scholarly journals Isotope hydrology model and stable isotopes in sediment records from Balkan lakes

2020 ◽  
Keyword(s):  
Land Surface ◽  
Climatic Factors ◽  
Strong Dependence ◽  
Lake Basin ◽  
Strongly Correlated ◽  
Key Factors ◽  
Run Off ◽  
Karst Systems ◽  
Lake Systems ◽  
Closed Lake

<p>Isotope mass balance in lake systems is strongly correlated with several climatic factors such as temperature, evaporation, precipitation and air moisture. On the other hand, the sedimentary budget of lake basins driven by climate, tectonic and/or human impact is an essential pool of environmental records. Precipitation, springs and lake water δD and δ18O isotope data were used in order to understand the key factors for the hydrological balance of Balkan lakes in West Macedonia. In general, it is concluded that the open lake Ohrida and the semi-closed lake Kastoria are more buffered hydrological as karst systems and less sensitive to evaporation effect, in contrast to the closed lake system of Prespes that present a strong dependence on climate seasonality. Based on oxygen isotopes in bulk sediments, it is concluded that in Kastoria lake basin an increased run-off on the land surface, probably under a more humid period, in 2.4 kyr BP disturbed the transition to a drier regime from mid/late Holocene to present.</p>

scholarly journals An Assessment of Drought Stress in Tea Estates Using Optical and Thermal Remote Sensing

2021 ◽  
Vol 13 (14) ◽  
pp. 2730
Author(s):  
Animesh Chandra Das ◽  
Ryozo Noguchi ◽  
Tofael Ahamed
Keyword(s):  
Remote Sensing ◽  
Drought Stress ◽  
Land Surface ◽  
Climatic Factors ◽  
Standardized Precipitation Index ◽  
Landsat 8 ◽  
Drought Frequency ◽  
Moisture Index ◽  
Area Index ◽  
Drought Period

Drought is one of the detrimental climatic factors that affects the productivity and quality of tea by limiting the growth and development of the plants. The aim of this research was to determine drought stress in tea estates using a remote sensing technique with the standardized precipitation index (SPI). Landsat 8 OLI/TIRS images were processed to measure the land surface temperature (LST) and soil moisture index (SMI). Maps for the normalized difference moisture index (NDMI), normalized difference vegetation index (NDVI), and leaf area index (LAI), as well as yield maps, were developed from Sentinel-2 satellite images. The drought frequency was calculated from the classification of droughts utilizing the SPI. The results of this study show that the drought frequency for the Sylhet station was 38.46% for near-normal, 35.90% for normal, and 25.64% for moderately dry months. In contrast, the Sreemangal station demonstrated frequencies of 28.21%, 41.02%, and 30.77% for near-normal, normal, and moderately dry months, respectively. The correlation coefficients between the SMI and NDMI were 0.84, 0.77, and 0.79 for the drought periods of 2018–2019, 2019–2020 and 2020–2021, respectively, indicating a strong relationship between soil and plant canopy moisture. The results of yield prediction with respect to drought stress in tea estates demonstrate that 61%, 60%, and 60% of estates in the study area had lower yields than the actual yield during the drought period, which accounted for 7.72%, 11.92%, and 12.52% yield losses in 2018, 2019, and 2020, respectively. This research suggests that satellite remote sensing with the SPI could be a valuable tool for land use planners, policy makers, and scientists to measure drought stress in tea estates.

scholarly journals Remote sensing of environmental risk factors for malaria in different geographic contexts

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Andrea McMahon ◽  
Abere Mihretie ◽  
Adem Agmas Ahmed ◽  
Mastewal Lake ◽  
Worku Awoke ◽  
...  
Keyword(s):  
Risk Factors ◽  
Surface Water ◽  
Environmental Risk ◽  
Land Surface ◽  
Climatic Factors ◽  
Environmental Risk Factors ◽  
Environmental Data ◽  
Health Concern ◽  
Irrigated Agriculture ◽  
Boosted Regression Tree

