Modeling surface water-groundwater interaction in arid and semi-arid regions with intensive agriculture

doi:10.1016/j.envsoft.2014.10.011

Environmental Modelling & Software

Volume 63, January 2015, Pages 170-184

https://doi.org/10.1016/j.envsoft.2014.10.011 Get rights and content

Highlights

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Integrated surface water-groundwater modeling coupled with hydraulic simulation.
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A systematic view on how agricultural water use would impact the water cycle.
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Insights from the modeling into data collection, model improvement and management.

Abstract

In semi-arid and arid areas with intensive agriculture, surface water-groundwater (SW-GW) interaction and agricultural water use are two critical and closely interrelated hydrological processes. However, the impact of agricultural water use on the hydrologic cycle has been rarely explored by integrated SW-GW modeling, especially in large basins. This study coupled the Storm Water Management Model (SWMM), which is able to simulate highly engineered flow systems, with the Coupled Ground-Water and Surface-Water Flow Model (GSFLOW). The new model was applied to study the hydrologic cycle of the Zhangye Basin, northwest China, a typical arid to semi-arid area with significant irrigation. After the successful calibration, the model produced a holistic view of the hydrological cycle impact by the agricultural water use, and generated insights into the spatial and temporal patterns of the SW-GW interaction in the study area. Different water resources management scenarios were also evaluated via the modeling. The results showed that if the irrigation demand continuous to increase, the current management strategy would lead to acceleration of the groundwater depletion, and therefore introduce ecological problems to this basin. Overall, this study demonstrated the applicability of the new model and its value to the water resources management in arid and semi-arid areas.

Introduction

In arid and semi-arid regions, interaction between surface water (SW) and groundwater (GW) plays an important role in the eco-hydrological system (Sophocleous, 2002, Gilfedder et al., 2012). The interaction is often complicated by agricultural activities including surface water diversion, groundwater pumping and irrigation, as they could significantly alter the flow regimes of both surface water and groundwater (Barlow et al., 2000, McCallum et al., 2013, Shah, 2014, Siebert et al., 2010). Understanding the complex behavior of the integrated SW-GW system is very important to the regional water resources management (Rassam et al., 2013), and integrated modeling is a highly desired approach.

A number of integrated SW-GW models have been developed, such as GSFLOW (Markstrom et al., 2008), HydroGeoSphere (Brunner and Simmons, 2012, Therrien et al., 2010), ParFlow (VanderKwaak and Loague, 2001), MIKE SHE (Graham and Butts, 2005), MODHMS (Panday and Huyakorn, 2004) and SWATMOD (Sophocleous et al., 1999). Some of these models incorporate MODFLOW (Harbaug, 2005), a classic 3-D groundwater simulator, as their subsurface module. For example, GSFLOW integrates Precipitation Runoff Modeling System (PRMS) (Leavesley et al., 1983) with MODFLOW; SWATMOD couples the widely applied Soil Water Assessment Tool (SWAT) (Arnold et al., 1998) model with MODFLOW; and MODHMS introduces 2-D diffusion wave routing for surface water into MODFLOW. The existing models have been applied to address different water resources issues, including irrigation management (e.g., Pérez et al., 2011), SW-GW interactions (e.g., Huntington and Niswonger, 2012, Niswonger et al., 2008, Werner et al., 2006), land use and climate change (e.g., Graham and Butts, 2005, Markstrom, 2012), water quality (e.g., Borah and Bera, 2003) and so on.

However, few studies (Demetriou and Punthakey, 1998) have investigated the hydrologic impacts of agricultural water use in the context of integrated SW-GW modeling, especially for large river basins. The lack of research is in part due to the limited capacity of the existing integrated models in simulating the complicated flow regime in an irrigation system. For example, unlike a natural river network in which tributaries run into the main stream, an irrigation network has a main aqueduct which splits water into lower-order aqueducts. Also, engineering structures (e.g., culverts, weirs, gates, and pumps) and their operations in irrigation systems are often ignored by the existing models. Hydraulic modules in the current models are not able to handle these complexities. On the other hand, some studies (Rassam, 2011, Rodriguez et al., 2008, Valerio et al., 2010, Welsh et al., 2013) introduced advanced hydraulic engines (e.g., HEC-RAS, RiverWare, SIMS) into MODFLOW, but the basin-scale SW-GW interaction was not fully accounted for.

To better address the role of agricultural water use in integrating SW-GW modeling, this study coupled GSFLOW with SWMM (Rossman, 2009). To our best knowledge, this coupling has not been attempted by previous studies. SWMM is a dynamic and distributed model for simulating runoff quantity and quality. It has been widely used to study different rainfall-runoff issues (Gironás et al., 2010, Peterson and Wicks, 2006, Shrestha et al., 2013). Its hydraulic engine can nicely handle the flow in artificial waterways with different engineering structures. GSFLOW's strength in modeling SW-GW interaction and SWMM's strength in hydraulic simulation complement each other. In addition to the coupling, two modules were added, one to allocate diverted water from aqueducts to farms, and the other to allocate pumped water from wells to farms.

