Statistics for the Evaluation and Comparison of Models

Copyright 1985 by the American Geophysical Union.Procedures that may be used to evaluate the operational performance of a wide spectrum of geophysical models are introduced. Primarily using a complementary set of difference measures, both model accuracy and precision can be meaningfully estimated, regardless of whether the model predictions are manifesteda s scalars,d irections,o r vectors.I t is additionally suggestedth at the reliability of the accuracy and precision measures can be determined from bootstrap estimates of confidence and significance. Recommendedp roceduresa re illustrated with a comparativee valuation of two models that estimate wind velocity over the South Atlantic Bight

First-order decay models to describe soil C-CO2 Loss after rotary tillage

To further understand the impact of tillage on CO2 emission, the applicability of two conceptual models was tested, which describe the CO2 emission after tillage as a function of the non-tilled emission plus a correction due to the tillage disturbance. Models assume that C in readily decomposable organic matter follows a first-order reaction kinetics equation as: dCsoil (t) / dt = -k Csoil (t), and that soil C-CO2 emission is proportional to the C decay rate in soil, where Csoil(t) is the available labile soil C (g m-2) at any time (t) and k is the decay constant (time-1). Two possible assumptions were tested to determine the tilled (F T) fluxes: the decay constants (k) of labile soil C before and after tillage are different (Model 1) or not (Model 2). Accordingly, C flux relationships between non-tilled (F NT) and tilled (F T) conditions are given by: F T = F NT + a1 e-a2t (model 1) and F T = a3 F NT e-a4t (model 2), where t is time after tillage. Predicted and observed CO2 fluxes presented good agreement based on the coefficient of determination (R² = 0.91). Model comparison revealed a slightly improved statistical fit of model 2, where all C pools are assigned with the same k constant. Rotary speed was related to increases in the amount of labile C available and to changes of the mean resident labile C pool available after tillage. This approach allows describing the temporal variability of tillage-induced emissions by a simple analytical function, including non-tilled emission plus an exponential term modulated by tillage and environmentally dependent parameters.Para entendimento do impacto do preparo do solo sobre as emissões de CO2 desenvolvemos e aplicamos dois modelos conceituais que são capazes de prever a emissão de CO2 do solo após seu preparo em função da emissão da parcela sem distúrbio, acrescida de uma correção devido ao preparo. Os modelos assumem que o carbono presente na matéria orgânica lábil segue uma cinética de decaimento de primeira ordem, dada pela seguinte equação: dCsoil (t) / dt = -k Csoil (t), e que a emissão de C-CO2 é proporcional a taxa de decaimento do C no solo, onde Csolo(t) é a quantidade de carbono lábil disponível no tempo (t) e k é a constante de decaimento (tempo-1). Duas suposições foram testadas para determinação das emissões após o preparo do solo (Fp): a constante de decaimento do carbono lábil do solo (k) antes e após o preparo é igual (Modelo 1) ou desigual (Modelo 2). Conseqüentemente, a relação entre os fluxos de C das parcelas sem distúrbio (F SD) e onde o preparo do solo foi conduzido (F P) são dadas por: F P = F SD + a1 e-a2t (modelo 1) e F P = a3 F SD e-a4t (modelo 2), onde t é o tempo após o preparo. Fluxos de CO2 previstos e observados relevam um bom ajuste dos resultados com coeficiente de determinação (R²) tão alto quanto 0,91. O modelo 2 produz um ajuste ligeiramente superior quando comparado com o outro modelo. A velocidade das pás da enxada rotativa foi relacionada a um aumento na quantidade de carbono lábil e nas modificações do tempo de residência médio do carbono lábil do solo após preparo. A vantagem desta metodologia é que a variabilidade temporal das emissões induzidas pelo preparo do solo pode ser descrita a partir de uma função analítica simples, que inclui a emissão da parcela sem distúrbio e um termo exponencial modulado por parâmetros dependentes do preparo e de condições ambientais onde o experimento foi conduzido

