The importance of cooperation on transboundary waters is stated as a target in the United Nations 2030 Agenda for Sustainable Development Goals (SDG6: water). Cooperation on transboundary water management is critical, particularly because it concerns issues across multiple states, SDGs and targets regarding agriculture, energy, ecosystems, climate adaptation, health, and peace and security. The percentage of transboundary basin area within a country that has an “operational arrangement” for water cooperation is used as the main indicator of such cooperation in the SDGs for “equitable and reasonable use“ of water resources (SDG 6.5.2). However, no clear criteria and explanation are available for what exactly constitutes an “equitable and reasonable use” in any such “operational arrangements.” Furthermore, it is understandable that any such arrangements may be shaped by differences in historical, legal, and political contexts and hence may be inherently unjust. Here, we highlight the limitations of SDG indicators, particularly SDG 6.5.2, to monitor equity of resource sharing in transboundary river systems. Using Walzer’s theory of morality of the state and cosmopolitanism as a framework, we examine the Nile basin as a case study to demonstrate the shortcomings of current SDG criteria and indicators. Our article contributes ideas of “operationalizing” theoretical justice toward a more equitable water management in transboundary rivers.@en

A web-based framework (AgriSuit) that integrates various global data from different sources for multi-criteria based agricultural land suitability assessment based on the Google Earth Engine (GEE) platform is developed and presented. The platform enables online data gathering, training and classifying of land cover classes based on remote sensing and GIS techniques, as well as computation of suitability of land-use classes for agricultural activities. A demonstration of the framework on the Upper Blue Nile basin in Ethiopia is presented.@en

A web-based framework (AgriSuit) that integrates various global data from different sources for multi-criteria based agricultural land suitability assessment based on the Google Earth Engine (GEE) platform is developed and presented. The platform enables online data gathering, training and classifying of land cover classes based on remote sensing and GIS techniques, as well as computation of suitability of land-use classes for agricultural activities. A demonstration of the framework on the Upper Blue Nile basin in Ethiopia is presented.@en

A web-based framework (AgriSuit) that integrates various global data from different sources for multi-criteria based agricultural land suitability assessment based on the Google Earth Engine (GEE) platform is developed and presented. The platform enables online data gathering, training and classifying of land cover classes based on remote sensing and GIS techniques, as well as computation of suitability of land-use classes for agricultural activities. A demonstration of the framework on the Upper Blue Nile basin in Ethiopia is presented.@en

The Upper Blue Nile is home to a large human and livestock population that live in diverse biophysical and socio-economic environment. The basin is increasingly experiencing multi-dimensional pressures including population growth, climate change and variability, deforestation, land/soil degradation, as well as increasing upstream-downstream tension on water use rights. Understanding the dynamic interactions of land use and water resources in the basin comes at the forefront of any effort to improving the livelihood and sustainability in the basin. As part of a study to develop a decision support system for an integrated natural resources management for the Upper Blue Nile basin, methods and techniques are developed to identify land use suitably based on various biophysical and socio-economic factors, and water resources availability in the basin. Possible biophysical and socio-economic land use change drivers on a mesoscale catchment, Jedeb, were identified using historical remote sensing data as well as primary data sources such as field observations, questionnaires and interviewing key stakeholder informants. Then, major land use change drivers were ranked using regression analysis (PCA). A hydrological model was setup using the Soil and Water Assessment Tool (SWAT) for the Jedeb catchment. Based on the identified high impact land use change drivers and additional factors such as agro-ecological zones and water resources availability (output from the hydrological model), a land use suitability analysis for the catchment was developed using the SITE (SImulation of Terrestrial Environments) generic land use change modeling framework. The land use and hydrological models exchange yearly simulation results to determine land use suitability analysis and impacts of land use change on components of the basin's hydrology, and vice-versa. Land use scenario was analyzed by assuming a 20% increase in population in the catchment. Preliminary results indicate a clear shift mainly from grassland land use type to cultivation land use type. It is concluded that the techniques and methodologies used in this study especially for integrating the two models can be used for a more realistic and thorough analysis of land use suitability and water resources dynamics and assessment study. Outputs of this study are used as inputs to develop a spatial decision support system for an integrated assessment and management of land use and water resources in the basin.@en

