Development of models to predict Pinus radiata productivity throughout New Zealand

2010 ◽  
Vol 40 (3) ◽  
pp. 488-499 ◽  
Author(s):  
Michael S. Watt ◽  
David J. Palmer ◽  
Mark O. Kimberley ◽  
Barbara K. Höck ◽  
Tim W. Payn ◽  
...  
Keyword(s):  
New Zealand ◽  
Pinus Radiata ◽  
Root Zone ◽  
Water Storage ◽  
Site Index ◽  
Parent Material ◽  
Data Set ◽  
Final Model ◽  
Soil Parent Material ◽  
Zone Water

Development of spatial surfaces describing variation in productivity across broad landscapes at a fine resolution would be of considerable use to forest managers as decision support tools to optimize productivity. In New Zealand, the two most widely used indices to quantify productivity of Pinus radiata D. Don are Site Index and 300 Index. Using an extensive national data set comprising a comprehensive set of national extent maps, multiple regression models and spatial surfaces of these indices for P. radiata were constructed. The final models accounted for 64% and 53%, respectively, of the variance in Site Index and 300 Index. For Site Index, variables included in the final model in order of importance were mean annual air temperature, fractional mean annual available root-zone water storage, mean annual windspeed, length and slope factor, categories describing Land Environments of New Zealand (LENZ), and major soil parent material. The variables included in the final model of 300 Index in order of importance included the degree of ground frost during autumn, fractional mean annual available root-zone water storage, categories describing LENZ, vegetation classification, foliar nitrogen, taxonomic soil order, and major soil parent material. These results highlight the utility of thematic spatial layers as driving variables in the development of productivity models.

scholarly journals WAYS v1: a hydrological model for root zone water storage simulation on a global scale

2019 ◽  
Vol 12 (12) ◽  
pp. 5267-5289 ◽  
Author(s):  
Ganquan Mao ◽  
Junguo Liu
Keyword(s):  
Spatial Heterogeneity ◽  
Soil Water ◽  
Regional Differences ◽  
Hydrological Model ◽  
Root Zone ◽  
Water Storage ◽  
Global Scale ◽  
Distribution Model ◽  
Lumped Model ◽  
Zone Water

Abstract. The soil water stored in the root zone is a critical variable for many applications, as it plays a key role in several hydrological and atmospheric processes. Many studies have been conducted to obtain reliable information on soil water in the root zone layer. However, most of them are mainly focused on the soil moisture within a certain depth rather than the water stored in the entire rooting system. In this work, a hydrological model named the Water And ecosYstem Simulator (WAYS) is developed to simulate the root zone water storage (RZWS) on a global scale. The model is based on a well-validated lumped model and has now been extended to a distribution model. To reflect the natural spatial heterogeneity of the plant rooting system across the world, a key variable that influences RZWS, i.e., root zone storage capacity (RZSC), is integrated into the model. The newly developed model is first evaluated based on runoff and RZWS simulations across 10 major basins. The results show the ability of the model to mimic RZWS dynamics in most of the regions through comparison with proxy data, the normalized difference infrared index (NDII). The model is further evaluated against station observations, including flux tower and gauge data. Despite regional differences, generally good performance is found for both the evaporation and discharge simulations. Compared to existing hydrological models, WAYS's ability to resolve the field-scale spatial heterogeneity of RZSC and simulate RZWS may offer benefits for many applications, e.g., agriculture and land–vegetation–climate interaction investigations. However, the results from this study suggest an additional evaluation of RZWS is required for the regions where the NDII might not be the correct proxy.

scholarly journals New interpretation of the role of water balance in an extended Budyko hypothesis in arid regions

2016 ◽  
Vol 20 (1) ◽  
pp. 393-409 ◽  
Author(s):  
C. Du ◽  
F. Sun ◽  
J. Yu ◽  
X. Liu ◽  
Y. Chen
Keyword(s):  
Steady State ◽  
Water Balance ◽  
Water Supply ◽  
Arid Regions ◽  
Root Zone ◽  
Water Storage ◽  
Unsteady State ◽  
Monthly Water Balance ◽  
Storage Change ◽  
Zone Water

