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Growing agricultural and domestic demand exacerbates water shortages globally, creating substantial environmental challenges, especially in lakes and wetlands ecosystems. This paper presents a stationary policy to restore and sustain the water level in natural lakes using a new version of hedging rule that accounts for time-dependent environmental demand and the water allocation to the agricultural and municipal sectors under different climate change projections. The proposed framework is demonstrated via operational policy derived to rehabilitate Lake Urmia in Iran. To simplify the modeling process, all reservoirs in the basin are replaced with an equivalent reservoir (ER) to allocate the available water between potential users. The ER is then operated using the set of hedging rules derived for staged restoration and sustainability of the lake level while meeting other stakeholder objectives. A system dynamics-based model is used to simulate the multi-sectoral system of the basin while using a built-in optimization algorithm to develop the most desirable multi-period operational policy. The lake-level condition is investigated by producing lake-level duration curves, while the reservoir performance indices (reliability, resiliency, and vulnerability) are used for assessing water supply in the basin. The results indicate that the proposed framework is highly effective in restoring lake level while meeting agricultural and municipal water demand in the basin. The proposed model provides a stationary policy for the lake restoration accounting for the dynamic variation of the lake level and fluctuations of the reservoirs inflow due to climate variability and change. [ABSTRACT FROM AUTHOR]

Holding a lasting balance between the water resources and water demands has become a challenging task for water resources managers, especially in recent years with the looming global warming crisis and its resulting climatic change effects. This paper focuses on modeling the optimized operation of the Zayandehrud Reservoir, located in west-central Iran, under two fifth-generation climate change scenarios called RCP4.5 and RCP8.5. A novel variant of the gravitational search algorithm (GSA), named the adaptive accelerated GSA (AAGSA) is proposed and adopted as the optimizer of the reservoir operation in this paper. The major advancement of the AAGSA against the original GSA is its high exploration capability, allowing the proposal to effectively tackle a variety of difficulties any complex optimization problem can face. The goal of the optimization process is the maximization of the sustainability of supplying the downstream water demands by the reservoir. The optimal results obtained by the original GSA and the proposed AAGSA algorithms suggest that the AAGSA can achieve much more accurate results with much less computational runtime, such that the proposed AAGSA is able to achieve the reservoir operation sustainability index of 98.53% and 99.46%, under RCP4.5 and RCP8.5 scenarios, respectively. These figures are higher than those obtained by the original GSA by 23.5% and 16% under RCP4.5 and RCP8.5, respectively, while the runtime of the proposal is reduced by over 80% in both scenarios, as compared to the GSA, suggesting the high competence of the proposed AAGSA to solve such a high-dimensional and complex real-world engineering problem. [ABSTRACT FROM AUTHOR]

Water quality models survey and predict changes in the water quality parameters with the optimized monitoring costs. The Gharasou River is the primary resource of water supply for the Karkheh River Basin (KRB), the third-greatest and most productive basin in Iran. This paper reviewed the estimation of water quality of the Gharasou River by W-ANN, QUAL2K, MPSIAC, WEPP, SWAT, SRM, AWBM, HBV, SDSM, and ANN models. The results of the QUAL2K simulation showed the rapid increases of BOD, TN, and TP in the Sahra Company site. The SRM and AWBM could simulate monthly runoff. The results also showed that the SWAT model simulated monthly runoff reasonably in some studies but weakly in another. Results indicated that W-ANN could estimate accurately EC (r = 0.996) and TDS (r = 0.999). The HBV model could simulate ETa reasonably in the KRB. The MPSIAC model estimated the erosion rates of 4.47, 16.60, and 18.57 t ha−1 yr−1in the agriculture area, rangeland, and forest, respectively. The WEPP model predicted the runoff accurately especially in the slope of 25%, but under-estimated soil erosion in the slopes of 35% and 45%. SDSM and ANN models showed a significant reduction of streamflow of − 3.7 and − 9.47 m3 s−1, respectively. While these models predict + 0.58 and + 0.48 °C increases in temperature, they forecast − 0.1 and − 0.4 mm decreases in daily rainfall, respectively. This review provides a more accurate and comprehensive picture of the Gharasou River Basin circumstances using publications that modeled water quality of the Gharasou River Basin, regarded as a basin-scale or sub-basin of the KRB. [ABSTRACT FROM AUTHOR]

