Studying the effects of droughts and heavy rain events on DOC in Scot pine in Belgium

2020 ◽  
Author(s):  
Cristina Ariza Carricondo
Keyword(s):  
Climate Extremes ◽  
Heavy Rain ◽  
Drainage Water ◽  
Precipitation Extremes ◽  
Water Drainage ◽  
Precipitation Regime ◽  
Precipitation Regimes ◽  
Doc Export ◽  
Doc Production ◽  
Rain Events

<p><strong>Studying the effects of droughts and heavy rain events on DOC in Scot pine in Belgium</strong></p><p>Cristina Ariza-Carricondo(1,2), Marilyn Roland(1), Bert Gielen(1), Eric Struyf(1), Caroline Vincke(2) and Ivan Janssens(1).</p><p>(1) PLECO, University of Antwerp, Belgium. (2) Faculty of Bioscience Engineering & Earth and Life Institute, University of Louvain-la-Neuve, Louvain-la-Neuve, Belgium.</p><p>Climate extremes, including extreme rain events, are becoming more frequent and more extreme, and affect the carbon cycle of ecosystems. Very little is known about how Dissolved Organic Carbon (DOC) production and leaching are affected by such precipitation extremes while the relation between dissolved and gaseous exports of carbon under different precipitation regimes remains unexplored.</p><p>Hydrological conditions are the main driver of DOC leaching and alterations in precipitation patterns may cause large changes in the carbon balance of forests. To test the effects of precipitation extremes on DOC, we designed a manipulation experiment in a Scots pine forest in Belgium.</p><p>One of the challenges to estimate DOC export is the quantification of water drainage flow. In this study we used self-designed Zero Tension Lysimeters (ZTL) to capture leaching water and analyze its DOC-concentrations as well as other elements along profiles in the soil (up to 75cm depth), to study how DOC moves under different precipitation regimes. Different manipulation experiments were performed where we modified the precipitation regime simulating heavy rain events after different droughts as well as experiments where we modified the precipitation intensity over time. Leached water was collected at different depths at monthly intervals after natural rain events as well as after irrigations.</p><p>Preliminary results showed that drainage water transported DOC differently through the soil when different amounts of water were added. Furthermore, more frequent small rain events appear to favor the production of DOC as compared to less frequent high intensity rain events, while DOC production ceases during droughts.</p>

scholarly journals The Sensitivity of River Catchments to Dissolved Organic Carbon Release During Rain Events - A Study of Eight Catchments in Southern Patagonia

2021 ◽  
Author(s):  
Marta Pérez-Rodríguez ◽  
Harald Biester
Keyword(s):  
Organic Carbon ◽  
Dissolved Organic Carbon ◽  
Soil Layer ◽  
Dominant Factor ◽  
Carbon Pools ◽  
Patagonian Steppe ◽  
Precipitation Regimes ◽  
Southern Patagonia ◽  
Doc Export ◽  
Rain Events

Abstract Understanding the role of catchment properties is crucial for anticipating soil-derived dissolved organic carbon (DOC) export to aquatic systems, especially under changing climatic conditions. We present natural variations in DOC concentrations and fluxes in eight catchments differing in size (3 – 300 km 2 ), morphology (very steep to flat), and landscape type (Patagonian steppe, forest and peatland) along a steep precipitation gradient in remote pristine southern Patagonia, Chile. Discharge, precipitation and water chemical parameters were used to differentiate the mechanisms controlling DOC release in different catchment types. The results show large differences between catchments in terms of DOC concentrations (2 - 47 mg L -1 ) and fluxes (1 to 44 tons km -2 yr -1 ) but also in response to changes in precipitation. Small steep and forested catchments are the most reactive in terms of DOC export; specifically, changes in discharge produce fast, high and exponential increases in DOC release. DOC leaching by surface run-off through the organic soil layer is the main source of DOC during high precipitation events, and steep catchments became short-term hotspots for DOC export. In the flat catchments of the Patagonian steppe, the generally lower precipitation rates favour temporal accumulation of DOC in soils, and seasonal high discharge events produce one-off increases in DOC fluxes. Although peatlands constitute a large and continuous source of DOC export, the influence of discharge variation on DOC fluxes in peatland-dominated catchments appears to be low, despite the large carbon pools. Thus, in DOC catchments with similar precipitation regimes, morphology is the dominant factor determining ecosystem responses, where the steepest catchments show the highest sensitivity to rain events in terms of DOC export. Morphology and hydrological buffer capacity rather than the size of the carbon pools or precipitation intensity determine the export of DOC from catchments during strong rain events.

