Water Resources Systems Research Articles

A green-gray path to global water security and sustainable infrastructure

Sustainable development demands reliable water resources, yet traditional water management has broadly failed to avoid environmental degradation and contain infrastructure costs. We explore the global-scale feasibility of combining natural capital with engineering-based (green-gray) approaches to meet water security threats over the 21st century. Threats to water resource systems are projected to rise throughout this period, together with a significant expansion in engineering deployments and progressive loss of natural capital. In many parts of the world, strong path dependencies are projected to arise from the legacy of prior environmental degradation that constrains future water management to a heavy reliance on engineering-based approaches. Elsewhere, retaining existing stocks of natural capital creates opportunities to employ blended green-gray water infrastructure. By 2050, annual engineering expenditures are projected to triple to $2.3 trillion, invested mainly in developing economies. In contrast, preserving natural capital for threat suppression represents a potential $3.0 trillion in avoided replacement costs by mid-century. Society pays a premium whenever these nature-based assets are lost, as the engineering costs necessary to achieve an equivalent level of threat management are, on average, twice as expensive. Countries projected to rapidly expand their engineering investments while losing natural capital will be most constrained in realizing green-gray water management. The situation is expected to be most restrictive across the developing world, where the economic, technical, and governance capacities to overcome such challenges remain limited. Our results demonstrate that policies that support blended green-gray approaches offer a pathway to future global water security but will require a strategic commitment to preserving natural capital. Absent such stewardship, the costs of water resource infrastructure and services will likely rise substantially and frustrate efforts to attain universal and sustainable water security.

Comprehensive analysis of water carrying capacity based on wireless sensor network and image texture of feature extraction

This article takes the complex uncertainty in the carrying process of water resources system as the research object. Firstly, the water resources carrying capacity system is divided into three sub-systems: bearing support capacity, bearing pressure and bearing regulation capacity. System analysis methods based on wireless sensor network and image texture of feature extraction for correlation analysis, gray correlation analysis, and multi-dimensional conditional cloud algorithm are introduced into the field of water resources carrying capacity evaluation research. Moreover, combine it with the subtraction set opposition, the effect partial bias connection number, and the risk matrix. Finally, three types of models for water resource carrying capacity evaluation and trend analysis were constructed. The evaluation results of water resources carrying capacity are consistent with the actual process, and the overall development trend is gradually improving. The application results of the evaluation model of water resource carrying capacity are established. The calculation results of the image texture feature of extraction model are similar to the overall change trend of the model before the improvement. The trend of change is more obvious. It can not only describe the water resource carrying level as a whole, but also characterize the reliability of the calculation results and the bearing risk caused by the uncertainty of the water resource carrying system. The water resources carrying capacity evaluation and trend analysis of calculation results are reasonable and feasible. The research results can provide a reasonable and effective decision-making basis for the systematic analysis of the bearing boundary issues between regional complex water resources systems and human water activities, and then propose adaptive risk prevention and control strategies for water resources carrying capacity.

Simulation Of Reservoir Operation In A Multi Reservoir System

The present study aims to apply simulation software MIKE Basin for the operation of reservoirs of Mahanadi Reservoir Project (MRP) Complex. MRP complex is a multipurpose multi reservoir system. Simulation is a technique by which we emulate the behavior of a system. Simulation is a very powerful technique in analyzing most complex water resource system in detail for performance evaluation. Reservoir operation study has been done for data of 34 years. The results extracted from the study indicated that the performance of simulation model MIKE Basin is satisfactory.

