S4

Many countries vulnerable to climate change do not yet have national modelling systems in place to guide adaptation measures. Especially low- and middle-income countries are at the mercy of global or large-scale estimates of climate change impacts, which might not be relevant to the spatial scale of societal challenges or to engineering methods based on observations.

Climate services are launched with scientific data, which can be misunderstood and misused if not communicated in a pedagogic way. For instance, the results from climate models represents an average for a calculation unit and neglects the spatial variability within that unit. In-situ observations from monitoring stations represents a point value and may thus be very different from areal estimates. Moreover, observations are relatively few leaving large areas ungauged. Sometimes, the area of interest falls in between grids or is very small compared to the grid or catchment and the average values may then not be representative or useful.

Moreover, the results from climate models represents a statistical period of 30 years, but not the chronological happening of events or weather conditions. Time-series from climate models are thus not representing specific dates and should not be compared to observed time-series but only to statistical estimates, such as indicators. 

In this presentation we showcase (1) state-of the art methods to produce climate indicators for weather and water data over large domains, and (2) some ways to tailor climate and water data for local applications and practical use.

We will demonstrate the global climate service climateinformation.org, in which climate and water indicators result from an extensive production chain, merging data from various sources with different resolution in time and space.

For water indicators, climateinformation.org uses results from a global integrated-catchment model, the world-wide HYPE. To tailor data, it is recommended to use a more detailed national/local model or set-up the HYPE model using national/local data. SMHI share the open source HYPE-model code and here we will explain how to apply climate indicators to calculate climate-change effects on water resources using a local/national model. Showcases are given for St Lucia, DR Congo, Cape Verde, and Cambodia.

How to cite: Arheimer, B., Gyllensvärd, F., Capell, R., and Andersson, J.: Tailoring large-scale hydrological models for national planning of climate actions in vulnerable countries, IAHS-AISH Scientific Assembly 2022, Montpellier, France, 29 May–3 Jun 2022, IAHS2022-426, https://doi.org/10.5194/iahs2022-426, 2022.

Data assimilation is a powerful tool that has been used to correct states and parameters of rainfall-runoff models based on recent streamflow, remotely sensed soil moisture or groundwater data. Data assimilation is now routinely applied by forecasting centres around the world to improve simulations and increase forecast skill. In this work, we are less concerned with the direct benefits of data assimilation on model outputs, but more on the nature of the corrections introduced and how they can be analysed to diagnose structural deficiencies in rainfall-runoff models.

Rainfall-runoff models have been shown to lack extrapolation capacity in simulating dry and wet periods that are more extreme than calibration conditions. This is particularly concerning in the context of climate change studies where more climate extremes are generally predicted for expected. This is the case in South-Eastern Australia where annual rainfall is expected to decrease significantly under most climate scenarios. Consequently, the improvement of rainfall-runoff model structures to better simulate dry flow regimes is critical to obtain robust estimates of water resources availability.

In this work, we assimilated streamflow data in the GR2M monthly rainfall-runoff models for 100 catchments in South-East Australia. The assimilation was conducted during a wet period between 1970 to 1995 and used to identify model structure deficiencies, particularly in the function computing water exchanges with nearby catchments. An attempt of correcting these deficiencies was undertaken using a simple regression approach. Finally, the correction was applied during a dry period (1995-2010) and performance was compared with the original (uncorrected) model. The results suggest that the corrected simulations better capture streamflow extremes, especially low flows. Further work is also discussed related to the use of additional data such as LAI and groundwater data to better constrain the correction regression.

How to cite: Lerat, J., Chiew, F., Zheng, H., and Robertson, D.: Use of data assimilation to improve rainfall-runoff model structure for climate change projections, IAHS-AISH Scientific Assembly 2022, Montpellier, France, 29 May–3 Jun 2022, IAHS2022-365, https://doi.org/10.5194/iahs2022-365, 2022.

The program NEXUS Gains addresses key challenges of transforming water, energy, food and ecosystem (WEFE) systems in transboundary bread-basket basins in East and Southern Africa (Blue Nile and Limpopo basins), Central (Aral Sea basin) and South Asia (Ganges and Indus basin) in a changing world. The program particularly explores water resource management options to understand WEFE system interdependencies, trade-offs and synergies and develop more sustainable development pathways for all members society.

The presentation will discuss alternative interventions to increase water productivity different sectors (irrigation, forestry, industries) across scales ranging from farm to watershed to river basin scales. Therefore, particular attention will be given to integrated water storage management in human built and natural infrastructure in South Asia and East Africa. The implications for hydrological process and water resources dynamics and wider environmental, social and economic systems are analyzed and related policy implications are discussed considering also climate change.

