Estimating precipitation height in data-scarce regions is important for its wide application in water resource management-related topics. In this study, the performance of the Extreme Gradient Boosting (XGBoost) model was evaluated for predicting precipitation depth at short-term forecasting horizons, ranging from daily to 7-day averaged precipitation, in the Karkheh River Basin. For this purpose, three-hourly data on precipitation, air temperature, and relative humidity recorded at synoptic stations during the period from January 2001 to February 2024 were used. Then, data preprocessing steps were carried out, including completing missing data recorded by stations and removing outliers. Additionally, to consider the effects of precipitation, relative humidity, and air temperature from previous days on the current day’s precipitation prediction, time lags from one to seven past days were applied to the data and prepared as inputs to the machine learning model in seven different scenarios. Test section results showed that the prediction accuracy of the model increased with the use of more historical information; such that in the seven-day scenario, the model demonstrated more accurate precipitation time prediction with R² = 0.93, RMSE = 0.41 mm, and MAE = 0.19 mm compared to the one-day scenario, which had indices of R² = 0.46, RMSE = 1.13 mm, and MAE = 0.61 mm.
One of the key components of economic and social sustainability linked to water security is food security. Iran’s arid and semi-arid climate, along with a significant reduction in the country’s renewable water resources, has created challenges in the sustainable supply of food. Under such conditions, enhancing agricultural water productivity is an inevitable necessity, serving as a guarantee for the adequate and sustainable production of agricultural goods. This study analyzes the “National Spatial Planning Document,” the “Agricultural Productivity Enhancement Document,” the “Knowledge-Based National Food Security Document,” the “National Water Roadmap,” and the “Seventh Five-Year Development Plan,” compares them with relevant policy documents from other countries, and investigates the reasons behind the inefficacy of these policies. Qualitative analysis results indicate that the category of “weak governance and lack of institutional coordination,” cited in all reviewed documents, represents the most significant challenge, accounting for 32.02%. This is followed by “short-sighted policy approaches” (15.81%), “ineffective economic instruments” (15.61%), and “inadequate technical and informational infrastructure” (15.22%) all of which reflect structural and managerial barriers within the policymaking system. In contrast, categories such as “lack of financial resources,” observed in only four documents (1.19%), are relatively less critical. The findings highlight “weak governance and lack of institutional coordination” as the core factor underlying policy inefficiency, Indicating that any proposed solutions should prioritize targeted reforms of institutional frameworks and the enhancement of coordination among organizations.
In the present study, conducted with the aim of modeling groundwater quality, a method for calculating the spatial structure of data in the modeling process is proposed. This method considers the distance between observation points and the estimation point as one of the inputs to the model. The GBR, GPR, KNN, MLP, SVM, and RF models were utilized, and the models were trained and tested using groundwater quality data obtained from the Qazvin province in northwestern Iran. Specifically, data sets included 3,058 wells for 4 nearby observation wells, 2,724 wells for 5 nearby observation wells, 2,080 wells for 6 nearby observation wells, 1,364 wells for 7 nearby observation wells, and finally 631 wells for 8 nearby observation wells. Two separate data sets, comprising information from the first six months and the second six months of the year, were used. The average error (MAE), R-squared, Pearson correlation coefficient, and RMSE for models with four, five, six, seven, and eight neighboring wells indicated satisfactory performance of the Random Forest model. This model demonstrated very good performance in both the training and testing phases, exhibiting the lowest error and highest correlation. Although the complexity and execution time of this model may be higher, its high accuracy compensates for these drawbacks.
Sustainable water resource management requires establishing a balance in the water balance equation to achieve sustainable development goals. The study aims to examine the application of uncertainty and reliability of affecting indicators on water resource carrying capacity (WRCC) in the Qarnqou watershed using a combination of grey theory, entropy, and Z-numbers. A system dynamics (SD) model was developed to investigate feedback among the environmental, economic, and social subsystems. Ten indicators affecting WRCC were identified from the SD model, some of the indicators had a positive nature while others were inversely related. Identified indicators were weighted using a combination of Z-numbers in grey theory and entropy. Subsequently, WRCC values for the period 2000-2020 were extracted, and linguistic variables were applied to the obtained values. Results indicate a change in the WRCC status of the watershed from a poor (P) state in 2000 to a good (G) state in 2020, and in recent years, this good (G) status has been associated with fairly (F) reliability. To rank the indicators affecting WRCC, the Z-TOPSIS method was employed. The results show that the population indicator achieved the first rank, followed by environmental indicators such as agricultural land and evapotranspiration catch second and third ranks. The ranking obtained from the Z-TOPSIS method for the indicators is more consistent with the concept of WRCC. This study highlights the importance of integrating reliability and uncertainty based on linguistic variables in water resource assessments and enhances the innovative use of Z-numbers and grey entropy in managing water issues.
