The prediction of seasonal and inter-annual climate variations and their impacts on the water resources in the eastern seaboard of Thailand

The research of this thesis dissertation covers developments and applications of short-and long-term climate predictions. The short-term prediction emphasizes monthly and seasonal climate, i.e. forecasting from up to the next month over a season to up to a year or so. The long-term predictions pertain to the analysis of inter-annual- and decadal climate variations over the whole 21st century. These two climate prediction methods are validated and applied in the study area, namely, Khlong Yai (KY) water basin located in the eastern seaboard of Thailand which is a major industrial zone of the country and which has been suffering from severe drought and water shortage in recent years. Since water resources are essential for the further industrial development in this region, a thorough analysis of the potential climate change with its subsequent impact on the water supply in the area is at the heart of this thesis research. The short-term forecast of the next-season climate, such as temperatures and rainfall, offers a potential general guideline for water management and reservoir operation. To that avail, statistical models based on autoregressive techniques, i.e., AR-, ARIMA- and ARIMAex-, which includes additional external regressors, and multiple linear regression- (MLR) models, are developed and applied in the study region. Teleconnections between ocean states and the local climate are investigated and used as extra external predictors in the ARIMAex- and the MLR-model and shown to enhance the accuracy of the short-term predictions significantly. However, as the ocean state – local climate teleconnective relationships provide only a one- to four-month ahead lead time, the ocean state indices can support only a one-season-ahead forecast. Hence, GCM- climate predictors are also suggested as an additional predictor-set for a more reliable and somewhat longer short-term forecast. For the preparation of “pre-warning” information for up-coming possible future climate change with potential adverse hydrological impacts in the study region, the long-term climate prediction methodology is applied. The latter is based on the downscaling of climate predictions from several single- and multi-domain GCMs, using the two well-known downscaling methods SDSM and LARS-WG and a newly developed MLR-downscaling technique that allows the incorporation of a multitude of monthly or daily climate predictors from one- or several (multi-domain) parent GCMs. The numerous downscaling experiments indicate that the MLR- method is more accurate than SDSM and LARS-WG in predicting the recent past 20th-century (1971-2000) long-term monthly climate in the region. The MLR-model is, consequently, then employed to downscale 21st-century GCM- climate predictions under SRES-scenarios A1B, A2 and B1. However, since the hydrological watershed model requires daily-scale climate input data, a new stochastic daily climate generator is developed to rescale monthly observed or predicted climate series to daily series, while adhering to the statistical and geospatial distributional attributes of observed (past) daily climate series in the calibration phase. Employing this daily climate generator, 30 realizations of future daily climate series from downscaled monthly GCM-climate predictor sets are produced and used as input in the SWAT- distributed watershed model, to simulate future streamflow and other hydrological water budget components in the study region in a multi-realization manner. In addition to a general examination of the future changes of the hydrological regime in the KY-basin, potential future changes of the water budgets of three main reservoirs in the basin are analysed, as these are a major source of water supply in the study region. The results of the long-term 21st-century downscaled climate predictions provide evidence that, compared with the past 20th-reference period, the future climate in the study area will be more extreme, particularly, for SRES A1B. Thus, the temperatures will be higher and exhibit larger fluctuations. Although the future intensity of the rainfall is nearly constant, its spatial distribution across the region is partially changing. There is further evidence that the sequential rainfall occurrence will be decreased, so that short periods of high intensities will be followed by longer dry spells. This change in the sequential rainfall pattern will also lead to seasonal reductions of the streamflow and seasonal changes (decreases) of the water storage in the reservoirs. In any case, these predicted future climate changes with their hydrological impacts should encourage water planner and policy makers to develop adaptation strategies to properly handle the future water supply in this area, following the guidelines suggested in this study.