scholarly journals The climatic imprint of bimodal distributions in vegetation cover for western Africa

2016 ◽  
Vol 13 (11) ◽  
pp. 3343-3357 ◽  
Author(s):  
Zun Yin ◽  
Stefan C. Dekker ◽  
Bart J. J. M. van den Hurk ◽  
Henk A. Dijkstra
Keyword(s):  
Land Cover ◽  
Congo Basin ◽  
Shortwave Radiation ◽  
Mean Annual Precipitation ◽  
Above Ground Biomass ◽  
Precipitation Regime ◽  
Ground Biomass ◽  
Western Africa ◽  
Precipitation Regimes ◽  
Woody Cover

Abstract. Observed bimodal distributions of woody cover in western Africa provide evidence that alternative ecosystem states may exist under the same precipitation regimes. In this study, we show that bimodality can also be observed in mean annual shortwave radiation and above-ground biomass, which might closely relate to woody cover due to vegetation–climate interactions. Thus we expect that use of radiation and above-ground biomass enables us to distinguish the two modes of woody cover. However, through conditional histogram analysis, we find that the bimodality of woody cover still can exist under conditions of low mean annual shortwave radiation and low above-ground biomass. It suggests that this specific condition might play a key role in critical transitions between the two modes, while under other conditions no bimodality was found. Based on a land cover map in which anthropogenic land use was removed, six climatic indicators that represent water, energy, climate seasonality and water–radiation coupling are analysed to investigate the coexistence of these indicators with specific land cover types. From this analysis we find that the mean annual precipitation is not sufficient to predict potential land cover change. Indicators of climate seasonality are strongly related to the observed land cover type. However, these indicators cannot predict a stable forest state under the observed climatic conditions, in contrast to observed forest states. A new indicator (the normalized difference of precipitation) successfully expresses the stability of the precipitation regime and can improve the prediction accuracy of forest states. Next we evaluate land cover predictions based on different combinations of climatic indicators. Regions with high potential of land cover transitions are revealed. The results suggest that the tropical forest in the Congo basin may be unstable and shows the possibility of decreasing significantly. An increase in the area covered by savanna and grass is possible, which coincides with the observed regreening of the Sahara.

scholarly journals Vegetation Change and Its Response to Climate Extremes in the Arid Region of Northwest China

2021 ◽  
Vol 13 (7) ◽  
pp. 1230
Author(s):  
Simeng Wang ◽  
Qihang Liu ◽  
Chang Huang
Keyword(s):  
Arid Region ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Pearson Correlation ◽  
Time Lag ◽  
Climate Extremes ◽  
Northwest China ◽  
Precipitation Extremes ◽  
Temperature Extremes ◽  
Increasing Trend

Changes in climate extremes have a profound impact on vegetation growth. In this study, we employed the Moderate Resolution Imaging Spectroradiometer (MODIS) and a recently published climate extremes dataset (HadEX3) to study the temporal and spatial evolution of vegetation cover, and its responses to climate extremes in the arid region of northwest China (ARNC). Mann-Kendall test, Anomaly analysis, Pearson correlation analysis, Time lag cross-correlation method, and Least absolute shrinkage and selection operator logistic regression (Lasso) were conducted to quantitatively analyze the response characteristics between Normalized Difference Vegetation Index (NDVI) and climate extremes from 2000 to 2018. The results showed that: (1) The vegetation in the ARNC had a fluctuating upward trend, with vegetation significantly increasing in Xinjiang Tianshan, Altai Mountain, and Tarim Basin, and decreasing in the central inland desert. (2) Temperature extremes showed an increasing trend, with extremely high-temperature events increasing and extremely low-temperature events decreasing. Precipitation extremes events also exhibited a slightly increasing trend. (3) NDVI was overall positively correlated with the climate extremes indices (CEIs), although both positive and negative correlations spatially coexisted. (4) The responses of NDVI and climate extremes showed time lag effects and spatial differences in the growing period. (5) Precipitation extremes were closely related to NDVI than temperature extremes according to Lasso modeling results. This study provides a reference for understanding vegetation variations and their response to climate extremes in arid regions.