Recent advances in remote sensing have provided effective solutions to address data scarcity. This study estimates river discharge using the remote sensing-based geoBAM (geomorphologically-enhanced variant of BAM) algorithm, applied in both expert and unsupervised classification frameworks. The algorithm follows the McFLI approach and incorporates river geomorphological features. To obtain the initial dataset, river width information was extracted from satellite imagery, while the remaining hydraulic parameters were obtained from the HEC-RAS model. A total of 17 images of Landsat 8 as well as 78 images of Sentinel-2 from the 2017–2018 water year were used to analyze a non-braided and non-meandering section of the Karun River between Mollasani and Ahvaz. Time series validation of the estimated discharge result against observed data showed that Sentinel-2-based discharge estimates outperformed those from Landsat 8 in both classification modes (NSE values of 0.53 vs. 0.20 and 0.74 vs. 0.14 for expert and unsupervised modes, respectively). The improved spatial and temporal resolution of Sentinel-2 led to more accurate discharge estimation. Interestingly, the unsupervised mode yielded better results than the expert mode when using Sentinel-2 data, which may be due to a mismatch between predefined expert priors and the actual hydraulic characteristics of the study area.
This study investigates the role of social capital and women's participation in integrated watershed management within Aq Qala County. Employing social network analysis, the research focuses on two critical dimensions: trust and participation among local stakeholders. Data were collected through questionnaires distributed to 40 members of rural development councils across three target villages. Findings reveal that the structure of social networks significantly influences social cohesion and the effective management of natural resources. Villages exhibiting strong, reciprocal social ties demonstrated higher social solidarity, enhanced local collaboration, and more efficient transmission of indigenous knowledge. Conversely, communities with fragmented networks, heavily reliant on intermediaries, faced diminished cohesion and participation, complicating resource management efforts. Additionally, despite cultural constraints, women occupy central positions within trust networks and play a vital role in strengthening social cohesion and facilitating cooperation, whereas men predominantly act as intermediaries connecting wider networks. This gendered differentiation underscores the importance of leveraging the complementary capacities of both women and men in natural resource governance. The study highlights the critical need to incorporate gender dimensions into the social network structure to enhance participatory watershed management.
Water allocation approach is of crucial importance. The question therefore is: should it be a matter of centralised allocation, or competitive market is the better option? Despite the roots of this question in the history of economics, it remains a topic of interest to researchers specialising in the water market. In certain instances, this has resulted in a division of opinion among experts in the water sector. The present article, whilst formulating the problem from an economic perspective, examines the impact of altering the structure of the water market on demand, from a strong concentration to a competitive market. The research method employed reproduces the theory of microeconomic optimisation and the allocation of markets, with a focus on water as an economic good. The findings indicate that within a theoretical framework grounded in a select set of assumptions, a restructuring of the existing structure, characterised by a transition from a state of pronounced concentration and regulation to a competitive environment predicated on price discovery, is unlikely to engender an unambiguous and irrevocable impact on water demand. The final result is influenced by two key factors: the characteristics of the centralized system and the reliability of the assumptions selected during implementation. In the event of the centralized institution adopting a protective (water-friendly) approach, the results obtained are entirely different from those obtained from a strong suppression (water-hostile) approach.
