GIS based ecotourism potential assessment in Munessa Shashemene Concession Forest and its surrounding area,Ethiopia

This study aims to understand GIS based ecotourism potential of Munessa Shashemene Concession Forest and its surrounding area in Ethiopia. Landsat images from 2009/2010 and 2013 were used to drive baseline data including land cover, land use, stream and road. Elevation based agro-ecology and slope map were derived from SRTM DEM. Rapid wild animals survey, identifying the location of known historical, cultural and unique features were carried out in the filed with the help of key-informants. A suitability model was designed in GIS environment to assess the suitability of an area for tourism considering suitability factors such as land cover types, wild animal zone, unique features, topography and distance to a road. The result showed areas which are highly suitable, moderately suitable, marginally suitable, or unsuitable for tourism. The old giant, Podocarpus (Podocarpus falcatus) trees that serve as habitat of the endangered and endemic mountain nyala (Tragelaphus buxtoni), were identified as very high suitable areas for tourists. The highly suitable areas include forest area along the lake which is seasonally visited by mountain nyala and areas of plantation forest that are found adjacent to natural forest. These areas follow remnants of the natural forest and found along boundary between the mid-highland and the highland agro-ecologies. The agricultural land use types consisting of maize/haricot-bean and wheat/barley were evaluated as marginally suitable, nevertheless these could be considered as potential for agri-tourism. The study revealed that the concession area is found to be a suitable area with its huge potential for ecotourism development.     

Assessing the social context of wildfire-affected areas. The case of mainland Portugal

Wildfires cause different impacts, depending on the conditions and resilience level of the exposed communities. Wildfire occurrence in mainland Portugal was assessed with regard to socioeconomic and demographic parameters, to identify the most distinctive conditions of fire-affected areas, without implying the existence of causal relationships. The latest population and agriculture census data were used to retrieve conditions at the civil parish level, regarding demographic patterns, social and labor conditions, physical structures and agricultural activities. To identify differences between parishes, two groups were created with the communities that showed the highest and lowest 20% of wildfire incidence between 2007 and 2014, separately for density of fire events and for burned area. A stepwise approach based on classification trees and random Forest methods was applied to identify the best discriminant variables between the groups. First, irrelevant variables were removed by an interactive process based on misclassification rates. The second step used random Forest analysis to the remaining variables to evaluate their importance in distinguishing the groups. In the final step, cluster analysis was applied to test the correspondence between the clusters created with the selected variables and the initial groups. Results showed that parishes with higher fire density have higher population density, higher proportion of young and educated people, larger families and more overcrowded buildings. On the contrary, parishes with larger burned area are less populated, less attractive to foreigners, have a higher proportion of elderly people, more degraded housing conditions and agricultural activities, visible in the density of sheep and goat and pastures, are still relevant. The cluster analysis demonstrated a better performance of the model for wildfire density, revealing a strong association with socioeconomic dynamics with an agreement above 0.85, much higher than for burned areas which is 0.29. Overall, the spatial distribution of wildfire impacts is framed by societal settings and particular conditions must be further understood to improve the coping capacity of affected communities.     

Extending the conversation on socially engaged geographic visualization: representing spatial inequality in Buffalo,New York

This paper is situated at the intersections among GIS and geovisualization, critical social theory, and urban studies. It presents an analysis of housing segregation and unequal food and transportation access in Buffalo, New York. We demonstrate how the representation and examination of this socially complex multi-scalar issue benefits from deliberate, reflexive conversation between different critical social-spatial epistemologies. We begin with a relatively simple GIS analysis of spatial segregation and arrive through critical iteration at a more qualitatively nuanced cartogram which moves beyond representations of fixed space to reveal a much more relational situation—a case of “time-space expansion” in which the travel time needed to meet a basic daily need is much greater for the poor and people of color than it is for whiter, more affluent populations. We conclude by infusing this narrative with additional considerations from social theory to show how even a limited visualization such as ours might better critically engage broader social and discursive processes in and across urban space.     

