مجله مدیریت آب و آبیاری
سال دوازدهم شماره 1 (بهار 1401)

In this paper, a study on the use of precipitation prediction techniques with time series data was presented. Time series are an effective tool for understanding the nature of hydrological phenomena that with sufficient knowledge of them, future changes can be modeled and predicted. Various statistical models have been considered with the aim of reducing error and increasing forecast accuracy. Due to its structural and flexibility, state space makes it possible to model each of the components of a variable, including surface, seasonal and random separately. Therefore, by identifying the system in the way of modeling the studied variable, it is possible to control and minimize the estimation error, more intelligently compared to classical models. In the present study, in order to evaluate the modeling capability of state space and compare it with classical models, monthly preciptation modeling was performed in three rain gauge stations in Dez catchment, with four structural models of state space including Kalman filter, ETS exponential smoothing model and Modified exponential smoothing models were BATS and TBATS and the classic model was ARIMA. The results showed that at Sepiddasht Sezar station based on RMSE and MAE criteria of TBATS model and in Tangpanj Bakhtiyari station based on RMSE and MAE criterion of Kalman filter model and in Telezang station according to RMSE and MAE criterion of TBATS model the best models were chosen.

River flow is one of the most important components of the hydrological cycle, which depends on several climatic factors and its accurate estimation is used in various fields of water resources management. Therefore, in the present study, random forest (RF) and support vector machine (SVM) models were used to predict the monthly streamflow of the Maroon River in the period of 1981- 2017. One of the important steps in the application of artificial intelligence models is the definition of input patterns and determining the effective variables in the modeling process. The Shannon entropy method was used to select the most efficient inputs among precipitation, evaporation, and minimum, maximum, and average temperatures. The results showed that the total weight of precipitation and evaporation was more than 85 percent. In the next step, three different structures were developed for modeling. In the first case, climate-based patterns were defined that used meteorological data as input. In the second case, nonlinear periodicity was added to the climate-based patterns, and in the third case, the climate-based input data were decomposed using five mother wavelet functions, and W-RF and W-SVM hybrid models were created. The performance evaluation of the standalone RF and SVM models showed that by considering the periodic term, the accuracy is somewhat increased compared to the climate-based inputs, but the analysis of the data with wavelet theory significantly reduced the modeling error. In the meantime, the performance of the two models W-RF and W-SVM was very close to each other, but according to the violin plot, the W-SVM model is suggested as the most suitable option for predicting the monthly streamflow of the Maroon River.

Nonlinear weirs are among the hydraulic structures that, despite their great importance and application, so far, no general method for estimating their discharge capacity has been accomplished. Laboratory or numerical modelling is commonly used to achieve nonlinear weir discharge capacity. It should be noted that employing the design equation from one geometric family of nonlinear weirs to another is impractical. The utilization of numerical or laboratory models in the preliminary stages of the design of these structures is a time and cost-consuming process, which is highlighted by the variety of nonlinear weir geometry. In this research, a general method for estimating the nonlinear weirs discharge capacity is presented. The proposed method analyzes nonlinear weir discharge capacity using energy and discharge equations for discretized solution fields. Furthermore, the local submergence in nonlinear weirs, which has a tangible effect on their discharge capacity, has been corrected. Results of laboratory models performed on the oblique weir, arced labyrinth weir, and Isabella dam weir have been used to evaluate the efficiency of the proposed method. The proposed method with high correlation and accuracy has estimated the discharge capacity of these weirs. The maximum error observed was 12 percent for the oblique weir,15 percent for the arced labyrinth weir, and 15 percent for the Isabella Dam weir.

The purpose of this study is to investigate the effects of climate change on the inflow of Maroon Dam using the SWAT model under two climatic scenarios RCP4.5 and RCP8.5 in the next three twenty-year periods. Flow data measured at Idnak and Tang-e-Takab stations were used to calibrate and validate the model. The Nash-Sutcliffe index of Idnak station was equal to 0.69 and 0.65 and Tang-e-Takab station of Behbahan was equal to 0.67 and 0.59 in the calibration and validation stages. The highest temperature increase will be in the final period and under the RCP8.5 climate scenario. To simulate the flow in future periods, precipitation and air temperature under the two scenarios were micro-scaled using the LARS-WG model and by entering the data into the SWAT model, the inflow to the dam was simulated for the next three periods. The results of forecasting the inflow to the dam showed that although the amount of rainfall in the area has increased, but increasing the temperature in this basin will have a greater effect and efficiency in reducing the amount of flow. The highest decrease in the average inflow to the Maroon Dam in the near future is in the middle scenario of RCP4.5 with 21.91 and 26 percent and in the pessimistic scenario of RCP8.5 with 19 and 22.36 percent in February and March respectively. As a result, the maximum reduction of the inflow to the Maroon Dam compared to the baseline conditions is in the RCP4.5 release scenarios.

