Resource Management Scenarios Research Articles

A cost and demand sensitive adjustment algorithm for service function chain in data center network

The introduction of Network Function Virtualization (NFV) and Software-Defined Network (SDN) architectures has significantly reduced the Operational Expenditure (OPEX) and Capital Expenditure (CAPEX) of network system. However, NFV orchestration management also brings about challenges. After the initial deployment of VNFs, due to the volatility of network requests, the original deployment may not be able to meet user resource demands. The key issue is how to readjust resources dynamically to accommodate more network requests without violating Quality of Service (QoS) for users. Several existing techniques can be used to achieve this goal, such as horizontal scaling, vertical scaling, and virtual network function (VNF) migration. However, these techniques inevitably incur some overhead, such as the cost of instantiating VNF and link rerouting. Additionally, resource adjustment may also result in unbalanced distribution of network resources. In this paper, an Intelligent Service Function Chain Dynamic Adjustment Algorithm (ISFCDAA) is proposed to address the above challenges. Firstly, an Integer Linear Programming (ILP) model is established with the objective of minimizing the long-term adjustment cost and reducing the imbalance of resource distribution. Then we transform the optimization process into a Markov Decision Process (MDP). Secondly, to solve the problems that the state and action space is too large and the state transition probability is uncertain in MDP, a SFC dynamic adjustment algorithm based on deep reinforcement learning is proposed. This algorithm can obtain an approximate optimal adjustment strategy for ILP model. The simulation results show that ISFCDAA can reduce the adjustment overhead and maintain a balanced distribution of network resources while ensuring the QoS. Compared with the existing algorithms, the average standard deviation of resource distribution of ISFCDAA is reduced by up to 9.90%, the average acceptance rate of ISFCDAA is improved by up to 39.57%, and the average long-term profit is improved by up to 42.92%. The incorporation of cost and demand-sensitive considerations into ISFCDAA enhances its responsiveness to fluctuating network demands, solidifying its effectiveness in dynamic resource management scenarios.

The Application of a Smart Nexus for Agriculture in Korea for Assessing the Holistic Impacts of Climate Change

Sustainable development involves maximizing the benefits of development while minimizing its consequent effects on the environment. This study uses a water–energy–food nexus framework, the Smart Nexus for Agriculture in Korea (SNAK), to assess the impact of climate change on sustainable resource management in agriculture. The nexus database applied in this study comprises three individual databases related to resources, interlinkages, and resource management scenarios, which include all variables and scenarios of the framework. Different resource management scenarios were evaluated via investigating the interlinkages between resources and quantifying resource consumption and sustainability. The variable selection and application module uses the interlinkage database to quantitatively model how the production and supply of one resource affects the consumption of other resources. The scenario analysis module involves the identification and application of resource management scenarios based on policies for individual resources and climate change. The sustainability evaluation module links the previous two modules to quantify food production, the consumption of food and energy resources, carbon (CO2) emissions, and land use in each scenario. Finally, resource security and economic benefits were considered when estimating the sustainability index of each scenario. The SNAK platform is anticipated to possess the ability to analyze environmental, social, and economic systems grounded in water, energy, and food. It is believed that the platform can optimize the timing and allocation of agricultural resources, leading to the derivation of optimal management scenarios. Furthermore, the platform will utilize water–energy–food linkage assessments to formulate scenario-based policies addressing food demand, water resource utilization, and energy consumption.

Multi-Station Hydrological Modelling to Assess Groundwater Recharge of a Vast Semi-Arid Basin Considering the Problem of Lack of Data: A Case Study in Seybouse Basin, Algeria

