1 2423-5970 Iranian Rainwater Catchment Systems Association 553 Special Validation of Rainfall Estimation Methods in Golestan Province Aghajan Liafo Farkhondeh b Javid Mehrnaz c Javan Mahjoub Dost Mohammad d Nazarnejad Habib e Nainiva Pedram f b M.Sc. Student, Department of Watershed Sciences and Engineering, Faculty of Range and Watershed Management, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran, Email: farkhondeaghajan@gmail.com c B.Sc. Student, Department of Water Engineering and Science, Faculty of Water Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran, Email: mehrnazjavid.22@gmail.com d B.Sc. Student, Department of Forest Sciences and Engineering, Faculty of Forest Sciences, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran, Email: mohammad.javanmd@gmail.com e Associate Professor, Department of Watershed Sciences and Engineering, Faculty of Range and Watershed Management, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran, Email: h.nazarnejad@gau.ac.ir f Ph.D. Student, Department of Watershed Sciences and Engineering, Faculty of Range and Watershed Management, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran, Email: Pedram.nainava@gmail.com 1 5 2025 13 1 1 16 30 06 2024 14 09 2024 Atmospheric precipitation, especially rainfall, is very important for hydrological analysis and design. Due to the dispersion of rain gauge stations in a region, there is a need to use rainfall estimation methods to generalize results to points lacking statistics. The choice of these methods requires validation of the methods and the proposal of the method according to each region. Therefore, the present research has evaluated some methods of interpolation and geostatistics in estimating the monthly rainfall of Golestan Province and selecting the best model. The semivariogram model was used to explain the spatial relationship between rainfall data, and based on variographic analysis, the exponential model was shown as the best model for the semivariogram in most months. The spline method gives a more favorable result in areas where the station density is high. The interpolation results show the high efficiency of the spline method compared to other methods used, so this method has the highest level of performance in terms of R2, RMSE, and NS evaluation indices in March, April, September, October, and November. The Kriging and IDW methods are placed in the next priority. Since the density of rain gauge stations in plain areas of the province is lower than in mountainous areas, to increase the accuracy of rainfall estimation, it is suggested that the province be divided into two homogeneous areas, plain and mountainous, and interpolation methods should be done for each area separately.
567 Special Determining the optimal plot size and sample size for vegetation monitoring and biodiversity assessment in the Birjand flood spreading area Rostampour Moslem g Mirmiran2 Seyedeh Mahbubeh h Yari Reza i g Associate Professor, Department of Rangeland and Watershed Management and Research Group of Drought and Climate Change, Faculty of Natural Resources and Environment, University of Birjand, Birjand, Iran, Email: rostampour@birjand.ac.ir h Assistant Professor, Khorasan-e-Razavi Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Mashhad, Iran, Email: mmirmiran@yahoo.com i Assistant Professor, Khorasan-e-Razavi Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Mashhad, Iran, Email: yarireza1364@gmail.com 1 5 2025 13 1 17 34 16 10 2024 28 12 2024 The foundation of plant research results is the sampling and determination of the plot size and sample size. This research was conducted to determine the optimal size and number of plots for monitoring vegetation cover and assessing biodiversity in a part of the rangelands of the flood spreading project in the Birjand plain in the spring of 2024. In this study, plots measuring 1, 2, 3, 4, 5, and 6 m2 with the same number (30 plots each) were established along 5 transects of 100 m each to determine plot dimensions. The time required to measure the density for each plot size was recorded, and based on Wiegert's method, relative variance and relative cost were calculated to determine the optimal plot size for vegetation cover in the flood spreading area. After determining the appropriate plot size, 10, 20, 30, 40, 50, and 60 plots were established along 6 transects, and the density, vegetation cover, and numerical biodiversity indices were determined within