1 2423-5970 Iranian Rainwater Catchment Systems Association 617 Special Bias correction of numerical precipitation forecasting model outputs from the TIGGE database Behiyan Motlagh Soudabeh b Honarbakhsh Afshin c b Former Ph.D. Student, Department of Natural Engineering, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord, Iran. Email: sodabehbehyan@gmail.com c Associate Professor, Department of Natural Engineering, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord, Iran. Email: afshin.honarbakhsh@gmail.com 1 8 2026 14 3 1 22 23 04 2026 27 06 2026 Accurate precipitation forecasting is essential for flood forecasting and water resources management. In recent years, numerical weather prediction (NWP) models have been extensively developed and are widely used by major meteorological centers for operational weather forecasting. The TIGGE database integrates forecasts from these models, providing a valuable resource for evaluating precipitation prediction performance. This study investigated the effectiveness of seven bias-correction methods applied to precipitation forecasts generated by ten NWP models available in the TIGGE database for the Poldokhtar watershed. The results showed that most forecasting models exhibited the lowest root mean square error (RMSE) at low elevations and the highest RMSE at high elevations. Among the ten models evaluated, the ECMWF model achieved the lowest RMSE (approximately 5 mm day⁻¹), whereas the NCMRWF model produced the highest RMSE (approximately 8.8 mm day⁻¹). Evaluation of the bias-corrected precipitation forecasts indicated that the EZ, STB, and QM methods outperformed the other correction methods at several stations across the study area. In contrast, the Delta method consistently improved forecast performance across all evaluated models, regardless of geographical location. The LS and EQM methods showed little to no improvement in precipitation forecasts, while the TVSV method produced corrected precipitation values that differed considerably from the observed precipitation. Overall, the results demonstrate that post-processing of precipitation forecasts can substantially improve the performance of numerical weather prediction models, thereby enhancing their applicability for flood forecasting and early warning systems.
621 Special Feasibility of extracting livestock drinking water in the nomadic areas of Dargaz city with underground water storage Bagherian Kalat Ali d Eslami Ali Reza e Rostami Khalaj Mohammad f d Assistant Professor, Khorasan-e-Razavi Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Mashhad, Iran. Email: Alibagheriankalat@gmail.com e Associated Professor, Khorasan-e-Razavi Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Mashhad, Iran. Email: Ar.eslami@areeo.ac.ir f Assistant Professor, Khorasan-e-Razavi Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Mashhad, Iran. Email: M.rostamikhalaj@areeo.ac.ir 1 8 2026 14 3 23 38 25 05 2026 05 07 2026 In some nomadic areas of Dargaz County, water supply to nomads has been carried out through mobile tankers. Initial desk and field surveys showed that the conventional methods of water supply to nomads have many limitations. Therefore, in this article, for some nomadic areas of Dargaz County where mobile tankers supply water, the feasibility of water supply through the construction of an underground dam was investigated. For this purpose, first, parts of the region that do not have the ability to construct an underground dam were removed from the study area using Boolean logic. Then, using the Fuzzy AHP method, in all areas that have the initial potential for constructing an underground dam, the factors effective in locating the underground dam were weighted, and the susceptible areas were identified. Among the weighted parameters using the AHP method, geology and slope received the highest scores with scores of 0.40 and 0.27, and land use and access distance to the underground dam site received the lowest scores with scores of 0.08 and 0.09, respectively, according to experts. In the third stage of the research, in areas with potential for underground dam construction, surveys were conducted to determine the desired points as suitable points for underground dam construction, and these points were prioritized. To determine the location of suitable axes for underground dams, according to existing maps and Google Earth images, the location of narrowing of waterways in areas with potential for underground dam construction was determined. The points were field visited, and finally three suitable points for underground dam construction were identified. If dams are constructed at the three points D4, D2, and D3 as proposed in this study, each of these dams can extract and utilize approximately 40,000, 16,500, and 14,000 m3 of subsurface water annually, respectively. This amount of water will not only provide drinking water for approximately 20,000 livestock of nomads and local livestock farmers, but will also provide part of the drinking and sanitary water needed by the nomads. 