The Upper Blue Nile is home to a large human and livestock population that live in diverse biophysical and socio-economic environment. The basin is increasingly experiencing multi-dimensional pressures including population growth, climate change and variability, deforestation, land/soil degradation, as well as increasing upstream-downstream tension on water use rights. Understanding the dynamic interactions of land use and water resources in the basin comes at the forefront of any effort to improving the livelihood and sustainability in the basin. As part of a study to develop a decision support system for an integrated natural resources management for the Upper Blue Nile basin, methods and techniques are developed to identify land use suitably based on various biophysical and socio-economic factors, and water resources availability in the basin. Possible biophysical and socio-economic land use change drivers on a mesoscale catchment, Jedeb, were identified using historical remote sensing data as well as primary data sources such as field observations, questionnaires and interviewing key stakeholder informants. Then, major land use change drivers were ranked using regression analysis (PCA). A hydrological model was setup using the Soil and Water Assessment Tool (SWAT) for the Jedeb catchment. Based on the identified high impact land use change drivers and additional factors such as agro-ecological zones and water resources availability (output from the hydrological model), a land use suitability analysis for the catchment was developed using the SITE (SImulation of Terrestrial Environments) generic land use change modeling framework. The land use and hydrological models exchange yearly simulation results to determine land use suitability analysis and impacts of land use change on components of the basin's hydrology, and vice-versa. Land use scenario was analyzed by assuming a 20% increase in population in the catchment. Preliminary results indicate a clear shift mainly from grassland land use type to cultivation land use type. It is concluded that the techniques and methodologies used in this study especially for integrating the two models can be used for a more realistic and thorough analysis of land use suitability and water resources dynamics and assessment study. Outputs of this study are used as inputs to develop a spatial decision support system for an integrated assessment and management of land use and water resources in the basin.@en

The Upper Blue Nile is home to a large human and livestock population that live in diverse biophysical and socio-economic environment. The basin is increasingly experiencing multi-dimensional pressures including population growth, climate change and variability, deforestation, land/soil degradation, as well as increasing upstream-downstream tension on water use rights. Understanding the dynamic interactions of land use and water resources in the basin comes at the forefront of any effort to improving the livelihood and sustainability in the basin. As part of a study to develop a decision support system for an integrated natural resources management for the Upper Blue Nile basin, methods and techniques are developed to identify land use suitably based on various biophysical and socio-economic factors, and water resources availability in the basin. Possible biophysical and socio-economic land use change drivers on a mesoscale catchment, Jedeb, were identified using historical remote sensing data as well as primary data sources such as field observations, questionnaires and interviewing key stakeholder informants. Then, major land use change drivers were ranked using regression analysis (PCA). A hydrological model was setup using the Soil and Water Assessment Tool (SWAT) for the Jedeb catchment. Based on the identified high impact land use change drivers and additional factors such as agro-ecological zones and water resources availability (output from the hydrological model), a land use suitability analysis for the catchment was developed using the SITE (SImulation of Terrestrial Environments) generic land use change modeling framework. The land use and hydrological models exchange yearly simulation results to determine land use suitability analysis and impacts of land use change on components of the basin's hydrology, and vice-versa. Land use scenario was analyzed by assuming a 20% increase in population in the catchment. Preliminary results indicate a clear shift mainly from grassland land use type to cultivation land use type. It is concluded that the techniques and methodologies used in this study especially for integrating the two models can be used for a more realistic and thorough analysis of land use suitability and water resources dynamics and assessment study. Outputs of this study are used as inputs to develop a spatial decision support system for an integrated assessment and management of land use and water resources in the basin.@en

