The influences of sponge city construction on spring discharge in Jinan city of China

In recent years, intense human activities have threatened to dry up the well-known karst springs in Jinan, China. Sponge city construction program was one of the measures aiming to improve the recharge to groundwater and also protect sources of spring discharge. An influence study of sponge city construction on groundwater is necessary while not fully evaluated. In this paper, a threedimensional numerical groundwater flow model was developed to address this issue. Model calibration showed that the simulated groundwater level successfully reproduced the observed results. Then, 12 scenarios were established and predicted according to different precipitation conditions and the achieved degrees of sponge city construction. The results indicated that the sponge city construction was conducive to the rise of regional groundwater level after 20 years. However, the groundwater level around the spring groups would only increase by an average of 0.22 m, and the annual spring discharge would increase by approximately 9.00 million m after 20 years. Results revealed that the extent of spring discharge recovery was not evident in a short time frame. The proper positioning of sponge city construction was suggested to be considered further to balance the protection of springs with the issue of waterlogging. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/). doi: 10.2166/nh.2020.008 ://iwaponline.com/hr/article-pdf/doi/10.2166/nh.2020.008/697159/nh2020008.pdf Kangning Sun Litang Hu (corresponding author) College of Water Sciences, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, Beijing 100875, China and Engineering Research Center of Groundwater Pollution Control and Remediation of Ministry of Education, Beijing 100875, China E-mail: litanghu@bnu.edu.cn Xiaomeng Liu The Government of Beishicao Town Shunyi District, Beijing 101300, China


INTRODUCTION
The earliest two-dimensional groundwater flow model with one-year calibration was established in 1989 to explore the balance of groundwater supply and spring protection, and then over five groundwater flow models were progressively constructed (Wang et al. ). Two typical three-dimensional groundwater models were developed by Qian et al. () and Wang et al. (), aiming at estimation of the causes of groundwater level decline and the drying up of springs. These investigations and studies provide good references for our further analysis. To our knowledge, the influence of sponge city construction on groundwater flow has not been fully examined, especially the short-term and long-term influences of the project on groundwater level and spring discharge. The purpose of this study was to develop a numerical model to evaluate the influence of sponge city construction on the regional groundwater level

Geology and hydrogeology
As shown in Figure 1, the Archean Taishan Group (Art), consisting of metamorphic rocks, is distributed in the southern area and is the basement of the study area. The Cambrian (∈) strata is characterized by interbeds of limestone and shale, which are well exposed from south to north. The Ordovician (O) strata is composed of thickbedded limestone and mainly distributed in the middle of the study area. Most of the Carboniferous (C) and Permian (P) strata are buried and exposed only slightly in the northwest. The Quaternary (Q) strata is well exposed in the northern area. Several large faults are distributed throughout the study area in northwest and northeast directions.
The Dongwu Fault is impermeable in most areas, demonstrating weak permeability only in the northeastern part of the spring area; the Mashan Fault is impermeable in the southern mountainous area and permeable in the northern area. The Qianfoshan Fault is in the central part of the Jinan spring area and is impermeable in the south and permeable in the north. The remaining small faults are all permeable.
Pore water in a Quaternary aquifer and fractured-karst groundwater in an Ordovician aquifer are the main types of groundwater in the study area, which account for more than 80% of the total groundwater discharge, especially the karst aquifer, which is the major recharge resource for source. The karst groundwater in the study area is mainly discharged through groundwater exploitation, springs, and recharge of the Quaternary pore water, while the pore water is mainly discharged through evaporation, springs, and groundwater exploitation.

Groundwater utilization
Groundwater utilization can be classified into four stages

Equivalent porous media method
Flow in a fractured-karst aquifer is usually a non-Darcy flow.
Flow simulation in a fractured-karst medium is challenging.
According to the condition of whether physical processes The geology structure in the study area is complex, and the aquifer contains karst, fissures, and porous aquifers with different pore sizes, which are difficult to generalize with one another. In this study, a convenient and efficient equivalent medium simulation method was chosen, which is widely used at present in physically based models. In particular, when the main aquifer media are dissolution pores rather than caves and channels, this kind of model can be used to simulate water balances and trends of the regional groundwater flow (Scanlon et al. ). Therefore, this method could be employed in our study area. Likewise, it has been successfully applied in most of the karst aquifer systems in northern China (Kang et al. ).

Simulation program
This study chose a polygon grid finite difference groundwater modeling system (named PGMS) to establish a 3D groundwater flow numerical model. The PGMS was based on a polygonal grid, which was more convenient, flexible, and accessible and had more advantages than a rectangular grid. Moreover, the PGMS could deal well with problems associated with karst groundwater and karst springs, and it was applied in the Heihe River Basin ( and 'driver' files). The template file was a parameter control file that wrote the parameters in a separate file, and the model file generated by the PGMS needed this file to read the parameters automatically. The driver file contained all the adjustable parameters. The model parameter settings could be changed in this file, and the results of the model operation could also be processed.

Conceptual model
The Jinan spring catchment was selected as the model area.