scholarly journals Comparison of Radar-Based Hail Detection Using Single- and Dual-Polarization

2019 ◽  
Vol 11 (12) ◽  
pp. 1436 ◽  
Author(s):  
Skripniková ◽  
Řezáčová
Keyword(s):  
Comparative Analysis ◽  
Heavy Rain ◽  
Radar Data ◽  
Severe Weather ◽  
Detection Methods ◽  
Polarimetric Radar ◽  
Dual Polarization ◽  
Rain Events ◽  
Single Polarization ◽  
Strong Agreement

The comparative analysis of radar-based hail detection methods presented here, uses C-band polarimetric radar data from Czech territory for 5 stormy days in May and June 2016. The 27 hail events were selected from hail reports of the European Severe Weather Database (ESWD) along with 21 heavy rain events. The hail detection results compared in this study were obtained using a criterion, which is based on single-polarization radar data and a technique, which uses dual-polarization radar data. Both techniques successfully detected large hail events in a similar way and showed a strong agreement. The hail detection, as applied to heavy rain events, indicated a weak enhancement of the number of false detected hail pixels via the dual-polarization hydrometeor classification. We also examined the performance of hail size detection from radar data using both single- and dual-polarization methods. Both the methods recognized events with large hail but could not select the reported events with maximum hail size (diameter above 4 cm).

Evaluation of GPROF V05 Precipitation Retrievals under Different Cloud Regimes

2021 ◽  
Keyword(s):  
Discrete Systems ◽  
The United States ◽  
Precipitation Variability ◽  
Substantial Fraction ◽  
Precipitation Regime ◽  
Surface Type ◽  
Precipitation Regimes ◽  
Channel Configuration ◽  
Global Precipitation ◽  
Cloud Regimes

AbstractPrecipitation retrievals from passive microwave satellite observations form the basis of many widely used precipitation products, but the performance of the retrievals depends on numerous factors such as surface type and precipitation variability. Previous evaluation efforts have identified bias dependence on precipitation regime, which may reflect the influence on retrievals of recurring factors. In this study, the concept of a regime-based evaluation of precipitation from the Goddard Profiling (GPROF) algorithm is extended to cloud regimes. Specifically, GPROF V05 precipitation retrievals under four different cloud regimes are evaluated against ground radars over the United States. GPROF is generally able to accurately retrieve the precipitation associated with both organized convection and less organized storms, which collectively produce a substantial fraction of global precipitation. However, precipitation from stratocumulus systems is underestimated over land and overestimated over water. Similarly, precipitation associated with trade cumulus environments is underestimated over land, while biases over water depend on the sensor’s channel configuration. By extending the evaluation to more sensors and suppressed environments, these results complement insights previously obtained from precipitation regimes, thus demonstrating the potential of cloud regimes in categorizing the global atmosphere into discrete systems.

Phytophthora nicotianae var. parasitica. [Descriptions of Fungi and Bacteria].

1964 ◽  
Author(s):  
G. M. Waterhouse
Keyword(s):  
Geographical Distribution ◽  
Citrus Fruit ◽  
Heavy Rain ◽  
Drainage Water ◽  
Phytophthora Nicotianae ◽  
Crown Rot ◽  
Fruit Rot ◽  
Piper Betle ◽  
Wide Range ◽  
Southern Rhodesia