In this study, the sustainability status of surface and groundwater resources in the Zayandehrood River Basin was evaluated using the Multivariate Water Resources Index (MWRI). This index integrates three key parameters—average precipitation, available surface water volume, and exploitable groundwater volume—calculated through the entropy weighting method. To provide a more detailed analysis of sustainability, three functional components of the system reliability, reversibility, and vulnerability were calculated for each sub-basin, from which the initial sustainability index was derived. The novelty of this research lies in the incorporation of the temporal trend of the water resources index, assessed using the Mann-Kendall test, into the base sustainability model, leading to the development of a modified sustainability index. Utilizing 20 years of data on precipitation, surface flow volume, and groundwater level fluctuations, a composite water resources sustainability index was formulated. The analysis included five sub-basins: Buein-Miandasht (upstream of the dam) and four downstream sub-basins Lenjanat, Najafabad, Esfahan-Borkhar, and Kuhpayeh-Segzi. Results indicated that only the Buein-Miandasht sub-basin, with a modified sustainability index of 0.31, is in an acceptable condition, while the other sub-basins demonstrated critically low values (less than 0.001), indicating unsustainable conditions. These findings are consistent with field observations and the significant reduction in water resources downstream of the Zayandehrood Dam, underscoring the urgent need for a revision in regional water resource management strategies. The application of the MWRI in this study provides an effective framework for the integrated assessment of water resource sustainability at the basin level.
In recent decades, the recurrent occurrence of destructive floods in the Kan basin, located in western Tehran, has highlighted the need for a more detailed analysis of the rainfall–runoff relationship. This study aims to investigate the statistical dependence between annual peak instantaneous discharge and the maximum daily rainfall on flood days over 24, 48, and 72-hour durations using copula functions. After assessing the correlation between variables with Kendall’s tau and Spearman’s rho tests, the best-fitting marginal and copula distributions among the Frank, Gumbel, Clayton, and Plackett models were selected based on the Cramér–von Mises test and AIC and BIC criteria. The results indicate that the Soleghan and Kiga sub-basins exhibit stronger rainfall–discharge dependence, and that increasing the rainfall duration from 24 to 72 hours enhances the likelihood of simultaneous occurrence of rainfall and flood events (joint return period). Moreover, conditional return period analysis reveals that exceeding critical rainfall thresholds significantly increases peak discharge and prolongs the conditional return period. These findings suggest that long-duration rainfall plays a decisive role in generating major floods, and that instantaneous rainfall intensity alone is not a sufficient indicator for flood hazard assessment. The proposed framework can serve as a practical tool for risk estimation, the design of flood control structures, prioritization of watershed management interventions, and the development of early warning systems in similar catchments.
Environmental responsibility and positive emotions, as key factors in shaping optimal consumer behaviors and management decisions, can have a significant impact on preserving and reducing water crises in different societies. This study aimed to investigate the effect of environmental responsibility, risk perception, and positive emotions on water conservation behavior. Using the correlation and causality method and structural equation modeling, the relationships between key research variables were analyzed. The statistical population was all urban water consumers in Tabriz, and data were collected through a questionnaire and analyzed with SPSS 26 and STATA 17 software. Based on the results, environmental responsibility and risk perception have a positive and significant effect on positive emotions, and positive emotions play a mediating role in promoting water conservation behaviors. Water conservation behaviors are the result of the interaction of psychological and social factors, and strengthening the sense of environmental responsibility and awareness of risks can strengthen positive environmental behaviors. Based on the results, several policy recommendations were made, including: creating public awareness campaigns, encouraging responsibility through financial and non-financial incentives, and promoting positive environmental behaviors through formal education, which can help improve environmental behaviors and reduce excessive water consumption.
This research investigates the significance of accurate water sales programs and the role of executive and supervisory bodies in the success of water markets in achieving their objectives. With the aim of evaluating the effects of establishing a water market in the Hashtgerd plain, under conditions of non-conformity between water exchange programs and regional circumstances, coupled with weaknesses in program updates and inadequate management and supervision 20 years after its launch, a Multi Objective Decision Making model (MODM) (focusing on reducing groundwater extraction and increasing economic profit) was developed in GAMS software and solved using the Augmented epsilon-constraint (AEC) method. The results indicated that in the absence of sufficient supervision and management, the water market leads to the development of certain industrial and agricultural activities (greenhouses and orchards) with higher profitability and lower water consumption. This, in turn, disrupts the balance of production in the region. Despite a significant increase in the region’s economic profitability (from 53.8 billion to 3,777 billion annually), the annual water withdrawal from groundwater resources increases from 227 to 288 million cubic meters. This is because market participants, motivated by greater profit, are disinclined to reduce their water usage. This study emphasizes the critical importance of active supervision and management in water markets. Failure to update water sales programs in line with upstream policies and the absence of necessary restrictions can lead to irreparable damage to water resources and exacerbate social conflicts. To ensure the success of the water market and the sustainability of water resources, recommendations are proposed, including the development of regional planning models, modernization of control equipment, continuous monitoring of market impacts, and the revision of regulations pertaining to existing villa-orchards in the region.
