Geology topics

Matthew P. Dannenberg

Publications and source records attributed to Matthew P. Dannenberg.

5 recordsLinked to original sources

USGS2026

Potential flood events in the lower Missouri River basin over multiple centuries identified using tree-ring based multi-model streamflow reconstructions

The Missouri River basin (MRB), the largest river basin in the United States, presents major water management challenges due to its complex topology and extensive infrastructure designed to manage high annual flows. Severe hydroclimatic events, particularly floods in 1993, 2011, and 2019, have highlighted vulnerabilities, leading the U.S. Army Corps of Engineers to enhance flood risk assessments in 2023. This study focuses on the full MRB, using tree-ring based streamflow reconstructions to extend the Basin's historic streamflow perspective. We developed annual streamflow reconstructions for the Hermann, Missouri streamgage from water years 1360–1900 using K-nearest neighbor and principal component regression methods. These reconstructions incorporate 183 tree-ring chronologies (1360–2020) and modeled natural streamflow (1901–‍2020). Reconstructions were evaluated for consistency using statistical measures and wavelet analysis. Both methods produced similar results, confirming their reliability in reconstructing multi-century streamflows. This novel methodology, guided by wavelet analysis, was developed to identify potential flood events in the lower Missouri River basin (LMRB), resulting in the identification of 172 potential flood events from water years 1360–2020, with 126 events common to the two versions of the MRB reconstructions. The reconstructed streamflow records showed an increase in the number of events until the late-18th- or mid-19th-century. These findings provide insights into evolving flood characteristics in the LMRB. The novel methodology developed in this study can be used to identify potential flood events from tree-ring based annual streamflow reconstructions and generally be applicable to other river basins.

Colorado, Iowa, Kansas, Missouri, Nebraska, Wyomin↗

USGS2024

Reply to comment on "Five decades of observed daily precipitation reveal longer and more variable drought events across much of the western United States"

Paciorek and Wehner raise important questions around our use of the Mann-Kendall nonparametric trend test on smoothed data for analyzing long-term hydrometeorological trends in Zhang et al. (2021, https://doi.org/10.1029/2020gl092293 ). We thank them for initiating this important conversation and their gracious cooperation in exploring the issues addressed in their comment. In this reply we confirm the inflation of significant p -values by our choice to smooth, illustrate the relatively minor impacts on the main conclusions of our paper, and add our voices to those of Paciorek and Wehner in highlighting the lack of methodology for hypothesis testing across multiple stations that have spatial structure (i.e., testing for regionally consistent trends).

western United States↗

USGS2022

Satellite solar-induced chlorophyll fluorescence and near-infrared reflectance capture complementary aspects of dryland vegetation productivity dynamics

Mounting evidence indicates dryland ecosystems play an important role in driving the interannual variability and trend of the terrestrial carbon sink. Nevertheless, our understanding of the seasonal dynamics of dryland ecosystem carbon uptake through photosynthesis [gross primary productivity (GPP)] remains relatively limited due in part to the limited availability of long-term data and unique challenges associated with satellite remote sensing across dryland ecosystems. Here, we comprehensively evaluated longstanding and emerging satellite vegetation proxies in their ability to capture seasonal dryland GPP dynamics. Specifically, we evaluated: 1) reflectance-based proxies normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), near infrared reflectance index (NIR v ), and kernel NDVI (kNDVI) from the MODerate resolution Imaging Spectroradiometer (MODIS); and 2) newly available physiologically-based proxy solar-induced chlorophyll fluorescence (SIF) from the TROPOspheric Monitoring Instrument (TROPOMI). As a performance benchmark, we used GPP estimates from a robust network of 21 western United States eddy covariance tower sites that span representative gradients in dryland ecosystem climate and functional composition. We found that NIR v and SIF were the best performing GPP proxies and captured complementary aspects of seasonal GPP dynamics across dryland ecosystem types. NIR v offered better performance than the other proxies across relatively low-productivity, sparsely non-evergreen vegetated sites (R 2 = 0.59 ± 0.13); whereas SIF best captured seasonal dynamics across relatively high-productivity sites, including evergreen-dominated sites (R 2 = 0.74 ± 0.07). Notably, across grass-dominated sites, all reflectance-based proxies (NDVI, SAVI, NIR v and kNDVI) showed significant seasonal bias (hysteresis) that strengthened with the total fraction of woody vegetation cover, likely due to seasonal patterns in woody vegetation reflectance that are unrelated to or decoupled from GPP. Future efforts to fully integrate the complementary strengths of NIR v and SIF could significantly improve our understanding and representation of dryland GPP dynamics in satellite-based models.

