Predicting the impacts of climate change on groundwater recharge in an arid environment using modeling approach

Abstract

Purpose Groundwater is an important source of water supply in arid and semi-arid areas. The purpose of this study is to predict the impact of climate change on groundwater recharge in an arid environment in Ilam Province, west of Iran. Design/methodology/approach A three-dimensional transient groundwater flow model (modular finite difference groundwater FLOW model: MODFLOW) was used to simulate the impacts of three climate scenarios (i.e. an average of a long-term rainfall, predicted rainfall in 2015-2030 and three years moving average rainfall) on groundwater recharge and groundwater levels. Various climate scenarios in Long Ashton Research Station Weather Generator were applied to predict weather data. Findings HadCM3 climatic model and A2 emission scenario were selected as the best methods for weather data generation. Based on the results of these models, annual precipitation will decrease by 3 per cent during 2015-2030. For three emission scenarios, i.e. an average of a long-term rainfall, predicted rainfall in 2015-2030 and three years moving average rainfall, precipitation in 2030 is estimated to be 265, 257 and 247 mm, respectively. For the studied aquifer, predicted recharge will decrease compared to recharge calculated based on the average of long-term rainfall. Originality/value The decline of groundwater level in the study area was 11.45 m during the past 24 years or 0.48 m/year. Annual groundwater depletion should increase to 0.75 m in the coming 16 years via climate change. Climate change adaptation policies in the basin should include changing the crop type, as well as water productivity and irrigation efficiency enhancement at the farm and regional scales.

How Do Gaining and Losing Streams React to the Combined Effects of Climate Change and Pumping in the Gharehsoo River Basin, Iran?

“…Water Resources Research TAIE SEMIROMI AND KOCH precipitation and the rise of the projected min and maximum temperature. Previous studies (e.g., Bovolo et al, 2009;Crosbie et al, 2010;Crosbie et al, 2013;Erturk et al, 2014;Gemitzi et al, 2017;Ghazavi & Ebrahimi, 2019;Goodarzi et al, 2016;Jyrkama & Sykes, 2007;Kahsay et al, 2018;Karian & Dudewicz, 2000;Moeck et al, 2016;Nassery & Salami, 2016;Riasati et al, 2012;Rosenberg et al, 1999;Scibek & Allen, 2006;Shrestha et al, 2016;Smerdon, 2017;Stoll et al, 2011;Thampi & Raneesh, 2012) have broadly linked climate change-induced precipitation changes to spatiotemporal variabilities of groundwater recharge. However, whereas there is an unequivocal rise in temperature due to the global warming, the projected recharge could increase or reduce, depending on how precipitation reacts to climate change effects (Jyrkama & Sykes, 2007).…”

“…Groundwater resources response to climate change occures directly through the flux exchange with surface water bodies, including lakes, wetlands, and river networks (e.g., Dwire et al, 2017; Goderniaux et al, 2011; P. Goderniaux et al, 2009; Scibek et al, 2007; Taviani & Henriksen, 2015; van Engelenburg et al, 2018; Yidana et al, 2019). Groundwater reaction to climate change effects takes place indirectly via the recharge processes (e.g., Bovolo et al, 2009; Crosbie et al, 2010; Erturk et al, 2014; Gemitzi et al, 2017; Ghazavi & Ebrahimi, 2019; Goodarzi et al, 2016; Jyrkama & Sykes, 2007; Kahsay et al, 2018; Nassery & Salami, 2016; Riasati et al, 2012; Scibek & Allen, 2006; Shrestha et al, 2016; Smerdon, 2017). In addition, dependency on the groundwater consumption can be increased in the wake of less availability of surface water under a changing climate (e.g., Goodarzi et al, 2019).…”

Impact of extreme events on conversion efficiency of wave energy converter

“…HadCM3 model was developed by Gordon et al 49 at the Hadley Centre in the United Kingdom which considered the influence of both atmospheric and oceanic parameters and includes the impact of aerosol on the climate. The model was widely used for different predictive studies such as estimation of climate change impact on groundwater recharge in arid regions of Iran, 50 water availability for different types of consumption in Tanzania, 51 water resources and soil erosion in Burkina Faso, West Africa, 52 paddy irrigation water requirements in Sri Lanka, 53 estimation of future distribution of plant species in the European continent, 54 and change in Arctic sea ice thickness and area for the future time slabs. 55 HadCM3 does not include flux adjustment due to its stable control climatology.…”

Toward Bridging Future Irrigation Deficits Utilizing the Shark Algorithm Integrated with a Climate Change Model

“…This climate change information for the basin and the input from the HAD-CM3 model are subsequently used to simulate climate change conditions for future periods. Thus, the LARS-WG model is considered a black box model [36][37][38].…”