A stochastic modeling approach for analyzing water resources systems

Many uncertain factors exist in the water resource systems, leading to dynamic characteristics of the water distribution process. Especially for the watershed including irrigation area with multiple water sources and water users, it is complicated that the joint risk among available water from each water source and multi-uncertainties under water resource allocation among multiple water users. In this research, an approach is developed that a copula-based interval multi-stage fuzzy stochastic programming (CIMFSP) model. This research aims at figuring out the planning of a case study for water-resources management. In the multi-sources water supply subsystem, the copula function is introduced to tackle the interaction of water availability between two water sources (i.e., A &B). Joint risk was set 0.05, 0.10, 0.15 to reflect the shortage risk of total available water at diverse levels. An interval parameter multi-stage fuzzy stochastic programming (IMFSP) model is developed for water resource distribution in a multi-users water-demand subsystem. Through this model, uncertainties presented as interval numbers and probability distributions, as well as fuzzy sets, were handled. The dynamics of the entire water resource system can be reflected by multi-stage discrete trees. A series of solutions can be generated under multiple scenarios (i.e., joint risk and α-cut levels). The modeling results will produce a series of alternatives under a battery of scenarios and help the decision-makers get an insight into the tradeoff between the system economic benefit and financial penalties under the corresponding risk level. This approach is valuable for improving the feasibility of optimal results in the watershed with irrigation region water resource management.

Integrated modelling to assess the impacts of water stress in a transboundary river basin: Bridging local-scale water resource operations to a river basin economy

In this study, we develop a hydro-economic modelling framework for river-basin scales by integrating a water resources system model and an economic model. This framework allows for the representation of both local-scale features, such as reservoirs, diversions, and water licenses and priorities, and regional- and provincial-scale features, such as cross-sectoral and inter-regional connectedness and trade flows. This framework is able to: (a) represent nonlinearities and interactions that cannot be represented by either of typical water resources or economic models; (b) analyze the sensitivity of macro-scale economy to different local water management decisions (called ‘decision levers’ herein); and (c) identify water allocation strategies that are economically sound across sectors and regions. This integrated model is applied to the multi-jurisdictional Saskatchewan River Basin in Western Canada. Our findings reveal that an economically optimal water allocation strategy can mitigate the economic losses of water stress up to 80% compared to the existing water allocation strategy. We draw lessons from our analysis and discuss how integrated inter-regional hydro-economic modelling can benefit vulnerability assessment and robust decision making.

RETRACTED ARTICLE: Image classification-based groundwater pollution prediction and regional economic collaborative innovation

At present, as a nonrenewable resource, water resource has become an important living condition of human society and the whole ecosystem. As an important part of the whole social water resources system, groundwater resources play a very important role in human society. Due to the scarcity of surface water resources and the aggravation of pollution, human beings began to exploit the relatively clean underground water. In China, groundwater accounts for about one third of all water resources, and is one of the important water sources for people’s living water, social production, and development. At present, many cities in China are using groundwater as industrial and domestic water. Because of the nature of groundwater, when it is polluted, it is difficult to treat and recycle, which directly affects people’s water use and social development. Therefore, we propose a groundwater pollution prediction method based on image classification. Supply chain coordination based on the analysis of the basic principles of regional economic innovation system, this paper focuses on the problems related to the supply chain system coordinated with the development of regional economic innovation. By creating a supply chain system and combining with the characteristics of regional economic development, the decentralized system can be integrated across different regions, departments and companies. In this paper, through the realization of the optimal allocation of production factors resources, to achieve the value reconstruction and create the added value of regional economy and industrial collaborative innovation, effectively promote the healthy and scientific development of China’s social economy.

The agro-meteorological perspective of drought over northwest Himalayas: Kashmir valley from 1979 to 2014

Understanding the anatomy of drought is important to reduce the drought hazards in arid and semi-arid regions around the globe. This study pertains to disclose the spatio-temporal variability of rainfall over the Kashmir region in all four seasons of a year (winter, spring, summer, and fall) along with Mann–Kendall trend analysis to provide a preferable insight into the rainfall excess and deficit years. We have used the daily precipitation data of five meteorological stations from 1969 to 2014 over the study area. The standard precipitation index (SPI) has been manipulated to investigate the pitfalls of drought years on the agricultural and horticulture production of the Kashmir region. The analysis reveals that the spring season experiences maximum rainy days showing a decreasing trend and the year 1992, as the poorest rainfall year. The following years (1970, 1971, 1977, 1992, 1999, 2000, and 2001) were found to be under-drought with variation in intensity from moderate to extreme over the whole study region. The implications of drought on agriculture have been visible as the drought years have constricted apple and the total production, which in turn drastically harmed the economy of the valley since it is mainly boosted by apple production. This study will help to plan and design the water resource system in such a way as to decrease the potential effect of future drought years on the economy of the valley.

