Impact of Climate Change on Runoff of the Major River Basins of India Using Global Circulation Model (HadCM3) Projected Data

The effects of climate change on hydrological regimes have become a priority area for water and catchment management strategies. The terrestrial hydrology driven by monsoon rainfall plays a crucial role in shaping the agriculture, surface and ground water scenario in India. Thus, it is imperative to assess the impact of the changing climatic scenario projected under various climate change scenario towards the hydrological aspects for India. Runoff is one of the key parameters used as an indicator of hydrological process. A study was taken up to analyse the climate change impact on the runoff of river basins of India. The global circulation model output of Hadley centre (HADCM3) projected climate change data was used. Scenario for 2080 (A2 scenario indicating more industrial growth) was selected. The runoff was modeled using the curve number method in spatial domain using satellite derived current landuse/cover map. The derived runoff was compared with the runoff using normal climatic data (1951–1980). The results showed that there is a decline in the future climatic runoff in most of the river basins of India compared to normal climatic runoff. However, significant reduction was observed for the river basins in the eastern region viz: lower part of Ganga, Bahamani-Baitrani, Subarnrekha and upper parts of the Mahanadi. The mean projected runoff reduction during monsoon season (June–September) were 18 Billion Cubic Meter (BCM), 3.2 BCM, 3.5 BCM and 5.9 BCM for Brahmaputra-Barak Subarnrekha, Subarnarekha and Brahmini-Baitrani basin, respectively in comparison to normal climatic runoff. Overall reduction in seasonal runoff was high for Subarnrekha basin (54.1%). Rainfall to runoff conversion was high for Brahmaputra-Barak basin (72%), whereas coefficient of variation for runoff was more for Mahanadi basin (1.88) considering the monsoon season. Study indicates that eastern India agriculture may be affected due to shortage of surface water availability.     

Modeling projected changes of mangrove biomass in different climatic scenarios in the Sunda Banda Seascapes

ABSTRACT

Mangroves are critical in the ecological, economic and social development of coastal rural and urban communities. However, they are under threat by climate change and anthropogenic activities. The Sunda Banda Seascape (SBS), Indonesia, is among the world’s richest regions of mangrove biomass and biodiversity. To inform current and future management strategies, it is critical to provide estimates of how mangroves will respond to climate change in this region. Therefore, this paper utilized spatial analysis with model-based climatic indicators (temperature and precipitation) and mangrove distribution maps to estimate a benchmark for the mangrove biomass of the SBS in six scenarios, namely the Last Inter-glacial Period, the current scenario (1950–2000) and all four projected Representative Concentration Pathways in 2070 due to climate change. Despite mangroves gaining more biomass with climate change (the increase in CO₂ concentration), this paper highlighted the great proportion of below-ground biomass in mangrove forests. It also showed that the changes in spatial distribution of mangrove biomass became more variable in the context of climate change. As mangroves have been proposed as an essential component of climate change strategies, this study can serve as a baseline for future studies and resource management strategies.     

Future productivity and phenology changes in European grasslands for different warming levels: implications for grassland management and carbon balance

Background

Europe has warmed more than the global average (land and ocean) since pre-industrial times, and is also projected to continue to warm faster than the global average in the twenty-first century. According to the climate models ensemble projections for various climate scenarios, annual mean temperature of Europe for 2071–2100 is predicted to be 1–5.5 °C higher than that for 1971–2000. Climate change and elevated CO₂ concentration are anticipated to affect grassland management and livestock production in Europe. However, there has been little work done to quantify the European-wide response of grassland to future climate change. Here we applied ORCHIDEE-GM v2.2, a grid-based model for managed grassland, over European grassland to estimate the impacts of future global change.

Results

Increases in grassland productivity are simulated in response to future global change, which are mainly attributed to the simulated fertilization effect of rising CO₂. The results show significant phenology shifts, in particular an earlier winter-spring onset of grass growth over Europe. A longer growing season is projected over southern and southeastern Europe. In other regions, summer drought causes an earlier end to the growing season, overall reducing growing season length. Future global change allows an increase of management intensity with higher than current potential annual grass forage yield, grazing capacity and livestock density, and a shift in seasonal grazing capacity. We found a continual grassland soil carbon sink in Mediterranean, Alpine, North eastern, South eastern and Eastern regions under specific warming level (SWL) of 1.5 and 2 °C relative to pre-industrial climate. However, this carbon sink is found to saturate, and gradually turn to a carbon source at warming level reaching 3.5 °C.

