Dynamic puddle delineation and modeling of puddle-to-puddle filling-spilling-merging-splitting overland flow processes

Chu, Xuefeng; Yang, Jun; Chi, Yaping; Zhang, Jianli

doi:10.1002/wrcr.20286

Cited by 90 publications

(109 citation statements)

References 17 publications

Supporting

Mentioning

108

Contrasting

Order By: Relevance

“…However, due to a series of complexities related to these depressions and their characteristics (e.g., hydrologic connectivity of depressions), hydrologic modeling for the PPR is a challenging task [2]. Different studies have been conducted to address the depression storage effects and simulate the characteristics of depression-dominated areas [3][4][5][6][7][8][9]. For example, Chu et al [6] developed a physically based hydrologic model which took the dynamic variations of puddles into account.…”

Section: Introductionmentioning

confidence: 99%

“…Different studies have been conducted to address the depression storage effects and simulate the characteristics of depression-dominated areas [3][4][5][6][7][8][9]. For example, Chu et al [6] developed a physically based hydrologic model which took the dynamic variations of puddles into account. The puddle-to-puddle (P2P) model incorporated the Puddle Delineation (PD) algorithm [5] to obtain detailed characteristics of depressions and simulate the real microtopography-controlled P2P overland flow, as well as infiltration and unsaturated flow [6].…”

Section: Introductionmentioning

confidence: 99%

“…For example, Chu et al [6] developed a physically based hydrologic model which took the dynamic variations of puddles into account. The puddle-to-puddle (P2P) model incorporated the Puddle Delineation (PD) algorithm [5] to obtain detailed characteristics of depressions and simulate the real microtopography-controlled P2P overland flow, as well as infiltration and unsaturated flow [6]. It provided all details on the cell to cell and puddle to puddle overland flow processes, puddle filling, spilling, merging, and splitting dynamics, spatial and temporal distributions of ponded water, variations in hydrologic connectivity, and discharges at basin outlets [6].…”

Section: Introductionmentioning

confidence: 99%

“…The puddle-to-puddle (P2P) model incorporated the Puddle Delineation (PD) algorithm [5] to obtain detailed characteristics of depressions and simulate the real microtopography-controlled P2P overland flow, as well as infiltration and unsaturated flow [6]. It provided all details on the cell to cell and puddle to puddle overland flow processes, puddle filling, spilling, merging, and splitting dynamics, spatial and temporal distributions of ponded water, variations in hydrologic connectivity, and discharges at basin outlets [6]. The P2P model has been tested for various laboratory and field surfaces, including a site in the PPR, which highlighted the significance of the dynamic P2P processes and threshold behavior of potholes [7,9].…”

Section: Introductionmentioning

confidence: 99%

“…The outputs from the PD can be incorporated into hydrologic models to account for the dynamic variations of puddles and their impacts on the hydrologic simulation [6]. It should be noted that PD is able to cope with special topographic features, such as flats (i.e., a set of adjacent grids with the same elevation) and multi-threshold depressions (i.e., depressions with two or more thresholds) [5,6]. Figure 1 illustrates the fundamental steps of the coupled PD-SWAT modeling system.…”

Section: Introduction To the Pd Algorithm: How To Consider Real Topogmentioning

confidence: 99%

See 4 more Smart Citations

SWAT Modeling for Depression-Dominated Areas: How Do Depressions Manipulate Hydrologic Modeling?

Nasab

Singh

Chu

2017

Water

Self Cite

View full text Add to dashboard Cite

Abstract:Modeling hydrologic processes for depression-dominated areas such as the North American Prairie Pothole Region is complex and reliant on a clear understanding of dynamic filling-spilling-merging-splitting processes of numerous depressions over the surface. Puddles are spatially distributed over a watershed and their sizes, storages, and interactions vary over time. However, most hydrologic models fail to account for these dynamic processes. Like other traditional methods, depressions are filled as a required preprocessing step in the Soil and Water Assessment Tool (SWAT). The objective of this study was to facilitate hydrologic modeling for depression-dominated areas by coupling SWAT with a Puddle Delineation (PD) algorithm. In the coupled PD-SWAT model, the PD algorithm was utilized to quantify topographic details, including the characteristics, distribution, and hierarchical relationships of depressions, which were incorporated into SWAT at the hydrologic response unit (HRU) scale. The new PD-SWAT model was tested for a large watershed in North Dakota under real precipitation events. In addition, hydrologic modeling of a small watershed was conducted under two extreme high and low synthetic precipitation conditions. In particular, the PD-SWAT was compared against the regular SWAT based on depressionless DEMs. The impact of depressions on the hydrologic modeling of the large and small watersheds was evaluated. The simulation results for the large watershed indicated that SWAT systematically overestimated the outlet discharge, which can be attributed to the failure to account for the hydrologic effects of depressions. It was found from the PD-SWAT modeling results that at the HRU scale surface runoff initiation was significantly delayed due to the threshold control of depressions. Under the high precipitation scenario, depressions increased the surface runoff peak. However, the low precipitation scenario could not fully fill depressions to reach the overflow thresholds in the selected sub-basins. These results suggest the importance of depressions as gatekeepers in watershed modeling.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introduction To the Pd Algorithm: How To Consider Real Topogmentioning

confidence: 99%

See 3 more Smart Citations

SWAT Modeling for Depression-Dominated Areas: How Do Depressions Manipulate Hydrologic Modeling?