In this research, the water security index (WSI) in Tabriz city was evaluated using the PSIR (Pressure-State-Impact-Response) index. In this method, there are four main indices, and 56 sub-indices, all of which were evaluated. The values of the first three indices, i.e., pressure, state, and impact, were determined according to the relevant references and previous reliable research for Tabriz city. But, the value of the fourth index, i.e., the Response Index, is evaluated based on a qualitative approach via questionnaire and experts’ opinions in the field of water engineering. The findings indicated that the value of the Pressure Index (P-Index) for Tabriz city was 22.83 out of 100 (the value is dimensionless). Tabriz city scored 28.5 out of 100 in the Status Index (S-Index), 25 out of 100 in the Impact Index, and 30.92 out of 100 in the Response Index. Ultimately, the obtained results showed that the final value of Water Security Index (W-Index) for Tabriz was equal to 26.81 out of 100, which implied the poor condition compared to the values reported for ten other cities around the globe i.e. Amsterdam, Toronto, Singapore, Dubai, Beijing, Hong Kong, São Paulo, Nairobi, Lima, and Jakarta. Therefore, it is necessary for decision makers to use new scientific and practical methods to manage water insecurity in this city and reduce restrictions and impacts. Finally, it should be emphasized that the method used in this study represents a novel perspective in the perception of water security and its complexity. This method was efficient in analysing the Tabriz city water security, and it is recommended to use it for other cities in Iran.
The increasing population and limited water resources necessitate better water resources management. In many parts of the world, the establishment of an integrated water resources management (IWRM) process has been unsuccessful, and identifying issues and their solutions remains one of the main challenges of its implementation. Therefore, in recent years, addressing the challenges of water resources from the perspective of water governance has been raised. The water resources of Hashtgerd-study-area have experienced a sharp decline over the past few decades. In recent years, the groundwater level in this study area has decreased by an average of 92 centimeters annually. The aim of this research is to identify the network of issues in the Hashtgerd study area and provide a problem theory in order to lay the basis for designing management interventions to reform the local governance system and improve the water resources situation in this area. In this regard, the issues and obstacles to achieving the expected outputs and achievements of the water governance system in this area are investigated. For this purpose, 24 semi-structured interviews were conducted using the snowball-sampling-method. The collected data were analyzed by the method of inductive qualitative content analysis, and the conceptual model of Hashtgerd issues was explained. Some of the most important issues include land use change, lack of participation of users in water management, decrease in social capital and influence from the central government. These have created problems such as reduction in production and threats to food security, creating a sense of deprivation in farmers, reducing groundwater resources and insensitivity of landowners to the water issue.
This study presents a novel framework for assessing the Water Quality Index (WQI) by integrating data uncertainty into the calculations to enhance the reliability of water quality evaluations. The proposed framework, termed the Uncertainty-Informed Water Quality Index (UWQI), leverages advanced multivariate statistical techniques, including uncertainty-aware principal component analysis (UPCA) and Gaussian model, to account for uncertainty in WQI computations. Unlike traditional methods that treat data as fixed values, UPCA incorporates probability distributions over the data domain, enabling a more robust analysis. The UWQI framework was applied to data collected for eight key water quality parameters from 76 wells across three aquifers—Kahriz, Urmia, and Rashkan—within the Urmia Basin. Results revealed that ignoring data uncertainty significantly affected PCA outputs, sub-index weights, and overall water quality classifications. When uncertainty was incorporated, substantial shifts in quality categories were observed: wells initially classified as having excellent water quality were reassigned to good (3% increase) and medium (19% increase) quality categories. These shifts were primarily driven by data uncertainty influencing sub-index weights, with parameters such as pH, HCO₃⁻, and SO₄²⁻ exhibiting the highest levels of uncertainty and sensitivity, as indicated by coefficients of variation of 33.9%, 19.3%, and 19.2%, respectively. This study underscores the critical importance of integrating data uncertainty into WQI assessments. The proposed UWQI framework provides water resource managers with a more reliable and informed decision-making tool, supporting effective pollution control strategies and reducing environmental and public health risks associated with inaccurate water quality evaluations.