Abstract A description is provided for Phytophthora nicotianae var. parasitica. Information is included on the disease caused by the organism, its transmission, geographical distribution, and hosts. HOSTS: On a very wide range of host plants comprising 58 families including: avocado, castor, Cinchona spp., citrus, cotton, eggplant, guava, lucerne, papaw, parsley, pineapple, Piper betle, rhubarb, sesame, strawberry, tomato. DISEASES: Damping-off of seedlings (tomato, castor, citrus, cotton); root rot (citrus, avocado, strawberry, lucerne); crown rot (parsley, rhubarb, strawberry, lucerne); brown stem rot of tobacco; stem canker and tip blight of Cinchona spp. ; leaf blight (castor, sesame, pineapple, Piper betle) and fruit rot (citrus, tomato, guava, papaw, eggplant). GEOGRAPHICAL DISTRIBUTION: Africa (Ethiopia, Mali, Madagascar, Mauritius, Morocco, Nigeria, Sierra Leone, Southern Rhodesia, Tanganyika); Asia (Burma, Ceylon, China, Formosa, India, Israel, Japan, Java, Malaya, Philippines); Australia & Oceania (Australia, Hawaii, Tasmania); Europe (Cyprus, France, Germany, Great Britain, Holland, Ireland, Italy, Poland, Portugal, U.S.S.R.); North America (Bermuda, Canada, Mexico, U.S.A.); Central America & West Indies (Costa Rica, Cuba, El Salvador, Guatemala, Jamaica, Montserrat, Puerto Rico, Trinidad);. South America (Argentina, Brazil, British Guiana, Colombia, Paraguay, Peru, Venezuela). TRANSMISSION: Soil-borne, spreading rapidly after heavy rain or where soil remains moist or water-logged (40: 470). Also recorded in drainage water in India and in reservoirs and canals supplying citrus groves in U.S.A. (23: 45; 39: 24). A method for determining a disease potential index in soil using lemon fruit has been described (38: 4). Also present in testas of seeds from diseased citrus fruit which may infect nursery seedbeds (37: 165).

scholarly journals Spatial structures and directionalities in Monsoonal precipitation over South Asia

2010 ◽  
Vol 17 (5) ◽  
pp. 371-381 ◽  
Author(s):  
N. Malik ◽  
N. Marwan ◽  
J. Kurths
Keyword(s):  
Indian Subcontinent ◽  
Monsoon Season ◽  
Daily Rainfall ◽  
Heavy Rain ◽  
Data Sets ◽  
Spatial Structures ◽  
Break Phase ◽  
Rainfall Events ◽  
Monsoonal Precipitation ◽  
Rain Events

Abstract. Precipitation during the monsoon season over the Indian subcontinent occurs in form of enormously complex spatiotemporal patterns due to the underlying dynamics of atmospheric circulation and varying topography. Employing methods from nonlinear time series analysis, we study spatial structures of the rainfall field during the summer monsoon and identify principle regions where the dynamics of monsoonal rainfall is more coherent or homogenous. Moreover, we estimate the time delay patterns of rain events. Here we present an analysis of two separate high resolution gridded data sets of daily rainfall covering the Indian subcontinent. Using the method of event synchronization (ES), we estimate regions where heavy rain events during monsoon happen in some lag synchronised form. Further using the delay behaviour of rainfall events, we estimate the directionalities related to the progress of such type of rainfall events. The Active (break) phase of a monsoon is characterised by an increase(decrease) of rainfall over certain regions of the Indian subcontinent. We show that our method is able to identify regions of such coherent rainfall activity.

scholarly journals Effect of natural rainfall on the migration characteristics of runoff and sediment on purple soil sloping cropland during different planting stages

2021 ◽  
Author(s):  
Yi Wang ◽  
Jiupai Ni ◽  
Chengsheng Ni ◽  
Sheng Wang ◽  
Deti Xie
Keyword(s):  
Sediment Yield ◽  
Soil Loss ◽  
Heavy Rain ◽  
Sediment Concentration ◽  
Purple Soil ◽  
Torrential Rain ◽  
Sediment Yields ◽  
Natural Rainfall ◽  
Sediment Loss ◽  
Rain Events