Modeling the interplay between land use, bioenergy production and climate change

Land use has become a force of global importance, considering that 34% of the Earth’s ice-free surface was covered by croplands or pastures in 2000. The expected increase in global human population together with eminent climate change and associated search for energy sources other than fossil fuels can, through land-use and land-cover changes (LUCC), increase the pressure on nature’s resources, further degrade ecosystem services, and disrupt other planetary systems of key importance to humanity. This thesis presents four modeling studies on the interplay between LUCC, increased production of biofuels and climate change in four selected world regions. In the first study case two new crop types (sugarcane and jatropha) are parameterized in the LPJ for managed Lands dynamic global vegetation model for calculation of their potential productivity. Country-wide spatial variation in the yields of sugarcane and jatropha incurs into substantially different land requirements to meet the biofuel production targets for 2015 in Brazil and India, depending on the location of plantations. Particularly the average land requirements for jatropha in India are considerably higher than previously estimated. These findings indicate that crop zoning is important to avoid excessive LUCC. In the second study case the LandSHIFT model of land-use and land-cover changes is combined with life cycle assessments to investigate the occurrence and extent of biofuel-driven indirect land-use changes (ILUC) in Brazil by 2020. The results show that Brazilian biofuels can indeed cause considerable ILUC, especially by pushing the rangeland frontier into the Amazonian forests. The carbon debt caused by such ILUC would result in no carbon savings (from using plant-based ethanol and biodiesel instead of fossil fuels) before 44 years for sugarcane ethanol and 246 years for soybean biodiesel. The intensification of livestock grazing could avoid such ILUC. We argue that such an intensification of livestock should be supported by the Brazilian biofuel sector, based on the sector’s own interest in minimizing carbon emissions. In the third study there is the development of a new method for crop allocation in LandSHIFT, as influenced by the occurrence and capacity of specific infrastructure units. The method is exemplarily applied in a first assessment of the potential availability of land for biogas production in Germany. The results indicate that Germany has enough land to fulfill virtually all (90 to 98%) its current biogas plant capacity with only cultivated feedstocks. Biogas plants located in South and Southwestern (North and Northeastern) Germany might face more (less) difficulties to fulfill their capacities with cultivated feedstocks, considering that feedstock transport distance to plants is a crucial issue for biogas production. In the fourth study an adapted version of LandSHIFT is used to assess the impacts of contrasting scenarios of climate change and conservation targets on land use in the Brazilian Amazon. Model results show that severe climate change in some regions by 2050 can shift the deforestation frontier to areas that would experience low levels of human intervention under mild climate change (such as the western Amazon forests or parts of the Cerrado savannas). Halting deforestation of the Amazon and of the Brazilian Cerrado would require either a reduction in the production of meat or an intensification of livestock grazing in the region. Such findings point out the need for an integrated/multicisciplinary plan for adaptation to climate change in the Amazon. The overall conclusions of this thesis are that (i) biofuels must be analyzed and planned carefully in order to effectively reduce carbon emissions; (ii) climate change can have considerable impacts on the location and extent of LUCC; and (iii) intensification of grazing livestock represents a promising venue for minimizing the impacts of future land-use and land-cover changes in Brazil.

The role of ligneous vegetation for livestock nutrition in the sub-Sahelian and Sudanian zones of West Africa: Potential effects of climate change

