WEPPcloud: An online watershed-scale hydrologic modeling tool. Part II. Model performance assessment and applications to forest management and wildfires

Dobre, Mariana; Srivastava, Anurag; Lew, Roger; Deval, Chinmay; Brooks, Erin S.; Elliot, William J.; Robichaud, Peter R.

doi:10.1016/j.jhydrol.2022.127776

Cited by 18 publications

(11 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The hydrologic simulations were performed with the WEPPcloud interface [ 7 , 8 ] for 28 relatively undisturbed watersheds in the U.S. Pacific Northwest (Lake Tahoe basin, CA/NV; Bull Run Watershed, OR; Cedar River and Taylor Creek, WA, and two watersheds in Mica Creek Experimental Watershed, ID) and compared model outputs such as streamflow, sediment and phosphorus yield to observed data recorded at USGS gaging stations and recorded with flumes ( Table 1 ; [1] ). Each model run (including data input and output) can be viewed either online by accessing the web links in Table 1 or by accessing the zipped folders stored in the HydroShare repository.…”

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

“…10 ). Goodness-of-fit statistics (Nash-Sutcliffe Efficiency, the Kling-Gupta efficiency, and percent bias) and additional graphs can be found in [1] .…”

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

“…In the Lake Tahoe Basin, we were interested in applying the WEPPcloud interface to all 63 watersheds that flow into the lake and further run the models for disturbed conditions (thinning, prescribed fire, wildfire, simulated fire) [ 1 , 2 ], however, the model calibration was performed only for 17 watersheds with long-term USGS data. Therefore, we manually distributed the calibrating parameters to the remaining watersheds based on the watersheds' similarities, parent material, and proximity ( Fig.…”

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

“…Part II. Model performance assessment and applications to forest management and wildfires [1] and are also part of an additional study on the impacts of future forest management options on water quality in the Lake Tahoe basin, California/Nevada [2] . Fig.…”

Section: Data Descriptionmentioning

confidence: 99%

See 3 more Smart Citations

WEPPcloud hydrologic and erosion simulation datasets from 28 watersheds in US Pacific Northwest and calibrating model parameters for undisturbed and disturbed forest management conditions

et al. 2022

Self Cite

View full text Add to dashboard Cite

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

“…10 ). Goodness-of-fit statistics (Nash-Sutcliffe Efficiency, the Kling-Gupta efficiency, and percent bias) and additional graphs can be found in [1] .…”

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

Section: Data Descriptionmentioning

confidence: 99%

See 2 more Smart Citations

WEPPcloud hydrologic and erosion simulation datasets from 28 watersheds in US Pacific Northwest and calibrating model parameters for undisturbed and disturbed forest management conditions

et al. 2022

Self Cite

View full text Add to dashboard Cite

“…A part of the soil components of RRED were incorporated into the online USDA Forest Service WEPP interfaces. The online tools allow for even easier modeling access (Robichaud et al, 2019;Lew et al, 2022;Dobre et al, 2022; https://wepp1.nkn.uidaho.edu/weppcloud/). Efforts are ongoing to improve both accessibility and accuracy of post-fire models and datasets used to assess risks from post-fire flooding and erosion.…”

Section: Property Valuesmentioning

confidence: 99%

Socio-Economic Impact of the Rapid Response Erosion Database (RRED)

Miller¹,

Breffle²,

Battaglia³

et al. 2022

GEP

View full text Add to dashboard Cite

Rapid response is critical following natural disasters like wildfire. Fire, runoff, and erosion risks are highly heterogeneous in space, creating an urgent need for rapid, spatially-explicit assessment. In the past, data preparation has been time consuming and expensive, resulting in extensive losses in values-at-risk (VARs). The Rapid Response Erosion Database (RRED, http://rred.mtri.org/rred/) allows researchers and land managers to access properly-formatted spatial model inputs for the Water Erosion Prediction Project (WEPP) anywhere within the continental US and eventually beyond. Comprehensive support for post-fire hydrological modeling is provided by allowing users to upload spatial soil burn severity maps, and within moments download spatial model inputs. The database has been used to help assess and plan remediation on more than a dozen wildfires in the Western U.S. RRED has already saved $694,000 between May 2016-December 2018 in administrative costs. In the future, the potential to save time and money on data preparation can extend beyond wildfire to include tracking contaminated sediments, agricultural pollution, and construction site erosion. RRED may also be a useful tool to protect VARs as illustrated by our analysis of recreation, property values, and clean drinking water.

show abstract

Opportunities and challenges for precipitation forcing data in post‐wildfire hydrologic modeling applications

Partridge,

Johnson,

Sleeter

et al. 2024

WIREs Water

View full text Add to dashboard Cite

The frequency and extent of wildfires have increased in recent decades with immediate and cascading effects on water availability in many regions of the world. Precipitation is used as primary input to hydrologic models and is a critical driver of post‐wildfire hydrologic hazards including debris flows, flash floods, water‐quality effects, and reservoir sedimentation. These models are valuable tools for understanding the hydrologic response to wildfire but require accurate precipitation data at suitable spatial and temporal resolutions. Wildfires often occur in data‐sparse, headwater catchments in complex terrain, and post‐wildfire hydrologic effects are particularly sensitive to high‐intensity, short‐duration precipitation events, which are highly variable and difficult to measure or estimate. Therefore, the assessment and prediction of wildfire‐induced changes to watershed hydrology, including the associated effects on ecosystems and communities, are complicated by uncertainty in precipitation data. When direct measurements of precipitation are not available, datasets of indirect measurements or estimates are often used. Choosing the most appropriate precipitation dataset can be difficult as different datasets have unique trade‐offs in terms of spatial and temporal accuracy, resolution, and completeness. Here, we outline the challenges and opportunities associated with different precipitation datasets as they apply to post‐wildfire hydrologic models and modeling objectives. We highlight the need for expanded precipitation gage deployment in wildfire‐prone areas and discuss potential opportunities for future research and the integration of precipitation data from disparate sources into a common hydrologic modeling framework.This article is categorized under: Science of Water > Hydrological Processes Science of Water > Methods Science of Water > Water and Environmental Change

show abstract

WEPPcloud: An online watershed-scale hydrologic modeling tool. Part II. Model performance assessment and applications to forest management and wildfires

Cited by 18 publications

References 54 publications

WEPPcloud hydrologic and erosion simulation datasets from 28 watersheds in US Pacific Northwest and calibrating model parameters for undisturbed and disturbed forest management conditions

WEPPcloud hydrologic and erosion simulation datasets from 28 watersheds in US Pacific Northwest and calibrating model parameters for undisturbed and disturbed forest management conditions

Socio-Economic Impact of the Rapid Response Erosion Database (RRED)

Opportunities and challenges for precipitation forcing data in post‐wildfire hydrologic modeling applications

Contact Info

Product

Resources

About