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Integrating Geographical Data Scienc...

Zhang, Han.

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Integrating Geographical Data Science with Soil Erosion Modeling to Support Soil Conservation and Environmental Sustainability: A Hybrid Geo-Spatial Approach.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Integrating Geographical Data Science with Soil Erosion Modeling to Support Soil Conservation and Environmental Sustainability: A Hybrid Geo-Spatial Approach./
作者:	Zhang, Han.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2023,
面頁冊數:	183 p.
附註:	Source: Dissertations Abstracts International, Volume: 84-12, Section: B.
Contained By:	Dissertations Abstracts International84-12B.
標題:	Soil sciences. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30425528
ISBN:	9798379735067

Integrating Geographical Data Science with Soil Erosion Modeling to Support Soil Conservation and Environmental Sustainability: A Hybrid Geo-Spatial Approach.
Zhang, Han.

Integrating Geographical Data Science with Soil Erosion Modeling to Support Soil Conservation and Environmental Sustainability: A Hybrid Geo-Spatial Approach. - Ann Arbor : ProQuest Dissertations & Theses, 2023 - 183 p.

Source: Dissertations Abstracts International, Volume: 84-12, Section: B.

Thesis (Ph.D.)--State University of New York at Buffalo, 2023.

This item must not be sold to any third party vendors.

Many challenges remain in attaining the goal of accurately predicting sediment production measured at the outlet of a watershed, as well as accurately estimating soil redistribution within a watershed. Despite the large number of model applications and parameterization studies, questions remain unanswered about how the simulation outcomes determine the design of the steps to parameterize the model and how to temporally and spatially distribute the assessment of the outcomes. Detailed analysis of soil erosion using fine-resolution data at the watershed scale is also needed due to its difficulties in representing soil erosion with high accuracy and the lack of measurement data. This study aims to establish a baseline for long-term process-based soil erosion modeling of event-based runoff and sediment yields and spatially explicit, pixel-based soil redistribution within subwatersheds in the USDA-Agricultural Research Service Walnut Gulch Experimental Watershed surrounding Tombstone, Arizona. This study also develops a method to precisely extract soil stoniness and vegetation using advanced data science techniques and geospatial technology. The objectives of the study are: 1) establish the baseline for soil erosion modelling in a set of six, nested small watersheds with long-term measurements of runoff and sediment yield at watershed outlets; 2) extend the baseline to include validation of the spatially distributed soil loss and sediment deposition rates based on previously reported 137CS measurements within the watersheds; 3) develop and validate a new-generation open-source geo-spatial interface for the Water Erosion Prediction Project (QGeoWEPP) to integrate the GIS and process-based soilerosion model with maximized flexibility; 4) identify the spatial distribution of soil stoniness and vegetation cover from UAV images using a method that incorporates DEMs and a CNN algorithm; and 5) analyze the importance of representing the spatial variability of soil stoniness and vegetation cover within the watershed on simulated soil redistribution using QGeoWEPP.

ISBN: 9798379735067Subjects--Topical Terms:

2122699
Soil sciences.
Subjects--Index Terms:

Data science

Integrating Geographical Data Science with Soil Erosion Modeling to Support Soil Conservation and Environmental Sustainability: A Hybrid Geo-Spatial Approach.
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520 $a Many challenges remain in attaining the goal of accurately predicting sediment production measured at the outlet of a watershed, as well as accurately estimating soil redistribution within a watershed. Despite the large number of model applications and parameterization studies, questions remain unanswered about how the simulation outcomes determine the design of the steps to parameterize the model and how to temporally and spatially distribute the assessment of the outcomes. Detailed analysis of soil erosion using fine-resolution data at the watershed scale is also needed due to its difficulties in representing soil erosion with high accuracy and the lack of measurement data. This study aims to establish a baseline for long-term process-based soil erosion modeling of event-based runoff and sediment yields and spatially explicit, pixel-based soil redistribution within subwatersheds in the USDA-Agricultural Research Service Walnut Gulch Experimental Watershed surrounding Tombstone, Arizona. This study also develops a method to precisely extract soil stoniness and vegetation using advanced data science techniques and geospatial technology. The objectives of the study are: 1) establish the baseline for soil erosion modelling in a set of six, nested small watersheds with long-term measurements of runoff and sediment yield at watershed outlets; 2) extend the baseline to include validation of the spatially distributed soil loss and sediment deposition rates based on previously reported 137CS measurements within the watersheds; 3) develop and validate a new-generation open-source geo-spatial interface for the Water Erosion Prediction Project (QGeoWEPP) to integrate the GIS and process-based soilerosion model with maximized flexibility; 4) identify the spatial distribution of soil stoniness and vegetation cover from UAV images using a method that incorporates DEMs and a CNN algorithm; and 5) analyze the importance of representing the spatial variability of soil stoniness and vegetation cover within the watershed on simulated soil redistribution using QGeoWEPP.
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