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机构地区:[1]浙江省慈溪市海洋与渔业局,浙江慈溪315300 [2]浙江省慈溪市水产技术推广中心,浙江慈溪315300
出 处:《宁波大学学报(理工版)》2012年第1期7-12,共6页Journal of Ningbo University:Natural Science and Engineering Edition
基 金:宁波市海洋与渔业专项资金资助(200801)
摘 要:通过对凡纳滨对虾养殖大棚内外池塘水温与气温的同步监测分析,利用统计方法研究了池塘温度变化特征及水温预测模型.结果表明:与气温相比,池塘水温日振幅较小,日最高温度出现时间滞后:晴天条件下水温与气温的日变化大于阴天;由于增氧设备的使用,池塘上下层水温温差较小,滞后不明显;与棚外池塘水温相比,大棚池塘水温变化平缓,受外界天气条件影响较小,日平均水温比棚外高出9.47℃,且能维持在30~33℃,为最适宜对虾生长的水温.利用水温与气温的相关关系及水温滞后效应分别建立了大棚内、大棚外池塘日最高和最低水温自回归模型,经Durbin—h检验及广义差分法消除自相关,对部分回归模型进行了修正,各模型的回归效果达到了显著水平,平均相对误差均在5.0%以内.经验证各模型预测精度较高,具有较好的可靠性和普适性,可用于池塘水温的预报.Temperature characteristics and water temperature prediction are studied in this paper using statistical analytical approach with the on-site measured data of water and air temperature in the open-air and greenhouse ponds designated for Litopenaeus vannamei culture. The results show that daily fluctuation of water temperature of pond is relatively small and occurring time of daily maximum water temperature lags behind that of the air temperature. Daily change of water and air temperature under clear weather is more frequent than that under overcast one. The temperature variation and time lagging effect are not obvious on the upper and bottom layers of pond due to oxygen aerator.operation. The variation of water temperature in the greenhouse ponds is found to be insignificant than that in the open-air ponds, and less affected by weather conditions. On average, a 9.47 ℃ increase in water temperature can be achieved by adding a greenhouse rooftop. Greenhouse pond maintains water temperature at 30- 33℃, which proves optimal for Litopenaeus vannamei development. Correlation analysis between water temperature and air temperature shows that water temperature is closely correlated with air temperature. Based on time lagging effect of water temperature, autoregressive models of daily maximum and minimum water temperature are established in the open-air and greenhouse ponds, respectively. Autocorrelation in the time series are checked by Durbin-h test and removed using generalized difference method. Verifications of these models are statistically effective and their average relative errors do not exceed 5.0%. The verifying results indicate that the developed models with wide applicability and good reliability can be applied to forecast water temperature ofLitopenaeus vannamei culture pond.
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