Assessing the impact of human interventions on floods and low flows in the Wei River Basin in China using the LISFLOOD model

Floods are extreme hydroclimatic events that threaten societies and ecosystems. The effects of these events are greatly influenced by the changes that humans have imposed on the environment. The LISFLOOD model is a physically based rainfall-runoff model that simulates the hydrological processes in a catchment. Using globally available land cover, soil, and vegetation as well as meteorological and geographical datasets as input, the LISFLOOD model has the potential to be applied worldwide, even for regions where data are lacking. This study first calibrated and validated the LISFLOOD model in the Wei River Basin in China (432,000 km2) for the years between 2000 and 2010 at 0.05° resolution with a monthly Nash-Sutcliffe model efficiency coefficient of 0.79 at the Huaxian station located at the catchment outlet. The outlets of 17 tributaries draining into the main river were then identified in order to assess the contribution of each tributary to the total runoff occurring as a result of flooding. Four categories of scenarios focusing on human interventions in the basin were created and evaluated: 1) Business as usual, 2) Additional reservoirs constructed in different catchments, 3) Land use as in 1980, and 4)Water diversion plan with a pipeline injection of a fixed daily inflow from an adjacent catchment. The results of the scenarios are presented for three strategically important cities located on the floodplain. In general, the construction of the reservoirs could have an effect on reducing peak flows and decreasing the flood return periods while increasing the low flows. The water diversion plan scenarios increased the low flow by 41 times averaged for the three cities. In conclusion, the LISFLOOD model is a sophisticated model for land and water management planning on the catchment scale for reducing the effects of flood and drought.

GAI Lingtong;  NUNES Joao;  BAARTMAN Jantiene;  ZHANG Hongming;  WANG Fei;  DE ROO Arie;  RITSEMA Coen J.;  GEISSEN Violette; 

2018-12-30

ELSEVIER SCIENCE BV

JRC114032

0048-9697 (online),   

https://www.sciencedirect.com/science/article/pii/S0048969718342797?via%3Dihub,    https://publications.jrc.ec.europa.eu/repository/handle/JRC114032,   

10.1016/j.scitotenv.2018.10.379 (online),