The response of the South Asian Summer Monsoon circulation to intensified irrigation in global climate model simulations

Agricultural intensification in South Asia has resulted in the expansion and intensification of surface irrigation over the twentieth century. The resulting changes to the surface energy balance could affect the temperature contrasts between the South Asian land surface and the equatorial Indian Ocean, potentially altering the South Asian Summer Monsoon (SASM) circulation. Prior studies have noted apparent declines in the monsoon intensity over the twentieth century and have focused on how altered surface energy balances impact the SASM rainfall distribution. Here, we use the coupled Goddard Institute for Space Studies ModelE-R general circulation model to investigate the impact of intensifying irrigation on the large-scale SASM circulation over the twentieth century, including how the effect of irrigation compares to the impact of increasing greenhouse gas (GHG) forcing. We force our simulations with time-varying, historical estimates of irrigation, both alone and with twentieth century GHGs and other forcings. In the irrigation only experiment, irrigation rates correlate strongly with lower and upper level temperature contrasts between the Indian sub-continent and the Indian Ocean (Pearson’s r = ?0.66 and r = ?0.46, respectively), important quantities that control the strength of the SASM circulation. When GHG forcing is included, these correlations strengthen: r = ?0.72 and r = ?0.47 for lower and upper level temperature contrasts, respectively. Under irrigated conditions, the mean SASM intensity in the model decreases only slightly and insignificantly. However, in the simulation with irrigation and GHG forcing, inter-annual variability of the SASM circulation decreases by ~40 %, consistent with trends in the reanalysis products. This suggests that the inclusion of irrigation may be necessary to accurately simulate the historical trends and variability of the SASM system over the last 50 years. These findings suggest that intensifying irrigation, in concert with increased GHG forcing, is capable of reducing the variability of the simulated SASM circulation and altering the regional moisture transport by limiting the surface warming and reducing land–sea temperature gradients.     

River rafting in mountainous regions of Uttarakhand: Impacts, suggested mitigation measures and sustainability

Uttarakhand state in India is well known for its mountainous ecosystems,traditional communities and a variety of ecotourism destinations.Among various tourism activities,River Rafting along the banks of the Ganges River has increased tremendously for two decades,and has had unprecedented impacts on the traditional communities and the bio-diversity.Therefore,it is meaningful to do a comprehensive study on the various impacts associated with river rafting so as to suggest the pathways to achieve the environmental sustainability in this region.In this study,we collected primary data from randomly selected population units across all stake holders such as local people(n = 100),and camp personnel(n = 22),through a pre-tested questionnaire survey between August 2009 and May 2010.The questionnaire contains issues on culture,social,economic,institutional and associated perceived impacts on pollution and biodiversity including views for sustainability.Secondary information was also collected from various sources and government records to supplement and strengthen the analysis.The impacts were analyzed qualitatively through a ranking mechanism to facilitate the decision making process.The perception of the interviewee about the various possible impacts of rafting was discussed with mitigating mechanism.The ranking analysis as percollected data reveals that economy and education of local community was improved significantly;however aquatic and terrestrial fauna,social cohesion and pollution(water,air,land) were significantly deteriorated.The results show that the existing practices are not sufficient to address the adverse impacts.Improvement in practices is necessary,mainly in the policy regime.Based on the analysis,some measures are recommended on how to protect community interest and environment with the development of river rafting as an ecotourism opportunity.     

Hurricane effects on subtropical pine rocklands of the Florida Keys

We investigate the effects of Hurricane Wilma??s storm surge (23?C24 October 2005) on the dominant tree Pinus elliottii var densa (South Florida slash pine) and rare plant species in subtropical pine rocklands of the Lower Florida Keys. We examine the role of elevation on species abundance in 1995 (Hurricane Betsy in 1965), 2005 (Hurricane Georges in 1998), and 2008 (Hurricane Wilma in 2005) to investigate if hurricanes influence abundance by eliminating plants at lower elevation on Big Pine Key, the largest island in the Lower Florida Keys. We compare densities before and after Hurricane Wilma over the 2005?C2008 sampling period and examine the role of elevation on changes in pine and rare species densities three years after Hurricane Wilma. We use elevation to assess the impact of hurricanes because elevation determined whether a location was influenced by storm surge (maximum surge of 2 m) in the Lower Florida Keys, where pine rocklands occur at a maximum elevation of 3 m. In 1995 (30 years after a major storm), elevation did not explain the abundance of South Florida slash pine or Chamaecrista lineata, but explained significant variation in abundance of Chamaesyce deltoidea. The latter two species are rare herbaceous plants restricted to pine rocklands. In 2008, 3 years after Hurricane Wilma, the positive relationship between elevation and abundance was strongest for South Florida slash pine, C. deltoidea, and C. lineata. Effects of Hurricane Wilma were not significant for rare species with wider distribution, occurring in plant communities adjacent to pine rocklands and in disturbed rocklands. Our results suggest that hurricanes drive population dynamics of South Florida slash pine and rare species that occur exclusively in pine rocklands at higher elevations. Rare species restricted to pine rocklands showed dramatic declines after Hurricane Wilma and were eliminated at elevations <0.5 m. Widely distributed rare species did not show significant changes in density after Hurricane Wilma. Abundance increased with elevation for South Florida slash pine and C. lineata after the hurricane. In an environment influenced by sea level rise, concrete plans to conserve pine ecosystems are warranted. Results from this study will help define conservation strategies by strengthening predictive understanding of plant responses to disturbance in the backdrop of sea level rise.     

