Shengnan Zhou
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Shengnan Zhou has a total of 42 co-authors. Here are the top co-authors by number of shared publications:
A.N. Papanicolaou
Dep. of Civil and Environmental Engineering Univ. of Tennessee Knoxville TN 37996
1 shared publicationAllison E. Goodwell
Dep. of Civil Engineering Univ. of Colorado Denver CO 80204
1 shared publicationAndrew J. Margenot
1 shared publication- Andrew J. Margenot
Department of Crop Sciences University of Illinois Urbana‐Champaign Urbana Illinois USA
1 shared publication Andrew Stumpf
Illinois Geological Survey Champaign IL 61820
1 shared publicationArt Bettis
Dep. of Earth and Environmental Sciences Univ. of Iowa Iowa City IA 52242
1 shared publication
Latest Publications
- Open Access
- 11 December 2024
- Published by Elsevier in Journal of Hydrology
- Vol. 651
The double-edged sword of agricultural tile drainage effects on stream flashiness: A meta-analysis
- 11 December 2024
- Published by Elsevier in Journal of Hydrology
- Vol. 651
Open AccessThe double-edged sword of agricultural tile drainage effects on stream flashiness: A meta-analysis
- Open Access
- 11 December 2018
- Published by MDPI AG in Geosciences
- Vol. 8 (12) , 470
The Role of Hydraulic Connectivity and Management on Soil Aggregate Size and Stability in the Clear Creek Watershed, Iowa
The role of tillage practices on soil aggregate properties has been mainly addressed at the pedon scale (i.e., soilscape scale) by treating landscape elements as disconnected. However, there is observed heterogeneity in aggregate properties along flowpaths, suggesting that landscape scale hydraulic processes are also important. This study examines this supposition using field, laboratory and modeling analysis to assess aggregate size and stability along flowpaths under different management conditions: (1) tillage-induced abrasion effects on aggregate size were evaluated with the dry mean weight diameter (DMWD); (2) raindrop impact effects were evaluated with small macroaggregate stability (SMAGGSTAB) using rainfall simulators; and (3) these aggregate proxies were studied in the context of connectivity through the excess bed shear stress (δ), quantified using a physically-based landscape model. DMWD and SMAGGSTAB decreased along the flowpaths for all managements, and a negative correspondence between the proxies and δ was observed. δ captured roughness effects on connectivity along the flowpaths: highest connectivity was noted for parallel-ridge-till flowpaths, where δ ranged from 0–8.2 Pa, and lowest connectivity for contour-ridge-till flowpaths, where δ ranged from 0–1.1 Pa. High tillage intensity likely led to an increase in aggregate susceptibility to hydraulic forcing, reflected in the higher gradients of aggregate size and stability trendlines with respect to δ. Finally, a linear relationship between DMWD and SMAGGSTAB was established.
- 11 December 2018
- Published by MDPI AG in Geosciences
- Vol. 8 (12) , 470
Open AccessThe Role of Hydraulic Connectivity and Management on Soil Aggregate Size and Stability in the Clear Creek Watershed, Iowa
The role of tillage practices on soil aggregate properties has been mainly addressed at the pedon scale (i.e., soilscape scale) by treating landscape elements as disconnected. However, there is observed heterogeneity in aggregate properties along flowpaths, suggesting that landscape scale hydraulic processes are also important. This study examines this supposition using field, laboratory and modeling analysis to assess aggregate size and stability along flowpaths under different management conditions: (1) tillage-induced abrasion effects on aggregate size were evaluated with the dry mean weight diameter (DMWD); (2) raindrop impact effects were evaluated with small macroaggregate stability (SMAGGSTAB) using rainfall simulators; and (3) these aggregate proxies were studied in the context of connectivity through the excess bed shear stress (δ), quantified using a physically-based landscape model. DMWD and SMAGGSTAB decreased along the flowpaths for all managements, and a negative correspondence between the proxies and δ was observed. δ captured roughness effects on connectivity along the flowpaths: highest connectivity was noted for parallel-ridge-till flowpaths, where δ ranged from 0–8.2 Pa, and lowest connectivity for contour-ridge-till flowpaths, where δ ranged from 0–1.1 Pa. High tillage intensity likely led to an increase in aggregate susceptibility to hydraulic forcing, reflected in the higher gradients of aggregate size and stability trendlines with respect to δ. Finally, a linear relationship between DMWD and SMAGGSTAB was established.