626 Special Investigating the effect of the integrated system of semi-circular bunds with seed sowing on vegetation and species diversity in dry rangelands (Case study: Esfakany Rangelands, Boshrouyeh, South Khorasan) Solaimani Sayyed Hossein g Rostampour Moslem h Yari Reza i g Former M.Sc. Student, Department of Rangeland and Watershed Management, Faculty of Natural Resources and Environment, University of Birjand, Birjand, Iran. E-mail: solaimani.s.h@gmail.com h Associate Professor, Department of Rangeland and Watershed Management, the Research Group on Future Studies in Environmental Sciences, Faculty of Natural Resources and Environment, University of Birjand, Birjand, Iran. E-mail: rostampour@birjand.ac.ir i Assistant Professor, Khorasan-e-Razavi Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Mashhad, Iran. E-mail: yarireza1364@gmail.com 1 8 2026 14 3 39 54 10 06 2026 11 07 2026 The objective of the present study was to investigate the effect of the integrated system of semi-circular bunds with seed sowing inside them on soil surface cover characteristics and biodiversity in the rangelands of Esfakany, Boshrouyeh, South Khorasan Province. Vegetation sampling was conducted in the spring of 2024, during the flowering stage of dominant plants, using a systematic-random method with quadrats. Vegetation characteristics, including density, composition, percentage of soil surface cover, number of species, species richness indices (Margalef, Chao1, and Menhinick), species diversity indices (Simpson and Shannon-Wiener), species evenness (Pielou), and Simpson's dominance, were measured and compared across three areas (inside the semi-circular bunds, outside the semi-circular bunds, and control). The results showed that the effect of semi-circular bunds combined with seed sowing on cryptogam cover, litter, stone and gravel cover, and vegetation cover was significant (p ≤ 0.05), but its effect on bare soil percentage was not significant (p ≥ 0.05). Furthermore, the semi-circular bunds significantly affected the number of species, number of individuals, Simpson's dominance, Margalef richness, Chao1 richness, and Shannon and Simpson diversity indices, while their effects on Menhinick richness and species evenness were not significant (p ≥ 0.05). The results of the omega-squared effect size indicated that the semi-circular bunds had the greatest effect on the species number of individuals (0.96) and the least effect on Menhinick richness (0.31). The chi-square goodness-of-fit test showed that in both inside and outside the semi-circular bunds, the log-normal model fitted the species abundance distribution data well, indicating that the species frequency distribution follows a log-normal pattern and reflects stable and diverse communities in these areas. 630 Special Comparative analysis of legal frameworks and upstream laws of rainwater harvesting: Global experiences and policy strategies in Iran Kiani-Harchegani Mahboobeh j Hazbavi Zeinab k j Ph.D., Department of Water Resources Basic Studies, Esfahan Regional Water Company, Ministry of Energy, Esfahan, Iran. Email: Mahboobeh.kiyani20@gmail.com k Associate Professor, Department of Range and Watershed Management, Faculty of Agriculture and Natural Resources, Water Management Research Center, University of Mohaghegh Ardabili, Ardabil, Iran. Email: z.hazbavi@uma.ac.ir 1 8 2026 14 3 55 72 24 06 2026 12 07 2026 Rainwater Harvesting Systems (RWHSs) emerge as an efficient, cost-effective, and environmentally sustainable solution that can significantly contribute to meeting water needs, particularly in urban and rural areas. However, the development of this technology in Iran faces numerous legal, institutional, and executive barriers. This paper aims to conduct a comparative analysis of the legal and regulatory frameworks governing rainwater harvesting at the global level and to examine its position within Iran's upstream laws and development programs. This study employs a descriptive-analytical approach utilizing library and documentary research methods. Data were collected through the examination of domestic laws and regulations (including the Law