Water Resources Systems Research Articles

Impact of Climate Change on Integrated Management of Water Resources in The lower Basin of Diyala River, Iraq

Climate change could affect the world's water resources system, especially at the level of the basin. Climate change would impact streamflow and corresponding future water resources. The lower basin of the Diyala River is currently experiencing water shortage and contamination issues. This study aims to use Water Evaluation And Planning (WEAP) model to create an integrated modeling system for evaluating the effects of climate change on water supply and demand within the lower Diyala River basin. The WEAP model was calibrated and verified employing monthly streamflow data from the Diyala River outflow station. Following that, the calibrated model was loaded with various future scenarios ranging from 2020-2045. Future scenarios used included the reference scenario, the high population growth rate scenario, and the climate change scenario. The results indicated that the WEAP model accurately predicted the basin's water supply and demand, with RMSE, NSE, and R² values of 0.85, 0.91, and 0.867, respectively, throughout the validation period. Furthermore, Water demand and supply were found to be unmet in all projected future scenarios, showing that sustainable water management in the lower basin of the Diyala River is highly required.

Fundamentals of Climatology for Engineers: Lecture Note

The study of climatology serves as a foundation for students who wish to specialize in water resources, hydrology, or environmental engineering. Climatology is the study of long-term average weather patterns. It is a distinct field of study from meteorology and is subdivided into a number of subfields. In order to predict the future hydrologic and hydraulic scenarios, knowledge of climatology is essential. In other words, climatology allows us to determine the likelihood of snowfall and hail, the amount of solar thermal radiation that can reach a specific location, etc. Climatology focuses frequently on how the climate has changed over time and how these changes have affected people and events. The primary objective of this technical note is to acquaint and encourage engineers with the basics of the climate and its processes so that they can understand the climatic impact on water resource systems as beginners.

Coupled coordination of water resources–economy–ecosystem complex in the Henan section of the Yellow River basin

Abstract This study investigates the coordination of factors in the three coupled systems of water resources, economy and ecosystem. The study data were economic, social, environmental and water resource indicators of the Henan section of the Yellow River basin from 2000 to 2019. Data were analyzed using a model of coupling coordination, grey relational analysis and a combined sparrow search algorithm–back propagation (SSA-BP) prediction model. Evaluation, analysis and prediction of the water resources–economy–ecosystem complex were undertaken. The results show that: (1) the degree of coupling coordination of the water resources–economy–ecosystem complex in the Henan section of the Yellow River basin showed an increasing trend that reached 0.8105 in 2019, which indicates good coordination; (2) the water resources subsystem had the greatest influence on the overall degree of coupling coordination, followed by the economic and natural environment subsystems; and (3) the SSA-BP model predicted that the degree of coupling coordination would remain good for the next six years and reach 0.8333 in 2025. To ensure the sustainability of expected rapid economic development, Henan Province must increase the utilization efficiency of water resources, strengthen environmental protection, and coordinate development in the region.

Prospective of the utilization of rainfall in coastal regions in the context of climatic changes: case study of Egypt

Changes in climate drivers are projected to have a considerable impact on coastal freshwater supply and demand systems in future decades. The utilization of rainfall in coastal regions to secure sufficient freshwater to satisfy the rising demands of socioeconomic development has become a critical duty for decision-makers. This article assesses the present state of rainwater utilization in the water resources system for the coastal regions in Egypt. Volumes of annual rainfall that precipitate in 11 coastal Egyptian cities are estimated using ArcGIS maps and the run off rational equation. A future vision of using the estimated rainwater harvesting (RWH) from urban coastal cities in the water resources system is presented. Several scenarios are suggested and analyzed for using these volumes of water in the total water resources system in Egypt and also in the water resources system corresponding to each selected coastal governorate. The results indicated that over the areas under consideration, the annual maximum total amount of precipitation is limited to 1.8 km3. However, it is anticipated that 1 km3 of the average annual quantity of rainfall water is efficiently used for agriculture. These findings are intended to help managers, planners, and decision-makers to choose locations, invest in water resources, and employ RWH as a substitute for traditional water sources.

