بهرام ثقفیان

In Iran, due to warming and severe precipitation variation along with development in recent decades, more attention should be paid to comprehend the role of climatic factors in water resources. Therefore, this study aims to analyze the trend and heterogeneity of the climatic variables as well as their impact on hydrological processes.

Material and Methodology :

The stations with long-term data were analyzed for trend analysis (Mann-Kendall tests) and homogeneity (Pettitt test) of climatic variables in a 30-year statistical period (1984-2014). The impacts of climatic variables on the basin's runoff were investigated using the Soil and Water Assessment Tool (SWAT) for two climatic time periods (1984-2001 and 2001-2014).

The homogeneity investigation in the stations demonstrated that only in Soleiman Tangeh Station, the year 1998 was determined as the turning point. This case was not observed in other stations. Regarding the investigation of temperature associated with Gharakhil station, the turning point was obtained in 1997 and the trend was increasing and meaningful. The results of the coefficient of determination and Nash-Sutcliffe achieved from the calibration and validation of the SWAT were quite satisfactory.

In general, climate change over the past three decades has led to decline in the runoff of the basin, which may be partly due to the increased evapotranspiration as a result of increased temperature or reduced precipitation in most months. The present study attempts to indicate the significance of climate change and its consequences in the water resource management of the Tajan basin.

Given the application of hydrological response in a watershed, various methods have been used to determine this response and the results have shown a high degree of accuracy and accuracy variability depending on the data used. By reviewing and summarizing the results of research carried out in the modeling of rainfall-runoff, particularly the time-area method, it was found that in most of these studies, the concept of watershed time concentration was used, which in most of the formulas used, the physical properties of the watershed were used and the dependence of time concentration on rainfall conditions was not studied. Therefore, this study was conducted to evaluate these methods using the kinematic wave method in the GIS environment, the HEC-1 method, and optimization methods using genetic algorithms in a V-shaped experimental watershed.

Observational data available in the V-shaped experimental watershed of the University of Illinois was used for rainfall-runoff modeling. The studied watershed had an impermeable aluminum surface and two uniform side sheets with a one-sided slope towards the channel with a constant value of 1%. In addition, a central channel with a one-sided slope towards the outlet of the watershed with a constant value of 1% was present. The roughness coefficient in this watershed was determined based on trial and error at 0.014.

After preparing the time-area histogram of the watershed using each of the mentioned methods, the corresponding outflow hydrographs of the watershed were determined. Then, the results were compared with observational data, and various components of the computational hydrographs were also examined. The results showed that the performance of the genetic algorithm in determining the peak time of the hydrograph with a 15% relative error was better than the performance of the kinematic wave and HEC-1 models. Additionally, the genetic algorithm model had the highest correlation coefficient with observational hydrographs with an average Nash-Sutcliffe Index of 0.968 and an average correlation coefficient of 0.983. Furthermore, by fitting the curve to the modeling results, an equation was obtained to determine the equilibrium time of the watershed relative to rainfall intensity, with a determination coefficient of 0.999. This equation expresses the inverse relationship between equilibrium time and rainfall intensity (with a power of 0.33), i.e., doubling the rainfall intensity reduces the equilibrium time by 20%. Finally, the coefficient of the equation determining the equilibrium time for this watershed was found to be 495.2, and for each rainfall intensity, its corresponding equilibrium time can be calculated with high accuracy.

In this study, under experimental watershed conditions, rainfall-runoff modeling was performed with three categories of events and three categories of different rainfall durations, each event category having four different rainfall intensity sizes. Corresponding hydrographs were obtained for each event by examining the computational hydrographs and comparing them with observational hydrographs, and it was found that the three models had one to two percent relative error in determining the maximum runoff, but in determining the time to reach the hydrograph peak, the kinematic wave and HEC-1 models had an average error of 44%. Finally, using the correlation and Nash-Sutcliffe coefficients, it was determined that the computational hydrographs produced by the genetic algorithm method were closer to the observational hydrographs and had a higher degree of correlation. It is worth mentioning that in this experimental watershed, the dependence of equilibrium time on rainfall intensity in impermeable conditions was confirmed. It is recommended that the effect of infiltration or changes in surface roughness and the determination of the dependence size be investigated.