Conclusions

This study provides a European-wide assessment of the future changes in productivity and phenology of grassland, and their consequences for the management intensity and the carbon balance. The simulated productivity increase in response to future global change enables an intensification of grassland management over Europe. However, the simulated increase in the interannual variability of grassland productivity over some regions may reduce the farmers’ ability to take advantage of the increased long-term mean productivity in the face of more frequent, and more severe drops of productivity in the future.

     

青藏高原湖泊面积、水位与水量变化遥感监测研究进展

青藏高原湖泊数量多、分布广、所占面积大,是亚洲水塔的重要组成部分,其受到人类活动的干扰较少,是理解高原生态环境变化机理的钥匙.青藏高原湖泊是气候变化敏感的指示器,在全球快速变暖背景下其对气候变化的响应如何?本研究基于多源遥感数据监测结果,系统地总结了青藏高原湖泊(大于1 km2)在过去近50 a(1976年-2018年...     

Annual variations in water storage and precipitation in the Amazon Basin

We combine satellite gravity data from the gravity recovery and climate experiment (GRACE) and precipitation measurements from the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center’s (CPC) Merged Analysis of Precipitation (CMAP) and the Tropical Rainfall Measuring Mission (TRMM), over the period from mid-2002 to mid-2006, to investigate the relative importance of sink (runoff and evaporation) and source (precipitation) terms in the hydrological balance of the Amazon Basin. When linear and quadratic terms are removed, the time-series of land water storage variations estimated from GRACE exhibits a dominant annual signal of 250 mm peak-to-peak, which is equivalent to a water volume change of ~1,800 km³. A comparison of this trend with accumulated (i.e., integrated) precipitation shows excellent agreement and no evidence of basin saturation. The agreement indicates that the net runoff and evaporation contributes significantly less than precipitation to the annual hydrological mass balance. Indeed, raw residuals between the de-trended water storage and precipitation anomalies range from ±40 mm. This range is consistent with stream-flow measurements from the region, although the latter are characterized by a stronger annual signal than our residuals, suggesting that runoff and evaporation may act to partially cancel each other.     

Biodiversity Conservation in the REDD

Background

Forests occur across diverse biomes, each of which shows a specific composition of plant communities associated with the particular climate regimes. Predicted future climate change will have impacts on the vulnerability and productivity of forests; in some regions higher temperatures will extend the growing season and thus improve forest productivity, while changed annual precipitation patterns may show disadvantageous effects in areas, where water availability is restricted. While adaptation of forests to predicted future climate scenarios has been intensively studied, less attention was paid to mitigation strategies such as the introduction of tree species well adapted to changing environmental conditions.

Results

We simulated the development of managed forest ecosystems in Germany for the time period between 2000 and 2100 under different forest management regimes and climate change scenarios. The management regimes reflect different rotation periods, harvesting intensities and species selection for reforestations. The climate change scenarios were taken from the IPCC's Special Report on Emission Scenarios (SRES). We used the scenarios A1B (rapid and successful economic development) and B1 (high level of environmental and social consciousness combined with a globally coherent approach to a more sustainable development). Our results indicate that the effects of different climate change scenarios on the future productivity and species composition of German forests are minor compared to the effects of forest management.

Conclusions

The inherent natural adaptive capacity of forest ecosystems to changing environmental conditions is limited by the long life time of trees. Planting of adapted species and forest management will reduce the impact of predicted future climate change on forests.     