The Upper Blue Nile is home to a large human and livestock population that live in diverse biophysical and socio-economic environment. The basin is increasingly experiencing multi-dimensional pressures including population growth, climate change and variability, deforestation, land/soil degradation, as well as increasing upstream-downstream tension on water use rights. Understanding the dynamic interactions of land use and water resources in the basin comes at the forefront of any effort to improving the livelihood and sustainability in the basin. As part of a study to develop a decision support system for an integrated natural resources management for the Upper Blue Nile basin, methods and techniques are developed to identify land use suitably based on various biophysical and socio-economic factors, and water resources availability in the basin. Possible biophysical and socio-economic land use change drivers on a mesoscale catchment, Jedeb, were identified using historical remote sensing data as well as primary data sources such as field observations, questionnaires and interviewing key stakeholder informants. Then, major land use change drivers were ranked using regression analysis (PCA). A hydrological model was setup using the Soil and Water Assessment Tool (SWAT) for the Jedeb catchment. Based on the identified high impact land use change drivers and additional factors such as agro-ecological zones and water resources availability (output from the hydrological model), a land use suitability analysis for the catchment was developed using the SITE (SImulation of Terrestrial Environments) generic land use change modeling framework. The land use and hydrological models exchange yearly simulation results to determine land use suitability analysis and impacts of land use change on components of the basin's hydrology, and vice-versa. Land use scenario was analyzed by assuming a 20% increase in population in the catchment. Preliminary results indicate a clear shift mainly from grassland land use type to cultivation land use type. It is concluded that the techniques and methodologies used in this study especially for integrating the two models can be used for a more realistic and thorough analysis of land use suitability and water resources dynamics and assessment study. Outputs of this study are used as inputs to develop a spatial decision support system for an integrated assessment and management of land use and water resources in the basin.@en

The Upper Blue Nile is home to a large human and livestock population that live in diverse biophysical and socio-economic environment. The basin is increasingly experiencing multi-dimensional pressures including population growth, climate change and variability, deforestation, land/soil degradation, as well as increasing upstream-downstream tension on water use rights. Understanding the dynamic interactions of land use and water resources in the basin comes at the forefront of any effort to improving the livelihood and sustainability in the basin. As part of a study to develop a decision support system for an integrated natural resources management for the Upper Blue Nile basin, methods and techniques are developed to identify land use suitably based on various biophysical and socio-economic factors, and water resources availability in the basin. Possible biophysical and socio-economic land use change drivers on a mesoscale catchment, Jedeb, were identified using historical remote sensing data as well as primary data sources such as field observations, questionnaires and interviewing key stakeholder informants. Then, major land use change drivers were ranked using regression analysis (PCA). A hydrological model was setup using the Soil and Water Assessment Tool (SWAT) for the Jedeb catchment. Based on the identified high impact land use change drivers and additional factors such as agro-ecological zones and water resources availability (output from the hydrological model), a land use suitability analysis for the catchment was developed using the SITE (SImulation of Terrestrial Environments) generic land use change modeling framework. The land use and hydrological models exchange yearly simulation results to determine land use suitability analysis and impacts of land use change on components of the basin's hydrology, and vice-versa. Land use scenario was analyzed by assuming a 20% increase in population in the catchment. Preliminary results indicate a clear shift mainly from grassland land use type to cultivation land use type. It is concluded that the techniques and methodologies used in this study especially for integrating the two models can be used for a more realistic and thorough analysis of land use suitability and water resources dynamics and assessment study. Outputs of this study are used as inputs to develop a spatial decision support system for an integrated assessment and management of land use and water resources in the basin.@en

