Operational Water Resources Management Research Articles

Towards Informed Water Resources Planning and Management

In Water Resources Planning and Management, decision makers, although unsure of future outcomes, must take the most reliable and assuring decisions. Deterministic and probabilistic prediction techniques, combined with optimization tools, have been widely used to meet the objective of improving planning as well as management. Bayesian decision approaches are available to link probabilistic predictions to optimized decision schemes, but scientists are not fully able to express themselves in a language familiar to decision makers, who fear basing their decisions on “uncertain” forecasts in the vain belief that deterministic forecasts are more informative and reliable. This situation is even worse in the case of climate change projections, which bring additional degrees of uncertainty into the picture. Therefore, a need emerges to create a common approach and means of communication between scientists, who deal with optimization tools, probabilistic predictions and long-term projections, and operational decision makers, who must be facilitated in understanding, accepting, and acknowledging the benefits arising from operational water resources management based on probabilistic predictions and projections. Our aim here was to formulate the terms of the problem and the rationale for explaining and involving decision makers with the final objective of using probabilistic predictions/projections in their decision-making processes.

System model of integrated management of the water resources of the Ingulets River by a basin principal

For integrated water management in river basins in Ukraine, there is no toolkit for system modeling and selection of management structure in river basins according to environmental and economic criteria, which corresponds to the creation of water management systems under conditions of sustainable development. Therefore, the urgent task is to develop a system model of integrated water management on the example of the Ingulets River basin.
 The purpose of the work is to create a system model of integrated water resources management in Ingulets River basin, which provides scenario modeling of technological solutions, their evaluation and optimization of economic criteria for efficient water use under environmental constraints and criteria for achieving a good or excellent ecological status of the river basin.
 The system model is used as a toolkit, the method of decomposition of the river basin into subsystems, analysis of subsystems and their composition into a holistic model of integrated management by the basin principle. Telecommunication methods are proposed to improve monitoring. A method of scenario analysis is proposed, which performs simulation modeling of prospective management scenarios at the first level of the hierarchy, and at the second level - options are evaluated according to the criteria of cost-effective water use with environmental objectives and regulatory restrictions. For simulation modeling, a system of balance difference equations for the dynamics of water masses, mixing and spreading of pollution in rivers and reservoirs is formalized. A system of combined control for the impulse method of river washing was developed. Multicriteria optimization of variants of the control structure is carried out on the Pareto principle.
 A system model has been developed for integrated water resources management in the Ingulets River basin that meets the requirements of the EU Water Framework Directive on the establishment of cost-effective water use while ensuring good or excellent ecological status of rivers. The structural and functional diagram of the system model includes the subsystems: the water supply subsystem of the Dnipro-Ingulets canal; a subsystem for flushing the Ingulets River from the Karachunivske reservoir and displacing the saline prism into the Dnipro River; subsystem of environmental safety when discharging pollution into the river Ingulets; subsystem of water supply for irrigation in the Ingulets irrigation system, prevention of soil salinization. A system of technological, economic and environmental criteria for evaluating integrated management by the basin principle has been developed. 
 They include maintaining the water level in reservoirs, displacement of salt water prism and limitation on water quality, ensuring the ecological condition of the river, and the dynamics of water resources consumption. Technological criteria determine the maintenance of water levels in reservoirs. Cost-effective water use is estimated on the basis of the dynamics of water consumption for river washing and irrigation.
 The formalized integrated management system in the Ingulets River basin includes operational water resources management and structure management. Integrated management is carried out according to subsystems, types of management and a system of criteria. For operational management the balance differential equations of water exchange in reservoirs are formalized. A two-layer model of water masses dynamics, pollutants distribution and mixing when flushing rivers from reservoirs is used. 
 Scenario analysis is offered to select the optimal structure of the management system. Simulation scenarios are being simulated. Scenario optimization is performed on the Pareto principle.
 An example of evaluating the effectiveness of the proposed system and its comparison with the existing regulations for Ingulets River flushing is given.

State updating of root zone soil moisture estimates of an unsaturated zone metamodel for operational water resources management

Combining metamodels with data assimilation schemes allows the incorporation of up-to-date information in metamodels, offering new opportunities for operational water resources management. We developed a data assimilation scheme for the unsaturated zone metamodel MetaSWAP using OpenDA, which is an open source data assimilation framework. A twin experiment showed the feasibility of applying an Ensemble Kalman filter as a data assimilation method for updating metamodels. Furthermore, we assessed the accuracy of root zone soil moisture model estimates when assimilating the regional SMAP L3 Enhanced surface soil moisture product. The model accuracy is assessed using in situ soil moisture measurements collected at 12 locations in the Twente region, the Netherlands. Although the accuracy of the model estimates does not improve in terms of correlation coefficient, the accuracy does improve in terms of Root Mean Square Error and bias. Therefore, the assimilation of surface soil moisture observations has value for updating root zone soil moisture model estimates. In addition, the accuracy of the model estimates improves on both regional and local spatial scales. The increasing availability of remotely sensed soil moisture data will lead to new possibilities for integrating metamodelling and data assimilation in operational water resources management. However, we expect that significant investments in computational capacities are necessary for effective implementation in decision-making.

