## 5 Conclusions  
In this study, we have modeled gross primary production with the use of solar-induced chlorophyll fluorescence, precipitation and soil moisture, while considering differences in grass and crop plant functional types over the contiguous US. Our results show that correlation (root-mean-square error) between the FLUXNET and modeled gross primary production increases (decreases) from 0.41 (8.97 gC/m\({}^{2}\)/d) to 0.99 (0.13 gC/m\({}^{2}\)/d) with the addition of extra parameters such as precipitation and soil moisture and inclusion of the lead-lag relationship. Mean monthly GPP values calculated for summers in 2007-2012 with the use of the multiple linear regression approach and lead-lag are comparable to the FLUXNET measurements, while reference MODIS and BESS datasets demonstrate a tendency to underestimate GPP by approximately 50%. GPP values calculated with the use of the MLR approach and lead-lag also capture the drought trends successfully and are consistent with the observational trends from MODIS and BESS. In 2011, modeled GPP over Texas is approximately 50-75 gC/m\({}^{2}\)/month lower than in a normal yielding year of 2007; over the Great Plains, such a departure is comparable to that over Texas, as the area with production greater than 400 gC/m\({}^{2}\)/month was reduced significantly in July and August 2012. Our results demonstrate that GPP values based on various combinations of predictors, i.e., SIF, precipitation and soil moisture, have lower correlation coefficients and higher RMSE until and unless lead-lag relationship between the above mentioned predictors is considered. Since a plant is most vulnerable to water stress in its development period, we expect that plant production later in the season would depend on precipitation and soil moisture during the development stage. This study highlights the importance of water availability for plants during their development stage and its influence on plant production later in the season. It is also the first one to demonstrate that incorporation of plant physiological variations associated with water availability and demand at different stages of its lifetime can play an important role in estimation of plant production [97; 98; 99; 100], especially under drought conditions that are likely to increase in frequency and severity in future. This study further supports the claim that relationships between SIF and GPP are different for crops and grasses; using the statistically justified inclusion of regional precipitation and soil moisture, such relationships can be derived and used to improve GPP estimates. Conceptualization, M.H. and Z.-L.Y. ; methodology, Z.-L.Y. and M.H. ; formal analysis, M.H. ; investigation, M.H. ; resources, Z.-L.Y. ; writing--original draft preparation, M.H. ; writing--review and editing, M.H. and Z.-L.Y. ; visualization, M.H. ; supervision, Z.-L.Y. ; funding acquisition, Z.-L.Y. All authors have read and agreed to the published version of the manuscript. This study was supported by the National Key Research and Development Program of China (Grant No. 2016 YFA0600403) and funds from Jackson School of Geosciences. GME-2 v25 level 3 SIF data are available at [[http://avdc.gsfc.nasa.gov](http://avdc.gsfc.nasa.gov)]([http://avdc.gsfc.nasa.gov](http://avdc.gsfc.nasa.gov)). TRMM 3B42 and 3B43 products were obtained from [[https://mirador.gsfc.nasa.gov/](https://mirador.gsfc.nasa.gov/)]([https://mirador.gsfc.nasa.gov/](https://mirador.gsfc.nasa.gov/)). MODIS and FLUXNET GPP data are publicly available at [[https://lpdaac.usgs.gov/](https://lpdaac.usgs.gov/)]([https://lpdaac.usgs.gov/](https://lpdaac.usgs.gov/)) and [[https://fluxnet.ornl.gov/](https://fluxnet.ornl.gov/)]([https://fluxnet.ornl.gov/](https://fluxnet.ornl.gov/)), respectively. ESA CCI soil moisture products are provided by the European Space Agency at [[http://www.esa-soil](http://www.esa-soil)]([http://www.esa-soil](http://www.esa-soil)) moisture-ccl.org/.