A geostatistical model for mountain precipitation mapping (ASOADeK)

The ASOADeK-constructed monthly precipitation map of a mountain region in northern New Mexico is comparable to PRISM, and with higher spatial resolution. See on the right the ASOADeK-generated mean annual precipitation for the northern New Mexico.

Related links:

PowerPoint file titled "Geostatistical Mapping of Mountain Precipitation Incorporating Auto-searched Effects of Terrain and Climatic Characteristics" (10 MB), to be presented at American Meteorological Society 85th Annual Meeting, San Diego, 2005

Poster titled "Geostatistical mapping of mountain precipitation incorporating auto-searched effects of terrain and climatic characteristics" (6 MB PDF), presented at SAHRA 4th Annual Meeting, Albuquerque, 2004

Tele-connection of mountain precipitation in northern New Mexico to the ENSO and PDO cycles

The seasonal precipitation anomalies were analyzed for each of the six categories of specific ENSO and PDO phase combinations. The results indicate that PDO is a more dominant factor than ENSO influencing winter and spring precipitation in the northern New Mexico. For the high PDO years, El Nino slightly enhances, but La Nina does not significantly dampen,  the positive winter precipitation anomaly. For the low PDO years, El Nino strongly dampen, and La Nina significantly enhances, the negative winter and spring precipitation anomalies. The spatial distribution of the precipitation anomalies was also explored using the ASOADeK model.

On the right is the ASOADeK-contrusted seasonal precipitation anomaly. The three white areas are high elevations of Sangre de Cristo, Jemez, and San Juan Mountains, respectively, in northern New Mexico. (Of each of the four categories, top-left panel = October, top-right panel = winter (NDJFM), bottom-left panel = spring (AMJ), and bottom-right panel = summer (JAS). the scale bar is from -50 to 50 mm).
 

A Topography- and Vegetation-based surface energy partitioning model for ET modeling (TVET)

The model considers both topographic and vegetation effects on evapotranspiration. It generates potential evaporation and potential transpiration separately based on the surface characteristics, which can be derived from remote sensing data and DEM data. Further hydrologic modeling (e.g., using HYDRUS) is necessary to obtain actual evapotranspiration. The former acronym of this model was SEP4HillET.

Related links:

Poster titled "A surface energy partitioning model for hillslope ET modeling (SEP4HillET) & its applications" (5 MB PDF), presented at SAHRA 4th Annual Meeting, Albuquerque, 2004

Matlab code of the TVET model 

Remote sensing surface vegetation coverage

Vegetation plays an important role in the near-surface hydrologic processes, by modifying the energy and water (vapor) fluxes. It changes the surface albedo, modifies aerodynamic boundary layer, intercepts rainfall, transpirates soil water, modifies soil structures (leading to preferential subsurface flow), etc.

Vegetation also works as an indicator of local hydrologic (climate) conditions. Changes in vegetation coverage may indicate the environment alteration due to the climate change or local anthropogenic disturbance.

Remote sensing is the most effective approach to quantify surface vegetation coverage. The graph to the right examines three algorithms for estimating fractional vegetation cover from remote sensing imaginary.

Modeling hillslope water partitioning

Two major limitations, a lack in understanding hydrologic processes, and sparse observation networks, hinder predictive mountain-block hydrologic studies. The above three research projects address the data problem in mountain. This project and the following ones aim at improved understanding hydrologic processes in mountains.

2D numerical simulations of variably-saturated subsurface water flow are conducted at a hillslope scale. The factors influencing hillslope water partitioning are investigated, including climate, vegetation, topography (steepness and aspect), soil cover, bedrock permeability, bedrock surface roughness.

Related links:

Poster titled "Variably saturated water flow across soil-bedrock interface on conceptual hillslopes" (2 MB PDF), presented at AGU Fall Meeting, 2002.

PowerPoint file titled "Modeling investigation of water partitioning at a semi-arid hillslope" (9 MB), presented at AGU Fall Meeting, 2003

PowerPoint file titled "Hydrologic effects and implications of vegetation in semiarid mountain regions" (14 MB), presented at SAHRA 4th Annual Meeting, Albuquerque, 2004

Assessing distributed mountain-block recharge in semiarid environments

Mountain-front recharge (MFR) is a significant groundwater replenishment to the adjacent basin aquifer. To improve MFR estimates and predict its response to potential climate change, we propose a mountain-centered view approach [Wilson and Guan, 2004]. To make various MFR estimates comparable, we suggest dividing MFR into direct MFR that occurs at the mountain front, and indirect MFR (or mountain-block recharge) that occurs in the mountain block.

Previous studies suggest significant mountain block recharge occurs in Sangre de Cristo Mountains and San Juan Mountains. Our study examined distributed mountain-block recharge with application of ASOADeK and SEP4HillET, and hydrologic process modeling.

Related links:

PowerPoint file titled "Assessing distributed mountain-block recharge in semiarid environments" (8 MB), presented at GSA Annual Meeting, Denver, 2004

Assessing climate variability impact on mountain-block recharge in semiarid regions

Mountain-block recharge is sensitive to climate variability and change. ENSO and PDO are two large-scale oceanic and atmospheric cycles affecting precipitation in the southwestern U.S. Their impacts on mountain-block recharge was assessed for two mountain blocks in the northern New Mexico, the Sangre de Cristo (right column) and Jemez (left column) Mountains. With its multi-decadal period, PDO-associated recharge variability may influence basin-scale ground water balance, and regional water resource management.