![]() ![]() They often have a weakness either in crop growth simulation or hydrology. The process-based models simulate the physiological development, growth and yield of a crop based on the interaction of environmental variables and plant physiological processes (e.g., photosynthesis and respiration). Therefore, they can only estimate yield, without predicting crop water uptake and soil evaporation. Most of the empirical models are regression-based models, where a correlation is established between the statistical crop yield and local weather-related, geostatistical-related, and management-related (e.g., irrigation) factors. In general, the models on crop-water relations can be divided into two categories: empirical and process-based models. analyzed the effective depth of irrigation water that can keep the soil moisture close to saturation for irrigation intervals to increase water productivity. There is also much interest in the different methods to improve the CWP. They found significantly higher water productivity in irrigated than rain-fed agriculture. analyzed the impact of drought (2005, 2012) and drought management plans (2006–2008) on agricultural water productivity in Guadalquivir River Basin in Spain for the period of 2004 to 2012. m −3 when considering total water use and crop AET, respectively.They found water productivity values, ranging from 1.39 to 2.17 kg used different full and deficit irrigation practices to calibrate and validate soil water balance in western Uruguay using the soil water balance simulation model SIMDualKc. They found an overall increase of 33% crop water productivity. ![]() evaluated crop evapotranspiration, crop production and agricultural gross domestic product contribution to assess the crop water productivity of Malawi from 2000 to 2013. They found that the range of CWP is 0.6–1.7 kg
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