Impacts of Land Use Types, Soil Properties, and Topography on Baseflow Recharge and Prediction in an Agricultural Watershed

Chong Wei, Xiaohua Dong (), Yaoming Ma (), Wenyi Zhao, Dan Yu, Muhammad Tayyab and Huijuan Bo
Additional contact information
Chong Wei: College of Hydraulic & Environmental Engineering, China Three Gorges University, Yichang 443002, China
Xiaohua Dong: College of Hydraulic & Environmental Engineering, China Three Gorges University, Yichang 443002, China
Yaoming Ma: Land-Atmosphere Interaction and Its Climatic Effects Group, State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
Wenyi Zhao: College of Hydraulic & Environmental Engineering, China Three Gorges University, Yichang 443002, China
Dan Yu: College of Hydraulic & Environmental Engineering, China Three Gorges University, Yichang 443002, China
Muhammad Tayyab: College of Hydraulic & Environmental Engineering, China Three Gorges University, Yichang 443002, China
Huijuan Bo: College of Hydraulic & Environmental Engineering, China Three Gorges University, Yichang 443002, China

Land, 2022, vol. 12, issue 1, 1-20

Abstract: Baseflow is an essential component of runoff, which is the dominant water resource for the dry season. To better manage water resources, it is vital to investigate the links between the multiple influencing factors and the baseflow for better prediction in light of global changes. Previous studies have seldom separated these influencing factors in the analysis, making it difficult to determine their effect on the baseflow. In this study, based on the analysis datasets generated by the Soil and Water Assessment Tool (SWAT) model, the control single variables, correlation analysis, and multiple linear regression (MRL) methods were firstly combined to analyze the influences of the chosen factors (land use, topography, and soil type) on the baseflow. The findings revealed that the ability of precipitation to replenish the baseflow was better in areas with a higher slope. The ability of precipitation to recharge the baseflow for different land uses was ranked as “forest land > grass land > agricultural land > urban land”; land use factors should be added to the baseflow prediction equation. The hydrological group is the main property of soil affecting the baseflow recharge. A regression model established using publicly acquired remote sensing data had a good performance (R 2 = 0.84) on baseflow prediction on an annual scale. As a result of this information, relevant government officials and environmentalists may better manage water supplies in drought years. In addition, this regression model frame has the potential to be used for a baseflow inquiry inside an ungauged zone for a better ecological assessment.

Keywords: baseflow; land use; soil property; SWAT model; control variable method; MRL analysis (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2073-445X/12/1/109/pdf (application/pdf)
https://www.mdpi.com/2073-445X/12/1/109/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:12:y:2022:i:1:p:109-:d:1019235

Access Statistics for this article

Land is currently edited by Ms. Carol Ma

More articles in Land from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().