For an effective reservoir operation during drought, the variations of both water supply and water demand which depend on hydrological and meteorological conditions need to be dealt with. This paper aimed to consider these variations in the Aharchay basin (Iran) by coupling a hedging rule (HR)-based reservoir operation model (HRROM) with a climate-based irrigation scheduling model (CBISM) at the farm level. Through the HRROM, optimal long-term decisions for Sattarkhan reservoir were made by considering the probable streamflow scenarios in the system. Given the variable agricultural demands (VAD) in the CBISM, the irrigation water was optimally allocated to the crops using several evapotranspiration (ET) scenarios. The CBISM employs three sub-models including linear programming (LP), nonlinear programming (NLP), and particle swarm optimization (PSO) to maximize the total income of the Aharchay agricultural network as a function of the climate factors and the supplied water. To this end, the daily weather and discharge data from 1990 to 2015 were used in this study. The standardized precipitation-evapotranspiration index (SPEI) and the streamflow drought index (SDI) were used to detect the meteorological and hydrological droughts, respectively. The SPEI was calculated based on the high-resolution-gridded datasets of the Climatic Research Unit (CRU). The findings demonstrated that the HRROM-CBISM generally managed to increase the time-based (αt) and volume-based (αv) reliability indices by 20% and 44%, respectively, compared with the conventional standard operation policy (SOP). For more investigations, the three major droughts of 2000–2002, 2004–2006, and 2008–2014 were separately analyzed. The average values of αt, αv, and vulnerability (V) for SOP were 0.33, 0.51, and 0.48, respectively. With the HRROM-CBISM, these values were about 0.5, 0.55, and 0.45, respectively. Among these indices, αt had the highest variations, while αv had the lowest variations in both the SOP and HRROM-CBISM approaches. The average water shortage for the mentioned droughts was significantly decreased from 89 (SOP) to 75 MCM (HRROM-CBISM). [ABSTRACT FROM AUTHOR]

Water and water management are no longer related to environmental studies. There is a very strong link between water and a state's security, as well as its survival and development. A decline in water availability may lead to a collapse or even the extinction of a whole civilization. Sometimes referred to as a "water‐bankrupt" state, Iran is a case that underlines the close relation between water and security, from the perspective of survival and opportunities for development. Without a doubt, the Islamic Republic of Iran is among those countries that are the most affected by climate change and low water levels. The main goal of this paper is to analyze challenges related to water in Iran, including the political, security, economic, and social dimensions. [ABSTRACT FROM AUTHOR]

Human interventions and climate change have caused significant alterations in the hydrologic response of several highly managed basins in Iran. One of these alterations is a considerable reduction in streamflow quantity, resulting in severe water supply insecurity. This paper presents an integrated modeling approach combining remote sensing, water balance analysis, reservoir operations, and water allocation policy evaluations. The approach helps in understanding of the relative contribution of anthropogenic factors in places where a major challenge is the lack of measured data for the historical time series of water withdrawals for agricultural development and water lost from the system through actual evapotranspiration (AET). Calibrated moderate-resolution imaging spectroradiometer (MODIS) remote sensing data of monthly AET (MOD16), modified Thornthwaite-Mather (M-TWM) water balance model, annual MODIS Land Cover Type (MCD12Q1) products (MCQD12Q1), mass curve analyses, and periodic analysis of water balance parameters were used to evaluate the contribution of anthropogenic factors and the effect of climatic impacts on the inflow time series for the Talvar Reservoir. The procedure led to an estimation of the naturalized series of the streamflow free of anthropogenic impacts; based on this, more plausible estimates of the basin's future water availability were determined, which were then used in a water evaluation and planning (WEAP) model for Talvar Reservoir operations and water allocations. The study yielded four main results. First, it was seen that there were two abrupt change points in the analyzed mass curves, in the years 1998 and 2007, dividing the study period (1988–2012) into three periods. Periodic analysis of water balance parameters showed that while climate change caused streamflow changes in postimpact period A (1998–2007), intensified human activities brought about streamflow changes in postimpact period B (2008–2012). Secondly, it was found that the naturalized series of the Talvar streamflow had a better correlation coefficient with precipitation than the observed series for river flow. Thirdly, despite the proposed approach lacking the use of some water balance components such as soil moisture and snow water equivalent, the percentage of unaccounted water content was between 5% and 10%, indicating good accuracy of the proposed approach as a tool for sustainable water resources management. Fourth, the WEAP model simulation results demonstrated that the unfavorable condition of the aquifer can be ameliorated by applying proper management policies. The results also showed that to increase water supply security and facilitate sustainability, a certain amount of reduction in ground-water withdrawals and agricultural areas is inevitable. [ABSTRACT FROM AUTHOR]

