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In this study, we assessed the impacts of climate variations on streamflow in 28 near-natural catchments in Iran. To this end, we analysed the trend of annual streamflow, precipitation, and temperatures using the Mann-Kendall test and Sen's slope between water years 1982 and 2011. We evaluated the frequency of precipitation in different classes, i.e. below 5, 5–10, 10–15, and above 15 mm/day. Our results indicate a decline in streamflow at 25 catchments, at a rate of −5.66 to −0.19 mm/year. The annual precipitation amount did not decrease significantly, while the frequency of light precipitation events (<5 mm/day) increased. About 60% of the upward trend was significant. Mean temperature increased at all studied catchments, at an average rate of 0.055°C/year. In short, our results indicate that increases in temperature and the frequency of light precipitation events are two leading factors in streamflow reduction across studied catchments. [ABSTRACT FROM AUTHOR]

We assessed how climate change may impact the canopy hydrology of individual Pinus eldarica, Pinus brutia, and Cupressus arizonica trees planted in arid and semi-arid climates in Iran. Precipitation that reaches the forest floor as throughfall (TF) represents a significant portion of individual precipitation events (Pg). We used a nondimensional relative sensitivity coefficient to examine the sensitivity of TF to changes in Pg. The Coupled Model Intercomparison Project phase 5 (CMIP5) HadGEM2-ES product was used under two emission scenarios (Representative Concentration Pathway (RCP) 2.6 and 8.5) to project yearly precipitation and Pg for the measurement sites from 2020–50. There was a strong linear relationship between TF and Pg at all sites [TF = 0.6 (Pg) − 0.2; R2 = 0.9]. The arid P. eldarica trees showed the highest sensitivity coefficient (5.3) compared with semi-arid C. arizonica trees (1.6). The sensitivity coefficient approximately doubled for individual P. eldarica and C. arizonica trees in the arid climate relative to P. brutia and C. arizonica trees in the semi-arid climate. This suggests that TF under trees in the arid climate were more affected by changing Pg than in the semi-arid climate. Pinus eldarica trees planted in the dry climate exhibited the largest sensitivity coefficient differences (3.4) between small and large Pg. Changes in precipitation and increased smaller storm frequency are expected for arid and semi-arid regions. To buffer expected shifts in storm size due to climate change, it may be suitable to incorporate TF sensitivity when selecting trees for landscaping and urban greening. [ABSTRACT FROM AUTHOR]

Desiccation of the Namak Lake (NL) can result in the release of fine-grained dust contaminated with heavy metals, while there is little information available on the propagation of metals in the bed sediments of this lake. In this study, contamination of metals in the surface sediments of the NL was analyzed and the pollution status of sediments was assessed using geo-accumulation index (Igeo), enrichment factor (EF), the consensus-based sediment quality guidelines (CBSQGs), and mean probable effect concentration quotient (mPECQ). Results indicated that metal concentrations at the southern part were higher than at the middle and northern parts of the lake. Possible reasons are (i) pollution loads mainly entered the lake through the rivers at the west and northwest, but accumulated at the southern parts, (ii) hard layer of salt covering the bottom of the NL at the northern part suppresses adsorption of metals to the sediment, and (iii) the muddy nature of sediments at the southern part makes it easier for metals to be absorbed. EF results showed that sediments at the southern part of the lake were moderately enriched with lead (Pb). The low Igeo values suggested no pollution with the metals, and CBSQG values showed that the sediments of the NL were not toxic, while the mPECQ index suggested a toxicity probability of less than 25%. Cluster analysis classified the metals into two clusters. In general, the results showed that metal pollution in the surface sediments of NL was generally low although the concentration of Pb at the southern part of the lake was worrisome. [ABSTRACT FROM AUTHOR]

Although many studies have explored the effect of teleconnection patterns on floods, few investigations have focused on the assessment of expected flood damage under such large-scale atmospheric signals. This study aims to determine the effect of the most emblematic teleconnection, El Niño, on the expected damage due to floods with short return periods in the Kan River basin, Iran. To determine the flood damage costs, the median of annual precipitation changes (ΔP) during El Niño conditions was used, although ΔP cannot necessarily be transferred to extreme values. Then the flooded area was determined under the increased rainfall due to El Niño for 5-, 10-, and 50-year return periods. The results showed that El Niño has increased the annual precipitation by 12.2 %. Flood damage assessment using damage–depth curves showed that the relative increase in expected damage during El Niño conditions is much higher for short return period floods than that for long return period floods. In general, a 12.2 % increase in the annual precipitation would increase the damage by 1671 % and 176 %, respectively, for the return periods of 5 and 10 years. However, in the case of a 50-year flood, this increased percentile decreased to 52 %. These results indicate the importance of small flood events in flood management planning during El Niño. [ABSTRACT FROM AUTHOR]