In the goals of the United Nations for the sustainable development of societies in the third millennium, the approach of water and food nexus is considered one of the important interdisciplinary perspectives in the direction of the dynamic balance of production and consumption of resources. Due to the consumption of more than 90% of the country's water resources in the agricultural sector, access to accurate statistics of this field is vitally important in creating a balance between water production and consumption in the water-food nexus approach. In such a way, the presentation of incorrect statistics or statistics with many errors, especially by official authorities, by entering into different models developed by researchers, will lead to distorted results, wrong decisions and ultimately economic and environmental damages and social tensions. In this research, with the approach of using the connections of ecosystems, water-food nexus was investigated; Thus, the correlation between the presented statistics of the production sector and the water consumption sector was analyzed by using water-food nexus with the method of uncomplicated calculations. Based on the information, the inconsisitency of the statistics provided by different departments is evident. According to the statistics of crop production in 2014-2015 and 2019-2020, the undercultivated area in the agricultural sector in 2019-2020 has grown by about 1% compared to 2014-2015, and in 13 provinces the undercultivated area has increased and in other provinces the undercultivated area in the agricultural sector has decreased. Water consumption in the agricultural sector has grown by about 10%, so that in 23 provinces, water consumption in the agricultural sector has increased and in 8 provinces, water consumption in the agricultural sector has decreased. This difference is due to the change in the cultivation pattern and the crop selected by farmers in the country. Also, according to the amount of programmable water that has been announced by the Ministry of Energy, in 12 provinces, the amount of programmable water is not enough to meet the Pure water consumption for crops, and even in some provinces, the amount of programmable water is only enough to supply garden products. This important and basic finding implies and emphasizes the need to solve the problems of statistics of different authorities of the country.

The construction of check dams in the branches is one of the common methods of watershed management to control sedimentation, watercourse stability and reduce the flood hydrograph from the time of concentration and peak flow. In Iran, despite being 50 years old, in the wide implementation of this small-scale structure by the bodies affiliated to the country's Natural Resources and Watershed Management Organization as an executive body, a suitable quantitative and qualitative evaluation method has not been provided. In expressing the effectiveness of this structure, it is inevitable to simulate natural conditions in the presence and absence of this structure in hydrological and hydraulic models. Of course, field visits and measurement of the relevant parameters in the field are also considered to be primary measures in the verification of the simulation and the approximate expression of the effectiveness. The investigations showed that in many researches, the effect of correction dams on the runoff hydrograph has been considered. Simulation of the dams has been done hydrologically with changes in the slope of the waterway and basin time concentration or by using the method of routing in the reservoir that according to simplified hypotheses, estimates more than reality. Hydraulic simulation is more precise but has its own complexity and obstacles. Therefore, in this study, we tried to apply the effectiveness of improving check dams in runoff hydrograph by using both the accuracy of hydraulic simulation and the lack of complexity of hydrological relations. The effectiveness of check dams is computed by determining and applying coefficients in the waterway output hydrograph without improving check dams to obtain the waterway output hydrograph with check dams.

In this research, the effectiveness of successive check dams in reducing the output hydrograph of a triangular channel with three lengths of 1000, 2000 and 3000 meters in three longitudinal slopes of five, 10 and 15%, using the MIKE 11 hydrodynamic model, is considered. In this study, it is assumed that series check dams with a height of 2.5 meters will be constructed in each triangular canal, therefore, the number of check dams will vary from 20 to 180 based on their length and slope. In this study, the output hydrograph of the triangular channel was considered as the dependent variable, and the input hydrograph, channel length, and channel slope were considered as independent variables. Variations of  outflow hydrograph peak discharge were investigated under two scenarios. The first scenario for the condition where the channel is without improving check dams and the second scenario for the case where the channel was studied with full of sediment series check dams in order to simulate the effectiveness of the dams in a waterway with hydrological parameters. Two criteria were defined to express effectiveness: the percentage of the intensity of hydrograph routing and the percentage of flow discharge change. The percentage of changes in peak discharge of the hydrograph is determined in relation to the peak discharge of the inlet hydrograph. In other words, "attenuation coefficient" was named based on the difference between inlet and outlet discharge for the scenario and for changes in length of waterway, slope and different amounts of inlet hydrograph. The percentage of change in peak flow discharge from the second scenario compared to the first scenario was also considered as the percentage of flow discharge change.