In recent decades, the depletion of surface water resources within the Lake Urmia Basin (LUB), Iran, has emerged as a significant environmental concern. Both anthropogenic activities and climate change have influenced the availability and distribution of surface water resources in this area. This research endeavors to provide a comprehensive evaluation of the impacts of climate change and anthropogenic activities on surface water resources across the LUB. Various critical climatic and anthropogenic factors affecting surface water bodies, such as air temperature (AT), cropland (CL), potential evapotranspiration (PET), snow cover, precipitation, built-up areas, and groundwater salinity, were analyzed from 2000 to 2021 using the Google Earth Engine (GEE) cloud platform. The JRC-Global surface water mapping layers V1.4, with a spatial resolution of 30 m, were employed to monitor surface water patterns. Additionally, the Mann–Kendall (MK) non-parametric trend test was utilized to identify statistically significant trends in the time series data. The results reveal negative correlations of −0.56, −0.89, −0.09, −0.99, and −0.79 between AT, CL, snow cover, built-up areas, and groundwater salinity with surface water resources, respectively. Conversely, positive correlations of 0.07 and 0.12 were observed between precipitation and PET and surface water resources, respectively. Notably, the findings indicate that approximately 40% of the surface water bodies in the LUB have remained permanent over the past four decades. However, there has been a loss of around 30% of permanent water resources, transitioning into seasonal water bodies, which now account for nearly 13% of the total. The results of our research also indicate that December and January are the months with the most water presence over the LUB from 1984 to 2021. This is because these months align with winter in the LUB, during which there is no water consumption for the agriculture sector. The driest months in the study area are August, September, and October, with the presence of water almost at zero percent. These months coincide with the summer and autumn seasons in the study area. In summary, the results underscore the significant impact of human activities on surface water resources compared to climatic variables. [ABSTRACT FROM AUTHOR]

This study examines the influence of human activities and climate variability on 86 dams and hydropower across Iran. The term 'mirage water' is introduced to estimate the impact of these factors on inflow. Data analysis shows that out of 1729 m3s−1 of mirage water, 705 m3s−1 are contributed by anthropogenic activities and 1024 m3s−1 by precipitation deficits. This indicates that some parts of Iran's strategic investments in water resources management over the past 60 years have failed. The study underscores the necessity for enhanced management practices and infrastructure investments to ensure sustainable water resources in arid and semi-arid regions. [ABSTRACT FROM AUTHOR]

The water shortage crisis is one of the main concerns that is threatening the biological security in Iran. According to available data and information, providing a framework for the assessment of water poverty in Iran seems crucial. The land-dividing unit in Iran is the province, and most of the governmental information is gathered based on this unit. In this sense, Isfahan province, which is one of the central provinces in Iran that is suffering from water crises, has been selected. The water poverty index (WPI), which is adopted in accordance with Iran's situation, including five components of resources, access, capacity, use, and environment, has been used for each of Isfahan's cities. "Capacity" and "use" has the greatest correlation, and it seems any advancement in water utilization for economic purposes might result in increased capacity, and vice versa. Also, there is a positive correlation between WPI and components of access, capacity, use, and environment. It can be interpreted that the lack of access to water services may be due to a lack of income or education. Finally, access, capacity, and use showed the strongest relationships between WPI and its subcategories. Therefore, these three elements should be the main focus of any initiative to manage the water poverty in Isfahan province. [ABSTRACT FROM AUTHOR]