The coupled model (hereafter called GSFLOW-SWMM) was then applied to Zhangye Basin (ZB), a typical arid and semi-arid area in northwest China. ZB is the mid-stream part of Heihe River Basin (HRB), which is the second largest inland river basin in China. The SW-GW interaction in ZB is significant and complicated (Hu et al., 2007), and highly impacted by agricultural irrigation which consumes a great amount of water from the Heihe River and local aquifers. Securing the environmental flow towards the downstream has been an important management issue, due to the fast degradation of the ecosystem in the lower HRB (the Gobi Desert area) and the shrink of the terminal lake, the Juyan Lake (Guo et al., 2009). Hydrological modeling has been performed for both the entire HRB and ZB alone (Li et al., 2013, Li et al., 2010, Wang et al., 2010, Wen et al., 2007, Zhang et al., 2004), but fully integrated SW-GW modeling has not been attempted for this area.

Overall, this study was aimed to: 1) enhance the capability of the integrated SW-GW modeling in addressing highly engineered flow systems such as the agricultural irrigation system; and 2) demonstrate how the integrated modeling would benefit the hydrological process understanding and water resources management at large basins. In the remaining of this paper, Section 2 introduces the coupling strategy and additional modules added. Section 3 describes the study area and the modeling procedure. Results and discussion are presented in Sections 4, and conclusions are provided in Section 5.

Section snippets

Introduction to GSFLOW and SWMM

GSFLOW (Coupled Ground-Water and Surface-Water Flow Model) is a model developed by USGS (Markstrom et al., 2008) which simulates all major processes of the hydrologic cycle. It integrates PRMS with MODFLOW which perform surface hydrology simulation and 3-D groundwater simulation, respectively. The MODFLOW2005 version adopts the UZF package (Niswonger et al., 2006) as its unsaturated-zone flow simulation module, the SFR2 package (Niswonger and Prudic, 2005) as its streamflow module, and the WELL

Study area

Our study area (Fig. 2), the Zhangye Basin (ZB), is the midstream region of Heihe River Basin (HRB). It is a sedimentary basin bounded by the Qilian Mountains on the south, the Bei Mountains on the north, the Jiuquan-west Basin on the west and the Maying Basin on the east. Yingluoxia and Zhengyixia are the starting points of the midstream and downstream of the Heihe River, respectively. The modeling domain has an area of 9097 km², and the elevation ranges from 1290 m in the northwest to 2200 m

Calibration results

Fig. 3 compares the monthly streamflow simulated by GSFLOW-SWMM against the observations at the Gaoai and Zhengyixia stations. The Nash-Sutcliffe model efficiency (NSE) is 0.885 at the Gaoai station and 0.884 at the Zhengyixia station. The logNSE equals to 0.837 and 0.602, and the BIAS equals to 0.09 and −0.04 for the two stations, respectively. For daily streamflow (not illustrated), the NSE equals to 0.833 and 0.831, respectively. These goodness-of-fit metrics indicate that, the model

Conclusions

In this study, GSFLOW and the hydraulic engine of SWMM were successfully coupled, and additional improvements were made. The new model, referred to as GSFLOW-SWMM, can effectively address a complicated irrigation system with both surface water diversion and groundwater pumping. The case study in the Zhangye Basin demonstrated the applicability of the model for large basins, as well as its strength in providing a holistic view of the water cycle, characterizing the SW-GW interaction with

Acknowledgments

This work was supported by the National Natural Science Foundation of China (NSFC) (No. 91125021, No. 91225301 and No. 41371473). The data set was provided by Cold and Arid Regions Science Data Center in Lanzhou, China (http://westdc.westgis.ac.cn). We also thank the three anonymous reviewers for their insightful comments and suggestions.

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View full text

Modeling surface water-groundwater interaction in arid and semi-arid regions with intensive agriculture

Highlights

Abstract

Introduction

Section snippets

Introduction to GSFLOW and SWMM

Study area

Calibration results

Conclusions

Acknowledgments

J. Hydrol.

Environ. Model. Softw.

Environ. Model. Softw.

Environ. Model. Softw.

Environ. Model. Softw.

Environ. Model. Softw.

Int. J. Appl. Earth Obs. Geoinform.

J. Hydrol.

Agric. For. Meteorol.

J. Hydrol.

J. Hydrol.

Adv. Water Resour.

J. Hydrol.

Environ. Model. Softw.

Environ. Model. Softw.

J. Hydrol.

J. Hydrol.

Environ. Model. Softw.

J. Hydrol.

J. Hydrol.

Environ. Model. Softw.

J. Hydrol.

Evaluation of FAO-56 Penman–Monteith and temperature based models in estimating reference evapotranspiration using complete and limited data, application to Nigeria

Agric. Eng. Int. CIGR J.

Crop Evapotranspiration -Guidelines for Computing Crop Water Requirements-FAO Irrigation and Drainage Paper 56

Large area hydrologic modeling and assessment part I: model development

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Hydrogeol. J.

Water-ecological-economic System Integrated Management Research on Heihe River Basin