Geology topics

Jiaqi Zhang

Publications and source records attributed to Jiaqi Zhang.

3 recordsLinked to original sources

USGS2026

Groundwater dependency and hydroclimatic influences on riparian and upland vegetation productivity, Upper San Pedro, Arizona, United States

In arid and semi-arid regions, groundwater sustains vegetation through subsurface water access, yet the responses of groundwater-dependent ecosystems (GDEs) to changing hydroclimate and groundwater availability are relatively understudied. This study investigates seasonal and spatial patterns in vegetation greenness using Landsat Enhanced Vegetation Index (EVI) values across riparian and upland zones in the semi-arid Upper San Pedro (USP) watershed, southern Arizona, which experiences a bimodal precipitation regime. We paired 25 years (2000–2024) of EVI and depth to groundwater (DTG) data from 89 wells and climate metrics (precipitation and vapour pressure deficit) to quantify the sensitivity of vegetation to subsurface moisture as well as atmospheric moisture supply and demand. Vegetation at wells near the USP riparian area showed strong associations between EVI and DTG anomalies during the monsoon season, indicating sustained groundwater use even during this wet period when summer precipitation is abundant. In contrast, upland vegetation that lacked access to groundwater showed minimal sensitivity in EVI to DTG and was generally less responsive to vapour pressure deficit. Interestingly, the riparian GDEs were not decoupled from precipitation and climate variability. These results underscore the importance of groundwater for maintaining riparian productivity and highlight the utility of remote sensing in identifying vegetation-climate-groundwater linkages across heterogeneous dryland landscapes.

Arizona↗

USGS2021

Technique to estimate generalized skew coefficients of annual peak streamflow for natural watershed conditions in Texas, Oklahoma, and eastern New Mexico

Reliable information about the frequency of annual peak streamflow is needed for floodplain management, objective assessment of flood risk, and cost-effective design of dams, levees, other flood-control structures, and roads, bridges, and culverts. Generalized skew coefficients are among the data needed for log-Pearson type III peak-streamflow frequency analyses of annual peak streamflows. A technique is presented to estimate generalized skew coefficients used for log-Pearson type III peak-streamflow frequency analyses of annual peak streamflow from natural watersheds (minimal regulation and minimal impervious cover). The estimation of generalized skew coefficients was based on annual and historical peak streamflow data from an initial set of 444 selected USGS streamgaging stations (streamgages) with at least 30 years of recorded annual peak streamflows from natural watersheds in Texas, Oklahoma, and the part of New Mexico east of the Great Continental Divide. The primary focus was to obtain information that could be used to update previously published generalized skew coefficients in Texas. Of the 444 candidate streamgages, 341 were used in the final construction of statistical models. Two generalized additive models (GAMs) were used to predict generalized skew based on a 2-dimensional smooth on projected Albers equal area coordinates of either (1) the locations of the centroids of the gaged watersheds or (2) the streamgage locations. To create maps of generalized skew coefficients, predictions were made on a 1-kilometer grid and contour lines were superimposed. The centroid-location map, with a mean-squared error (MSE) of 0.216, is preferred. Generalized skew coefficients from the centroid-location map, along with the MSE, are useful for computing weighted-skew values when conducting frequency analyses of annual peak streamflow following the guidelines set forth in Bulletin 17C. Based on the results of the study, text revision of the TxDOT Hydraulic Design Manual could be made.

New Mexico, Oklahoma, Texas↗

USGS2017

Estimating floodwater depths from flood inundation maps and topography

Information on flood inundation extent is important for understanding societal exposure, water storage volumes, flood wave attenuation, future flood hazard, and other variables. A number of organizations now provide flood inundation maps based on satellite remote sensing. These data products can efficiently and accurately provide the areal extent of a flood event, but do not provide floodwater depth, an important attribute for first responders and damage assessment. Here we present a new methodology and a GIS-based tool, the Floodwater Depth Estimation Tool (FwDET), for estimating floodwater depth based solely on an inundation map and a digital elevation model (DEM). We compare the FwDET results against water depth maps derived from hydraulic simulation of two flood events, a large-scale event for which we use medium resolution input layer (10 m) and a small-scale event for which we use a high-resolution (LiDAR; 1 m) input. Further testing is performed for two inundation maps with a number of challenging features that include a narrow valley, a large reservoir, and an urban setting. The results show FwDET can accurately calculate floodwater depth for diverse flooding scenarios but also leads to considerable bias in locations where the inundation extent does not align well with the DEM. In these locations, manual adjustment or higher spatial resolution input is required.

Journal of the American Water Resources Associatio↗