The water level of the Urmia Lake Basin (ULB), located in the northwest of Iran, started to decline dramatically about two decades ago. As a result, the area has become the focus of increasing scientific research. In order to improve understanding of the connections between declining lake level and changing local drought conditions, three common drought indices are employed to analyze the period 1981–2018: The Standard Precipitation Index (SPI), the Standard Precipitation-Evaporation Index (SPEI), and the Standardized Snow Melt and Rain Index (SMRI). Although rainfall is a significant indicator of water availability, temperature is also a key factor since it determines rates of evapotranspiration and snowmelt. These different processes are captured by the three drought indices mentioned above to describe drought in the catchment. Therefore, the main objective of this paper is to provide a comparative analysis of drought over the ULB by incorporating different drought indices. Since there is not enough long-term observational data of sufficiently high density for the ULB region, ECMWF Reanalysis data version 5(ERA5) has been used to estimate SPI, SPEI, and SMRI drought indicators. These are shown to work well, with AUC-ROC > 0.9, in capturing different classes of basin drought characteristics. The results show a downward trend for SPEI and SMRI (but not for SPI), suggesting that both evaporation and lack of snowmelt exacerbate droughts. Owing to the increasing temperatures in the basin and the decrease in snowfall, drought events have become particularly pronounced in the SPEI and SMRI time series since 1995. No significant SMRI drought was detected prior to 1995, thus indicating that sufficient snowfall was available at the beginning of the study period. The study results also reveal that the decrease in lake water level from 2010 to 2018 was not only caused by changes in the water balance components, but also by unsustainable water management. [ABSTRACT FROM AUTHOR]

Water resources/reservoir management in developing countries attracts considerable attention due to growing human requirements and environmental concerns. The Seimare–Karkheh hydropower reservoir cascade, in the Karkheh River basin southwest of Iran, was studied. The impacts of changing reservoir operating water levels on hydropower generation and downstream environmental requirements were evaluated under different climate change conditions. For several years, the operating water level of Seimare reservoir was 704.5–720.0 metres above sea level (masl) (H1). Decision makers then adopted a different policy, with the operating range changed to 704.5–723.0 masl (H2). More recently, decision makers reduced the normal and minimum water levels so the reservoir now operates at 695.0–704.5 masl (H3). It was found that, for the period 2006–2050, based on H3, hydropower production would be reduced by 2.3–12.1% and 2.4–12.6% compared with policies H1 and H2, respectively. In 2051–2100, these reductions were found to be 5.8–11.2% and 7.7–11.3%, respectively. Furthermore, the results demonstrated that the current policy would substantially affect downstream hydrological alteration: 60–72% in Seimare River and 48–66% in Karkheh River for the period 2006–2050. The issue was found to be more pronounced in 2051–2100, with hydrological alteration of 68–73% in Seimare River and 59–66% in Karkheh River. [ABSTRACT FROM AUTHOR]

The impacts of climate change on the conjunctive use of surface water and groundwater resources of the Khorramabad basin were evaluated. Monthly temperature and rainfall modelled using HadCM3 and CGCM2 under greenhouse gas emissions scenarios (GHGESs) A2 and B2 were downscaled to baseline (1971–2000) and future periods (2040–2069 and 2070–2099). Simulations were performed for four climate change scenarios (CCSs) (A2-2040–2069, A2-2070–2099, B2-2040–2069 and B2-2070–2099). The projections indicated an increase in temperature and a decrease in rainfall. Future surface water resources were simulated using IHACRES. The results indicated that average annual runoff under GHGESs A2 and B2 would decrease by, respectively, 2.03% and 4.17% in 2040–2069 and by 6.64% and 8.94% in 2070–2099. Groundwater simulation was carried out using ModFlow. The results showed that under, the four CCSs, groundwater level would decline by 2.3, 3.0, 2.5 and 3.4%, respectively, relative to the baseline. Aquifer recharge under the four scenarios would decline by 1.43, 5.71, 2.86 and 7.14%, respectively. The results from IHACRES and ModFlow were employed to develop a conjunctive operation model with the Weap model. Several CCSs with various levels of future water demand were assessed using Weap. A 20% increase in water demand relative to the baseline, for instance, was projected to produce annual deficits in future agricultural water supply of 3.3, 5.08, 3.05 and 5.18 (× 106 m3), respectively, under the four CCSs. [ABSTRACT FROM AUTHOR]