A spatial agent-based model for hydraulic fracturing water distribution

Agent-based modeling (ABM) has been employed to understand and capture the complexity of the coupled human-nature processes in water resource systems. One of the challenges is to model human decisions in the coupled human and natural systems. Hydraulic fracturing water uses were distributed through a depot-based water allocation system in the Bakken region of western North Dakota, United States. In this study, a spatially explicit ABM was developed to simulate this unique water allocation system. In the ABM, institution theory was used to model the State’s regulatory policies and procedures, while evolutionary programming was employed to allow the water-depot owners (or agents) to select appropriate strategies when applying for water permits. Cognitive maps simulated the water-depot agents’ ability and willingness to compete for more water sales. All agents had their influence boundaries that restricted their competitive behavior toward their neighbors, but not for non-neighboring agents. The decision-making process was constructed and parameterized with both quantitative and qualitative information. The ABM was calibrated against real-world water-use data, and the calibration results showed that the spatial ABM performed well in simulating the total number of water depots as well as the locations and water uses of water depots at the county level. By linking institution theory, evolutionary programming, and cognitive maps, our study exhibited a new exploration of modeling the highly complex dynamics of the decision-making process involved in coupled human-nature water resource systems.

Pathways of carbon emissions reduction under the water-energy constraint: A case study of Beijing in China

China is striving for carbon peak before 2030 and carbon neutrality before 2060 (“Dual Carbon” strategy). Dual Carbon strategy is a complex systematic work involving the whole society, particularly the energy system and water resources system, and cities play a key role in the strategy. Using LEAP-WEAP-Beijing model, this paper examines the pathways of carbon emissions reduction for 2020–2030 under the water-energy constraint in Beijing. It is found that Beijing has large potential to reduce carbon emissions, and that the deployment of local gas-fired power has the greatest emissions reduction effect. Nevertheless, it is not advisable to prioritize local gas-fired power as it would undermine the water resources security. Instead, renewable energy deployment and optimization of imported power structure should be prioritized. Further, it is not appropriate to eliminate conventional energy sources at an early stage as diversification of energy sources is the guarantee of energy security. On the energy consumption side, although electrification is recognized as an important measure to reduce emissions, it should be pushed forward in a stepwise way. Partial electrification is the optimal pathway in terms of both emissions reduction and energy security level. Building on these findings, specific recommendations to policy makers are provided.

Spatiotemporal Patterns of Extreme Precipitation Events over Jhelum River Basin

Climate change has a wide range of impacts on Pakistan’s water resources system, followed by increased magnitude, frequency and intensity of extreme events. Therefore, investigating the variations in extreme climatic events is vital in planning and developing agriculture and water conservation projects. Hence, the present study investigated the spatiotemporal variability of extreme precipitation indices (EPIs) over the Jhelum River basin (JRB) using the Mann-Kendall (MK) and innovative trend analysis (ITA) methods. In addition, variations in the event-based extreme precipitation (EEPs) and time distribution patterns (TDPs) were analyzed because EPIs considered the daily precipitation values only and the combined effect of the extreme events that last for more than 1 day were often neglected. The results show that the fixed and station-related EPIs, i.e., R10, R20, R25, CWD, Prcpt and R95p, exhibited significant decreasing trends at 06, 05, 04, 04, 07 and 05 stations, whereas an increasing trend was evident for consecutive dry days (CDD) at nine stations with a magnitude of 0.33 days/year, indicating a rise in the drought events compared to floods. Moreover, precipitation events with an amount of 40–290 mm, duration of 4–7 days and concentration ratio of 0.7–0.95 were found to be dominant across JRB. Therefore, an increase in the CDD and a decrease in the consecutive wet days (CWD) may change the magnitude, intensity and frequency of extreme precipitation events and consequently pressure the availability of water resources. Therefore, the findings of this study may help understand the precipitation variability over JRB and play a pivotal role in future development projects.

