Climate change is affecting freshwater systems, leading to increased water temperatures, which is posing a threat to freshwater ecological communities. In the Nechako River, British Columbia, a water management program has been in place since the 1980s to maintain water temperatures at 20 °C during the migration of adult Sockeye salmon. However, the program's effectiveness in mitigating the impacts of climate change on resident species like Chinook salmon's thermal exposure is uncertain. In this study, we utilised the CEQUEAU hydrological model and life stage-specific physiological data to evaluate the consequences of the current program on Chinook salmon's thermal exposure under two contrasting climate change and socio-economic scenarios (SSP2-4.5 and SSP5-8.5). The results indicate that the thermal exposure risk is projected to be above the optimal threshold for parr (intermediate juvenile) and adult life stages under both scenarios relative to the 1980s. Under the SSP5-8.5 scenario, these life stages could experience an increase in thermal exposure ranging from two to five times higher by the 2090s compared to the 1980s. This exposure is projected to occur during the months in which these life stages emerge, including the period when the program is active (July 20th to August 20th). Additionally, our study shows that climate change will result in a substantial rise in cumulative heat degree days, ranging from 1.9 to 5.8 times (2050s) and 2.9 to 12.9 times (2090s) in comparison to the 1980s under SSP5-8.5. Our study highlights the need for a holistic approach to reviewing the current Nechako management plan, ensuring that all species in the Nechako River system are considered especially in the face of climate change.

A paper recently published entitled “Water crisis in Iran: A system dynamics approach on water, energy, food, land, and climate (WEFLC) nexus” (Barati et al., 2023). In the mentioned study, a WEFLC model is developed to analyze the water scarcity in Iran. Water crisis, as a complex and challenging issue, has different interdependencies in the context of socio-ecological systems (SES), making it an incorrigible issue. The original paper attempted to assess the water resource dynamics through a systemic lens and explore the impact of various driving forces of water resource planning and management on the water crisis. Iran is a well-studied country, especially around water-related problems. Many interesting facts and findings through the water scarcity analysis in the context of WEFLC are mentioned in the original paper. For instance, it is highlighted that “Mitigation and adaptation policies must be system-oriented and coherent at sectors.” However, the original paper did not benefit enough from the previous studies and the full potential of available data. Moreover, some arguments contradict previous findings and, in some cases, are logically flawed. The original paper barely alludes to the nonlinear functional relationships among the components of WEFLC, the core expected component in complex system analysis. Incorrect problem statement formation, flawed methodology, insufficient information on the applied method, ambiguity in models' coupling or cohesion, lack of rational explanation, and inappropriate interpretations of abnormal findings may even mislead many readers. This paper aims to point out some concerns related to the problems mentioned above in the published study, with suggestions to improve the current study and methodological notes for future research.

This paper evaluates the impact of climate change on the water temperature of the Nechako River near the town of Vanderhoof (British Columbia, Canada). To do so, the Hydrologic Engineering Center's River Analysis System (HEC-RAS) hydraulic and water temperature model was used with data from 10 climate models representing two Shared Socioeconomic Pathways (SSP 2-4.5 and SSP 5-8.5) over two future time periods (2041-2070 and 2071-2100). The results showed an upward trend in projected water temperatures for all tested discharge rates from the impounding reservoir during the warmest periods of the year. The study found that water temperatures are expected to increase by up to 2.57 degrees C for the near future (2041-2070) and up to 3.56 degrees C on average for all flow scenarios studied for a far future (2071-2100) when using SSP5-8.5. The timing of the peak water temperature during the summer is also expected to shift, with maximum water temperatures occurring up to 10 days later than in the reference period. In 10.3% of the far future SSP5-8.5 scenarios, at least one day per summer had a mean daily temperature of at least 24 degrees C, which exceeds limits of 20 degrees C for sockeye salmon and 21 degrees C for white sturgeon which are considered detrimental for the fish. It has been shown that over 50% of sockeye salmon will stop their sustained swimming at water temperatures of 24 degrees C due to cardiac limitations. Cette publication evalue l'impact des changements climatiques sur la temperature de l'eau de la riviere Nechako pres de la ville de Vanderhoof (Colombie-Britannique, Canada). Pour ce faire, le modele hydraulique et thermique du Hydrologic Engineering Center's River Analysis System (HEC-RAS) a ete utilise conjointement aux donnees de 10 modeles climatiques representant deux trajectoires socio-economiques partagees (SSP 2-4.5 et SSP 5-8.5) couvrant deux horizons futurs (2041-2070 et 2071-2100). Les resultats demontrent une tendance ascendante de la temperature des eaux pour tous les scenarii de debits etudies provenant du reservoir en amont durant la periode la plus chaude de l'annee. Il est attendu que la temperature de l'eau augmente autant que 2.57 degrees C pour le futur rapproche (2041-2070) et jusqu'a 3.56 degrees C pour le futur lointain (2071-2100) pour le scenario SSP 5-8.5. Les temperatures de pointes se deplaceront aussi et seront retardees d'environ 10 jours comparativement a la periode de reference. Dans 10.3% des cas etudies pour le scenario du futur lointain de SSP 5-8.5, la temperature de l'eau excede 24 degrees C au moins une journee par ete, ce qui depasse largement les limites de 20 degrees C pour le saumon rouge et 21 degrees C pour l'esturgeon blanc, limites considerees nuisibles a la sante de ces poissons. Il a ete demontre que plus de 50% des saumons rouges arreteront leur nage prolongee lorsque l'eau atteint le seuil des 24 degrees C en raison des limitations cardiaques.

