مجله تحقیقات منابع آب ایران
سال نوزدهم شماره 4 (پیاپی 67، پاییز 1402)

Environmental crises are usually silent and go beyond the geography of countries, affecting the global community. The water crisis is one of them. This crisis, sometimes seems such unstoppable that the United Nations considered the occurrence of water war in many regions of the world (until 2050), along with security, economic and food supply tensions for a population over 5Billions of people in the world, probable. Therefore, it has warned legislators, governments and international institutions about the unfortunate consequences.This disaster has warned (United Nations 2, 2021). In Iran, the correct management of limited water resources is important for the exploitation of today and the future. It has been manifested as severe concerns of environmental experts in Iran; Therefore, according to importance of the issue, it’s logical to have a holistic and wisely thought, based on the policy. In this research, by designing a knowledge-based supporting system, the ambiguity of water issue is in center of attention and should be consider wicked problems at the level of public administration and governance organization according to categories such as security, economy, intergenerational, cultural and social justice, at the level of public administration and governance institutions comments. In this research, stratified purposive sampling method was used and during it, interviewed with 13 and analyzing votes of them. Then by coding them, Using Maxqda software, the coordinates of the support system were identified to contain the water crisis in line with development sustainable.

Estimating runoff caused by excess rainfall at the watershed scale is necessary for precise design of water structures, comprehensive watershed, and flood management. In this research, we evaluated deep learning methods in comparison to polynomial neural networks and HEC-HMS models in three watersheds, i.e., Bar-Erieh, Kasilian, and Latian. For this purpose, daily runoff was simulated using a long short-term memory (LSTM) deep learning model and compared to multi-layer perceptron (MLP) as the most common artificial intelligence model, group method of data handling (GMDH) and HEC-HMS as a physically based model for robust neural network modeling. The results showed that the R2 ranged from 0.872 to 0.986, RMSE from 0.086 m3/s to 2.22 m3/s, and NRMSE from 18.9 to 66.0%. The results indicate that the performance of the MLP model is mediocre with an average NRMSE of 51.2%, the performance of the GMDH model is good with an average NRMSE of 44.6%, and the LSTM model is very good with an average NRMSE of 26.8%. Considering the high computational cost of LSTM compared to the GMDH model, it can be recommended that the GMDH model should be used if the user does not expect very high accuracy and precision, and if higher accuracy is required, the user may need to accept a high computational cost and the LSTM model. Also, if the process and scenario-based modeling are the focus, the HEC-HMS model is preferred.

Therefore, it is necessary to evaluate the quality of the wetland. In this regard, the aim of the present study is to evaluate the amount of nitrate and phosphate pollution of Miankaleh wetland using the WASP model. The input information to the model includes the data measured by the General Department of Environmental Protection of Mazandaran province in 6 stations of Dahaneh-ye-chopoghli, Mian ghaleh, Bandar-e-Gaz, Gharesu, Ismaeilsay and Galougah during 6 seasons and 8 sampling periods of lagoon water. have been collected. 4 sampling periods were considered for calibration and 4 periods for model validation. The performance of the model was evaluated based on three indicators, R2, RMSE and CP. The evaluation results of the model show the optimal performance of the model in the simulation of phosphate and nitrate parameters. According to the obtained results, the concentration of nitrates in the wetland is within the permissible limits, but it has been increasing in Dahaneh-ye-chopoghli, Mian ghaleh, Bandar-e-Gaz, Gharesu and Ismaeilsay stations. While the concentration of phosphate in all stations is more than the permissible limit. In general, the results show the deterioration of lagoon water quality. Therefore, correct management of wastewater discharge from different centers, quantitative and qualitative monitoring of wetland water, use of modeling methods in order to provide and evaluate management solutions, as well as the use of organic fertilizers as an alternative to chemical fertilizers in agricultural lands and aquaculture farms can control and not intensify the amount Phosphate and nitrate pollution in Miankala wetland.