Agricultural Productive Carrying Capacity Improve and Water Optimal Allocation under Uncertainty Based on Remote Sensing Data in Lancang County, Southwest China

Through the reasonable calculation of water resources, evaluating the irrigation carrying capacity of farmland under the constraints of water resources is crucial for optimizing the spatial distribution of agricultural production and ecology and rationally adjusting the scale of agricultural production. This paper proposes an optimization framework based on Type 2 fuzzy chance-constrained programming (T2FCCP) to solve the problem of regional water resources optimal allocation and evaluation of farmland irrigation carrying capacity under uncertain conditions. To illustrate the applicability of the proposed framework, this paper conducts a case study on Lancang County, Puer City, Yunnan Province. Methods, such as watershed harmony evaluation method, remote sensing data, and shared socioeconomic pathways (SSPs), are applied and integrated into the proposed optimization framework to systematically deal with uncertainties in water resource systems and agricultural systems. The results include the costs and benefits of regional water and soil resources systems, water resources optimal allocation, and crop planting structure results under different SSPs in Lancang County, Puer City. The results also show that the total cost under T2FCCP is about 5% lower than that under fuzzy chance-constrained programming (FCCP) and about 17% lower than that under chance-constrained programming (CCP). By 2025, the water resources carrying capacity of different tributaries in Lancang County, Puer City will increase, and based on the evaluation results of agricultural production irrigation carrying capacity, suggestions are given to ensure agricultural production carrying capacity.

Development of wavelet-based Kalman Online Sequential Extreme Learning Machine optimized with Boruta-Random Forest for drought index forecasting

Drought is a stochastic and recurring hydrological natural hazard that occurs due to a shortage of precipitation over a period of time. Drought forecasting in water resources systems has an important role in reducing devastating ecological and social impacts. However, due to the fluctuating nature of drought indicator time series, their forecasting on a short time scale without advanced pre-processing is extremely challenging, and little research has been presented in this field. In this study, a new complementary machine learning (ML) approach, Kalman filter regression-based Online Sequential Extreme Learning Machine and (KOSELM) coupled with the Boundary Corrected Maximal Overlap Discrete Wavelet Transform (BC-MODWT-KOSELM), was implemented for forecasting one-month/three-month ahead Standardized Precipitation Evapotranspiration Index (i.e., SPEI 12 and SPEI 24). Here, the Kalman filter regression was employed to optimize the hyper-parameters of the Online Sequential Extreme Learning Machine (OSELM). Precipitation and potential evapotranspiration data from Bandar Abbas (warm semi-humid climate) and Rasmar (humid climate) synoptic stations, Iran were used in the analysis for a period of (1987–2019). In order to validate the BC-MODWT-KOSELM model, it was compared with two other well-known ML approaches, classical Extreme Learning Machine (ELM) and Generalized Regression Neural Network (GRNN) in both standalone and BC-MODWT-based complementary frameworks (i.e., BC-MODWT-ELM and BC-MODWT-GRNN). First, the original time series of the benchmark drought index was decomposed into the wavelet and scaling coefficients based on three mother wavelets and different decomposition levels. Afterward, the most significant lags were extracted using the Boruta-random forest (B-RF) feature selection. The BC-MODWT-KOSELM was identified as the superior forecasting model for SPEI 12 (t ＋ 1) with R = 0.9511 and RMSE = 0.3318; for SPEI 12 (t ＋ 3) with R = 0.8171 and RMSE = 0.6168; for SPEI 24 (t ＋ 1) with R = 0.9710 and RMSE = 0.2156; for SPEI 24 (t ＋ 3) with R = 0.9014 and RMSE = 0.3937 in the Bandar Abbas station. Besides, the BC-MODWT-KOSELM outperformed the comparative counterpart model for SPEI 12 (t ＋ 1 with R = 0.9401 and RMSE = 0.3371; SPEI 12 (t ＋ 3) with R = 0.8266 and RMSE = 0.5723; for SPEI 24 (t ＋ 1) with R = 0.9640 and RMSE = 0.2974; for SPEI 24 (t ＋ 3) with R = 0.9063 and RMSE = 0.4874 in the Ramsar station.

