ارزیابی دقت نقشه های خاک جهانی و منطقه ای در پیش بینی جریان با استفاده از مدل SWAT حوزه آبخیز تالار استان مازندران (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
در اکثر کشورهای درحال توسعه، داده های جامع مرجع مکانی دقیق خاک هنوز در دسترس نیست. FAO از طریق پایگاه داده هماهنگ شده جهانی خاک، نقشه جهانی را آماده سازی کرد. هدف این مطالعه ارزیابی جزئیات موردنیاز نقشه منطقه ای در مقایسه با نقشه جهانی خاک حوزه آبخیز تالار با استفاده از مدل SWAT بود. در این مدل، داده های اقلیمی 2017-2004 برای شبیه سازی رواناب استفاده شد. دو سال اول به عنوان دوره گرم کردن مدل، سال های 2015-2005 جهت واسنجی و 2017-2016 برای صحت سنجی مدل بکار گرفته شد. تحلیل حساسیت و عدم قطعیت در نرم افزار SWAT-CUP با کمک الگوریتم SUFI-2 انجام شد. ارزیابی مدل با استفاده از آماره های ضرایب تبیین (R2) و نش- ساتکلیف (NSE) انجام شد. پارامتر ظرفیت آبِ قابل دسترس خاک، پارامتر حساس تعیین شد. بارش (جریان روزمینی) قبل از واسنجی، 7/32 درصد (جهانی) و 3/29 درصد (منطقه ای) شبیه سازی شد. پس از واسنجی بر اساس نقشه خاک منطقه ای (NSE=0.56 و R2= 0.74) و جهانی (NSE=0.56 و R2= 0.64) و در مرحله صحت سنجی نیز به ترتیب منطقه ای (NSE=0.59 و R2= 0.76) جهانی (NSE=0.62 و R2= 0.75) برآورد گردید. نتایج بیانگر عملکرد قابل قبول مدل در شبیه سازی جریان بود. زیر حوضه 9 (جنگل برگ ریز) و 14 (چراگاه تابستانه) به ترتیب کمترین و بیشترین سهم را در تولید رواناب داشتند. نقشه منطقه ای نتایج مطمئن تری ارائه نمود. اگرچه اطلاعات اضافی ارائه شده نقشه منطقه ای ضمن تغییر پارامترهای بهینه شده در مدل، فاقد تأثیر بر جریان خروجی حوضه است، نتایج حاکی از عدم تأثیر قابل توجه نقشه خاک منطقه ای، بر پیش بینی جریان بود و می توان در صورت عدم دسترسی آن، از اطلاعات نقشه خاک جهانی استفاده کرد.Evaluation of Global and Regional Soil Maps in Flow Forecasting using SWAT Model (Talar Watershed, of Mazandaran Province)
In most developing countries soil georeferenced data is not yet available. The FAO prepared the global map through the Coordinated Global Soil Database. The aim of this study was to evaluate the required details of the regional map in comparison with the soil global map of Talar watershed using the SWAT model. In this model, climatic data of 2004-2017 were used to simulate runoff. The first two years were used as model warm-up period, 2005-2015 for calibration and 2016-2017 for model validation. Sensitivity and uncertainty analysis, was done in SWAT-CUP software with the help of SUFI-2 algorithm. The evaluation of the model was done using the coefficients of explanation (R2) and Nash-Sutcliffe (NSE) statistics. The available soil water capacity (SOL_AWC) parameter was determined as a sensitive parameter. Before calibration, 32.7% (global) and 29.3% (regional) precipitation was simulated as daily flow. After recalibration based on the regional soil map (NSE=0.56 and R2=0.74) and global (NSE=0.56 and R2=0.64) and in the verification stage according to the regional soil map (NSE=0.59 and R2=0.76) and global (NSE=0.62) and R2=0.75) was estimated. The results showed the acceptable performance of the model in flow simulation. Sub-basin 9 (deciduous forest) and 14 (summer pasture) had the lowest and highest share in runoff production, respectively. The regional map provided more reliable results. Although the additional information provided by the regional map, while changing the optimized parameters in the model, has no effect on the outflow of the basin, the results indicated that the regional soil map has no significant effect on the flow prediction, and if it is not available, the global soil map information can be used.Extended AbstractIntroductionDue to the limitation of measurement methods in flood control projects and the need to have a method to generalize existing statistics to basins without statistics or places where measurement is not possible, simulating changes in Future hydrology is one of the main reasons for hydrological simulation. Hydrologists and water resource managers have widely used hydrological models to simulate such changes in the past decades. One of the hydrological models is the Soil and Water Assessment Tools or SWAT model, which was presented in the United States to evaluate the effects of conservation agriculture on hydrological processes and water quality at the watershed scale in 1998. In the SWAT model, the watershed is divided into several sub-basins. Using sub-basins in simulation is beneficial, especially for areas with complex soil characteristics and land use. Then these sub-basins are divided into hydrological response units (HRUs) with the same soil characteristics, land use and management. One important and effective data in this model is soil data and map. Soil data and its related characteristics, including permeability and water retention capacity, determine the amount of runoff production. In most research studies and practical plans, the lack of appropriate soil information prevents researchers and decision-makers from using hydrological models to determine sub-basins sensitive to runoff production. While the existence of soil information (global maps) can make it possible to use hydrological models in basins without measured soil data. This information is such that due to the need for exorbitant cost in stratification and creation of soil profile, usually most areas of the country lack regional soil data, and the need to use the global soil map becomes necessary in such areas. Since this research compares two maps in two different scales for the first time, the main goal of this research is to prepare global and regional soil maps for the Talar watershed of Mazandaran province as one of the most effective SWAT model inputs, the accuracy of this model with two different inputs from soil maps will also be checked in predicting the runoff flow. MethodologyThe first step to implement the SWAT model is to create hydrological response