The anthropogenic impacts of development and frequent droughts have limited Iran's water availability. This has major implications for Iran's agricultural sector which is responsible for about 90% of water consumption at the national scale. This study investigates if declining water availability impacted agriculture in Iran. Using the Mann‐Kendall and Sen's slope estimator methods, we explored the changes in Iran's agricultural production and area during the 1981–2013 period. Despite decreasing water availability during this period, irrigated agricultural production and area continuously increased. This unsustainable agricultural development, which would have been impossible without the overabstraction of surface and ground water resources, has major long‐term water, food, environmental, and human security implications for Iran. Plain Language Summary: Given the heavy reliance of the agricultural sector on water availability, it is important to examine if Iran's agriculture has been impacted by water availability changes in recent decades. The investigation of the long‐term impacts of natural water availability changes on agricultural activities in the country during the 1981–2013 period revealed that the agricultural sector in Iran continued to expand regardless of decreasing water availability in the country. This expansion was facilitated by the excessive use of nonrenewable water resources which has significant environmental and socioeconomic implications. Key Points: Trends in Iran's agricultural production and area did not follow natural water availability changes due to meteorological variabilityIran's agricultural production continuously increased despite water availability reduction during 1981–2013The unsustainable growth of Iran's agriculture has important water, food, environmental, economic, and human security implications [ABSTRACT FROM AUTHOR]

This study attempts to assess the validity of the Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG) products across Iran. Six IMERG precipitation products (IPPs) including early, late, and final runs for versions 05 and 06 were compared with precipitation data from 76 synoptic stations on a daily scale for the period from June 2014 to June 2018. According to the results, V05 performed better than V06, particularly in early and late runs. The IPPs overestimate precipitation ranging from 5% to 32%; however, IPPs tended to underestimate (overestimate) the amount of precipitation for wet (dry) areas and precipitation classes higher than 5 mm day−1 (less than 5 mm day−1). The probability of detection (POD) in IPPs was almost similar (with a median equal to 0.60), whereas other categorical validation metrics like false alarm ratio (FAR) improved in the final run. Our assessments revealed that the dependency of IPPs to the elevation was low, while the error characteristics of IPPs were strongly dependent on the climate and precipitation intensity. For instance, the systematic error varied between less than 12% in dry regions to more than 60% in wet regions. Also, according to modified Kling–Gupta efficiency (KGE) and relative bias (RBias), the performance of IPPs in winter with the highest KGE (ranging from 0.47 to 0.63) and lowest RBias (ranging from 0% to 16%) was better than other seasons. Further improvement is recommended in the satellite sensors and the precipitation retrieval algorithms to achieve a reliable precipitation source. [ABSTRACT FROM AUTHOR]

In this study, we corrected the bias in the Princeton forcing dataset, i.e., precipitation, maximum and minimum temperatures, and wind speed, by adjusting its long-term mean monthly climatology to match observations for the period 1988–2012 using the delta-ratio method. To this end, we collected meteorological data from 97 stations covering the domain of Iran. We divided Iran into three climatic zones based on the De Martonne classification, i.e., Arid, Humid, and Per-Humid zones, and then applied the delta-ratio method for each climatic zone separately to adjust the bias. After adjustment, the new datasets were compared to the observations in 1958–1987. Results based on four skill scores, including the Nash Sutcliffe efficiency (NSE), percent bias (PBIAS), root-mean-square error (RMSE), and R2, indicate that the adjustment greatly improved the quality of the gridded dataset, specifically, precipitation, maximum temperature, and wind speed. For example, NSE for annual precipitation during the validation time period increased from −0.03 to 0.72, PBIAS reduced from 29.2% to 6.6%, RMSE decreased by 182.44 mm, and R2 increased from 0.06 to 0.75. Assessing the results in different climatic zones of Iran reveals that precipitation improved more significantly in the Per-Humid zone followed by the Humid zone, while maximum temperature improved better in the Arid areas. For wind speed, the values improved comparably in the three climate zones. However, the delta values for monthly minimum temperature calculated during the adjustment time period cannot be applied in the validation time period, due to the fact that the Princeton climate data cannot follow the behavior of minimum temperature during the validation phase. In short, we showed that a simple bias adjustment approach, along with minimum observed station data, can significantly improve the performance of global gridded datasets. [ABSTRACT FROM AUTHOR]