Land-use and land-cover changes are driving unprecedented changes in ecosystems and environmental processes at different scales. This study was aimed at identifying the potential land-use drivers in the Jedeb catchment of the Abbay basin by combining statistical analysis, field investigation and remote sensing. To do so, a land-use change model was calibrated and evaluated using the SITE (SImulation of Terrestrial Environment) modelling framework. SITE is cellular automata based multi-criteria decision analysis framework for simulating land-use conversion based on socio-economic and environmental factors. Past land-use trajectories (1986–2009) were evaluated using a reference Landsat-derived map (agreement of 84%). Results show that major land-use change drivers in the study area were population, slope, livestock and distances from various infrastructures (roads, markets and water). It was also found that farmers seem to increasingly prefer plantations of trees such as Eucalyptus by replacing croplands perhaps mainly due to declining crop yield, soil fertility and climate variability. Potential future trajectory of land-use change was also predicted under a business-as-usual scenario (2009–2025). Results show that agricultural land will continue to expand from 69.5% in 2009 to 77.5% in 2025 in the catchment albeit at a declining rate when compared with the period from 1986 to 2009. Plantation forest will also increase at a much higher rate, mainly at the expense of natural vegetation, agricultural land and grasslands. This study provides critical information to land-use planners and policy makers for a more effective and proactive management in this highland catchment.@en

Representation of land-use and hydrologic interactions in respective models has traditionally been problematic. The use of static land-use in most hydrologic models or that of the use of simple hydrologic proxies in land-use change models call for more integrated approaches. The objective of this study is to assess whether dynamic feedback between land-use change and hydrology can (1) improve model performances, and/or (2) produce a more realistic quantification of ecosystem services. To test this, we coupled a land-use change model and a hydrologic mode. First, the land-use change and the hydrologic models were separately developed and calibrated. Then, the two models were dynamically coupled to exchange data at yearly time-steps. The approach is applied to a catchment in South Africa. Performance of coupled models when compared to the uncoupled models were marginal, but the coupled models excelled at the quantification of catchment ecosystem services more robustly.@en

In this paper, we present the LandscapeIMAGES modeling framework for multi-scale spatially explicit analysis of tradeoffs and synergies among ecosystem services provisioning across agricultural landscapes. The framework generates large sets of spatially explicit land-use and management scenarios to inform discussions among stakeholders involved in landscape planning processes. The generated plans are evaluated and optimized for multiple indicators of ecosystem services provisioning. The framework has been developed with an object-oriented programming approach to allow rapid implementation of new indicators and application to new case study landscapes. The modeling system includes (i) a generic framework for Pareto-based multi-objective optimization to generate a set of land-use and management plans, (ii) an easily expandable collection of modules to quantify indicators of ecosystem services provisioning, which can be used as objectives or constraints in optimization, and (iii) a graphical user interface that allows parameterization of the model and inspection of the original and generated land-use and management plans. This allows visualization of trade-offs and synergies among ecosystem services as a consequence of land-use and management planning choices. LandscapeIMAGES is currently used in projects aiming to improve the provision of multiple ecosystem services within landscapes in Asia, Africa, Latin America and Europe.@en

The Soil and Water Assessment Tool (SWAT) has been used widely for large scale applications, reaching entire continents. Within the EU funded EnviroGrids project, a detailed application of SWAT on the Black Sea Basin is envisaged using high resolution data. In order to support the computation, the model is run on a computer grid. The use of the SWAT allowed for such computations with little adaptations to the source. A 3-step procedure is needed. In the first step, a program is run in order to split the model into several sub-models. Afterwards, the sub-models are run in parallel. In a last step, the outputs of the sub-basins are collected at a central computer and the routing is performed. High computations are also needed when simulations have to be repeated, such as for sensitivity, calibration and uncertainty analysis. In these cases, the simulations are repeated for different parameter sets. In this paper, we discuss the gridification of the algorithm "LH-OAT" that performs sensitivity analysis and has been linked to the SWAT model. The results show a clear improvement in calculation time. Nevertheless, it is concluded that the parallel computing of a distributed model is mainly beneficial for large scale applications with high resolution, while running the sensitivity analysis algorithm has more general and obvious benefit. In a next step, the gridification will be optimised depending on the application and the overheads that are due to submission and receiving of files, as well as potential waiting times for executions on the grid.@en