Driving forces of grassland vegetation changes in Chen Barag Banner,Inner Mongolia

ABSTRACT

Inner Mongolia is an important ecological zone of northern China and 67% of its land area is grassland. This ecologically fragile region has experienced significant vegetation degradation during the last decades. Although the spatial extents and rates of vegetation change have previously been characterized through various remote sensing and GIS studies, the underlying driving factors of vegetation changes are still not well understood. In this study, we first used time-series MODIS NDVI data from 2000 to 2016 to characterize the temporal trend of vegetation changes. These vegetation change trends were compared with climate and socioeconomic variables to determine the potential drivers. We used a set of statistical methods, including multiple linear regression (MLR), spatial correlation analysis, and partial least squares (PLS) regression analyzes, to quantify the spatial distribution of the driving forces and their relative importance to vegetation changes. Results show that the main driving factors and their impact magnitude (weight) are in the order of human activities (r = -0.785, p < 0.01, VIP = 1.37), precipitation (r = 0.541, p < 0.05, VIP = 0.89), temperature (r = -0.319, p > 0.05 VIP = 0.59). The area affected by human activities was 10.57%. Specific human activities, such as coal mining and grazing were negatively associated with vegetation cover, while eco-engineering projects had positive impacts. This study provided thorough quantification of driving forces of vegetation change and enhanced our understanding of their interactions. Our integrated geospatial-statistical approach is particularly important for sustainable development of ecosystem balance in Chen Barag Banner and other areas facing similar challenges.     

Assessment of Post-fire Soil Erosion Risk in Fire-Affected Watersheds Using Remote Sensing and GIS

Soil erosion is a prominent cause of land degradation and desertification in Mediterranean countries. The detrimental effects of soil erosion are exemplified in climate (in particular climate change), topography, human activities, and natural disasters. Forest fires, which are an integral part of Mediterranean ecosystems, are responsible for the destruction of above-and below-ground vegetation that protects against soil erosion. Under this perspective, the estimation of potential soil erosion, especially after fire events, is critical for identifying watersheds that require management to prevent sediment loss, flooding, and increased ecosystem degradation. The objective of this study was to model the potential post-fire soil erosion risk following a large and intensive wildland fire, in order to prioritize protection and management actions at the watershed level in a Mediterranean landscape. Burn severity and preand post-fire land cover/uses were mapped using an ASTER image acquired two years before the fire, air photos acquired shortly after the fire, and a Landsat TM image acquired within one month after-fire. We estimated pre-and post-fire sediment loss using an integrated GIS-based approach, and additionally we analyzed landscape erosion patterns. The overall accuracy of the severity map reached 83%. Severe and heavy potential erosion classes covered approximately 90% of the total area following the fire, compared to 55% before. The fire had a profound effect on the spatial erosion pattern by altering the distribution of the potential erosion classes in 21 out of 24 watersheds, and seven watersheds were identified as being the most vulnerable to post-fire soil erosion. The spatial pattern of the erosion process is important because landscape cover heterogeneity induced especially by fire is a dominant factor controlling runoff generation and erosion rate, and should be considered in post-fire erosion risk assessment.     

Effects of climate change on forests of the eastern United States

A multi‐phased approach was used to estimate potential impacts of climate change on forests of the eastern United States. Phase I was at community‐level and Phase II examined selected species, both using three 2 x CO₂ climate scenarios. Geographic information systems (GIS) and statistical modeling techniques were used to manipulate and analyze climate and vegetation data, and model vegetation responses to climate change. The first two stages of the study indicated possible large‐scale alteration of forest communities by future climate change. Although results varied among climate models, several trends were apparent. In northern states of the study area, ranges of several conifers declined significantly and ranges of oaks and hickories moved northward. In central states, ranges of sugar maple and tulip poplar became much smaller, with concomitant increases in ranges of southern oaks and loblolly pine. In . southern states, American beech declined and ranges of southern oaks increased northward. This paper discusses results of the first two phases and current progress of the third phase.     

Digital Earth in support of global change research

Abstract

The Digital Earth concept as originally proposed by former US Vice president Al Gore is now well established and widely adopted internationally. Similarly, many researchers world-wide are studying the causes, effects and impacts of Global Change. The authors commence by describing a five-step approach to the development of Digital Earth technologies. This is followed by a detailed account of Digital Earth research and developments in China. The authors then present the research results of Global Change studies carried out in China, based on the Digital Earth approach. These research results are based on a classification of global change regions. This covers the following global change situations:

Forest and grassland fires in Northern China, temperate region desertification and dust storms, underground coal fires, deforestation and carbon sequestration, protection and utilisation of wetlands, Avian Influenza and the spread of diseases, Tibet Plateau uplift and sub-tropical monsoon climate region, and sea-level rise. The research results show that the environment does not behave in a way easily understood by the traditional disciplinary approach. Although man is clearly a contributing factor to certain Global Change aspects, such as underground coal fires, desertification, land use changes etc., many of the aspects of Global Change are naturally occurring phenomena which have been changing over centuries, and will continue to do so, no matter what actions we undertake to reverse these processes. Hence, in their conclusions, the authors propose that the communities involved in Digital Earth modelling and in Global Change research co-operate closer to overcome the limitations inherent in the current ‘conventional’ scientific approach, where scientists have very much stayed within their respective scientific boundaries. Such an integrated approach will enable us to build the next level of scientific infrastructure required to understand and predict naturally occurring environmental changes, as well as that of coupled human–environmental systems.     

Land Cover Change and Associated Trends in Surface Reflectivity and Vegetation Index in Southwest Kansas: 1972-1992

Abstract

Land cover is an important component of the earth system. Human induced surface alteration can affect earth systems directly, through loss or degradation of ecosystems, or indirectly through impact on the climate and biogeochemical cycles necessary to sustain life on earth. The significance of the earth's surface has made land use/land cover change an important issue in global change research. Alteration of land cover occurs at a variety of spatial scales, but as with many environmental change issues, the impacts of surface changes are often conceptualized at the global scale. In this study, we investigate the effects of land cover change on total reflected radiation and the Normalized Difference Vegetation Index (NDVI) in a 10,000 km² local area in the High Plains of southwestern Kansas. Landsat MSS data from five years of record within the twenty‐year period 1973 to 1992 were classified into cool season crop, warm season crop, and pasture/prairie. Mean values of summer reflectance and NDVI from each cover type and for the study area as a whole were then analyzed for systematic change over the study period. Both reflectivity and vegetation index increased during the study period, although causes for the increase appear to be different. Results suggest that changes in mean surface reflectance in the study site are strongly influenced by land cover change, whereas changes in NDVI are more closely linked to 50‐day antecedent precipitation.     

中国城市洪涝实时预报研究:现状与挑战

全球气候变化和快速城市化打破了城市降水—汇水—排水原有的平衡,加剧了中国城市洪涝问题,造成了巨大的生命和财产损失。因此,亟须探索精确、高效的城市洪涝预报方法,提高城市防洪抗灾能力,降低灾害损失影响。然而,城市气象水文过程的复杂性使得城市洪涝实时预报研究面临诸多挑战。本文梳理了我国城市洪涝频发的原因,总结了国内城市洪涝实时预报研究在数据和模型方面的进展,指出了当前研究面临的问题和挑战,并对未来的发展趋势进行了展望,以期为我国城市防洪减灾研究和工作提供参考依据。     

A comparative assessment of catchment runoff generation and forest productivity in a semi-arid environment

Understanding the dynamic interactions between forest ecosystems and water in the Mediterranean region is essential for increasing ecosystem services. Even if many studies were implemented to analyse the variations of water and net primary productivity (NPP) in the last decade, this is still an important research question especially for the Eastern Mediterranean, where the research attempts are limited. The main objective of this study was to carry out a comparative analysis of catchment runoff generation and forest NPP and to reveal their temporal dynamics at basin scale in a semi-arid Mediterranean environment. The methodology consisted three steps: (i) estimating catchment runoff generation by implementing process-based J2000 modelling suite, (ii) modelling NPP of the land cover/use types by adapting an ecosystem-process model (BIOME-Biogeochemical cycles) and (iii) assessing the spatio-temporal variability of NPP and runoff dynamics by incorporating the modelling results with multiple regression analysis. Model simulations showed that temperature highly contributed to NPP variations of needle-leaf forests and grasslands. The multiple regression analysis also indicated that runoff was influenced by elevation, precipitation and forest cover. This relationship showed that the inter-annual variability in forest NPP would relate to the variations in runoff distribution across a small Mediterranean subcatchment.     

