Water Resources Systems Research Articles

Study on evaluation index system of sustainable development of mine water resources based on PSO-AHP model and fuzzy comprehensive evaluation

Water resources is an important basic energy. The determination of weights is one of the important indexes in water resources evaluation system and reasonable allocation of weights is the key to quantitative evaluation. In order to establish a scientific evaluation index system of the influence of mining disturbance on water resources for purpose of a more reliable and effective evaluation result and realizing the protection of water resources system, a comprehensive evaluation system of water resources based on PSO-AHP model is proposed in the paper. Combined with the specific geological environment characteristics of mines, this paper establishes a four-level evaluation index system after identifying the factors affecting water resources and ecological environment. By applying the particle swarm optimization (PSO) to the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation method, a PSO-AHP model and then a fitness function are constructed to solve and optimize the weight values in the evaluation index system, and the calculated weight values are checked by consistency checking method. The evaluation results suggest that the index system can accurately reflect the impact of mining on water resources and water ecological environment and etc., providing certain reference value for sewage resourcing and reducing the harmful effect on environment by sewage discharge.

Improving Performance Criteria in the Water Resource Systems Based on Fuzzy Approach

Reliability, resilience, and vulnerability (RRV) have been widely used as the performance criteria of a water supply system in the studies conducted over the last three decades. This study attempts to modify the traditional method commonly applied to estimate these criteria using fuzzy logic thereby the performance criteria of the points with the threshold and intermediate values are more accurately estimated. Traditional methods (RRV-Fixed) of estimating these criteria are based on the fixed threshold values to represent the functionality of a water supply system, using a binary system to identify the periods a system fails to supply the water demands. The employment of this binary system may be taken into account as a weakness of the evaluating system, especially when water portion met is close to the threshold values. The present study develops a new method named RRV-Fuzzy, to ameliorate the weaknesses of the traditional RRV-Fixed estimating system.The method is designated as “Fuzzy Performance Criteria” built upon the traditional RRV formulae with improvements made to their structures using fuzzy membership functions. The efficiency of the proposed method is verified via implementation on two case studies including a theoretical and a real-world water basin. A comparison of the proposed RRV-Fuzzy and the traditional RRV-Fixed methods confirms the efficiency of the proposed method with regard to the improvements achieved in the relevant estimations, validating the new approach to be quite effective and practicable.

Intensity-duration-frequency curves in the municipality of Belo Horizonte from the perspective of non-stationarity

ABSTRACT The study of changes in hydrological data series is of great scientific and practical importance for water resources systems, since these are normally projected based on the assumption that time series is statistically stationary. However, such assumption may not be verified when aspects as changes or climatic variability are considered. In this sense, the present study sought to identify trends in maximum rainfall intensities in Belo Horizonte (MG) and propose, in view of the observed results, a new intensity-duration-frequency (IDF) curve from the perspective of non-stationarity. For the trend analysis, statistical tests were applied, and an adaptation of the concept “Minimax Design Life Level” was proposed to quantify rainfall intensities and fit a non-stationary IDF curve. As a result, different trends were detected, with an increase in rainfall intensities for durations equal to or less than 1 hour starting in 2000. Regarding the IDF relationships, the obtained rain intensities were up to 48% higher than current estimates. Our results emphasize the need to periodically review IDF relationships in order to avoid under or overestimation in the design of hydraulic structures.

Water resources management – towards performance based approach.