This study compares single-site and multisite calibration methods with upscaled parameters for thermal modelling. Multisite calibration and parameter upscaling are novel for calibrating a hydrological-thermal model. To this end, model calibration and simulations are carried out using a semi-distributed hydrological-thermal model (CEQUEAU). First, a hydrological calibration is carried out. The same calibrated hydrological model outputs are used for all thermal calibrations. The covariance matrix adaptation evolution strategy (CMA-ES) single-objective optimization algorithm is applied to calibrate the thermal module using observed water temperatures at seven monitoring sites within the Nechako Watershed in British Columbia, Canada. Single-site calibration provided the best performance for individual sites, but these sets of parameters performed poorly when applied to the other sites. The multisite calibration and the upscaled methods perform adequately for all sites with overall Root Mean Square Error (RMSE)<2 degrees C as an acceptable threshold. However, the multisite method resulted in the best performance metrics and shortest computing time.

Water temperature is a key variable affecting fish habitat in rivers. The Sockeye salmon ( Oncorhynchus nerka ), a keystone species in north western aquatic ecosystems of North America, is profoundly affected by thermal regime changes in rivers, and it holds a pivotal role in ecological and economic contexts due to its life history, extensive distribution, and commercial fishery. In this study, we explore the effects of climate change on the thermal regime of the Nechako River (British Columbia, Canada), a relatively large river partially controlled by the Skins Lake Spillway. The CEQUEAU hydrological-thermal model was calibrated using discharge and water temperature observations. The model was forced using the Fifth generation of ECMWF Atmospheric Reanalysis data for the past and meteorological projections (downscaled and bias-corrected) from climate models for future scenarios. Hydrological calibration was completed for the 1980–2019 period using data from two hydrometric stations, and water temperature calibration was implemented using observations for 2005–2019 from eight water temperature stations. Changes in water temperature were assessed for two future periods (2040–2069 and 2070–2099) using eight Coupled Model Intercomparison Project Phase 6 climate models and using two Shared Socioeconomic Pathway scenarios (4.5 and 8.5 W/m 2 by 2100) for each period. Results show that water temperatures above 20°C (an upper threshold for adequate thermal habitat for Sockeye salmon migration in this river) at the Vanderhoof station will increase in daily frequency. While the frequency of occurrence of this phenomenon is 1% (0–9 days/summer) based on 2005–2019 observations, this number range is 3.8–36% (0–62 days/summer) according to the ensemble of climate change scenarios. These results show the decreasing habitat availability for Sockeye salmon due to climate change and the importance of water management in addressing this issue.

Longwave radiation (LR) is one of the energy balance components responsible for warming and cooling water during hot summers. Both downward incoming LR, emitted by the atmosphere, and outgoing LR emitted by the land surface are not widely measured. The influence of clouds on the LR heat budget makes it even harder to establish reliable formulations for all-sky conditions. This paper uses air temperature and cloud cover from the ERA5 reanalysis database to compare 20 models for the downward longwave irradiance (DLI) at Earth's surface and compare them with ERA5's DLI product. Our work uses long-time continuous DLI measured data at three stations over Canada, and ERA5 reanalysis, a reliable source for data-scarce regions, such as central British Columbia (Canada). The results show the feasibility of the local calibration of different formulations using ERA5 reanalysis data for all-sky conditions with RMSE metrics ranging from 37.1 to 267.3 W m-2, which is comparable with ERA5 reanalysis data and can easily be applied at broader scales by implementing it into hydrological models. Moreover, it is shown that ERA5 gridded data for DLI shows the best results with RMSE 5 31.7 W m-2. This higher performance suggests using ERA5 data directly as input data for hydrological and ecological models.

