Pattern of agricultural and pastoral development under water resource constraints in semi-arid areas: A case study of Tongliao, Inner Mongolia

With progress in China’s industrialization and urbanization, the contradiction of social and economic development with water resource supply–demand and water environmental pollution becomes increasingly prominent. To cope with the dual constraints of resource shortage and environmental regulations, the concept of water resource green efficiency that considers economic, environmental, and ecological factors is highly involved to promote sustainable economic development. The theoretical and practice circle devote to scientific green efficiency assessment of water resources and effective recognition of relevant influencing factors. However, to an extent they neglect social benefits brought by sustainable development and possible influences of industrial restructuring on green efficiency. They also lack concern on green efficiency of water resources in inland arid areas. To offset the disadvantages of existing studies, the philosophy of sustainable development was integrated into the input–output assessment system of green efficiency of water resources, and an assessment model was constructed using the SBM–Tobit (slack-based measure and Tobit) method. Moreover, a case study based on Henan Province, China was carried out. The green efficiencies of water resources in 18 cities of Henan Province during 2011–2018 were calculated. The operation mechanism of relevant influencing factors was discussed, and the methods to improve green efficiency of water resources were determined. Results reveal that the sustainable green efficiency of water resources in Henan Province increased in fluctuation during 2011–2018. The mean green efficiency increased from 0.425 in 2011 to 0.498 in 2018. At present, green efficiency of water resources in Henan Province remains at a low level, with a mean of 0.504. Reducing water consumption intensity and increasing investment to water environmental pollution technologies can promote green efficiency of water resources significantly. Conclusions provide a new method for scientific measurement and green efficiency assessment of water resources in inland arid areas.

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Is the impact of climate change on desertification predictable?

10.5194/egusphere-egu2020-6141 ◽

2020 ◽

Author(s):

YaoJie Yue ◽

Min Li

Keyword(s):

Climate Change ◽

Inner Mongolia ◽

North China ◽

Evaluation Model ◽

Future Climate Change ◽

Climate Change Scenarios ◽

Arid Areas ◽

Sandy Land ◽

Desertification Risk ◽

Semi Arid

Desertification, as one of the gravest ecological and environmental problems in the world, is affected both by climate change and human activities. As the consequences of global warming, the temperature in global arid and semi-arid areas is expected to increase by 1-3&#8451; by the end of this century. This change will significantly influence the spatial and temporal pattern of temperature, precipitation and wind speed in global arid and semi-arid areas, and in turn, ultimately impact the processing of desertification. Although current studies point out that future climate change tends to increase the risk of desertification. However, the future global or regional desertification risk under different climate change scenarios hasn&#8217;t been quantitively assessed. In this paper, we focused on this question by building a new model to evaluate this risk of desertification under an extreme climate change scenario, i.e. RCP8.5 (Representative Concentration Pathways, RCPs). We selected the northern agro-pastoral ecotone in China as the study area, where is highly sensitive to desertification. Firstly, the risk indicators of desertification were chosen in both natural and anthropic aspects, such as temperature, precipitation, wind speed, evaporation, and population. Secondly, the decision tree C5.0 algorithm of the machine learning technique was used to construct the quantitative evaluation model of land desertification risk based on the database of the 1:100,000 desertification map in China. Thirdly, with the support of the simulated meteorological data by General Circulation Models of HadGEM2-ES, the risk of desertification in the agro-pastoral ecotone in the north China under the RCP 8.5 scenario and SSP3 scenario (Shared Socioeconomic Pathways, SSPs) were predicted. The results show that the overall accuracy of the C5.0-based quantitative evaluation model for desertification risk is up to 83.32%, indicating that the C5.0 can better distinguish the risk of desertification according to the status of desertification impacting factors. Under the influence of future climate change, the agro-pastoral ecotone in northern China was estimated to be dominated by mild desertification risk, covering an area of more than 70%. Severe and moderate desertification risk is mainly distributed in the vicinity of Hulunbuir sandy land in the northeast of Inner Mongolia and the Horqin sandy land in the junction between Inner Mongolia, Jilin and Liaoning provinces. Compared with the datum period, the risk of desertification will decrease under the RCP8.5-SSP3 scenario. However, the desertification risk in Hulunbuir sandy land and that in the northwest of Jilin province will increase. The results of this study provide a scientific basis for developing more effective desertification control strategies to adapt to climate change in the agro-pastoral ecotone in north China. More importantly, it shows that the desertification risk can be predicted under the different climate change scenarios, which will help us to make a better understanding of the potential trend of desertification in the future, especially when the earth is getting warmer.

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Assessment of groundwater flow system for management of Stampriet Transboundary Aquifer System

10.5194/egusphere-egu2020-19896 ◽

2020 ◽

Author(s):

Irene Kinoti ◽

Marc Leblanc ◽

Albert Olioso ◽

Maciek Lubczynski

Keyword(s):

South Africa ◽

Remote Sensing ◽

Water Resources ◽

Water Resource ◽

Flow System ◽

Arid Areas ◽

Time Step ◽

Transboundary Aquifer ◽

Aquifer System ◽

Semi Arid

Groundwater is the main water resource in arid and semi-arid areas. Its evaluation in terms of recharge, discharge, flow system and change in storage is thus vital for management purposes. However, distributed numerical models which are considered as favourable tools for assessment of groundwater resources are often limited by availability of input data especially in arid and semi-arid areas in developing countries where monitoring networks are scarce. Moreover, in case of transboundary aquifers, political, institutional, cultural, socio-economic differences among countries make management of groundwater even more complex.Remote sensing is a handy tool for monitoring water resources in data scarce areas. This study entails application of remote sensing data in developing a distributed integrated hydrological model for Stampriet Transboundary Aquifer System using MODFLOW-NWT coupled with the Unsaturated Zone Flow (UZF1) Package.Stampriet Transboundary Aquifer is a multi-layered aquifer system shared between Namibia, Botswana and South Africa. The aquifer system consists of three aquifers, characterized by low transmissivity and low storage, intercalated by two aquitards. Conceptually, the physical processes taking place in this system are reasonably understood in Namibia and not as much in Botswana and South Africa. However, quantification of water resources and fluxes is still limited.The aquifer system is mainly exploited in Namibia for socio-economic growth, where abstraction from storage has led to decline in local groundwater level. Water quality constraints have restrained its usage in South Africa, while in Botswana the potential for available resources is likely to be exploited, but there is not enough data for making firm decisions.A numerical model has been set &#8211; up in transient conditions at daily time step and calibrated with groundwater levels as the state variables and satellite rainfall and potential evapotranspiration as the model driving forces. The calibrated model provides spatio-temporal water flux dynamics as well as water balances and hence an understanding of the groundwater-resource dynamics and replenishment. The results are compared to analysis of GRACE data to further constrain the model. This information is useful for proper management of the transboundary water resource as well as for policy making.

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