CAJ | 학술논문

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．
통과대범납빈대하양식대붕내외지당수온여기온적동보감측분석，이용통계방법연구료지당온도변화특정급수온예측모형．결과표명：여기온상비，지당수온일진폭교소，일최고온도출현시간체후：청천조건하수온여기온적일변화대우음천；유우증양설비적사용，지당상하층수온온차교소，체후불명현；여붕외지당수온상비，대붕지당수온변화평완，수외계천기조건영향교소，일평균수온비붕외고출9．47℃，차능유지재30～33℃，위최괄의대하생장적수온．이용수온여기온적상관관계급수온체후효응분별건립료대붕내、대붕외지당일최고화최저수온자회귀모형，경Durbin—h검험급엄의차분법소제자상관，대부분회귀모형진행료수정，각모형적회귀효과체도료현저수평，평균상대오차균재5．0％이내．경험증각모형예측정도교고，구유교호적가고성화보괄성，가용우지당수온적예보．
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.