Estimation of tail dependence coefficient in rainfall accumulation fields

Extreme rainfall events are of particular importance due to their severe impacts on the economy, the environment and the society. Characterization and quantification of extremes and their spatial dependence structure may lead to a better understanding of extreme events. An important concept in statistical modeling is the tail dependence coefficient (TDC) that describes the degree of association between concurrent rainfall extremes at different locations. Accurate knowledge of the spatial characteristics of the TDC can help improve on the existing models of the occurrence probability of extreme storms. In this study, efficient estimation of the TDC in rainfall is investigated using a dense network of rain gauges located in south Louisiana, USA. The inter-gauge distances in this network range from about 1 km to 9 km. Four different nonparametric TDC estimators are implemented on samples of the rain gauge data and their advantages and disadvantages are discussed. Three averaging time-scales are considered: 1 h, 2 h and 3 h. The results indicate that a significant tail dependency may exist that cannot be ignored for realistic modeling of multivariate rainfall fields. Presence of a strong dependence among extremes contradicts with the assumption of joint normality, commonly used in hydrologic applications.     

Conditional simulation of remotely sensed rainfall data using a non-Gaussian v-transformed copula

Quantification of rainfall and its spatial and temporal variability is extremely important for reliable hydrological and meteorological modeling. While rain gauge measurements do not provide reasonable areal representation of rainfall, remotely sensed precipitation estimates offer much higher spatial resolution. However, uncertainties associated with remotely sensed rainfall estimates are not well quantified. This issue is important considering the fact that uncertainties in input rainfall are the main sources of error in hydrologic processes. Using an ensemble of rainfall estimates that resembles multiple realizations of possible true rainfall, one can assess uncertainties associated with remotely sensed rainfall data. In this paper, ensembles are generated by imposing rainfall error fields over remotely sensed rainfall estimates. A non-Gaussian copula-based model is introduced for simulation of rainfall error fields. The v-transformed copula is employed to describe the dependence structure of rainfall error estimates without the influence of the marginal distribution. Simulations using this model can be performed unconditionally or conditioned on ground reference measurements such that rain gauge data are honored at their locations. The presented model is implemented for simulation of rainfall ensembles across the Little Washita watershed, Oklahoma. The results indicate that the model generates rainfall fields with similar spatio-temporal characteristics and stochastic properties to those of observed rainfall data.     

Steady state and liquefaction characteristics of gravely sands

Liquefaction of loose and saturated soils during earthquakes and strong ground motions has been a major cause of damage to buildings and earth embankments as well as other civil engineering structures. In order to evaluate the liquefaction potential and steady state characteristics of gravely sand of south west Tehran,a subsoil exploration program conducted dividing the region into 10 zones. In each zone of 500 m × 500 m a borehole of 20 m deep was drilled. SPT was performed at one meter intervals in each borehole and a total of 200 samples were recovered. Soils of similar grain size distribution have been considered to have similar steady state characteristics,therefore consolidated undrained triaxial tests were performed on these soils of similar grain size distribution to evaluate the steady state strength. The steady state line for each soil type was derived. Comparing the steady state strengths with the shear stress due to an earthquake with a PGA of 0.35 g,the potential of sand liquefaction and .ow failure in soil layers has been evaluated and the settlement of soil due to the liquefaction phenomena is calculated. Finally some recommendations for estimating the steady state strength from simple SPT test in gravely sands are presented.     

Effect of the thermal gradient variation through geological time on basin modeling; a case study: The Paris basin

Many studies investigated the thermal modeling of the Paris basin for petroleum interests during the 1970s. Most of the softwares developed by oil companies or research centers were based on the assumption of a constant thermal gradient. In order to take into consideration the variation of the thermal gradient during basin evolution, we developed the TherMO's Visual Basic 1D program. We applied our model to twenty boreholes located along a cross-section roughly running EW over 150 km in the center of the Paris basin. The numerical results were calibrated with organic matter maturity data. TherMO's simulates the amount of heat provided to the sedimentary organic matter. The heat parameter simulated shows lateral variation along the cross-section. It decreases from Rambouillet to Trou Aux Loups boreholes (87–66 mW/m²) at about 100 km more to the east whereas the heat flux value simulated is 73 mW/m² in St. Loup borehole. The mean thermal gradient calculated for liassic horizons at 87 My for the Rambouillet well is 50.4 °C/km. This value is similar to previously published results. By integrating the calculation of the thermal gradients and conductivities related to the burial of each stratigraphic sequence, our approach points out variations in the thermal regimes the sedimentary organic matter (SOM) has been subjected to through geological time.     