them. In this study, in addition, the required number of plots was also calculated using Cochran's method. All statistical analyses were performed in R and PAST software. The results of Wiegert's method and coefficient of variation (CV) showed that a plot size of 4 m2 was the most accurate in measuring vegetation cover in the study area. Considering the dominant growth form of the region's plants and to avoid wasting time and reduce costs, a total of 35 plots of 4 m2 are sufficient to determine the percentage of vegetation cover in this area. Additionally, to investigate and calculate species diversity indices in the flood-spreading area, 90 plots of 6 m2 are required. The results of graphical methods (refraction curve and diversity ordering curve) and nonparametric permutation tests showed that density and species diversity, and dominance are affected by sampling effort. 570 Special Modeling and evaluating the performance of groundwater resources drought index using XGBoost and SVM algorithms in Ghorveh-Dehgolan Plain in Kurdistan Province Yousefi Mobarhan Ebrahim 1 5 2025 13 1 35 48 06 01 2025 17 02 2025 The Ghorveh-Dehgolan plain is the largest plain in Kurdistan province, which is of great importance for this province in terms of agriculture, and knowledge of the status of groundwater resources and optimal management of the plain is a detailed study of groundwater level fluctuations. The aim of this research is to investigate and apply machine models to improve the accuracy of predictions and promote groundwater resource management in the Ghorveh-Dehgolan plain, where the Groundwater Resources Index (GRI) is a reliable indicator for monitoring the drought status of the study area during the period. It was used from 1379 to 1399. The results show that the value of the GRI index has a decreasing trend and in 1397, a high degree of hydrogeological drought occurred in the groundwater resources of this region, which in the continuation of this trend will be accompanied by a serious crisis of groundwater level reduction and the consequences for the region. Predictions using machine learning models show that both machine learning models (support vector machine and boost) fit well with the experimental data of the groundwater resource drought index. Validation of the models used in predicting this index using Taylor plot showed that the boost intensity model (XGBoost) with correlation coefficient (r=0.93) and root mean square error (RMSE=0.071) had the best performance in predicting the GRI index as well as the machine learning model. Support vector with correlation coefficient (r=0.87) and RMSE=0.149 showed high performance in predicting the index. The results of this study confirm that machine learning models are suitable for groundwater resource drought prediction indices, which are recommended in other similar areas.  568 Special Prioritizing watershed management practices based on hydrological factors in Chehelchay Watershed Hoseinie Saeedeh Sadat l Heshmatpour Ali m Ruohani Hamed n Farazjoo Hassan o l M.Sc. Student, Department of Watershed Management, Faculty of Agricultural Sciences and Natural Resources, Gonbad Kavous University, Gonbad Kavous, Iran, Email: s_hoseinie@yahoo.com m Associate Professor, Department of Watershed Management, Faculty of Natural Resources, Gonbad Kavous University, Gonbad Kavous, Iran, Email: Heshmatpoura@gmail.com n Assistant Professor, Department of Watershed Management, Faculty of Natural Resources, Gonbad Kavous University, Gonbad Kavous, Iran, Email: HamedRuohani@gonbad.ac.ir o Former M.Sc. Student, Department of Watershed Management,, Jihad-e-Keshavarzi Organization of Golestan Province, Gorgan, Iran, Email: Farazjoo_h@gmail.com 1 5 2025 13 1 49 66 10 11 2024 25 01 2025 Periodic floods are causing increasing destructive impacts and resulting in human and financial losses in many parts of the country. In this context, identifying flood-prone areas within watersheds and prioritizing sub-watersheds for implementing watershed management projects as a preventive measure against floods is considered one of the effective strategies in natural resource management. In this study, the contribution of sub-watersheds to the total flood runoff, based on a 50-year return period, was determined by integrating Geographic Information System (GIS) and HEC-HMS hydrological modeling. Then, the three sub-watersheds of the study area were divided into 18 management units. Using the