Assessing the status of water resources is essential for long-term planning related to water and many other needs of a country. According to climate reports, climate change is on the rise in all parts of the world; however, this phenomenon will have more consequences in arid and semi-arid regions. The aim of this study is to evaluate the effects of climate change on groundwater, surface water, and their exchanges in Shazand plain in Iran, which has experienced a significant decline in streamflow and groundwater level in recent years. To address this issue, we propose the use of the integrated hydrological model MODFLOW-OWHM to simulate groundwater level, surface water routing, and their interactions; a climate model, NorESM, under scenario SSP2, for climate data prediction; and, finally, the HEC-HMS model to predict future river discharge. The results predict that, under future climate conditions, the river discharges at the hydrometric stations of the region may decrease by 58%, 63%, 75%, and 81%. The average groundwater level in 2060 may decrease significantly by 15.1 m compared to 2010. The results of this study reveal the likely destructive effects of climate change on water resources in this region and highlight the need for sustainable management methods to mitigate these future effects. [ABSTRACT FROM AUTHOR]

Snow is one of the most important climatic-hydrological variables that plays a vital role in watersheds. This importance is multiplied in Iran, as Iran is a warm country which is dependent on melting snow for the warm seasons. The purpose of this study is to monitor and project snowfall changes in Iran. To this end, we used two sources of data; the daily snow cover data of MODIS Terra satellite with horizontal resolution of 0.01 arc degree during the period of 2000–2019 for snow monitoring, and bias-corrected output of CMIP6 models under SSP scenarios for the period 2021–2100 with horizontal resolution of 0.5 arc degree for projection of snow cover. According to satellite data, spatial snow cover often occurs in the Alborz and Zagros altitudes with a snow boundary of 4000 m above sea level (MASL), and most snow cover occurs in January. The snowfall projection for the future period showed a significant downward trend at level of 0.05, the slope of which is steeper in the cold months of the year (December to February). Caspian Sea, Persian Gulf, and Oman Sea basins show a more decreasing trend of snowfall than other basins. Under a pessimistic scenario of SSP 5–8.5 in the period 2061–2100, snowfall will decrease by 6.8–7.4 cm in the Persian Gulf and Oman Sea basins for the high Zagros highlands in January. Due to the reduction of snowfall in the main basins of Iran, integrated watershed management is crucial in the field of water resources. [ABSTRACT FROM AUTHOR]

The study of water resources and reviewing periodic and spatial changes in the quality of water in aquatic ecosystems are of important necessity due to the reasons including, climate change, water resource constraints, and increased human water requirements. Given the fact that Koohsar Lake water in Zanjan Province is one of the sources of drinking water in the region, the present study aimed to measure the values of 19 parameters of water quality in two seasons of summer and spring at four stations. The samples were transferred to a laboratory under steady-state and sunlight conditions and analyzed according to the standard methods. Statistical analyses were performed using SPSS software. Moreover, the study applied factor analysis using principle components to analyze the variance of data. In addition, the values of the parameters were compared with the permissible limits of drinking water of national standard. The results indicated a significant difference between the parameters studied at stations and different sampling times by repeated measurements. The results of factor analysis also showed that the total of three main components in the summer and spring were 96.573% and 98.581% of the variance of data respectively. The main parameters in the summer included Chlorophyll-a, Na, DO, pH, BOD, COD, TDS, EC, and nitrate. Also, EC, TDS, alkalinity, pH, COD, BOD, Ca, and ammonia were found as the main parameters in the spring. Also, it was found that except for the pH in the spring and at stations 3 and 4 which were below the standard minimum, the lake water in both seasons and all stations, in terms of parameters, was within the standard range and exhibited a good quality for drinking. Implications are discussed in light of the study findings. [ABSTRACT FROM AUTHOR]

