Xinchun Cao

An evaluation of the water utilization and grain production of irrigated and rain-fed croplands in China

Irrigation plays a major role in Chinese agricultural production, as China is experiencing water and food scarcity. Assessing water use (WU) and water productivity (WP) will contribute to regional water management and grain production improvement. This paper quantifies the water use and productivity in grain production for 31 Chinese provinces, autonomous regions and municipalities (PAMs) by distinguishing between irrigated and rain-fed farmland. An indicator of marginal productivity of blue water (MWPb) is established and calculated to evaluate irrigation profits. National water use (WUt) for grain cultivation from 1998 to 2010 was approximately 689.04 Gm(3) (42.26% blue water and 57.74% green water). The productive water proportions for irrigated and total croplands were 65.57% and 76.85%, respectively. Water use compositions from both blue-green and productive-unproductive perspectives changed slightly over time. The water use productivity (WPU) and water consumption productivity (WPC) for integrated grain products of China during the study period were 0.747 and 0.972 kg/m(3), respectively. The spatial distribution patterns of irrigated WPs (WPUI, WPCI) were consistent with those for total cropland. China has achieved sufficient food supply without increasing water use. The national MWPb was estimated to be 0.673 kg/m(3), revealing a higher increase in crop yield on irrigated land compared to rain-fed land. The northeast provinces urgently need to improve irrigation efficiency, and the North China Plain PAMs should promote rain-fed crop yield to increase grain production and control water use in the future.

A drought hazard assessment index based on the VIC–PDSI model and its application on the Loess Plateau, China

Drought is a complex natural hazard that is poorly understood and difficult to assess. This paper describes a VIC–PDSI model approach to understanding drought in which the Variable Infiltration Capacity (VIC) Model was combined with the Palmer Drought Severity Index (PDSI). Simulated results obtained using the VIC model were used to replace the output of the more conventional two-layer bucket-type model for hydrological accounting, and a two-class-based procedure for calibrating the characteristic climate coefficient (Kj) was introduced to allow for a more reliable computation of the PDSI. The VIC–PDSI model was used in conjunction with GIS technology to create a new drought assessment index (DAI) that provides a comprehensive overview of drought duration, intensity, frequency, and spatial extent. This new index was applied to drought hazard assessment across six subregions of the whole Loess Plateau. The results show that the DAI over the whole Loess Plateau ranged between 11 and 26 (the greater value of the DAI means the more severe of the drought hazard level). The drought hazards in the upper reaches of Yellow River were more severe than that in the middle reaches. The drought prone regions over the study area were mainly concentrated in Inner Mongolian small rivers, Zuli and Qingshui Rivers basin, while the drought hazards in the drainage area between Hekouzhen–Longmen and Weihe River basin were relatively mild during 1971–2010. The most serious drought vulnerabilities were associated with the area around Lanzhou, Zhongning, and Yinchuan, where the development of water-saving irrigation is the most direct and effective way to defend against and reduce losses from drought. For the relatively humid regions, it will be necessary to establish the rainwater harvesting systems, which could help to relieve the risk of water shortage and guarantee regional food security. Due to the DAI considers the multiple characteristic of drought duration, intensity, frequency, and spatial extent, and because it is based on the VIC–PDSI model and GIS technologies, the DAI could provide some new way on directly comparing the drought hazards over different regions during a long-term period. The result of this study may be useful to decision makers when formulating drought management policies to alleviate the risk of water shortages and guarantee regional food security.

Impacts of changing cropping pattern on virtual water flows related to crops transfer: a case study for the Hetao irrigation district, China.

BACKGROUND Analysis of cropping patterns is a prerequisite for their optimisation, and evaluation of virtual water flows could shed new light on water resources management. This study is intended to explore the effects of cropping pattern changes between 1960 and 2008 on virtual water flows related to crops transfer in the Hetao irrigation district, China. RESULTS (1) The sown area of crops increased at an average rate of 3.57 × 10(3) ha year(-1) while the proportion of sown grain crops decreased from 92.83% in the 1960s to 50.22% in the 2000s. (2) Virtual water content decreased during the study period while net virtual water exports increased since the 1980s. (3) Assuming that the cropping pattern was constant and was equal to the average 1960s value, accumulated net virtual water export in 1980-2008 would have been 4.76 × 10(9) m(3) greater than that in the actual cropping pattern scenario. CONCLUSION Cropping pattern changes in the Hetao irrigation district could not only be seen as resulting from the pursuit for higher economic returns, but also as a feedback response to limited water resources. A systematic framework is still needed for future cropping pattern planning by taking food security, continued agricultural expansion and other constraints into consideration.

GANN models for reference evapotranspiration estimation developed with weather data from different climatic regions

Accurate estimation of reference evapotranspiration (ET0) becomes imperative for better managing the more and more limited agricultural water resources. This study examined the feasibility of developing generalized artificial neural network (GANN) models for ET0 estimation using weather data from four locations representing different climatic patterns. Four GANN models with different combinations of meteorological variables as inputs were examined. The developed models were directly tested with climatic data from other four distinct stations. The results showed that the GANN model with five inputs, maximum temperature, minimum temperature, relative humidity, solar radiation, and wind speed, performed the best, while that considering only maximum temperature and minimum temperature resulted in the lowest accuracy. All the GANN models exhibited high accuracy under both arid and humid conditions. The GANN models were also compared with multivariate linear regression (MLR) models and three conventional methods: Hargreaves, Priestley–Taylor, and Penman equations. All the GANN models showed better performance than the corresponding MLR models. Although Hargreaves and Priestley–Taylor equations performed slightly better than the GANN models considering the same inputs at arid and semiarid stations, they showed worse performance at humid and subhumid stations, and GANN models performed better on average. The results of this study demonstrated the great generalization potential of artificial neural techniques in ET0 modeling.