The Bowen Ratio of an Alpine Grassland in Three-River Headwaters,Qinghai-Tibet Plateau,from 2001 to 2018

The Bowen ratio (β) is used to quantify heat transfer from the land surface into the air, which is becoming a hot topic in research on the biogeophysical effects of land use and cover changes. The Three-River Headwaters (TRH), as a sensitive and fragile region, was selected as the study area. The β for 2001-2018 was estimated from the evapotranspiration product (ET_MOD16) of MODIS and the net radiation of the land surface through the albedo from GLASS. The ET_MOD16 data were evaluated against the observation data (ET_OBS) at two alpine grassland flux towers obtained from ChinaFLUX. The interannual trend of the β was analyzed by multiple linear regression (MLR) and structure model (SEM) with the multiple factors of precipitation, temperature, humidity, albedo, and normalized difference vegetation index (NDVI, MOD09Q1). The results show that the ET_MOD16 values were significantly correlated with ET_OBS, with a correlation coefficient above 0.70 (P < 0.01) for the two sites. In 2001-2018, the regional mean β was 2.52 ± 0.77 for the whole grassland, and its spatial distribution gradually increased from the eastern to western region. The interannual β showed a downward trend with a slope of -0.025 and a multiple regression coefficient (R ²) of 0.21 (P = 0.056). Most of the variability (51%) in the interannual β can be explained by the linear regression of the above multiple factors, and the temperature plays a dominant role for the whole region. The SEM analysis further shows that an increasing NDVI results in a decreasing albedo with a path coefficient of -0.57, because the albedo was negatively correlated with NDVI (R ² = 0.52, P < 0.01), which indicates a negative and indirect effect on β from vegetation restoration. An obvious warming climate was found to prompt more evapotranspiration, and restoring vegetation makes the land surface receive more radiation, which both resulted in a decreasing trend in the annual β. This study revealed the biogeophysical mechanisms of vegetation restoration under a changing climate, and demonstrated the Bowen ratio can be applied as an indicator of climate-regulating functions in ecosystem assessments.     

Assessing climate change impacts on California hydropower generation and ancillary services provision

Climate change is already affecting species and their distributions. Distributional range changes have occurred and are projected to intensify for many widespread plants and animals, creating associated risks to many ecosystems. Here, we estimate the climate change-related risks to the species in globally significant biodiversity conservation areas over a range of climate scenarios, assessing their value as climate refugia. In particular, we quantify the aggregated benefit of countries’ emission reduction pledges (Intended Nationally Determined Contributions and Nationally Determined Contributions under the Paris Agreement), and also of further constraining global warming to 2 °C above pre-industrial levels, against an unmitigated scenario of 4.5 °C warming. We also quantify the contribution that can be made by using smart spatial conservation planning to facilitate some levels of autonomous (i.e. natural) adaptation to climate change by dispersal. We find that without mitigation, on average 33% of each conservation area can act as climate refugium (or 18% if species are unable to disperse), whereas if warming is constrained to 2 °C, the average area of climate refuges doubles to 67% of each conservation area (or, without dispersal, more than doubles to 56% of each area). If the country pledges are fulfilled, an intermediate estimate of 47–52% (or 31–38%, without dispersal) is obtained. We conclude that the Nationally Determined Contributions alone have important but limited benefits for biodiversity conservation, with larger benefits accruing if warming is constrained to 2 °C. Greater benefits would result if warming was constrained to well below 2 °C as set out in the Paris Agreement.     

Predicting the expansion of an urban boundary using spatial logistic regression and hybrid raster–vector routines with remote sensing and GIS