Water resource management scenarios have become more crucial for arid to semi-arid regions. Their application prerequisites rigorous hydrological modelling approaches since data are usually exposed to uncertainties and inaccuracies. In this work, Soil Water Assessment Tool (SWAT), an open source semi-distributed, continuous-time, process-based physical hydrological model is used to model hydrological processes and eventually calculate groundwater recharge estimations in Seybouse basin, Northeast Algeria. The model uses estimated rainfall to calibrate the model with observed discharge from hydrometric stations. Model calibration and validation are performed over four hydrometric stations located in the basin. Uncertainty analysis and sensitivity analysis supported the calibration period. SUFI-2 algorithm is used for uncertainty estimations along with a global sensitivity analysis prior to calibration simulations. Simulated flood hydrographs showed generally good accuracy with few misfits on the peaks. The model obtained satisfactory and consistent calibration and validation results for which the Nash score varied from 0.5 to 0.7 for calibration and from −0.1 to 0.6 for validation and R2 from 0.6 to 0.7 for calibration and 0.03 to 0.8 for validation. Moreover, estimated water budget values show strong similarities with the observed values found in the literature. The present work shows that the rigorously calibrated and validated SWAT model can simulate hydrological processes as well as major high and low flows using estimated rainfall data.

Comparison of three group decision-making frameworks for evaluating resilience time series of water resources systems under uncertainty

This study compared three uncertainty-based decision-making frameworks (considering/not considering the hierarchical structure of stakeholders) using resilience-based indices for evaluating different water resources management (WRM) scenarios under the impacts of climate change. The first step involved identifying significant stakeholders in the study area and establishing their relative weights. In the next step, stakeholders were asked to evaluate the management scenarios in the three different decision-making frameworks based on their decision criteria (nine resilience-based indices, implementation cost, and employment). Different types of weights (explicit and interval) were assigned to each stakeholder and their decision criteria, to account for the uncertainty associated with estimating their respective weights. This methodology was applied to the case of the Zarrinehrud River basin in northwest Iran. The best management scenario identified (MSC1346) was able increase lake elevation by 2.6 m (from 1271.3 m to 1273.9 m), improve the resilience of the system by 25 %, and enhance provisioning ecosystem services such as water and food supply and regulating services such as air quality. Comparing the results of the three decision-making frameworks revealed that the two which considered the hierarchical structure of stakeholders were more effective in determining the best scenario. The best scenario selected in the framework that ignored the hierarchical structure of stakeholders (MSC13567) had USD 202 million higher overall implementation and construction costs and gave a negligible difference in resilience value (0.04 difference) compared with scenario MSC1346.

Water resources management scenarios and transboundary hydro-political concerns in Iran’s eastern border areas

Motives: Since the main sources of some rivers are located in neighbouring countries, hydrological issues in the eastern part of Iran are critical. The water dispute between Iran and the neighbouring Afghanistan is related to environmental issues and human health.Aim: The aim of this study was to demonstrate how transboundary water conflicts increase human vulnerability through economic issues such as reduced productivity in the agricultural sector.Results: The study’s originality lies in the application of the positive mathematical programming approach to the agricultural sector, specifically in evaluating the impact of water pricing policies on crop selection and irrigation water use. A quadratic cost function was calibrated to develop three scenarios of water resources consumption (30%, 40%, and 70% reduction for farmers in group 1, and 10%, 25%, and 75% reduction for farmers in group 2) and price increase (70%, 80%, and 100% increase). The calibration of the quadratic cost function revealed an increase in irrigation efficiency (water resources consumption) as well as an increase in the region’s irrigated area.

Simulation-Based Education in Acute and Chronic Pain Training.

The use of simulation-based education (SBE) in medical training has expanded greatly and has grown to include high fidelity and task simulation along with hybrid models using patient actors to enhance education and training of critical events as well as technical skills. In the field of anesthesiology, SBE has been particularly useful for crisis resource management and rare critical scenarios and new research into the use of SBE using task simulation for procedural skill development has been done highlighting the benefits to subspecialty procedural training. Medical simulation has become a common practice in medical training and research. SBE has demonstrated positive outcomes in improving technical skills, knowledge, comfort, and clinical performance. The widespread implementation of SBE in regional anesthesia and chronic pain training varies, with cost and availability being factors. Nonetheless, SBE has shown great potential in enhancing education and preparing physicians in subspecialties of anesthesia.