Global change that results from population growth, global warming, and land use change (especially rapid urbanization) directly affects the complexity of water resources management problems and the uncertainty they are exposed to. Both, the complexity and the uncertainty, are the result of dynamic interactions of innumerable system parts within three major systems: (i) the physical environment; (ii) the social and demographic characteristics of the region under consideration; and (iii) the pipes, roads, bridges, buildings, and other components of the constructed environment (infrastructure). Recent trends in dealing with complex water resources systems include consideration of the entire region being affected, explicit consideration of all costs and benefits, elaboration of a large number of alternative solutions, and the greater participation of all stakeholders in the decision-making. Systems approaches based on simulation, optimization, and multi-objective analyses, in deterministic, stochastic and fuzzy forms, demonstrated in the last 50 years, an excellent potential for providing appropriate support for effective water resources management. This paper explores the future opportunities based on the advances in systems theory that can, on a broader scale, majorly transform the management of water resources. The paper identifies performance-based water resources engineering as a methodological framework to improve water resources management in the face of rapid climate destabilization so that sustainability becomes the norm, not the occasional success story.

Multiple Hydropower Reservoirs Operation by Hyperbolic Grey Wolf Optimizer Based on Elitism Selection and Adaptive Mutation

Multiple hydropower reservoirs operation is an effective measure to rationally allocate the limited water resources under uncertainty. With the rapid expansion of water resources system, it becomes much more difficult for traditional methods to quickly yield the reasonable operational policy. Grey wolf optimizer, inspired by the wolves’ hunting behaviors, is a famous metaheuristic method to resolve engineering optimization problems, but still suffers from the local convergence and search stagnation defects. To alleviate this problem, this study proposes a hybrid grey wolf optimizer (HGWO) where the hyperbolic accelerating strategy is introduced to improve the local search ability; the adaptive mutation strategy is used to diversify the swarm; the elitism selection strategy is used to enhance the convergence speed. The experimental results show that the HGWO method can produce better solutions than its original version in several test functions. Then, the HGWO method is applied to resolve the optimal operation of a real-world hydropower system with the goal of maximizing the total generation benefit. The simulations indicate that the HGWO method produces satisfying scheduling schemes than several control methods in terms of all the statistical indicators. Hence, with the merits of superior search ability, rapid convergence rate and gradient information avoidance, HGWO proves to be a promising alternative optimization tool for the complex multireservoir system operation problem.

Climate change impact on optimal reservoir operation and agricultural water allocation

Considering the need to supply water and food in future periods, this study assessed the effects of climate change on the water resource system of the Ballarood reservoir that located in the northwest of Khuzestan province, Iran. The outputs of ten general circulation models (GCMs) under two scenarios RCP8.5 and RCP4.5 have been used to simulate the effects of climate change. The results indicated an increase in average annual temperature by 2.34 (1.64)°C under RCP8.5 (RCP4.5). An increase in the amount of agricultural water requirement for downstream and decrease in the amount of runoff into the reservoir (31% under the RCP8.5 scenario and 11% under the RCP4.5) are other results of this study. Based on this results, the increase of vulnerability [46% (21%) under RCP8.5 (RCP4.5)] and decrease reliability [41% (18%) under RCP8.5 (RCP4.5)] of reservoir water supply system is simulated in the future period (2030-2055) relative to the basis period (1980-2005).

A Non-Deterministic Integrated Optimization Model with Risk Measure for Identifying Water Resources Management Strategy

Water resources system planning often exhibits high modeling error and uncertainty. Uncertainty in system parameters as well as their interrelationships can strengthen the conflict-laden issue of water allocation among competing interests. In this study, a non-deterministic integrated optimization model with risk measure is developed for planning water resources management. It can (i) deal with complex uncertainties described as probability distributions, fuzzy sets, and their combinations, (ii) provide an effective linkage between the predefined policies and the associated economic implications, and (iii) reflect policymakers’ preferences to the tradeoff between system benefit and economic loss. The developed model is then applied to planning water resources allocation of the Heshui River Basin (China), where 960 scenarios are analyzed under various uncertainty and risk measures. Results disclose that (i) not only uncertainties of fuzziness and randomness but also risk attitudes of decision makers have significant impacts on water-allocation scheme and system benefit; (ii) the selection of a suitable alternative among solutions under different I± , I¼ and I» values is complicated; (iii) water shortage would occur when water availability is less than the promised target; (iv) agriculture would encounter most serious scarcity compared to municipal and industry; (v) the conflict between economic development and agricultural sustainability would be a challenged issue that would enforce the local authority to adjust water-allocation policy. The findings can provide superior fundamental understanding of the study basin to improve water-allocation decisions under complex uncertain condition.