Evaluation of the model results for hydrograph routing along the channel in exchange for changing independent variables in the form of two scenarios resulted in decreasing peak flow, increasing the base time of output hydrograph, and delayed time due to trending. The existence of check dams has doubled the change in the mentioned parameters. As the longitudinal slope of the waterway increases, the amount of storage in the canal decreases, and the output discharge and therefore the intensity of the routing (decrease in peak outflow relative to the inlet). Increasing the volume of inflow decreases the intensity of the routing. Routing intensity has an inverse relationship with longitudinal slope and has a direct relationship with channel length. Increasing the number of check dams increases the amount of storage in the canal and as a result, slope reduction occurs and the changes in output discharge are greater than inlet flow. Therefore, the intensity of routing increases. The main purpose of this study was to determine the effectiveness of improving check dams in reducing peak discharge of ouflow hydrograph from a triangular channel based on different conditions using a mathematical model. After performing various simulations and investigating different methods, it was observed that the effects of improving check dams on a outflow hydrougraph can be modeled as the effect of a linear reservoir with a lag time at the end of the channel. In other words, two linear reservoir function and a lag time function are applied to independent variables to obtain the dependent variable. For both output hydrographs obtained in the channel without and with improving dams, K values were estimated as linear reservoir function and TL as  lag time function. The average storage coefficient (K) of the linear reservoir was estimated 500, 1100 and 1400 seconds respectively for lengths of 1000, 2000, and 3000 m and for three slopes. The mean lag time for the three mentioned lengths was 540, 1750, and 3700 seconds, respectively. As the length of the channel increases, the slope of the canal, as well as the inflow to the canal, as well as the inflow to the canal decreases, and the amount of the above parameters and therefore the attenuation coefficient increases.

If a stream is selected for the construction of improving check dams and the output hydrograph is available using empirical, hydraulic, and hydrological models in the absence of check dams, the outflow hydrograph from the stream will be simulated and modified for the existence of small-scale structures by applying the linear reservoir storage coefficients and the lag time obtained from this research. In this way, the effectiveness of the construction of improving check dams in flood control will be achieved in the mentioned waterway.

Runoff production is due to watershed response to rainfall event. Various researches have been performed in order to accurately determine the watershed response. In most response models, as in kinematic wave-based models, require detailed input data such as cover characteristics, slope, initial moisture, and soil infiltration properties. In this study, a time-area histogram extraction technique was presented via genetic algorithm optimization and deconvolution methods and results were evaluated in theoretical and real watersheds. In the model presented, a set of rainfall-runoff events in matrix form were called as inputs while the corresponding time-area diagrams were extracted. The results showed that the accuracy of the model in estimating the response of a theoretical watershed was 99%, while similar accuracy in direct approach was 74%. The accuracy of the model in estimating the response of the V-shaped geometric watershed and the real Walnut Gulch watershed reached an average of 99%. Therefore, the model introduced in this research is effective in determining the time-area diagram of the V-shaped watershed and may be used in other basins.

Hydrological response is one of the most important issues in watershed studies. Various researches have been performed in order to determine the hydrological response, including the kinematic wave model, and the results indicate the advantages and disadvantages of the models. In this paper, the numerical and analytical methods of solving the kinematic wave equation were investigated and the results were evaluated in a laboratory watershed. So, the finite difference method was used in the framework of HEC-HMS software, and to evaluate the analytical method, by the kinematic wave equation and using GIS software, the flow routing in the laboratory watershed were investigated. The results of the two mentioned methods were placed next to the results of the time-area method in the HEC-1 model, and finally the results of these three methods were compared with the observational results of the rainfall-runoff events in the laboratory watershed. The error of the kinematic wave analytical model, the kinematic wave numerical model and the HEC-1 model in determining the maximum flow rate, according to the relative error index, was about one percent. Also, according to Nash-Sutcliffe index, the kinematic wave analytical model had the best performance with a value of 0.926 and the numerical solution of the kinematic wave with a value of 0.838 was weak compared to the other two models in derivation of the hydrograph. However, the regression index of the HEC-1 model was 0.944 and analytical method with a value of 0.932 ranked second, and the numerical model of the kinematic wave with a value of 0.899 was ranked third.

