TWINLATIN: Twinning European and Latin-American river basins for research enabling sustainable water resources management. Combined Report D3.1 Hydrological modelling report and D3.2 Evaluation report

Water use has almost tripled over the past 50 years and in some regions the water demand already exceeds supply (Vorosmarty et al., 2000). The world is facing a “global water crisis”; in many countries, current levels of water use are unsustainable, with systems vulnerable to collapse from even small changes in water availability. The need for a scientifically-based assessment of the potential impacts on water resources of future changes, as a basis for society to adapt to such changes, is strong for most parts of the world. Although the focus of such assessments has tended to be climate change, socio-economic changes can have as significant an impact on water availability across the four main use sectors i.e. domestic, agricultural, industrial (including energy) and environmental. Withdrawal and consumption of water is expected to continue to grow substantially over the next 20-50 years (Cosgrove & Rijsberman, 2002), and consequent changes in availability may drastically affect society and economies. One of the most needed improvements in Latin American river basin management is a higher level of detail in hydrological modelling and erosion risk assessment, as a basis for identification and analysis of mitigation actions, as well as for analysis of global change scenarios. Flow measurements are too costly to be realised at more than a few locations, which means that modelled data are required for the rest of the basin. Hence, TWINLATIN Work Package 3 “Hydrological modelling and extremes” was formulated to provide methods and tools to be used by other WPs, in particular WP6 on “Pollution pressure and impact analysis” and WP8 on “Change effects and vulnerability assessment”. With an emphasis on high and low flows and their impacts, WP3 was originally called “Hydrological modelling, flooding, erosion, water scarcity and water abstraction”. However, at the TWINLATIN kick-off meeting it was agreed that some of these issues resided more appropriately in WP6 and WP8, and so WP3 was renamed to focus on hydrological modelling and hydrological extremes. The specific objectives of WP3 as set out in the Description of Work are

The impact of water erosion and climate change on global cereal yields

Water erosion can degrade soils and reduce agricultural productivity. Global modelling studies are increasingly used to explore the potential impacts of environmental change, especially climate change, on crop yields. Despite its impact on crops and its direct link to the climate system, water erosion has not previously been considered in projections of the impacts of climate change on global crop yields. Similarly, global water erosion assessments have not considered how water erosion affects crops, and vice versa. This thesis identifies a method to estimate global water erosion patterns and evaluates it using a global database of erosion measurements. It then examines the global potential impacts of erosion on maize and wheat yields, and explores how these might be affected by climate change in the future. The Environmental Policy Integrated Climate (EPIC) crop model is used with global datasets on soil, topography, climate and field management to estimate erosion and its impacts on crop yields. Estimates using weather data for the years 1980–2010 suggest that water erosion reduced maize and wheat yields by 3% annually in around half of global arable land under current land management regimes. The estimated annual maize and wheat production losses due to water erosion accounted for less than 1% of the global production volume. However, water erosion in maize and wheat fields at low latitudes is likely to increase in the future due to the adverse effects of climate change on both crops. Uncertainties remain about estimates of water erosion that need to be addressed through better integration of models and observations. Nevertheless, the integrated biophysical modelling framework developed in this study can provide a link between robust estimates of water erosion, economics, and policy making that have so far been lacking in global agricultural assessments

Carbon Dynamics and Land-Use Choices: Building a Regional-Scale Multidisciplinary Model

Policy enabling tropical forests to approach their potential contribution to global-climate-change mitigation requires forecasts of land use and carbon storage on a large scale over long periods. In this paper, we present an integrated modeling methodology that addresses these needs. We model the dynamics of the human land-use system and of C pools contained in each ecosystem, as well as their interactions. The model is national scale, and is currently applied in a preliminary way to Costa Rica using data spanning a period of over fifty years. It combines an ecological process model, parameterized using field and other data, with an economic model, estimated using historical data to ensure a close link to actual behavior. These two models are linked so that ecological conditions affect land-use choices and vice versa. The integrated model predicts land use and its consequences for C storage for policy scenarios. These predictions can be used to create baselines, reward sequestration, and estimate the value in both environmental and economic terms of including C sequestration in tropical forests as part of the efforts to mitigate global climate change. The model can also be used to assess the benefits from costly activities to increase accuracy and thus reduce errors and their societal costs.carbon, sequestration, climate change, land use, modelling

Carbon Dynamics and Land-use Choices: Building a Regional-scale Multidisciplinary Model

