## 3 Results
### Effect of Integration Time on Spectral Acquisition of Water  
We all know that when a spectrometer performs electro-optical conversion it is mainly influenced by three main parameters [30]: the integration time, aperture and temperature of the micro-spectrometer. The longer the integration time, the more energy is collected by the micro-spectrometer; the larger the aperture, the more energy is collected by the micro-spectrometer; the temperature of the micro-spectrometer creates thermal noise; and different temperatures bring about different thermal noises. When measuring in the field, we pre-warmed the micro-spectrometer for 60 min to keep it below normal operating temperature to avoid the effects of thermal noise caused by temperature. For dealing with the effects of the aperture, micro-spectrometers are often used with a fixed fiber; thus, we use a fixed fiber diameter to control the effect of the aperture on the spectrum. The signal-to-noise ratio (SNR) of a spectrometer is a very important metric when using micro-spectrometers for the spectral acquisition of water bodies. The current international water color satellites MODIS Terra /Aqua (spatial resolution: 250 m and 500 m), MERIS Envisat (spatial resolution: 300 m), VIIRS (spatial resolution: 750 m) and Sentinel-3A/B (spatial resolution: 300 m) all have SNRs greater than 1000 for measurements that occur in the ocean [31]; measurements in inland lakes mainly use Landsat OLI (spatial resolution: 30 m) HJ-1 (spatial resolution: 30 m), etc., all of which have SNRs greater than 100 [32]. The use of Landsat as a data source for lake water observations on the Qinghai-Tibet Plateau requires that the signal-to-noise ratio of the micro-spectrometer be greater than 100 for application in field measurements. We believe that in the electro-optical conversion of a micro-spectrometer, the noise of the micro-spectrometer is caused by the dark current; thus, we calculated the SNRs as the total signal ratio over the dark current signal (Equation (7)). The SNRs are the ratio of the useful signal to the noisy signal in the total signal. The higher the signal-to-noise ratio, the better. \[SNR\mathrm{s}=\frac{L_{total}}{L_{darkcurrent}} \tag{7}\]  
We first measured the dark current at different integration times after warming up the micro-spectrometer for 60 min (Figure 3a) and found that the dark current increased in a logarithmic fashion with integration time. The micro-spectrometer is considered to operate at a stable maximum temperature after 60 min of operation. As we used a reference plate with a maximum reflectance of 95% for field calibrations, but the DN range of the micro-spectrometer is 0-65,535, we first needed to ensure that we did not exceed the DN limit when collecting 95% of the reference plat and that our integration time was not too long, as the state of the water body changes rapidly. We should ideally be able to measure a water body spectrum within 2 s, but in a full water body spectrum measurement, the effects of waves, boat wake, etc., need to be taken into account. We generally took several measurements to average the water body spectra for field measurements. Two schemes were used to measure 95% of the reference plate, the first using a micro-spectrometer and optical fiber to measure the DN values corresponding to radiance, and the second using a micro-spectrometer, optical fiber and cosine receiver to measure the DN values corresponding to irradiance. The SNR plot of the DN values corresponding to radiance (Figure 3b) shows that the integration time exceeds the SNRs \(\sim\)100:1 at 500 ms, but that there are higher SNRs at 1000 ms and 1500 ms; therefore, we chose 1000 ms as the integration time for the DN values of radiance. The SNR diagram for the irradiance  
Figure 3: Dark current diagram for different integration times (**a**), SNR diagram for radiance measurement of DN values (**b**), SNR diagram for irradiance measurement of DN values (**c**).