Nasab

Singh

Chu

2017

Water

Self Cite

View full text Add to dashboard Cite

show abstract

Power law scaling of topographic depressions and their hydrologic connectivity

Kumar

2014

Geophysical Research Letters

View full text Add to dashboard Cite

Topographic depressions, areas of no lateral surface flow, are ubiquitous characteristics of the land surface that control many ecosystem and biogeochemical processes. High density of depressions increases the surface storage capacity, whereas lower depression density increases runoff, thus influencing soil moisture states, hydrologic connectivity, and the climate‐soil‐vegetation interactions. With the widespread availability of high‐resolution lidar‐based digital elevation model (lDEM) data, it is now possible to identify and characterize the structure of the spatial distribution of topographic depressions for incorporation in ecohydrologic and biogeochemical studies. Here we use lDEM data to document the prevalence and patterns of topographic depressions across five different landscapes in the United States and quantitatively characterize the probability distribution of attributes, such as surface area, storage volume, and the distance to the nearest neighbor. Through the use of a depression identification algorithm, we show that these probability distributions of attributes follow scaling laws indicative of a structure in which a large fraction of land surface areas can consist of high number of topographic depressions of all sizes and can account for 4 to 21 mm of depression storage. This implies that the impacts of small‐scale topographic depressions in the landscapes on the redistribution of material fluxes, evaporation, and hydrologic connectivity are quite significant.

show abstract

Are all runoff processes the same? Numerical experiments comparing a Darcy‐Richards solver to an overland flow‐based approach for subsurface storm runoff simulation

Ameli

Craig

McDonnell

2015

Water Resources Research

View full text Add to dashboard Cite

Hillslope runoff theory is based largely on the differentiation between infiltration excess overland flow, saturation excess overland flow, and subsurface stormflow. Here we explore to what extent a 2-D friction-based overland flow model is useful for predicting hillslope-scale subsurface stormflow, posited here as phenomenologically the same as infiltration excess at depth. We compare our results to a 3-D variably saturated Darcy-Richards subsurface solver for individual rainfall runoff events. We use field data from the well-studied Panola Mountain Experimental hillslope in Georgia USA. Our results show that the two models are largely indistinguishable in terms of their ability to simulate the hillslope hydrograph magnitude and timing for a range of slopes and rainfall depths. Furthermore, we find that the descriptive ability of the overland flow model is comparable to the variably saturated subsurface flow model in terms of its ability to represent the spatial distribution of subsurface stormflow and infiltration across the soil-bedrock interface. More importantly, these results imply that the physics of infiltration excess subsurface stormflow at the soilbedrock interface is similar to infiltration excess overland flow at the soil surface, in terms of detention storage, loss along the lower boundary, and threshold-like activation at the larger hillslope scale. Given the phenomenological similarity of overland flow and subsurface stormflow and the fact that overland flow model predictions are considerably faster to run (particularly as slope and rainfall depth increase), these findings imply that new forms of hillslope-scale subsurface storm runoff predictions may be possible with the knowledge of bedrock permeability and limited soil information. Finally, this work suggests that the role of soil mantle vis-a-vis subsurface stormflow is mainly as a filter that delays the development of patches of saturation along the bedrock surface. Our model results show that simple realizations of soil based on a few soil depth measurements can possibly be enough to characterize this filtering effect.Subsurface stormflow response to precipitation is also a threshold-like process [e.g., Peters et al., 2003;Tromp-van Meerveld and McDonnell, 2006b] that depends upon the microtopography, mesotopography, and macrotopography-not of the surface topography but the topography of the restricting layer at depth Key Points: Richards' and overland flow approaches similarly simulate subsurface stormflow Infiltration excess subsurface stormflow (SSF) can occur along the bedrock surface SSF and overland flow show similar behaviors in terms of the role of their lower boundaries Correspondence to: A. A. Ameli, aaameli@uwaterloo.ca Citation: Ameli, A. A., J. R. Craig, and J. J. McDonnell (2015), Are all runoff processes the same? Numerical experiments comparing a Darcy-Richards solver to an overland flowbased approach for subsurface storm runoff simulation, Water Resour. Water Resources Research PUBLICATIONS (e.g., soil-bedrock interface, soi...

show abstract

Dynamic puddle delineation and modeling of puddle-to-puddle filling-spilling-merging-splitting overland flow processes

Cited by 90 publications

References 17 publications

SWAT Modeling for Depression-Dominated Areas: How Do Depressions Manipulate Hydrologic Modeling?

SWAT Modeling for Depression-Dominated Areas: How Do Depressions Manipulate Hydrologic Modeling?

Power law scaling of topographic depressions and their hydrologic connectivity

Are all runoff processes the same? Numerical experiments comparing a Darcy‐Richards solver to an overland flow‐based approach for subsurface storm runoff simulation

Contact Info

Product

Resources

About