Water temperature plays a crucial role in the physiology of aquatic species, particularly in their survival and development. Thus, resource programs are commonly used to manage water quality conditions for endemic species. In a river system like the Nechako River system, central British Columbia, a water management program was established in the 1980s to alter water release in the summer months to prevent water temperatures from exceeding a 20 °C threshold downstream during the spawning season of Sockeye salmon (Oncorhynchus nerka). Such a management regime could have consequences for other resident species like the white sturgeon (Acipenser transmontanus). Here, we use a hydrothermal model and white sturgeon life stage-specific experimental thermal tolerance data to evaluate water releases and potential hydrothermal impacts based on the Nechako water management plan (1980-2019). Our analysis focused mainly on the warmest five-month period of the year (May to September), which includes the water release management period (July-August). Our results show that the thermal exposure risk, an index that measures temperature impact on species physiology of Nechako white sturgeon across all early life stages (embryo, yolk-sac larvae, larvae, and juvenile) has increased substantially, especially in the 2010s relative to the management program implementations' first decade (the 1980s). The embryonic life stage was the most impacted, with a continuous increase in potential adverse thermal exposure in all months examined in the study. We also recorded major impacts of increased thermal exposure on the critical habitats necessary for Nechako white sturgeon recovery. Our study highlights the importance of a holistic management program with consideration for all species of the Nechako River system and the merit of possibly reviewing the current management plan, particularly with the current concerns about climate change impacts on the Nechako River.

Globally, agriculture is the primary water consumption sector. This study used water footprint (WF) as a bottom-up tool and satellite imagery as a top-down tool to estimate the internal water use (WU) in the agricultural sector in an innovative way to show the effects of water-intensive use in agriculture in an arid country. The WF of Iran has been quantified for 19 main crops and for related agricultural products exported from Iran to partner countries. Using a bottom-up approach, Iran's total yearly agriculture net water consumption is estimated to be 42.43 billion cubic meters (BCM) per year. Out of 42.43 BCM total net internal water use, only 1.61 BCM is virtual-water export related to these 19 products, and the remaining 40.82 BCM is for internal use. Our results using satellite imagery show that in case of using all possible lands for agriculture, it would require 77.4 BCM. However, not all these lands are within human reach, and the maximum available water is way lower than this amount. Using satellite imagery, the total evaporation from agricultural lands shows 55.27 BCM for 2020, which agrees with national reports during 2005–2014. This study shows that agricultural water consumption tends to use internal water resources at a maximum level for export and national use, significantly impacting renewable and non-renewable water resource availability, especially in groundwater.

Climate change is influencing freshwater systems, leading to an increase in water temperatures, harmful algal blooms, pollution, and a decrease in dissolved oxygen levels, all of which pose a concern for the freshwater ecological communities. In dammed river systems such as the Nechako River in central BC, Canada, these impacts could be particularly significant. However, a water management program in operation since the 1980s discharges water from a reservoir located over 100km upstream during hot summer months to prevent downstream water temperatures from exceeding 20°C thresholds. Nevertheless, climate change may render this management approach less effective in achieving its objective of maintaining water temperatures within the optimal thermal range for resident fish species, particularly for resident species such as Chinook salmon (Oncorhynchus tshawytscha). In this study, we used a hydrological model and life stage-specific physiological experimental data to evaluate the consequences of the current Nechako water management program on the thermal exposure of Chinook salmon under two contrasting climate change and socio-economic scenarios: SSP2-4.5 and SSP5-8.5. We analysed the thermal exposure risk for the warmest six-month period of the year (May to October). Our findings indicate that thermal exposure risk (Te), an index that measures the temperature impact on species physiology, is projected to be above the optimal level for all life stages under both scenarios relative to the management program's first decade (the 1980s). In the 1980s, the Te values for fry and parr were below the optimal threshold, except in August for the adult stage. Under the future scenarios, the fry life stage Te will increase above optimal in June, particularly by the end of the century, while parr and adult Te values are projected to increase in July, August and September in most river sections. These results suggest that climate change will lead to increased thermal exposure risks for the Nechako Chinook salmon in the future. Our study highlights the need to review the current Nechako management plan and consider a holistic approach that considers all species of the Nechako River system in the face of climate change.