SCS model and the individual sub-watersheds removal method, along with the flood-specific index, the sub-watersheds and management units of the watershed were prioritized for the implementation of watershed management operations. The findings indicated that management units 10, 14, and 16, with a peak discharge of 647.9 m3 s-1 in sub-watersheds CH3; management unit 7, with a peak discharge of 80.9 m3 s-1 in sub-watersheds CH2; and management units 3 and 5, with a peak discharge of 64.7 m3 s-1 in sub-watersheds CH1, are identified as having more critical conditions and higher priority for the implementation of control and protective measures. The results obtained from this study will enhance the accuracy and speed of selecting suitable locations, while also reducing costs for the managers of the implementation sectors. Additionally, strengthening vegetation cover and applying traditional methods, such as the construction of small dams in more critical areas, are recommended. 574 Special Analysis of changes in area and water quality of wetlands in the Godarchay Watershed Koohani Mohammad p Behmanesh Javad Rezaverdinejad Vahid p Ph.D. Student, Water Engineering Depatment, Faculty of agriculture, University of Urmia, Urmia, Iran, Email: Koohani27@gmail.com Professor, Water Engineering Depatment, Faculty of agriculture, University of Urmia, Urmia, Iran, Email: j.behmanesh@urmia.ac.ir Professor, Water Engineering Depatment, Faculty of agriculture, University of Urmia, Urmia, Iran, Email: v.verdinejad@urmia.ac.ir 1 5 2025 13 1 67 84 04 02 2025 12 03 2025 This study examines the changes in the area and water quality of both permanent and seasonal wetlands over 34 years, highlighting their sensitivity to climate change and human activities. Wetlands, vital for regulating the water cycle and supporting biodiversity, have seen a significant decline in area and water quality in recent decades. Satellite images from Landsat 5, 7, and Sentinel-2, with high spatial resolution, were used to generate land use maps, processed with ArcGIS Pro and ENVI software. The analysis utilized advanced techniques such as SVM, Markov, and CA-Markov models. Water quality data from 2021 to 2024 in permanent wetlands were analyzed, focusing on parameters such as TSS, NO₃, PO₄²⁻, pH, TDS, COD, BOD₅, and EC. The results indicate a notable increase in water bodies and orchards, expanding from 348.77 km2 in 1990 to 634.20 km2 in 2024, with a predicted rise to 722.90 km2 by 2030. Conversely, rangelands decreased from 1,498.13 km² in 1990 to 1,037.06 km² in 2024, and are expected to further decrease to 938.30 km² by 2030. Rainfed lands remained relatively stable, while seasonal wetlands exhibited more fluctuations than permanent ones. The study also revealed that seasonal wetlands like Yadegarlu and Taleghan experienced significant reductions during dry years, whereas permanent wetlands such as Agh-Gol and Dargeh-Sangi showed greater stability. These findings underscore the importance of effective water resource management and planning, particularly during drought periods, to ensure the protection and sustainability of wetlands.. 573 Special Evaluation and comparison of CMIP5 and CMIP6 models in estimating precipitation in Iran Nemati Shishehgaran Nima Babaeian Fariba Mianabadi Hojjat Former M.Sc. Student, Department of Water Engineering and Management, Faculty of Agriculture, Tarbiat Modares University, Tehran, Iran. E-mail: Nima.Nemati@modares.ac.ir Former Ph.D. Student, Department of Water Recourses Engineering, Faculty of Agriculture, Tarbiat Modares University, Tehran, Iran. E-mail: Fariba_babaeian@modares.ac.ir Assistant Professor, Department of Water Resources Engineering and Management, Tarbiat Modares University, Tehran, Iran. E-mail: hmianabadi@modares.ac.ir 1 5 2025 13 1 85 102 01 02 2025 24 02 2025 Climate models are primary tools for projecting precipitation changes and assessing the impacts of climate change in various fields. This study aims to evaluate the simulation performance of the CMIP6 and CMIP5 models and to detail the efficacy of each climate model in estimating precipitation patterns in Iran. Accordingly, the precipitation simulation performance of 30 climate models from CMIP6 and CMIP5, as well as their multi-model ensemble for Iran, was evaluated against observational data. After bias correction of the simulated precipitation values using the quantile mapping method, the performance of each General Circulation