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Integrating remote sensing, census and weather data for an assessment of rice yield, water consumption and water productivity in the Indo-Gangetic river basin

机译:集成遥感,人口普查和天气数据,以评估印度恒河流域的水稻产量,耗水量和水生产率

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摘要

Crop consumptive water use and productivity are key elements to understand basin water management performance. This article presents a simplified approach to map rice (Oryza sativa L.) water consumption, yield, and water productivity (WP) in the Indo-Gangetic Basin (IGB) by combining remotely sensed imagery, national census and meteorological data. The statistical rice cropped area and production data were synthesized to calculate district-level land productivity, which is then further extrapolated to pixel-level values using MODIS NDVI product based on a crop dominance map. The water consumption by actual evapotranspiration is estimated with Simplified Surface Energy Balance (SSEB) model taking meteorological data and MODIS land surface temperature products as inputs. WP maps are then generated by dividing the rice productivity map with the seasonal actual evapotranspiration (ET) map. The average rice yields for Pakistan, India, Nepal and Bangladesh in the basin are 2.60, 2.53, 3.54 and 2.75tons/ha, respectively. The average rice ET is 416mm, accounting for only 68.2% of potential ET. The average WP of rice is 0.74kg/mpd. The WP generally varies with the trends of yield variation. A comparative analysis of ET, yield, rainfall and WP maps indicates greater scope for improvement of the downstream areas of the Ganges basin. The method proposed is simple, with satisfactory accuracy, and can be easily applied elsewhere.
机译:作物耗水量和生产力是了解流域水管理绩效的关键要素。本文提出了一种简化的方法,通过结合遥感图像,国势普查和气象数据来绘制印度恒河盆地(IGB)中水稻(Oryza sativa L.)的耗水量,产量和水生产率(WP)。合成了统计的水稻种植面积和生产数据,以计算区级土地生产力,然后使用MODIS NDVI产品基于作物优势图,将其进一步外推到像素级值。通过简化的表面能平衡(SSEB)模型,以气象数据和MODIS地表温度乘积为输入,估算了实际蒸发蒸腾的耗水量。然后通过将稻米生产率图除以季节实际蒸散量(ET)图来生成WP图。该盆地巴基斯坦,印度,尼泊尔和孟加拉国的大米平均产量分别为每公顷2.60、2.53、3.54和2.75吨。大米的平均ET为416mm,仅占潜在ET的68.2%。大米的平均可湿性粉剂为0.74kg / mpd。 WP通常随产量变化趋势而变化。对ET,产量,降雨量和WP图的比较分析表明,恒河流域下游地区的改善空间更大。所提出的方法简单,准确度令人满意,并且可以容易地应用于其他地方。

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