on Equitable Distribution of Water, the Seventh Five-Year Development Plan, and the General Policies on Water Resources) as well as the study of successful experiences of leading countries in rainwater harvesting. The gathered data were analyzed using content analysis and comparative analysis methods. The results indicate that countries adopt four general approaches toward rainwater harvesting: 1) Mandatory approach (e.g., Germany and Turkey), 2) Incentive-based approach (e.g., Brazil and Japan), 3) Facilitation approach (e.g., the United Kingdom and Malaysia), and 4) Restrictive approach (which was previously common in some countries). In Iran, despite clear mandates in upstream documents—such as the requirement to increase water harvesting by 15% in the Seventh Development Plan and the obligation of the Ministry of Energy to provide facilities in regions with rainfall exceeding 250 mm—no significant progress has been made in practice. The most critical barriers identified in the implementation of RWHSs in Iran are: 1) Legal vacuum resulting from the classification of rainwater as public property and the lack of clarity regarding its ownership, 2) Institutional weakness and the absence of a designated coordinating body among executive agencies, 3) Incomplete implementation of existing laws, and 4) Technical and financial obstacles such as high initial costs and the lack of codified national standards. 631 Special Superiority of the maximum entropy (MaxEnt) model over random forest for flood susceptibility mapping with limited data in semi-arid regions (Case Study: Alashtar Watershed, Lorestan Province, Iran) Arjmand Negar l Haghi Zadeh Ali m Fathi Ganji Reza n l Ph.D. Student, Department of Watershed Management, Faculty of Natural Resources, Lorestan University, Khorramabad, Lorestan Province, Iran. Email: Negar.arjmand87@gmail.com m Professor, Department of Watershed Management Engineering, Faculty of Natural Resources, Lorestan University, Khorramabad, Lorestan Province, Iran. Email: Email: haghizadeh.a@lu.ac.ir n Ph.D. Student, Department of Watershed Management, Faculty of Natural Resources, Lorestan University, Khorramabad, Lorestan Province, Iran. Email: fathiganji.reza@ut.ac.ir 1 8 2026 14 3 73 94 02 07 2026 22 07 2026 This study aimed to conduct flood susceptibility zoning using artificial intelligence models in the Alashtar watershed, located in Lorestan Province, Iran. The study area, covering 797.64 km², is part of the Karkheh sub-basin and experiences a semi-arid, cold climate with an average annual precipitation of 570 mm.In this research, ten influencing factors namely, slope, aspect, precipitation, distance from roads, distance from rivers, soil type, land use, geological formation, Topographic Wetness Index (TWI), and drainage densitywere employed as input data. From a total of 58 observation points (comprising 33 flood points and 25 non-flood points), 70% were allocated for model training and the remaining 30% for validation. The performance of two models, Random Forest (RF) and Maximum Entropy (MaxEnt), was evaluated using the Receiver Operating Characteristic (ROC) curve and the Area Under the Curve (AUC) index.The results indicated that the MaxEnt model, with AUC values of 0.98 in the training phase and 0.93 in the validation phase, demonstrated superior performance in predicting flood susceptibility. Analysis of the influencing factors revealed that most floods occurred under the following conditions: precipitation classes of 600–700 mm, distances of 0–100 m from roads and rivers, slope classes of 0–5% and 5–15%, northwest-facing aspects, rainfed agricultural land use, and old alluvial formations. According to the susceptibility map, 83.23% of the area fell into the very low susceptibility class, 9.22% into the low class, 4.66% into the moderate class, 2.12% into the high class, and only 0.74% into the very high class. Furthermore, a direct relationship was observed between the TWI and flood occurrence. Finally, the flood susceptibility zonation map was prepared using the superior MaxEnt model. 