The water evaluation and planning (WEAP) approach and the invasive weed optimization algorithm (IWOA) are herein employed to determine the optimal operating policies in conjunctive (surface water/groundwater) systems for water supply in agricultural municipal/industrial (M&I) sectors under climate change. Climatic variables are simulated with atmospheric-ocean general circulation models (AOGCMs) under emission scenarios A2 and B2 during the baseline period 1971–2000 and the future periods 2040–2069 and 2070–2099 in the Khorramabad basin, Iran. The Hadley Centre Coupled Model, version 3 (HadCM3), and the Canadian Global Coupled Model, version 2 (CGCM2), produced superior temperature and rainfall projections, respectively, than other climate models. Under both emissions scenarios and during each future period, this study indicates an increase in temperature and a decrease in rainfall. Simulations of surface water with the IHACRES (Identification of unit Hydrographs And Component flows from Rainfall, Evaporation and Streamflow data) calibrated model shows a decrease in the future runoff. The Groundwater Modeling System (GMS) calibrated software projects a decrease in water level and a decrease in recharge under climate change scenarios. Simulation results from IHACRES and GMS are input to the Water Evaluation and Planning (WEAP) system to develop operational policies for the combined use of water resources., The water-allocation reliability of the system is estimated with the WEAP system for 24 scenarios reflecting climate change scenarios assuming increases in water demand, ranging from 10 to 60% in agriculture and from 20 to 30% in the municipal and industrial (M&I) sector. The IWOA is applied to optimize the conjunctive system of water resources (i.e., surface water and groundwater). The objective function is to maximize the system's water allocation reliability. The range of optimal water-allocation reliability changes is between 3 and 16%, with the lowest increase corresponding to the baseline period for agricultural water demand, and the highest rise corresponding to an increase of 50% in water demand under the B2 emissions scenario in 2040–2069 for the M&I water sector. [ABSTRACT FROM AUTHOR]

Extreme precipitation events such as floods and droughts have occurred with higher frequency over the recent decades as a result of the climate change and anthropogenic activities. To understand and mitigate such events, it is crucial to investigate their spatio-temporal variations globally or regionally. Global precipitation products provide an alternative way to the in situ observations over such a region. In this study, we have evaluated the performance of the latest version of the Global Precipitation Measurement-Integrated Multi-satellitE Retrievals (GPM-IMERGV6.0 Final Run (GPM-IMERGF)). To this end, we have employed ten most common extreme precipitation indices, including maximum indices (Rx1day, Rx5day, CDD, and CWD), percentile indices (R95pTOT and R99pTOT), and absolute threshold indices (R10mm, R20mm, SDII, and PRCPTOT). Overall, the spatial distribution results for error metrics showed that the highest and lowest accuracy for GPM-IMERGF were reported for the absolute threshold indices and percentile indices, respectively. Considering the spatial distribution of the results, the highest accuracy of GPM-IMERGF in capturing extreme precipitations was observed over the western highlands, while the worst results were obtained along the Caspian Sea regions. Our analysis can significantly contribute to various hydro-metrological applications for the study region, including identifying drought and flood-prone areas and water resources planning. [ABSTRACT FROM AUTHOR]

Different sensing methods provide valuable information for comprehensive monitoring strategies, which are crucial for the ecological management of lakes and watersheds. Subsequently, the resulting spatio-temporal information can be considered the fundamental knowledge for the water resources management of watersheds. Lake Urmia is deemed one of the most important aquatic habitats in Iran. It has been experiencing significant changes during recent years due to climate change, anthropogenic activities, and a lack of coherent management approaches. Hence, awareness of the hydro-ecological factors during the last few decades is critical for identifying the problems. In this research, the impacts of changes in key parameters such as precipitation, evapotranspiration, water surface temperatures, suspended sediment concentration, saline features, and vegetation are explored using satellite imagery. The primary purpose of this study is to evaluate the Lake Urmia crisis concerning human-involved and climate factors such as the agriculture sector and construction of the causeway. In this regard, a limbic-based Emotional Artificial Neural Network (EANN) is developed as a non-linear universal mapping and implemented for the first time to demonstrate the interactions between the considered hydro-ecological factors and the sensitivity of the two indicators the lake health. Providing a comprehensive spatio-temporal analysis is another objective of this study to detect the onset of deterioration in the parameters. The values of the efficiency criteria were measured to evaluate the sensitivity of the EANN models to the related inputs. The results of the model in scenario 4 with evapotranspiration, precipitation, runoff and vegetation as input variables led to higher performance with the best efficiency criteria, including DC = 0.868 and RMSE = 0.096. The quantitative results confirm that the combination of both climate and anthropogenic factors, including the agricultural sector's overdraft, leads to the most efficient EANN model and, consequently, is considered the leading cause of the crisis. [ABSTRACT FROM AUTHOR]

