Application of Spatially Distributed Calibrated Hydrological Model in Evapotranspiration Simulation of Three Gorges Reservoir Area of China:A Case Study in the Madu River Basin

Evapotranspiration(ET)is the key to the water cycle process and an important factor for studying near-surface water and heat balance.Accurately estimating ET is significant for hydrology,meteorology,ecology,agriculture,etc..This paper simulates ET in the Madu River Basin of Three Gorges Reservoir Area of China during 2009-2018 based on the Soil and Water Assessment Tool(SWAT)model,which was calibrated and validated using the MODIS(Moderate-resolution Imaging Spectroradiometer)/Terra Net ET 8-Day L4 Global 500 m SIN Grid(MOD16A2)dataset and measured ET.Two calibration strategies(lumped calibration(LC)and spatially distributed calibration(SDC))were used.The basin was divided into 34 sub-basins,and the coefficient of determination(R^(2))and NashSutcliffe efficiency coefficient(NSE)of each sub-basin were greater than 0.6 in both the calibration and validation periods.The R2 and NSE were higher in the validation period than those in the calibration period.Compared with the measured ET,the accuracy of the model on the daily scale is:R^(2)=0.704 and NSE=0.759(SDC results).The model simulation accuracy of LC and SDC for the sub-basin scale was R^(2)=0.857,R^(2)=0.862(monthly)and R^(2)=0.227,R^(2)=0.404(annually),respectively;for the whole basin scale was R^(2)=0.902,R^(2)=0.900(monthly)and R^(2)=0.507 and R^(2)=0.519(annually),respectively.The model performed acceptably,and SDC performed the best,indicating that remote sensing data can be used for SWAT model calibration.During 2009-2018,ET generally increased in the Madu River Basin(SDC results,7.21 mm/yr),with a multiyear average value of 734.37 mm/yr.The annual ET change rate for the sub-basin was relatively low upstream and downstream.The linear correlation analysis between ET and meteorological factors shows that on the monthly scale,precipitation,solar radiation and daily maximum and minimum temperature were significantly correlated with ET;annually,solar radiation and wind speed had a moderate correlation with ET.The correlation between maximum temperature and ET is best on the monthly scale(Pearson correlation coefficient R=0.945),which may means that the increasing ET originating from increasing temperature(global warming).However,the sub-basins near Shennongjia Nature Reserve that are in upstream have a negative ET change rate,which means that ET decreases in these sub-basins,indicating that the’Evaporation Paradox’exists in these sub-basins.This study explored the potential of remote-sensing-based ET data for hydrological model calibration and provides a decision-making reference for water resource management in the Madu River Basin.

Responses of water productivity to irrigation and N supply for hybrid maize seed production in an arid region of Northwest China

Water and nitrogen（N） are generally two of the most important factors in determining the crop productivity. Proper water and N managements are prerequisites for agriculture sustainable development in arid areas. Field experiments were conducted to study the responses of water productivity for crop yield（WP_（Y-ET）） and final biomass（WP_（B-ET）） of film-mulched hybrid maize seed production to different irrigation and N treatments in the Hexi Corridor, Northwest China during April to September in 2013 and also during April to September in 2014. Three irrigation levels（70%–65%, 60%–55%, and 50%–45% of the field capacity） combined with three N rates（500, 400, and 300 kg N/hm^2） were tested in 2013. The N treatments were adjusted to 500, 300, and 100 kg N/hm^2 in 2014. Results showed that the responses of WP_（Y-ET） and WP_（B-ET） to different irrigation amounts were different. WP_（Y-ET） was significantly reduced by lowering irrigation amounts while WP_（B-ET） stayed relatively insensitive to irrigation amounts. However, WP_（Y-ET） and WP_（B-ET） behaved consistently when subjected to different N treatments. There was a slight effect of reducing N input from 500 to 300 kg/hm^2 on the WP_（Y-ET） and WP_（B-ET）, however, when reducing N input to 100 kg/hm^2, the values of WP_（Y-ET） and WP_（B-ET） were significantly reduced. Water is the primary factor and N is the secondary factor in determining both yield（Y） and final biomass（B）. Partial factor productivity from applied N（PFP_N） was the maximum under the higher irrigation level and in lower N rate（100–300 kg N/hm^2） in both years（2013 and 2014）. Lowering the irrigation amount significantly reduced evapotranspiration（ET）, but ET did not vary with different N rates（100–500 kg N/hm^2）. Both Y and B had robust linear relationships with ET, but the correlation between B and ET（R^2=0.8588） was much better than that between Y and ET（R^2=0.6062）. When ET increased, WP_（Y-ET） linearly increased and WP_（B-ET） decreased. Taking the indices of Y, B, WP_（Y-ET）, WP_（B-ET） and PFP_N into account, a higher irrigation level（70%–65% of the field capacity） and a lower N rate（100–300 kg N/hm^2） are recommended to be a proper irrigation and N application strategy for plastic film-mulched hybrid maize seed production in arid Northwest China.

Effects of Drought on Net Primary Productivity:Roles of Temperature,Drought Intensity,and Duration

Northeast China has experienced frequent droughts over the past fifteen years. However, the effects of droughts on net primary productivity(NPP) in Northeast China remain unclear. In this paper, the droughts that occurred in Northeast China between 1999 and 2013 were identified using the Standardized Precipitation Evapotranspiration Index(SPEI). The NPP standardized anomaly index(NPP-SAI) was used to evaluate NPP anomalies. The years of 1999, 2000, 2001, and 2007 were further investigated in order to explore the influence of droughts on NPP at different time scales(3, 6, and 12 months). Based on the NPP-SAI of normal areas, we found droughts overall decreased NPP by 112.06 Tg C between 1999 and 2013. Lower temperatures at the beginning of the growing season could cause declines in NPP by shortening the length of the growing season. Mild drought or short-term drought with higher temperatures might increase NPP, and weak intensity droughts intensified the lag effects of droughts on NPP.