Long-term Temporal Variations in Characteristics of Leachates from a Closed Landfill in an Arid Region

Long-term climate change may strongly affect the aquatic environment in mid-latitude water resources. In particular, it can be demonstrated that temporal variations in surface water temperature in a reservoir have strong responses to air temperature. We adopted deep neural networks (DNNs) to understand the long-term relationships between air temperature and surface water temperature, because DNNs can easily deal with nonlinear data, including uncertainties, that are obtained in complicated climate and aquatic systems. In general, DNNs cannot appropriately predict unexperienced data (i.e., out-of-range training data), such as future water temperature. To improve this limitation, our idea is to introduce a transfer learning (TL) approach. The observed data were used to train a DNN-based model. Continuous data (i.e., air temperature) ranging over 150 years to pre-training to climate change, which were obtained from climate models and include a downscaling model, were used to predict past and future surface water temperatures in the reservoir. The results showed that the DNN-based model with the TL approach was able to approximately predict based on the difference between past and future air temperatures. The model suggested that the occurrences in the highest water temperature increased, and the occurrences in the lowest water temperature decreased in the future predictions.

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CO2 dynamics and heterogeneity in a cave atmosphere: role of ventilation patterns and airflow pathways

Theoretical and Applied Climatology ◽

10.1007/s00704-021-03722-w ◽

2021 ◽

Author(s):

Lovel Kukuljan ◽

Franci Gabrovšek ◽

Matthew D. Covington ◽

Vanessa E. Johnston

Keyword(s):

Temporal Variations ◽

Observation Point ◽

Spatially Distributed ◽

Combined Action ◽

Karst Systems ◽

The Relationship ◽

Co2 Dynamics ◽

Global Carbon

AbstractUnderstanding the dynamics and distribution of CO2 in the subsurface atmosphere of carbonate karst massifs provides important insights into dissolution and precipitation processes, the role of karst systems in the global carbon cycle, and the use of speleothems for paleoclimate reconstructions. We discuss long-term microclimatic observations in a passage of Postojna Cave, Slovenia, focusing on high spatial and temporal variations of pCO2. We show (1) that the airflow through the massif is determined by the combined action of the chimney effect and external winds and (2) that the relationship between the direction of the airflow, the geometry of the airflow pathways, and the position of the observation point explains the observed variations of pCO2. Namely, in the terminal chamber of the passage, the pCO2 is low and uniform during updraft, when outside air flows to the site through a system of large open galleries. When the airflow reverses direction to downdraft, the chamber is fed by inlets with diverse flow rates and pCO2, which enter via small conduits and fractures embedded in a CO2-rich vadose zone. If the spatial distribution of inlets and outlets produces minimal mixing between low and high pCO2 inflows, high and persistent gradients in pCO2 are formed. Such is the case in the chamber, where vertical gradients of up to 1000 ppm/m are observed during downdraft. The results presented in this work provide new insights into the dynamics and composition of the subsurface atmosphere and demonstrate the importance of long-term and spatially distributed observations.

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Effects of long-term water table drawdown on evapotranspiration and vegetation in an arid region phreatophyte community

Journal of Hydrology ◽

10.1016/j.jhydrol.2005.09.035 ◽

2006 ◽

Vol 325 (1-4) ◽

pp. 21-34 ◽

Cited By ~ 106

Author(s):

David J. Cooper ◽

John S. Sanderson ◽

David I. Stannard ◽

David P. Groeneveld

Keyword(s):

Water Table ◽

Arid Region

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Nudibranchs out of water: long-term temporal variations in the abundance of two Dendrodoris species under emersion

Helgoland Marine Research ◽

10.1186/s10152-018-0516-4 ◽

2018 ◽

Vol 72 (1) ◽

Author(s):

Ricardo Cyrne ◽

Inês C. Rosa ◽

Filipa Faleiro ◽

Gisela Dionísio ◽

Miguel Baptista ◽

...

Keyword(s):

Temporal Variations

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An Investigation of the Soil Property Changes and Heavy Metal Accumulation in Relation to Long-term Wastewater Irrigation in the Semi-arid Region of Iran

Soil and Sediment Contamination An International Journal ◽

10.1080/15320383.2011.609202 ◽

2011 ◽

Vol 20 (7) ◽

pp. 841-856 ◽

Cited By ~ 9

Author(s):

S. Rezapour ◽

A. Samadi ◽

Habib Khodaverdiloo

Keyword(s):

Heavy Metal ◽

Arid Region ◽

Soil Property ◽

Metal Accumulation ◽

Heavy Metal Accumulation ◽

Wastewater Irrigation ◽

Semi Arid Region ◽

Property Changes ◽

Semi Arid

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Performance analysis of a reservoir in arid region Case study: Babar reservoir, Aurès region, Algeria

Journal of Water and Land Development ◽

10.2478/jwld-2018-0069 ◽

2018 ◽

Vol 39 (1) ◽

pp. 141-146 ◽

Cited By ~ 2

Author(s):

Fatima Z. Tebbi ◽

Hadda Dridi ◽

Mahdi Kalla

Keyword(s):

Reservoir Operation ◽

Arid Region ◽

R Package ◽

Performance Criteria ◽

Stochastic Dynamic ◽

Operation Optimization ◽

Rule Curves ◽

Demand Scenario

AbstractLong term and mid-term reservoir operation involves derivation of rule curves for optimal management of the available resource. The present work deals with reservoir operation in the Aurès arid region. As an example, Babar reservoir is selected to apply the proposed approach which estimates all the water balance terms, especially those which are random as water inflows. For each demand scenario a reservoir operation optimization model using Explicit Stochastic Dynamic Programming (ESDP) is performed, to derive optimal rule curves based on historical operating records (Jan 2002–Dec 2013) and using “Reservoir” R package®. Subsequently, risk analysis is conducted for these different demand scenarios rules by the RRV (reliability, resilience, vulnerability) metrics. Results show the advantage of using the “Reservoir” R package for a rapid and an easy analysis of the performance criteria jointly with the optimization algorithm to Re-operate Reservoir operation.