How to cite: Uhlenbrook, S., Ringler, C., Lautze, J., McCartney, M., and Hafeez, M.: On the role of water resources management to transform water, energy, food and ecosystem (WEFE) systems in transboundary river basins, IAHS-AISH Scientific Assembly 2022, Montpellier, France, 29 May–3 Jun 2022, IAHS2022-463, https://doi.org/10.5194/iahs2022-463, 2022.

Enhanced coordination is an important feature of the water–energy–food (WEF) nexus – an agenda that highlights the interdependencies between these sectors. But, while greater coordination is often promoted as a goal, particularly in relation to policy and planning, achieving it is far from easy. There are two complementary dimensions to understanding the WEF nexus; quantifying the physical links between sectors, and unravelling the management and governance structures involved. This paper profiles two different approaches to address the former dimension as a means to enable greater understanding of multi-sector interdependencies. One uses a multi-scale analysis of nexus linkages in the Gulf region to show how integrating new datasets can allow a more comprehensive analysis of WEF interdependencies, and in so doing highlight emerging areas of risk. The other illustrates how application of visualisation methods in a river basin can help present to stakeholders the complex trade-offs that exist across the WEF nexus and potentially contribute to decision-making. This study sought guidance on what stakeholders felt were important services that development in their river basin should achieve sustainably (performance indicators) and then simulated many thousands of combinations of options to identify which ones worked best across the different performance indicators using multi-objective optimisation. Respectively, these examples show how a nexus approach can reveal that a country’s food imports are associated with unsustainable agricultural practices and where the use of innovative modelling and visualisation techniques can provide opportunities to convey the complex outcomes of decisions, capturing alternative perspectives and values. So - while coordination is hard to achieve - new datasets and innovative methods of visualisation offer promise in addressing at least some of the barriers that confront progress in moving forward a nexus agenda.

How to cite: Conway, D.: Progress in characterising water-energy-food interdependencies, IAHS-AISH Scientific Assembly 2022, Montpellier, France, 29 May–3 Jun 2022, IAHS2022-360, https://doi.org/10.5194/iahs2022-360, 2022.

Abstract

Conflict over water resources emerges from complex interactions among biophysical, social, and economic processes operating at multiple scales. The concomitant use of surface and groundwater managed for multiple uses is a classic coping strategy to manage the water scarcity yet a relevant example of such conflict. Managing these resources is thus a dynamic decision-making process involving actors with different perceptions of the situation, who adapt different strategies to satisfy their objectives and interests. This paper presents the results of an effort to address these conflicts through reinforcing the adaptive capacity of different actors to cope with water scarcity in a multi-scale irrigation system. The study site focuses on the irrigated area of Zaouiet Jedidi in Northeast Tunisia. This region is characterized by an intensive irrigated agriculture, mostly through an excessive pumping of groundwater resources. Individual strategies to face the water scarcity are dominating leading to a rapid deterioration of the groundwater resources. Irrigation through individual and informal wells is an example of such strategies. As the demand for agricultural and urban water has concurrently continued to develop, the groundwater has continued to drop. Despite the State’s efforts to increase the water supply to the region through the transfer of surface water from the dams of northwestern Tunisia, the overexploitation of groundwater resources exceeded 200%. A participatory process was implemented to initiate a process of interaction and coordination between the different stakeholders involved in the management of the irrigated area. We analyzed to what extent and by what mechanisms, a participatory problem-solving process can facilitate the emergence of collection action to face the water scarcity.

How to cite: Ferchichi, I., Zairi, A., and Marlet, S.: Water scarcity conflicts: Supporting dialogue and negotiation, IAHS-AISH Scientific Assembly 2022, Montpellier, France, 29 May–3 Jun 2022, IAHS2022-425, https://doi.org/10.5194/iahs2022-425, 2022.

The concept of sustainability in water management remains an amorphous notion. Despite its widespread use, there is not a shared and accepted definition of the concept of sustainability in water management, including its monitoring and assessment, particularly at river basin scale. Sustainability Assessment (SA) can be defined as any process that aims at planning and direct decision-making toward sustainable development. An interdisciplinary approach for understanding, measuring and monitoring sustainability of water management practices includes the holistic development of Indicator-Based Assessment (IBA) frameworks as policy/decision support tools. The IBA refers to the positive, negative, and neutral qualifications of an indicator based on the comparison between its observed evolution (and/or status), and the desired evolution set for the indicator by means of a frame of reference. Therefore, developing IBA frameworks help to synthesize information and monitor changes in water management systems.

