Variations in the streamflow of the Nierji Reservoir Basin and quantification of the influencing factors

Abstract

ABSTRACT Nierji Reservoir is the largest and most important water conservancy project in the Nenjiang River Basin. A thorough understanding of variations in streamflow and the driving factors of the Nierji Reservoir Basin (NERB) is crucial, but there are still gaps. In this paper, the annual streamflow data of Nierji Reservoir from 1898 to 2013 were applied to detect changing trends and abrupt changes using the Mann–Kendall method. Additionally, a Back Propagation–Artificial Neural Network (BP-ANN) model was developed to explore the relationships between the streamflow and its influencing factors and further quantify the relative contribution of each factor to the streamflow change. The results revealed that the annual streamflow of NERB significantly increased from 1898 to 2013 but declined during 1988–2013. Human activities were found to be the primary driver of streamflow decrease during 1988–2013 (nearly 75% of the total change). GDP had the largest influence, contributing 32% to the overall variation. Forest area, precipitation, and cultivated area had contributions of 25%, 23%, and 18%, respectively. Temperature had the least impact, with a relative contribution of 2%. This study provides valuable insights into water resources management in the Nenjiang River Basin, benefiting both agriculture and ecology.