The role of soil water availability in potential rainfed rice productivity in Bangladesh: applications of the CERES-Rice mode

Soil water stress and its impact on the monsoon season potential rainfed rice productivity in Bangladesh is investigated. A crop growth simulation model, CERES-Rice, is applied to 16 locations representative of the major rice growing regions of Bangladesh to determine the impact of soil water stress on the regional scale potential yield for four transplanting dates: 1 June, 1 July, 15 July, and 15 August. A quantified estimate of potential yield loss for four regions and for Bangladesh as a whole is calculated for water stress during flowering and maturing stages. For example, in Bangladesh, average potential yield for 1 June transplanting date, under low water stress during both flowering and maturing stages, is 7218 kg ha–1. On the other hand, high water stress during maturing, flowering, and both flowering and maturing stages, results in yield reduction of 37%, 46%, and 73%, respectively. Model applications show that for a 15 July transplanting date, average potential yield under low water stress during both flowering and maturing stages is 6077 kg ha–1. However, the loss of potential yields are 39%, 57%, and 70% for this transplanting date, due to high water stress during maturing, flowering, and both flowering and maturing stages, respectively. For a 15 August transplanting, average potential yield is 4217 kg ha–1 and loss is 32%, 38%, and 38% for high water stress during maturing, flowering, and both flowering and maturing stages, respectively. The results of this study can be further utilized for future agricultural planning in Bangladesh and other parts of monsoonal Asia

The CERES-Rice Model-Based Estimates of Potential Monsoon Season Rainfed Rice Productivity in Bangladesh

Agricultural practices in Bangladesh are largely dependent on the monsoonal rainfall. Historically, Bangladesh often experiences severe droughts and floods during the monsoon months, with significant crop losses during both extreme conditions. This article provides a quantitative assessment of potential monsoon-season aman rice for four transplanting dates: 1 June, 1 July, 15 July, and 15 August. A crop-growth simulation model, the CERES-Rice, is applied to sixteen locations representing major rice-growing regions of Bangladesh to determine baseline yield estimates for four transplanting dates. The applications were conducted for 1975 through 1987. Average potential yield in Bangladesh is 6,907, 5,039, 3,637, and 1,762 kg ha–1 for the above transplanting dates, respectively. In other words, Bangladesh would obtain 27 percent, 48 percent, and 75 percent less yield for 1 July, 15 July, and 15 August transplanting, respectively, than for 1 June transplanting. Potential yield vulnerability is the least for 1 June transplanting (up to 5 percent) and the highest (up to 66 percent) for 15 July transplanting date. The model applications show that regional variations exist for potential yield and yield vulnerability for a particular transplanting date. In addition, response of yield and vulnerability for a region changes with transplanting dates

Using Wavelet Analysis to Examine Bark Microrelief

An important metric of canopy structure, bark microrelief affects both the hydrology and biogeochemistry of forests. Increased bark microrelief leads to reduced stemflow volumes and higher concentrations of stemflow leachates and nutrient-ions. Consequently, an improved representation of bark microrelief would be useful to describe the influence of various tree species on water and solute contributions to the forest floor. Most existing methods to quantify bark microrelief are ‘global’ measures; that is, they provide a single number that represents the overall bark microrelief of the entire perimeter of the tree. To remedy this, wavelet analysis of LaserBark™ automated tree measurement system data is proposed and described to quantify variations in bark microrelief around the perimeter of the tree. This measure describes the spatial differences in bark microrelief and allows representation of trees that exhibit directional variability in bark microrelief due to natural or anthropogenic effects. The results show that wavelet analysis is effective in quantifying both bark microrelief and large-scale tree asymmetry. The radial component highlights changes in the depth of bark microrelief while the tangential component relates to the distance between bark furrows in the bark cross section. Thus, wavelet analysis may be a useful tool for comparing bark structure that varies, for example, within- and between-tree species, at different stages of tree growth, and among trees grown under different environmental conditions