Climate change impact on optimal reservoir operation and agricultural water allocation

Considering the need to supply water and food in future periods, this study assessed the effects of climate change on the water resource system of the Ballarood reservoir that located in the northwest of Khuzestan province, Iran. The outputs of ten general circulation models (GCMs) under two scenarios RCP8.5 and RCP4.5 have been used to simulate the effects of climate change. The results indicated an increase in average annual temperature by 2.34 (1.64)°C under RCP8.5 (RCP4.5). An increase in the amount of agricultural water requirement for downstream and decrease in the amount of runoff into the reservoir (31% under the RCP8.5 scenario and 11% under the RCP4.5) are other results of this study. Based on this results, the increase of vulnerability [46% (21%) under RCP8.5 (RCP4.5)] and decrease reliability [41% (18%) under RCP8.5 (RCP4.5)] of reservoir water supply system is simulated in the future period (2030-2055) relative to the basis period (1980-2005).

Assessment of High Resolution Air Temperature Fields at Rocky Mountain National Park by Combining Scarce Point Measurements with Elevation and Remote Sensing Data

There is necessity of considering air temperature to simulate the hydrology and management within water resources systems. In many cases, a big issue is considering the scarcity of data due to poor accessibility and limited funds. This paper proposes a methodology to obtain high resolution air temperature fields by combining scarce point measurements with elevation data and land surface temperature (LST) data from remote sensing. The available station data (SNOTEL stations) are sparse at Rocky Mountain National Park, necessitating the inclusion of correlated and well-sampled variables to assess the spatial variability of air temperature. Different geostatistical approaches and weighted solutions thereof were employed to obtain air temperature fields. These estimates were compared with two relatively direct solutions, the LST (MODIS) and a lapse rate-based interpolation technique. The methodology was evaluated using data from different seasons. The performance of the techniques was assessed through a cross validation experiment. In both cases, the weighted kriging with external drift solution (considering LST and elevation) showed the best results, with a mean squared error of 3.7 and 3.6 °C2 for the application and validation, respectively.

Parallel computing and swarm intelligence based artificial intelligence model for multi-step-ahead hydrological time series prediction

Accurate future runoff prediction information is of great importance for the planning and management of both water resource and electric power systems. As employed to address the hydrological forecasting problem, artificial neural network (ANN) exhibits strong generalization and flexibility, but usually suffers from some shortcomings in practice, like unsatisfying learning efficiency and local convergence. The goal of this research is to develop a parallel computing and swarm intelligence based artificial neural network for multi-step-ahead hydrological time series prediction. Specially, the connection weights and biases of the ANN model are incrementally optimized via a parallelized particle swarm optimization obeying the Fork/Join framework, where the large-scale swarm is divided into a series of small and independent subswarms that will search for the optimal solution in the feasible space at the same time. The proposed method is driven to forecast the runoff time series of two real-world hydrological stations in China. The simulations indicate that the proposed method betters the conventional forecasting methods with respect to various indexes in different cases. For instance, in the 2-step-ahead case, the proposed method betters ANN with about 6.4 % improvement in the Nash-Sutcliffe efficiency value during the testing phase. Hence, the main contribution of this research is the utilization of swarm intelligence algorithm and high-performance parallel computing technique to improve the artificial intelligence model’s performances in time series forecasting.

