GRASS GIS-embedded Decision Support Framework for Flood Simulation and Forecasting

This study presents a spatiotemporal analysis tool, called Shyska. This tool allows the simulation and prediction of flash floods in semiarid basins. Shyska has been developed by Geographical Information System (GIS)‐embedded functions, allowing the integration of hydrometeorological information from modern technologies of data acquisition in real time. A Digital Elevation Model (DEM) is used in order to obtain the relevant parameters from the integrated rainfall‐runoff models. Some of its most relevant modules and methodology employed for its development are described. Case studies in basins of south‐east Spain illustrate the applicability of the proposed techniques.     

Knickpoint recession rate and catchment area: the case of uplifted rivers in Eastern Scotland

Knickpoint behaviour is a key to understanding both the landscape responses to a base‐level fall and the corresponding sediment fluxes from rejuvenated catchments, and must be accommodated in numerical models of large‐scale landscape evolution. Knickpoint recession in streams draining to glacio‐isostatically uplifted shorelines in eastern Scotland is used to assess whether knickpoint recession is a function of discharge (here represented by its surrogate, catchment area). Knickpoints are identified using DS plots (log slope versus log downstream distance). A statistically significant power relationship is found between distance of headward recession and catchment area. Such knickpoint recession data may be used to determine the values of m and n in the stream power law, E = KA^mSⁿ. The data have too many uncertainties, however, to judge definitively whether they are consistent with m = n = 1 (bedrock erosion is proportional to stream power and KPs should be maintained and propagate headwards) or m = 0·3, n = 0·7 (bedrock incision is proportional to shear stress and KPs do not propagate but degrade in place by rotation or replacement). Nonetheless, the E Scotland m and n values point to the dominance of catchment area (discharge) in determining knickpoint retreat rates and are therefore more consistent with the stream power law formulation in which bedrock erosion is proportional to stream power. Copyright © 2005 John Wiley & Sons, Ltd.     

Determination of lower and upper bounds of predicted production from history-matched models

We present a method to determine lower and upper bounds to the predicted production or any other economic objective from history-matched reservoir models. The method consists of two steps: 1) performing a traditional computer-assisted history match of a reservoir model with the objective to minimize the mismatch between predicted and observed production data through adjusting the grid block permeability values of the model. 2) performing two optimization exercises to minimize and maximize an economic objective over the remaining field life, for a fixed production strategy, by manipulating the same grid block permeabilities, however without significantly changing the mismatch obtained under step 1. This is accomplished through a hierarchical optimization procedure that limits the solution space of a secondary optimization problem to the (approximate) null space of the primary optimization problem. We applied this procedure to two different reservoir models. We performed a history match based on synthetic data, starting from a uniform prior and using a gradient-based minimization procedure. After history matching, minimization and maximization of the net present value (NPV), using a fixed control strategy, were executed as secondary optimization problems by changing the model parameters while staying close to the null space of the primary optimization problem. In other words, we optimized the secondary objective functions, while requiring that optimality of the primary objective (a good history match) was preserved. This method therefore provides a way to quantify the economic consequences of the well-known problem that history matching is a strongly ill-posed problem. We also investigated how this method can be used as a means to assess the cost-effectiveness of acquiring different data types to reduce the uncertainty in the expected NPV.     

Exploring seven hundred years of transhumance,climate dynamic,fire and human activity through a historical mountain pass in central Spain

A high-altitude peat sequence from the heart of the Spanish Central System (Gredos range) was analysed through a multi-proxy approach to determine the sensitivity of high-mountain habitats to climate, fire and land use changes during the last seven hundred years, providing valuable insight into our understanding of the vegetation history and environmental changes in a mountain pass close to a traditional route of transhumance. The pollen data indicate that the vegetation was dominated by shrublands and grasslands with scattered pines in high-mountain areas, while in the valleys cereals, chestnut and olive trees were cultivated. Strong declines of high-mountain pines percentages are recorded at 1540, 1675, 1765, 1835 and 1925 cal AD, which may be related to increasing grazing activities and/or the occurrence of anthropogenic fires. The practice of mountain summer farming and transhumance deeply changed and redesigned the landscape of the high altitudes in central Spain (Gredos range) since the Middle Ages, although its dynamics was influenced in some way by climate variability of the past seven centuries.     