A resilience-based framework for evaluating the carrying capacity of water and environmental resources under the climate change

This paper proposes a new framework for evaluating water and environmental resources carrying capacity (WERCC) based on the concept of resilience under uncertainty. First, several quantitative and qualitative criteria based on the seven principles of resilience and the Pressure-Support-State (PSS) framework are defined to incorporate the positive and negative impacts of human interventions and natural factors on water resources and the environment. The resilience principles include redundancy and diversity, managing connectivity, managing slow variables and their feedbacks, fostering complex adaptive system (CAS) thinking, encouraging learning, broadening participation, and promoting polycentric governance. After evaluating the values of the criteria and sub-criteria using a two-point evidential reasoning (TPER) approach and considering the existing uncertainties, the monthly time series of WERCC with uncertainty bands are calculated. The proposed methodology is then used to evaluate the WERCC in the Zarrinehrud river basin in Iran for a given historical period (1991–2012), and the period of 2020 to 2049 under different climate change scenarios. The results of this analysis demonstrate the inadequacy of the WERCC during the historical period and indicate that the continuation of the existing trend (base scenario, MSC0) will cause many environmental issues. Hence, several water and environmental resources management (WERM) scenarios are proposed to enhance the WERCC. These scenarios are evaluated using a multi-agent-multi-criteria decision-making method to identify the preferable WERM scenario (MSC12356). This scenario, which encompasses various projects (e.g., development and enhancement of water transfer networks and upgrading cultivation methods), improves the average value of the WERCC by 26 %. The results of the proposed methodology are compared with those of a traditional decision-making method, which considers three criteria of average WERCC, the pressure-support index, and the implementation cost. The results demonstrate that the multi-agent-multi-criteria decision-making approach provides a more cost-effective management scenario, with 30 % less cost, leading to only 3 % less carrying capacity.

Modern Trends and Technologies of Human Resource Management

The relevance of the study is determined by the fact that the socio-economic transformations taking place in the world require a rapid adjustment of the conditions for the functioning of a business, for which human resources become a determining factor in competitiveness, which determines survival in a rapidly changing market. The study of trends and modern technologies of human resource management becomes especially relevant in such circumstances, since it allows you to identify areas for improving relations between employees and employers.The purpose of the study is determined by the need to study modern trends in the development of human resources that affect their management technologies in modern conditions.The objectives of the study are as follows: to study modern approaches to the content of human resources and determine the conceptual foundations of their management; substantiate the reasons for the transition to the humanistic concept of human management; to systematize the key directions of development of human resources and technologies for their management; identify scenarios for the future development of relationships between employees and employers.Methodology the research methodology is based on the methods of logical and comparative analysis, data grouping, the method of expert assessments, modeling and forecasting.The results of the study show that the modern concept of human resource management is being transformed, realizing the transition from the organizational and social to the humanistic concept of human management. The modern business strategy is defined by the functionality of human resource management from the position of recognizing the abilities and talents of a person as a special object of management. The work reveals a set of reasons that led to the transformation of managerial functions: the predominance in the 21st century of the format for describing the decisionmaking environment BANI instead of VUCA; digitalization of most of all processes and phenomena surrounding a person; high mobility of workers and their commitment to the idea of lifelong education. Taking into account these patterns, the study identified basic trends in human resource management, which are grouped into three blocks: socio-economic and organizational, managerial-technological and humanitarian-behavioral. Based on expert assessments, scenarios for the development of human resources have been developed from the point of view of their interaction with employers under the influence of factors of a growing supply of talents and the regulatory role of the state.Conclusions: the conclusions obtained as a result of the study indicate that the growing complexity of the modern world requires a transition to the maximum variability of human resource management scenarios and the rejection of universal technologies, for which there is no place left in modern conditions of unpredictability.

An adaptive social forestry model in West Papua based on cultural forests and the main potential of NTFPS: Theory and practice

The presence of the Job Creation Law Number 11 of 2020 opened a new discourse on social forestry policy in Indonesia. The discourse on the concept of forest resource management is used as the basis for the theory and practice of local community-based development. The purpose of this paper is to develop a model of adaptive natural resource management for the development of site-scale social forestry. As potential superior Non-Timber Forest Products (NTFPs), the types of Papuan nutmeg and black fruit have been utilized by local communities for generations. A mixed method using descriptive system analysis was used in developing the concept of cultural forest. The results of the study found that a cultural-forest-based adaptive natural resource management scenario in West Papua from case studies on the use of nutmeg in Fakfak and black fruit districts in Teluk Wondama district can be designed as a model for social forestry at the site level. The three landscape typologies of natural forest habitat, secondary forest and home gardens are a systemic-holistic unit that demonstrates certainty of access and ownership for determining site-scale social forestry schemes in West Papua.