Regional agricultural water resources management with respect to fuzzy return and energy constraint under uncertainty: An integrated optimization approach

In this study, an integrated framework is proposed for agricultural water and land resources management under uncertain circumstances and energy-water nexus. The framework has two components: the optimized interval solutions generation of unknown market quotation and environment situation through the novel interval fuzzy-expectation programming, and the post-optimization decision-making of the tradeoff between system risk and return through risk-explicit interval programming. An optimization model based on the framework was developed from a real description for agricultural water resources system of Guangdong province under considering various crop, multiple water sources, and the related energy consumption in irrigation and drainage. The impact of energy consumption and risk level control on water resources allocation among different crops and system benefits were analyzed. The results indicated that the preference for surface water resources as the main water sources can effectively reduce regional irrigation energy consumption, and the planting area of each crop would have different variations duo to resources endowment constraints. Risk tradeoff-based results can provide valuable information and additional concern for developing low carbon-oriented agricultural water resources management schemes.

Assessment of Future Climate Change Impact on an Agricultural Reservoir in South Korea

Drought has been frequently occurring in South Korea due to climate change. Analyzing the water supply capacity of the water resource system provides essential information for water resource management. This study evaluates the future water supply capacity of the Gwanghye (GH) agricultural reservoir based on the representative concentration pathways 4.5 and 8.5 climate change scenarios. We performed a reservoir simulation by reflecting the full water level of the reservoir before and after reservoir heightening. Climate change is expected to decrease the GH reservoir’s future available water resources due to the overall reduction in the reservoir’s runoff. After the reservoir-heightening project, an overall improvement was observed in the stability of the future irrigation water supply. Moreover, the remaining water after the supply of the irrigation water could supply 0.6–7.2 × 103 m3 of daily instream water. Thus, flexible reservoir operations are necessary according to climate change scenarios and the reservoir operation period. The use of climate change information should be expanded to establish reasonable water management policies for future climate change scenarios.

Nonstationary-Probabilistic Framework to Assess the Water Resources System Vulnerability: Long-Term Robust Planning and Timing

AbstractMultiobjective water resources systems require long-term operational plans that consider vulnerability to failure under nonstationary conditions due to climate change. The paper presents a ...

Surface Water Detection Method for Water Resources Management

Small significance earth dams during the dry period for locals at most semi-arid cannot be overestimated. Water stored in the same of these dams is little or no lack of domestic water and drinking water for residents during dry periods. The main limitation is the lack of knowledge of the storage quantities of small dams in the study area and knowing this form of field data regularly is costly and needs a long and arduous time. Remote sensing and geographic information systems (GIS) can be used in this study due to their ability to measure and analyze the amount of water stored in some small reservoirs. In this paper, the Water Natural Difference Index (NDWI) is used to detect the surface area as the base to estimate small reservoir storage capacities. The model equation created by this study provided a tool to know the amount of water available per day in the small reservoirs during the dry season and thus was able to obtain clear pictures of the water resources system by the planners. This method may help the planners and water managers will quickly make decisions on how to utilize and manage the available water given the various competing uses.