This study investigated the effect of Phragmites australis in constructed wetlands for removing copper, lead, zinc and cadmium and different concentrations of COD. In order to study various parameters such as pH, initial concentrations of COD (120, 500 and 1000 mg / l) and initial concentrations of copper, lead, zinc and cadmium (2, 10 and 30 mg / l). PVC pipes with an inner diameter of 16 cm and a height of 70 cm were made as columns to simulate the performance of constructed wetlands. For evaluating these parameters, Effluent wastewater samples were calculated according to the hydraulic retention time (3 days) from the outlet of the column. The results showed that the biomass of the roots of wetland plants had a positive effect on the removal efficiency. In addition, the results of pH evaluation showed that the amount of pH was decreased with increasing of zinc, cadmium, copper and lead′s concentrations. Moreover, according to the results, the maximum COD removal efficiency (17.25%) was occurred in 500 mg/l. The results of pollutant removal efficiency showed that with increasing the concentration of pollutants from 2 mg/l to 10 mg/l, the removal efficiency was increased, then with increase of initial concentrations of heavy metals to 30 mg/l it was decreased. The highest removal efficiencies of copper, lead, zinc and cadmium ions in 90 minutes were 63.84%, 60.77%, 59.14% and 57.71%, respectively. According to the results, the presence of Phragmites australis and use of constructed wetland systems with sandy bed showed a positive effect on the removal efficiency of copper, lead, zinc and cadmium, but was not effective on COD removal efficiency.

Long-term studies of the effects of the use of irrigation systems, in addition to being time consuming, impose high costs on the researcher. On the other hand, environmental and non-uniform changes in long-term data collection can affect the accuracy of the experiment. The use of numerical models and long-term experimental simulations based on calibrated parameters for a short-term experiment can be an effective aid in such research. In this study, the main purpose was to simulate the long-term effect of surface and subsurface strip irrigation on salt accumulation in soil profiles using the HYDRUS-2D model. Firstly, the model was calibrated using volumetric moisture data and measured electrical conductivity, Then, to ensure that the model provides logical results, the model was validated using data that were not used in the calibration step. The RMSE (Root Mean Square Error) and NRMSE (Normalized Root Mean Square Error) statistical indices were used to assess the validity of the model. The results of ten years of simulation for surface irrigation showed that the electrical conductivity of soil layers increased on average from 1 dS / m to 9 dS / m. Also, the EC of soil layers for the subsurface system has increased from 0.73 dS / m to 5.5 dS / m on average over five years. Due to the lack of effective leaching for both systems, accumulated salt is much more at soil surface and decreasing by depth. Based on the results, soil leaching at out-season time is necessary and salt removing from root zone is highly recommended to preserve salinity balance and sustainability in farming.

One of the most important economic tools in promoting the agricultural sector is the optimal use of inputs, especially water inputs. Water scarcity and the high costs of providing it have made increasing the efficiency and value of water consumption one of the most important national goals. Therefore, this study was conducted to investigate the water use efficiency in the country's agriculture sub-sector. For this purpose, the non-parametric stochastic data model (StoNED) has been used. The research data include gross crop production, water consumption, labor and intermediate inputs in the agricultural sub-sector of 30 provinces of the country during the years 2005-2015, which has been collected from the website of the Ministry of Jihad Agriculture. Based on the results, the average efficiency of total production inputs in the agricultural sub-sector was equal to 93.36 percent and the average efficiency of irrigation water during the period under study in this sub-sector was equal to 83.02 percent (periodic average). Irrigation water efficiency in all years under study was less than the efficiency of total production inputs. Therefore, due to the low efficiency of water input consumption compared to other used inputs, it is suggested that extension courses be held to inform farmers in the field of correct and optimal use of water input. Also, the results of this study have shown that the average water efficiency of the provinces in the agricultural sub-sector has been equal to 83.14 percent (cross-sectional average) that the provinces of Gilan and Qom have the highest (87.76 percent) and the lowest (81.85 percent), respectively. Therefore, in order to improve water use efficiency, it is suggested that in the cultivation planning of provinces with low water efficiency, including Qom, Ilam, South Khorasan, Ardabil, Hormozgan, Sistan and Baluchestan, Bushehr, Kurdistan, Semnan and North Khorasan, Take actions such as Improving the irrigation system of crops and modifying the cultivation pattern towards cultivating low-water crops and optimizing it.