Abstract Background Despite global intervention efforts, malaria remains a major public health concern in many parts of the world. Understanding geographic variation in malaria patterns and their environmental determinants can support targeting of malaria control and development of elimination strategies. Methods We used remotely sensed environmental data to analyze the influences of environmental risk factors on malaria cases caused by Plasmodium falciparum and Plasmodium vivax from 2014 to 2017 in two geographic settings in Ethiopia. Geospatial datasets were derived from multiple sources and characterized climate, vegetation, land use, topography, and surface water. All data were summarized annually at the sub-district (kebele) level for each of the two study areas. We analyzed the associations between environmental data and malaria cases with Boosted Regression Tree (BRT) models. Results We found considerable spatial variation in malaria occurrence. Spectral indices related to land cover greenness (NDVI) and moisture (NDWI) showed negative associations with malaria, as the highest malaria rates were found in landscapes with low vegetation cover and moisture during the months that follow the rainy season. Climatic factors, including precipitation and land surface temperature, had positive associations with malaria. Settlement structure also played an important role, with different effects in the two study areas. Variables related to surface water, such as irrigated agriculture, wetlands, seasonally flooded waterbodies, and height above nearest drainage did not have strong influences on malaria. Conclusion We found different relationships between malaria and environmental conditions in two geographically distinctive areas. These results emphasize that studies of malaria-environmental relationships and predictive models of malaria occurrence should be context specific to account for such differences.

The Success of the Link Model Programme in Rural Bangladesh: An Empirical Analysis

2018 ◽  
Vol 3 (2) ◽  
pp. 191-214
Author(s):  
Shutaro Takeda ◽  
Go Okui ◽  
Nanao Fujimura ◽  
Hisae Abe ◽  
Yuka Ohashi ◽  
...  
Keyword(s):  
Success Factors ◽  
Strongly Correlated ◽  
Key Factors ◽  
Or Education ◽  
Key Success Factors ◽  
Development Officers ◽  
Model Project ◽  
Degree Of Satisfaction ◽  
Link Model ◽  
Rural Appraisal

Link Model, a participatory rural appraisal (PRA) programme for micro-infrastructure construction funding aid, has received much attention in Bangladesh over the last few decades. This study aims to contribute to the latest phase of the Link Model project, launched in July 2016 by the Bangladeshi government. To this end, the authors conducted a field survey in Kalihati Upazila, which involved 102 villagers and 153 local representatives. The authors used the survey to examine the efficacy of the programme and to identify the key factors that contribute to its success. Results obtained from the questionnaire survey showed that the programme had high degrees of satisfaction and penetration in the surveyed villages. Moreover, the degree of satisfaction was unaffected by gender, religion, income or education background, which is notably consistent with the ideals of PRA. Villagers who understood the policy better were more satisfied with the micro-infrastructures developed through the Link Model programme. The ratings of union development officers (UDO) strongly correlated with the number of micro-infrastructures. Therefore, this study concludes that the key success factors of Link Model are (a) the understanding of villagers on the programme for quality and (b) the capability of UDO for quantity.

scholarly journals Spatio-Temporal Variations of Carbon Use Efficiency in Natural Terrestrial Ecosystems and the Relationship with Climatic Factors in the Songnen Plain, China

2019 ◽  
Vol 11 (21) ◽  
pp. 2513 ◽  
Author(s):  
Bo Li ◽  
Fang Huang ◽  
Lijie Qin ◽  
Hang Qi ◽  
Ning Sun
Keyword(s):  
Primary Productivity ◽  
Land Surface ◽  
Climatic Factors ◽  
Transitional Region ◽  
Songnen Plain ◽  
Natural Ecosystems ◽  
Land Surface Phenology ◽  
Carbon Use Efficiency ◽  
Use Efficiency ◽  
The Impact