Kızılırmak Havzasında Hidrolik Yapıların Planlanmasında Nehir Akımlarının Mevsimselliğinin Belirlenmesi

The demand for water resources is increasing day by day due to the rapid increase in the world population, drought caused by industrialization, urbanization and global climate change. The efficient use of water resources depends on the correct planning and operation of the water resources systems of the future. The seasonality analysis is to reveal the similarities between the hydrological characteristics of the currents regionally. Examining the seasonality of river flow data is essential for the correct design and efficient operation of the hydraulic structures to be designed. In this study; the seasonal similarity of low and high stream flows throughout the year was determined by using the daily flow data of 5 flow streamflow gauging stations selected at certain geographical points of the Kızılırmak basin. The similarity of the basins was determined by using the seasonal statistics calculated and the direction of the average occurrence dates for each station. This observed similarity was also associated with the hydrological similarity between stations and the hydrological characteristics of the basins were found.

Strategic analysis of the drought resilience of water supply systems

Severe droughts can result in shortages of water supplies, with widespread social and economic consequences. Here we use a coupled simulation model to assess the reliability of public water supplies in England, in the context of changing scenarios of water demand, water regulation and climate change. The coupled simulation model combines climate simulations, a national-scale hydrological model and a national-scale water resource systems model to demonstrate how extreme meteorological droughts translate into hydrological droughts and water shortages for water users. We use this model to explore the effectiveness of strategic water resource options that are being planned in England to secure water supplies to most of England's population up to a drought return period of 1 in 500 years. We conclude that it is possible to achieve a 1-in-500-years standard in locations where strategic resource options are used, while also reducing water abstraction to restore the aquatic environment. However, the target will be easier to achieve if effective steps are also taken to reduce water demand.This article is part of the Royal Society Science+ meeting issue ‘Drought risk in the Anthropocene’.

Multi-objective Optimization of water resources in real time based on integration of NSGA-II and support vector machines.

One of the management strategies of water resources systems is the combination of simulation and optimization models to achieve the optimal policies of reservoir operation in the form of specific optimization. This study utilizes an integration of the NSGA-II multi-objective algorithm and WEAP simulator model so that the first objective is to maximize the reliability of providing the needs in front of the second goal, i.e., to minimize the drawdown the water table at the end of the operation time. The dam rule curve or the amount of released volume from the reservoir is optimized to supply downstream uses in these conditions. However, in certain optimizations, the optimal solutions cannot be generalized to other possible inputs to the reservoir, and if the inflow to the reservoirs changes, the obtained optimal solutions are no longer efficient and the system must be re-optimized in the form of an optimizer algorithm. Therefore, to solve this problem, a new method is extended on the basis of the combination of the support vector machine and NSGA-II algorithm for optimal real-time operation of the system. The results demonstrate that the average error rate of optimal rules derived from support vector machines is less than 2.5% compared to the output of the NSGA-II algorithm in the verification step, which indicates the efficiency of this method in predicting the optimal pattern of the dam rule curve in real time. In this structure, based on the inflow to the reservoir, the volume of water storage in the reservoir and changes in the reservoir storage (at the beginning of the month) and the downstream demands of the current month, the optimal release amount can be achieved in real time. Therefore, the developed support vector machine has the ability to provide optimal operation policies based on new data of the inflow to the dam in a way that allows us optimally manage the system in real time.

Evaluate cities' urban water resources system resilience along a river and identify its critical driving factors.