Today, due to climate change, we are witnessing limited water resources such as droughts and floods in all parts of the world. From the past until now, dams have been used for water storage, electricity production, and agricultural and industrial uses, which, along with their advantages, will cause environmental damage. The construction of dams will divide the basins into engineering and natural basins, and one of the approaches of this research is to explain the differences and performance of these two types of basins in terms of water resources and drought indicators. The purpose of this research is to review and evaluate the existing indicators and provide an integrated index including the influencing factors of drought, which was chosen as a case study due to the sensitive location of the Zayandeh Rood watershed in the central plateau of Iran. The imbalance between resources and consumption, especially in recent years, is considered as the main factor aggravating drought. The integrated drought index includes various factors such as meteorological and hydrological factors and is verified using agricultural factors. The results showed that in the studied natural basin, the correlation value of the index based on rainfall and evaporation and the validation index is 0.52 and 0.53, respectively, while the correlation of the bivariate index and the validation index is 0.66. In the studied engineering basin, the correlation difference varies from 0.26 and 0.41 respectively for the indices based on rainfall and evaporation to 0.91 for the bivariate index.

Monitoring snow cover areas and estimating the resulting snowmelt runoff in mountain areas is highly important.There are mainly two approaches to improve the performance of snowmelt runoff in rainfall-runoff models, including improvement of snow parameters through observations and modifying their snowmelt module. This study investigates the impact of these approaches on the accuracy of snowmelt runoff using the SWAT model in the mountain Basin of Zarineh River, northwest of Iran. Firstly, the snow parameters of SWAT were extracted through the MODIS daily snow cover products and the in-situ snow depth data and were replaced in the model. Secondly, the UBCWM energy balance model was substituted for the original SWAT snowmelt module, which is based on the degree-day method. Results show that the baseline SWAT model underestimates runoff at the upstream and downstream hydrometric stations. However, the performance of the model with the modified snow parameters improves at the two stations by 6% and 14% for Nash–Sutcliffe Efficiency (NSE) and 35% and 14% for Kling-Gupta Efficiency (KGE), respectively. On the contrary, using UBCWM in SWAT deteriorates the simulated runoffs at the two stations due to underestimating the peaks and overestimating the snowmelt duration. This study's findings can help achieve more accurate runoff estimations in mountain basins, especially during peak runoffs.

Currently, numerous sub-basins located in the Urmia Lake Basin (ULB) are experiencing water shortages. Gadar River basin is one of the most important basins of the ULB in which proper water allocation and management are paramount of importance. A decision support system based on a water evaluation and planning system (WEAP) could be highly beneficial in water allocation plans at the basin scale. In this research, the WEAP-MABIA model has been used to analyze and simulate water supply and demand in the three major catchments of Gadar River basin. The year 2009 was chosen as the base year of modeling, all nodes of supply and resources were created, and the rainfall-runoff model was simulated. Then, the Gauss-Levenberg-Marquardt optimization algorithm, embedded in the PEST tool, is implemented for calibration. The efficiency of the model is proved by the Nash-Sutcliffe coefficient for the calibration and validation period, which is ranged from 0.68-0.87. Ultimately, several management strategies such as a slight increase in irrigation efficiency, fallow implementation, and cultivation of low-demanded were employed to investigate the sustainability of water resources in the Gadar River basin. The results revealed that simultaneous implementation of %10 fallow along with 5% increase in irrigation efficiency could enhance the water supply reliability, compare to status que, in Oshnaviyeh, Naqadeh and Hasanlu basins %12, %19, and %11 respectively. Hence, this scenario, with decreasing the unmet demand, would play a major role to ameliorate the water shortages in the study area.

Drought can mainly affect agriculture, especially rainfed agriculture due to its high dependence on precipitation, thereby compromising food security and social protection. In this study, the correlation between SPI and SPEI drought indices with rainfed wheat yield of 5 filds in Saqqez city during the period of 2001-2020 was investigated with neural network, random forest and support vector regression. TRMM precipitation and CRU evapotranspiration were used to calculate SPI and SPEI drought indices. The AquaCrop model was calibrated with observational data and then filds performance was simulated with the AquaCrop model for the period 2001-2020. The average yield of the filds was evaluated with the average yield of the entire Saqqez city, and the results showed that the data simulated with the model had a good correlation (R2=0.90) with the average rainfed wheat yield of Saqqez city. The results of evaluating the relationship between SPI and SPEI indices with rainfed wheat yield showed that the neural network and random forest method with a significant probability of 95% (P-value=0.0) and an explanatory coefficient of more than 0.70% and a high value of Nash Sutcliffe index And a small amount of underestimation has had a good estimate of the rainfed wheat yield and there is a significant relationship between SPI and SPEI drought indices with the rainfed wheat yield in the study area.