Population growth and the development of agriculture and industry have led to a significant reduction in groundwater resources. According to this issue, one of the useful and effective solutions for the optimal operation of aquifers is the implementation of artificial feeding systems. In this research, using mathematical model (HEC-HMS), flood routing in Karaj river and artificial feeding system reservoirs was performed. In this study, Considering to the mathematical model (HEC-HMS), flood routing was performed in Karaj river and artificial recharge system reservoirs. Then the storage volume in the artificial recharge system reservoirs was simulated by an artificial neural network and finally entered into a multi-objective genetic algorithm (NSGA-II). Multi-objective genetic algorithm (NSGA-II) was used for optimal utilization of the artificial recharge system , Considering to the optimal groundwater level changes. Based on the results, the total volume of optimal recharge in the desired time period by the artificial recharge system is equal to 97.94 million cubic meters and also optimal groundwater level changes have increased by 2.62 meters. Therefore, by allocating the optimal volume of the Bilqan diversion dam to the artificial recharge system, the optimal recharge volume and also optimal groundwater level changes in the desired time period have increased compared to the current conditions. considering that the optimal recharge volume and optimal groundwater level changes are proportional to each other, this performance will improve the aquifer conditions.

After about six decades of widespread government interventions, the effects of these measures on the current mechanisms of the water resources management system are undesirable and in some cases, irreversible. Therefore, in recent years, there has been a shift from the focus on the state to a concept of governance, as a system of power distribution, participation, and the use of all social capacities to advance public affairs. One of the frameworks in this regard is the Institutional Analysis and Development framework (IAD), established by Strom. This study, used the IAD framework to evaluate the water resources management system in the irrigation and drainage network of the Sahand dam downstream. The required information was collected through valid documents, observation and interviewing 25 people, including users, managers of water cooperatives and experts of related government organizations. The information obtained through interviews as well as the available documents were analyzed by content analysis method and the results were interpreted in the form of IAD framework. Findings show that due to the subsistence of agriculture in the study area and strong dependence on water resources, free riding in the area interests many; Moreover, inefficient monitoring, and the lack of a proportionate and deterrent punishment mechanism, increase the motivation for infringement. The attraction of the free riding and increasing the motivation to commit violations has weakened the performance of the water resources system of the Sahand Dam downstream network in order to achieve collective action. Accordingly, empowering the local community and water cooperatives in terms of legal power and legitimizing their presence and activities, the participation of the local community in policy decisions to increase the enforceability of policies and Increasing the sense of responsibility in the local community, reforming the laws in the areas of supervision, and deterrent punishment of violators can be considered as policy recommendations of the present study.

The Inter-basin water transfer is one of the ways to deal with water shortage. However, in some cases, this solution has more destructive effects than its benefits. Therefore, it is necessary to fully identify the potential damages of inter-basin water transfer projects, so that they can be prevented in future plans. Iran is one of the leading countries in inter-basin water transfer projects and so far, 10 projects are under operation and 19 more are on the agenda. The main purpose of this research study is to identify the damages of projects in operation in Iran. To achieve this aim, all information related to the in-operation projects were collected and extracted involving descriptive-analytical approach, from literature resources, news and interviews. A total of 20 damages were identified as a result of the investigations. Due to the different nature of these damages, after identification, they were classified into four areas including, environmental, economic, political and social. According to the results, there were only 10 damages in the research literature, which means that the literature is incomplete in relation to the damages of inter-basin water transfer projects. It is recommended that the results of this research be used in the study of future plans.