The emergence of a series of problems, such as serious water environment pollution and flood disasters, leads to an increase in an urban water resources system's vulnerability and pressure. In order to alleviate an urban water resources crisis, calculating the water resources system resilience (WRSR) and identifying its impact factors are essential. This paper constructed a resilience evaluation framework of the "Economy-Social Development-Infrastructure-Water Resources-Ecological Environment" water resources system from three stages, i.e. resistance, restoration and adaptability. Then, taking 21 cities along the Yangtze River Economic Belt's lower reaches (YREB's lower reaches) as an example, we scientifically measured the WRSR by using the Projection Pursuit Evaluation Model of Real Coding based on the Accelerating Genetic Algorithm (RAGA-PP) and analyzed its driving factors with Geographic Detectors (GD). (1) From 2010 to 2018, the overall level of the WRSR along the YREB's lower reaches was low, and it was characterized by attenuation from central cities to marginal cities; Suzhou had the highest average WRSR (0.656), while Chizhou had the lowest (0.207). (2) From stage characteristics, compared with 2010, resistance and restoration of most cities along the YREB's lower reaches showed an upward trend in 2018; however, the adaptability level of some cities was still low. From the perspective of sub-system resilience, resilience levels of different sub-systems in each urban water resources system (UWRS) were different. (3) For impact factors, average factor interpretations of per capita GDP, average wages of employees and affected areas of floods, geological disasters and typhoons were largest. Based on this, this paper provides relevant suggestions for improving the WRSR along the YREB's lower reaches to improve ability of UWRS to resist external risks.

Habitat alteration assessment for the management of environmental flows in regulated basins.

The management of environmental flows is of paramount importance in regulated water resources systems to preserve river ecosystems. This work proposes a methodology to assess habitat alteration in river basins altered by management activities. The methodology is based on the joint application of a basin management model (SIMGES, AQUATOOL) and a model to estimate habitat time series (CAUDECO). CAUDECO is based on the weighted useable areas of the species in their different vital stages that, in turn, depend on the flows in each river stretch and the biological periods of the species. The final output is an indicator of habitat alteration, which is defined ad hoc for this work to relate the habitat suitability under regulated and natural regimes. The methodology was applied to a case study in north-western Spain: the Órbigo River basin. The results in the current management scenario highlight that the ecological flows improve the habitat suitability of several species with respect to natural regime conditions. For instance, the mean values of the habitat time series in the Órbigo River for the brown trout and bermejuela under regulated conditions are 69.6% and 88%; whereas in natural regime they are equal to 55.1% and 72.9%, respectively. Based on these results, eight additional scenarios of ecological flows were tested and their effects on both habitat alteration and water demand reliability were quantified and discussed. It was found that increases in the ecological flows up to 30% do not affect the reliability of water demands and reduce habitat alteration (i.e., lead to values of the habitat alteration indicator closer to 1) for all species present in the river basin. These results highlight that the methodology and indicator of habitat alteration proposed in this paper are useful to support the management of regulated river basins, since they allow assessing the implications of ecological flows on both habitat suitability and reliability of water demands.

Analysis on competition strategy and regulatory strategy of international river water resources system – with the participation of co-operational agencies

Abstract In order to reasonably allocate water resources, meet the water demand of water users, and solve the frequent conflicts of water resources in international rivers, this paper explores the optimal regulation strategy of water resources with the participation of co-operational agency based on game model. Our results show that: for water users, the regulatory strategy of co-operational agencies affects the competition of water users, and the competition strategies among water users also affect each other. The economic benefits of water resources, water withdrawal costs, fine and honor value all affect the water resources competition strategy of water users. For co-operational agencies, the competition strategy of water users affects the regulatory strategy of co-operational agencies. The intensity of penalization and the regulatory cost have an impact on the regulatory strategy of co-operational agencies, but the amount of operation funds of co-operational agencies does not affect its regulatory strategy. The research shows the water resources game process of international rivers with the participation of co-operational agencies, and provides some insights for the water resources regulation of international rivers.

Coupling Relationship and Influencing Factors of the Water–Energy–Cotton System in Tarim River Basin

