Geology topics

Qiang Li

Publications and source records attributed to Qiang Li.

4 recordsLinked to original sources

USGS2025

Exploring management and environment effects on edge-of-field phosphorus losses with linear mixed models

Evaluating how weather, farm management, and soil conditions impact phosphorus (P) loss from agricultural sites is essential for improving our waterways in agricultural watersheds. In this study, rainfall characteristics, manure application timing, tillage, surface condition, and soil test phosphorus (STP) were analyzed to determine their effects on total phosphorus (TP) and dissolved phosphorus (DP) loss using 125 site-years of runoff data collected by the University of Wisconsin Discovery Farms and Discovery Farms Minnesota. Three linear mixed models (LMMs) were then used to evaluate the influence of those factors on TP and DP losses: (1) a model that included all runoff events, (2) manured sites only, and (3) precipitation events only. Results show that the timing of manure application relative to the timing of a runoff event only had a marginal association with P loads and concentrations, although the majority of the runoff events were collected after 10 days of manure application. Tillage was as influential factor, with greater DP loads and concentrations associated with no-till, especially during frozen conditions. Fields in this study had high STP values, but the model results only showed positive associations between DP load and DP flow-weighted mean concentration (FWMC) loss at the 0- to 15-cm depth. The precipitation event LMM (which included precipitation characteristics) was the model that resulted in the largest R 2 value. While the predictive capacity of the LMMs was low, they did illuminate the relative importance of management and environmental variables on P loss, and can be used to guide future research on P loss in this region.

Minnesota, Wisconsin↗

USGS2024

Decomposition of physical processes controlling EASM precipitation changes during the mid-Piacenzian: New insights into data–model integration

The mid-Piacenzian warm period (MPWP, ~3.264–3.025 Ma) has gained widespread interest due to its partial analogy with future climate. However, quantitative data–model comparison of East Asian Summer Monsoon (EASM) precipitation during the MPWP is relatively rare, especially due to problems in decoding the imprint of physical processes to climate signals in the records. In this study, pollen-based precipitation records are reconstructed and compared to the multi-model ensemble mean of the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2). We find spatially consistent precipitation increase in most simulations but a spatially divergent change in MPWP records. We reconcile proxy data and simulation by decomposing physical processes that control precipitation. Our results 1) reveal thermodynamic control of an overall enhancement of EASM precipitation and 2) highlight a distinct control of thermodynamic and dynamical processes on increases of tropical and subtropical EASM precipitation, reflecting the two pathways of water vapor supply that enhance EASM precipitation, respectively.

npj Climate and Atmospheric Science↗

USGS2020

Evaluation of Arctic warming in mid-Pliocene climate simulations

Palaeoclimate simulations improve our understanding of the climate, inform us about the performance of climate models in a different climate scenario, and help to identify robust features of the climate system. Here, we analyse Arctic warming in an ensemble of 16 simulations of the mid-Pliocene Warm Period (mPWP), derived from the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2). The PlioMIP2 ensemble simulates Arctic (60–90 ∘ N) annual mean surface air temperature (SAT) increases of 3.7 to 11.6 ∘ C compared to the pre-industrial period, with a multi-model mean (MMM) increase of 7.2 ∘ C. The Arctic warming amplification ratio relative to global SAT anomalies in the ensemble ranges from 1.8 to 3.1 (MMM is 2.3). Sea ice extent anomalies range from −3.0 to - 10.4 × 10 6 "> − 10.4 × 10 6 km 2 , with a MMM anomaly of - 5.6 × 10 6 "> − 5.6 × 10 6 km 2 , which constitutes a decrease of 53 % compared to the pre-industrial period. The majority (11 out of 16) of models simulate summer sea-ice-free conditions ( ≤ 1 × 10 6 "> ≤ 1 × 10 6 km 2 ) in their mPWP simulation. The ensemble tends to underestimate SAT in the Arctic when compared to available reconstructions, although the degree of underestimation varies strongly between the simulations. The simulations with the highest Arctic SAT anomalies tend to match the proxy dataset in its current form better. The ensemble shows some agreement with reconstructions of sea ice, particularly with regard to seasonal sea ice. Large uncertainties limit the confidence that can be placed in the findings and the compatibility of the different proxy datasets. We show that while reducing uncertainties in the reconstructions could decrease the SAT data–model discord substantially, further improvements are likely to be found in enhanced boundary conditions or model physics. Lastly, we compare the Arctic warming in the mPWP to projections of future Arctic warming and find that the PlioMIP2 ensemble simulates greater Arctic amplification than CMIP5 future climate simulations and an increase instead of a decrease in Atlantic Meridional Overturning Circulation (AMOC) strength compared to pre-industrial period. The results highlight the importance of slow feedbacks in equilibrium climate simulations, and that caution must be taken when using simulations of the mPWP as an analogue for future climate change.

Climate of the Past↗

USGS2017

Shallow microearthquakes near Chongqing, China triggered by the Rayleigh waves of the 2015 M7.8 Gorkha, Nepal earthquake

We present a case of remotely triggered seismicity in Southwest China by the 2015/04/25 M7.8 Gorkha, Nepal earthquake. A local magnitude ML3.8 event occurred near the Qijiang district south of Chongqing city approximately 12 min after the Gorkha mainshock. Within 30km of this ML3.8 event there are 62 earthquakes since 2009 and only 7 ML>3events, which corresponds to a likelihood of 0.3% for a ML>3on any given day by a random chance. This observation motivates us to investigate the relationship between the ML3.8 event and the Gorkha mainshock. The ML3.8 event is listed in the China Earthquake National Center (CENC) catalog and occurred at shallow depth (∼3km). By examining high-frequency waveforms, we identify a smaller local event (∼ML2.5) ∼15s before the ML3.8 event. Both events occurred during the first two cycles of the Rayleigh waves from the Gorkha mainshock. We perform seismic event detection based on envelope function and waveform matching by using the two events as templates. Both analyses found a statistically significant rate change during the mainshock, suggesting that they were indeed dynamically triggered by the Rayleigh waves. Both events occurred during the peak normal and dilatational stress changes (∼10–30 kPa), consistent with observations of dynamic triggering in other geothermal/volcanic regions. Although other recent events (i.e., the 2011 M9.1 Tohoku-Oki earthquake) produced similar peak ground velocities, the 2015 Gorkha mainshock was the only event that produced clear dynamic triggering in this region. The triggering site is close to hydraulic fracturing wells that began production in 2013–2014. Hence we suspect that fluid injections may increase the region’s susceptibility to remote dynamic triggering.

Chongqing↗