Monthly Streamflow Forecasting Using Machine Learning

Streamflow forecasting holds a vital role in planning, design, and management of basin water resources. Accurate streamflow forecast provides a more efficient design of water resources systems technically and economically. In this study, various machine learning algorithms were used to model monthly streamflow data in the Coruh river basin, Turkey. For modeling, Support Vector Machines (SVM), Adaptive Boosting (AdaBoost), K-Nearest Neighbours (KNN) and Random Forest algorithms were considered and compared. Based on the test scores of the considered models with the hyperparameters, Random Forest based model outperforms all other models.

Simulation of the virtual water flow pattern associated with interprovincial grain trade and its impact on water resources stress in China

With fast development of economy and trade globalization, the water resources system has undergone profound changes due to the overconsumption of physical water and the complex virtual water flow. China is poor in water and rich in arable land for the north, but rich in water and poor in arable land for the south. The spatial mismatch of water and food production has posed a great threat to sustainable development. To quantify the virtual water flow with grain trade and evaluate its influence on the regional water resources system, this study simulated the interprovincial virtual water flow embedded in grain transportation based on a linear optimization model and assessed the water pressure induced by virtual water flow. Results show that the annual virtual water flow (as much as 73.46 billion m3 in 2012) associated with interprovincial grain trade is mainly from the North to the South. The grain output areas are mainly located in the Northeast, Northwest, and the North China Plain, while the grain input areas are mainly distributed in the eastern and southern coastal provinces with well-developed economies. According to the estimation, when China’s food demand reaches a peak of 650 million tons in 2030, the virtual water flow will further increase and the volume of virtual water flowing out of Northeast China will be up to 50 billion m3, accounting for 90% of the total virtual water flow. The increasing the virtual water outflow in North China will severely exceed the local water resources capacity in the arid and semi-arid areas and have an obvious negative impact on sustainable development in Northern China. Further improving the water use efficiency, adjusting the structure of spatial grain production distribution and physical-virtual water coupled management are effective countermeasures to ensure the coordination safety of food and water in China.

A re-look at canal irrigation system performance: a pilot study of the Sina irrigation system in Maharashtra, India

AbstractThe general perception of canal irrigation systems in India is one of built infrastructure with low service performance. This paper presents an analytical framework, applied to the Sina medium irrigation system in Maharashtra state of India, to study the performance of an expanded water influence zone (WIZ) including a buffer zone outside the canal command area (CCA) influenced by the irrigation system's water resources. The framework used satellite-based estimates of land-use and cropping patterns. The results indicate that there is hardly any gap between the irrigation potential created (IPC) and the irrigation potential utilized (IPU) in the CCA. The fraction of consumptive water use (CWU) of irrigation is low in the CCA, but almost one in the WIZ, due to the reuse of return flows in the WIZ. Future investments should focus on increasing economic water productivity ($/m3) in order to enhance the resilience of the farming community in the WIZ, which is frequently affected by water scarcity.

Study on Comprehensive Assessment of Water-Resource Safety Based on Improved TOPSIS Coupled with GA-BP

Xie, C.; Cao, J.; Chao, L., and Li, Y., 2020. Study on comprehensive assessment of water-resource safety based on improved TOPSIS coupled with GA-BP. In: Hu, C. and Cai, M. (eds.), Geo-informatics and Oceanography. Journal of Coastal Research, Special Issue No. 105, pp. 33–35. Coconut Creek (Florida), ISSN 0749-0208.The water-resources security evaluation index system is constructed from the coupling system of water resources–economic society–ecological environment. The absolute ideal point and the I-FAHP–improved constant TOPSIS method were used to avoid the reverse defect caused by the ideal solution and its weight change, so the comprehensive evaluation model of water-resources security based on the improved TOPSIS method was established. Finally, the improved TOPSIS and GA-BP neural network were effectively combined for training and testing. This evaluation model is applied to grade the water-resource security state of Hunan province from 2016 to 2019.The results show that the water-resource security in Hunan province from 2016 to 2019 is in a relatively stable state on the whole, belonging to the range of relatively safe state and critical safety state, and the level of safety state presents a trend of steady rise.