Connecting distinct realms along multiple dimensions: A meta-ecosystem resilience perspective

Resilience research is central to confront the sustainability challenges to ecosystems and human societies in a rapidly changing world. Given that social-ecological problems span the entire Earth system, there is a critical need for resilience models that account for the connectivity across intricately linked ecosystems (i.e., freshwater, marine, terrestrial, atmosphere). We present a resilience perspective of meta-ecosystems that are connected through the flow of biota, matter and energy within and across aquatic and terrestrial realms, and the atmosphere. We demonstrate ecological resilience sensu Holling using aquatic-terrestrial linkages and riparian ecosystems more generally. A discussion of applications in riparian ecology and meta-ecosystem research (e.g., resilience quantification, panarchy, meta-ecosystem boundary delineations, spatial regime migration, including early warning indications) concludes the paper. Understanding meta-ecosystem resilience may have potential to support decision making for natural resource management (scenario planning, risk and vulnerability assessments).

Enhancing the resilience of ecosystem services under extreme events in socio-hydrological systems: A spatio-temporal analysis

Due to the adverse impacts of severe droughts on various aspects of human life and ecosystem services (ESs), the spatio-temporal assessment of the resilience of ESs under droughts is essential. In this paper, we propose a new methodology for assessing ESs-based resilience, taking into account the seven resilience principles: a) redundancy and diversity, b) managing connectivity, c) managing slow variables and their feedback, d) complex adaptive system (CAS) thinking, e) experimentation and learning, f) broadening participation, and g) polycentric governance. These principles enable us to consider the main social, political, hydrological, economic, and environmental aspects concerning resilience which have been overlooked in previous studies. The methodology is evaluated by applying it to Zarrinehroud River Basin (ZRB) in north-western Iran. A set of qualitative and quantitative criteria and their sub-criteria are proposed for quantifying the ES-based resilience and generating time series of resilience against severe droughts in several sub-basins in the study area. To evaluate the criteria and sub-criteria, the required data are derived from calibrated SWAT and MODSIM models as well as experts’ judjments. The time series of ES-based resilience under 128 Water and Environmental Resources Management (WERM) scenarios (for enhancing agricultural practices, altering and modernizing irrigation methods, improving irrigation network and drainage facilities) and Climate Change (CC) scenarios (RCP 4.5, RCP6.0, and RCP 8.5) are derived for each sub-basin based on short-term (2020–2049) and long-term (2020–2098) periods. The low resilience values (0.53–0.6) of all sub-basins under the base management scenario (the status quo scenario (SC0)) illustrate the need for implementing some projects to enhance the ESs in the study area. The results show that the WERM scenario SC12346 can improve the values of the resilience criterion in sub-basins up to 0.85 and reduce the vulnerability of the study area to droughts. By evaluating all management scenarios, scenario SC12346 is reported as the best scenario, since it can significantly increase the resilience of all sub-basins against extreme droughts with an acceptable cost of 636 million US dollars compared to other scenarios. Under this WERM scenario, the resilience values of sub-basins increase up to 40%. This scenario suggests implementing a set of projects such as improving irrigation networks and drainage facilities.

A multi-agent decision-making framework for evaluating water and environmental resources management scenarios under climate change

This paper introduces a hierarchical multi-agent decision-making framework for Water and Environmental Resources Management Scenarios (WERMSs) under uncertain conditions of climate change and complex agent characteristics. The proposed framework utilizes three Game Theory concepts: the Stackelberg, Bayesian (Incomplete), and Imperfect games, in order to incorporate the hierarchical structure of the agents and the temporal distribution and accuracy of information between them. The methodology is applied to the Zarrinehroud River Basin (ZRB), the largest hypersaline lake in the Middle East. The area of the lake has decreased dramatically (about 50 %) during past decades causing various environmental, social, and economic problems. WERMSs were evaluated using qualitative and quantitative hydrological, social, economic, and ecological criteria under different climate change scenarios. The proposed methodology provides equilibriums in the decision-making process while considering different climate change scenarios. Applying the selected WERM results in an accumulated value of 2995 million m3 of water flow to the lake until 2049. Moreover, the lake's elevation reaches a new level of 1272.6 m above sea level at the end of the following 30 years, compared to the elevation of 1271.3 at the beginning of the evaluation period.