Abstract Due to the difficulty in monitoring subsurface runoff and sediment migration, their loss loads are still not clear and need further study. This study monitored water and soil loss occurring within experimental field plots for two calendar years under natural rainfall events. The sediment loss load was quantified by considering the corresponding water flow flux and its sediment concentration. The results showed that 60.04% of the runoff and 2.83% of the sediment were lost underground. The annual underground sediment loss reached up to 54.6 kg*ha−1*yr−1. A total of 69.68% of the runoff yield and 67.25% of the sediment yield were produced during the corn planting stage (CPS: March–July). Heavy rain and torrential rain events produced 94.45%, 65.46% of the annual runoff and 94.45%, 76.21% of the sediment yields during the corn-planting stage and summer fallow period (SFP: August–September). The rain frequency, rainfall, and rainfall duration of each planting stage significantly affected the resulting runoff and sediment yield. Measures aimed at the prevention and control of water-soil loss from purple soil sloping land should heavily focus on torrential rain and heavy rain events during the CPS and SFP. This paper aims to provide a practical reference for quantifying the water and soil loss from purple soil sloping cropland.

scholarly journals Export of <sup>134</sup>Cs and <sup>137</sup>Cs in the Fukushima river systems at heavy rains by Typhoon Roke in September 2011

2013 ◽  
Vol 10 (2) ◽  
pp. 2767-2790 ◽  
Author(s):  
S. Nagao ◽  
M. Kanamori ◽  
S. Ochiai ◽  
S. Tomihara ◽  
K. Fukushi ◽  
...  
Keyword(s):  
Nuclear Power ◽  
Heavy Rain ◽  
Rain Event ◽  
Normal Flow ◽  
Flow Conditions ◽  
Pulse Input ◽  
Heavy Rain Event ◽  
Coastal Marine ◽  
Rain Events ◽  
Heavy Rains

Abstract. Effects of a heavy rain event on radiocesium export were studied at stations on the Natsui River and the Same River in Fukushima Prefecture, Japan after Typhoon Roke during 21–22 September 2011, six months after the Fukushima Daiichi Nuclear Power Plant accident. Radioactivity of 134Cs and 137Cs in river waters was 0.011–0.098 Bq L−1 at normal flow conditions during July–September in 2011, but it increased to 0.85 Bq L−1 in high flow conditions by heavy rains occurring with the typhoon. The particulate fractions of 134Cs and 137Cs were 21–56% in the normal flow condition, but were close to 100% after the typhoon. These results indicate that the pulse input of radiocesium associated with suspended particles from land to coastal ocean occurred by the heavy rain event. Export flux of 134Cs and 137Cs by the heavy rain accounts for 30–50% of annual radiocesium flux in 2011. Results show that rain events are one factor controlling the transport and dispersion of radiocesium in river watersheds and coastal marine environments.

scholarly journals Improvement in WRF model prediction for heavy rain events over North Sumatra region using satellite data assimilation

2021 ◽  
Vol 893 (1) ◽  
pp. 012040
Author(s):  
Immanuel Jhonson Arizona Saragih ◽  
Huda Abshor Mukhsinin ◽  
Kerista Tarigan ◽  
Marzuki Sinambela ◽  
Marhaposan Situmorang ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Initial Data ◽  
Satellite Data ◽  
Wrf Model ◽  
Heavy Rain ◽  
Convective System ◽  
Large Area ◽  
Weather Forecasts ◽  
Rain Events ◽  
North Sumatra

Abstract Located adjacent to the Indian Ocean and the Malacca Strait as a source of water vapour, and traversed by the Barisan Mountains which raise the air orographically causing high diurnal convective activity over the North Sumatra region. The convective system that was formed can cause heavy rainfall over a large area. Weather Research and Forecasting (WRF) was a numerical weather model used to make objective weather forecasts. To improve the weather forecasts accuracy, especially for predict heavy rain events, needed to improve the output of the WRF model by the assimilation technique to correct the initial data. This research was conducted to compare the output of the WRF model with- and without assimilation on 17 June 2020 and 14 September 2020. Assimilation was carried out using the 3D-Var technique and warm starts mode on three assimilation schemes, i.e. DA-AMSU which used AMSU-A satellite data, DA-MHS which used MHS satellite data, and DA-BOTH which used both AMSU-A and MHS satellite data. Model output verification was carried out using the observational data (AWS, AAWS, and ARG) and GPM-IMERG data. The results showed that the satellite data assimilation corrects the WRF model initial data, so as increasing the accuracy of rainfall predictions. The DA-BOTH scheme provided the best improvement with a final weighted performance score of 0.64.

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