Abstract. The Budyko hypothesis (BH) is an effective approach to investigating long-term water balance at large basin scale under steady state. The assumption of steady state prevents applications of the BH to basins, which is unclosed, or with significant variations in root zone water storage, i.e., under unsteady state, such as in extremely arid regions. In this study, we choose the Heihe River basin (HRB) in China, an extremely arid inland basin, as the study area. We firstly use a calibrated and then validated monthly water balance model, i.e., the abcd model, to quantitatively determine annual and monthly variations of water balance for the sub-basins and the whole catchment of the HRB, and find that the roles of root zone water storage change and that of inflow from upper sub-basins in monthly water balance are significant. With the recognition of the inflow water from other regions and the root zone water storage change as additional possible water sources to evapotranspiration in unclosed basins, we further define the equivalent precipitation (Pe) to include local precipitation, inflow water and root zone water storage change as the water supply in the Budyko framework. With the newly defined water supply, the Budyko curve can successfully describe the relationship between the evapotranspiration ratio and the aridity index at both annual and monthly timescales, whilst it fails when only the local precipitation being considered. Adding to that, we develop a new Fu-type Budyko equation with two non-dimensional parameters (ω and λ) based on the deviation of Fu's equation. Over the annual timescale, the new Fu-type Budyko equation developed here has more or less identical performance to Fu's original equation for the sub-basins and the whole catchment. However, over the monthly timescale, due to large seasonality of root zone water storage and inflow water, the new Fu-type Budyko equation generally performs better than Fu's original equation. The new Fu-type Budyko equation (ω and λ) developed here enables one to apply the BH to interpret regional water balance over extremely dry environments under unsteady state (e.g., unclosed basins or sub-annual timescales).

scholarly journals A hydrological model for root zone water storage simulation on a global scale

2019 ◽  
Author(s):  
Ganquan Mao ◽  
Junguo Liu
Keyword(s):  
Soil Water ◽  
Hydrological Model ◽  
Storage Capacity ◽  
Root Zone ◽  
Water Storage ◽  
Global Scale ◽  
Distribution Model ◽  
Lumped Model ◽  
Zone Water ◽  
Strong Capacity

Abstract. The soil water stored in the root zone is a critical variable for many applications as it plays key role in several hydrological and atmospheric processes. Many studies have been done to obtain reliable soil water information in the root zone layer. However, most of them are mainly focused on the soil moisture in a certain depth rather than the water stored in the entire rooting system. In this work, a hydrological model is developed to simulate the root zone water storage (RZWS) on a global scale. The model is based on a well validated lumped model and has been extended now to a distribution model. To reflect the natural spatial heterogeneity of the plant rooting system across the world, a key variable that influencing the RZWS, i.e. root zone storage capacity (RZSC), is integrated into the model. The newly developed model is evaluated on runoff and RZWS simulation across ten major basins. The evaluation of runoff indicates the strong capacity of the model for monthly simulation with a good performance on time series and distribution depiction. Results also show the ability of the model for RZWS dynamics mimicing in most of the regions. This model may offer benefits for many applications due to its ability for RZWS simulation. However, attentions need to also be paid for application as the high latitude regions are not investigated by this work due to the incomplete latitudinal coverage of the RZSC. Therefore, the performance of the model in such regions are not justified.

Subsurface Water Retention Technology Improves Root Zone Water Storage for Corn Production on Coarse-Textured Soils

2015 ◽  
Vol 14 (7) ◽  
pp. vzj2014.11.0166 ◽  
Author(s):  
Andrey K Guber ◽  
Alvin J. M. Smucker ◽  
Samrawi Berhanu ◽  
James M. L. Miller
Keyword(s):  
Water Retention ◽  
Root Zone ◽  
Water Storage ◽  
Subsurface Water ◽  
Corn Production ◽  
Zone Water

Predicting the severity of Cyclaneusma minus on Pinus radiata under current climate in New Zealand