Policy enabling tropical forests to approach their potential contribution to global-climate-change mitigation requires forecasts of land use and carbon storage on a large scale over long periods. In this paper, we present an integrated modeling methodology that addresses these needs. We model the dynamics of the human land-use system and of C pools contained in each ecosystem, as well as their interactions. The model is national scale, and is currently applied in a preliminary way to Costa Rica using data spanning a period of over fifty years. It combines an ecological process model, parameterized using field and other data, with an economic model, estimated using historical data to ensure a close link to actual behavior. These two models are linked so that ecological conditions affect land-use choices and vice versa. The integrated model predicts land use and its consequences for C storage for policy scenarios. These predictions can be used to create baselines, reward sequestration, and estimate the value in both environmental and economic terms of including C sequestration in tropical forests as part of the efforts to mitigate global climate change. The model can also be used to assess the benefits from costly activities to increase accuracy and thus reduce errors and their societal costs.carbon, sequestration, climate change, land use, modelling

Climate change alters fish community size-structure, requiring adaptive policy targets

Size‐based indicators are used worldwide in research that supports the management of commercially exploited wild fish populations, because of their responsiveness to fishing pressure. Observational and experimental data, however, have highlighted the deeply rooted links between fish size and environmental conditions that can drive additional, interannual changes in these indicators. Here, we have used biogeochemical and mechanistic niche modelling of commercially exploited demersal fish species to project time series to the end of the 21st century for one such indicator, the large fish indicator (LFI), under global CO2 emissions scenarios. Our modelling results, validated against survey data, suggest that the LFI's previously proposed policy target may be unachievable under future climate change. In turn, our results help to identify what may be achievable policy targets for demersal fish communities experiencing climate change. While fisheries modelling has grown as a science, climate change modelling is seldom used specifically to address policy aims. Studies such as this one can, however, enable a more sustainable exploitation of marine food resources under changes unmanageable by fisheries control. Indeed, such studies can be used to aid resilient policy target setting by taking into account climate‐driven effects on fish community size‐structure

Host Specificity in Variable Environments

Host specificity encompasses the range and diversity of host species that a parasite is capable of infecting and is considered a crucial measure of a parasite's potential to shift hosts and trigger disease emergence. Yet empirical studies rarely consider that regional observations only reflect a parasite's 'realized' host range under particular conditions: the true 'fundamental' range of host specificity is typically not approached. We provide an overview of challenges and directions in modelling host specificity under variable environmental conditions. Combining tractable modelling frameworks with multiple data sources that account for the strong interplay between a parasite's evolutionary history, transmission mode, and environmental filters that shape host-parasite interactions will improve efforts to quantify emerging disease risk in times of global change

System complexity and policy integration challenges: The Brazilian Energy- Water-Food Nexus

The Energy-Water-Food Nexus is one of the most complex sustainability challenges faced by the world. This is particularly true in Brazil, where insufficiently understood interactions within the Nexus are contributing to large-scale deforestation and land-use change, water and energy scarcity, and increased vulnerability to climate change. The reason is a combination of global environmental change and global economic change, putting unprecedented pressures on the Brazilian environment and ecosystems. In this paper, we identify and discuss the main Nexus challenges faced by Brazil across sectors (e.g. energy, agriculture, water) and scales (e.g. federal, state, municipal). We use four case studies to explore all nodes of the Nexus. For each, we analyse data from economic and biophysical modelling sources in combination with an overview of the legislative and policy landscape, in order to identify governance shortcomings in the context of growing challenges. We analyse the complex interdependence of developments at the global and local (Brazilian) levels, highlighting the impact of global environmental and economic change on Brazil and, conversely, that of developments in Brazil for other countries and the world. We conclude that there is a need to adjust the scientific approach to these challenges as an enabling condition for stronger science-policy bridges for sustainability policy-making. © 2019 The Author(s

An interdisciplinary modelling framework for selecting adaptation measures at the river basin scale in a global change scenario

Shaping global change adaptation strategy in water resource systems requires an interdisciplinary approach to deal with the multiple dimensions of the problem. The modelling framework presented integrates climate, economic, agronomic and hydrological scenarios to design a programme of adaptation measures at the river basin scale. Future demand scenarios; combined with a down-scaled climate scenario, provide the basis to estimate the demand and water resources in 2030. A least-cost river basin optimisation model is then applied to select adaptation measures ensuring that environmental and supply management goals are achieved. In the Orb river basin (France), the least-cost portfolio selected suggests mixing demand and supply side measures to adapt to global change. Trade-offs among the cost of the programme of measures, the deficit in agricultural water supply and the level of environmental flows are investigated. The challenges to implement such interdisciplinary approaches in the definition of adaptation strategies are finally discussed. (C) 2015 Elsevier Ltd. All rights reserved.The study has been partially supported by ONEMA, by the Scarce Project (Consolider-Ingenio 2010 CSD2009-00065) and IMPADAPT project (CGL2013-48424-C2-1-R) of the Spanish ministry MINECO (Ministerio de Economia y Competitividad) with European FEDER funds. Corentin Girard is supported by a grant from the University Lecturer Training Program (FPU12/03803) of the Ministry of Education, Culture and Sports of Spain. We also acknowledge the CERFACS for the climate scenarios provided from their SCRATCH 2010 dataset (March 2012 release - http://www.cerfacs.fr/similar to page/work/scratch/). We are very grateful to S. Chazot (BRLi), E. Vier and F. Aigoui (GINGERGROUP) and L. Rippert and its team from the SMVOL for their advice during the research and for the data provided. We thank as well the anonymous reviewers, and the Editor-in-Chief of Environmental Modelling and Software, Anthony Jakeman, for their support in the improvement of the manuscript and their encouraging comments.Girard, CDP.; Rinaudo, J.; Pulido-Velazquez, M.; Caballero, Y. (2015). An interdisciplinary modelling framework for selecting adaptation measures at the river basin scale in a global change scenario. Environmental Modelling and Software. 69:42-54. https://doi.org/10.1016/j.envsoft.2015.02.023S42546