The increasing interest in larger spatial and temporal scale models and high resolution input data processing comes at a price of higher computational demand. This price is evidently even higher when common modeling routines such as calibration and uncertainty analysis are involved. Likewise, methods and techniques for reducing computation time in large scale socio-environmental modeling software is growing. Recent advancements in distributed computing such as Grid infrastructure have provided further opportunity to this effort. In the interest of gaining computational efficiency, we developed generic tools and techniques for enabling the Soil and Water Assessment Tool (SWAT) model application to run on the EGEE (Enabling Grids for E-science projects in Europe) Grid. Various program components/scripts were written to split a large scale hydrological model of the Soil and Water Assessment Tool (SWAT), to submit the split models to the Grid, and to collect and merge results into single output format. A three-step procedure was applied to take advantage of the Grid. Firstly, a python script was run in order to split the SWAT model into several sub-models. Then, individual sub-models were submitted in parallel for execution on the Grid. Finally, the outputs of the sub-basins were collected and the reach routing process was performed with another script executing a modified SWAT program. We conducted experimental simulations with multiple temporal and spatial scale hydrological models on the Grid infrastructure. Results showed that, in spite of computing overheads, parallel computation of socio-environmental models on the Grid is beneficial for model applications especially with large spatial and temporal scales. In the end, we conclude by recommending methods for further reducing computational overheads while running large scale model applications on the Grid.@en

The increasing interest in larger spatial and temporal scale models and high resolution input data processing comes at a price of higher computational demand. This price is evidently even higher when common modeling routines such as calibration and uncertainty analysis are involved. Likewise, methods and techniques for reducing computation time in large scale socio-environmental modeling software is growing. Recent advancements in distributed computing such as Grid infrastructure have provided further opportunity to this effort. In the interest of gaining computational efficiency, we developed generic tools and techniques for enabling the Soil and Water Assessment Tool (SWAT) model application to run on the EGEE (Enabling Grids for E-science projects in Europe) Grid. Various program components/scripts were written to split a large scale hydrological model of the Soil and Water Assessment Tool (SWAT), to submit the split models to the Grid, and to collect and merge results into single output format. A three-step procedure was applied to take advantage of the Grid. Firstly, a python script was run in order to split the SWAT model into several sub-models. Then, individual sub-models were submitted in parallel for execution on the Grid. Finally, the outputs of the sub-basins were collected and the reach routing process was performed with another script executing a modified SWAT program. We conducted experimental simulations with multiple temporal and spatial scale hydrological models on the Grid infrastructure. Results showed that, in spite of computing overheads, parallel computation of socio-environmental models on the Grid is beneficial for model applications especially with large spatial and temporal scales. In the end, we conclude by recommending methods for further reducing computational overheads while running large scale model applications on the Grid.@en

Policy makers have to select effective planning strategies regarding ecosystem services management using the best information that science and technology can provide them. It has been demonstrated that spatial indicators have the power of bringing together necessary data to inform policy makers. Furthermore, spatial indicators provide a starting point for decision-making. The ultimate objective of this study is to develop a decision support tool that can be used by policy makers to assess the impact of their integrated natural resources management (INRM) strategies on selected ecosystem services. This study proposes a spatial planning tool to present spatial indicators to track changes in ecosystem services provision by considering the mutual interaction between hydrological and land-use changes. The results of modelling scenarios from the coupling of a hydrological model (SW IM) and a land-use model (SITE) have been used to derive spatial indicators. These spatial indicators quantify dynamic changes of landscape patterns related to ecosystem services provision. The approach used has been applied to a case study dealing with INRM in the Drakensberg area, South Africa. The spatial indicators were selected specifically to show the consequences of action or inaction by humans for human well-being and ecosystems by measuring the efficacy of spatial management measures we take on the spatial configuration of the landscape. In the future, a web-based indicator atlas will be implemented, based on the same open source technology. The spatial planning tool displays spatial indicators of the changes in ecosystem services provision over time as a function of land-use and hydrological dynamics, represented in GIS layers produced by the models. The proposed tool is valuable in a decision making process, because it provides a better way of communicating complex model results to the public and stakeholders, informing them how socio-economic development and planning measures will affect the ecosystem services in their region.@en