The Songnen Plain (SNP) is an important grain production base, and is designated as an ecological red-line as a protected area in China. Natural ecosystems such as the ecological protection barrier play an important role in maintaining the productivity and sustainability of farmland. Carbon use efficiency (CUE), defined as the ratio of net primary productivity (NPP) to gross primary productivity (GPP), represents the ecosystem capacity of transferring carbon from the atmosphere to terrestrial biomass. The understanding of the CUE of natural ecosystems in protected farmland areas is vital to predicting the impact of global change and human disturbances on carbon budgets and evaluating ecosystem functions. To date, the changes in CUE at different time scales and their relationships with climatic factors have yet to be fully understood. CUE and the response to land surface phenology are also deserving attention. In this study, variations in ecosystem CUE in the SNP during 2001–2015 were investigated using Moderate-Resolution Imaging Spectroradiometer (MODIS) GPP and NPP data products estimated using the Carnegie-Ames-Stanford approach (CASA) model. The relationships between CUE and phenological and climate factors were explored. The results showed that ecosystem CUE fluctuated over time in the SNP. The lowest and highest CUE values mainly occurred in May and October, respectively. At seasonal scale, average CUE followed a descending order of Autumn > Summer > Spring. The CUE of mixed forest was greater than that of other ecosystems at both monthly and seasonal scales. Land surface phenology plays an important role in the regulation of CUE. The earlier start (SOS), the later end (EOS) and longer length (LOS) of the growing season would contribute increasing of CUE. Precipitation and temperature affected CUE positively in most areas of the SNP. These findings help explain the CUE of natural ecosystems in the protected farmland areas and improve our understanding of ecosystem carbon allocation dynamics in temperate semi-humid to semi-arid transitional region under climate and phenological fluctuations.

scholarly journals Impact of humidity biases on light precipitation occurrence: observations versus simulations

2018 ◽  
Author(s):  
Sophie Bastin ◽  
Philippe Drobinski ◽  
Marjolaine Chiriaco ◽  
Olivier Bock ◽  
Romain Roehrig ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Regional Climate ◽  
Strong Dependence ◽  
Mediterranean Area ◽  
Critical Value ◽  
Critical Values ◽  
Frequency Of Occurrence ◽  
The Impact ◽  
Light Precipitation

Abstract. This work uses a network of GPS stations over Europe from which a homogenised integrated water vapor (IWV) dataset has been retrieved, completed with colocated temperature and precipitation measurements over specific stations to i) estimate the biases of six regional climate models over Europe in terms of humidity; ii) understand their origins; iii) and finally assess the impact of these biases on the frequency of occurrence of precipitation. The evaluated simulations have been performed in the framework of HYMEX/Med-CORDEX programs and cover the Mediterranean area and part of Europe at horizontal resolutions of 50 to 12 km. The analysis shows that models tend to overestimate the low values of IWV and the use of the nudging technique reduces the differences between GPS and simulated IWV. Results suggest that physics of models mostly explain the mean biases, while dynamics affects the variability. The land surface/atmosphere exchanges affect the estimation of IWV over most part of Europe, especially in summer. The limitations of the models to represent these processes explain part of their baises in IWV. However, models correctly simulate the dependance between IWV and temperature, and specifically the deviation that this relationship experiences regarding the Clausius-Clapeyron law after a critical value of temperature (Tbreak). The high spatial variability of Tbreak indicates that it has a strong dependence on local processes which drive the local humidity sources. This explains why the maximum values of IWV are not necessarely observed over warmer area, that are often dry area. Finally, it is shown over SIRTA observatory (near Paris) that the frequency of occurrence of light precipitation is strongly conditioned by the biases in IWV and by the precision of the models to reproduce the distribution of IWV as a function of the temperature. The results of the models indicate that a similar dependence occurs in other areas of Europe, especially where precipitation has a predominantly convective character. According to the observations, for each range of temperature, there is a critical value of IWV from which precipitation picks up. The critical values and the probability to exceed them are simulated with a bias that depends on the model. Those models which present too often light precipitation generally show lower critical values and higher probability to exceed them.

scholarly journals Quantifying the Impacts of Climate Change and Vegetation Variation on Actual Evapotranspiration Based on the Budyko Hypothesis in North and South Panjiang Basin, China