Climate change and variability in sub-Saharan West Africa is expected to have negative consequences for crop and livestock farming due to the strong dependence of these sectors on rainfall and natural resources, and the low adaptive capacity of crops farmers, agro-pastoralist and pastoralists in the region. The objective of this PhD research was to investigate the anticipated impacts of expected future climate change and variability on nutrition and grazing management of livestock in the prevailing extensive agro-pastoral and pastoral systems of the Sahelian and Sudanian zones of Burkina Faso. To achieve this, three studies were undertaken in selected village territories (100 km² each) in the southern Sahelian (Taffogo), northern Sudanian (Nobere, Safane) and southern Sudanian (Sokouraba) zone of the country during 2009 and 2010. The choice of two villages in the northern Sudanian zone was guided by the dichotomy between intense agricultural land use and high population density near Safane, and lower agricultural land use in the tampon zone between the village of Nobere and the National Park Kaboré Tambi of Pô. Using global positioning and geographical information systems tools, the spatio-temporal variation in the use of grazing areas by cattle, sheep and goats, and in their foraging behaviour in the four villages was assessed by monitoring three herds each per species during a one-year cycle (Chapter 2). Maximum itinerary lengths (km/d) were observed in the hot dry season (March-May); they were longer for sheep (18.8) and cattle (17.4) than for goats (10.5, p<0.05). Daily total grazing time spent on pasture ranged from 6 - 11 h with cattle staying longer on pasture than small ruminants (p<0.05). Feeding time accounted for 52% - 72% of daily time on pasture, irrespective of species. Herds spent longer time on pasture and walked farther distances in the southern Sahelian than the two Sudanian zones (p<0.01), while daily feeding time was longer in the southern Sudanian than in the other two zones (p>0.05). Proportional time spent resting decreased from the rainy (June - October) to the cool (November - February) and hot dry season (p<0.05), while in parallel the proportion of walking time increased. Feeding time of all species was to a significantly high proportion spent on wooded land (tree crown cover 5-10%, or shrub cover >10%) in the southern Sahelian zone, and on forest land (tree crown cover >10%) in the two Sudanian zones, irrespective of season. It is concluded that with the expansion of cropland in the whole region, remaining islands of wooded land, including also fields fallowed for three or more years with their considerable shrub cover, are particularly valuable pasturing areas for ruminant stock. Measures must be taken that counteract the shrinking of wooded land and forests across the whole region, including also active protection and (re)establishment of drought-tolerant fodder trees. Observation of the selection behaviour of the above herds of cattle and small ruminant as far as browse species were concerned, and interviews with 75 of Fulani livestock keepers on use of browse as feed by their ruminant stock and as remedies for animal disease treatment was undertaken (Chapter 3) in order to evaluate the consequence of climate change for the contribution of browse to livestock nutrition and animal health in the extensive grazing-based livestock systems. The results indicated that grazing cattle and small ruminants do make considerable use of browse species on pasture across the studied agro-ecological zones. Goats spent more time (p<0.01) feeding on browse species than sheep and cattle, which spent a low to moderate proportion of their feeding time on browsing in any of the study sites. As far as the agro-ecological zones were concerned, the contribution of browse species to livestock nutrition was more important in the southern Sahelian and northern Sudanian zone than the southern Sudanian zone, and this contribution is higher during the cold and hot dry season than during the rainy season. A total of 75 browse species were selected on pasture year around, whereby cattle strongly preferred Afzelia africana, Pterocarpus erinaceus and Piliostigma sp., while sheep and goats primarily fed on Balanites aegyptiaca, Ziziphus mauritiana and Acacia sp. Crude protein concentration (in DM) of pods or fruits of the most important browse species selected by goats, sheep and cattle ranged from 7% to 13% for pods, and from 10% to 18% for foliage. The concentration of digestible organic matter of preferred browse species mostly ranged from 40% to 60%, and the concentrations of total phenols, condensed tannins and acid detergent lignin were low. Linear regression analyses showed that browse preference on pasture is strongly related to its contents (% of DM) of CP, ADF, NDF and OM digestibility. Interviewed livestock keepers reported that browse species are increasingly use by their grazing animals, while for animal health care use of tree- and shrub-based remedies decreased over the last two decades. It is concluded that due to climate change with expected negative impact on the productivity of the herbaceous layer of communal pastures browse fodder will gain in importance for animal nutrition. Therefore re-establishment and dissemination of locally adapted browse species preferred by ruminants is needed to increase the nutritional situation of ruminant stock in the region and contribute to species diversity and soil fertility restoration in degraded pasture areas. In Chapter 4 a combination of household surveys and participatory research approaches was used in the four villages, and additionally in the village of Zogoré (southern Sahelian zone) and of Karangasso Vigué (northern Sudanian zone) to investigate pastoralists’ (n= 76) and agro-pastoralists’ (n= 83) perception of climate change, and their adaptation strategies in crop and livestock production at farm level. Across the three agro-ecological zones, the majority of the interviewees perceived an increase in maximum day temperatures and decrease of total annual rainfall over the last two decades. Perceptions of change in climate patterns were in line with meteorological data for increased temperatures while for total rainfall farmers’ views contrasted the rainfall records which showed a slight increase of precipitation. According to all interviewees climate change and variability have negative impacts on their crop and animal husbandry, and most of them already adopted some coping and adaptation strategies at farm level to secure their livelihoods and reduce negative impacts on their farming system. Although these strategies are valuable and can help crop and livestock farmers to cope with the recurrent droughts and climate variability, they are not effective against expected extreme climate events. Governmental and non-governmental organisations should develop effective policies and strategies at local, regional and national level to support farmers in their endeavours to cope with climate change phenomena; measures should be site-specific and take into account farmers’ experiences and strategies already in place.