In this study, by using the technical-economic approach of virtual water and related indicators in 13 selected agricultural crops in the province of Kurdistan has been evaluated and analyzed.Water productivity is the inverse of virtual water consumption. Alfalfa had the lowest and tomatoes had the highest water productivity in crops. Walnuts and nectarines also had the lowest and highest water productivity among garden products.Crops implicitly exchange the lowest market value for water for consumption. Among these products, alfalfa has exchanged the lowest price range of water due to its special water consumption. Among crops and horticulture, potatoes and nectarines have the highest market productivity. The results showed that horticultural products have on average 9 times the market revenue of virtual water compared to agricultural products.Analysis of the relations test between the two variables of technical water efficiency and market value of virtual water consumed at the selected products in the province shows that their relationship is negative at 95% confidence level. In other words, products with more virtual water had lower prices and market value in the market. Both the lack of market value of water consumption and the amount of virtual water consumption show that the structure of the production system and cultivation pattern is not commensurate with the weight and size of water consumption of products and is even inverse.

Modeling the lake water surface temperature (WST) can help to improve the simulation of the evaporation component. In this study, with the aim of simulating the WST of Lake Urmia, the one-dimensional FLake model was used for the period 2001-2021 and the results were compared with the observations obtained from MODIS images. The results showed that the north (N) and south (S) of the lake have thermodynamic differences. In both the northern and southern parts of the lake, an increasing trend (0.084 °C year-1 and 0.117 °C year-1, respectively) in water surface temperature is observed, and the slope of changes in the south of the lake is steeper than in the north of the lake. The FLake model is able to simulate WST fluctuations in a relatively good way. However, the model shows a warm bias of about 3 °C in both parts. In general, the model is less accurate in simulating the temperature of the winter days (MBE_N=4.4 °C and MBE_S=4.2 °C) than the summer days (MBE_N=1.9 °C and MBE_S=1.0 °C). The modeled stratification of the lake is of warm monomictic type, and the investigation of the thermal stratification pattern indicates an earlier start of the mixing period in the south of the lake. Also, the examination of the relationship between the changes in WST and the atmospheric characteristics showed that air temperature and air humidity explain the most variance in WST; but the increasing trend of WST is only related to the increasing trend of air temperature.

Floods in urban areas have always been associated with financial losses. While estimating the amount of flood loss for all contents of residential buildings is very important, the existing models only estimate the amount of direct damage caused to the building structure. Then, the damage caused to the movable content of the building is assessed as a percentage of the damage to the structure. Considering the inaccuracy of the existing models and because no such research has been done in Iran, in this research, determining the amount of direct loss of the contents of residential buildings, both movable and immovable, has been considered in full detail. The study was carried out in five neighborhoods with various economic levels in Rasht City, and through a questionnaire, 381 people living in the study area were evaluated and the appliances in their homes were valued at the current price. Finally, the flood depth-loss curves for all movable and immovable items were presented and the results obtained from them were compared with the results obtained from the loss functions used in other countries. The average loss calculated by the developed model was lower up to a depth of one meter and higher than the global models from this depth onwards. This indicates the need to produce loss functions caused by urban flooding at the national level. The method used in this research and the developed dimensionless loss functions are recommended for many similar urban areas in Iran.

In the present study, the variable of the time interval between the peak flood and the peak of drought in thirteen basins of Karkheh basin was investigated. Since the time interval variable from the flood peak and the peak of previous drought has a discrete nature, eight well-known discrete probability distribution functions were tested for frequency analysis. In general, the results of the research showed that in most of the studied small and fourth-degree basins, with the increase in the intensity of annual droughts, the corresponding peak flood discharges will decrease up to SPI= -1, and after that, as the droughts continue to intensify (SPI <-1), the discharges will decrease. The flood peak will increase with an exponential and quadratic pattern. While in large basins and the third level, with the intensification of drought, the peak discharges of floods will also decrease. The results of the frequency analysis determined that the probability distribution functions of DPO and NBI have the most appropriate fits to the time interval variable between the peak of flood and the peak of drought. Based on the frequency analysis, it was found that the time interval between the peak of flood and the peak of drought is approximately 6 to 8 months. The defined variable reflects the interaction and impact of two extreme events of flood and drought in a basin.