Multi-Scenario Model Predictive Control Based on Genetic Algorithms for Level Regulation of Open Water Systems under Ensemble Forecasts

Operational water resources management needs to adopt operational strategies to re-allocate water resources by manipulating hydraulic structures. Model Predictive Control (MPC) has been shown to be a promising technique in this context. However, we still need to advance MPC in the face of hydrological uncertainties. This study makes the first attempt to combine Multi-Scenario MPC (MSMPC) with a Genetic Algorithm (GA) to find Pareto optimal solutions for a multi-scenario operational water resources management problem. Then three performance metrics are adopted to select the solution to be implemented. In order to assess the performance of the proposed approach, a case study of the North Sea Canal in the Netherlands is carried out, in which ensemble discharge forecasts are used. Compared with classic MSMPC approaches that deal with uncertainty by the weighted sum approach, GA-MSMPC can better fulfill management goals although it may also be computationally expensive. With the rapid development of multi-objective evolutionary algorithms, our study suggests the potential of GA-MSMPC to deal with a wide range of operational water management problems in the future.

Validation and assessment of SPoRT-LIS surface soil moisture estimates for water resources management applications

Evaluation of surface soil moisture is necessary to understand spatiotemporal soil moisture trends and their implications on water resources management. This research evaluated a real-time instantiation of NASA’s Land Information System (LIS) for water resources management applications at a higher spatial and temporal resolution than is currently available with remotely-sensed satellite estimates or in situ measurements of the same product. Managed by NASA’s Short-term Prediction Research and Transition (SPoRT) Center, the “SPoRT-LIS” is an observation-driven, real-time simulation of the Noah land surface model at a 3-km resolution over the full continental United States. Surface soil moisture estimates from SPoRT-LIS (0–10 cm layer) were validated against in situ soil moisture from the International Soil Moisture Network in the Missouri and Arkansas-Red-White River Basins. Validation was conducted at in situ measurement depths of 5-cm and 10-cm, and performance was evaluated across varying soil types, land cover, depth, slope, aspect, and pixel heterogeneity to determine conditions under which SPoRT-LIS surface soil moisture had excellent estimation capability. Results demonstrate that 53% of data at a depth of 5-cm and 51% of the data at a depth of 10-cm were significantly correlated with a Spearman’s ρ greater than 0.5 on a daily basis. Based upon validation results, it is evident that the SPoRT-LIS surface soil moisture estimate is satisfactory for research and operational water resources management applications.

Identifying and validating freshwater ecoregions in Jinan City, China

Summary Freshwater ecoregion is currently widely used by biologists, conservators and resource managers. Most of ecoregion delineations are developed at the basin scale and are not fully adapted in a practical manner because operational water resources management is primarily conducted by political administrative departments. In this study, an ecoregion delineation framework was proposed to classify three-level ecoregions in Jinan City with geographic information systems and cluster analysis. The first level ecoregion was composed of three watersheds (a part of the Yellow River, Xiaoqing River and Tuhaimajia River) plus the urban area, which was primarily determined on the basis of the city administrative divisions and river watersheds. The classification of the second level ecoregion is primarily based on the spatial heterogeneity of land use. The third level ecoregion was delineated for each second level ecoregion by using the cluster analysis on water quality. At the same time, administrative boundaries were used to rectify the boundaries of each ecoregion in this study to facilitate the administration of each ecoregion. Furthermore, ecological health assessment (IBI) based on fish communities were employed to validate the freshwater ecoregion. The results demonstrated that 73.3% of ecoregions were in line with the distribution of fish IBI, indicating that the freshwater ecoregions are acceptable for future water resources management.

Calibration, validation, parameter indentifiability and uncertainty analysis of a 2 – parameter parsimonious monthly rainfall-runoff model in two catchments in Zimbabwe