Computing derivative information of sequentially coupled subsurface models

A generic framework for the computation of derivative information required for gradient-based optimization using sequentially coupled subsurface simulation models is presented. The proposed approach allows for the computation of any derivative information with no modification of the mathematical framework. It only requires the forward model Jacobians and the objective function to be appropriately defined. The flexibility of the framework is demonstrated by its application in different reservoir management studies. The performance of the gradient computation strategy is demonstrated in a synthetic water-flooding model, where the forward model is constructed based on a sequentially coupled flow-transport system. The methodology is illustrated for a synthetic model, with different types of applications of data assimilation and life-cycle optimization. Results are compared with the classical fully coupled (FIM) forward simulation. Based on the presented numerical examples, it is demonstrated how, without any modifications of the basic framework, the solution of gradient-based optimization models can be obtained for any given set of coupled equations. The sequential derivative computation methods deliver similar results compared to FIM methods, while being computationally more efficient.     

Deformation behavior of migmatites: insights from microstructural analysis of a garnet–sillimanite–mullite–quartz–feldspar-bearing anatectic migmatite at Rampura–Agucha,Aravalli–Delhi Fold Belt,NW India

International Journal of Earth Sciences - In the present study we investigate the microstructural development in mullite, quartz and garnet in an anatectic migmatite hosted within a Grenvillian-age...     

MARLI: a mobile application for regional landslide inventories in Ecuador

The regions of Central and South America most susceptible to the occurrence of landslides will become even more vulnerable in the context of climate change. The Josefina disaster, in 1993, demonstrated both the vulnerability of local infrastructures and communities in the Paute River basin (Ecuador). Since this natural phenomena, several landslide inventories and susceptibility studies were developed, revealing the vulnerability of the Paute River basin to unstable terrain and the need for further studies throughout the basin. Despite this, no studies have been done since then to update the information generated. This paper describes a Mobile Application for Regional Landslide Inventories (MARLI), a simple but efficient open-access platform to report landslide events using the Open Data Kit system. Its design makes reporting fast, simple and cost-effective with an added benefit, and a specialized knowledge is not required for its use. MARLI was tested for the collection of landslides in Cuenca (Ecuador). From the data taken in the field, it was possible to analyze the performance and suitability of collected data and compare the results with regional inventories in the same area. Additionally, these results can be used for the elaboration and update of large-scale inventories or the training of automatic identification systems of landslides and later evaluation of their precision in a small-medium scale. Likewise, this product constitutes a fundamental input for the formulation of mitigation strategies, to formulate the appropriate response and in time, also the elaboration of reconstruction plans before the increase in the occurrence of such phenomena.

     

Spatiotemporal patterns of burned areas,fire drivers,and fire probability across the equatorial Andes

Field-based fire studies in the equatorial Andes indicate that fires are strongly associated with biophysical and anthropogenic variables. However, fire controls and fire regimes at the regional scale remain undocumented. Therefore, this paper describes spatial and temporal burned-area patterns, identifies biophysical and anthropogenic fire drivers, and quantifies fire probability across 6° of latitude and 3° of longitude in the equatorial Andes. The spatial and temporal burned-area analysis was carried out based on 18 years(2001-2018) of the MCD64 A1 MODIS burned-area product. Climate, topography, vegetation, and anthropogenic variables were integrated in a logistic regression model to identify the significance of explanatory variables and determine fire occurrence probability. A total of 5779 fire events were registered during the 18 years of this study, located primarily along the western cordillera of the Andes and spreading from North to South. Eighty-eight percent of these fires took place within two fire hotspots located in the northwestern and southwestern corners of the study area. Ninety-nine percent occurred during the second part of the year, between June and December. The largest density of fires was primarily located on herbaceous vegetation and shrublands. Results show that mean monthly temperature, precipitation and NDVI during the prefire season, the location of land cover classes such as forest and agriculture, distance to roads and urban areas, slope, and aspect were the most important determinants of spatial and temporal fire distribution. The logistic regression model achieved a good accuracy in predicting fire probability(80%). Probability was higher in the southwestern and northern corners of the study area, and lower towards the north in the western and eastern piedmonts of the Andes. This analysis contributes to the understanding of fires in mountains within the tropics. The results here presented have the potential to contribute to fire management and control in the region.     

Understanding the Past and Present and Predicting the Future: Farmers’ Use of Multiple Nutrient Best Management Practices in the Upper Midwest

Understanding what drives farmers’ voluntary adoption of nutrient and soil best management practices has important consequences for many environmental outcomes including water quality. We build on research revealing the need for simultaneous use of multiple nitrogen best management practices to achieve water quality improvement goals. Using social, economic and attitudinal variables we predict the use of multiple nitrogen best management practices at three time points: current use (2013), past use (before 2013), and likelihood of use on their largest field in the next three years. Our empirical analysis uses structural equation modeling with latent variables and 2014 farmer survey data from three Midwestern US states. Most farmers in our sample used at least one of the six best management practices. Our results reveal that farmers’ attitudes, use of information sources, and conservation program participation affect the number of nitrogen best management practices concurrently in use at multiple time points.