An Integrated Framework for Risk‐Based Analysis of Economic Impacts of Drought and Water Scarcity in England and Wales

AbstractDrought and water scarcity pose a risk to the economy, particularly sectors where water is a crucial input to the production process. This paper describes integrated simulations of water shortages from a dynamic national water resource systems model with a static economic input‐output (I‐O) model to assess total drought risk to the economy. To quantify the economic risks of drought and water scarcity, the analysis: (a) integrates a large ensemble of simulated meteorological droughts, propagated through a national hydrological model and water resource systems model to simulate water availability from reservoirs and groundwater; (b) assesses implications of restrictions on water availability for multiple water user categories, representing natural and human contributions to water scarcity; (c) investigates how water shortages propagate into economy‐wide direct and indirect impacts. The study focuses on England and Wales where the water supply system is considered under strain, with growing recognition of the economic risk of prolonged and widespread shortages. The direct Expected Annual Loss (EAL) to water users, averaged over an ensemble equivalent to 2800 years of synthetic daily weather, is estimated to be £11.7 million in the 2011 base‐year. Accounting for indirect economic losses results in a total EAL of £30.2 million in 2011. The most severe event simulated results in a total loss of £1.4 billion in 2011, equivalent to 0.11% of GVA. The analysis provides a framework to assess what the economically efficient level of system reliability should be, and for deciding upon appropriate water management regulations and strategic investments.

A self‐exciting marked point process model for drought analysis

AbstractA self‐exciting marked point process approach is proposed to model clustered low‐flow events. It combines a self‐exciting ground process designed to capture the temporal clustering behavior of extreme values and an extended Generalized Pareto mark distribution for the exceedances over a subasymptotic threshold. The model takes into account the dependence between the magnitude and occurrence time of exceedances and allows for closed‐form inference on tail probabilities and large quantiles. It is used to analyze daily water levels from the Rivière des Mille Îles (Québec, Canada) and to characterize drought patterns in the Montréal area. The model is useful to generate short‐term probability forecasts and to estimate the return period of major droughts. This information on the drought events is critical to water resource professionals in planning, designing, building, and managing more efficient water resource systems to hedge against the water shortage in case of extreme droughts.

A Continental Assessment of Reservoir Storage and Water Availability in South America

This study presents the first continental assessment of water storage and its influence on the availability of water of the river systems of South America. Although hydraulic infrastructure has the potential to cause several impacts on river systems and the environment, their relevance in water resources systems is irrefutable. The human services that dams and reservoirs provide to society, e.g., hydroelectricity, water supply, irrigation, or flood control, are vital services that society requires to develop. Despite this fact, the interactions of dams and reservoirs in the river systems of South America have not been explored from a hydrological perspective. In this study, we present the first assessment of the potential effects of water storage at a basin scale in South America. For this purpose, first we present an analysis of the current conditions and the influence of water storage in the basins of the continent. Then, we estimate the potential water availability of each basin, to evaluate the role of water storage in the availability of water in the continent. Our findings indicate that the ‘Colorado’ and ‘Negro’ basins in Argentina are the most influenced by water storage in the continent. Moreover, our results suggest that reservoirs improve the potential water availability capacity, particularly in the southern basins of the continent. With this study, we expect to provide helpful insights about the current interactions of reservoirs with the river systems of the continent.

A prediction method of regional water resources carrying capacity based on artificial neural network

To better predict the water resources carrying capacity and guide the social and economic activities, a prediction method of regional water resources carrying capacity is proposed based on an artificial neural network. Zhaozhou County is selected as the research area of water resources carrying capacity prediction, and its natural geographical characteristics, social economy, and water resources situation are explored. According to the regional water resources quantity and utilization characteristics and evaluation emphasis, the evaluation index system of water resources carrying capacity is constructed to evaluate the importance and correlation of water resource carrying capacity. The pressure degree of water resources carrying capacity is divided into five grades. According to the evaluation standard of bearing capacity, the artificial intelligence BP neural network model is constructed. Based on the main impact factors of water resources carrying capacity in this area, the water resources carrying capacity grade is obtained by weight calculation and convergence iteration by using neural network model and influence factor data to realize the prediction of water resources carrying capacity. The research results show that the network model can meet the demand for precision. The prediction results have a high degree of fit with the actual data, indicating that human intelligence can obtain accurate prediction results in water resources carrying capacity prediction.