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 508 ◽  
Author(s):  
Tiansheng Li ◽  
Jun Xia ◽  
Dunxian She ◽  
Lei Cheng ◽  
Lei Zou ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Surface ◽  
Climatic Factors ◽  
Actual Evapotranspiration ◽  
Maximum Temperature ◽  
Linear Regression Method ◽  
North And South ◽  
Average Contribution ◽  
Vegetation Variation ◽  
Impacts Of Climate Change

Actual evapotranspiration (Ea) plays a key role in the global water and energy cycles. The accurate quantification of the impacts of different factors on Ea change can help us better understand the driving mechanisms of Ea in a changing environment. Climate change and vegetation variations are well known as two main factors that have significant impacts on Ea change. Our study used three differential Budyko-type equations to quantify the contributions of climate change and vegetation variations to Ea change. First, in order to establish the relationship between the parameter n, which usually presents the land surface characteristics in the Budyko-type equations, with basic climatic variables and the Normalized Difference Vegetation Index (NDVI), the stepwise linear regression method has been used. Then, elasticity and contribution analyses were performed to quantify the contributions of different numbers of climatic factors and NDVI to Ea change. The North and South Panjiang basin in China was selected to investigate the efficiency of the modified Budyko-type equations and quantify the impacts of climate change and vegetation variations on Ea change. The empirical formal of the parameter n established in this study can be used to simulate the parameter n and Ea for the study area. The results of the elasticity and contribution analyses suggest that climate change contributed (whose average contribution is 149.6%) more to Ea change than vegetation variation (whose average contribution is −49.4%). Precipitation, NDVI and the maximum temperature are the major drivers of Ea change, while the minimum temperature and wind speed contribute the least to Ea change.

Analysis of water budget prediction accuracy using ARIMA models

2017 ◽  
Vol 18 (3) ◽  
pp. 819-830 ◽  
Author(s):  
M. Birylo ◽  
Z. Rzepecka ◽  
J. Kuczynska-Siehien ◽  
J. Nastula
Keyword(s):  
Groundwater Level ◽  
Land Surface ◽  
Water Budget ◽  
Prediction Accuracy ◽  
Moving Average ◽  
The European Union ◽  
Arima Models ◽  
Autoregressive Integrated Moving Average ◽  
Run Off ◽  
Satisfactory Prediction

Abstract The European Union Water Framework Directive obliges each country to monitor the groundwater level as it is an important source of drinking water, but also an important part of agriculture. A water budget is used for assessing the accuracy of the groundwater level determination. The computations of the water budget are based on evapotranspiration and the state of land surface hydrosphere. On the basis of the determined water budget, statistics and the prognosis for the next 12 months can be computed. In this paper, all the components of the water budget, such as precipitation, surface run-off and evapotranspiration, are studied for the three tested locations in Poland: Suwalki, Zegrzynski and Tarnow cells. The resultant water budget was also determined and presented graphically. On the basis of the water budget research, a prognosis was determined using AutoRegressive Integrated Moving Average (ARIMA) models with the parameters (2,0,2). A comparison between actual water budget data and a prediction prepared for 2015.08–2016.08 indicated that analysing a 12-month period provides a satisfactory prediction assessment.

scholarly journals Leaching of Chromium, Copper, and Arsenic from CCA-Treated Utility Poles

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Cynthia A. Coles ◽  
Joseph A. Arisi ◽  
Marion Organ ◽  
Geoff I. Veinott
Keyword(s):  
Cation Exchange Capacity ◽  
Exchange Capacity ◽  
Soil Samples ◽  
Strongly Correlated ◽  
Run Off ◽  
Utility Pole ◽  
Utility Poles ◽  
Rainwater Runoff ◽  
Pole Location ◽  
Copper Arsenate

