Yield Maximization of Wheat (Triticum aestivum L.) Cultivars through Improved Water Management Strategy

2016 ◽  
Vol 3 (2) ◽  
pp. 67
Author(s):  
Dhiman Mukherjee
2007 ◽  
Vol 22 (01) ◽  
pp. 59-68 ◽  
Author(s):  
Ahmed S. Abou-Sayed ◽  
Karim S. Zaki ◽  
Gary Wang ◽  
Manoj Dnyandeo Sarfare ◽  
Martin H. Harris

2017 ◽  
Vol 76 ◽  
pp. 319-327
Author(s):  
Wenlong Zhang ◽  
Yi Li ◽  
Chao Wang ◽  
Peifang Wang ◽  
Qing Wang ◽  
...  

2020 ◽  
Author(s):  
Katja Friedrich ◽  
Kyoko Ikeda ◽  
Sarah Tessendorf ◽  
Jeffrey French ◽  
Robert Rauber ◽  
...  

<p>Cloud seeding has been used as one water management strategy to overcome the increasing demand for water despite decades of inconclusive results on the efficacy of cloud seeding. In this study snowfall accumulation from glaciogenic cloud seeding is quantified based on snow gauge and radar observations from three days in January 2017, when orographic clouds in the absent of natural precipitation were seeded with silver iodide (AgI) in the Payette basin of Idaho during the Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment (SNOWIE). On each day, a seeding aircraft equipped with AgI flares flew back and forth on a straight-line flight track producing a zig-zag pattern representing two to eight lines of clouds visible through enhancements in radar reflectivity. As these seeding lines started to form precipitation, they passed over several snow gauges and through the radar observational domain. For the three cases presented here, precipitation gauges measured increases between 0.05-0.3 mm as precipitation generated by cloud seeding pass over the instruments. A variety of relationships between radar reflectivity factor and liquid equivalent snowfall rate were used to quantify snowfall within the radar observation domain. For the three cases, snowfall occurred within the radar observational domain between 25 -160 min producing a total amount of water generated by cloud seeding ranging from 123,220 to 339,540 m3 using the best-match Ze-S relationship. Uncertainties in radar reflectivity estimated snowfall are provided by considering not only the best-match Ze-S relationship but also an ensemble of Ze-S relationships based on the range of coefficients published from previous studies and then examining the percentile of snowfall estimates based on all of the Ze-S relationships within the ensemble. Considering the interquartile range and 5<sup>th</sup>/95<sup>th</sup> percentiles, uncertainties in total amount of water generated by cloud seeding can range between 20-45% compared to the best-math estimates. These results provide new insights towards understanding how cloud seeding impacts precipitation and its distribution across a region.</p>


Author(s):  
S. Chandran ◽  
S. R. Thiruchelve ◽  
M. Dhanasekarapandian

Abstract Economic growth of any nation like India depends on growth of cities. In India 31% of total population exists in urban extent. Smart City mission of India was established with the objective to deliver the basic requirements of the citizens in a sustainable manner. Madurai city located at Peninsular India with 1.4 Million population was taken for this study. The objective is to develop an Integrated Urban Water Management Strategy after analysing all the components of Urban Water Cycle such as rainfall, runoff, groundwater and wastewater. The population forecast for 2021 was done for the Local Planning Area (LPA) of 726.34 km2 and the water demand was calculated as 109 Mm3/year. To meet the demand, runoff from the average rainfall was estimated as 393 Mm3/yr using SCS-CN method. The storage capacity in the water bodies to store the Surface water was estimated as 156 Mm3/yr and groundwater recharge potential was estimated as 22 Mm3/yr. The Integrated Urban Water Management strategy developed, shows that there is a huge potential for rainwater storage at the surface level and subsequent recharge through artificial recharge techniques.


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