Qinghua Luan

Dr. Qinghua Luan

orcid

Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
5 June 2020 in Water Resources Management
Verified
Journal Article
Closed access
PDF file
LYLei Yan
Lei Yan
LXLihua Xiong
Lihua Xiong
QLQinghua Luan
Qinghua Luan
CJCong Jiang
Cong Jiang
YKYu kunxia
Yu kunxia
Chong-Yu XuChong-Yu Xu
Chong-Yu Xu

6 January 2017 in Water
Verified
Journal Article
Open access
PDF file
Weiwei SHAOWeiwei SHAO
Weiwei SHAO
JCJingya Cai
Jingya Cai
Jiahong LiuJiahong Liu
Jiahong Liu
QLQinghua Luan
Qinghua Luan
MXMao Xiaomin
Mao Xiaomin
JZJun Zhang
Jun Zhang
This study produced a drought map for the Fenhe River basin covering the period from 150 BC to 2012 using regional historical drought records. Based on meteorological and hydrological features, the characteristics and causes of water scarcity in the Fenhe River basin were examined, along with their impact on the national economy and ecological environment. The effects of water scarcity in the basin on the national economy were determined from agricultural, industrial, and domestic perspectives. The impact on aquatic ecosystems was ascertained through an evolution trend analysis of surface water systems, including rivers, wetlands, and slope ecosystems, and subterranean water systems, including groundwater and karst springs. As a result of these analyses, strategies are presented for coping with water scarcity in this basin, including engineering countermeasures, such as the construction of a water network in Shanxi, and the non-engineering approach of groundwater resource preservation. These comprehensive coping strategies are proposed with the aim of assisting the prevention and control of water scarcity in the arid and semi-arid areas of China.

XHXu Huan
Xu Huan
YWYing Wang
Ying Wang
Xiaoran FuXiaoran Fu
Xiaoran Fu
DWDong Wang
Dong Wang
QLQinghua Luan
Qinghua Luan
The frequency of urban storms has increased, influenced by the climate changing and urbanization, and the process of urban rainfall runoff has also changed, leading to severe urban waterlogging problems. Against this background, the risk of urban waterlogging was analyzed and assessed accurately, using an urban stormwater model as necessary. Most studies have used urban hydrological models to assess flood risk; however, due to limited flow pipeline data, the calibration and the validation of the models are difficult. This study applied the MIKE URBAN model to build a drainage system model in the Beijing Future Science City of China, where the discharge of pipelines was absent. Three methods, of empirical calibration, formula validation, and validation based on field investigation, were used to calibrate and validate the parameters of the model. After the empirical calibration, the relative error range between the simulated value and the measured value was verified by the formula as within 25%. The simulated runoff depth was consistent with a field survey verified by the method of validation based on field investigation, showing the model has good applicability in the study area. Then, the rainfall scenarios of different return periods were designed and simulated. Simulation results showed that, for the 10-year return period, there are overflow pipe sections in northern and southern regions, and the number of overflow pipe sections in the northern region is more than that in the southern region. For the 20-year return period and 50-year return period, the number of overflow pipe sections and nodes in the northern region increased, while for the 100-year return period, the number of overflow nodes both increased. With the increase in the rainfall return period, the pipe network load increased, the points and sections prone to accumulation and waterlogging increased, and the regional waterlogging risk increased. The southern region is prone to waterlogging because the pipeline network density is higher than that in the northern region and the terrain is low-lying. This study provides a reference for the establishment of rainwater drainage models in regions with similar database limitations and provides a technical reference for the calibration and validation of stormwater models that lack rainfall runoff data.

5 June 2018 in Proceedings of IAHS
Verified
Journal Article
Open access
PDF file
QLQinghua Luan
Qinghua Luan
KZKun Zhang
Kun Zhang
JLJiahong Liu
Jiahong Liu
DWDong Wang
Dong Wang
JMJun Ma
Jun Ma
Recently, the water disaster in cities especially in Chinese mountainous cities is more serious, due to the coupling influences of waterlogging and regional floods. It is necessary to study the surface runoff process of mountainous cities and examine the regional drainage pipeline network. In this study, the runoff processes of Lincheng county (located in Hebei province, China) in different scenarios were simulated through Mike Urban model. The results show that all of the runoff process of the old town and the new residential area with larger slope, is significant and full flow of these above zones exists in the part of the drainage pipeline network; and the overflow exists in part of the drainage pipeline network when the return period is ten years or twenty years, which illuminates that the waterlogging risk in this zone of Lincheng is higher. Therefore, remodeling drainage pipeline network in the old town of Lincheng and adding water storage ponds in the new residential areas were suggested. This research provides both technical support and decision-making reference to local storm flood management, also give the experiences for the study on the runoff process of similar cities.

1 July 2020 in Water Resources Management
Verified
Journal Article
Closed access
PDF file
LYLei Yan
Lei Yan
LXLihua Xiong
Lihua Xiong
QLQinghua Luan
Qinghua Luan
CJCong Jiang
Cong Jiang
YKYu kunxia
Yu kunxia
Chong-Yu XuChong-Yu Xu
Chong-Yu Xu

17 May 2018
Verified
Book Chapter
Closed access
PDF file
YWYing Wang
Ying Wang
QLQinghua Luan
Qinghua Luan
HWHaichao Wang
Haichao Wang
JLJiahong Liu
Jiahong Liu
JMJun Ma
Jun Ma