scholarly journals Defining guidelines for ditch depth in drained Scots pine dominated peatland forests

Silva Fennica ◽  
2021 ◽  
Vol 55 (3) ◽  
Author(s):  
Hannu Hökkä ◽  
Ari Laurén ◽  
Leena Stenberg ◽  
Samuli Launiainen ◽  
Kersti Leppä ◽  
...  

We used a process-based hydrological model SUSI to improve guidelines for ditch network maintenance (DNM) operations on drained peatland forests. SUSI takes daily weather data, ditch depth, strip width, peat properties, and forest stand characteristics as input and calculates daily water table depth (WTD) at different distances from ditch. The study focuses on Scots pine ( L.) dominated stands which are the most common subjects of DNM. Based on a literature survey, and consideration of the tradeoffs between forest growth and detrimental environmental impacts, long term median July–August WTD of 0.35 m was chosen as a target WTD. The results showed that ditch depths required to reach such WTD depends strongly on climatic locations, stand volume, ditch spacing, and peat thickness and type. In typical ditch cleaning areas in Finland with parallel ditches placed about 40 m apart and tree stand volumes exceeding 45 m ha, 0.3–0.8 m deep ditches were generally sufficient to lower WTD to the targeted depth of 0.35 m. These are significantly shallower ditch depths than generally recommended in operational forestry. The main collector ditch should be naturally somewhat deeper to permit water outflow. Our study brings a firmer basis on environmentally sound forestry on drained peatlands.Pinus sylvestris3–1

Author(s):  
G. Bracho-Mujica ◽  
P.T. Hayman ◽  
V.O. Sadras ◽  
B. Ostendorf

Abstract Process-based crop models are a robust approach to assess climate impacts on crop productivity and long-term viability of cropping systems. However, these models require high-quality climate data that cannot always be met. To overcome this issue, the current research tested a simple method for scaling daily data and extrapolating long-term risk profiles of modelled crop yields. An extreme situation was tested, in which high-quality weather data was only available at one single location (reference site: Snowtown, South Australia, 33.78°S, 138.21°E), and limited weather data was available for 49 study sites within the Australian grain belt (spanning from 26.67 to 38.02°S of latitude, and 115.44 to 151.85°E of longitude). Daily weather data were perturbed with a delta factor calculated as the difference between averaged climate data from the reference site and the study sites. Risk profiles were built using a step-wise combination of adjustments from the most simple (adjusted series of precipitation only) to the most detailed (adjusted series of precipitation, temperatures and solar radiation), and a variable record length (from 10 to 100 years). The simplest adjustment and shortest record length produced bias of modelled yield grain risk profiles between −10 and 10% in 41% of the sites, which increased to 86% of the study sites with the most detailed adjustment and longest record (100 years). Results indicate that the quality of the extrapolation of risk profiles was more sensitive to the number of adjustments applied rather than the record length per se.


Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2731
Author(s):  
Sari Uusheimo ◽  
Tiina Tulonen ◽  
Jussi Huotari ◽  
Lauri Arvola

Agriculture contributes significantly to phosphorus and nitrogen loading in southern Finland. Climate change with higher winter air temperatures and precipitation may also promote loading increase further. We analyzed long-term nutrient trends (2001–2020) based on year-round weekly water sampling and daily weather data from a boreal small agricultural watershed. In addition, nutrient retention was studied in a constructed sedimentation pond system for two years. We did not find any statistically significant trends in weather conditions (temperature, precipitation, discharge, snow depth) except for an increase in discharge in March. Increasing trends in annual concentrations were found for nitrate, phosphate, and total phosphorus and total nitrogen. In fact, phosphate concentration increased in every season and nitrate concentration in other seasons except in autumn. Total phosphorus and total nitrogen concentrations increased in winter as well and total phosphorus also in summer. Increasing annual loading trend was found for total phosphorus, phosphate, and nitrate. Increasing winter loading was found for nitrate and total nitrogen, but phosphate loading increased in winter, spring, and summer. In the pond system, annual retention of total nitrogen was 1.9–4.8% and that of phosphorus 4.3–6.9%. In addition, 25–40% of suspended solids was sedimented in the ponds. Our results suggest that even small ponds can be utilized to decrease nutrient and material transport, but their retention efficiency varies between years. We conclude that nutrient loading from small boreal agricultural catchments, especially in wintertime, has already increased and is likely to increase even further in the future due to climate change. Thus, the need for new management tools to reduce loading from boreal agricultural lands becomes even more acute.