Climate as one of the key factors in water resources management affects the amount of water in the hydrological cycle, which subsequently impacts the level of water availability. Considering the challenges that the South Alborz Region, Iran is currently facing in supplying water for various consumers; in this study, the climate change adaptation scenarios are investigated for sustainable water supply and demand. This study uses a procedure in which five different adaptation approaches, under RCPs scenarios, were established using the WEAP model to assess the impacts of various adaptation strategies on increasing the balance between water supply and demand over current and 2020s accounts. The findings suggest an imbalance between supply and demand in the current situation with the greatest imbalance in domestic use while the minimum in the industrial sector. The results of assessing adaptive scenarios show that various scenarios have different effects on balancing the water supply and demand by different consumers; on the other hand, the scenarios that directly affect domestic water demand have the greatest effect on minimizing the gap between supply and demand in the region; therefore, the options for decreasing the population demand along with diminishing the losses in the domestic water distribution network are the most effective alternatives for balancing supply and demand under all of the climate scenarios. The findings of this research indicate that adaptive management with the focus on restricting demand helps actively management of water resources in the regions with scarce water resources. [ABSTRACT FROM AUTHOR]

In arid and semi-arid regions of the world, the occurrence of prolonged drought events (megadroughts) associated with climate change can seriously affect the balance between water supply and demand, thereby severely increasing the susceptibility of such regions to adverse impacts. In this study, a simple framework is introduced to estimate renewable water volumes (RW) to mitigate the challenges of megadrought events by managing the groundwater resources. The framework connects a weighted annual hydrological drought index (wSPEI) to RW, based on the short time-scale precipitation volume. The proposed framework, which was in a proof-of-concept case study applied to the Neishaboor watershed in the semi-arid part of Iran, showed that developing the weighted drought index can be valuable to estimate RW. The results suggested that the wSPEI, aggregating hydrological drought index (HSPEI) with the time scale k = 5 days and the regional coefficient s = 1.3 can be used to estimate RW with reasonable accuracy (R2 = 0.73, RMSE = 11.5 mm year−1). This indicates that in the Neishaboor watershed, the best estimation of RW can be determined by precipitation volumes (or the lack thereof) falling over 5-day aggregation periods rather than by any other time scales. The accuracy of the relationship was then investigated by cross validation (leave-one-out method). According to the results, the proposed framework performed fairly well for the estimation of RW, with R2 = 0.75 and RMSE = 12.2 mm year−1 for k = 5 days. The Overall agreement between the wSPEI, the RW derived from water balance calculations, and the estimated RW by the proposed framework was also assessed for a period of 34 years. It showed that the annual RW followed closely the wSPEI, indicating a reasonable relationship between wSPEI and the annual RW. Accordingly, the proposed framework is capable to estimate the renewable water of a given watershed for different climate change scenarios. [ABSTRACT FROM AUTHOR]

Water plays a quintessential role in the lives of individuals and communities. In recent decades, population growth, migration from rural to urban areas, industrialization, and climate change have increasingly jeopardized the sustainability of cities, especially in developing countries, including Iran. The purpose of this study is to assess recent and future perspectives for urban water security in Iran. To do so, the paper extends previous water security studies within the region by collecting data on urban water security from a cohort of cities rather than a single location. To assess the state of water security in the recent past, from 2013 to 2019, we introduce a dedicated framework comprised of five dimensions and twelve indicators. In estimating future water resources for Iran in the period up to 2100, ensemble-based hydro-climatic regional climate model projections for RCPs 4.5 and 8.5 were analyzed in time and space. The results show that four of the five dimensions of present-day urban water security, including accessibility, availability, water health and sanitation, and the economic value of water, all demonstrate general improvements in water-related urban infrastructure, whereas the environmental indicator depicts a decreasing trend. Future projected trends for Iran's hydro-climate show a general decline in its net availability from already scarce conditions and also increased variability due to climate change. In general, the study indicates both advances in Iran's urban water security recently and severe implications for future water availability in certain regions and periods in the decades to come. The study also advises policymakers to seek to mitigate the water crisis in so far, as also enforced by climate change, by increasing the appropriate infrastructure and using new technologies in the water and wastewater industry. [Display omitted] • A new and recent data set on urban water security indicators in Iran was analyzed. • Twelve indicators formed the novel and combined urban water security index. • Four out of five water security dimensions showed progress during 2013–2019. • The urban water environment dimension showed a declining trend. • Projected future water recourses in Iran is under increasing pressure towards 2100. [ABSTRACT FROM AUTHOR]