Poor management of agricultural waste is one of the sources of water pollution. In this study, the surface water quality of Jiroft Dam watershed was modeled using the QSWAT model. The study area is located at the upstream of Jiroft Dam watershed with the total area of 783446.81 hectares in Kerman province. The rainfall-runoff model was simulated over the 21 years from 2000 to 2020 for a monthly time step. Data from Konaroye hydrometric station was used as observed flow data. The meteorological data was collected from Baft synoptic station. The model was calibrated and validated using the SUFI-2 automated algorithm in SWAT-CUP software for periods (2011-2019) and (2008-2010), respectively. The final results of determination and Nash-Sutcliffe coefficients from calibration and validation processes obtained 0.79, 0.77, 0.81 and 0.82, respectively. Sensitivity analysis was performed for 12 calibration parameters. The results show that base-flow alpha factor is the most sensitive parameter. After modeling of the flow rates in watershed, in next step surface water quality was modeled in QSWAT by considering Urea as fertilizer which is mostly used on the area under cultivation of Jiroft Dam watershed. The results for Nitrate load show that model prediction is in good agreement with the experimental data. The results of this study show that QSWAT model can be used as an effective and efficient method in order to predict surface water quality and managing of water resources.

Irregular development of agricultural areas, crops planting with high water need in the Urmia Lake Basin and also low irrigation efficiency have caused a significant reduction in the lake surface in recent years, so estimating water consumption in agriculture can be efficient in both accurate agriculture management and water resources management. In this context, by using METRIC algorithm and Landsat 8 and MODIS satellite images, the actual evapotranspiration have been estimated for a part of the Urmia Lake basin - Hasanlu dam downstream - in the year 2015 and 2016. Therefore, by considering the percipitation at Naghadeh station as the representative of percipitation in the study area, the valoum of irrigation water used in the agricultural area downstream of Hasanlu Dam was estimated. Then, the valoum of water allocated to this dam and estimation water volume was compared to the WaPOR product. The estimated values for Landsat 8 are 468 and 315 mm and for MODIS, 240 and 208 mm for 2015 and 2016, respectively. The estimated usage of the METRIC algorithm is significantly different from the allocated values and the WaPOR system. The estimated values are far higher than the ground statistics and the WaPOR system for nearly all months of the two years. The difference between METRIC and ground statistics and WaPOR product in the study area is calculated equal 23 and 26.6 million cubic meters, respectively.

Water accounting is one of the important approaches to formulate the water cycle and quantitative changes in various dimensions. Therefore, a framework that can quantify the hydrological cycle as standard, as well as a framework that estimates the hydrological processes of the basin in such a way that managed and manageable flows include land use interaction are essential. WA + framework as one of the water accounting methods using remote sensing analyzes the various parameters at the level of a basin. The aim of this study was to analyze the parameters of the hydro-climatological balance using the WA + framework to calculate the three sheets of resource base, evapotranspiration and withdrawal of water resources. According to the volume of 604 MCM inflow, it was determined that 465.5 MCM is used for evapotranspiration and according to the return flow of the basin, 38.8 MCM is used for infiltration and 59.7 MCM is used for runoff in the region. The results obtained from the hydro-climatological balance using the WA + framework showed that due to the same consideration of precipitation, the rate of evapotranspiration in this framework increases compared to the computational method and constitutes about 74 percent of the output volume of the balance. The amount of infiltration and runoff obtained in these conditions is less than the computational method. The results obtained from the water accounting framework showed that this approach can reduce the uncertainty of the input parameters to the hydro-climatology balance.

Iran is located in the arid and semi-arid area and it is very necessary to assess the conditions of rainfed farming of strategic plants. In order to assessment of wheat and barley yield under rainfed climatic conditions collected data from 44 stations were studied during the period of 1981-2020 (40 years). Weather data after spatial interpolation between stations and converting to daily values were used as inputs of a multiple regression model for estimating wheat and barley yield. In this study, Iran was divided into six coastal wet, mountain, semi mountain, semi desert, desert and, coastal desert. The results showed that the highest and lowest annual rainfall was observed in stations Bandar Anzali (1748 mm y-1) and Zabol (57.7 mm y-1), respectively. The greatest and lowest decrease in rainfall occurred in Bandar-Anzali station (gradient 5.8 percent) and, in Kermanshah station (gradient -0.8 percent) respectively. Only 11.36 percent of the stations were in good condition and, in other stations were in a critical situation (88.64 percent). The results of this study showed that the coefficient of determination of predicted yield for rainfed wheat in humid climates was more accurate than in other climates (R2=0.83). The lowest coefficient of determination predicted yield was obtained for rain-fed wheat (R2=0.71) and rain-fed barley (R2=0.53) in desert climates.