Water Resources Carrying Capacity of Qingshui River Basin Based on System Dynamics Modeling

doi:10.11988/ckyyb.20231245

Abstract

Abstract:

This study selects the Qingshui River Basin, the largest first-order tributary of the Yellow River in Ningxia, as the research area. It comprehensively considers the co-development of water resources, socio-economic, and water environment subsystems in this basin. By applying the system dynamics method, we established a system dynamics model of the Qingshui River Basin using Vensim software and set up five different scenarios. Based on historical data from 2006 to 2020, we employed the entropy weighting-TOPSIS method to predict the dynamic changes in water resources carrying capacity under these five scenarios from 2021 to 2030 so as to identify the optimal solution for enhancing the basin’s water resources carrying capacity. Results indicate that the water resources carrying capacity of the Qingshui River Basin remains inferior under the status-quo continuation scenario. The economic-priority, agricultural-priority, and environmental-priority scenarios can only partially alleviate the pressures on socio-economic development, water resources supply and demand, and the water environment. In contrast, the comprehensive and coordinated scenario can comprehensively improve the evaluation indicators of water resources carrying capacity, meeting the requirements for promoting the basin’s sustainable development. This study offers a reference for water resources management and planning in the Qingshui River Basin.

Key words: water carrying capacity, water resource forecasting, system dynamics, entropy weight-TOPSIS method, Qingshui River basin

CLC Number:

TV213.4水利资源的管理、保护与改造

WU Jia-wei, LI Jin-yan, MA Zhan-cun. Water Resources Carrying Capacity of Qingshui River Basin Based on System Dynamics Modeling[J]. Journal of Changjiang River Scientific Research Institute, 2025, 42(4): 71-79.

Figures/Tables 14

Fig.1 Map of the Qingshui River Basin

Fig.2 Research roadmap

Fig.3 Flow chart of the water resource carrying capacity model

Table 1 Equations for main parameters of the SD model

用水总量/ (亿m³)	畜牧用水/ (亿m³)	水资源供水量/(亿m³)	第三产业增加值/(亿元)	第三产业用水量/(亿m³)	城镇人口数量/(万人)	农村人口数量/(万人)	农业灌溉用水量/(亿m³)	地区生产总值/(亿元)	人均 GDP/元
用水总量=生产用水量+生活用水量+生态环境用水量	畜牧用水=大牲蓄用水量+小牲蓄用水量	水资源供水量=地表水资源+地下水资源+污水处理回用	第三产业增加值=INGET(第三产业增长率,第三产业增加值初始值)	第三产业用水量=第三产业万元增加值用水量×第三产业增加值	城镇人口数量=总人口数量×城镇化率	农村人口数量=总人口数量—城镇人口数量	农业灌溉用水量=农业灌溉面积×农业灌溉用水定额	地区生产总值=第一产业增加值+第二产业增加值+第三产业增加值	人均GDP=地区生产总值/总人口数量

Table 2 Historical test data

年份	总人口数量/(万人)			地区生产总值/(亿元)
年份	Y_t	$Y ∧ t$	ARE		Y_t	$Y ∧ t$	ARE
2016	141.453	138.62	0.02		73.96	77.66	0.05
2017	143.182	141.75	0.01		77.77	79.33	0.02
2018	144.787	146.23	0.01		81.92	85.20	0.04
2019	146.393	149.32	0.02		86.57	84.84	0.02
2020	147.998	143.56	0.03		91.92	91.00	0.01
年份	农业灌溉面积/hm²			水资源供水量/(亿m³)
年份	Y_t	$Y ∧ t$	ARE		Y_t	$Y ∧ t$	ARE
2016	112 000	108 640	0.03		3.127	3.10	0.01
2017	116 480	119 973	0.03		3.610	3.65	0.01
2018	119 470	120 010	0.01		3.254	3.29	0.01
2019	126 200	124 930	0.01		3.131	3.29	0.05
2020	129 170	131 760	0.02		3.131	3.26	0.04