Recently, developing indicator-based assessment frameworks and constructing indexes have evolved significantly toward monitoring the United Nations Sustainable Development Goals (UN SDGs). However, there are limited studies on developing sustainability indexes or indicator-based sustainability assessment frameworks at the river basin scale for complex issues of water management. The aim of this work is to provide a review of i) the concept of SA in water management and also ii) the methodology of indicator-based framework development. Finally, a case study of developing an indicator-based sustainability assessment framework is presented for the Mashhad River basin in Iran.

How to cite: Shafiei, M., Gharari, S., Gharesifard, M., Ghoreishi, M., and V. Castro, C.: Sustainability Assessment: The role of Indicator-based Frameworks in Sustainable Water Management, IAHS-AISH Scientific Assembly 2022, Montpellier, France, 29 May–3 Jun 2022, IAHS2022-271, https://doi.org/10.5194/iahs2022-271, 2022.

Warming climate is altering streamflow characteristics and posing pressure on water systems. Here, the impacts of climate change on a headwater system in Alberta, Canada, is evaluated, with the primary goal of understanding the role of hydrological system representation. For this purpose, a conceptual hydrological model, i.e., HBV-MTL, is coupled with two snowmelt estimation modules, i.e., Degree-Day and CemaNeige. The models are calibrated using point- and grid-based climatic data and considering lumped and semi-distributed representation of the basin and are linked to a water allocation model to simulate reservoir dynamics and downstream water deliveries. The bias-corrected outputs of 19 climate models during 2021-2099 are then used to estimate the future water system conditions. Results show that during the historical period, all models provide acceptable performance, with minor distinctions; however, their simulations highly divergence in the future period. The models unanimously project significant water deficit in meeting agricultural water demands and flood risk in the future. However, the quantified vulnerabilities depend on the considered hydrological models, among the utilized snow routine module highly influences estimated natural and regulated flow values. It is suggested to consider these projections and revise the Oldman reservoir water allocation plans to mitigate climate change's adverse impacts on this water system.

How to cite: Hassanzadeh, E. and Sharifinejad, A.: Evaluating the impact of climate change on water system vulnerabilities using multiple hydrological models, IAHS-AISH Scientific Assembly 2022, Montpellier, France, 29 May–3 Jun 2022, IAHS2022-234, https://doi.org/10.5194/iahs2022-234, 2022.

Rainwater harvesting systems (RHS) has been a relevant alternative of water supply in urban areas facing increasing water demand associated to limited water availability. However, previous work has showed that the performance of these systems is highly affected by climate data such as precipitation (well characterized uncertainties). The present study aims to assess the impact of system parameters (water demand, tariffs, storage volume, collect area) named here as deep uncertainties factors influence the feasibility of RHS. So, performance criteria were defined such as Percentage of Satisfied Demand - PSD, Reliability - REL, Percentage of Rainwater Harvesting - PRH, Net Present Value - NPV, Net Present Value Volume - NPV and Benefit Cost Rate - BCR for different scenarios that incorporate uncertainties in precipitation regime, water tariff, discount rate and increase of operating costs rate. The simulation of the RHS performance considered eight categories of residential buildings according to representative water consumption (ranging from 4.748 to 44.673 m³/month) and two characteristic catchment areas for each of the four group of demands (ranging from 60 to 400 m²) in the city of Rio Verde located in the central of Brazil. An ensemble of 1000 scenarios was defined using the Latin Hipercube Sampling (LHS) method and booststrapping resampling (in the case of precipitation). Then, it was evaluated how different scenarios affected each indicator and if uncertainties from some of the parameters have a greater impact on the performance criteria. Results showed low influence of precipitation scenarios on the performance criteria, maybe due to the sampling method that did not generate significant variability. For the elements with deep uncertainty, the relationship among the water tariff and the discount rate readjustments with NPV was confirmed. Thus, the importance of evaluating these elements carefully to achieve rainwater harvesting systems projected performance was confirmed.

How to cite: Ribeiro Pacheco, G. C. and Albuquerque Alves, C. D. M.: The performance of rainwater harvesting systems in the context of deep uncertainties, IAHS-AISH Scientific Assembly 2022, Montpellier, France, 29 May–3 Jun 2022, IAHS2022-283, https://doi.org/10.5194/iahs2022-283, 2022.

