Study on Applicability of Conceptual Hydrological Models for Flood Forecasting in Humid, Semi-Humid Semi-Arid and Arid Basins in China

Abstract

Flood simulation and forecasting in various types of watersheds is a hot issue in hydrology. Conceptual hydrological models have been widely applied to flood forecasting for decades. With the development of economy, modern China faces with severe flood disasters in all types of watersheds include humid, semi-humid semi-arid and arid watersheds. However, conceptual model-based flood forecasting in semi-humid semi-arid and arid regions is still challenging. To investigate the applicability of conceptual hydrological models for flood forecasting in the above mentioned regions, three typical conceptual models, include Xinanjiang (XAJ), mix runoff generation (MIX) and northern Shannxi (NS), are applied to 3 humid, 3 semi-humid semi-arid, and 3 arid watersheds. The rainfall-runoff data of the 9 watersheds are analyzed based on statistical analysis and information theory, and the model performances are compared and analyzed based on boxplots and scatter plots. It is observed the complexity of drier watershed data is higher than that of the wetter watersheds. This indicates the flood forecasting is harder in drier watersheds. Simulation results indicate all models perform satisfactorily in humid watersheds and only NS model is applicable in arid watersheds. Model with consideration of saturation excess runoff generation (XAJ and MIX) perform better than the infiltration excess-based NS model in semi-humid semi-arid watersheds. It is concluded more accurate mix runoff generation theory, more stable and efficient numerical solution of infiltration equation and rainfall data with higher spatial-temporal resolution are main obstacles for conceptual model-based flood simulation and forecasting.

Estimating dominant runoff modes across the conterminous United States

“…This requires users to make a priori assumptions regarding the dominant runoff generating mechanism—often with little guidance. The importance of applying a valid runoff generating mechanism is underscored by the findings of numerous studies that show incorrect application of IE‐based hydrologic, and water quality models in VSA dominated regions can lead to substantial errors in streamflow predictions, nutrient, and sediment transport and incorrect identification of runoff generating zones and critical source areas (Easton et al, ; Kan et al, ; Lyon, McHale, Walter, & Steenhuis, ; Schneiderman et al, ; Valeo & Moin, ).…”

“…Such (Easton et al, 2008), (c) denitrification zones (Anderson, Groffman, & Walter, 2015), (d) non-point source pollution hotspots for precision agriculture (Buchanan et al, 2013), and (e) areas of high wetland potential (Horvath, Christensen, Mehaffey, & Neale, 2017 to make a priori assumptions regarding the dominant runoff generating mechanism-often with little guidance. The importance of applying a valid runoff generating mechanism is underscored by the findings of numerous studies that show incorrect application of IE-based hydrologic, and water quality models in VSA dominated regions can lead to substantial errors in streamflow predictions, nutrient, and sediment transport and incorrect identification of runoff generating zones and critical source areas (Easton et al, 2008;Kan et al, 2017;Lyon, McHale, Walter, & Steenhuis, 2006;Schneiderman et al, 2007;Valeo & Moin, 2001). as intensified precipitation can be evaluated in future studies to quantify trends in runoff generating mechanisms that can impact pollution transport, flood risk, and denitrification potential.…”

Applicability of ε-Support Vector Machine and Artificial Neural Network for Flood Forecasting in Humid, Semi-Humid and Semi-Arid Basins in China

“…China has invested much time studying rainfall-runoff since the early 1960s [6]. Many years ago, hydrologists focused on developing flood forecasting models for humid areas in the southern part of the Yangtze River, China, because of frequent severe flood events [7]. Further developments due to climate change and an increase in the economy contributed to an increase in runoff.…”

“…Further developments due to climate change and an increase in the economy contributed to an increase in runoff. There are increasingly urgent demands for flood forecasting in semi-arid and arid areas, and these have become a severe issue in water science, since flood forecasting is entirely different from that of humid areas [7]. Modeling hydrologic processes of semi-arid and arid basins is challenging due to the specific characteristics of these basins [8].…”

“…Modeling hydrologic processes of semi-arid and arid basins is challenging due to the specific characteristics of these basins [8]. There is a variability of runoff that sub-basins bring about both in space and time, resulting in a highly complicated rainfall-runoff relationship, and there are also lapses in storage excess runoff generation mechanisms [7,8]. Furthermore, in arid and semi-arid areas, few models are considered adequate due to the difficulty in effectively modeling infiltration-excess runoff processes as the dominant generation mechanism [9,10].…”