Seasonal precipitation forecasting plays a pivotal role in water resource management and development of warning systems. This study evaluated the ensemble forecasts of three C3S models over the period 1993–2017 in Iran’s eight classified precipitation clusters for 1- to 3-month lead times. The quantile mapping (QM), the linear scaling (LS), and the gamma distribution mapping (GDM) for post-processing of precipitation forecasts, and the LS and variance scaling (VS) was used to post-process temperature forecasts. The results were then compared with the raw forecasts. It is indicated that the models performed best in western precipitation clusters, while in the northern humid cluster the models had negative skill scores. Almost all the post-processing methods were able to reduce the errors and improve the forecast accuracy in most groups. In general, after post-processing the ECMWF models had the best performance and the MF model had the worst performance. Among the precipitation post-processing methods, GDM and LS performed better, and the superiority of these methods is quite noticeable, especially in the rain-heavy groups of northern Iran (G6 and G8), which had poor raw forecasts. Regarding the post-processing of ensemble temperature forecasts, the performance of each LS and VS method is similar, they have a slight difference in increasing the accuracy of forecasts. Of course, overall, the VS method has worked a little better. The performance of post-processing methods is very effective in the cold months of the year (late autumn and winter) and slightly weaker in the hot months (summer).

The use of temperature and precipitation data from the NASA Earth Exchange Global Daily Downscaled Projections dataset (NEX-GDDP) is increasingly expanding as one of the products derived from the global climate models. Investigating the quality of this product’s precipitation data in Iran can help the researchers to consciously use them in hydrological and water resources practices. In this study, first, the degree of improvement of the monthly precipitation data of ACCESS1-0 model from the NEX-GDDP product was investigated against the corresponding GCM model as well as the observational data measured at stations located in eight homogeneous precipitation regions of Iran. Then the NEX-GDDP data was bias-corrected using the Quantile Mapping (QM) method through using the SSPLINE, QUANT, PTF, RQUANT and DIST functions. Comparison of monthly precipitation data of the selected models of the NEX-GDDP product with its raw GCM data showed that R, PBIAS, NSE, and KGE statistics have significantly improved respectively in 75%, 100%, 100%, and 88% of the studied stations. The correlation between the bias-corrected data and the observational data was also improved in 50% of the stations, the NSE and KGE were improved respectively in 75% and 62.5% of the stations, and PBIAS was improved in all stations. This study also showed that among the used bias correction functions, the RQUANT had the best performance.

Today, scientific research on the types of Nexus, especially the water- energy- food Nexus as the driver of improving the welfare of society, is expanding. Since the Nexus approach is relatively new and requires the cooperation of several fields, explaining the concepts, its literature review, with a special focus on the water- energy- food Nexus is essential. This article aims to express Nexus approach simple and clear, by a detailed review of several related articles from 2011 to 2021. Articles were reviewed and categorized by year, source variety, and topic. So the outline of the formation of the Nexus approach, water- energy- food Nexus and the questions raised about this approach were codified in a way that provides a practical insight for policy making. In general, the Nexus approach, especially the water- energy- food Nexus which creates a very complex system and must be considered from a political, social and economic perspective, is difficult to implement. However, the Nexus approach is transitioning to an important component of development planning, and its success requires the guidance of strategic policies and institutional structures in multilevel governance. It seems that countries need to reform their governance structures in line with the Nexus approach. Another issue that has been considered in this article is the difference between the Water- Energy- Food Nexus approach with the approach of integrated water resources management. Due to the similarities, there are doubts about the need to move from integrated water resources management to Water- Energy- Food Nexus.