Dynamic long-term streamflow probabilistic forecasting model for a multisite system considering real-time forecast updating through spatio-temporal dependent error correction

Long-term streamflow forecasting for a multisite river basin system can experience oscillation of spatio-temporal dependent forecast errors. Characterizing the dependent information and conducting spatio-temporal dependent forecast error correction can reduce the total uncertainty in real-time forecasting. On the basis of a single-site martingale model of forecast evolution (MMFE), which can simulate forecast uncertainty evolution over the temporal scale, this study developed a dynamic long-term streamflow probabilistic forecasting model that addresses spatio-temporal dependent error correction for a multisite system. Error characteristics and hybrid spatio-temporal forecast improvements with complex dependencies are captured by Copula function, which describes the systemwide evolution of forecast uncertainty. The proposed model was verified by forecasting the streamflow of the Hongze Lake–Luoma Lake system in China. The results revealed the following. 1) The spatio-temporal dependent error correction based on MMFE can refine the spatio-temporal dimension hybrid error information, which is helpful in improving forecast accuracy. 2) As the spatio-temporal dependence of forecast uncertainty is described using a Copula function, selection of the marginal distribution and connection function is flexible through combining statistical and informational characteristics of the errors, which is helpful in improving the fittedness of complex system error simulation. 3) Compared with the benchmark forecast model without correction, the proposed model greatly decreased forecast uncertainty by reducing the standard deviation of the errors, continuous ranked probability score (CRPS), and Brier score (BS) by nearly 40%, 11.4%, and 34.6%, respectively, and further reduce the CRPS by 2.1% on average (highest value: 3.7%) and reduce the BS by 1.2% on average (highest value: 2.0%) in comparison with only temporal correction. The results demonstrate that the proposed model improves the accuracy and reliability of probabilistic streamflow forecasting for complex water resource systems by reducing uncertainty.

Assessment and Prediction of Water Resources Vulnerability Based on a NRS-RF Model: A Case Study of the Song-Liao River Basin, China.

The vulnerability of water resources is an important criterion for evaluating the carrying capacity of water resources systems under the influence of climate change and human activities. Moreover, assessment and prediction of river basins’ water resources vulnerability are important means to assess the water resources security state of river basins and identify possible problems in future water resources systems. Based on the constructed indicator system of water resources vulnerability assessment in Song-Liao River Basin, this paper uses the neighborhood rough set (abbreviated as NRS) method to reduce the dimensionality of the original indicator system to remove redundant attributes. Then, assessment indicators’ standard values after dimensionality reduction are taken as the evaluation sample, and the random forest regression (abbreviated as RF) model is used to assess the water resources vulnerability of the river basin. Finally, based on data under three different future climate and socio-economic scenarios, scenario predictions are made on the vulnerability of future water resources. The results show that the overall water resources vulnerability of the Song-Liao River Basin has not improved significantly in the past 18 years, and the overall vulnerability of the Song-Liao River Basin is in the level V of moderate to high vulnerability. In the future scenario 1, the overall water resources vulnerability of the river basin will improve, and it is expected to achieve an improvement to the level III of moderate to low vulnerability. At the same time, the natural vulnerability and vulnerability of carrying capacity will increase significantly in the future, and the man-made vulnerability will increase slowly, which will deteriorate to the level V of moderate to high vulnerability under Scenario 3. Therefore, taking active measures can significantly reduce the vulnerability of nature and carrying capacity, but man-made vulnerability will become a bottleneck restricting the fragility of the overall water resources of the river basin in the future.