Use of multi-temporal Landsat images for analyzing forest transition in relation to socioeconomic factors and the environment

Recently there have been reports of forest regrowth occurring in different regions across the world. There is also a growing recognition of the potential beneficial impact that secondary forests may have on the global environment: providing crucial ecosystem services such as soil conservation, stabilization of hydrological cycles, carbon sequestration, and support for forest dependent communities. Consequently, there is a growing awareness of the need to recognize that landscapes are complex shifting mosaics wherein forest clearing and reforestation take place. In this study, the rates of reforestation, deforestation, forest regrowth and degradation were measured using multi-temporal Landsat images of Danjiangkou, China. Landsat data from 1990, 1999 and 2007 were (1) classified as dense forest, open forest and non-forest areas and (2) compared between years to identify forest cutting, regeneration and degradation. The results showed that there was a net gain of 29,315 ha of forest area (including dense and open forest) from 1990 to 2007, showing a clear trend of reforestation in the study area. Forest modification (degradation and regrowth) and change categories (deforestation and reforestation) occurred simultaneously during the observation time period. Socioeconomic data from public statistics and environmental attributes allowed the assessment of the socioeconomic factors and the environmental conditions that caused these changes using non-metric multidimensional scaling (NMDS). The research showed that the socioeconomic factors due to different policies were major driving forces of forest transition, whereas environmental attributes of the underlying landscape constrained forest cover changes. These findings have led to a better understanding of forest transition at a local scale in our study region. Comprehensive knowledge of these relationships may be useful to reconstruct past forest transitions and predict future changes, and may help to enhance sustainable management practices aimed at preserving essential ecological functions.     

Assessing urbanisation effects on rainfall-runoff using a remote sensing supported modelling strategy

This paper aims at developing a methodology for assessing urban dynamics in urban catchments and the related impact on hydrology. Using a multi-temporal remote sensing supported hydrological modelling approach an improved simulation of runoff for urban areas is targeted. A time-series of five medium resolution urban masks and corresponding sub-pixel sealed surface proportions maps was generated from Landsat and SPOT imagery. The consistency of the urban mask and sealed surface proportion time-series was imposed through an urban change trajectory analysis. The physically based rainfall-runoff model WetSpa was successfully adapted for integration of remote sensing derived information of detailed urban land use and sealed surface characteristics.A first scenario compares the original land-use class based approach for hydrological parameterisation with a remote sensing sub-pixel based approach. A second scenario assesses the impact of urban growth on hydrology. Study area is the Tolka River basin in Dublin, Ireland.The grid-based approach of WetSpa enables an optimal use of the spatially distributed properties of remote sensing derived input.Though change trajectory analysis remains little used in urban studies it is shown to be of utmost importance in case of time series analysis. The analysis enabled to assign a rational trajectory to 99% of all pixels. The study showed that consistent remote sensing derived land-use maps are preferred over alternative sources (such as CORINE) to avoid over-estimation errors, interpretation inconsistencies and assure enough spatial detail for urban studies. Scenario 1 reveals that both the class and remote sensing sub-pixel based approaches are able to simulate discharges at the catchment outlet in an equally satisfactory way, but the sub-pixel approach yields considerably higher peak discharges. The result confirms the importance of detailed information on the sealed surface proportion for hydrological simulations in urbanised catchments. In addition a major advantage with respect to hydrological parameterisation using remote sensing is the fact that it is site- and period-specific. Regarding the assessment of the impact of urbanisation (scenario 2) the hydrological simulations revealed that the steady urban growth in the Tolka basin between 1988 and 2006 had a considerable impact on peak discharges. Additionally, the hydrological response is quicker as a result of urbanisation. Spatially distributed surface runoff maps identify the zones with high runoff production.It is evident that this type of information is important for urban water management and decision makers. The results of the remote sensing supported modelling approach do not only indicate increased volumes due to urbanisation, but also identifies the locations where the most relevant impacts took place.     

Modelling tropical cyclone risks for present and future climate change scenarios using geospatial techniques

Tropical cyclones and their devastating impacts are of great concern to coastal communities globally. An appropriate approach integrating climate change scenarios at local scales is essential for producing detailed risk models to support cyclone mitigation measures. This study developed a simple cyclone risk-modelling approach under present and future climate change scenarios using geospatial techniques at local scales, and tested using a case study in Sarankhola Upazila from coastal Bangladesh. Linear storm-surge models were developed up to 100-year return periods. A local sea level rise scenario of 0.34?m for the year 2050 was integrated with surge models to assess the climate change impact. The resultant storm-surge models were used in the risk-modelling procedures. The developed risk models successfully identified the spatial extent and levels of risk that match with actual extent and levels within an acceptable limit of deviation. The result showed that cyclone risk areas increased with the increase of return period. The study also revealed that climate change scenario intensified the cyclone risk area by 5–10% in every return period. The findings indicate this approach has the potential to model cyclone risk in other similar coastal environments for developing mitigation plans and strategies.     