In recent decades, urban, industrial and agricultural development has led to growing challenges in water resources supply. The challenge has deepened due to natural hydrological variability, severe droughts, climate change and inadequate water resources management policies. Thus, we are witnessing more and more conflicts among water users over limited water resources. Such conflicts are more intense in inter-basin water transfer projects which are often costly and affect water rights and interests of numerous water users. Due to the complexity of process, it is very important for water policy makers in such projects to rely on a tool for decision making. Sustainable development can be considered as an appropriate approach in this process based on existing needs, without conflicting with the needs of future generations. In this research, an experimental method has been adopted for assessing sustainability in a large-scale and controversial water transfer plan in central Iran, called Behesht-Abad. Sustainable development can be considered from different aspects, one of which can be taken into account as conflict stability and the other as hydrological sustainability. The first one can be evaluated by the concepts of stability definitions in non-cooperative game theories. Non-cooperative game theory involves a stability analysis in order to show which stability definition determine the behavior of the two players as source and recipient basins. If all players achieve a stable solution, they do not move from that condition and the situation remains stable. It is also necessary to evaluate each player's priorities and their choices and solutions in relation to the water transfer project to develop a conflict model. A conflict model called GMCR+ was executed to analyze various solutions and scenarios between the two players. GMCR+ generated a list of all possible states, whereas infeasible states were removed after evaluating the produced scenarios. Then, the most stable scenarios among various solutions are selected in terms of cooperative and non-cooperative scenarios. In the next step, the hydrological sustainability of the selected scenarios must be examined. Sustainability can be quantified by various multidimensional indicators. However, the largest problem is to interpret the combination of all these indicators in such projects. Various methods of aggregating could be applied to achieve composite indicators to help this problem. Development of composite indicators may be beneficial in such large-scale inter-basin water transfer project. Aggregating indicators involves multivariate analysis, data standardization, assignment of weights, and applying different methods of aggregating. In this study, 10 indicators of sustainability in three dimensions of economic, social and environmental were used, which finally turn into four composite indicators to obtain a robust analysis. Then, the hydrological sustainability of the two basins in the selected scenarios based on the composite indicators of sustainability (CIS) was investigated through a simulation model. MODSIM simulation model was adopted to simulate the selected scenarios. Also, a multivariate statistical method such as principal component analysis (PCA) was performed to determine the main indicators in the source and recipient basins. Comparative analysis of the individual CIS was performed to prove whether they are really delivering the same concept of sustainability in inter-basin water transfer. Correlations analysis among the composite indicators showed that they were normally distributed, so Pearson's ratio was utilized as a test of parametric correlation. The results revealed that using various methods to construct composite indicators can help further to analyze the dimensions of such large-scale projects. According to PCA method, all selected indicators were essential for extracting CIS approaches and none of them could be ignored. The results also indicated positive and significant correlations between more CISs. However, it depended on the kind of method used for weighting and aggregating methods. In addition, despite stability of the region, the hydrological sustainability of the two basins did not seem to be appropriate. Although obtaining revenue for source basin seemed fair in point view of the game theory analysis, the hydrological sustainability was reduced in every four applied methods. The recipient basin would not be in a better condition. The results showed, the hydrological sustainability of the recipient basin would not increase significantly due to the use of transferred water in projects development and lack of supply and demand management. Therefore, transferred water for a short time might solve the problem of water shortage in recipient basin, but in the long run, problem would return more seriously.

At the present time, population growth in the world has led to increasing need for water resources in agriculture, industry and urban, and it is necessary to planning for optimal and sustainable use of limited available water resources. In this paper, supply water demands with controlling changes in groundwater level, especially in agricultural lands with maximizing economic profits, has been defined as objectives of Numerical simulation and multi-objective nonlinear optimization modeling. In the model, combined use of optimization and simulation techniques has been used as a useful and powerful way to determine management strategies for optimal utilization of water resources. The optimization approach shows that the amount of water allocated to the agricultural sector decreased by nine percent, and this amount of savings in water consumption led to raised only one percent crop cost in the cultivation. Environmental sustainability and Aquifer saving improved in the amount of 3/03 million cubic meters per year, and this has been achieved while maintaining profits in addition to agricultural economy, supply of drinking water and industry in the region that has been fully provided

Recurring droughts at various intensity leads to decline in streamflow and wetland area. In this study, using Landsat satellite images, temporal changes in the area of the Bakhtegan and Tashk lake from 1986 to 2019 were investigated. Also, based on the Standard Precipitation Index (SPI), the effect of precipitation falling on the lake area as well as the total inflow to the lake were studied. Then, by generating land-use maps, land-use changes in Bakhtegan and Tashk basin area were analyzed. In addition, a model for forecasting lake area (of next year) on the basis of lake area, total inflow, and annual precipitation falling on the lake basin area associated with the previous year was presented. The results showed that in the study period, the minimum lake area occurred in 2011 and was equal to 17.038 square kilometers, which shows a decrease of 98% compared to the maximum area corresponding to the year 1993. Furthermore, 12-month SPI in Bakhtegan and Tashk Lake basin indicated that the meteorological drought index directly affects the changes of the lake area. However, from 2006 to 2012, the inflow to the lake has severely decreased due to the increasing human interventions within the basin such that, during this period, lake surface area does not strongly respond to SPI variations. The results of the forecast model showed that the coefficient of determination between neural network model output (lake area) with observed lake area corresponding to satellite images was equal to 0.72. As a result, the forecast model could acceptably predict the lake area.

