Shaofeng Jia

Addressing China’s grand challenge of achieving food security while ensuring environmental sustainability

China’s increasingly urbanized and wealthy population is driving a growing and changing demand for food, which might not be met without significant increase in agricultural productivity and sustainable use of natural resources. Given the past relationship between lack of access to affordable food and political instability, food security has to be given a high priority on national political agendas in the context of globalization. The drive for increased food production has had a significant impact on the environment, and the deterioration in ecosystem quality due to historic and current levels of pollution will potentially compromise the food production system in China. We discuss the grand challenges of not only producing more food but also producing it sustainably and without environmental degradation. In addressing these challenges, food production should be considered as part of an environmental system (soil, air, water, and biodiversity) and not independent from it. It is imperative that new ways of meeting the demand for food are developed while safeguarding the natural resources upon which food production is based. We present a holistic approach to both science and policy to ensure future food security while embracing the ambition of achieving environmental sustainability in China. It is a unique opportunity for China to be a role model as a new global player, especially for other emerging economies.

An Interval-Parameter Fuzzy Linear Programming with Stochastic Vertices Model for Water Resources Management under Uncertainty

An interval-parameter fuzzy linear programming with stochastic vertices (IFLPSV) method is developed for water resources management under uncertainty by coupling interval-parameter fuzzy linear programming (IFLP) with stochastic programming (SP). As an extension of existing interval parameter fuzzy linear programming, the developed IFLPSV approach has advantages in dealing with dual uncertainty optimization problems, which uncertainty presents as interval parameter with stochastic vertices in both of the objective functions and constraints. The developed IFLPSV method improves upon the IFLP method by allowing dual uncertainty parameters to be incorporated into the optimization processes. A hybrid intelligent algorithm based on genetic algorithm and artificial neural network is used to solve the developed model. The developed method is then applied to water resources allocation in Beijing city of China in 2020, where water resources shortage is a challenging issue. The results indicate that reasonable solutions have been obtained, which are helpful and useful for decision makers. Although the amount of water supply from Guanting and Miyun reservoirs is declining with rainfall reduction, water supply from the South-to-North Water Transfer project will have important impact on water supply structure of Beijing city, particularly in dry year and extraordinary dry year.

Spatio-Temporal Changes in Vegetation Activity and Its Driving Factors during the Growing Season in China from 1982 to 2011

Using National Oceanographic and Atmospheric Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR) and Climatic Research Unit (CRU) climate datasets, we analyzed interannual trends in the growing-season Normalized Difference Vegetation Index (NDVI) in China from 1982 to 2011, as well as the effects of climatic variables and human activities on vegetation variation. Growing-season (period between the onset and end of plant growth) NDVI significantly increased (p < 0.01) on a national scale and showed positive trends in 52.76% of the study area. A multiple regression model was used to investigate the response of vegetation to climatic factors during recent and previous time intervals. The interactions between growing-season NDVI and climatic variables were more complex than expected, and a lag existed between climatic factors and their effects on NDVI. The regression residuals were used to show that over 6% of the study area experienced significantly human-induced vegetation variations (p < 0.05). These regions were mostly located in densely populated, reclaimed agriculture, afforestation, and conservation areas. Similar conclusions were drawn based on land-use change over the study period.

Meeting the Basin Closure of the Yellow River in China

Since the 1950s, the major gauging stations along the Yellow River have recorded a trend of decline in measured discharge. During the 1990s, the Yellow River once became seasonal and sent no water to the sea for several months in a year. This study investigates changes in the availability of water resources and water use at different sections of the Yellow River and in different economic sectors in the basin. Some hard and soft landing measures in dealing with basin closure are introduced and policy implications regarding the reallocation of water resources are addressed.

Monitoring the fluctuation of lake Qinghai using multi-source remote sensing data

The knowledge of water storage variations in ungauged lakes is of fundamental importance to understanding the water balance on the Tibetan Plateau. In this paper, a simple framework was presented to monitor the fluctuation of inland water bodies by the combination of satellite altimetry measurements and optical satellite imagery without any in situ measurements. The fluctuation of water level, surface area, and water storage variations in Lake Qinghai were estimated to demonstrate this framework. Water levels retrieved from ICESat (Ice, Cloud, and and Elevation Satellite) elevation data and lake surface area derived from MODIS (Moderate Resolution Imaging Spectroradiometer) product were fitted by linear regression during the period from 2003 to 2009 when the overpass time for both of them was coincident. Based on this relationship, the time series of water levels from 1999 to 2002 were extended by using the water surface area extracted from Landsat TM/ETM+ images as inputs, and finally the variations of water volume in Lake Qinghai were estimated from 1999 to 2009. The overall errors of water levels retrieved by the simple method in our work were comparable with other globally available test results with r = 0.93, MAE = 0.07 m, and RMSE = 0.09 m. The annual average rate of increase was 0.11 m/yr, which was very close to the results obtained from in situ measurements. High accuracy was obtained in the estimation of surface areas. The MAE and RMSE were only 6 km2, and 8 km2, respectively, which were even lower than the MAE and RMAE of surface area extracted from Landsat TM images. The estimated water volume variations effectively captured the trend of annual variation of Lake Qinghai. Good agreement was achieved between the estimated and measured water volume variations with MAE = 0.4 billion m3, and RMSE = 0.5 billion m3, which only account for 0.7% of the total water volume of Lake Qinghai. This study demonstrates that it is feasible to monitor comprehensively the fluctuation of large water bodies based entirely on remote sensing data.

