Combining Process Modelling and LAI Observations to Diagnose Winter Wheat Nitrogen Status and Forecast Yield  
[PERSON]  
1 School of Geosciences and National Centre for Earth Observation, University of Edinburgh, Edinburgh EH9 3 FPE, UK [EMAIL_ADDRESS] (V.M.J. ; [PERSON].M. ); [PERSON]SS] (M.W)  
[PERSON]  
1 School of Geosciences and National Centre for Earth Observation, University of Edinburgh, Edinburgh EH9 3 FPE, UK [EMAIL_ADDRESS] (V.M.J. ; [PERSON].M. ); [PERSON]SS] (M.W)  
[PERSON]  
2 Agriculture, Horticulture and Engineering Science Department, Scotland's Rural College, Edinburgh EH9 3 GJC, UK; [PERSON]S] (A.F. ); [PERSON]RESS] (S.H. ); [PERSON]DDRESS] (R.R.) [PERSON]  
2 Agriculture, Horticulture and Engineering Science Department, Scotland's Rural College, Edinburgh EH9 3 GJC, UK; [PERSON]S] (A.F. ); [PERSON]RESS] (S.H. ); [PERSON]DDRESS] (R.R.) [PERSON]  
[PERSON]DDRESS] (R.R.) [PERSON]  
1 School of Geosciences and National Centre for Earth Observation, University of Edinburgh, Edinburgh EH9 3 FPE, UK; [EMAIL_ADDRESS] (V.M.J. ; [PERSON].M. ); [PERSON]SS] (M.W)  
[PERSON]  
2 Agriculture, Horticulture and Engineering Science Department, Scotland's Rural College, Edinburgh EH9 3 GJC, UK; [PERSON]S] (A.F. ); [PERSON]RESS] (S.H. ); [PERSON]DDRESS] (S.H. );  
aboveground biomass required for maximum growth at a given time and field condition [9]. The general decrease in N concentration observed with crop growth can be described using N dilution curves. These curves are typically established based on the relationship between N content and dry matter (e.g., shoot or leaf) from destructive sample measurements [10]. Crop leaf N content correlates with chlorophyll concentration and leaf area index (LAI) [11], both of which can be estimated from satellite Earth observation (EO) multispectral data [12; 13]. EO sensors can provide valuable synoptic and repetitive coverages of crops over large areas [14]. Optical EO data is, however, a function of the spectral characteristics (i.e., transmission, absorption, and reflectance properties) of the entire crop canopy, including leaf, stem and ears. Consequently, the spectral data is highly convolved and the covariance between traits, including chlorophyll content and LAI (and thus foliar N) [12], can complicate the retrievals of individual leaf traits. The retrieval of crop traits from EO is further confounded by spatial scaling mismatches. These mismatches exist between the ground measurements, used for calibrating retrieval models, and the spatial resolution of satellite sensors, as demonstrated in [PERSON] at al. [15]. The extent to which optical EO data can be used to provide estimates of crop N is also dependent on the availability of cloud-free imagery. Because the timing of N applications coincides with key crop growth stages, at least biweekly observations are required for the effective tracking of crop growth dynamics [16; 17]. This regularity in observations may not always be available in temperate latitudes under frequent cloud-cover. Process-based crop growth models can estimate daily crop growth and productivity in response to inputs of meteorology and management [18]. Crucially the models simulate interactions between these inputs. Crop models explicitly link crop development and leaf traits to leaf function (i.e., photosynthesis and growth) and yield potential [19]. In comparison to EO data, crop models can simulate the mechanisms leading to yield formation and, in doing so, provide an intrinsic explanation for spatial and temporal yield differences. The models can, therefore, be used as a decision-making tool to simulate crop productivity under different agricultural practices [20; 21; 22] including those concerning N application [5; 23]. Detailed crop models, including those that simulate leaf-level processes over multiple canopy layers [24], can have a high level of complexity and typically require an extensive number of parameters [25]. For instance, the WOFOST model uses 27 parameters to simulate phenological development and leaf growth alone [26].