2003 ◽  
Vol 43 (8) ◽  
pp. 907 ◽  
Author(s):  
R. E. White ◽  
B. P. Christy ◽  
A. M. Ridley ◽  
A. E. Okom ◽  
S. R. Murphy ◽  
...  

Eleven experimental sites in the Sustainable Grazing Systems (SGS) national experiment were established in the high rainfall zone (HRZ, >600 mm/year) of Western Australia, Victoria and New South Wales to measure components of the water balance, and pathways of water movement, for a range of pastures from 1997 to 2001. The effect of widely spaced river red gums (Eucalyptus camaldulensis) in pasture, and of belts of plantation blue gums (E. globulus), was studied at 2 of the sites. The soil types tested ranged from Kurosols, Chromosols and Sodosols, with different subsoil permeabilities, to Hydrosols and Tenosols. The pasture types tested were kikuyu (Pennisetum clandestinum), phalaris (Phalaris aquatica), redgrass (Bothriochloa macra) and annual ryegrass (Lolium rigidum), with subterranean clover (Trifolium subterraneum) included. Management variables were set stocking v. rotational grazing, adjustable stocking rates, and level of fertiliser input. Soil, pasture and animal measurements were used to set parameters for the biophysical SGS pasture model, which simulated the long-term effects of soil, pasture type, grazing method and management on water use and movement, using as inputs daily weather data for 31 years from selected sites representing a range of climates. Measurements of mean maximum soil water deficit Sm were used to estimate the probability of surplus water occurring in winter, and the average amount of this surplus, which was highest (97–201 mm/year) for pastures in the cooler, winter-rainfall dominant regions of north-east and western Victoria and lowest (3–11 mm/year) in the warmer, lower rainfall regions of the eastern Riverina and Esperance, Western Australia. Kikuyu in Western Australia achieved the largest increase in Sm compared with annual pasture (55–71 mm), while increases due to phalaris were 18–45 mm, and those of native perennials were small and variable. Long-term model simulations suggested rooting depth was crucial in decreasing deep drainage, to about 50 mm/year for kikuyu rooting to 2.5 m, compared with 70–200 mm/year for annuals rooting to only 0.8 m. Plantation blue gums dried the soil profile to 5.25 m by an average of 400 mm more than kikuyu pasture, reducing the probability of winter surplus water to zero, and eliminating drainage below the root zone. Widely spaced river red gums had a much smaller effect on water use, and would need to number at least 14 trees per hectare to achieve extra soil drying of about 50 mm over a catchment. Soil type affected water use primarily through controlling the rooting depth of the vegetation, but it also changed the partitioning of surplus water between runoff and deep drainage. Strongly duplex soils such as Sodosols shed 50% or more surplus water as runoff, which is important for flushing streams, provided the water is of good quality. Grazing method and pasture management had only a marginal effect in increasing water use, but could have a positive effect on farm profitability through increased livestock production per hectare and improved persistence of perennial species.