Karst groundwater resources in Lorestan Province (west Iran) are one of the most critical drinking water sources in the region. However, no comprehensive study has yet been conducted to assess their age and quality. To address this gap, the present research employs tritium isotopes (³H) and hydrogeochemical indices to analyze the relative age and quality of these resources. Twelve groundwater samples, including seven sulfurous, three non-sulfurous, and two saline samples, were collected in 2023 and analyzed for their ionic and isotopic compositions. Tritium data and chemical indicators (SO₄/Cl, Na/Cl, Mg/Ca ratios, EC, and major ion concentrations) were analyzed to determine relative age, origin, and mixing patterns. Piper diagrams, ion scatter plots, and saturation indices of calcite, dolomite, and gypsum were used to interpret geochemical processes and water-rock interactions. Results indicated that most groundwater samples are of modern age (tritium: 1.31–3.07 TU), with a few showing mixed modern–submodern characteristics. The dominant bicarbonate type reflects carbonate origin and recent precipitation recharge, while chloride-sodium (samples S6, S7) and sulfate-chloride-calcium types (samples W2, S2) suggest influence from the Gachsaran Formation or contamination. Notably, samples S6 and S7 exhibited high tritium and salinity, indicating rapid infiltration of recent rainfall into the Gachsaran Formation and localized salt dissolution. Furthermore, the characteristics of samples W2 and P1, including high SO₄/Cl ratios and elevated tritium concentrations, indicated potential contamination and the introduction of pollutants into the groundwater system. Samples W1, P2, and S3, characterized by simple ionic compositions and high tritium levels, represented young waters, whereas samples S1, S2, and S4, with more evolved ionic compositions and lower tritium concentrations, indicated mixed sources and intermediate behavior in terms of age and hydrochemical composition. Other samples, such as P3 and S5, with moderate SO₄/Cl ratios and tritium levels, lie at the boundary between young waters and mixed sources, likely influenced by mixing, surface recharge, anthropogenic contamination, or water inflow through faults.
To face the severe water scarcity in eastern Iran, a 1342-km pipeline project has been proposed to transfer 120 MCM/year from the Oman Sea to the city of Mashhad. Meanwhile, the region's substantial agricultural exports represent significant virtual water outflows. This study employs a water footprint framework to compare the proposed pipeline's costs (water volume, energy use, and financial expenses) with virtual water flows from agricultural exports, focusing on cucurbit crops as water-intensive and non-strategic products. Our analysis reveales that the region exports 257 MCM/year of virtual water through these crops- more than double the pipeline's proposed capacity. Moreover, their trades provide 0.55$ net profit per m3 with only 0.33 kWh electricity consumption, compared to the pipeline′s 3.2/m³ cost and 27.3 kWh/m³ energy demand. These findings underscore the need to prioritize alternative water management given that an investment of about 6.8 billion euros has been planned for the above-mentioned project.
One of the challenges in water resources planning and management is allocating water under scarcity, where available resources are insufficient to meet demands. In such cases, water allocation can be approached using bankruptcy rules. However, applying these rules to complex water resource systems requires addressing both the spatial heterogeneity and temporal mismatch between water availability and demands. In this study, optimal proportional bankruptcy coefficients are obtained using NSGAII-MODSIM multi-objective simulation-optimization model, specifically developed for the Sirwan-Diyala transboundary basin shared by Iran and Iraq. The model incorporates spatial and temporal variability of water development plans through the MODSIM decision-support system. Within the NSGA-II multi-objective optimization algorithm, the objective functions are the maximization of each country’s self-utility function. To evaluate the solutions, a stability index is utilized, measuring the distance from each country’s best allocation status. Results indicated that under the proposed allocation scheme, Iraq would need to reduce its agricultural water demand by 14%. Additionally, when temporal reliability for meeting agricultural demands is included in the objective functions, both countries must further reduce their agricultural demands by 9% and 62% for Iran and Iraq, respectively. The results also indicated that meeting the high agricultural demand in Iraq leads to ecological unsustainability on the Iraqi-side of the basin.