Efficient forecast of precipitation and temperature with a one-month horizon can provide managers with an exceptional opportunity to plan water resources and deal with floods and droughts. The application of proper post-processing and bias correction methods can much improve the accuracy of these predictions. In this study, the S2S (Sub seasonal to Seasonal) precipitation and temperature forecasts of ECMWF were evaluated in one of the important basins of Iran. A variety of methods were used for post-processing and bias correction of these predictions, and the results were compared with different evaluation criteria. Quantile mapping (QM), Bayesian model averaging (BMA), Support vector regression (SVR), an Empirical equation for bias correction of temperature, and some hybrid methods were applied to forecasts. The BMA outperformed the other methods in improving both temperature and precipitation forecasts. Raw precipitation and temperature forecasts were only applicable in 2 or 3 months of the year, but post-processing methods were able to accurately improve precipitation in half of the months, especially rainy months. The hybrid of empirical equation-BMA in 10 months of the year was led to better results than the estimate of the next month's temperature using climatological data.

Risk-based optimization in flood diversion system is a framework that allows the designer to involve uncertainties in the decision-making process and determine the reliability of the hydraulic structure. This study was conducted to incorporate hydrological and hydraulic uncertainties in the probabilistic design of Karun-4 diversion system in Khuzestan province, southwestern Iran. The risk-based multivariate probabilistic model was developed for determining the effect of uncertainty sources on the characteristics of the flow diversion system. For this purpose, the time series of annual maximum peak flow and maximum flood volume data for a period of 37 years were prepared and evaluated. Archimedean copula function and non-dominated sorting genetic algorithm were adopted to minimize the overtapping risk and construction cost as objective functions. Diameter, slope, wall covering and tunnel entrance height, cofferdam height at upstream and downstream were searched as decision variables in the possible space of the problem. The results show that optimal values of upstream cofferdam height, downstream cofferdam height and the diameter of the first and second tunnels were estimated as 44.5, 12.5, 10.5 and 9.9 m, respectively, all corresponding to 25-year return period. Moreover, the results suggest that the proposed framework could be valuable for decision makers when economic, hydraulic and hydrological uncertainties are expected.

One way to deal with this phenomenon is to impose a fine policy by the competent authorities. Since farmers are over-exploitation under specific socio-economic and agricultural conditions, evaluation of the effects of penalty patterns based on a socio-economic simulation is required. This research has provided an agent based simulation framework to study the status of three agricultural, environmental and regulator agent in agricultural environment. In this research, agricultural sector behavior has been modeled in two layers, one is agricultural sub-factors in order to maximize individual profit under physical and behavioral constraints by using fuzzy inference system and mathematical programming, and other is the group-agricultural agents in order to maximize agricultural profitability under the constraints of individual preferences by combining non-dominated sorting genetic algorithm (NSGA-II) and social chose method. The proposed framework was applied to the Najafabad hydrological unit in Isfahan. The results showed that the level of unit hydrograph’s aquifer was drawdown 21.82, 17.18 and 10.5, respectively, while the fines of 2, 3, and 4 thousand Rials per cubic meter were imposed by regulator agent.

One of the major impacts on climate changes is change in extreme precipitation regime in the future, which have to be predicted to counteract the harmful effects of climate change. In this paper, climate change impact is assessed on extreme rainfalls in arid regions of Iran.

Future scenarios are downscaled using the NSRP model. Long-term daily rainfall series are generated for current climate and future scenarios. By comparing the distribution of extreme daily rainfalls for current and future conditions, the impacts of climate change on extreme rainfalls are assessed. In downscaling method, a wide range of statistics of large-scale scenarios has been transferred to downscaled scenarios. The understudying stations are in Bam, Zahedan, Tehran and Yazd synoptic stations as representatives of the arid regions of Iran.

Validation results indicate that the performance of this method in simulating daily rainfall series and distribution of extreme rainfall is acceptable. Results for most of stations and scenarios show that intensity of extreme daily rainfalls will increase in the future while average rainfall will decrease. As instance, in Yazd, extreme rainfall of 50 years return period would increase between 14 to 58 percent, while the average precipitation will change between +3 to -20 percent.

These results indicate that the precipitation situation in arid areas of Iran will worsen in the future. Therefore, more extensive investments and taking preventive activities to adapt to climate change is essential.