Variation in climatic parameters affecting water access can play a key role in the sustainable development of agriculture and the environment. Reference evapotranspiration (ET0), after precipitation, is the most important parameter affecting access to water resources in the arid and semiarid areas like Iran. In this study, data were collected from 50 synoptic weather stations for a period of 30 years (1988–2017) in the area with high population density and critical agricultural regions of Iran. Trend analysis of ET0 and climatic parameters including maximum and minimum temperature (Tmax and Tmin), sunshine duration (SD), relative humidity (RH), wind speed (WS), and air pressure (P) were investigated. Also, the effects of climatic parameters on ET0 were analyzed using dimensionless sensitivity coefficients. The aridity index (AI) was also evaluated using precipitation and ET0 data in the study area. Results showed that on an annual time scale, ET0 had a significant increasing trend (p ≤ 0.05) in 77.1% of the studied stations. In the seasonal time scale, the most increasing trend of ET0 was observed in winter. The results of sensitivity analysis showed that Tmax, RH, and WS were the most effective variables on ET0. The trend analysis of AI revealed that 92% of the stations had a significant (p ≤ 0.05) increasing trend over the study period. The spatial distribution of the annual AI indicated that only 10% of the study area meets the atmospheric evaporation demand, and in 90% of the study area, the annual ET0 was greater than the annual precipitation. These areas were highly affected by aridity and thus required additional water for crop production. These results indicated that climate change in Iran has increased ET0 and aridity, thereby increasing the water requirement for plants in agricultural lands. Hence, the optimum use of water resources for agricultural purposes is a suitable way to deal with the crisis of water shortage and aridity in Iran. [ABSTRACT FROM AUTHOR]

Climate change influences the agricultural sector by reducing available water resources, thereby influencing income, consumer and producer surplus, and crop prices. So, it is necessary to have a comprehensive integrated method to measure the effects of these changes on natural resources and social conditions. The present study aims to use the positive mathematical programming method to discover the trend and conditions of groundwater resources, agricultural water use, food security, and economic welfare of the agricultural sector in Iran. To this end, data for the period 2000–2015 was used under four different scenarios of normal climate change, climate change, climate variability, and concurrent climate change The results showed that the mean agricultural water use will amount to 35,103.6, 26,533.8, 35,216, and 26,510.7 million m3 and the mean decline in the reserves of aquifers will amount to 4422.22, 11,165.6, 4438.25, and 11,267.4 million m3 under the scenarios, respectively. With respect to food security, the net farm revenue will be 314,560, 248,753, 315,427, and 248,574 billion IRR, respectively. The mean crop price per ton will reach 905.3, 1141.8, 904, and 1142.8 million IRR, respectively. The mean consumer surplus will be 172,107.7, 166,450, 172,024, and 166,403 billion IRR and the mean producer surplus will be 419,959.2, 395,380, 419,751, and 395,204 billion IRR, respectively. Based on the results, to reduce the adverse impacts of climate change on different studied aspects, it is necessary to change policymaking in the water and agricultural sectors, especially regarding the shift from traditional agricultural water allocation to its market-based allocation and to change planting pattern. [ABSTRACT FROM AUTHOR]

Climate and climatic variables are very important factors in grape growth. Usually, temperature variables (maximum, average and minimum), as well as precipitation variables (annual, monthly and daily), are used to determine the regional climate and to study the type and amount of climate change. Most of the viticultural climatic indices presented by researchers have been using the above variables. Northwestern and western regions of Iran are considered as the most important areas of grape cultivation with different climatic conditions in different parts that have led to the cultivation of grape cultivars. In this study, five temperature indices (Huglin, latitude-temperature, night cooling, temperature variability and Winkler) and two precipitation indices were investigated based on De Martonne and hydrothermal drought indices. Then, they were analyzed by Mann-Kendall method and Sen's slope estimator index. The studies showed significant positive trends in Huglin, Winkler, night cooling and latitude-temperature indices, while the temperature variability index is significant only in a few stations. On the other hand, the indices related to drought and hydrothermal show no trend. However, some southern stations in the region showed a different trend in some indices. As a result, the trend of changes in temperature indices can lead to the expansion of cultivation of grape cultivars in the coming years, although the limitation of water resources will be a negative factor. [ABSTRACT FROM AUTHOR]