Metabolic rate and evaporative water loss in the silky starling （Sturnus sericeus）

To better understand the physiological characteristics of the silky starling（Sturnus sericeus）, its body temperature（Tb）, basal metabolic rate（BMR）, evaporative water loss（EWL） and thermal conductance（C） elicited by different ambient temperatures（Ta）（5-30 ℃） were determined in the present study. Our results showed that they have a high Tb（41.6±0.1 ℃）, a wide thermal neutral zone（TNZ）（20-27.5 ℃） and a relatively low BMR within the TNZ（3.37±0.17 mL O2/g·h）. The EWL was nearly stable below the TNZ（0.91±0.07 mg H2O/g·h） but increased remarkably within and above the TNZ. The C was constant below the TNZ, with a minimum value of 0.14±0.01 mL O2/g·h·℃. These findings indicate that the BMR, Tb and EWL of the silky starling were all affected by Ta, especially when Ta was below 20℃ and the EWL plays an important role in thermal regulation.

Estimation of evaporation losses based on stable isotopes of stream water in a mountain watershed

Water stable isotopes(δ^(2) H andδ^(18)O)can record surface water evaporation,which is an important hydrological process for understanding watershed structure and function evolution.However,the isotopic estimation of water evaporation losses in the mountain watersheds remains poorly explored,which hinders understanding spatial variations of hydrological processes and their relationships with the temperature and vegetation.Here we investigatedδ^(2) H,δ^(18)O,and d-excess values of stream water along an altitude gradient of 2130 to 3380 m in Guan’egou mountain watershed at the east edge of the Qinghai-Tibet Plateau in China.The meanδ^(2) H(-69.6‰±2.6‰),δ^(18)O(-10.7‰±0.3‰),and dexcess values(16.0‰±1.4‰)of stream water indicate the inland moisture as the major source of precipitation in study area.Water stable isotopes increase linearly with decreasing altitudes,based on which we estimated the fractions of water evaporation losses along with the altitude and their variations in different vegetations.This study provides an isotopic evaluation method of water evaporation status in mountain watersheds,the results are useful for further understanding the relationship between hydrological processes and ecosystem function under the changing climate surrounding the Qinghai-Tibet Plateau.

A Novel Approach for Energy Efficiency Prediction of Various Natural Draft Wet Cooling Towers Using ANN

Cooling tower is crucial equipment in the cool-end system of power plant and the natural draft counter-flow wet cooling tower(NDWCT)gets wide application.The artificial neural network(ANN)technique is becoming an effective method for the thermal performance investigation of cooling towers.However,the neural network research on the energy efficiency performance of NDWCTs is not sufficient.In this paper,a novel approach was proposed to predict energy efficiency of various NDWCTs by using Back Propagation(BP)neural network:Firstly,based on 638 sets of field test data within 36 diverse NDWCTs in power plant,a three-layer BP neural network model with structure of 8-14-2 was developed.Then the cooling number and evaporation loss of water of different NDWCTs were predicted adopting the BP model.The results show that the established BP neural network has preferable prediction accuracy for the heat and mass transfer performance of NDWCT with various scales.The predicted cooling number and evaporative loss proportion of the testing cooling towers are in good agreement with experimental values with the mean relative error in the range of 2.11%–4.45%and 1.04%–4.52%,respectively.Furthermore,the energy efficiency of different NDWCTs can also be predicted by the proposed BP model with consideration of evaporation loss of water in cooling tower.At last,a novel method for energy efficiency prediction of various NDWCTs using the developed ANN model was proposed.The energy efficiency index(EEI)of different NDWCTs can be achieved readily without measuring the temperature as well as velocity of the outlet air.