Justice in the allocation and distribution of water is one of the most recent topics in the water resources management literature. This topic, i.e., justice/equity/fairness, is especially noteworthy in integrated water resources management where competing needs, sectors, and societal segments are involved in the utilization of water. Although the concept of justice, such as procedural justice, in general and in water management in particular is not as new, the concept of distributive justice and tools and technics for the allocation and distribution of water resources is very recent. As a result, particularly tools and techniques for the operationalization of such concepts are still lacking. In this study, we operationalized theoretical justice theories in terms of moral principles into functions and parameters for use with traditional water resources optimization models and frameworks. These moral principles include Utilitarianism (which evaluates measures according to their effect on welfare), Sufficientarianism (which makes sure that each individual gets a sufficient threshold), Prioritarianism (which guarantees extra weight to worse-off individuals), and envy-freeness (which requires that each individual prefers his share to the share of others). The result of the study as applied in the case study of the Susquehanna basin, USA, displays undertanding and outlooks of various perspectives of fairness on integrated water resources management among competing stakeholders and needs. Such perspectives are presented together with traditional resource efficiency and/or conservation oriented optimization techniques and methods to highlight synergy and trade-offs in integrated water resources management. We think that the methods and approaches presented here will advance the scientific discussion on the operationalization of justice/equity/fairness in real-world modeling and management of integrated water resources.@en

Land and water are two of the most important and interacting natural resources that are critical for human survival and development. Growing population and global economic expansion are accelerating the demand for land and water for uses such as agriculture, urbanization, irrigation, hydropower, and industrialization. The land surface changes dynamically due to these demands and other socio-economic drivers. Biophysical factors such as topographic suitability, climate change, and rainfall variability further influence land use changes and land-use change decisions. Water resources are likewise experiencing pressure from overuse, pollution, and changes in hydrologic processes as a result of both socio-economic and biophysical factors. @en

Although our knowledge of climate change impacts on energy systems has increased substantially over the past few decades, there remains a lack of comprehensive overview of impacts across spatial scales. Here, we analyse results of 220 studies projecting climate impacts on energy systems globally and at the regional scale. Globally, a potential increase in cooling demand and decrease in heating demand can be anticipated, in contrast to slight decreases in hydropower and thermal energy capacity. Impacts at the regional scale are more mixed and relatively uncertain across regions, but strongest impacts are reported for South Asia and Latin America. Our assessment shows that climate impacts on energy systems at regional and global scales are uncertain due partly to the wide range of methods and non-harmonized datasets used. For a comprehensive assessment of climate impacts on energy, we propose a consistent multi-model assessment framework to support regional-to-global-scale energy planning.@en

Although our knowledge of climate change impacts on energy systems has increased substantially over the past few decades, there remains a lack of comprehensive overview of impacts across spatial scales. Here, we analyse results of 220 studies projecting climate impacts on energy systems globally and at the regional scale. Globally, a potential increase in cooling demand and decrease in heating demand can be anticipated, in contrast to slight decreases in hydropower and thermal energy capacity. Impacts at the regional scale are more mixed and relatively uncertain across regions, but strongest impacts are reported for South Asia and Latin America. Our assessment shows that climate impacts on energy systems at regional and global scales are uncertain due partly to the wide range of methods and non-harmonized datasets used. For a comprehensive assessment of climate impacts on energy, we propose a consistent multi-model assessment framework to support regional-to-global-scale energy planning.@en