General Circulation Models (GCMs) are indispensable tools for understanding future climate change. However, the utilization of GCM output data requires an evaluation of its accuracy in comparison to observational data. The aim of this study is to compare the outputs of 13 CMIP6 models with observations using two bias correction methods called Quantile Mapping and Linear Scaling, along with a Bayesian model averaging approach. To explore the future changes in temperature and precipitation variables in the Khazar basin, climate model simulations in two scenarios, SSP245 and SSP585, were chosen. The results show that the quantile mapping method, despite its better performance in modifying climate models, is inefficient at the stations where the bias is unstable over time and the correction is not done properly. Also, using the Multi Models Ensemble (MME) provides a higher level of accuracy than individual models. Although averaging models after bias correction reduces the extreme fluctuations of the time series, it has better accuracy and performance than the second method (averaging models before correction and then applying bias correction). The findings show that the average precipitation in the Khazar basin for the two scenarios, SSP585 and SSP245, is not statistically different from the observational periods and ranges from 0% to 6% for both the near-future periods (2050–2021) and the far-future periods (2080–2051). The average temperature will rise 1.67 and 3.14 (1.8 and 3.65) ℃ more than it did during the observational periods for the near-future (2050-2021) and far-future (2051-2080) periods, respectively, under the SSP245 (SSP585) scenario.

Water yield is a key indicator of the performance and valuable ecosystem service that directly affects the sustainable development of the economy, human well-being, and ecosystems of the basin. Using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, were simulated water changes in 10 basins, in the eastern border basin of South Khorasan province under the influence of land use/land cover changes. The model was calibrated using the long-term data of flow at Efin, Khonik Olia, Mansourabad, Gezik, and Ahangaran stations. Also, the economic value of produced water service was calculated in each of the different land uses/land covers. The results showed the highest volume of produced water in the Esfadan basin with 8,126,129 cubic meters, and the lowest in Namakzar khaf Basin equal 185,590 cubic meters. The amount of produced water in the whole studied area was 14836168 cubic meters. The highest amount of produced water was in the land use of dense and semi-dense range with more than 12 million and 430 thousand cubic meters, followed by the land use of sparse range with more than 1 million and 990 thousand cubic meters. The total economic value of produced water in the eastern border basins was equal to 16115806.5 million Rials. The spatial indication of the distribution of economic values of the ecosystem, which was carried out in this research through quantification, mapping and valuation of ecosystem services, can be used as important and reliable tools for natural capital management and policy making.

The goals of irrigation modernization are mainly focused on increasing irrigation efficiency, improving water productivity, and ultimately reducing irrigation water consumption and saving scarce water resources in these countries. Meanwhile, various studies have shown that increasing irrigation efficiency and improving water productivity through the development of the use of efficient and modern irrigation systems, sometimes did not lead to real savings and reduction of agricultural water consumption as expected or vice versa, it has caused its increase. This phenomenon is called "rebound effect” of water. The concept of the rebound effect phenomenon is that with the use of efficient irrigation technologies, irrigation efficiency and water productivity increase, but part or all of the expected saved water may be offset by more water consumption. The effective factors and reasons for the rebound effect phenomenon are mainly: the increase in the irrigated area following the reduction of water consumption, the increase in evapotranspiration due to the change in the cropping pattern and increased crop yield, reduction in the quantity and quality of return flows due to increased irrigation efficiency, deficit irrigation to provide enough water for the increased cultivated area. In general, there is a need to mainstream the literature on the subject and following determining the extent of rebound effect and the necessary analysis, relevant hints to the policy makers and those responsible for the development of new irrigation technologies should be given to adopt a suitable policy and to take actions to implement technical, economic-social and political solutions.