Data preparation
The main data sources concerning groundwater level and spring discharge are listed in Table 1 and include topography, precipitation, hydrogeology, observation wells, spring discharge, and many research reports (Wang et al. ).
Sources and sinks were processed in this study. The main recharge sources included were infiltration from precipitation, rivers, and artificial recharge, and the return flow of irrigation water. The main rivers studied were the Yufu,

Model discretization and calibration
Model discretization and zonation of hydrogeological parameters The study area was divided into three layers, and each layer was divided into 6,488 auxiliary triangles for a total of 19,464 auxiliary triangles (Figure 4).  Table 2). The zonation of the three aquifers is presented in Figure 5, and the optimized parameters are listed in Table 2.

Comparison of observed and simulated groundwater level data
Calibration targets were calculated as the root mean square of the difference between the observed and simulated groundwater levels (Δh). There was a total of 17 observation wells (13 in the plains area and 4 in the mountainous area), and the observation data were collected from 2014 to 2016. The results (Table 3) indicated that the number of absolute errors between the simulated and observed values were less than 0.5 m, 1.0 m, and 3.0 m, which accounted for 27%, 47%, and 79%, respectively. The relative errors within 5%, 10%, and 20% accounted for 70%, 85%, and 94%, respectively.
The goodness-of-fit in the plains area was higher than that of the mountainous area. If the observation holes in the plains area were solely analyzed, the absolute errors were less than 0.5 m, 1.0 m, and 3.0 m, accounting for 33%, 58%, and 92%, respectively; the relative errors within 5%, 10%, and 20% accounted for 77%, 92%, and 95%, respectively. The fitting accuracy of the observation holes in the mountainous area was slightly poor, but the relative errors of the simulated value that were less than 20% also accounted for 91%, and more than half of them were less than 5%. Figure 6 shows the comparison between the simulated and observed groundwater levels (corresponding with observation wells a, b, c, d, e, and f in Figure 1). The results indicated that the prediction could adequately reflect the actual groundwater level.

Groundwater budget analysis
There were four springs in total, and observation data were  respectively, and the groundwater system was always in a

Construction of Jinan sponge city
The sponge city pilot was located in the southeast region of the study area with mountains to the south; the pilot was approximately 1.8 km north of the springs (Figure 7). The elevation of the pilot area ranged from 23 m to 460 m. In this area, the mountains and plains were merged, and the plains area (with its low permeability) was primarily utilized for development and construction. According to the construction and implementation plans for Jinan sponge city, the planning targets were to be set by each planning area, and when combined with our own research purposes, this area was divided into two zones. Zone a was the development and construction area with a sponge city construction target of runoff coefficient and annual runoff control rate of 0.7 and 75%, respectively. Zone b was the mountainous area with a sponge city construction target of runoff coefficient and annual runoff control rate of 0.4 and 85%, respectively. The total area of the pilot area was 39 km 2 , including 22 km 2 in Zone a and 17 km 2 in Zone b.

Scenarios set
The most direct effect of sponge city construction on groundwater was an increase in the infiltration capacity of the underlying surface; namely, the degree of sponge city construction could be represented by a precipitation infiltration coefficient. Twelve scenarios (S) were set, as shown in Table 4. Scenarios S0-S3 corresponded to the infiltration

Change in groundwater level around springs
We took observation well e as an example to demonstrate the influence of sponge city construction on the groundwater level near the spring groups. Under different precipitation conditions, the increment of the groundwater level from scenarios S1, S2, and S3 was compared to that of scenario S0 (Figure 9), and 240 data were collected for each scenario. Compared with scenario D-S0, where the maximum increment of the groundwater level was 0.09, 0.13, and 0.27 m, the average increment of the groundwater Dry year D-S0 D-S1 D-S2 D-S3 Normal year N-S0 N-S1 N-S2 N-S3 Wet year W-S0 W-S1 W-S2 W-S3

DISCUSSION
Based on our analysis, we found that sponge city construction, due to an increased precipitation infiltration capacity of the underlying surface, could affect the precipitation to recharge the local groundwater, which would be beneficial for the increment of the groundwater level in and around Therefore, an immediate response by the increment of spring discharge would not be observed in a short time frame.
In the Jinan spring area, the main groundwater recharge source was from the southern region where the Cambrian and Ordovician limestones were exposed over a large area topographic slope when rainstorms occur, the runoff would not be able to be intercepted in time, which would result in urban waterlogging; therefore, how to balance the protection of the springs with the issue of waterlogging will be a question worthy of further consideration. The results from the 12 scenarios showed that the larger the infiltration capacity of the sponge city pilot area, the more the groundwater level and spring discharge rose.

CONCLUSIONS
Additionally, the more precipitation that fell, the more the uplift of the groundwater level occurred. Sponge city con- The increased maximum annual spring discharge after 20 years could account for approximately 5% of the simulated average annual spring discharge. It was not possible for water managers to observe an immediate response of the groundwater level and spring discharge in a short time frame after the implementation of the project.
To increase spring discharge after the implementation of sponge city construction in Jinan, one method would be to further expand the pilot area, which would incur further expenses; the other method, to increase spring discharge, would be to move the pilot area to the southern region, which would probably enhance the recharge sources of the groundwater system. Jinan has a waterlogging issue due to its short distance from the recharge zone to the discharge zone. The combined influence of waterlogging and sponge city construction on the groundwater level was present and not discussed in this article; however, the proper positioning of a sponge city pilot area could depend on properly balancing the protection of springs with the issue of waterlogging.