The Middle East and North Africa (MENA) region has seen remarkable population growth over the last century, outpacing other global regions and resulting in an over-reliance on food imports. In consequence, it has become heavily dependent on grain imports, making it vulnerable to trade disruptions (e.g., due to the Russia-Ukraine War). Here, we quantify the importance of imported grains for dietary protein and energy, and determine the level of import reductions at which countries are threatened with severe hunger. Utilizing statistics provided by the Food and Agriculture Organization (FAO), we employed a stepwise calculation process to quantify the allocation of both locally produced and imported grains between the food and feed sectors. These calculations also enabled us to establish a connection between feed demand and production levels. Our analysis reveals that, across the MENA region, 40% of total dietary energy (1,261 kcal/capita/day) and 63% of protein (55 g/capita/day) is derived from imported grains, and could thus be jeopardized by trade disruptions. This includes 164 kcal/capita/day of energy and 11 g/capita/day of protein imported from Russia and Ukraine. If imports from these countries ceased completely, the region would thus face a severe challenge to adequately feed its population. This study emphasizes the need for proactive measures to mitigate risks and ensure a stable food and feed supply in the MENA region.

Hydrological modeling, water accounting assessments, and land evaluations are well-known techniques to carry out water resources carrying capacity (WRCC) assessments at multiple spatial levels. Using the results of an existing process-based model for assessing WRCC from very fine to national spatial scales, we propose a mathematical meta-model, i.e., a set of easily applicable simplified equations to assess WRCC as a function of high-quality agricultural lands for optimistic to realistic scenarios. These equations are based on multi-scale spatial results. Scales include national scale (L0), watersheds (L1), sub-watersheds (L2), and water management hydrological units (L3). Applying the meta-model for different scales could support spatial planning and water management. This method can quantify the effects of individual and collective behavior on self-sufficient WRCC and the level of dependency on external food resources in each area. Carrying capacity can be seen as the inverse of the ecological footprint. Hence, using publicly available data on the ecological footprint in Iran, the results of the proposed method are validated and give an estimation of lower and upper bounds for all biocapacity of the lands. Moreover, the results confirm the law of diminishing returns in the economy for the carrying capacity assessment across spatial scales. The proposed meta-model could be considered a complex manifest of land, water, plants, and human interaction for food production, and it could be used as a powerful tool in spatial planning studies.

Different methods have been proposed in population dynamics to estimate carrying capacity (K). This study estimates K for Iran, using three novel methods by integrating land and water limits into assessments based on Human Appropriated Net Primary Production (HANPP). The first method uses land suitability as the limiting resource. It gives theoretical estimates for K. The second method which is based on the first method, uses land suitability and water resources availability as limiting resources assuming highly efficient agriculture, also resulting in theoretical estimates for K. The third method is based on the second method assuming a lower, more realistic agricultural efficiency. The third therefore results in more realistic estimates. Four spatial hydrological scale levels were considered to estimate food production. Also, nine scenarios were defined: a reference one reflecting the current situation, five others for the first method, two for the second method, and finally, one scenario for the third method. Results show severe limitations on food production by the availability of suitable land, water availability, and crop productivity for agriculture. We estimated theoretical values for K using land and water limiting resources separately. Two realistic scenarios considering realistic agricultural productivity and water use at national and local levels were assessed, resulting in 35.5 and 20 million people, respectively. These are alarming values compared to the current population of Iran (84 million). Moreover, our conservative estimations are still higher than any assessment when considering social, economic, or political barriers. This research provides a systematic analysis of carrying capacity in Iran, showing the importance of food import on Iranians' lives, relevant to land, water, and food policies.

Many developing countries face water deficit due to various reasons such as population growth, limited surface water resources, uneven spatial and temporal distributions of precipitation, industrialization, climate change, and lack of efficient management. This fact has led to a significant reduction in water resources, which has further caused water conflicts among the stakeholders. Hence, developing comprehensive water allocation policies to account for social standards, economic efficiency, and environmental sustainability is necessary. The objective of this study is to integrate the system dynamics simulation-optimization technique, and the Nash bargaining theory for optimal allocations of water resources. The proposed simulation, optimization, and conflict resolution modeling approach was applied for the joint allocation of surface water and groundwater among drinking, industrial, agricultural, and environmental sectors in the Najaf-Abad sub-basin in Iran. To obtain the Pareto front, the NSGA-II multi-objective optimization algorithm was used to maximize the water supply (i.e., minimize the water deficit) (objective function 1) and also minimize the groundwater extraction from the Najaf-Abad aquifer (objective function 2) over the entire operation period. The decision variables, the percentages of surface water and groundwater extractions, were determined for a set of optimal solutions. The optimum water supply (objective function 1) was 16.84 x 10(6) m(3) and the optimum reduction of the water table of the aquifer (objective function 2) was 0.63 m, representing an improvement of 30% over the existing condition. This study demonstrates the ability of the proposed simulation optimization-conflict resolution modeling approach and its applicability for water resources allocation. (C) 2021 Elsevier B.V. All rights reserved.