Table 2 Historical test data

年份	总人口数量/(万人)			地区生产总值/(亿元)
年份	Y_t	$Y ∧ t$	ARE		Y_t	$Y ∧ t$	ARE
2016	141.453	138.62	0.02		73.96	77.66	0.05
2017	143.182	141.75	0.01		77.77	79.33	0.02
2018	144.787	146.23	0.01		81.92	85.20	0.04
2019	146.393	149.32	0.02		86.57	84.84	0.02
2020	147.998	143.56	0.03		91.92	91.00	0.01
年份	农业灌溉面积/hm²			水资源供水量/(亿m³)
年份	Y_t	$Y ∧ t$	ARE		Y_t	$Y ∧ t$	ARE
2016	112 000	108 640	0.03		3.127	3.10	0.01
2017	116 480	119 973	0.03		3.610	3.65	0.01
2018	119 470	120 010	0.01		3.254	3.29	0.01
2019	126 200	124 930	0.01		3.131	3.29	0.05
2020	129 170	131 760	0.02		3.131	3.26	0.04

Table 3 Indicator system for comprehensive evaluation of water resources carrying capacity of the Qingshui River Basin

目标层	准则层	指标层	指标层符号	准则层权重/%	单位	指标层权重/%	反馈
水资源承载力评价指标体系	水资源	水资源供需比	A₁	33.848	%	7.421	+
		人均水资源量	A₂		m³	5.316	+
		人均用水量	A₃		m³	4.134	+
		农业用水效率	A₄		%	5.217	+
		工业用水效率	A₅		%	3.931	+
		水资源开发利用率	A₆		%	7.827	+
	社会经济	城镇化率	A₇	50.314	%	8.176	+
		人口密度	A₈		人/km²	9.590	-
		人均GDP	A₉		元	11.983	+
		地区生产总值	A₁₀		亿元	10.258	+
		第三产业增加值用水量	A₁₁		m³/万元	5.390	-
		第二产业增加值用水量	A₁₂		m³/万元	4.917	-
	水环境	城市绿地用水量	A₁₃	15.838	亿m³	3.795	-
		第二产业污水排放量	A₁₄		亿m³	5.823	-
		人均绿地面积	A₁₅		m³	2.572	+
		生活污水排放量	A₁₆		亿m³	3.648	-

Table 4 Rating of water carrying capacity

级别	差	较差	中等	良好	优秀
$c i$	[0,0.2]	(0.2,0.4]	(0.4,0.6]	(0.6,0.8]	(0.8,1.0]

Table 4 Rating of water carrying capacity

级别	差	较差	中等	良好	优秀
$c i$	[0,0.2]	(0.2,0.4]	(0.4,0.6]	(0.6,0.8]	(0.8,1.0]

Table 5 Settings of SD scenarios

模式	方案
现状延续型	该模式依据研究区现有发展速度和发展规划
经济优先型	根据研究区发展现状,突出社会经济发展的要求,将产业增长率上调3%、人口增长率、城镇化等参数上调2%,产业万元用水量增加10%
环境优先型	根据研究区发展现状,突出环境保护的重要性,将产业增长率、城镇化等参数下调2%,人口增长率下调1%、用水定额相应减少,污水回用量调整为现状延续模式的1.2倍
农业优先型	根据研究区域产业发展特点,突出发展流域主要产业,在现状延续模式基础上将第一产业增长率、农业灌溉率提高3%,城镇化率下调3%
综合协调型	在现状延续模式基础上,保证社会经济发展的同时,注重环境保护,对社会经济、水资源与水环境参数下调

Table 6 Parameters of scenarios

情景方案	人口增长率/%	第一产业增长率/%	第二产业增长率/%	第三产业增长率/%	污水回用量/(亿m³)	第二产业万元增加值用水量/(m³·(万元)^-1)	第三产业万元增加值用水量/(m³·(万元)^-1)	城镇化率/%
现状延续型	1.3	4.1	6.5	6.8	0.018	32.0	41.0	15.5
经济优先型	3.3	7.1	9.5	9.8	0.024	35.2	45.1	17.5
环境优先型	0.3	2.1	4.5	4.8	0.026	28.8	36.9	13.5
农业优先型	1.3	9.1	6.5	6.8	0.016	32.0	41.0	12.5
综合协调型	1.3	3.1	5.5	5.8	0.018	30.0	38.0	15.5

Fig.4 Total water demand

Fig.5 Ratio of water supply to demand

Fig.6 Gross Regional Product

Fig.7 GDP per capita

Fig.8 Water resources carrying capacity under different scenarios

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