Nowadays, much effort has been made in improving meteorological forecasts. In this regard, ensemble forecasting systems have been developed to reduce forecast uncertainties. In this study, the performance of ensemble precipitation forecasts of seven numerical models in 2019 Gorganroud floods was studied. Initially, the precipitation forecasts of the seven numerical models were bias-corrected via gamma quantile mapping method. Then ensemble streamflow forecasts were obtained by ensemble precipitation of seven models using the GR4J conceptual rainfall-runoff model. Based on the optimized parameters, ensemble streamflow forecasts were performed with precipitation forecasts inputs while uncertainty of the models was analyzed based on inputs to the hydrological model. The results showed that the bias correction had a great impact on the improvement of flood forecast in the study basin such that the uncertainty bands of the ECMWF, NCMRWF and UKMO models well covered the observed flood values. P-factor and R-factor values of the ECMWF model was 0.5 and 0.96, respectively; however, the upper and lower bands of ECMWF model was symmetrical. The NCEP and CMA models had poorer performance in flood forecast compared with other models so that their P-factor values were 0.2 and 0.15, respectively. The JMA model overestimated the 2019 flood. Although the ECCC model bands covered 65% of the observed flood values, the gap between the upper and lower bands was quite high. Overall, the results of a number of NWP models in the study basin were satisfactory and their application is generally recommended for flood warning systems.

Although, many studies have been reported on meteorological drought monitoring and analysis, similar studies on groundwater drought in regions with high abstractions are lacking. In this paper, the effects of groundwater extraction of aquifer were investigated and groundwater drought analysis was performed using the naturalized groundwater level time series in Qazvin plain. For this purpose, MODFLOW-ANN coupled model were used to obtain the time series of naturalized groundwater level over a 50 year and a 3 year period. Then, Groundwater drought was monitored by means of the SGI and was compared with the SPI and SHDI indices. Also, drought characteristics were calculated along 50 year period and the regions with more hazard of drought were determined. Results showed that abstraction could cause severe negative trend in the groundwater level. The aquifer was in long duration dry condition at about 47% of the time. Groundwater level changes have a 9 months delay with changing in precipitation and flow rivers. Groundwater drought is more strongly correlated with hydrological drought than with meteorological drought. Also, Boeinzahra city has a higher hazard and Qazvin and Alborz has a lower hazard than other regions.

Nowadays, uncertainty assessment is a major step in hydrological modelling due to different sources of errors and lack of sureness. Quantifying the amount of uncertainty at models’ outputs is considered as the main step before using the models for water resources decision makings. In modelling processes, the uncertainty quantification is assessed along with model calibration. Therefore, paying attention to the model calibration and its relation with uncertainty assessment is essential. This review paper presents the necessary concepts of uncertainty assessment and their relationship with modelling processes.

For groundwater resource management, recognation of performance and prediction climate change and human activity effects on groundwater is necessary. In this research GMS10.05 software was used for determining and simulating characteristics of Mahabad aquifer. After calibration and validation of model, we researched about effective factors influncing groundwater change. For this aim in first step, results was considered without human activity factors .In this condition average of groundwater level was 3m more than groundwater level observation . investigating about dam constraction as a anthropogenic activity factor showed, dam construction causes groundwater level would be 1.11 lower than pervious condition. In this research we then predict groundwater EC and SAR using GEP as a function of groundwater level. We conclude anthropogenic activity in compared with natural change is primary force driving the groundwater level and guality down and changing irrigation of groundwater class to C3S1. The result of this study is applicable in developing criteria for adaptation groundwater resouce management in future.

Among different types of natural disasters in the world, floods, especially flash floods, are known as the most devastating hazard which cause serious damages and human deaths in residential areas. Importance of estimating the maximum possible number of fatalities due to flash floods in urban watersehds, in order to consider appropriate management plans to reduce the number of fatalities, is undeniable. Implementing some global equations in Kan watershed, located in the north of Tehran, led to this conclusion that their accuracy for estimating the number of human fatalities is not enough and developing a regional relationship is essential. In this study, using hydraulic parameters such as depth and velocity, a regional and comprehensive equation was developed to estimate loss of life due to flash flood in residential areas. Comparing the outcomes of the developed regional equation with the previously presented global equations showed that the proposed equation provides more accurate estimation of the number of fatalities in the study area. Finally, it can be concluded that in spite of existence of general relationships to estimate flash floods fatalities, developing a regional equation will be more accurate and practical for the watersheds with high flood fatality potential.