Simulation and Evaluation of Water Resources Management Scenarios Under Climate Change for Adaptive Management of Coastal Agricultural Watersheds

The main objective of this paper is to analyze the impact of climate change on water resources management and groundwater quantity and quality in the coastal agricultural Almyros Basin, in Greece. Intensive groundwater abstractions for irrigation and nitrogen fertilization for crop production maximization, have caused a large water deficit, nitrate pollution, as well as seawater intrusion in the Almyros aquifer system. Multi-model climate projections for Representative Concentration Pathways (RCPs 4.5 and 8.5) from the Med-CORDEX database for precipitation and temperature have been used to evaluate the impacts of climate change on the study area. The multi-model climate projections have been bias-corrected with Delta, Delta change of Mean and Variance, Quantile Delta Change, Quantile Empirical Mapping, and Quantile Gamma Mapping methods, and statistically tested to find the best GCM/RCM multi-model ensemble. Simulation of coastal water resources has been performed using an Integrated Modelling System (IMS) that contains connected models of surface hydrology (UTHBAL), groundwater hydrology (MODFLOW), nitrate leaching/crop growth (REPIC), nitrate pollution (MT3DMS), and seawater intrusion (SEAWAT). The results indicate that the best climate multi-model ensemble consists of three (3) climate models for both RCP4.5 and RCP8.5 using the Quantile Empirical Mapping bias-correction method. The IMS was applied for historical and future periods with observed and simulated meteorological inputs (e.g. precipitation and temperature) and various irrigation and agronomic scenarios and water storage works development (i.e. reservoirs). The results indicate that at least deficit irrigation and deficit irrigation along with rain-fed cultivation schemes, combined with or without the development and operation of reservoirs, should be applied to overcome the degradation of groundwater quality and quantity in the study basin. Based on the findings of this work, the water resources management should be adaptive to tackle the water resources problems of the Almyros Basin.

Vulnerability evaluation and prediction of the water-energy-food-ecology nexus in the Yangtze River Economic Belt based on TOPSIS, neighborhood rough set and support vector machine

With the intensification of human activities, the vulnerability of water, energy, food and ecology systems has become more and more prominent, and the research on the vulnerability of the water-energy-food-ecology (WEFE) nexus is significant to realizing regional sustainable development. This study aims to make a comprehensive measurement of the vulnerability of the WEFE nexus in the Yangtze River Economic Belt (YREB) from 2008 to 2019, clarify the evolutionary trend of its vulnerability, and predict the vulnerability of each province (municipality) in the future, to formulate policies to reduce vulnerability. This study firstly constructs a vulnerability evaluation index system of the WEFE nexus based on the VSD framework and uses the neighborhood rough set (NRS) to reduce the attributes. Then, the TOPSIS model is used to evaluate the vulnerability of the WEFE nexus. Finally, by comparing the training accuracy of the random forest, decision tree and support vector machine (SVM) model, the SVM model is selected to predict the vulnerability of the WEFE nexus under different scenarios in 2025. The results show that the vulnerability of the WEFE nexus in the YREB showed a fluctuating downward trend from 2008 to 2019. The decline is faster in the middle and upper reaches, and slower in the lower reaches. In 2025, under a strong resource management scenario, the vulnerability of the provinces (municipalities) in the YREB will decrease significantly, while the weak and moderate resource management scenarios are not conducive to reducing vulnerability and even worsening. Therefore, in the future, the provinces (municipalities) in the upper, middle and lower reaches should make reasonable use of the resource endowments, take measurements actively according to local conditions, and continuously strengthen the management of water, energy, food and ecological resources, thus promoting the continuous improvement of the vulnerability of the WEFE nexus.