Downscaling and Modeling the Effects of Climate Change on Hydrology and Water Resources in the Upper Blue Nile River Basin, Ethiopia

The Upper Blue Nile River Basin (UBNRB) located in the western part of Ethiopia, between 7° 45’ and 12° 45’N and 34° 05’ and 39° 45’E has a total area of 174962 km2 . More than 80% of the population in the basin is engaged in agricultural activities. Because of the particularly dry climate in the basin, likewise to most other regions of Ethiopia, the agricultural productivity depends to a very large extent on the occurrence of the seasonal rains. This situation makes agriculture highly vulnerable to the impact of potential climate hazards which are about to inflict Africa as a whole and Ethiopia in particular. To analyze these possible impacts of future climate change on the water resources in the UBNRB, in the first part of the thesis climate projection for precipitation, minimum and maximum temperatures in the basin, using downscaled predictors from three GCMs (ECHAM5, GFDL21 and CSIRO-MK3) under SRES scenarios A1B and A2 have been carried out. The two statistical downscaling models used are SDSM and LARS-WG, whereby SDSM is used to downscale ECHAM5-predictors alone and LARS-WG is applied in both mono-model mode with predictors from ECHAM5 and in multi-model mode with combined predictors from ECHAM5, GFDL21 and CSIRO-MK3. For the calibration/validation of the downscaled models, observed as well as NCEP climate data in the 1970 - 2000 reference period is used. The future projections are made for two time periods; 2046-2065 (2050s) and 2081-2100 (2090s). For the 2050s future time period the downscaled climate predictions indicate rise of 0.6°C to 2.7°C for the seasonal maximum temperatures Tmax, and of 0.5°C to 2.44°C for the minimum temperatures Tmin. Similarly, during the 2090s the seasonal Tmax increases by 0.9°C to 4.63°C and Tmin by 1°C to 4.6°C, whereby these increases are generally higher for the A2 than for the A1B scenario. For most sub-basins of the UBNRB, the predicted changes of Tmin are larger than those of Tmax. Meanwhile, for the precipitation, both downscaling tools predict large changes which, depending on the GCM employed, are such that the spring and summer seasons will be experiencing decreases between -36% to 1% and the autumn and winter seasons an increase of -8% to 126% for the two future time periods, regardless of the SRES scenario used. In the second part of the thesis the semi-distributed, physically based hydrologic model, SWAT (Soil Water Assessment Tool), is used to evaluate the impacts of the above-predicted future climate change on the hydrology and water resources of the UBNRB. Hereby the downscaled future predictors are used as input in the SWAT model to predict streamflow of the Upper Blue Nile as well as other relevant water resources parameter in the basin. Calibration and validation of the streamflow model is done again on 1970-2000 measured discharge at the outlet gage station Eldiem, whereby the most sensitive out the numerous “tuneable” calibration parameters in SWAT have been selected by means of a sophisticated sensitivity analysis. Consequently, a good calibration/validation model performance with a high NSE-coefficient of 0.89 is obtained. The results of the future simulations of streamflow in the basin, using both SDSM- and LARS-WG downscaled output in SWAT reveal a decline of -10% to -61% of the future Blue Nile streamflow, And, expectedly, these obviously adverse effects on the future UBNRB-water availibiliy are more exacerbated for the 2090’s than for the 2050’s, regardless of the SRES.