Hydrologic modelling lies at the core of hydrology and water resources management. Attempts at gaining a holistic grasp on model robustness, hydrologic theory and processes have inadvertently led to models that are not-well structured or too complex to apply in arid and semi-arid catchments and in Africa, in particular. In view of this, this paper reports on the application of a monthly parsimonious hydrologic model in two catchments in Zimbabwe, the Nyatsime and Upper Save river catchments. The two (2) parameter monthly parsimonious GR2M model was applied. The inputs were rainfall and potential evapotranspiration. Measured discharge was used for calibration and validation. Calibration and uncertainty analysis were done using the Differential Evolution Adaptive Metropolis (DREAM) algorithm. The performance of the GR2M model was evaluated using ten (10) model performance metrics. Parameter indentifiability was analysed on the basis of the shape of the posterior distribution of parameters. Parameter and total uncertainty were analysed in the context of the formal Bayesian DREAM approach. The 10 performance evaluation metrics showed that the model performed satisfactorily during calibration and validation in terms of the overall fit of observed and simulated stream flows, low flows and the runoff volumes. The Nash-Sutcliffe efficiency (NSE) was >0.85, the Kling–Gupta Efficiency (KGE) was >80% and Volume Efficiency was >59% during calibration. Slight performance drops were noted during validation except for the NSE in Nyatsime catchment whilst the KGE remained relatively high. The validation NSE was >0.65, the Kling–Gupta Efficiency (KGE) was >71% and Volume Efficiency was >55%. Calibrated parameters values showed good time-stability and were well identifiable with posterior parameter distributions having Gaussian shapes. Parameter uncertainty, in relation to total uncertainty was low. Parameter uncertainty constituted about 7% of the total uncertainty region. It was concluded that, although the model only had two parameters, the model performed quite satisfactorily in the simulation of monthly flows which makes it a good tool for operational hydrology and water resources modelling, planning and management especially in regions with inadequate data.

Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities

Abstract. Data assimilation (DA) holds considerable potential for improving hydrologic predictions as demonstrated in numerous research studies. However, advances in hydrologic DA research have not been adequately or timely implemented in operational forecast systems to improve the skill of forecasts for better informed real-world decision making. This is due in part to a lack of mechanisms to properly quantify the uncertainty in observations and forecast models in real-time forecasting situations and to conduct the merging of data and models in a way that is adequately efficient and transparent to operational forecasters. The need for effective DA of useful hydrologic data into the forecast process has become increasingly recognized in recent years. This motivated a hydrologic DA workshop in Delft, the Netherlands in November 2010, which focused on advancing DA in operational hydrologic forecasting and water resources management. As an outcome of the workshop, this paper reviews, in relevant detail, the current status of DA applications in both hydrologic research and operational practices, and discusses the existing or potential hurdles and challenges in transitioning hydrologic DA research into cost-effective operational forecasting tools, as well as the potential pathways and newly emerging opportunities for overcoming these challenges. Several related aspects are discussed, including (1) theoretical or mathematical aspects in DA algorithms, (2) the estimation of different types of uncertainty, (3) new observations and their objective use in hydrologic DA, (4) the use of DA for real-time control of water resources systems, and (5) the development of community-based, generic DA tools for hydrologic applications. It is recommended that cost-effective transition of hydrologic DA from research to operations should be helped by developing community-based, generic modeling and DA tools or frameworks, and through fostering collaborative efforts among hydrologic modellers, DA developers, and operational forecasters.

Advances in Data Assimilation for Operational Hydrologic Forecasting

International Workshop on Data Assimilation for Operational Hydrologic Forecasting and Water Resources Management; Delft, Netherlands, 1–3 November 2010; The abundance of new hydrologic observations (in situ or remotely sensed) in the past couple of decades has stimulated a great deal of research into the use of these observations for improved hydrologic predictions via model‐data infusion applications. Generally speaking, however, hydrologic data assimilation (DA) as an objective tool for reducing predictive uncertainty is not yet technically ready for operational hydrologic forecasting and water resources management. This is due in part to a lack of mechanisms to properly quantify the uncertainty in observations and forecast models in real‐time forecasting situations and to conduct the merging of data and models in a way that is adequately efficient and transparent to operational forecasters. Nevertheless, the need for effective assimilation of useful data into the forecast process is increasing. Within the framework of the Hydrologic Ensemble Prediction Experiment (HEPEX; http://www.hepex.org/), a workshop was held in the Netherlands. The overall goal of the workshop was to develop and foster community‐based efforts for collaborative research, development, and synthesis of techniques and tools for hydrologic data assimilation and for the cost‐effective transition of these techniques and tools from research to operations.

Harmonizing water management and social needs: a necessary condition for sustainable development. The case of Israel's coastal aquifer

This study focuses on the problem of most efficiently fulfilling the water requirements of society for sustainable water resources management. The goal is to coordinate effectively the social needs of the resident population with operational water resources management planning. The proposed approach consists of a pyramidal hierarchy of water resource management needs, similar to that suggested by psychologist Abraham Maslow for human social needs. The two pyramidal hierarchies can be simultaneously employed to delineate guidelines to synchronize planning for sustainable water resources development with the concerns and expectations of the resident population. In both hierarchies, higher level needs remain irrelevant and difficult to attain until lower level needs of the resident population have been fulfilled. Management planning measures employed with regard to Israel's coastal aquifer have been used to illustrate this approach. Observation of Israel's experience indicates markedly reduced effectiveness where such measures have failed to be properly synchronised with societal needs. Conversely, where hydrological management measures were successfully synchronized with societal concerns, increased efficiency towards attaining sustainable groundwater management was evident.