2012 ◽  
Vol 42 (4) ◽  
pp. 667-674 ◽  
Author(s):  
Michael S. Watt ◽  
Carol A. Rolando ◽  
David J. Palmer ◽  
Lindsay S. Bulman
Keyword(s):  
New Zealand ◽  
Pinus Radiata ◽  
High Elevation ◽  
Exponential Model ◽  
Stand Age ◽  
Spatial Covariance ◽  
Validation Data ◽  
Data Set ◽  
Needle Cast ◽  
Current Climate

Despite being a damaging foliar disease of Pinus species, little research has characterized spatial variation in disease severity of Cyclaneusma needle cast at a macroscale. Using an extensive data set describing Cyclaneusma needle cast (Ssev) on plantation-grown Pinus radiata D. Don stands distributed widely across New Zealand, the objectives of this research were to (i) develop a regression model describing Ssev, (ii) use this model to identify key drivers of Ssev and their functional form and relative importance, and (iii) develop spatial predictions of Ssev for New Zealand P. radiata under current climate. Using an independent validation data set, the final model accounted for 73% of the variance in Ssev using four significant (P < 0.001) explanatory variables and an isotrophic exponential model to account for the spatial covariance in the data. Ssev was most sensitive to elevation followed by mean winter air temperature, mean relative humidity during July, and then stand age. Ssev increased to a maximum at mean winter air temperatures of between 7 and 9 °C before declining. Relationships between Ssev and all other variables were linear and positive. Spatial predictions of Ssev varied widely throughout New Zealand. Values of Ssev were highest in moderately warm, wet, and humid high-elevation environments located in the central North Island. In contrast, relatively low values of Ssev were predicted in drier eastern and southern regions of New Zealand.

scholarly journals Plants as sensors: vegetation response to rainfall predicts root-zone water storage capacity in Mediterranean-type climates

2020 ◽  
Vol 15 (10) ◽  
pp. 104074
Author(s):  
David N Dralle ◽  
W Jesse Hahm ◽  
Daniella M Rempe ◽  
Nathaniel Karst ◽  
Leander D L Anderegg ◽  
...  
Keyword(s):  
Storage Capacity ◽  
Root Zone ◽  
Water Storage ◽  
Vegetation Response ◽  
Water Storage Capacity ◽  
Zone Water

scholarly journals Technical note: Accounting for snow in the estimation of root-zone water storage capacity from precipitation and evapotranspiration fluxes

2020 ◽  
Author(s):  
David N. Dralle ◽  
W. Jesse Hahm ◽  
K. Dana Chadwick ◽  
Erica McCormick ◽  
Daniella M. Rempe
Keyword(s):  
Sierra Nevada ◽  
Hydrological Modeling ◽  
Storage Capacity ◽  
Root Zone ◽  
Water Storage ◽  
Original Method ◽  
Technical Note ◽  
Simple Extension ◽  
Water Storage Capacity ◽  
Zone Water

Abstract. A common parameter in hydrological modeling frameworks is root-zone water storage capacity (SR[L]), which mediates plant-water availability during dry periods and the partitioning of rainfall between runoff and evapotranspiration. Recently, a simple flux-tracking based approach was introduced to estimate the value of SR (Wang-Erlandsson et al., 2016). Here, we build upon this original method, which we argue may overestimate SR in snow-dominated catchments due to snow melt and evaporation processes. We propose a simple extension to the method presented by Wang-Erlandsson et al. (2016), and show that the approach provides a more conservative minimum estimate of SR in snow-dominated watersheds. This SR dataset is available at 1 km resolution for the continental United States, along with the full analysis code, on Google Colaboratory and Earth Engine platforms. We highlight differences between the original and new methods across the rain-snow transition in the Southern Sierra Nevada, California, USA. As climate warms and precipitation increasingly arrives as rain instead of snow, the subsurface may be an increasingly important reservoir for storing plant-available water between wet and dry seasons; improved estimates of SR will therefore better clarify the future role of the subsurface as a storage reservoir that can sustain forests during seasonal dry periods and episodic drought.

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