Tropical Geography


Storm and Flood Prediction and Progress in Parameter Synthesis Research in Small and Medium-Sized Watersheds

Lingling Zhao1,2(), Changming Liu2,3, Ziyin Wang1,4(), Xinhui Zhang1,4, Xing Yang5   

  1. 1.Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China
    2.Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    3.College of Water Sciences, Beijing Normal University, Beijing 100875, China
    4.College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, China
    5.Anhui Traffic Survey and Design Institute Co. LTD, Hefei 230000, China
  • Received:2023-02-13 Revised:2023-03-10 Online:2023-10-31
  • Contact: Ziyin Wang;


The prediction of rainstorms and floods in small and medium-sized watersheds, as well as the synthesis of related parameters, plays a pivotal role in preventing flood disasters. Environmental changes have led to an increase in hydrological extremes such as rainstorms and floods, presenting unprecedented challenges for small and medium-sized river basins. In this review, we systematically categorize, and summarize the processes involved in predicting rainstorms and floods in these watersheds, along with advancements in correlated parameter synthesis research. Furthermore, we analyze and discuss the most commonly employed runoff and confluence estimation methods and their associated parameters in practical applications, as well as their limitations. First, we establish the concept of small- and medium-sized watersheds across various academic disciplines. From a hydrological perspective, these watersheds typically exhibit slope confluence and have relatively small catchment areas. In terms of eco-hydrology, the ecological water demand of the basin must be calculated based on the different communities occupying the river basin and divided by area according to the ecological samples from each district after the investigation. Thereafter, we summarized the methods and types of runoff calculation and parameter synthesis in small- and medium-sized basins, and the methods and principles of runoff analysis, such as rainfall–runoff correlation diagram, infiltration curve method, deduction method, runoff coefficient method, and hydrological model method as well as the methods of parameter synthesis, such as rainfall-runoff correlation diagrams and loss methods are introduced. Second, we summarize and discuss the assessment of confluence and its associated parameters in small- and medium-sized river basins. This encompasses background information and various calculation methods, such as the instantaneous unit line, comprehensive unit line, inference formula method, and empirical formula method. We also examine how the three major elements of parameter synthesis convergence influence confluence parameters. We emphasize that combining radar rainfall measurements, high-resolution remote sensing, high-performance computing, and deep learning can facilitate research on simulating and forecasting rainstorms and flood processes in small- and medium-sized basins. However, a significant portion of these basins lacks data, limiting the application of simulation and flood forecasting. To address this, integration with geographical parameters specific to small- and medium-sized basins is necessary to enhance regional reliability and forecasting accuracy. Additionally, when applying deep learning to simulate basins with limited or no data, the significance of parameter synthesis becomes even more pronounced. Finally, we discuss the problems and challenges associated with storm flood calculations and parameter synthesis methods in small- and medium-sized basins and offer predictions regarding future research and technical developments. We recommend strengthening the use of emerging technologies for watershed runoff and runoff parameter calculations and advocate for their application in storm flood design.

Key words: rainstorms, floods, watershed runoff caculation, parameter synthesis, simulation forecast, small- and medium-sized watersheds

CLC Number: 

  • TV122+.1