Nature-based solutions (NBSs) use earthen materials to mimic natural stormwater flow by increasing levels of greenspace within the built environment. Research has demonstrated the capability of NBSs to address overlapping issues of societal well-being, including improvements in mental and physical health, social vulnerability, sense of well-being, and socio-economics. However, existing NBS planning frameworks emphasize hydro-environmental modeling and cost-benefit analysis for regional spatial allocation. Social conditions are only incorporated at preliminary planning stages through visualization of geospatial hotspots and are not embedded directly within the optimization model. By relying on metrics of hydro-environmental mitigation, the unique spatial exposures of social deprivation that could benefit from NBSs are not well-captured. Water dynamics and social well-being are highly entangled, and we necessitate improved methods for combining hydrological and social characteristics in a robust manner. Here, a novel framework is proposed and demonstrated that integrates hydro-environmental modeling, economic efficiency, and social deprivation using a dimensionless Gini coefficient. Hydro-environmental risk and social disparity are combined within a common measurement unit to capture variation across spatial domains and to optimize fair distribution across the study area. Advances in neighborhood-scale datasets for measuring social deprivation are leveraged to improve fundamental, multi-objective planning in human-water systems. A case study in the White Oak Bayou watershed in Houston, Texas, USA is used to demonstrate how the optimal spatial allocation of NBSs is location-dependent with varying tradeoffs amidst overlapping goals (e.g., stormwater runoff mitigation, water quality abatement, economic efficiency, and equity-based allocation). The composite Gini coefficient demonstrates how water resources planning may be addressed as a holistic system of human-water phenomena to minimize tradeoffs across disparate domains while improving social justice.

How to cite: Vail Castro, C.: Water resources management as a coupled hydro-environmental and social-equity-based optimization framework, IAHS-AISH Scientific Assembly 2022, Montpellier, France, 29 May–3 Jun 2022, IAHS2022-257, https://doi.org/10.5194/iahs2022-257, 2022.

Maintaining ecological flow is a need for enviromental  sustainability of regulated rivers  in managed  water bodies, whatever the different and competitive water demands (urban supply, irrigation, energy, or ecology). This is a challenge that the hydropower sector has to deal with, in areas subjected to complex meteorology with long drought periods followed by intense flood episodes, like those affected by the Mediterranean climate, specially in run of river facilities. These facts point towards the introduction of new regulatory frameworks to push towards a minimum river flow regime more adapted to the naturally variable hydrological regime of streamflow in Mediterranean regions. This question is not trivial and this challenge becomes even more critical in a climate change scenario in which hydropower energy is markedly affected not only by the market but also  by a priori more extreme meteorological events. In this paper, the compliance of the minimum river flow regime established by the Water Authorities in ten water bodies with hydropower generation (6 run-of-river plants and 4 reservoir plants) in southern Spain has been analyzed using historical streamflow and reservoir inflow data series, respectively and assuming that these values  closely represent the natural regime upstream the hydropower plans. For each case, the compliance of ecological regime thresholds during the last 10 hydrological years (September 2010 - August 2020) was analyzed at daily scale. In addition,  an hourly scale analysis was added when hourly data series were available. The results obtained showed that the natural regime of the watercourses hardly complies with the conditions established in the state law on compliance with ecological flows in all of the cases, and that, therefore, these flows were oversized. This overestimation is extremely unbalanced in some of the bodies studied, as in the case of the Cala reservoir, where even a reduction of 90% of the ecological flow, cannot be met by one of the 4 conditions on more than 60% of occasions.

The results highlight the needs for a balanced and updated environmental flow regime in regions with large natural variability in order to support the sustainability of hidropower, especially in run of river facilities.

How to cite: Aparicio, J., Contreras, E., Aguilar, C., Moreno, F., and Polo, M. J.: Are the thresholds of ecological flows established by the water management authorities aligneed with the natural regime of rivers in Mediterranean regions?, IAHS-AISH Scientific Assembly 2022, Montpellier, France, 29 May–3 Jun 2022, IAHS2022-676, https://doi.org/10.5194/iahs2022-676, 2022.

Abstract

The construction of dams and reservoirs for hydropower generation has been increasing in major river basins around the world. These dams store huge amounts of water thereby reducing the streamflow in the low-lying regions. Such changed seasonality of streamflow has various socio-economic and environmental consequences. Downstream dwellers are left with reduced water for their daily lives, irrigation, fisheries, and ecological services, resulting in conflicts. This paper aims to study the benefit loss of downstream communities caused by the operation of a huge reservoir in the upstream area for hydropower purposes. The benefits are calculated in terms of economic benefit through hydropower, irrigation, fisheries in both upstream and downstream communities through simulation of socio-hydraulic changes after the reservoir operation. T