Water governance in Iran faces significant challenges, including institutional overlaps, fragmentation of responsibilities, and structural inefficiencies in integrated water resource management. The Seventh Five-Year Development Plan of the Islamic Republic of Iran provides a suitable platform for addressing structural gaps in water governance, promoting decentralization and advancing digitalization. However, despite the prominence of sustainable development principles in national policy documents, their practical implementation remains limited. This shortfall is attributed to the absence of causal mechanisms for translating policy solutions into actionable strategies, inadequate horizontal and vertical coordination within governance structures, and resistance to change within the entrenched bureaucratic system. Enterprise Architecture (EA) offers a structured framework for aligning organizational components including institutional structures, processes, information and communication technologies to achieve strategic objectives. The Zachman Framework, in particular, offers a systematic methodology for analyzing multi-dimensional governance challenges, breaking down complexity into manageable elements. This study examines the challenges and opportunities associated with implementing the Seventh Development Plan’s water governance objectives, analyzing Clause A of Article 38, Article 105 and Clauses B and C of Article 107 through the lens of EA. The main contribution of the study is a conceptual mapping of these legal provisions within the layers of the Zachman Framework to promote institutional alignment and scalable implementation in accordance with the legal mandates of the Seventh Development Plan.
Implementing groundwater management strategies from other countries is often ineffective due to the distinct characteristics of each plain. In volcanic–alluvial aquifers like the Ardabil Plain, effective groundwater governance requires a localized approach because of structural heterogeneity, significant secondary porosity, and sensitivity to climate variability. This study developed a tailored strategy for sustainable groundwater management specific to the Ardabil Plain. During the 2017–2018 hydrological year, the aquifer experienced an average water level decline of 0.57 meters and a storage deficit of 20.09 million cubic meters. In this study, to support targeted decision-making, the aquifer was divided into three management zones based on water level decline severity and surface–groundwater interactions. A MODFLOW-NWT model was developed, calibrated, and validated to simulate aquifer behavior. Management scenarios were designed initially based on reducing groundwater extraction. These were later refined to consider varying climatic conditions. A five-year planning horizon was adopted to account for the increasing unauthorized withdrawals and climatic shifts. Results indicated that under the optimal scenario—featuring respective 10 and 5 percent reduction in extraction in supercritical and critical zones—annual drawdown was limited to 0.4 meters and the storage deficit was reduced to 15.5 million cubic meters. This strategy not only alleviates pressure on the aquifer but also maintains agricultural productivity, promoting greater public acceptance of sustainable policies. The approach presented here offers a replicable framework for other regions facing similar hydrogeological and climatic challenges, supporting integrated policy development that balances environmental, economic, and social sustainability in water-scarce settings.
In recent years, the growing frequency of flood events and their associated damages has underscored the critical need to enhance flood risk management strategies, particularly in identifying flood-prone areas and assessing the extent of damage they incur. Recognizing the pivotal role of depth-damage functions in flood damage evaluation, this study focuses on Poldokhtar basin as a case study. It develops a regional model for estimating flood damage in residential areas while evaluating the potential of utilizing outputs from the WRF numerical weather model combined with HEC-HMS and HEC-RAS models to estimate hydrological, hydraulic, and damage components of flood. The study employs the WRF model for precipitation prediction, the HEC-HMS hydrological model for flood simulation, and the two-dimensional HEC-RAS hydraulic model for flood inundation simulation. The findings demonstrated that the WRF model combined with HEC-HMS and HEC-RAS models performs effectively in hydrological and hydraulic modeling, with minimal errors: approximately 1.47% in estimating peak flood discharge, 2.98% in simulating flood depth, and 1.93% in WSE. Additionally, the developed damage model exhibited strong accuracy, with a relative error of less than 10% in estimating flood damages in residential areas. The study also highlighted that improving spatial accuracy in calculating building areas and applying reconstruction/renovation cost coefficients for shallow floods resulted in more precise damage estimates. Integrating these models and methodologies into an online platform could serve as a comprehensive and practical forecasting system, offering significant value to researchers and policymakers at the national level. Such a system would play a crucial role in mitigating and managing flood-related damages.
