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【Objective】 Winter wheat-cotton rotation is a common cultivation in Yellow River Basin in China, but they have an overlapped growing period. How to plant the cotton to make most of above- and below-ground resources is an issue that is not well understood. This paper aims to investigate how planting and irrigation combine to modulate growth, yields, quality and economic return of the two crops. 【Method】 The experiment was conducted in a field, with the cotton either directly drilled before the wheat was harvested or transplanted from a seedling bed after wheat harvest. We compared three irrigations: border irrigation, micro-sprinkling hose irrigation and surface drip irrigation. 【Result】 Transplantation improved leaf area index (LAI) and yield of the winter wheat, as well as the net income of winter wheat compared with directly drilling, despite a 5.64% reduction in cotton yield; overall, its total net income was 8.64% higher than the directly drilling. Compared with border irrigation and micro-sprinkling hose irrigation, surface drip irrigation significantly improved the plant height, LAI, yield and economic return of the two crops. The total net income of surface drip irrigation was 36.01% and 10.10% higher than that of border irrigation and micro-sprinkling hose irrigation, respectively. Transplantation combined with surface drip irrigation gave the highest net income at 15 924.9 yuan/hm2. 【Conclusion】 Transplanting cotton seedling after harvesting the winter wheat combined with surface drip irrigation reduces their competition for resources and is therefore optimal for wheat-cotton rotation in the Yellow River Basin.

【Objective】 Identifying catchments and their hydrological boundaries in a river basin is important for improving water resource management and protecting its eco-environmental development. Taking the four rivers flowing through Henan province as an example, this paper calculated the catchments and their associated areas in each basin across the province. 【Method】 The four rivers we considered were the Yangtze River, the Yellow River, the Huai River and the Hai River; their catchment identification was based on the digital elevation model (DEM) data, where each catchment and its hydrological boundaries, streams at different levels, as well as counties in each basin were identified and calculated using ArcHydro in ArcGIS extension module. 【Result】 In terms of covered area, the biggest basin in the province is the Huai River, covering 52.70% of the provincial area, followed by the Yellow River with 21.62%, the Yangtze River with 16.50%, and the Hai River with 9.18%. In terms of areas being affected, the Yellow River impacted more places including Xingyang, Huiji and Jinshui District in Zhengzhou, Longting District, Xiangfu and Lankao County in Kaifeng, although some of them are not within its hydrological catchments. In terms of river network, the Yangtze River basin is most dense with a river-length density of 0.36 km/km2, followed by the Yellow River basin with 0.30 km/km2, the Huai River basin with 0.27 km/km2, and the Hai River basin with 0.20 km/km2. Spatially, river network is least dense in the north of the Yellow River, with a density of 0.15 km/km2 only. 【Conclusion】 ArcHydro in ArcGIS is accurate to extract catchment boundaries and the river network system in a basin, and it can be used for regional analysis of land usage or water resource management.

Increasing planting density is an important ways to increase maize yield. A hot topic of conversation in the current research is how to improve crop light efficiency and yield potential by optimizing the cultivation mode under high density planting is a hot topic in current research. Thus, in this study, a field experiment was conducted to explore the effects of stereo-planting patterns on water and the utilization light resource and maize yields. Planting patterns included the conventional flat planting pattern (as the control, CK) and the stereo-planting in ridge and furrow (T). Each planting pattern had three planting densities, i.e., 60,000 plants ha−1 (D1), 75,000 plants ha−1 (D2) and 90,000 plants ha−1 (D3). The results showed that stereo-planting affected the physiological characteristics of plants by changing the spatial distribution of soil moisture. At the silking stage (R1), photosynthetic rate (Pn) of plants on the ridge was similar to CK, and transpiration rate (Tr) was significantly lower than that of CK. Pn of maize in the furrow was significantly higher than that of CK, and Tr was similar to CK. Stereoscopic planting had different effects on intraspecific competition intensity in maize population in different growing stages. In the six-leaf stage (V6), stereo-planting increased competition intensity of maize on the ridge, but lowered that of maize in the furrow by affecting the spatial distribution of soil moisture. During the R1 stage, stereo-planting increased the light transmittance rate within the canopy and eased the plant's competition for light by reducing plant height and leaf area of maize under three density conditions. Stereo-planting had no effect on grain yield and dry matter accumulation of ridge-planted maize in the later growing stage, but it did increased the dry matter accumulation and grain yield of furrow-planted maize due to the improvement of the light environment and photosynthetic characteristics of the population. In two test years, stereo-planting increased 5.0–11.0% average yield of maize compared to CK under three density conditions. These results indicate that stereo-planting can reduce the plant's competition for light and water resources and improve its physiological traits of plant by optimizing its spatial distribution of soil moisture and canopy structure, thus further increasing grain yield of maize under high-density planting conditions. [ABSTRACT FROM AUTHOR]

Conventional farming practices not only constrained food security due to low yield but also threatened the ecosystem by causing groundwater decline and groundwater nitrate contamination. A two׹ear field experiment was conducted at the research station of North China University of Water Resources and Electric Power, Zhengzhou. The WHCNS model was used to simulate grain yield, water and nitrogen fertilizer use efficiencies (WUE and FNUEs) of spring maize under border irrigation method, drip irrigation, and rainfed conditions. In addition, a scenario analysis was also performed on different dry and rainy seasons to assess the long-term impact of rainfall variability on spring maize from 2000-2017. The result showed that the model precisely simulated soil water content, N concentration, crop biomass accumulation, and grain yield. The maximum and minimum range of relative root mean squire error ( RRMSE ) values were 0.5-36.0% for soil water content, 14.0-38.0% for soil nitrate concentrations, 19.0-24.0% for crop biomass and 1.0-2.0% for grain yield, respectively under three irrigation methods. Both the index of agreement ( IA ) and Pearson correlation coefficient ( r ) values were close 1. We found the lowest grain yield from the rainfed maize, whereas the drip irrigation method increased grain yield by 14% at 40% water saving than border irrigation method for the two years with the 11% lower evaporation and maintained transpiration rate. Moreover, the drip irrigated maize had a negligible amount of drainage and runoff, which subsequently improved WUE by 27% in the first growing season and 16% in the second rotation than border irrigation. The drip irrigated maize also showed 24% higher FNUE. The reason of lower WUE and FNUEs under the border irrigation method was increased drainage amounts and N leaching rates. Furthermore, scenario analysis indicated that the dry season could result in a 30.8% yield decline as compared to rainy season.