Evaporation modelling by heuristic regression approaches using only temperature data

Accurate estimation of pan evaporation (E_pan) is very important in water resources management, irrigation scheduling and water budget of lakes. This study investigates the accuracy of two heuristic regression approaches, multivariate adaptive regression splines (MARS) and M5 model tree (M5Tree) in estimating pan evaporation using only temperature data as input. Monthly minimum temperature, maximum temperature and E_pan data from three Turkish stations were used, with month number (periodicity information) added as input to see its effect on estimation accuracy. The models were compared with the calibrated Hargreaves-Samani (CHS), Stephens-Stewart (SS) and multiple linear regression methods. Three different train-test splitting strategies (50%–50%, 60%–40% and 75%–25%) were employed for better evaluation of the applied methods. The results show that the MARS method generally estimated monthly E_pan with higher accuracy compared to the M5Tree, CHS and SS methods. When extraterrestrial radiation, calculated from Julian date and latitude information, was used as input to the SS instead of solar radiation, satisfactory estimates were obtained. A positive effect on model accuracy was observed when involving periodicity information in inputs and increasing training data length.     

Development of a Darcy-Brinkman model to simulate water flow and tracer transport in a heterogeneous karstic aquifer (Val d’Orléans, France)

Darcy’s law is the equation of reference widely used to model aquifer flows. However, its use to model karstic aquifers functioning with large pores is problematic. The physics occurring within the karstic conduits requires the use of a more representative macroscopic equation. A hydrodynamic model is presented which is adapted to the karstic aquifer of the Val d’Orléans (France) using two flow equations: (1) Darcy’s law, used to describe water flow within the massive limestone, and (2) the Brinkman equation, used to model water flow within the conduits. The flow equations coupled with the transport equation allow the prediction of the karst transfer properties. The model was tested by using six dye tracer tests and compared to a model that uses Darcy’s law to describe the flow in karstic conduits. The simulations show that the conduit permeability ranges from 5?×?10^?6 to 5.5?×?10^?5?m² and the limestone permeability ranges from 8?×?10^?11 to 6?×?10^?10?m². The dispersivity coefficient ranges from 23 to 53 m in the conduits and from 1 to 5 m in the limestone. The results of the simulations carried out using Darcy’s law in the conduits show that the dispersion towards the fractures is underestimated.     

A new look on the Jurassic formations of the western part of Iraq

The Jurassic succession of western Iraq includes the Ubaid, Hussainiyat, Amij, Muhaiwir, and Najmah formations. Each formation is composed of basal clastic unit overlain by upper carbonate unit. Extensive and huge erosional unconformity occurred at the Triassic–Jurassic boundary due to marked shifting of structural (E–W) strike of the Triassic (Rhaetic) Zor Hauran Formation to (NE–SW) Jurassic formations. Sea level falling (lowstand system tracts) would result in the progradation of the land on the expense of the sea forming the recognizable progradation of the fluvial and deltaic deposits of the lower clastic units of the Jurassic formations, whereas sea level rising (highstand system tract), i.e., sea prograding, causes deposition of the carbonate units of the Jurassic formations system. This progradation resulted to various carbonate environments of deposition ranging from subtidal, intertidal, to supratidal. The main target on most of the exploration blocks in the western part of Iraq focused on the lower Paleozoic successions, whereas prospects in Triassic, Jurassic, and lower Cretaceous targets are less extensive but may have significant potential on certain blocks in both stratigraphic and structural traps. The western part of Iraq was subjected to intermittent pulses of uplifting (sea regression) and subsidence (sea transgression) to form the Jurassic basin system in the area. The Jurassic formations lack the characteristics of petroleum systems. In contrast, in the central and northern parts of Iraq, the Jurassic formations (Najmah and Gotnia formations) were deposited in subsiding basins in which the reservoir and sealed evaporitic rocks existed. In turn, in the western desert of Iraq, the Jurassic formations lack these petroleum system characteristics. Hence, it can be proposed that the petroleum–nonpetroleum inflection could be proposed in the east of area km 160.     

The changing social relations of a community-based mangrove forest project in Zanzibar

Coastal areas in East Africa are experiencing rapid economic, resource management, demographic and technological shifts. In response diverse Community-based Natural Resource Management (CBNRM) applications have been embraced to provide mutual conservation and use benefits. These initiatives have met with mixed success in practice. Reflecting on the limitations of past research using common pool resources theory theory to study CBNRM we use insights from actor oriented theory combined with satellite image analysis to describe and discuss the forces dynamically influencing institutional and mangrove forest cover change at Kisakasaka, Zanzibar focussing on the formal CBNRM project period between 1996 and 2001, but also considering the period before and after this. We examine the shifting social relations that affected the performance and viability of the formal CBNRM arrangements. An integrated approach was taken to the presentation and discussion of results where it was possible to enrich and expand explanations of socio-environmental change, which was driven by a lack of government support, the undermining effects of party political divisions, and the lack of institutional adaptive capacity. We conclude that this was a useful approach to explain CBNRM intervention events at Kisakasaka.     

Predicting Total Dissolved Gas Concentration on a Daily Scale Using Kriging Interpolation,Response Surface Method and Artificial Neural Network: Case Study of Columbia River Basin Dams,USA

Natural Resources Research - Total dissolved gas (TDG) is an important factor for aquatic life and can cause gas bubble trauma in fish if the concentration is higher than 110%. Dissolved gas is...     