- Open Access
- 1 January 2018
- Published by Wiley in Vadose Zone Journal
- Vol. 17 (1) , 1-21
The Intensively Managed Landscape Critical Zone Observatory: A Scientific Testbed for Understanding Critical Zone Processes in Agroecosystems
Core Ideas: IML‐CZO is structured to study system responses through event‐based monitoring. Management legacy has shaped critical zone processes. Management and weather affect landscape heterogeneity and surface–subsurface pathways. In intensively managed landscapes, interactions between surface (tillage) and subsurface (tile drainage) management with prevailing climate/weather alter landscape characteristics, transport pathways, and transformation rates of surface/subsurface water, soil/sediment, and particulate/dissolved nutrients. To capture the high spatial and temporal variability of constituent transport and residence times in the critical zone (between the bedrock and canopy) of these altered landscapes, both storm event and continuous measurements are needed. The Intensively Managed Landscapes Critical Zone Observatory (IML‐CZO) is comprised of three highly characterized, well instrumented, and representative watersheds (i.e., Clear Creek, Iowa; Upper Sangamon River, Illinois; and Minnesota River, Minnesota). It is organized to quantify the heterogeneity in structure and dynamic response of critical zone processes to human activities in the context of the glacial and management (anthropogenic) legacies. Observations of water, sediment, and nutrients are made at nested points of the landscape in the vertical and lateral directions during and between storm events (i.e., continuously). The measurements and corresponding observational strategy are organized as follows. First, reference measurements from surface soil and deep core extractions, geophysical surveys, lidar, and hyperspectral data, which are common across all Critical Zone Observatories, are available. The reference measurements include continuous quantification of energy, water, solutes, and sediment fluxes. The reference measurements are complemented with event‐based measurements unique to IML‐CZO. These measurements include water table fluctuations, enrichment ratios, and roughness as well as bank erosion, hysteresis, sediment sources, and lake/floodplain sedimentation. The coupling of reference and event‐based measurements support testing of the central hypothesis (i.e., system shifts from transformer to transporter in IML‐CZO due to the interplay between management and weather/climate). Data collected since 2014 are available through a data repository and through the Geodashboard interface, which can be used for process‐based model simulations.
- 1 January 2018
- Published by Wiley in Vadose Zone Journal
- Vol. 17 (1) , 1-21
Open AccessThe Intensively Managed Landscape Critical Zone Observatory: A Scientific Testbed for Understanding Critical Zone Processes in Agroecosystems
Core Ideas: IML‐CZO is structured to study system responses through event‐based monitoring. Management legacy has shaped critical zone processes. Management and weather affect landscape heterogeneity and surface–subsurface pathways. In intensively managed landscapes, interactions between surface (tillage) and subsurface (tile drainage) management with prevailing climate/weather alter landscape characteristics, transport pathways, and transformation rates of surface/subsurface water, soil/sediment, and particulate/dissolved nutrients. To capture the high spatial and temporal variability of constituent transport and residence times in the critical zone (between the bedrock and canopy) of these altered landscapes, both storm event and continuous measurements are needed. The Intensively Managed Landscapes Critical Zone Observatory (IML‐CZO) is comprised of three highly characterized, well instrumented, and representative watersheds (i.e., Clear Creek, Iowa; Upper Sangamon River, Illinois; and Minnesota River, Minnesota). It is organized to quantify the heterogeneity in structure and dynamic response of critical zone processes to human activities in the context of the glacial and management (anthropogenic) legacies. Observations of water, sediment, and nutrients are made at nested points of the landscape in the vertical and lateral directions during and between storm events (i.e., continuously). The measurements and corresponding observational strategy are organized as follows. First, reference measurements from surface soil and deep core extractions, geophysical surveys, lidar, and hyperspectral data, which are common across all Critical Zone Observatories, are available. The reference measurements include continuous quantification of energy, water, solutes, and sediment fluxes. The reference measurements are complemented with event‐based measurements unique to IML‐CZO. These measurements include water table fluctuations, enrichment ratios, and roughness as well as bank erosion, hysteresis, sediment sources, and lake/floodplain sedimentation. The coupling of reference and event‐based measurements support testing of the central hypothesis (i.e., system shifts from transformer to transporter in IML‐CZO due to the interplay between management and weather/climate). Data collected since 2014 are available through a data repository and through the Geodashboard interface, which can be used for process‐based model simulations.