Managing food-ecosystem synergies to sustain water resource systems

Measures implemented to restore ecosystem services are widely believed to conflict with food production in the world's irrigated regions because of their competition for scarce water. However, little integrated analysis has been conducted to test this hypothesis. This work tests that hypothesis by presenting results of a basin-scale hydroeconomic analysis linking biophysical, hydrologic, agronomic, ecological, economic, policy, and institutional dimensions of the partially-restored Mesopotamian Marshes of Western Asia. Results serve to partly reject the hypothesis: Here we find that an economically-optimized ecosystem restoration trajectory can be achieved with a minimal loss in food production or farm income where restored wetlands complement important dimensions of food production. Moreover, we find that where water shortage sharing rules can be made more flexible, ecosystem restoration more nearly complements improved food security. Our results point to previously unexplored synergies among food production, ecosystem restoration, and water laws in arid and semi-arid regions internationally.

Comprehensive evaluation of water resources security of the Huaihe Eco-economic Belt

Abstract The study of water resource security is a basic scientific issue that must be faced in the construction of the ecological environment. To examine the status of regional water resources security in the Huaihe Eco-economic Belt, this study builds a comprehensive evaluation index system based on the ‘Driving-Pressure-State-Impact-Response’ (DPSIR) framework, combines the entropy weight method and Lotka–Volterra symbiosis model to calculate the water resources security status from 2010 to 2018. Then the fixed effects regression model is used to analyze the factors affecting the water resources system. The results show that: (1) The status of water resources security in the Huaihe Eco-economic belt decreased from 2011 to 2017 and, thereby transitioned from a safe to a dangerous state. The coordination index of the economic system and water resource system was only −0.17 in 2017, and the partial development model benefited the economy but damaged the water resources. (2) The security status of 25 prefecture-level cities improved significantly, and the number of cities with status of alert or above increased from 11 to 15. However, there are apparent differences among the regions. The status has shifted to ‘north and south being better than east and west’. The water resources security status of Jining, Linyi, and Lu'an have improved, whereas Yancheng, Taizhou, Pingdingshan, and other cities showed rather poor development during 2017. (3) The correlation coefficient of the economic system was −0.154 and hindered the development of the water resources system. The correlation coefficients of the added value of the tertiary industry and the expenditure on energy conservation and environmental protection was 0.699 and 0.180 respectively and played a positive role in promoting the water resources system. It is necessary to optimize and adjust the industrial structure and protect the environment.

Development of hydro-social-economic-environmental sustainability index (HSEESI) in integrated water resources management.

Sustainable development is a grand challenge of the present century, with tremendous direct and indirect implications for a range of social, economic, and environmental factors. This research proposes a water-centric framework for evaluating "relative" sustainability of the status quo in a country via a new "hydro-social-economic-environmental sustainability index" (HSEESI). We test this framework across 35 countries of American continent using national-scale surveyed data for the 2005-2017 periods. HSEESI possesses four dimensions, namely economic, social development, knowledge and technology, and health sanitation and environment, and 12 related indicators for characterizing these dimensions. Based on the developed HSEESI scores, we assess the linkages between water resources and social-economic-environmental systems at the country level, using single and hybrid-artificial intelligence-gene expression programming (GEP) methods. The former method involves all the indicators, while the latter focuses only on the most effective indicators. Further, we aggregate these analyses at three spatial scales, including American continent, North American countries, and South American countries. Our analyses show that both methods lead to approximate similar results, but the latter is preferred for larger scales as it is more cost effective. Overall, results indicate that the status of water resources in North America is relatively sustainable, whereas in South America, it is relatively unsustainable. Importantly, social development, health sanitation, and environmental dimensions, in both North and South American continents, seem to have a relatively unsustainable status, indicating that water resources systems may not have enough capacity to meet the needs of those dimensions. At the country level, our analyses show that water resources systems of Uruguay, Guyana, and Venezuela may face the highest relative unsustainability, across economic, social development, and health sanitation and environment dimensions. The approach and the framework developed in this study can be applied in other regions around the world and with a more detailed representation of intra-country sustainability issues. It can inform managers and policymakers for sustainable planning and developing water resources projects across scales.