Agriculture ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 232
Author(s):  
Iraj Emadodin ◽  
Daniel Ernesto Flores Corral ◽  
Thorsten Reinsch ◽  
Christof Kluß ◽  
Friedhelm Taube

The effects of climate change on agricultural ecosystems are increasing, and droughts affect many regions. Drought has substantial ecological, social, and economic consequences for the sustainability of agricultural land. Many regions of the northern hemisphere have not experienced a high frequency of meteorological droughts in the past. For understanding the implications of climate change on grassland, analysis of the long-term climate data provides key information relevant for improved grassland management strategies. Using weather data and grassland production data from a long-term permanent grassland site, our aims were (i) to detect the most important drought periods that affected the region and (ii) to assess whether climate changes and variability significantly affected forage production in the last decade. For this purpose, long-term daily weather data (1961–2019) and the standardized precipitation index (SPI), De Martonne index (IDM), water deficit (WD), dryness index (DI), yield anomaly index (YAI), and annual yield loss index (YL) were used to provide a scientific estimation. The results show that, despite a positive trend in DI and a negative trend in WD and precipitation, the time-series trends of precipitation, WD, and DI indices for 1961–2019 were not significant. Extreme dry conditions were also identified with SPI values less than −2. The measured annual forage yield (2007–2018) harvested in a four-cut silage system (with and without organic N-fertilization) showed a strong correlation with WD (R = 0.64; p ˂ 0. 05). The main yield losses were indicated for the years 2008 and 2018. The results of this study could provide a perspective for drought monitoring, as well as drought warning, in grassland in northwest Europe.


2019 ◽  
Vol 9 (2) ◽  
pp. 1
Author(s):  
Jurgen Garbrecht ◽  
X. C. Zhang ◽  
David Brown ◽  
Phillip Busteed

Long-term simulations in watershed hydrology, soil and nutrient transport, and sustainability of agricultural production systems require long-term weather records that are often not available at the location of interest. Generation of synthetic daily weather data is a common approach to augment limited weather observations. Here a synthetic daily weather generation model (called SYNTOR) is described. SYNTOR fulfills the traditional role of generating alternative weather realizations that have statistical properties similar to those of the parent historical weather it is intended to simulate. In addition, it has the capability to simulate daily weather records for climate change scenarios and storm intensification due to climate change. The various model components are briefly summarized and an application is presented for semi-arid climate conditions in west-central Oklahoma. SYNTOR generated daily weather compared well with observed weather values. Climate change is simulated by adjusting weather generation parameters to reflect the changed mean monthly weather values of climate projections. Storm intensification is approximated by increasing the top 10 percentile of storm distribution by a predefined amount based on previous studies of trends in United States precipitation. Further evaluation of published storm intensification values and associated uncertainties and spatial variability is recommended.


2015 ◽  
Vol 54 (2) ◽  
pp. 98-106 ◽  
Author(s):  
F. Hutton ◽  
J.H. Spink ◽  
D. Griffin ◽  
S. Kildea ◽  
D. Bonner ◽  
...  

Abstract Virus diseases are of key importance in potato production and in particular for the production of disease-free potato seed. However, there is little known about the frequency and distribution of potato virus diseases in Ireland. Despite a large number of samples being tested each year, the data has never been collated either within or across years. Information from all known potato virus testing carried out in the years 2006–2012 by the Department of Agriculture Food and Marine was collated to give an indication of the distribution and incidence of potato virus in Ireland. It was found that there was significant variation between regions, varieties, years and seed classes. A definition of daily weather data suitable for aphid flight was developed, which accounted for a significant proportion of the variation in virus incidence between years. This use of weather data to predict virus risk could be developed to form the basis of an integrated pest management approach for aphid control in Irish potato crops.


2021 ◽  
Vol 13 (11) ◽  
pp. 2131
Author(s):  
Jamon Van Den Hoek ◽  
Alexander C. Smith ◽  
Kaspar Hurni ◽  
Sumeet Saksena ◽  
Jefferson Fox