Selecting the optimal exploitation option using a digital deposit model and the AHP

The prime objective of the study was to identify and evaluate options for development and exploitation of a prospective hard coal deposit using a digital geological model and a multi-criteria decision-making approach allowed, in elaborated research process, to identify investment alternatives and outline the one that maximizes the benefits for the potential investor. The developed research methodology was based on decision criteria including: economic, technical, geological, social, and environmental aspects. The combination of the above criteria made it possible to create six options for the development of the deposit named as: 1.2 MAX and 1.2 EKO, 1.5 MAX and 1.5 EKO, and 1.8 MAX and 1.8 EKO. The Analytic Hierarchy Process (AHP) was used as a method to select the optimum investment option. The research process consisted in taking into account the positive and negative impacts of individual exploitation options by building four separate hierarchical models (BOCR analysis), i.e. Benefits (B), Opportunities (O), Costs (C) and Risks (R).Digital geological model of the existing and prospective deposit was a key source of information for AHP assessment process. The structural model of 15 seams of economic importance and a qualitative model of coal quality parameters were elaborated. The structural and quality models were prepared on the basis of lithostratigraphic profiles from 55 surface boreholes, 16 underground boreholes and 250 geological profiles of mine workings in the area of the existing coal deposit. These models constituted input for the assessment of economic efficiency of the above mentioned options. The digital model served as the basis for the creation of access, development and mining work schedules, and the developed simulations of mining exploitation were used to build a model of surface deformation considered as one of the most significant decision-making factor.The result of the work was formulated as a ranking of the analyzed scenarios, indicating the most attractive ones. In this case, and in terms of the adopted AHP methodology, the dynamic strategy scenarios is represented by ‘No additional shafts' scenario, 1.8 EKO, 1.8 MAX and 1.5 EKO scenarios. Their implementation fulfils the policy of sustainable depletion of the reserves of a prospective deposit, while maintaining environmental standards and high economic efficiency. The ‘No additional shafts' scenario represents the idea of rapid decommissioning of the mining industry, while scenarios 1.8 EKO, 1.8 MAX and 1.5 EKO are in turn scenarios of rational resources management allowing for gradual depletion of the deposit reserves in a long-term perspective.

The economic-administrative role of geographic information systems in rural tourism and exhaustive local community development in African marginalized communities

PurposeThe purpose of this study was to examine the latent part of geographic information systems in inclusive sustainable rural tourism, community-based natural resource management (CBNRM) and community development and empowerment in Southern Africa, Africa generally and many rural areas elsewhere worldwide.Design/methodology/approachThe viewpoint utilizes literature and document reviews to assess African and worldwide agricultural, environmental and tourism resources management scenarios. It thus liaises with CBNRM and geographic information systems in sustainable tourism and local community development applications.FindingsThis review viewpoint uncovers a better potential synergetic relationship between tourism and rural (agricultural) activities that geographic information systems along a concept of CBNRM can amplify. Hence, it has poised a need for a decent and integrated tourism strategy to develop and empower the pertinent communities in many rural and marginalized areas within the continent.Originality/valueMany rural communities in Southern Africa and Africa broadly dwell in low-income areas. Such milieus are rich in natural biodiversity, including tourism destination areas. Geographic information systems, sustainable tourism and CBNRM can form a gestalt of local community development projects within their environs.

An Undergraduate Interprofessional Experience with Self-Learning Methodology in Simulation Environment (MAES©): A Qualitative Study.

This article describes the impact that a Self-learning Methodology in Simulated Environments can have on Interprofessional Education within a Crisis Resource Management simulated scenario. We used a qualitative approach. It is divided into three phases: study and design, plan of action, and analysis and evaluation. During the first phase of the study, there emerged a poor use of Interprofessional Education in the nursing and medical degrees, and it became apparent that there was a need for an implementation. Due to the possibility for better training for both technical and non-technical skills within Crisis Resource Management, a simulation scenario within this setting has been established as a learning baseline objective. The technique used to develop the scenario in the second phase of the study was the Self-learning Methodology in Simulated Environments. Its structure, comprising six items, was previously demonstrated in the literature as appropriate for healthcare degree students. The main result of the third phase shows an overall acceptance of an Interprofessional Education within Self-learning Methodology in Simulated Environments during the practice of a Crisis Resource Management scenario. The integrated application of a Self-learning Methodology in Simulated Environments, Interprofessional Education, and Crisis Resource Management result in a synergistic combination that allows students to share knowledge, technical, and non-technical skills using an innovative learning method.