Precipitation is one of the most important meteorological phenomena and the main parameter for streamflow forecasting. Therefore, determining the amount of precipitation in the future will help to manage water resources and predict the flood. In this regard, some of the most important meteorological centers in the world provided users with Quantitative Precipitation Forecasts (QPFs) on a global scale. The availability of global ensemble forecasting models in the TIGGE database creates new opportunities for flood forecasting. In this research, the effect of post-processing on the most important global numerical ensemble forecasting models such as UKMO, ECMWF, NCEP and CMA in the TIGGE database during the years 2007 to 2014 for the Bashar river Basin investigated. Evaluations were conducted in probabilistic and nonprobabilistic approach. Initially, the four NWP models with quantile mapping methods were bias corrected. Then, by using Bayesian model averaging (BMA), the post-processing was carried out. The results of probabilistic evaluation after post-processing showed that the skill of forecasting models for the Bashar basin increased and uniform distributions were achieved in verification rank histograms. Also, the results of the probabilistic evaluation with the BSS for the combined mode of four QPF Models with BMA method at most stations were close to 0.5 and in the simple combination was close to zero, indicating that Grand ensemble has a higher skill than single models.

The dynamical simulation model of WOFOST is widely used for yield estimation at farm and regional scales as well as different climate conditions. In modelling processes, there are lots of parameters which have to be estimated (calibrated) and also in the other hand there are limitations for providing enough observational data. Therefor it is required to choose sensitive parameters for model calibration. In this study, a global sensitivity analysis has presented for maize and wheat simulation in WOFOST model. Global sensitivity analysis methods are useful tools to rank the model parameters based on their influence on model outputs and considering the entire range of parameters. In other words, these methods consider the influence of a unique parameter as well as the influence of its combinations with the other parameters. In this paper, Regional Sensitivity Analysis (RSA) method is applied as a global method and its results are discussed. The variations of sensitivity index for the two crops are obtained from minimum 0.006 (insensitive) to 0.37 (high sensitive). Furthermore, Results for maize crop showed that the parameters which are related to temperature process (TSUMAM, TSUMEA) and absorbed radiation (SLA, AMAX, EFF) are among the most influential parameters in simulation of maize crop yield. In case of wheat crop, only the parameters which are related to absorbed radiation process (SLA, RGRLAI, AMAX, and EFF) are identified as most influential parameters.

Water balance models are generally based on mass continuity and the hydrologic cycle of water in the natural environment. Monthly water balance models evaluate the importance of various hydrological parameters under diverse hydrological conditions. As water balance models are becoming widespread, there is a significant effort devoted to the development of these models towards estimating the hydrological components of the basin. Different models and algorithms consider various parameters which range from relatively complex conceptual models for dry areas to very simple models for areas with temperate climates. Therefore, it is essential that these models be closely and precisely analysed, and ultimately, reviewed. Generally, rainfall data have long been recorded, but discharge data are often scarce. Therefore, the need to estimate the discharge of rivers resulted from rainfalls has motivated a great number of research in this area of study. In this paper, parameter naming in different models has been homogenised, presenting a clearer image of similarities and differences among different models. The overall framework of the models is similar and inspired by the Thornth Waite model. The input parameters are precipitation and temperature, and the output is the monthly runoff of the basin. All models include soil water storage capacity, evapotranspiration, and runoff. However, some of the models consist of water storage capacity layers, separation of rain and snow, groundwater storage, and base discharge. These differences in the number of parameters distinguish the models from each other.

Drought and water scarcity are two key phrases in the water resource management. Drought is a large scale natural disaster and its occurrence is beyond control of water resources managers. On the contrary, water scarcity is a result of increasing and wasteful use of water resources, although it may be controlled via proper management decisions aimed at water conservation. Nowadays, these two phenomena often occur simultaneously and result in water deficiency. In this paper, using a conceptual water balance model in an observational-modelling framework, the effects of drought and water scarcity on watershed runoff are separated. This framework was proposed by Van Loon and Van Lanen (2013), which allows the simulation of the natural hydrological response without the impact of human activities. The framework first calibrates a hydrological model during the period that the watershed is not disturbed by human interventions. Then, by comparing with the period when the watershed is influenced by coupled human and natural factors, separates the effect of these two factors. The results indicated that although between the 1379-1380 to 1390-1391 water years, the monthly precipitation decreased by nearly 12% compared with the long-term period of 1351-1352 to 1378-1379, the ecosystem could receive the minimum environmental water requirements while the major cause of water scarcity was extensive human activities. Moreover, even in studied wet years, a considerable decrease in discharge was detected.