Timber production assessment of a plantation forest: An integrated framework with field-based inventory,multi-source remote sensing data and forest management history

Timber production is the purpose for managing plantation forests, and its spatial and quantitative information is critical for advising management strategies. Previous studies have focused on growing stock volume (GSV), which represents the current potential of timber production, yet few studies have investigated historical process-harvested timber. This resulted in a gap in a synthetical ecosystem service assessment of timber production. In this paper, we established a Management Process–based Timber production (MPT) framework to integrate the current GSV and the harvested timber derived from historical logging regimes, trying to synthetically assess timber production for a historical period. In the MPT framework, age-class and current GSV determine the times of historical thinning and the corresponding harvested timber, by using a “space-for-time” substitution. The total timber production can be estimated by the historical harvested timber in each thinning and the current GSV. To test this MPT framework, an empirical study on a larch plantation (LP) with area of 43,946 ha was conducted in North China for a period from 1962 to 2010. Field-based inventory data was integrated with ALOS PALSAR (Advanced Land-Observing Satellite Phased Array L-band Synthetic Aperture Radar) and Landsat-8 OLI (Operational Land Imager) data for estimating the age-class and current GSV of LP. The random forest model with PALSAR backscatter intensity channels and OLI bands as input predictive variables yielded an accuracy of 67.9% with a Kappa coefficient of 0.59 for age-class classification. The regression model using PALSAR data produced a root mean square error (RMSE) of 36.5 m³ ha⁻¹. The total timber production of LP was estimated to be 7.27 × 10⁶ m³, with 4.87 × 10⁶ m³ in current GSV and 2.40 × 10⁶ m³ in harvested timber through historical thinning. The historical process-harvested timber accounts to 33.0% of the total timber production, which component has been neglected in the assessments for current status of plantation forests. Synthetically considering the RMSE for predictive GSV and misclassification of age-class, the error in timber production were supposed to range from −55.2 to 56.3 m³ ha⁻¹. The MPT framework can be used to assess timber production of other tree species at a larger spatial scale, providing crucial information for a better understanding of forest ecosystem service.     

Study of discontinuities in hydrological data using catastrophe theory

Abstract

Modelling and prediction of hydrological processes (e.g. rainfall–runoff) can be influenced by discontinuities in observed data, and one particular case may arise when the time scale (i.e. resolution) is coarse (e.g. monthly). This study investigates the application of catastrophe theory to examine its suitability to identify possible discontinuities in the rainfall–runoff process. A stochastic cusp catastrophe model is used to study possible discontinuities in the monthly rainfall–runoff process at the Aji River basin in Azerbaijan, Iran. Monthly-averaged rainfall and flow data observed over a period of 20 years (1981–2000) are analysed using the Cuspfit program. In this model, rainfall serves as a control variable and runoff as a behavioural variable. The performance of this model is evaluated using four measures: correlation coefficient, log-likelihood, Akaike information criterion (AIC) and Bayesian information criterion (BIC). The results indicate the presence of discontinuities in the rainfall–runoff process, with a significant sudden jump in flow (cusp signal) when rainfall reaches a threshold value. The performance of the model is also found to be better than that of linear and logistic models. The present results, though preliminary, are promising in the sense that catastrophe theory can play a possible role in the study of hydrological systems and processes, especially when the data are noisy.

Citation Ghorbani, M. A., Khatibi, R., Sivakumar, B. & Cobb, L. (2010) Study of discontinuities in hydrological data using catastrophe theory. Hydrol. Sci. J. 55(7), 1137–1151.     

A spatially distributed Clark’s unit hydrograph based hybrid hydrologic model (Distributed-Clark)

ABSTRACT

A hybrid hydrologic model (Distributed-Clark), which is a lumped conceptual and distributed feature model, was developed based on the combined concept of Clark’s unit hydrograph and its spatial decomposition methods, incorporating refined spatially variable flow dynamics to implement hydrological simulation for spatially distributed rainfall–runoff flow. In Distributed-Clark, the Soil Conservation Service (SCS) curve number method is utilized to estimate spatially distributed runoff depth and a set of separated unit hydrographs is used for runoff routing to obtain a direct runoff flow hydrograph. Case studies (four watersheds in the central part of the USA) using spatially distributed (Thiessen polygon-based) rainfall data of storm events were used to evaluate the model performance. Results demonstrate relatively good fit to observed streamflow, with a Nash-Sutcliffe efficiency (E_NS) of 0.84 and coefficient of determination (R²) of 0.86, as well as a better fit in comparison with outputs of spatially averaged rainfall data simulations for two models including HEC-HMS.     