Climate change and hunger as the challenges in the global food system

In the last decades, there has been a growing tendency towards international trade and globalisation, particularly leading to a significant increase in flows of agricultural commodities worldwide. From a macroeconomic perspective, the commodity projections are more optimistic than the previous years and the long run tendency shows an increasing demand for feedstock. However, the strong shifts of shocks and fluctuations (in terms of prices and volumes) are a concern to global food security, with the number of hungry people rising to nearly one billion. Agriculture is a main user of natural resources, and it has a strong link with rural societies and the environment. Forecasted impacts from climate change, limited productive endorsements and emerging rivals on crop production, such bio-energy, aggravate the panorama on food scarcity. In this context, it is a great challenge on farming and food systems to reduce global hunger and produce in sustainable ways adequate supplies for food, feed, and non-food uses. The main objective of this work is to question the sustainability of food and agriculture systems. It is particularly interesting to know its role and if it will be able to respond to a growing population with increasing food demand in a world where pressure on land, water and other natural resources are already evident, and, moreover, climate change will also condition and impact the outcome. Furthermore, a deeper focus will be set on developing countries, which are expected to emerge and take a leading role in the international arena. This short paper is structured as follows: Section I, “Introduction”, describes the social situation regarding hunger, Section II, “Global Context”, attempts to summarise the current scenario in the international trading scheme and present the emerging rivals for primary resources, and in Section III, “Climate Change”, presents an overview of possible changes in the sector and future perspectives in the field. Finally, in Section IV, “Conclusion”, the main conclusions are presented.

A pilot investigation of the relationship between climate variability and milk compounds under the bootstrap technique

This study analyzes the linear relationship between climate variables and milk components in Iran by applying bootstrapping to include and assess the uncertainty. The climate parameters, Temperature Humidity Index (THI) and Equivalent Temperature Index (ETI) are computed from the NASA-Modern Era Retrospective-Analysis for Research and Applications (NASA-MERRA) reanalysis (2002–2010). Milk data for fat, protein (measured on fresh matter bases), and milk yield are taken from 936,227 milk records for the same period, using cows fed by natural pasture from April to September. Confidence intervals for the regression model are calculated using the bootstrap technique. This method is applied to the original times series, generating statistically equivalent surrogate samples. As a result, despite the short time data and the related uncertainties, an interesting behavior of the relationships between milk compound and the climate parameters is visible. During spring only, a weak dependency of milk yield and climate variations is obvious, while fat and protein concentrations show reasonable correlations. In summer, milk yield shows a similar level of relationship with ETI, but not with temperature and THI. We suggest this methodology for studies in the field of the impacts of climate change and agriculture, also environment and food with short-term data.

Climate change adaptation strategies of maize producers of the Central Rift Valley of Ethiopia

The impacts of climate change are considered to be strong in countries located in tropical Africa that depend on agriculture for their food, income and livelihood. Therefore, a better understanding of the local dimensions of adaptation strategies is essential to develop appropriate measures that will mitigate adverse consequences. Hence, this study was conducted to identify the most commonly used adaptation strategies that farm households practice among a set of options to withstand the effects of climate change and to identify factors that affect the choice of climate change adaptation strategies in the Central Rift Valley of Ethiopia. To address this objective, Multivariate Probit model was used. The results of the model indicated that the likelihood of households to adapt improved varieties of crops, adjust planting date, crop diversification and soil conservation practices were 58.73%, 57.72%, 35.61% and 41.15%, respectively. The Simulated Maximum Likelihood estimation of the Multivariate Probit model results suggested that there was positive and significant interdependence between household decisions to adapt crop diversification and using improved varieties of crops; and between adjusting planting date and using improved varieties of crops. The results also showed that there was a negative and significant relationship between household decisions to adapt crop diversification and soil conservation practices. The paper also recommended household, socioeconomic, institutional and plot characteristics that facilitate and impede the probability of choosing those adaptation strategies.