• Reformulated Gash Analytical models (RGAM) applied for seven reforestations. • Models need frequent numbers of rainfall to estimate rainfall interception loss. • RGAM is advisable for predicting interception with small numbers of rain storms. • Ecohydrological parameters dramatically differs between studied stands. Modeling rainfall interception (I) is fundamental for understanding the forests' role in ecohydrological processes in local and regional scales. This research examines the Reformulated Gash Analytical Model (RGAM) applicability for estimating I in seven dissimilar plantations (Acer velutinum , Quercus castaneifolia , Pinus brutia , Picea abies , and Cupressus sempervirens L. var horizontalis) in the four reforested areas across the Hyrcanian temperate forests, northern Iran. Field measurements were performed from May-2012 to March-2014 for 167 distinct throughfall and gross rainfall observations. According to our results, the effects of inter-species variation on I value was evident, as P. abies might be the most excellent among the five frequently used tree species for planting project in temperate forests if the primary goal of plantation is to decrease erosion and surface runoff as it intercepted and evaporated more rainfall than other species. Our findings showed that in terms of average-based calculation, the mean of free throughfall coefficient (p) value in evergreen needle-leaved reforestations (0.47) was lower than those calculated for deciduous broad-leaved reforestations (0.59), and vice versa for the canopy storage capacity (S ; 1.85 mm vs. 1.36 mm, respectively), and mean of the ratio of evaporation rate to the mean of rainfall intensity during saturated canopy conditions ( E ¯ / R ¯ ; 0.45 vs. 0.38, respectively). The RGAM satisfactorily estimated I for all species (except for A. velutinum stand), because the estimation error of I was lower than 15% and the Nash–Sutcliffe efficiency was equal to or higher than 0.87. In conclusion, using data from a short time study period to derive canopy ecohydrological parameters as well as modeling I by the RGAM is advisable in reforestation areas across the Hyrcanian temperate forests and regions with similar forest and meteorological attributes. [ABSTRACT FROM AUTHOR]

• Unprecedented assessment of 44 gridded precipitation datasets for Iran. • In general, reanalysis products outperform satellite-based products over Iran. • A considerable discrepancy has been found between PERSIANN family products. • The ranking of the datasets is similar in both pointwise and pixelwise approaches. Global gridded precipitation datasets have been developed using rain gauges, satellite observations, and data assimilation techniques to fulfill the need in regions with a limited contribution of ground observations like Iran. This study presents a comprehensive evaluation of currently available precipitation datasets over Iran at monthly (44 datasets) and daily (34 datasets) time scales. To include the maximum number of datasets and in situ data, we consider two periods for the evaluations, namely 2003–2010 for the daily and monthly assessment and 2014–2018 for the daily. For the assessment, a network of more than 1500 rain gauges is utilized within 2003–2010 and 370 rain gauges within 2014–2018. Moreover, we compare the pixel-to-pixel (interpolated in situ data v.s. gridded datasets), and point-to-pixel (in situ data as a point v.s. gridded datasets) approaches in assessing datasets performances. In terms of the Kling-Gupta efficiency (KGE) parameters, the datasets perform worse in bias at monthly time scales and correlation at daily time scales. However, considering in situ precipitation above 5 mm/day, all datasets perform poorly in estimating precipitation variability. We find that, in general, reanalysis products have a higher KGE, ranging between 0.41 (0.21) and 0.91 (0.71), than satellite-based products with a KGE ranging from 0.14 (- 0.57) to 0.92 (0.57) over Iran at monthly (daily) scale. Moreover, GPCC overall matches the validation dataset better than other products over Iran's basins, whereas CPC, ERA5, and IMERG-Final are more suitable for near-real-time studies. Also, if latency is a top criterion, PERSIANN-PDIR will be the first option. Indeed, PERSIANN-PDIR with a KGE value of 0.69 (0.33) at monthly (daily) time scale within 2003–2010 performs remarkably well, as a non-adjusted real-time satellite-based product. The comparison between the point-to-pixel and the pixel-to-pixel approaches shows that the point-to-pixel approach underestimates the quality of the datasets but does not change the ranking of the datasets. [ABSTRACT FROM AUTHOR]

Global groundwater assessments rank Iran among countries with the highest groundwater depletion rate using coarse spatial scales that hinder detection of regional imbalances between renewable groundwater supply and human withdrawals. Herein, we use in situ data from 12,230 piezometers, 14,856 observation wells, and groundwater extraction points to provide ground-based evidence about Iran's widespread groundwater depletion and salinity problems. While the number of groundwater extraction points increased by 84.9% from 546,000 in 2002 to over a million in 2015, the annual groundwater withdrawal decreased by 18% (from 74.6 to 61.3 km 3 /y) primarily due to physical limits to fresh groundwater resources (i.e., depletion and/or salinization). On average, withdrawing 5.4 km 3 /y of nonrenewable water caused groundwater tables to decline 10 to 100 cm/y in different regions, averaging 49 cm/y across the country. This caused elevated annual average electrical conductivity (EC) of groundwater in vast arid/semiarid areas of central and eastern Iran (16 out of 30 subbasins), indicating "very high salinity hazard" for irrigation water. The annual average EC values were generally lower in the wetter northern and western regions, where groundwater EC improvements were detected in rare cases. Our results based on high-resolution groundwater measurements reveal alarming water security threats associated with declining fresh groundwater quantity and quality due to many years of unsustainable use. Our analysis offers insights into the environmental implications and limitations of water-intensive development plans that other water-scarce countries might adopt., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)