Evaluation And Optimal Allocation Of Water Resources Carrying Capacity In Harbin City

Water is a necessary natural resource for human life,as well as the basic material basis for urban construction,economic development and life health.But with the continuous study of the quality of life and the acceleration of the urbanization process,the increased demand for water and the total amount of water available in nature is not infinite,which brings about the problem of the contradiction between water supply and demand.Therefore,strategies for healthy and sustainable development of water resources and rational planning of water use must be maintained.The year of this article is the current situation of the level of 2018.According to the relevant requirements,the city of Harbin will implement water-saving action in the total control planning of annual water supply in the short-term and long-term 14five-year plans,combined with the planning goal of Harbin city to build energy-saving urban water supply plan.2025 and 2035 were selected as the horizontal planning and budget years for supply and demand in the study area.Under the premise of obtaining different guarantee rate,the water shortage degree of different industrial sectors in Harbin city.Based on the water supply prediction and multi-objective genetic algorithm,the optimal allocation of available water resources in the near and long term planning years of Harbin city is made.Here are the results:(1)From Harbin city rise,related land use,land use rainwater collection data,establish an exclusive spatial attribute data according to the flow of convergence area"characteristics and other factors,detailed analysis of the research subdivision of the research scope,it can be seen that the response of 869,22 regional hydrological watershed distributed hydrological model research,in addition,The SUFI-2 algorithm of SWAT-cup is used to verify the calibration of the model parameters which have great influence on the simulation results,so as to improve the simulation results and improve the reliability of the model.Finally,the validation results of 0.65