Time series forecasting of river flow using an integrated approach of wavelet multi-resolution analysis and evolutionary data-driven models. A case study: Sebaou River (Algeria)

The complexity of hydrological processes and lack of data for modeling require the use of specific tools for non-linear natural phenomenon. In this paper, an effort has been made to develop a conjunction model – wavelet transformation, data-driven models, and genetic algorithm (GA) – for forecasting the daily flow of a river in northern Algeria using the time series of runoff. This catchment has a semi-arid climate and strong variability in runoff. The original time series was decomposed into multi-frequency time series by wavelet transform algorithm and used as inputs to artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) models. Several factors must be optimized to determine the best model structures. Wavelet-based data-driven models using a GA are designed to optimize model structure. The performances of wavelet-based data-driven models (i.e. WANFIS and WANN) were superior to those of conventional models. WANFIS (RMSE = 12.15 m³/s, EC = 87.32%, R = .934) and WANN (RMSE = 15.73 m³/s, EC = 78.83%, R = .888) models improved the performances of ANFIS (RMSE = 23.13 m³/s, EC = 54.11%, R = .748) and ANN (RMSE = 22.43 m³/s, EC = 56.90%, R = .755) during the test period.     

Investigation of Soil Conditioning Tests with Three-Dimensional Numerical Modeling

Due to the diverse and complex structure of soil and the variety of foam-modifier materials that are used, it is difficult to provide a model to predict the laboratory behavior of modified soils. For example, several studies have shown independently that the amount of the foam-modified soil depends on several factors, such as the internal friction angle and normal stiffness. Of late, modeling by numerical methods has become popular in engineering sciences and the modeling of complex material behavior is possible with the help of numerical methods. In this research, the performance and efficiency of the numerical method in the modeling of laboratory tests such as the slump test and the uniaxial compressive strength test were investigated and it was found that numerical modeling performs very well in predicting the results of these tests for foam-modified sand samples. In order to achieve this goal, the slump test and the uniaxial compressive strength test were performed in the laboratory on several modified sand samples in order to obtain the laboratory results for these samples. Then, numerical simulation of these experiments was carried out using PFC^3D software. The results of numerical modeling were compared with the experimental results, and good agreement was observed. Finally, after calibration of the numerical model using the experimental results, the effect of changes in the internal friction angle and the normal stiffness of the modified sand in the amount of the slump was investigated. According to the results of this sensitivity analysis, it was determined that by increasing both effective parameters the amount of the slump of foam-modified sand decreases and that the parameters are the most important factors in controlling the slump value.     

Prediction of settlement trough induced by tunneling in cohesive ground

Surface settlements of soil due to tunneling are caused by stress relief and subsidence due to movement of support by excavation. There are significant discrepancies between empirical solutions to predict surface settlement trough because of different interpretations and database collection by different authors. In this paper, the shape of settlement trough caused by tunneling in cohesive ground is investigated by different approaches, namely analytical solutions, empirical solutions, and numerical solutions by the finite element method. The width of settlement trough was obtained by the finite element method through establishing the change in the slope of the computed settlement profile. The finite element elastic-plastic analysis gives better predictions than the linear elastic model with satisfactory estimate for the displacement magnitude and slightly overestimated width of the surface settlement trough. The finite element method overpredicted the settlement trough width i compared with the results of Peck for soft and stiff clay, but there is an excellent agreement with Rankin’s estimation. The results show that there is a good agreement between the complex variable analysis for Z/D = 1.5, while using Z/D = 2 and 3, the curve diverges in the region faraway from the center of the tunnel.     

A new fluid factor and its application using a deep learning approach

Amplitude interpretation for hydrocarbon prediction is an important task in the oil and gas industry. Seismic amplitude is dominated by porosity, the volume of clay, pore-filled fluid type and lithology. A few seismic attributes are proposed to predict the existence of hydrocarbon. This paper proposes a new fluid factor by adding a correct item based on the J attribute. The algorithm is verified through stochastic Monte Carlo modelling that contains various rock physical properties of sand and shale. Both gas and oil responses are separated by the new fluid factor. Furthermore, an approach based on the neural network model is trained using the deep learning method to predict the new fluid factor. The confusion matrix shows that this model performs well. This model allows the application of the new fluid factor in the seismic data. In this study, the Marmousi II data set is used to examine the performance of the new fluid factor, and the result is good. Most hydrocarbon reservoirs are identified in the shale–sandstone sequences. The combination of deep learning and the new fluid factor provides a more accurate way for hydrocarbon prediction.     

Seismic spectrograms of an anelastic layer with different source-receivers configurations

Thin and relatively thin anelastic layers (compared to the signal wavelength) generally represent hydrocarbon reservoirs, where the rock is a sandstone or a source rock saturated with brine, oil and gas. The study of the seismic response of these layers is important to detect the hydrocarbons on the basis of the reflection and transmission coefficients and the wave velocity and attenuation properties. Different seismic experiments (source-receiver configurations) can provide useful information to characterise its properties. In this work, we consider varying thicknesses and Q values of the layer and analyse the reflection and transmission coefficients. Moreover, we obtain spectrograms of surface seismic profiles and vertical and horizontal well profiles (VSP and HSP, respectively) to analyse their frequency content with offset due to variations of the attenuation properties of the layer. In addition, we compare the effects due to NMO stretching and intrinsic attenuation related to the low-frequency shadows (LFS) observed in real data after stacking, since LFS can have several causes. Ambiguity is present in this case, indicating that non-stretch NMO is required, otherwise an offset mute of the data may remove useful information regarding the intrinsic (physical) loss.