Integrated Modeling of Agronomic and Water Resources Management Scenarios in a Degraded Coastal Watershed (Almyros Basin, Magnesia, Greece)

The scope of this study is to assess the effects of agronomic and water resources management scenarios on groundwater balance, seawater intrusion, and nitrate pollution and the comparison of the developed scenarios relative to the current crop production and water management regime in the coastal agricultural Almyros basin in the Thessaly region, Greece. Agronomic and water resources scenarios have been simulated and analyzed for a period of 28 years, from 1991 to 2018. The analysis has been conducted with the use of an Integrated Modeling System for agricultural coastal watersheds, which consists of coupled and interlinked simulation models of surface water hydrology (UTHBAL), reservoir operation (UTHRL), agronomic/nitrate leaching model (REPIC), and groundwater models for the simulation of groundwater flow (MODFLOW) and contaminant transport of nitrates (MT3DMS) and chlorides (SEAWAT). The pressure on water resources has been estimated with the Water Exploitation Index (WEI+) and the reservoirs’ operation with the Reliability index to cover the water demands. The indices of Crop Water Productivity, Nitrogen Use Efficiency, and Economic Water Productivity have been used to quantify the benefits and the feasibility of the alternative scenarios. The best results for the sustainability of water resources are achieved under the deficit irrigation and rain-fed scenario, while the best results for water resources and the local economy are achieved under deficit irrigation and reduced fertilization scenario.

Buffalo Pound Lake—Modelling Water Resource Management Scenarios of a Large Multi-Purpose Prairie Reservoir

Water quality models are an emerging tool in water management to understand and inform decisions related to eutrophication. This study tested flow scenario effects on the water quality of Buffalo Pound Lake—a eutrophic reservoir supplying water for approximately 25% of Saskatchewan’s population. The model CE-QUAL-W2 was applied to assess the impact of inter-basin water diversion after the impounded lake received high inflows from local runoff. Three water diversion scenarios were tested: continuous flow, immediate release after nutrient loading increased, and a timed release initiated when water levels returned to normal operating range. Each scenario was tested at three different transfer flow rates. The transfers had a dilution effect but did not affect the timing of the nutrient peaks in the upstream portion of the lake. In the lake’s downstream section, nutrients peaked at similar concentrations as the base model, but peaks arrived earlier in the season and attenuated rapidly. Results showed greater variation among scenarios in wet years compared to dry years. Dependent on the timing and quantity of water transferred, some but not all water quality parameters are predicted to improve along with the water diversion flows over the period tested. The results suggest that it is optimal to transfer water while local watershed runoff is minimal.

Evaluating and improving the sustainability of ecosystem services in river basins under climate change

This paper presents a new framework for evaluating the sustainability of basin-wide ecosystem services (ESs) including provisioning, regulating, supporting, and cultural services. In this framework, the Soil and Water Assessment Tool (SWAT) and MODSIM11A generalized river basin decision support system and network flow model developed at the Colorado State University. models and experts' opinions are used to evaluate the ESs.To show the applicability of the proposed framework, it is applied to the Zarrinehrud river basin under three different climate change (CC) scenarios (i.e., RCP 4.5, 6.0, and 8.5) for two different time horizons (i.e., 2020–2049 and 2020–2098). This basin is the main water supplier of the largest hypersaline lake in the Middle East, Lake Urmia. In the next step, 128 water resources management (WRM) scenarios are taken into account considering the projects defined by Urmia Lake Restoration National Committee (ULRNC). All ecosystem services are evaluated considering all WRM and CC scenarios. Finally, a group COPRAS-based decision-making approach is used to determine the best WRM scenario under climate change. The results show that WRM scenario 128 is the best scenario for improving ecosystem services in the study area. This scenario includes some projects such as allocating water to the lake from new resources, rehabilitating irrigation and draining networks, and improving cropping patterns.