Communicating climate change: spatial analog versus color-banded isoline maps with and without accompanying text

People discount projected impacts of climate change that they see as spatially or temporally remote. To overcome this, climate change outreach must communicate impacts as local, concrete, immediate, and situated in a well-understood frame of reference. Spatial-analog mapping may meet this challenge: by drawing on people’s experience of existing climates, this technique matches a locality’s projected climates with present-day climates of other localities. However, analog maps’ effect on climate impact perceptions has not been compared with the effect on climate impact perceptions elicited by standard climate change mapping techniques. Accordingly, this study considers whether residents of Centre Region, Pennsylvania, who are shown spatial-analog maps for future Centre Region temperatures, perceive impacts as more salient than do residents shown the same temperature-change information directly using color-banded isallotherm maps. It also considers how responses differ when this information is presented using only text, only maps, or both maps and text. An online survey of 3094 members of 11 Centre Region organizations presents the maps and/or text and then assesses respondents’ impact perceptions. Based on 444 valid responses, the study finds that respondents, using spatial-analog survey forms, generally expect impacts to be less severe and disruptive than respondents using temperature-change forms. It also finds that respondents using survey forms with maps generally expect impacts to be more severe and disruptive than respondents using text-only forms. Climate change communicators who wish to improve understanding and engagement should therefore strongly consider using maps where possible, but should exercise caution before using spatial-analog approaches.     

Monitoring Intraurban temperature patterns and associated land cover in phoenix,Arizona using Landsat thermal data

Abstract

This study investigates urban climatologic modification associated with development and changing land use in the relatively arid urban environment of Phoenix, Arizona. An analysis of surface temperatures, as portrayed on Landsat thermal remotely sensed data, were compared to current land use patterns in regions of the rapidly expanding urban landscape. A second focus of this study involved investigation of the surface temperatures of this environment, as extracted from the radiometric data of the Landsat thermal band, to provide insights into the complexities of the relationship to the near‐surface atmospheric temperature, a parameter used extensively in climate change analyses and in models for energy and water demand in this desert region. The near surface air temperature is usually measured approximately two meters above the ground surface. In general, spatial temperature patterns of the metropolitan region were strongly correlated with the presence of open water or biomass which provide an evapotranspirative heat sink.     

青藏高原纳木错湖冰物候变化遥感监测与模拟

湖冰物候是反映区域气候变化的直观指标.由于青藏高原湖冰物候的地面观测不足,遥感与模拟成为动态监测湖冰物候变化并揭示其变化机理的重要途径.本文以纳木错为例,通过不同遥感方法获取了纳木错2000年-2015年湖冰物候的动态变化.在此基础上,将遥感与物理基础清晰的湖泊过程模型相结合,重建了纳木错1963年-2018年的湖冰物...     

Detecting patterns of climate change in long-term forecasts of marine environmental parameters

ABSTRACT

Forecasting environmental parameters in the distant future requires complex modelling and large computational resources. Due to the sensitivity and complexity of forecast models, long-term parameter forecasts (e.g. up to 2100) are uncommon and only produced by a few organisations, in heterogeneous formats and based on different assumptions of greenhouse gases emissions. However, data mining techniques can be used to coerce the data to a uniform time and spatial representation, which facilitates their use in many applications. In this paper, streams of big data coming from AquaMaps and NASA collections of 126 long-term forecasts of nine types of environmental parameters are processed through a cloud computing platform in order to (i) standardise and harmonise the data representations, (ii) produce intermediate scenarios and new informative parameters, and (iii) align all sets on a common time and spatial resolution. Time series cross-correlation applied to these aligned datasets reveals patterns of climate change and similarities between parameter trends in 10 marine areas. Our results highlight that (i) the Mediterranean Sea may have a standalone ‘response’ to climate change with respect to other areas, (ii) the Poles are most representative of global forecasted change, and (iii) the trends are generally alarming for most oceans.