Accurate remote sensing of mountainous forest cover change is important for myriad social and ecological reasons, but is challenged by topographic and illumination conditions that can affect detection of forests. Several topographic illumination correction (TIC) approaches have been developed to mitigate these effects, but existing research has focused mostly on whether TIC improves forest cover classification accuracy and has usually found only marginal gains. However, the beneficial effects of TIC may go well beyond accuracy since TIC promises to improve detection of low illuminated forest cover and thereby normalize measurements of the amount, geographic distribution, and rate of forest cover change regardless of illumination. To assess the effects of TIC on the extent and geographic distribution of forest cover change, in addition to classification accuracy, we mapped forest cover across mountainous Nepal using a 25-year (1992–2016) gap-filled Landsat time series in two ways—with and without TIC (i.e., nonTIC)—and classified annual forest cover using a Random Forest classifier. We found that TIC modestly increased classifier accuracy and produced more conservative estimates of net forest cover change across Nepal (−5.2% from 1992–2016) TIC. TIC also resulted in a more even distribution of forest cover gain across Nepal with 3–5% more net gain and 4–6% more regenerated forest in the least illuminated regions. These results show that TIC helped to normalize forest cover change across varying illumination conditions with particular benefits for detecting mountainous forest cover gain. We encourage the use of TIC for satellite remote sensing detection of long-term mountainous forest cover change.


2017 ◽  
Vol 8 (2) ◽  
pp. 328-332
Author(s):  
J. Zhang ◽  
Y. Miao ◽  
W.D. Batchelor

Over-application of nitrogen (N) in rice (Oryza sativaL.) production in China is common, leading to low N use efficiency (NUE) and high environmental risks. The objective of this work was to evaluate the ability of the CERES-Rice crop growth model to simulate N response in the cool climate of Northeast China, with the long term goal of using the model to develop optimum N management recommendations. Nitrogen experiments were conducted from 2011–2015 in Jiansanjiang, Heilongjiang Province in Northeast China. The CERES-Rice model was calibrated for 2014 and 2015 and evaluated for 2011 and 2013 experiments. Overall, the model gave good estimations of yield across N rates for the calibration years (R2=0.89) and evaluation years (R2=0.73). The calibrated model was then run using weather data from 2001–2015 for 20 different N rates to determine the N rate that maximized the long term marginal net return (MNR) for different N prices. The model results indicated that the optimum mean N rate was 120–130 kg N ha–1, but that the simulated optimum N rate varied each year, ranging from 100 to 200 kg N ha–1. Results of this study indicated that the CERES-Rice model was able to simulate cool season rice growth and provide estimates of optimum regional N rates that were consistent with field observations for the area.


Author(s):  
Daniel Samano ◽  
Shubhayu Saha ◽  
Taylor Corbin Kot ◽  
JoNell E. Potter ◽  
Lunthita M. Duthely

Extreme weather events (EWE) are expected to increase as climate change intensifies, leaving coastal regions exposed to higher risks. South Florida has the highest HIV infection rate in the United States, and disruptions in clinic utilization due to extreme weather conditions could affect adherence to treatment and increase community transmission. The objective of this study was to identify the association between EWE and HIV-clinic attendance rates at a large academic medical system serving the Miami-Dade communities. The following methods were utilized: (1) Extreme heat index (EHI) and extreme precipitation (EP) were identified using daily observations from 1990–2019 that were collected at the Miami International Airport weather station located 3.6 miles from the studied HIV clinics. Data on hurricanes, coastal storms and flooding were collected from the National Oceanic and Atmospheric Administration Storms Database (NOAA) for Miami-Dade County. (2) An all-HIV clinic registry identified scheduled daily visits during the study period (hurricane seasons from 2017–2019). (3) Daily weather data were linked to the all-HIV clinic registry, where patients’ ‘no-show’ status was the variable of interest. (4) A time-stratified, case crossover model was used to estimate the relative risk of no-show on days with a high heat index, precipitation, and/or an extreme natural event. A total of 26,444 scheduled visits were analyzed during the 383-day study period. A steady increase in the relative risk of ‘no-show’ was observed in successive categories, with a 14% increase observed on days when the heat index was extreme compared to days with a relatively low EHI, 13% on days with EP compared to days with no EP, and 10% higher on days with a reported extreme weather event compared to days without such incident. This study represents a novel approach to improving local understanding of the impacts of EWE on the HIV-population’s utilization of healthcare, particularly when the frequency and intensity of EWE is expected to increase and disproportionately affect vulnerable populations. More studies are needed to understand the impact of EWE on routine outpatient settings.


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