Sea level rise and South Florida coastal forests

Coastal ecosystems lie at the forefront of sea level rise. We posit that before the onset of actual inundation, sea level rise will influence the species composition of coastal hardwood hammocks and buttonwood (Conocarpus erectus L.) forests of the Everglades National Park based on tolerance to drought and salinity. Precipitation is the major water source in coastal hammocks and is stored in the soil vadose zone, but vadose water will diminish with the rising water table as a consequence of sea level rise, thereby subjecting plants to salt water stress. A model is used to demonstrate that the constraining effect of salinity on transpiration limits the distribution of freshwater-dependent communities. Field data collected in hardwood hammocks and coastal buttonwood forests over 11 years show that halophytes have replaced glycophytes. We establish that sea level rise threatens 21 rare coastal species in Everglades National Park and estimate the relative risk to each species using basic life history and population traits. We review salinity conditions in the estuarine region over 1999?C2009 and associate wide variability in the extent of the annual seawater intrusion to variation in freshwater inflows and precipitation. We also examine species composition in coastal and inland hammocks in connection with distance from the coast, depth to water table, and groundwater salinity. Though this study focuses on coastal forests and rare species of South Florida, it has implications for coastal forests threatened by saltwater intrusion across the globe.     

Flood susceptibility modelling using advanced ensemble machine learning models

Floods are one of nature's most destructive disasters because of the immense damage to land, buildings, and human fatalities.It is difficult to forecast the areas that are vulnerable to flash flooding due to the dynamic and complex nature of the flash floods.Therefore, earlier identification of flash flood susceptible sites can be performed using advanced machine learning models for managing flood disasters.In this study, we applied and assessed two new hybrid ensemble models, namely Dagging and Random Subspace(RS) coupled with Artificial Neural Network(ANN), Random Forest(RF), and Support Vector Machine(SVM) which are the other three state-of-the-art machine learning models for modelling flood susceptibility maps at the Teesta River basin, the northern region of Bangladesh.The application of these models includes twelve flood influencing factors with 413 current and former flooding points, which were transferred in a GIS environment.The information gain ratio, the multicollinearity diagnostics tests were employed to determine the association between the occurrences and flood influential factors.For the validation and the comparison of these models, for the ability to predict the statistical appraisal measures such as Freidman, Wilcoxon signed-rank, and t-paired tests and Receiver Operating Characteristic Curve(ROC) were employed.The value of the Area Under the Curve(AUC) of ROC was above 0.80 for all models.For flood susceptibility modelling, the Dagging model performs superior, followed by RF,the ANN, the SVM, and the RS, then the several benchmark models.The approach and solution-oriented outcomes outlined in this paper will assist state and local authorities as well as policy makers in reducing flood-related threats and will also assist in the implementation of effective mitigation strategies to mitigate future damage.     

Land use intensity dynamics in the Andhikhola watershed,middle hill of Nepal

Land use intensity is a valuable concept to understand integrated land use system, which is unlike the traditional approach of analysis that often examines one or a few aspects of land use disregarding multidimensionality of the intensification process in the complex land system. Land use intensity is based on an integrative conceptual framework focusing on both inputs to and outputs from the land. Geographers' non-stationary data-analysis technique is very suitable for most of the spatial data analysis. Our study was carried out in the northeast part of the Andhikhola watershed lying in the Middle Hills of Nepal, where over the last two decades, heavy loss of labor due to outmigration of rural farmers and increasing urbanization in the relatively easy accessible lowland areas has caused agricultural land abandonment. Our intention in this study was to ascertain factors of spatial pattern of intensity dynamism between human and nature relationships in the integrated traditional agricultural system. High resolution aerial photo and multispectral satellite image were used to derive data on land use and land cover. In addition, field verification, information collected from the field and census report were other data sources. Explanatory variables were derived from those digital and analogue data. Ordinary Least Square(OLS) technique was used for filtering of the variables. Geographically Weighted Regression(GWR) model was used to identify major determining factors of land use intensity dynamics. Moran's I technique was used for model validation. GWR model was executed to identify the strength of explanatory variables explaining change of land use intensity. Accordingly, 10 variables were identified having the greatest strength to explain land use intensity change in the study area, of which physical variables such as slope gradient, temperature and solar radiation revealed the highest strength followed by variables of accessibility and natural resource. Depopulation in recent decades has been a major driver of land use intensity change but spatial variability of land use intensity was highly controlled by physical suitability, accessibility and availability of natural resources.     

Ranking of CMIP5-based global climate models for India using compromise programming

In this study, regional patterns of precipitation in Marmara are described for the first time by means of Ward’s hierarchical cluster analysis. Daily values of winter precipitation data based on 19 meteorological stations were used for the period from 1960 to 2012. Five clusters of coherent zones were determined, namely Black Sea-Marmara, Black Sea, Marmara, Thrace, and Aegean sub-regions. To investigate the prevailing atmospheric circulation types (CTs) that cause precipitation occurrence and intensity in these five different rainfall sub-basins, objective Lamb weather type (LWT) methodology was applied to National Centers of Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis of daily mean sea level pressure (MSLP) data. Precipitation occurrence suggested that wet CTs (i.e. N, NE, NW, and C) offer a high chance of precipitation in all sub-regions. For the eastern (western) part of the region, the high probability of rainfall occurrence is shown under the influence of E (SE, S, SW) atmospheric CTs. In terms of precipitation intensity, N and C CTs had the highest positive gradients in all the sub-basins of the Marmara. In addition, although Marmara and Black Sea sub-regions have the highest daily rainfall potential during NE types, high daily rainfall totals are recorded in all sub-regions except the Black Sea during NW types.