The Effect of Climate Variability on Main Components of Cow Milk in Iran

The main purpose of this study is to assess the relationship between six bioclimatic indices for cattle (temperature humidity (THI), environmental stress (ESI), equivalent temperature (ESI), heat load (HLI), modified heat load (HLInew) and respiratory rate predictor(RRP)) and fundamental milk components (fat, protein, and milk yield) considering uncertainty. The climate parameters used to calculate the climate indices were taken from the NASA-Modern Era Retrospective-Analysis for Research and Applications (NASA-MERRA) reanalysis from 2002 to 2010. Cow milk data were considered for the same period from April to September when cows use natural pasture, with possibility for cows to choose to stay in the barn or to graze on the pasture in the pasturing system. The study is based on a linear regression analysis using correlations as a summarizing diagnostic. Bootstrapping is used to represent uncertainty estimation through resampling in the confidence intervals. To find the relationships between climate indices (THI, ETI, HLI, HLInew, ESI and RRP) and main components of cow milk (fat, protein and yield), multiple liner regression is applied. The least absolute shrinkage selection operator (LASSO) and the Akaike information criterion (AIC) techniques are applied to select the best model for milk predictands with the smallest number of climate predictors. Cross validation is used to avoid over-fitting. Based on results of investigation the effect of heat stress indices on milk compounds separately, we suggest the use of ESI and RRP in the summer and ESI in the spring. THI and HLInew are suggested for fat content and HLInew also is suggested for protein content in the spring season. The best linear models are found in spring between milk yield as predictands and THI, ESI,HLI, ETI and RRP as predictors with p-value < 0.001 and R2 0.50, 0.49. In summer, milk yield with independent variables of THI, ETI and ESI show the highest relation (p-value < 0.001) with R2 (0.69). For fat and protein the results are only marginal. It is strongly suggested that new and significant indices are needed to control critical heat stress conditions that consider more predictors of the effect of climate variability on animal products, such as sunshine duration, quality of pasture, the number of days of stress (NDS), the color of skin with attention to large black spots, and categorical predictors such as breed, welfare facility, and management system. This methodology is suggested for studies investigating the impacts of climate variability/change on food quality/security, animal science and agriculture using short term data considering uncertainty or data collection is expensive, difficult, or data with gaps.

Ensuring community and agricultural resiliency to climate change: Ceremonial practices as emic adaptive strategies

This paper is an analysis of emic versus etic approaches to climate change resiliency, taking as a case study the traditional ceremony performed by farmers in eastern Flores, Indonesia to rid their fields of rats. This paper begins by providing a theoretical framework discussion on the dominant etic and emic academic research on monsoons and climate change impacts on agriculture. The rat ceremony performed in villages throughout East Flores is a local custom used to rid agricultural fields of pests—often rats—that come from the surrounding forests to feed on the agricultural crops when the rains become erratic. This paper argues that analyzing the rat ceremony through an emic lens allows for better future resiliency to monsoon shifts due to climate change. It is argued that the rat ceremony demonstrates a way in which community resiliency is strengthened by an adaptive approach that supports an already existing community ceremony that emphasizes two essential tenets: community solidarity and coexistence with nature. Both tenets directly promote community resiliency. An explicit emphasis on emic approaches to climate change challenges could help re-define how resiliency is understood and supported within vulnerable communities such as rural villages.

Climate change adaptation solutions for the green sectors of selected zones in the MENA region

In this paper, we propose climate adaptation solutions for the green sectors in three different zones of MENA: Egypt’s Delta (irrigated), Karak, in the highlands of Jordan (rainfed), and Lebanon’s Orontes basin (mixed: rainfed-irrigated). We analysed land use and crop intensification, and calculated the economic productivity of water – a critical scarce resource in MENA. By integrating the results with evidence from literature on the potential impacts of climate change and socio-economic factors, we could identify vulnerability levels of the three regions and propose adaptation measures relying of the concept of the “food-water-energy nexus.” While the vulnerability levels are found to be high in the Delta (Egypt) and Karak (Jordan), mainly due to water scarcity and poor adaptive capacity, the vulnerability level is moderate in the Orontes zone (Lebanon) due to a diversified agricultural sector and good market development, coupled with moderate water scarcity. Proposed adaptation solutions range from measures to improve technical efficiency, to measures that encourage economically efficient allocation by use of market forces. For both cases, the development of market opportunities is emphasized to make the proposed measures attractive to farmers.