As the largest inland river basin in China, the Tarim River Basin is an important energy base and a key cotton-producing area in China. Therefore, the harmonious development of water resources, energy resources and cotton resources in the Tarim River Basin is a lifeline for stable quality and efficient development in this region. In this paper, the water–energy–cotton system of the Tarim River Basin is constructed and the weight of each index in the system is determined by using the entropy method. On this basis, the comprehensive development index of each subsystem and the water–energy–cotton system is calculated to measure the comprehensive development level of each system. Then, the coupling relationship between the three resources is quantitatively analyzed by using the coupling coordination degree model, and the mutual influence and strength of interaction between each system are calculated. Finally, a fractional regression model is established to analyze the factors affecting the coordinated development of the water–energy–cotton system in the Tarim River Basin. The results show that the comprehensive development index of the Tarim River Basin fluctuates obviously and the comprehensive development level of water resource systems is higher than that of the cotton resource and energy resource systems, and there are regional differences between each subsystem and the comprehensive development index of water–energy–cotton system. The coupling coordination degree of the basin is the primary coordination on the whole; however, there are significant differences in the coupling coordination degree of each region. In terms of influencing factors, the area of soil erosion treatment and water consumption in ecological environments both play a positive role in promoting the coupling coordination degree, and population size and GDP will hinder the development of the coupling coordination degree to a certain extent.

Simulation of the Water Demand in 2050 in the Lobo Watershed in Nibéhibé (Central-Western Cote d’Ivoire): Application of the WEAP Model

Due to climate change, which has caused the scarcity of rainfall and the depletion of water resources in recent decades, Côte d'Ivoire has embarked on a planning program for the integrated management of its water resources. The present study is carried out on the Lobo watershed in Nibéhibé, located in the western part of Côte d'Ivoire (between 6°17' and 6°44' W longitude and between 6°46' and 7°41' N latitude). Indeed, the multisectoral use, the impact of climate, the demographic growth on water resources as well as the uncoordinated management lead to a crucial water shortage in the basin. The objective of this study is to propose optimization scenarios for the use of water resources for planning and sustainable management. To this end, field surveys were carried out among the state structures and the populations of the basin to acquire the socio-economic data necessary for the simulation of future water demand. The product of the specific consumptions by the levels of activities allowed to estimate the needs by sectors of activities (water supply, agriculture, and breeding) and consequently the global needs of the basin in 2021. The Water Evaluation And Planning (WEAP) model, which is a water resources management tool, was used to simulate the future water demand of the basin under different scenarios. The results show that the water demand for 2021 is 30 180 588 m3. The water demands by 2050 under the reference, low population growth rate, high population growth rate, improved standard of living and climate change scenarios are 83,700,000 m3; 57,700,000 m3; 114,100,000 m3; 107,600,000 m3 and 114,100,000 m3 respectively. As a result, the unsatisfied water demands for the same scenarios are 23,700,000 m3; 10,700,000 m3; 38,600,000 m3; 34,300,000 m3 and 38,600,000 m3 respectively. The reduction of these unsatisfied demands for the well-being of the basin populations requires the implementation of planning and integrated management systems of the basin water resources through optimization scenarios.

Forecasting Hourly Intermittent Rainfall by Deep Belief Networks with Simple Exponential Smoothing

Accurate rainfall forecasting is essential in planning and managing water resource systems efficiently. However, intermittent rainfall patterns increase the difficulty of accurately forecasting rainfall values. Deep learning techniques have recently been popular and powerful in forecasting. Thus, this study employed deep belief networks with a simple exponential smoothing procedure (DBNSES) to forecast hourly intermittent rainfall values in Taiwan. Weather factors were used as independent variables to forecast rainfall volume. The simple exponential smoothing data preprocessing procedure was used to deal with the intermittent data patterns. The other three forecasting models, namely the least squares support vector regression (LSSVR), the generalized regression neural network (GRNN), and the backpropagation neural network (BPNN), were employed to forecast rainfall using the same data sets. In addition, genetic algorithms were utilized to determine the parameters of four forecasting models. The empirical results indicate that the developed DBNSES models are superior to the other forecasting models in terms of forecasting accuracy. In addition, the DBNSES can obtain smaller values of RMSE than those in the previous studies. Therefore, the DBNSES model is a suitable and effective way of forecasting rainfall with intermittent data patterns.