units (HRUs), which form the basis of the work in this study and the Talar watershed as one of the essential sub-basins of the Mazandaran Sea. HRUs are produced by integrating the map of sub-areas created in the study area (through DEM map), soil map, land use and slope. Finally, based on the input maps to the model, 14 sub-basins and 45 hydrological response units (HRUs) were produced in the study area. According to the input data type (minimum and maximum temperature information), the Hargreaves method was used to estimate daily reference evaporation-transpiration when the data of sunshine hours, relative humidity and wind speed were unavailable. In the simulation, the observational data of 2005-2015 were used for calibration and 2016-2017 for model validation. In order to adapt the model to the existing environmental conditions in the region, the first two years of simulation (2004-2005) were considered to warm up the model. After the calibration, the model's accuracy was measured using the obtained parameters and the observed values that were not used in the calibration stage. In case of acceptable simulation, the model will be ready for use. In order to evaluate the efficiency and accuracy of the SWAT model, two coefficients of determination (R2) and Nash-Sutcliffe coefficient of efficiency (NSE) were used. According to the research based on soil maps, firstly, a global soil map was prepared according to the global raster map, and after analysis in GIS, the soil type of the area was determined and entered into the SWAT database. On the other hand, having the data and soil layers of the region, a regional soil map was prepared, and this map was prepared for entering the SWAT model. After preparing the soil maps (global and regional), the model was implemented twice (the first time by entering the global soil map and the second time by entering the regional soil map). Then, after implementation with two different projects, the outputs of the model were extracted and compared with each other. Finally, to check the model's accuracy using the above maps' inflow forecasting, it was calibrated and verified through SWAT-CUP. Results and DiscussionAt first, by running the model in two simulation modes (based on the regional and global soil map) in the GIS environment, the Talar watershed was divided into 14 sub-basins and 45 hydrological response units. The results showed that approximately 29.3% of the basin's precipitation and 32.7% of it were lost as base flow or surface flow, respectively, in the global and regional soil maps. Therefore, in these two cases, the simulation resulted in the lowest amount of surface runoff (in the soil map of the region) and the highest amount of evaporation-transpiration (in the global soil map). By analyzing the general sensitivity of the desired parameters, the available soil water capacity parameter (SOL_AWC) was determined as the most sensitive parameter. After the recalibration of the model based on the regional soil map (NSE=0.56 and R2=0.74) and global (NSE=0.56 and R2=0.64) and in the verification stage also according to the regional soil map (NSE=0.59 and R2=0.76) and global (NSE= 0.62 and R2 = 0.75) were estimated. Also, the simulated flow (surface and base flow) decreased after recalibrating the model. Evaporation-transpiration and feeding to the deep aquifer increased due to the reduction of capillary rise from the shallow aquifer and the reduction of the minimum amount of water storage required in the aquifer for the base flow event. Despite improving the model's performance in Talar watershed during calibration and validation using the regional soil map, the simulated discharge at the outlet was higher than the observed discharge. So, in the calibration period, compared to the validation period, the model predicted the peak discharge much better. Using the global soil map, the model overestimated the discharge compared to the regional soil map. Therefore, the global soil map showed less accuracy than the regional soil map in the SWAT model, and the results of this research also showed that using soil information with good resolution can improve flow prediction. ConclusionsIn this study, we used soil information from regional and global soil maps to evaluate the effect of soil data representation and spatial variability. Flow forecasting was done in basin hydrology simulation using the SWAT hydrological model. Before calibrating the model, other water balance components decreased compared to calibrating period except for evapotranspiration. There is no significant difference between the coefficients obtained in the calibration and validation periods of the model. Therefore, the obtained coefficients show the model's efficiency in the direction of runoff simulation in Talar watershed. The results indicate that the use of regional soil information with more spatial details does not significantly affect flow prediction, and global soil information in the form of a global map can be used if this information is unavailable. The additional information provided in the regional soil map, although it can change the optimized parameters in the model, does not affect the watershed discharge. Our simulation results showed the effect of the global soil map used on flow forecasting for Talar watershed, and good resolution soil information (such as regional soil map) can also improve flow forecasting. FundingThere is no funding support. Authors’ Contribution All of the authors approved thecontent of the manuscript and agreed on all aspects of the work. Conflict of Interest Authors declared no conflict of interest. AcknowledgmentsWe are grateful to all the scientific consultants of this paper
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