Incorporating groundwater recharge and discharge functions into an existing monthly rainfall–runoff model/Incorporation de fonctions de recharge et de vidange superficielle de nappes au sein d’un modèle pluie-débit mensuel existant

Abstract

Abstract There is an urgent need for an integrated surface water and groundwater modelling tool that is suitable for southern African conditions and can be applied at various basin scales for broad strategic water resource planning purposes. The paper describes two new components (recharge and groundwater discharge) that have been added to an existing monthly time-step rainfall–runoff model that is widely used in the southern African subcontinent. The new components are relatively simple, consistent with the existing model formulation, but based on accepted groundwater flow principles and well understood groundwater parameters. The application of the revised model on two basins in southern Africa with quite different baseflow characteristics has demonstrated that the new components have a great deal of potential, even if the improvement is only to be able to simulate the groundwater baseflow component of total runoff more explicitly. More comprehensive testing and comparison of the results with existing groundwater and geohydrological data is required, while some extensions to the new components need to be considered to ensure that the model can be considered applicable to a wide range of basin and climate types.     

Controls on Devonian–Carboniferous magmatism in Tasmania,based on inherited zircon age patterns,Sr, Nd and Pb isotopes,and major and trace element geochemistry

Devonian–Carboniferous granites are widespread in Tasmania. In eastern Tasmania, Devonian granites intrude Ordovician–Early Devonian quartz-rich turbidites of the Mathinna Supergroup. The earliest (～400 Ma) I-type granodiorites may be arc-related. Following the Tabberabberan Orogeny (～389 Ma), more felsic and, finally, strongly fractionated I- and S-type granites were emplaced until ～373 Ma. In contrast, western Tasmania granites intrude a more diverse terrane of predominantly marine shelf successions, with depositional ages as old as Late Mesoproterozoic. They are mostly felsic and fractionated I- and S-types emplaced from ～374–351 Ma, possibly in response to post-collisional crustal extension following juxtaposition of the eastern and western Tasmanian terranes. Granites from the two terranes are readily distinguishable by the age spectra of their inherited zircon, which are noticeably similar to those of the detrital zircon from sedimentary successions in their respective terranes. Furthermore, within each terrane, both I and S-types yield similar inheritance patterns. This suggests a pivotal role for the sedimentary successions in the petrogenesis of both types. Western Tasmanian granites are also enriched in ～1600 Ma zircon, which is essentially unrepresented in the exposed supracrustal succession. Subtle differences between the inheritance and detrital age spectra in eastern Tasmania probably relate to unrepresentative sampling of the supracrustal rocks. Nd, Sr and Pb isotopic characteristics of the granites are consistent with their derivation by mixing of magmas derived from the mantle, possibly the lower crust, and from supracrustal rocks. Systematic isotopic trends in some eastern Tasmanian I-types, particularly in the Scottsdale Batholith, correlate well with major and trace element geochemistry and age. The isotopes are inconsistent with simple restite unmixing or crystal fractionation in a closed magma chamber, and indicate progressive contamination by the Mathinna Supergroup, or similar rocks. The isotopic characteristics of late, strongly fractionated granites, although sometimes obscured by hydrothermal alteration, are also consistent with concurrent assimilation-fractional crystallisation processes. Together with the close association of some strongly fractionated I- and S-types, this suggests that such granites were generated directly in the lower crust, and were not derived from unfractionated parental granite magmas.     

Increasing water losses from snow captured in the canopy of boreal forests: A case study using a 30 year data set

Water losses from snow intercepted by forest canopy can significantly influence the hydrological cycle in seasonally snow‐covered regions, yet how snow interception losses (SIL) are influenced by a changing climate are poorly understood. In this study, we used a unique 30 year record (1986–2015) of snow accumulation and snow water equivalent measurements in a mature mixed coniferous (Picea abies and Pinus sylvestris ) forest stand and an adjacent open area to assess how changes in weather conditions influence SIL. Given little change in canopy cover during this study, the 20% increase in SIL was likely the result of changes in winter weather conditions. However, there was no significant change in average wintertime precipitation and temperature during the study period. Instead, mean monthly temperature values increased during the early winter months (i.e., November and December), whereas there was a significant decrease in precipitation in March. We also assessed how daily variation in meteorological variables influenced SIL and found that about 50% of the variation in SIL was correlated to the amount of precipitation that occurred when temperatures were lower than ?3 °C and to the proportion of days with mean daily temperatures higher than +0.4 °C. Taken together, this study highlights the importance of understanding the appropriate time scale and thresholds in which weather conditions influence SIL in order to better predict how projected climate change will influence snow accumulation and hydrology in boreal forests in the future.