System dynamics simulation of regional water supply and demand using a food-energy-water nexus approach: Application to Qazvin Plain, Iran

Understanding the complexity and feedbacks among food, energy, and water (FEW) systems is key to making informed decisions about sustainable development. This paper presents qualitative representation and quantitative system dynamics simulation of the water resources system in the Qazvin Plain, Iran, taking into account the energy intensity of water supply and interconnected water use sectors (e.g., urban, industrial, and agricultural). Qazvin Plain faces water resources challenges that are common to arid/semi-arid areas, including frequent droughts, declining surface water and groundwater, and increased urban and agricultural water demand. A system dynamics model is developed using historical data (2006–2016) to investigate the effects of anticipated dynamics of integrated water and energy sectors in the next two decades. The results of policy scenarios (2020–2039) demonstrate that the continuation of the existing management policies will cause severe damage to the water and energy sectors, pushing the system towards water resources limits to growth. An annual groundwater table decline of nearly 1 m is anticipated, indicating significant overshoot of the plain's natural recharge capacity, which may lead to the depletion of recoverable groundwater in the plain within the next three decades. The groundwater table decline will cause energy consumption of water supply to increase by about 32% (i.e., 380 GWh) to maintain irrigated agriculture. It is critical to implement a combination of water demand and supply management policies (e.g., net agricultural water savings and recycling treated wastewater) to delay the problem of water limits to growth in the region.

Development tendency analysis for the water resource carrying capacity based on system dynamics model and the improved fuzzy comprehensive evaluation method in the Changchun city, China

Water resource carrying capacity describes the relationship between different systems such as the socio-economic, water environment, and water resources systems. Recent studies tend to focus on the qualitative description of water resource carrying capacity, with a lack of quantitative research on the topic. This study proposes an improved water resource carrying capacity assessment method based on combining the improved fuzzy comprehensive evaluation and the system dynamics model, enabling the quantitative and qualitative measurement of water resource carrying capacity. This method can dynamically compute the water resource carrying capacity under different social development scenarios through the feedback regulation and system simulation of social economy–water resources and the water environment interactions. A comprehensive assessment of trends from six scenarios between 2018 and 2025 was conducted, based on scenarios designed for different purposes. The results indicate that if the current development model is adopted, the water resource carrying capacity will continue to decline and remain at a low level of “normal carrying” (0.431 in 2025). However, the water resource carrying capacity in Changchun may improve by changing the production mode of the national economy and adjusting the proportion of the economy. Rationally allocating water resources and strengthening water ecological protections can significantly increase the water resource carrying capacity and maintain it at “positive carrying”, while maintaining steady economic and social growth.

Spatiotemporal Analysis of Hydrological Variations and Their Impacts on Vegetation in Semiarid Areas from Multiple Satellite Data

Understanding the spatiotemporal characteristics of hydrological components and their impacts on vegetation are critical for comprehending hydrological, climatological, and ecological processes under environmental change and solving future water management challenges. Innovative methods need to be developed in semiarid areas to analyze the special hydrological factors in the water resource systems of these areas. Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) were applied with the normalized difference vegetation index (NDVI) data in this paper to analyze spatiotemporal changes of hydrological factors in the Xiliaohe River Basin (XRB). The results showed that precipitation (P), evapotranspiration (ET) and temperature (T) had similar seasonal change patterns at rates of 0.05 cm/yr., 0.01 cm/yr. and −0.05 °C/yr., respectively. Total water storage change (TWSC) was consistent with the change trend of soil moisture change (SMC) and showed a fluctuating trend. Groundwater change (GWC) showed a decreasing trend at a rate of −0.43 cm/yr. P and ET had a greater impact on GLDAS data (R = 0.634, P < 0.05 and R = 0.686, P < 0.01, respectively) than on other factors. GWC was more sensitive to changes in T (R = 0.570, P < 0.05). Furthermore, a lag period of 0 to 1 months was observed for the effects of P and ET on TWSC and GLDAS. NDVI showed an upward trend at a rate of 0.001 yr−1 between 2002 and 2014. A spatial distribution of NDVI was heterogeneous in the study area. ET, GLDAS and GWC in growing season limited vegetation growth and were more important than other factors in XRB. The results may contribute to an understanding of the relationships between the hydrological cycle and climate change and provide scientific support for local environmental management.

