Seamless Integration of Rainfall Spatial Variability and a Conceptual Hydrological Model

Yan Zhou, Zhongmin Liang, Binquan Li, Yixin Huang, Kai Wang and Yiming Hu
Additional contact information
Yan Zhou: College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
Zhongmin Liang: College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
Binquan Li: College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
Yixin Huang: College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
Kai Wang: Bureau of Hydrology, The Huaihe River Commission of the Ministry of Water Resources, Bengbu 233001, China
Yiming Hu: College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China

Sustainability, 2021, vol. 13, issue 6, 1-16

Abstract: Rainfall is an important input to conceptual hydrological models, and its accuracy would have a considerable effect on that of the model simulations. However, traditional conceptual rainfall-runoff models commonly use catchment-average rainfall as inputs without recognizing its spatial variability. To solve this, a seamless integration framework that couples rainfall spatial variability with a conceptual rainfall-runoff model, named the statistical rainfall-runoff (SRR) model, is built in this study. In the SRR model, the exponential difference distribution (EDD) is proposed to describe the spatial variability of rainfall for traditional rain gauging stations. The EDD is then incorporated into the vertically mixed runoff (VMR) model to estimate the statistical runoff component. Then, the stochastic differential equation is adopted to deal with the flow routing under stochastic inflow. To test the performance, the SRR model is then calibrated and validated in a Chinese catchment. The results indicate that the EDD performs well in describing rainfall spatial variability, and that the SRR model is superior to the Xinanjiang model because it provides more accurate mean simulations. The seamless integration framework considering rainfall spatial variability can help build a more reasonable statistical rainfall-runoff model.

Keywords: rainfall spatial variability; statistical rainfall-runoff model; vertically mixed runoff model; stochastic differential equation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2071-1050/13/6/3588/pdf (application/pdf)
https://www.mdpi.com/2071-1050/13/6/3588/ (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:jsusta:v:13:y:2021:i:6:p:3588-:d:522916

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

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