observed in semiarid mountain settings. In this study, we quantify the vegetation controls on surface soil moisture by sampling a range of different ecosystems present in the Valles Caldera, New Mexico. Soil and atmospheric variables were measured during a 2-week field campaign conducted in late July to early August 2005 during the North American monsoon. Field observations were supplemented by a network of continuous instruments used to assess conditions prior to and after the sampling campaign. Results reveal that soil moisture responds directly to summer precipitation events and is mediated by plant interception, which differs across the grassland-forest continuum. The nature of the spatial and temporal variations in soil moisture changes across the different sampled ecosystems: wetlands, riparian forests, grasslands, ponderosa, deciduous and mixed conifer forests. In particular, statistical analyses of soil moisture distributions indicate that distinct regimes (e.g. probability density functions) exist along the semiarid vegetation gradient, which may not be revealed through simple metrics such as the ecosystem average. Ecosystem differences are further elucidated through comparison of the spatial variations in each vegetation type, indicating higher variability in wetland and grassland sites.

a b s t r a c tHyperresolution (<1 km) hydrologic modeling of regional watersheds is expected to support a broad range of terrestrial water cycle studies, but its feasibility is still challenging due to process, data and computational constraints, as well as difficulties in interpreting the high-dimensional dataset of spatiotemporal model forcings and outputs. We address some of these modeling challenges by extending the application of a physicallybased, distributed hydrologic model to the Río San Miguel watershed (3796 km 2 ) in Mexico based on prior efforts that demonstrated the process fidelity at smaller spatiotemporal scales. Long-term (7 year) simulations are conducted at a hyperresolution (∼78 m) over the large domain using parallel simulation capabilities. To address data sparseness, we develop strategies to integrate ground, remotely-sensed and reanalysis data for setting up, forcing and parameterizing the model. Complementary tests with observations at individual stations and remotely-sensed spatial patterns reveal a robust model performance. After building confidence in the model, we interpret the spatiotemporal model forcings and outputs using empirical orthogonal functions (EOFs) analyses. For all model outputs, a large portion (58-80%) of the spatiotemporal variability can be explained by two dominant EOFs, which are related to model forcings and basin properties. Terrain controls on soil water accumulation have a marked impact on the spatial distribution of most hydrologic variables during the wet season. In addition, soil properties affect soil moisture patterns, while vegetation and elevation distributions influence evapotranspiration and runoff fields. Given the large outputs from long-term hyperresolution simulations, EOF analyses provide a promising avenue for extracting meaningful hydrologic information within complex, regional watersheds.

No abstract

Non-forest ecosystems, dominated by shrubs, grasses and herbaceous plants, provide ecosystem services including carbon sequestration and forage for grazing, and are highly sensitive to climatic changes. Yet these ecosystems are