Less water, more grain in dry Hebei Province,China

Correlation analysis and a water productivity indicator are used to investigate the inverse relationship between increasing grain output and declining irrigation water use in Hebei Province, Peoples Republic of China, especially since 2003. A rapid improvement in water productivity more than offset the decline in available water even in one of the most water-stressed areas of north China. As long as this trend continues, there is little need for concern about a grain production crisis induced by water shortage.

Spatial distribution of vegetation and the influencing factors in Qaidam Basin based on NDVI

The spatial distribution of vegetation in Qaidam Basin was analyzed using GIMMS (Global Inventory Modeling and Mapping Studies) / NDVI (Normalized Difference Vegetation Index) data set from January 1982 to December 2006. Based on the data of precipitation, terrain, stream systems, land use and the map of vegetation distribution in Qaidam Basin, we studied the factors influencing the spatial distribution of vegetation. The results showed that the vegetation was generally low in Qaidam Basin and there was a clear semi-ring structure from southeast to northwest. In some areas, the existence of rivers, lakes and spring belts turned this semi-ring structure into a non-continuous state and formed distinct bright spots and continuous linear features. There were four main factors that affected the spatial distribution of vegetation coverage in Qaidam Basin, i.e., precipitation, hydrological conditions, altitude and human activities. Precipitation and altitude have a correlation and determine the basic pattern of vegetation distribution in Qaidam Basin. The impacts of hydrological conditions and human activities were mainly embodied in partial areas, and often broke the pattern of vegetation distribution dominated by precipitation and altitude.

Will the energy industry drain the water used for agricultural irrigation in the Yellow River basin

Abstract This article employs the case of the Yellow River basin to advance understanding of the water–energy–food nexus by demonstrating how the country’s energy and agriculture sectors are competing for limited water supplies and by quantifying the future water demands in the two sectors. The results show that in 2030 the water demands for food and energy are likely to increase by less than 4 km3 and 1 km3, respectively, in the Yellow River basin. The analysis suggests that agricultural water savings and inter-basin water transfers are the main ways to ensure sufficient water flows through the basin to fulfil demand for both sectors while preserving the natural ecosystems.

The fallacious strategy of virtual water trade

Abstract Since the concept of virtual water was put forward, there has been an increasing number of papers on the topic, as a result of which virtual water is now being mainstreamed in the water policy world. Unfortunately, virtual water trade strategy as a solution to water shortages is wrong and fallacious. Although the virtual water trade theory is considered a descendant of the comparative advantage theory of economics, it is in fact an over-simplification, going from the truth to fallacy. To make decisions of virtual water trade based on only one production factor, water, though there are many other production factors that influence the allocation of resources at the same time, is misleading theoretically and practically.

An extended linear scaling method for downscaling temperature and its implication in the Jhelum River basin, Pakistan, and India, using CMIP5 GCMs

In this study, the linear scaling method used for the downscaling of temperature was extended from monthly scaling factors to daily scaling factors (SFs) to improve the daily variations in the corrected temperature. In the original linear scaling (OLS), mean monthly SFs are used to correct the future data, but mean daily SFs are used to correct the future data in the extended linear scaling (ELS) method. The proposed method was evaluated in the Jhelum River basin for the period 1986–2000, using the observed maximum temperature (Tmax) and minimum temperature (Tmin) of 18 climate stations and the simulated Tmax and Tmin of five global climate models (GCMs) (GFDL-ESM2G, NorESM1-ME, HadGEM2-ES, MIROC5, and CanESM2), and the method was also compared with OLS to observe the improvement. Before the evaluation of ELS, these GCMs were also evaluated using their raw data against the observed data for the same period (1986–2000). Four statistical indicators, i.e., error in mean, error in standard deviation, root mean square error, and correlation coefficient, were used for the evaluation process. The evaluation results with GCMs’ raw data showed that GFDL-ESM2G and MIROC5 performed better than other GCMs according to all the indicators but with unsatisfactory results that confine their direct application in the basin. Nevertheless, after the correction with ELS, a noticeable improvement was observed in all the indicators except correlation coefficient because this method only adjusts (corrects) the magnitude. It was also noticed that the daily variations of the observed data were better captured by the corrected data with ELS than OLS. Finally, the ELS method was applied for the downscaling of five GCMs’ Tmax and Tmin for the period of 2041–2070 under RCP8.5 in the Jhelum basin. The results showed that the basin would face hotter climate in the future relative to the present climate, which may result in increasing water requirements in public, industrial, and agriculture sectors; change in the hydrological cycle and monsoon pattern; and lack of glaciers in the basin.