Biophysical and Human Controls of Land Productivity under Global Change : Development and Demonstration of Parsimonious Modelling Techniques

Net primary production (NPP) serves as an indicator for plant-based resources such as food, timber and biofuel for human appropriation. It is defined by the annual production of plant matter and is mainly controlled by climate and human activities. Climate change in combination with human activities is altering NPP. As the controls of NPP are expected to further change in the future, it is vital to investigate alterations in NPP and their magnitudes. The impacts of climate change and human activities on NPP can be explored in integrated assessment (IA) frameworks, where sectoral models are coupled and interact rapidly. For such frameworks, parsimonious models are desired because they enable rapid estimates and facilitate easy model coupling for explorations of multiple global change scenarios (i.e. large volumes of data). This thesis aims to advance parsimonious modelling techniques for quantifying current and future NPP on land. This is accomplished by developing and testing rapid models that facilitate easy model coupling to explore the impacts of multiple global change scenarios on NPP. The model development is based on the meta-modelling concept, which can be applied to simplify the dynamic vegetation model LPJ-GUESS in a parsimonious model. For this, multiple climate change and [CO2] perturbations are applied to LPJ-GUESS to simulate NPP. The NPP data are then used to define biophysically motivated relationships between NPP and the driving climate variables along with [CO2]. The relationships are then combined in a synergistic function – the meta-model. Thereafter, the meta-models are assessed for their performance in estimating NPP by comparing them to LPJ-GUESS NPP simulations, to independent field observations and to NPP experiments under enriched [CO2] on biome level. The results provide confidence in the modelled NPP estimates for the most productive biomes, which are important for global quantifications of NPP. The meta-models capture NPP enhancement under enhanced [CO2] adequately in the majority of the studied biomes. Finally, the NPP meta-models are coupled with other sectoral models in two IA modelling-frameworks in order to explore the impacts of global change on ecosystem indicators. The first framework enables an IA of climate change impacts and vulnerabilities for a range of sectors on the European level. This thesis conducts a sensitivity analysis on the effects of climatic and socio-economic change drivers on model outputs related to key sectors. This provides better quantification and increased understanding of the complex relationships between input and output variables in IA modelling-frameworks. The second framework addresses the NPP supply-demand balance in the Sahel region by coupling two sectoral models in order to analyze the timings and geographies of NPP shortfalls in the 21st century Sahel under global change. The results show consistent regional NPP shortfalls in the Sahel for the majority of global change scenarios.Overall, the parsimonious modelling techniques developed in this thesis contribute with rapid NPP estimates on the biome and global scale. BME NPP estimates agree reasonably well with NPP observations in the majority of biomes (especially in the most productive biomes). This thesis demonstrates that NPP meta-models facilitate easy model coupling for exploring the impacts of global change on human-environmental systems in IA modelling-frameworks

Environmental Niche Modelling with Desktop GARP for Wild Origanum vulgare L . (Lamiaceae) in Armenia

Predicting species’ distributions has became one of the significant components of conservation biology in recent years. During the study, GARP (genetic algorithm) has been identified the key modelling technique for determining Origanum vulgare L. (Oregano, Lamiaceae) environmental niche in the Republic of Armenia. For over three consecutive years, from 2010-2013 it has been created relevant environmental layers through ESRI ArcGIS programs to be used with the plant actual distribution (occurrence records) as input data of GARP. In the result of the study, it has been produced the fundamental and realized niche and predictive habitat distribution of O. vulgare L. with Bitmap under the global climate change. Produced Bitmap illustrates that Oregano distributions would decrease mostly in the central regions due to environmental deterioration and climate change. This research could provide significant data for future conservation planning of wild Oregano in the Republic of Armenia