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Autogenic versus allogenic controls on the evolution of a coupled fluvial megafan/mountainous catchment system: numerical modelling and comparison with the Lannemezan megafan system (Northern Pyrenees, France)

10.5194/esurf-2016-44 ◽

2016 ◽

Cited By ~ 2

Author(s):

Margaux Mouchené ◽

Peter van der Beek ◽

Sébastien Carretier ◽

Frédéric Mouthereau

Keyword(s):

Numerical Modelling ◽

Temporal Variations ◽

Tectonic Activity ◽

Mountain Range ◽

Stream Network ◽

Mountainous Catchment ◽

Isostatic Rebound ◽

Base Level ◽

Alluvial Terraces

Abstract. Alluvial megafans are sensitive recorders of landscape evolution, controlled by autogenic processes and allogenic forcing and influenced by the coupled dynamics of the fan with its mountainous catchment. The Lannemezan megafan in the northern Pyrenean foreland was abandoned by its mountainous feeder stream during the Quaternary and subsequently incised, leaving a flight of alluvial terraces along the stream network. We explore the relative roles of autogenic processes and external forcing in the building, abandonment and incision of a foreland megafan using numerical modelling and compare the results with the inferred evolution of the Lannemezan megafan. Autogenic processes are sufficient to explain the building of a megafan and the long-term entrenchment of its feeding river at time and space scales that match the Lannemezan setting. Climate, through temporal variations in precipitation rate, may have played a role in the episodic pattern of incision at a shorter time-scale. In contrast, base-level changes, tectonic activity in the mountain range or tilting of the foreland through flexural isostatic rebound appear unimportant.

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The impact of non-ideality on reconstructing spatial and temporal variations of aerosol acidity with multiphase buffer theory

10.5194/egusphere-egu21-9292 ◽

2021 ◽

Author(s):

Yafang Cheng ◽

Guangjie Zheng ◽

Hang Su ◽

Siwen Wang ◽

Andrea Pozzer

Keyword(s):

Molar Fraction ◽

Temporal Variations ◽

Spatial Variations ◽

Acid Dissociation ◽

Acid Dissociation Constant ◽

Aerosol Acidity ◽

Long Term Trends ◽

Factor C ◽

The Impact

Aerosol acidity is a key parameter in atmospheric aqueous chemistry and strongly influence the interactions of air pollutants and ecosystem. The recently proposed multiphase buffer theory provides a framework to reconstruct long-term trends and spatial variations of aerosol pH based on the effective acid dissociation constant of ammonia (Ka,NH3*). However, non-ideality in aerosol droplets is a major challenge limiting its broad applications. Here, we introduced a non-ideality correction factor (cni) and investigated its governing factors. We found that besides relative humidity (RH) and temperature, cni is mainly determined by the molar fraction of NO3- in aqueous-phase anions, due to different NH4+ activity coefficients between (NH4)2SO4- and NH4NO3-dominated aerosols. A parameterization method is thus proposed to estimate cni at given RH, temperature and NO3- fraction, and is validated against long-term observations and global simulations. In the ammonia-buffered regime, with cni correction the buffer theory can well reproduce the Ka,NH3* predicted by comprehensive thermodynamic models, with root-mean-square deviation ~0.1 and correlation coefficient ~1. Note that, while cni is needed to predict Ka,NH3* levels, it is usually not the dominant contributor to its variations, as ~90% of the temporal or spatial variations in Ka,NH3* is due to variations in aerosol water and temperature.

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Long-term temporal changes in the occurrence of a high forest fire danger in Finland

Natural Hazards and Earth System Science ◽

10.5194/nhess-12-2591-2012 ◽

2012 ◽

Vol 12 (8) ◽

pp. 2591-2601 ◽

Cited By ~ 6

Author(s):

H. M. Mäkelä ◽

M. Laapas ◽

A. Venäläinen

Keyword(s):

Forest Fire ◽

Forest Fires ◽

Large Scale ◽

Weather Conditions ◽

Temporal Variations ◽

Fire Danger ◽

Specific Information ◽

Climate Data ◽

Forest Fire Danger

Abstract. Climate variation and change influence several ecosystem components including forest fires. To examine long-term temporal variations of forest fire danger, a fire danger day (FDD) model was developed. Using mean temperature and total precipitation of the Finnish wildfire season (June–August), the model describes the climatological preconditions of fire occurrence and gives the number of fire danger days during the same time period. The performance of the model varied between different regions in Finland being best in south and west. In the study period 1908–2011, the year-to-year variation of FDD was large and no significant increasing or decreasing tendencies could be found. Negative slopes of linear regression lines for FDD could be explained by the simultaneous, mostly not significant increases in precipitation. Years with the largest wildfires did not stand out from the FDD time series. This indicates that intra-seasonal variations of FDD enable occurrence of large-scale fires, despite the whole season's fire danger is on an average level. Based on available monthly climate data, it is possible to estimate the general fire conditions of a summer. However, more detailed input data about weather conditions, land use, prevailing forestry conventions and socio-economical factors would be needed to gain more specific information about a season's fire risk.

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