Model (GCM) will be assessed using the Taylor skill score (TSS) and Taylor diagram, which includes correlation, standard deviation, root mean square deviation. In the following, the spatial and temporal patterns of simulated precipitation in Iran by the CMIP6 and CMIP5 models were compared using the relative bias criterion. The findings from the Taylor diagram and the TSS metric reveal that while most CMIP5 models display a standard deviation closer to observational data than CMIP6 models, overall, the majority of CMIP6 models exhibit superior performance in simulating precipitation in Iran. In terms of spatial and temporal variations, there exist relative bias between the observed and simulated precipitation values by the CMIP5 and CMIP6 models, with the CMIP6-MME exhibiting a lower relative bias compared to the CMIP5-MME. By evaluating simulated precipitation changes, it can be inferred that, alongside CMIP5-MME and CMIP6-MME, models such as BCC-CSM1-1-m, CMCC-CM, MPI-ESM-LR, and MPI-ESM-MR from CMIP5, as well as BCC-CSM2-MR, MPI-ESM1-2-HR, and MPI-ESM1-2-MR from CMIP6, exhibit superior capabilities in simulating precipitation in Iran compared to other models.   580 Special Assessing the impact of a new method of rainwater use on vegetation restoration, land reclamation, and dust control Sharifi Frood haghighi sahel Kargar Hadi Kazemi Rahim Davoodi Hamid Chatrnor Mansour Shoaei Zieaodin Professor, Hydrology and Water Resources Development Research Group, Soil Conservation and Watershed Management Research Institute, Iran, Email: fs1338@yahoo.com Research Expert, Soil Conservation and Watershed Management Research Institute, Iran, Email: Sahel.haghighi66@gmail.com Assistant Professor, Soil Conservation and Watershed Management Research Institute, Iran, Email: Hadi_k1360@yahoo.com Assistant Professor, Soil Conservation and Watershed Management Research Institute, Iran, Email: Ra_hkazemi@yahoo.com Research Expert, Soil Conservation and Watershed Management Research Institute, Iran, Email: Hamid_davoody@yahoo.com Research Expert, Iran's Soil and Water Research Institute, Iran, Email: m.chatrnor@gmail.com Associate Professor, Soil Conservation and Watershed Management Research Institute, Iran, Email: zshoai@gmail.com 1 5 2025 13 1 103 120 11 03 2025 09 04 2025 In this study, using modern technologies and a model for soil rehabilitation, a comprehensive solution is proposed for the restoration of alluvial desert lands in an area near Hendijan (one of the hot spots in Khuzestan province). In the year 2001, three provinces faced the issue of fine dust; after five years, the problem doubled, and after ten years, it expanded to 14 provinces. Although large dust storms do not occur frequently, when they do happen along their path, they can be either amplified or weakened, resulting in prolonged and more widespread regional damage. Therefore, implementing local source control measures can lead to regional dust control and reduce the intensity, concentration, and persistence of widespread dust storms. The study adopts a multi-dimensional approach that includes: using seasonal precipitation and flash floods for soil rehabilitation, aquifer recharging and soil leaching, employing bioengineering measures and planting drought-resistant vegetation, reducing salinity and evaporation, as well as preserving soil moisture. Implementing this model on 1,000 ha of alluvial lands has led to land restoration and effective, long-term control of dust storms with accompanying social benefits. Important outcomes of the project include: eliminating the need to transfer hundreds of billions of cubic meters from conventional water resources at high costs, Preventing the salinization and alkalization of lands, eliminating the use of oil-based mulches (which are not only expensive but also environmentally harmful), achieving a fully integrated rehabilitation of the lands as a more sustainable option (in contrast to point-wise planting of 200 low-yield trees per ha, which incurs several times higher costs and comes with maintenance and environmental challenges). This innovative model can serve as an efficient framework for the rehabilitation of other areas affected by soil erosion and dust storms. It plays an important role in sustainable land development and the improvement of environmental conditions, as well as in the production of forage, food, and industrial products with higher advantages, lower costs, and greater sustainability.