Development and comparison of artificial intelligence models for estimating daily reference evapotranspiration from limited input variables

The accurate and efficient computational modelling framework for computation of reference evapotranspiration (ET0) is the need of time and is highly essential for several agricultural, hydrological and hydro-climatological studies and applications. ET0 has its own role especially for the water resource system management including irrigation water allocation and management, utilization and demand assessments of water resources. Considering the potential and wide applicability of Artificial Intelligence (AI) models in input-output mapping, these were examined in this research for modelling ET0 utilising a variety of meteorological data, including maximum temperature (Tmax) and minimum temperature (Tmin), relative humidity (RH), wind speed (WS), and bright sunshine hours (BSS). The different AI models investigated in this study include Artificial Neural Network (ANN), Extreme Learning Machine (ELM), M5 Tree and Multiple Linear Regression (MLR). The implemented daily dataset was collected from the Sardarkrushinagar station which is located at the North Gujarat region of India. For performance verification of the developed AI models, the FAO-56 Penman-Monteith equation was employed as a benchmark. The developed model's accuracy was assessed using multiple quantitative metrics, including R2, NSE, RMSE, Pdv and MAE. The performance of ANN models was found better compared to the ELM, M5 Tree, and MLR models in terms of different performance indicators. The model's outcomes were highly practical and reliable for the investigated case studies. Another important finding in this research was that the selection of the appropriate input variables in models allows not only error minimization but also enhances the co-relationship amongst the dependant as well as independent variables.

Eutopian and Dystopian Water Resource Systems Design and Operation—Three Irish Case Studies

The Harvard Water Program is more than sixty years old. It was directed by an academic Steering Committee consisting of the professors of Government and Political Science, Planning, Economics, and Water Engineering. In 2022 we would add to the notional Steering Committee the professors of Ecology, Sociology and Water Law, calling it the augmented Harvard eutopian approach to the design and operation of Water Resource Systems. We use the Greek word ‘eu-topos’ to mean ‘a good place’, figuratively speaking, and ‘dys-topos’ its antonym, ‘not a good place’. By opposing eutopia and dystopia (latin forms) (Utopian literature begins with Thomas More’s (1478–1535) fictional socio-political satire “Utopia”, written in Latin and published in 1516: “Libellus vere aureus, nec minus salutaris quam festivus, de optimo rei publicae statu deque nova insula Utopia”. “A little, true book, not less beneficial than enjoyable, about how things should be in a state and about the new island Utopia” [Wikipedia translation]. He coined the word ‘utopia’ from the Greek ou-topos meaning ‘no place’ or ‘nowhere’. It was a pun-the almost identical Greek word eu-topos means ‘a good place’), we pass judgement on three Irish case studies, in whole and in part. The first case study deals with the dystopian measurement of the land phase of the hydrological cycle. The system components are distributed among many government departments that see little need to cooperate, leading to proposition 1: A call for a new Water Law. The second case study deals with a project to restore a 200 km2 polder landscape to its condition in 1957. The project came to the University with an hypothetical cause of the increased flooding and a tentative solution: dredge the Cashen estuary of its sand, speeding the flow of sluiced water to the sea, and the status quo ante would be restored. The first scientific innovation was the proof that restoration by dredging is impossible. Pumping is the only solution, but it raises disruptive questions that are not covered by Statute. The second important innovation was the discovery in the dynamic water balance, of large leakage into the polders, either around or between sluiced culverts, when the flap valves are nominally closed, impacting both their maintenance and minimization of pumping. Discussions on our findings ended in dystopian silence. Hence proposition 2: Moving towards eutopia may only be possible with a change in the Law. The third case study concerns the protection of Cork City from flooding: riverine, tidal and groundwater. The government’s “emerging solution” consists of major physical intervention in the city centre, driven hard against local opposition, as the only possible solution. Two hydro-electric reservoirs upstream were largely ignored as part of a solution because the relevant Statute did not mandate their use for flood control. The Supreme Court has recently overturned this interpretation of the governing Statute. A new theory of flood control with a cascade of reservoirs, dams and weirs is the scientific innovation here. Once more these findings have been greeted by government with dystopian silence. Hence proposition 3: Re-open the design process to find several much better solutions, approximating a eutopian water world.