615 Special Rainwater harvesting potential from insulation surfaces for supplemental irrigation of the Damask rose farm (Case study: Ismail Abad Agricultural Research Station, Qazvin) Uossef Gomrokchi Afshin o Roghani Mohammad p o Assistant Professor, Agricultural Engineering Research Department, Qazvin Agricultural and Natural Resources Research and Education Center, AREEO, Qazvin, Iran. Email: a.gomrokchi@areeo.ac.ir p Assistant Professor, Soil Conservation and Watershed Management Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran. Email: moroghani@gmail.com 1 8 2026 14 3 95 110 28 03 2026 26 07 2026 Rainwater harvesting systems in many parts of the world, especially in arid and semi-arid regions, are considered a practical method to minimize drought risk. Rainwater harvesting from insulated surfaces is a simple, low-cost approach that can complement other water sources, especially in areas where water is scarce. Several factors determine the reliability of rainwater harvesting systems, and structures designed in accordance with local climatic patterns improve operational reliability. This study was conducted at the Ismail Abad Agricultural Research Station in Qazvin Province to assess the feasibility of meeting part of the water requirement of the Damask rose farm by capturing rainfall. In this research, the rational method was used to determine the roof's maximum flow rate. Also, the water requirement of the Damask rose farm was estimated using CROPWAT software and based on 10-year statistics from the Ismail Abad Meteorological Station. The results indicate that the total amount of rain collected from insulation surfaces is 7734 m2, 2606 m3 y-1, and this amount of water extracted from insulation surfaces in the form of suitable storage will provide about 20% of the 4 ha of the Damask rose farm. Also, the amount of water extracted from the water requirement of an 8300 m2 Damask rose by the amount of water used in the field by the hydro module. This volume of harvested water represents the maximum potential of rainwater catchment areas to meet the water needs of the farm. In general, rainwater harvesting systems require accurate calculations of the harvested runoff volume and the water storage tank volume due to the implementation of rainwater harvesting operations in a relatively small area. Estimating the volume of water storage tanks in rainwater harvesting systems can be related to the annual rainfall, the temporal pattern of rainfall, the dimensions of the rainwater catchment areas (especially the area of the roofs), the water needs of the plants, and the temporal pattern of water consumption in the farm. 624 Special Evaluation of GPM-IMERG precipitation estimate errors using empirical quantile mapping for runoff management in the Caspian Coastal Region Salahi Bromand Shahi Ali Professor, Department of Physical Geography, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran, Salahi@uma.ac.ir Former Ph.D. Student, Department of Physical Geography, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran, ali.shahi@uma.ac.ir 1 8 2026 14 3 111 128 08 06 2026 30 07 2026 This study aimed to evaluate and bias-correct GPM-IMERG satellite precipitation estimates using the Empirical Quantile Mapping (EQM) method in the Caspian Sea coastal region of Iran over the 2005–2014 period. To this end, daily precipitation data from five synoptic stations—Bandar Anzali, Rasht, Ramsar, Babolsar, and Gorgan—representing the diverse climatic characteristics, were used. Ground-based observations were obtained from the Iran Meteorological Organization (IRIMO), while GPM-IMERG satellite data were retrieved via the Google Earth Engine (GEE) platform. The performance of the satellite estimates and the effectiveness of the bias correction were evaluated at daily, monthly, and annual timescales using several statistical metrics, including the Pearson correlation coefficient, Root Mean Square Error (RMSE), Nash–Sutcliffe Efficiency (NSE), Percent Bias (PBIAS), Probability of Detection (POD), and False Alarm Ratio (FAR). Additionally, Taylor diagrams were employed to simultaneously assess correlation, standard deviation, and root-mean-square error, analyzing satellite performance before and after bias correction. The results indicated that applying the EQM method improved GPM-IMERG performance at most stations across both daily and monthly timescales. At the daily scale, RMSE decreased by 5.7% to 20.4% across all stations. Furthermore, the absolute percent bias (∣PBIAS∣) converged toward zero, showing reductions ranging from 47.1% to 98.9%. The NSE values also improved across all stations, though they remained negative in most cases at the daily level. On the monthly scale, the impact of the bias correction was more pronounced; RMSE decreased by 6.2% to 27.9% in four out of five stations, although it increased by 4.6% in Bandar Anzali. Additionally, ∣PBIAS∣ decreased across all stations, with reductions ranging from 56.5% to 98.6%. Moreover, monthly NSE exhibited notable improvements, rising from 0.43 to 0.70 in Gorgan, 0.29 to 0.41 in Rasht, and -0.29 to 0.13 in Ramsar.