Crop conversion impacts on runoff and sediment loads in the Upper Sunflower River watershed

Momm, Henrique G.; Porter, Wesley; Yasarer, Lindsey; Elkadiri, R.; Bingner, R. L.; Aber, Jd

doi:10.1016/j.agwat.2019.03.012

Cited by 9 publications

(3 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The AnnAGNPS model was designed to assist decision-makers in identifying sources of pollutants, selection and spatial location of conservation practices, and quantifying the integrated effect of these in time and space. Detailed descriptions of the AnnAGNPS model's general structure, watershed characterization requirements, key modules for daily water balance and sediment and nutrients erosion and transportation calculations have been provided in previous studies [26][27][28][29][30][31] and therefore, only a summary description of key components pertinent to this study is included.…”

Section: Description Of the Annagnps Watershed Pollution Modelmentioning

confidence: 99%

See 1 more Smart Citation

Integrated Technology for Evaluation and Assessment of Multi-Scale Hydrological Systems in Managing Nonpoint Source Pollution

Momm

Bingner

Wells

et al. 2021

Water

Self Cite

View full text Add to dashboard Cite

Conservation agencies need information to guide planning activities and allocation of limited mitigation resources at regional scales. Utilization of hydrological modeling tools at sub-watershed scales can adequately represent existing conditions, but information on a few discrete uncoordinated efforts cannot be scaled up to the entire region. Conversely, large scale modeling studies suffer from overgeneralization caused by needed lumping of information. In this study, a multiscale and standardized procedure was sought to characterize water and nonpoint source pollution spatiotemporal dynamics at basin-scale but through detailed field-scale analysis. The AnnAGNPS watershed pollution model was enhanced with new capabilities for simulation of large areas based on an Integrated Technology for Evaluation and Assessment of Multi-scale-hydrological Systems (ITEAMS) approach. Comparisons between the standard and proposed ITEAMS approach indicated no difference in streamflow and small underestimation of suspended sediments during high intensity rainfall events. The ITEAMS approach was applied to a basin with a total area of 3,268,691 ha which was discretized into 469,628 sub-catchments with an average size of 6.8 ha. The resulting 366 linked AnnAGNPS simulations were executed hierarchically generating estimates of water and suspended sediment yield and loads. This pilot study revealed the ITEAMS approach is a viable alternative for modeling and simulating large areas but at high spatiotemporal resolution.

show abstract

Section: Description Of the Annagnps Watershed Pollution Modelmentioning

confidence: 99%

“…Typical farming practices include management schedules as a temporal series of in-field operations. Each farm management schedule contains a continuous sequence of activities from all years considered in the simulation [27].…”

Section: Land Use/land Cover and Farming Management Databasementioning

confidence: 99%

Integrated Technology for Evaluation and Assessment of Multi-Scale Hydrological Systems in Managing Nonpoint Source Pollution

Momm

Bingner

Wells

et al. 2021

Water

Self Cite

View full text Add to dashboard Cite

show abstract

“…These datasets support government agencies, private sector organizations, scientists, educators, and others seeking an improved understanding of cropland spatiotemporal variations and make informed decisions on farming and conservation practices [2,3]. Applications include, but are not limited to, crop yield estimation and prediction [1], natural hazard (e.g., floods and droughts) impact assessment on agricultural commodities [4][5][6], and nonpoint source pollution quantification and mitigation [5,6]. For the latter, hydrological watershed models, in particular the annualized agricultural non-point source (AnnAGNPS) [7,8] and the Soil and Water Assessment Tool (SWAT) [9,10], rely heavily on spatiotemporal crop type information to characterize agricultural watershed and best represent existing conditions of land use and farming practices.…”

Section: Introductionmentioning

confidence: 96%

Crop-Type Classification for Long-Term Modeling: An Integrated Remote Sensing and Machine Learning Approach

2020

View full text Add to dashboard Cite

Long-term temporal and spatial information of crop type supports a wide range of applications including hydrological and climatological studies. In the U.S., yearly crop data layers (CDLs) are available starting in the early 2000s and have been developed using combined field information and sets of temporal imagery from multiple sensors. Development of long-term crop-type layers similar to CDLs is restricted by reduced accessibility to imagery and the necessary auxiliary datasets. In this study, a procedure to generate a historical crop type was developed and evaluated. Time series of Normalized Difference Vegetation Index (NDVI) datasets from Landsat 5 TM sensor for the Lower Bear Creek watershed were collected and processed. Object-based pseudo phenology curves, represented by the NDVI time series, were generated using noise filtering and dimensionality standardization procedures for the years 1985, 1990, 1995, 2000, and 2005. Classifiers were developed and evaluated using random-forest machine learning algorithms and CDL datasets as the reference. Increased generalization performance was obtained when the model was developed using multi-year datasets. This can be attributed to improved crop type representation during the training phase coupled with characterization of yearly variations due to natural (weather) and anthropogenic factors (farming management). Source of uncertainties were the presence of multiple crops within objects, phenological similarities between soybean and corn/maize, and the accuracy of CDL itself. The proposed procedure supports the development of historic crop types for long-term studies at the field scale in agricultural watersheds.

show abstract

Evaluation of Agricultural Non-point Source Pollution: a Review

Luo,

Liu,

Legesse

et al. 2023

Water Air Soil Pollut

View full text Add to dashboard Cite

Crop conversion impacts on runoff and sediment loads in the Upper Sunflower River watershed

Cited by 9 publications

References 34 publications

Integrated Technology for Evaluation and Assessment of Multi-Scale Hydrological Systems in Managing Nonpoint Source Pollution

Integrated Technology for Evaluation and Assessment of Multi-Scale Hydrological Systems in Managing Nonpoint Source Pollution

Crop-Type Classification for Long-Term Modeling: An Integrated Remote Sensing and Machine Learning Approach

Evaluation of Agricultural Non-point Source Pollution: a Review

Contact Info

Product

Resources

About