This paper presents an urban growth boundary model (UGBM) which utilizes spatial logistic regression (SLR), remote sensing, and GIS to simulate the differentially expanding geometry of a dynamic urban boundary over decadal time periods. SLR is used as the core algorithm in a UGBM quantifying how biophysical factors influence the rate at which all edges of an urban boundary expand over time. Spatial drivers selected from a raster-based environment are used as input predictor variables to the SLR UGBM, the output response variable being the distance between time-separated urban boundary intersections along arcs extending radially from a point centered at the urban core relative to the maximum distance. Percent area match (PAM) quantity and location goodness-of-fit metrics, fit of the predicted distance versus observed distance, and the sensitivity of the SLR UGBM to the contribution of each predictor variable are used to assess the agreement between predicted and observed urban boundaries. The model is built, tested, and validated using satellite images of the city of Las Vegas, United States of America, collected in 1990, 2000, and 2010. We compare urban boundary simulation of full and reduced SLR UGBMs to a null UGBM lacking in specificity of predictor variables. Results indicate that the SLR UGBM has a better goodness of fit compared to a null UGBM using PAM quantity and location goodness-of-fit metrics. Then, we use the SLR UGBM to predict urban boundary expansion between the years 2000 and 2010 and describe how this model can be used to plan ahead for future boundary expansions given what is known about current edge conditions.     

The permeability of fault zones: a case study of the Dead Sea rift (Middle East)

Fault zone architecture plays an important role in flow regimes of hydrological systems. Fault zones can act as conduits, barriers, or conduits/barrier systems depending on their spatial architecture. The goal of this study is to determine the fault-zone permeability structure and its effect on the local hydrogeological system in the Dead Sea fault system. Permeability was measured on small-scale outcrop plug samples at four faults along the Dead Sea fault system, and large-scale slug tests in four boreholes, in different parts of the fault, at Yair fault in Israel. The research results show that values in the damage zone are two to five orders of magnitude higher than those of the fault core (~3.5?×?10^?10, 1?×?10^?15 m² respectively), resulting in an anisotropic permeability structure for the overall fault zone and preferable flow parallel to the fault. A set of injection tests in the Yair fault damage zone revealed a water-pressure-dependent behavior. The permeability of this zone increases when employing a higher water pressure in the fault fracture-dominated damage zone, due to the reopening of fractures.     

Assessing the impacts of climate and land use change on streamflow,water quality and suspended sediment in the Kor River Basin,Southwest of Iran

This research addressed the separate and combined impacts of climate and land use change on streamflow, suspended sediment and water quality in the Kor River Basin, Southwest of Iran, using (BASINS–WinHSPF) model. The model was calibrated and validated for hydrology, sediment and water quality for the period 2003–2012. The model was run under two climate changes, two land use changes and four combined change scenarios for near-future period (2020–2049). The results revealed that projected climate change impacts include an increase in streamflow (maximum increases of 52% under RCP 2.6 in December and 170% under RCP 8.5). Projected sediment concentrations under climate change scenarios showed a monthly average decrease of 10%. For land use change scenarios, agricultural development scenario indicated an opposite direction of changes in orthophosphate (increases in all months with an average increase of 6% under agricultural development scenario), leading to the conclusion that land use change is the dominant factor in nutrient concentration changes. Combined impacts results indicated that streamflows in late fall and winter months increased while in summer and early fall decreased. Suspended sediment and orthophosphate concentrations were decreased in all months except for increases in suspended sediment concentrations in September and October and orthophosphate concentrations in late winter and early spring due to the impact of land use change scenarios.     

Effect of $$\hbox {CO}_2$$ solubility on dissolution rate of calcite in saline aquifers for temperature range of 50–100 $$^{\circ } \hbox {C}$$∘C and pressures up to 600 bar: alterations of fractures geometry in carbonate rocks by $$\hbox {CO}_2$$-acidified brines

An empirical model is developed to predict the dissolution rate of calcite in saline solutions that are saturated with respect to dissolved \(\hbox {CO}_2\) over a broad range of both subcritical and supercritical conditions. The focus is on determining the rate of calcite dissolution within a temperature range of 50–100 \(^\circ \hbox {C}\) and pressures up to 600 bar, relevant for \(\hbox {CO}_2\) sequestration in saline aquifers. A general reaction kinetic model is used that is based on the extension of the standard Arrhenius equation with an added, solubility-dependent, pH term to account for the saturated concentration of dissolved \(\hbox {CO}_2\). On the basis of this kinetic model, a new rate equation is obtained using multi-parameter, nonlinear regression of experimental data to determine the dissolution of calcite as a function of temperature, pressure and salinity. Different models for the activity coefficient of \(\hbox {CO}_2\) dissolved in saline solutions are accounted for. The new rate equation helps us obtain good agreement with experimental data, and it is applied to study the geochemically induced alterations of fracture geometry due to calcite dissolution.