Study on mechanism and application of water resources system adaptability under changing environment

Abstract The water resources system is in a vulnerable situation because of the influence of climate change and the changing environment. The adaptation mechanism was discussed through the analysis of the process of passive response, adaptation and even active adjustment of water resources system under changing environment. The adaptability of the water resources system can be described as natural resilience (NR) of natural system and artificial adaptation (AA) social (artificial) system. The natural resilience indexes were identified and analyzed from the aspects of water quantity, water quality and water ecology. The artificial adaptation indexes were identified and analyzed from the aspects of resource, eco-environment, socio-economic and technical factors. On this basis, the index system was constructed in accord with process mechanism of water resources system adaptability. Besides, to address the two-dimension factors of water resources system adaptability, a method of system analysis based on connection numbers–fuzzy risk matrix was proposed based on the theory of risk matrix. The synthesis interval [Apess, Aopt] of water resources system adaptability is obtained, by defining the pessimistic criterion when two-dimension factors meet the evaluation standard at the same time, and the optimistic criterion when either of the two-dimension factors meets evaluation standard. Finally, the case study in the Huaihe River basin in China was carried out. The results show that the adaptability level of water resources system in the Huaihe River basin expressed fluctuating uprising tendency in 2006–2015. The adaptability level is the lowest [1.856, 2.625] in 2009, the highest [2.500, 3.536] in 2015.

Identifying critical climate conditions for use in scenario-neutral climate impact assessments

Scenario-neutral climate impact assessments are being used increasingly to assess water resource system responses to possible climate changes. The purpose of such assessments is to identify system sensitivity to a range of plausible climate conditions, often including an evaluation of the joint effect of multiple climate stressors. Given the large number of climate variables and associated statistics (averages, seasonality, intermittency, extremes, etc.) that could plausibly change and impact on system performance, it is essential that scenario-neutral assessments focus on those to which the system is most sensitive. A generic approach to identifying these ‘critical’ climate conditions is presented and tested on the Lake Como reservoir in Northern Italy considering two system objectives: irrigation deficit and flood reliability. Results indicate that different climate conditions are critical for the two objectives, and that the choice of which climate conditions to include has a significant effect on the climate impact assessment outcome.

Identification of Seasonal Sub-Regions of the Drought in the North China Plain

Regional climate variability assessment is of great significance in decision-making such as agriculture and water resources system management. The identification of sub-regions with similar drought variability can provide a basis for agricultural disaster reduction planning and water resource distribution. In this research, a modified daily Standardized Precipitation Evapotranspiration Index (SPEI) was used to monitor the spatial and temporal variation characteristics of agricultural drought in the North China Plain from 1960 to 2017, which was studied by using the rotated empirical orthogonal functions (REOF). Through the seasonal REOF process, 7–9 seasonal drought sub-regions are confirmed by applying time series and the correlation relationship of SPEI original data. The strong correlation of these sub-regions indicates that the climate and weather conditions causing the drought are consistent and the drought conditions are independent for the regions that show no correlation. In general, the results of the seasonal trend analysis show that there has been no significant trend value in most areas since 1960. However, it is worth noting that some regions have the positive and negative temporal trends in different seasons. These results illustrate the importance of seasonal analysis, particularly for agro-ecosystems that depend on timely rainfall during different growing seasons. If this trend continues, seasonal drought will become more complex, then a more elaborate water management strategy will be needed to reduce its impact.