In the original paper, Zamani et al. (Nat Hazards 76:327–346, 2015. doi: 10.1007/s11069-014-1492-x) analyzed droughts in arid and semiarid lands based on minimum streamflow values. In that article, drought index values at 3-, 6-, 9-, and 12-month time scales were analyzed by the SDI index and L-moment method. This article points out some problems about the L-moment method, which are discussed and corrected in this discussion.

Water pollution is one of the major problems in providing and preserving water resources, so identifying the pollution source plays a critical role in regulation actions. Thus, this paper addresses the process of pollution source identification, including location, concentration, and the time of injection in surface water by using a data-mining method [artificial neural network (ANN)] and optimization techniques [genetic algorithm (GA) and pattern search (PS)]. The CE-QUAL-W2 numerical model is used to produce input and output data in ANN and simulation models. To check the capability of the methodology, the identification of various hypothetical examples of pollution with several forms of injection of the pollutant in a nonprismatic water canal is performed. Results of data-driven and optimization methods are evaluated by employing statistical criteria. Final results show that the ANN method is capable of identifying a pollutant injection hydrograph and it is relatively sensitive to the accuracy of monitoring so that like the optimization method for errorless data, the determination coefficient (R-2) is nearly 100%, and the absolute average relative error (AARE) and total error (E) are nearly zero. If there is more than one active pollutant injection source and evaluation of the pollutant concentration is accompanied with errors, the optimization method gives better results than ANN so that in pollutant sources and for errors of 5 and 10%, the statistic AARE in the optimization method is less than 3.7 and 5.7% while in ANN it is less than 10.1 and 14.3%. If not all of the pollutant sources are active, the optimization method can well identify the inactive source even in several levels of error, while ANN can only identify the inactive source if there is no error. (C) 2014 American Society of Civil Engineers.

Major water resources projects such as design of reservoirs, flood control facilities (dams, levees, etc.), and flood plain delineation/mapping require projection of peak flows with different return periods (recurrence intervals, e.g., Q50, Q100, and Q500). It is a common practice to use design flood (design hydrograph) when there are no data, or the available data are limited both in quantity and quality. In this paper, the L- Moment theory is used to estimate maximum precipitation for different recurrence intervals for the Rude Zard watershed in Khuzestan Province, Iran. The L- Moment is very suitable for frequency analysis of extreme (outlier data) values. In L- Moments analysis, linear combination of order statistics are used for outlier data because it is almost unbiased for small sample sizes. For this project, the Depth-Duration-Frequency relations were determined using the HEC-HMS model, and simulated flood hydrographs for different return periods were developed. Based on regional analysis of data, rain gauge stations were divided into two areas, each fitting a specific frequency distribution. The Generalized Normal Distribution (GND) was found to be more appropriate for area I, and the Generalized Pareto Distribution (GPD) for area II. The results of model simulations show that the simulated hydrographs except for the two-year return period have the same base time. Also, the time to peak for all return periods except for two-year, seem to about the same.

Data generation in ungagged basins is one of the most important topics in hydrology. Rainfall records usually have a longer record period than river flood records. Thus it seems logically possible to derive flood patterns from rainfall patterns using an appropriate mathematical model. Duration and temporal pattern of rainfall have a great impact on simulated peak flow which is inferred from the model. In this study, through integration of L-Moment theory and the HEC-HMS hydrologic model, the impact of duration and temporal pattern of precipitation with different return periods on peak flow was decided upon. According to the frequency analysis results, generalized logistic distribution was found proper for study area hydrometric stations. Then basin peak flow was simulated with the aid of HEC-HMS model and considering depth, duration, and temporal precipitation distribution. From comparison of simulation results with L-Moment regional frequency analysis, it was deduced that for a two-year return period, a precipitation duration between 12 to 18 hours is appropriate; and for 5, 10, 25, 50 and 100-year return periods, appropriate durations are 12, 9-12, 6-9, 3-6, and 1hour(s) respectively.