Concentrations of Cu, Cr, and As in soils surrounding 26 Douglas Fir Chromated Copper Arsenate (CCA) treated utility poles and in rainwater runoff from a new CCA treated utility pole segment (log) suspended outside in a cylinder were studied. The age of the utility poles, distances from the poles, rainfall amounts, and characteristics of soil samples including cation exchange capacity (CEC), pH, and total organic carbon (TOC) were considered. Heavier rainfall, damp conditions, and more weathered poles contributed to the greatest leaching of Cu, Cr, and As. The maximum measured soil concentrations of Cu, Cr, and As were 37.5, 65.5, and 38.9 mmol/kg and maximum Cu, Cr, and As concentrations in rainwater run-off were 14, 77.7 and 55.8 μmol/L. Metal concentrations decreased with distance from the poles and, except at one utility pole location, Cu was the most leached of the three elements. The As appeared to have greater mobility in the soil than the Cr. Along the transmission line nearest the coast and from which the greatest amount of samples was collected, soil CEC and TOC values were the highest and the CEC and TOC were directly and strongly correlated.

Microplastics: Are they really a threat to groundwater systems?

2020 ◽  
Author(s):  
Ahmad Ameen ◽  
Margaret Stevenson ◽  
Alfred Paul Blaschke
Keyword(s):  
Land Surface ◽  
United Nations Environment Programme ◽  
Natural Environments ◽  
Key Factors ◽  
Ongoing Research ◽  
Chemical Mechanisms ◽  
Emerging Pollutant ◽  
Groundwater Systems ◽  
Transport Behaviour ◽  
Physical And Chemical

&lt;p&gt;Recently, global annual plastics production has reached a record of 359 million tonnes and in Europe nearly 62 million tonnes, with only a small portion (6-26%) being recycled. Plastic debris released into the environment are categorized, according to size, as macroplastics (&gt; 5mm), microplastics (0.1&amp;#956;m - 5mm) and nanoplastics (&lt; 0.1&amp;#956;m). Microplastics are now recognized as an emerging pollutant due to their abundance in natural environments, and because of growing concerns, the United Nations Environment Programme (UNEP) has included it in the list of top 10 environmental problems.&lt;/p&gt;&lt;p&gt;Additionally, microplastics have a tendency to act as a vector for other contaminants such as pathogens, organic pollutants and heavy metals due to strong dispersion and diffusion mechanisms. The majority of ongoing research on microplastics has primarily focussed on marine systems, but land surface contamination may also be important due to observed release rates that are approximately 20 times higher, in comparison to oceans. Nevertheless, only a few studies have addressed the presence of microplastics in soil and groundwater.&lt;/p&gt;&lt;p&gt;A research gap exists regarding the physical and chemical mechanisms that govern microplastic transport and retention in groundwater. Therefore, a study is being conducted to investigate the distribution, fate and transport of microplastics through groundwater. The overall aim is to improve the understanding of the transport mechanisms of these emerging pollutants and if they enhance the mobility of microbial communities. This research has two main objectives: firstly, to simulate the transport behaviour of various kinds of microplastics (different types, shapes, sizes, and surface morphology), secondly, to analyse the microplastics as potential vectors for microorganisms.&lt;/p&gt;&lt;p&gt;The key factors that are affecting the transport of different sized microplastics will be addressed. Additionally, the co-transport of microorganisms with microplastics during their movement within soil and groundwater will also be considered.&lt;/p&gt;

Price response of herd off-take under market liberalization in a developing cattle sector: panel analysis applied to Kenya's ranching

2009 ◽  
Vol 14 (2) ◽  
pp. 263-280 ◽  
Author(s):  
DICKSON M. NYARIKI
Keyword(s):  
Economic Policy ◽  
Statistical Power ◽  
Climatic Factors ◽  
Price Change ◽  
Panel Analysis ◽  
Classical Dynamic ◽  
Price Response ◽  
Long Run ◽  
Run Off ◽  
Supply Model

ABSTRACTThe influence of price, in view of macro-economic policy change and a set of other factors, on herd off-take rates from ranches in Kenya over a period of 17 years was assessed. An AR(1) equation, based on Nerlove's classical dynamic supply model, was derived and fitted to panel data using the Cochrane–Orcutt procedure. Pooling of data was done to circumvent data insufficiency, thereby improving the statistical power of the analysis. Results indicate that price change has had a significant effect on ranch herd off-take, and climatic factors also account for long-run off-take levels.

Sign in / Sign up

Export Citation Format

Share Document