Arizona, California, Colorado, Idaho, New Mexico, ↗

USGS2021

Five decades of observed daily precipitation reveal longer and more variable drought events across much of the western United States

Multiple lines of evidence suggest climate change will result in increased precipitation variability and consequently more frequent extreme events. These hydroclimatic changes will likely have significant socioecological impacts, especially across water-limited regions. Here we present an analysis of daily meteorological observations from 1976 to 2019 at 337 long-term weather stations distributed across the western United States (US). In addition to widespread warming (0.2 °C ± 0.01°C/decade, daily maximum temperature), we observed trends of reduced annual precipitation (−2.3 ± 1.5 mm/decade) across most of the region, with increasing interannual variability of precipitation. Critically, daily observations showed that extreme-duration drought became more common, with increases in both the mean and longest dry interval between precipitation events (0.6 ± 0.2, 2.4 ± 0.3 days/decade) and greater interannual variability in these dry intervals. These findings indicate that, against a backdrop of warming and drying, large regions of the western US are experiencing intensification of precipitation variability, with likely detrimental consequences for essential ecosystem services.

Geophysical Research Letters↗

USGS2019

Remote sensing of dryland ecosystem structure and function: Progress, challenges, and opportunities

Drylands make up roughly 40% of the Earth's land surface, and billions of people depend on services provided by these critically important ecosystems. Despite their relatively sparse vegetation, dryland ecosystems are structurally and functionally diverse, and emerging evidence suggests that these ecosystems play a dominant role in the trend and variability of the terrestrial carbon sink. More, drylands are highly sensitive to climate and are likely to have large, non-linear responses to hydroclimatic change. Monitoring the spatiotemporal dynamics of dryland ecosystem structure (e.g., leaf area index) and function (e.g., primary production and evapotranspiration) is therefore a high research priority. Yet, dryland remote sensing is defined by unique challenges not typically encountered in mesic or humid regions. Major challenges include low vegetation signal-to-noise ratios, high soil background reflectance, presence of photosynthetic soils (i.e., biological soil crusts), high spatial heterogeneity from plot to regional scales, and irregular growing seasons due to unpredictable seasonal rainfall and frequent periods of drought. Additionally, there is a relative paucity of continuous, long-term measurements in drylands, which impedes robust calibration and evaluation of remotely-sensed dryland data products. Due to these issues, remote sensing techniques developed in other ecosystems or for global application often result in inaccurate, poorly constrained estimates of dryland ecosystem structural and functional dynamics. Here, we review past achievements and current progress in remote sensing of dryland ecosystems, including a detailed discussion of the major challenges associated with remote sensing of key dryland structural and functional dynamics. We then identify strategies aimed at leveraging new and emerging opportunities in remote sensing to overcome previous challenges and more accurately contextualize drylands within the broader Earth system. Specifically, we recommend: 1) Exploring novel combinations of sensors and techniques (e.g., solar-induced fluorescence, thermal, microwave, hyperspectral, and LiDAR) across a range of spatiotemporal scales to gain new insights into dryland structural and functional dynamics; 2) utilizing near-continuous observations from new-and-improved geostationary satellites to capture the rapid responses of dryland ecosystems to diurnal variation in water stress; 3) expanding ground observational networks to better represent the heterogeneity of dryland systems and enable robust calibration and evaluation; 4) developing algorithms that are specifically tuned to dryland ecosystems by utilizing expanded ground observational network data; and 5) coupling remote sensing observations with process-based models using data assimilation to improve mechanistic understanding of dryland ecosystem dynamics and to better constrain ecological forecasts and long-term projections.

Remote Sensing of Environment↗