Pacific Southwest Inter-Agency Committee Research Articles

Comparative assessment of FSM and MPSIAC models in quantifying soil sedimentation rates in the semi-humid and alpine regions of northern Iran.

Soil erosion and sediment yield is a global problem that increasingly contributes to soil degradation. Although erosion analysis requires the availability of erosion and sedimentation data, the lack of sediment monitoring stations and the resulting limitations in collecting sediment measurements have necessitated the use of experimental models in many areas. The present study aimed to compare Factorial Scoring Model (FSM) and Modified Pacific South-West Inter-Agency Committee (MPSIAC) model for estimating erosion in the Mazdaran Basin (Firoozkuh, Iran). For this purpose, the required maps were prepared for both models, and the sediment rate was estimated using the two models to compare their efficiency using the corresponding maximum error (ME) and coefficient of determination (R2) values. The results showed that considering sediment based on the FSM model, the studied catchment consisted of regions with a high and very high sediment yield, while the MPSIAC model identified regions with low, medium, and high sediment yield. With an R2 value of 0.62 and an ME value of 2.24, the MPSIAC model provided more accurate estimates of the sediment yield in the studied area. Using the MPSIAC model, sediment yield was 6687.86 tons per year or the equivalent of 2.64 tons/ha per year.

Accommodating uncertainty in soil erosion risk assessment: Integration of Bayesian belief networks and MPSIAC model

Accommodating uncertainty stands as one of the most salient challenges in the development of soil erosion assessment tools. We presented a novel approach integrating the Modified Pacific Southwest Inter-Agency Committee (MPSIAC) model and Bayesian Belief Networks (BBNs) to assess soil erosion in a region of western Iran. The soil erosion status was reckoned based on the nine factors of MPSIAC. We utilized BBNs to produce a causal model for soil erosion, with output probabilities being validated through re-evaluation and sensitivity analysis. We identified erosion types, geological formations, run-off, soil erodibility, soil permeability, soil characteristics, and precipitation intensity as the main determinants of soil erosion. A significant, positive correlation existed between the erosion rate derived from MPSIAC and BBNs model in all land-use/covers over the work units. Overall, this study highlighted the potential of BBNs as a supportive tool for soil erosion prediction as well as a relatively simple and updatable soil erosion model for dealing with the diagnostic, scenario, and sensitivity analysis. Considering the increasing incidence of soil erosion, the BBNs model proposed in this study can be extended to a variety of ecosystems that are subject to soil erosion and changes in the probability of its causal factors.

Improved MPSIAC model for soil erosion rate assessment in semiarid zones

Erosion of soil by water is one of the most significant forms of soil degradation. The validity of the Modified Pacific South-West Inter-Agency Committee (MPSIAC) model for assessment of soil erosion rates has been demonstrated in many countries. We propose an improved version of the MPSIAC model to determine the erosion rate and expected sediment yield in two scenarios, conservative and adverse. Three microcatchments were selected from an arid semi-desert biome in Mexico, chosen for their advanced state of soil erosion by water and soil degradation. The improvements introduced to the MPSIAC model made field and laboratory work easier and can improve the methodology used for management of watersheds with similar conditions anywhere in the world. The improvements are related to selecting the microcatchment size, adding new categorization level of sediment yield, and calculating the time of rain concentration and modified erodibility factor K. The sensitivity analysis showed that runoff, surface erosion and channel erosion parameters are the most significant and soil factor K is the least sensitive parameter of the model. The improvements will support decision-making processes and selection of control practices that are best suited to the particular needs of each site and to preventing soil erosion risks.

Assessment of Annual Erosion and Sediment Yield Using Empirical Methods and Validating with Field Measurements—A Case Study

To implement soil conservation approaches, it is necessary to estimate the amount of annual sediment production from a watershed. The purpose of this study was to determine the erosion intensity and sedimentation rate from a watershed by employing empirical models, including the modified Pacific Southwest Inter-Agency Committee (MPSIAC), the erosion potential method (EPM), and Fournier. Moreover, the accuracy of these empirical models was studied based on field measurements. Field measurements were conducted along two reaches of Babolroud River. Total sediment transport, including suspended load and bed load, was predicted. Bed load transport rate was measured using a Helly–Smith sampler, and suspended load discharge was calculated by a sediment rating curve. The results of this study indicate that the erosion intensity coefficient (Z) of the Babolroud watershed is 0.54, with a deposition rate of 166.469 m3/(km2.year). Due to the existence of unusable crops, the highest amount of erosion appeared in the northern region of the watershed. The results using the EPM and MPSIAC models were compared with field measurements and indicated that both models provided good accuracy, with differences of 22.42% and 20.5% from the field results, respectively. Additionally, it could be concluded that the Fournier method is not an efficient method since it is unable to consider the erosion potential.

Investigating Anzali Wetland Sediment Estimation Using the MPSIAC Model

The adverse effects of upland erosion impact the Anzali Wetland in Iran. The Modified Pacific South-west Inter Agency Committee model (MPSIAC) was used to estimate the sediment yield in the watershed. The watershed was divided into twelve sub-watersheds based on the geomorphologic features and waterway orientations (Sw0-Sw11). To investigate the effect of different factors on erosion and sedimentation, data were digitized using ArcGIS software. The effective factor weights were determined using the MPSIAC model, and the total sediment yield was calculated for each sub-watershed. Results showed that the amount of particulate sediment in the critical sub-watersheds Sw6and Sw9was 777.9 and 730.2 t km−2. yr−1, respectively. Based on erosion and sedimentation results, the sub-watershed erosion was prioritized as Sw6> Sw9> Sw4> Sw1> Sw0> Sw5> Sw2> Sw8> Sw3> Sw11> Sw7> Sw10. Both model inputs (precipitation) and outputs (sediment) at different parts of the watershed were assessedviapoint observations data. Comparison of correlation values reveals that the correlation between the simulated and sampling values was strong in sub-watershed 1 (R2< 0.8). EF, RMSE, nRMSE, CRM, and MAE were 0.23, 16.74 tons per year, 5.05%, 0.55, and −3.6, respectively, which indicates the model’s high performance in Sw0. Areas with insufficient cover and bare soil showed a high correlation with the final erosion model. Thus, land-use classes, such as dense vegetation and good pastures, correspond to areas with low erosion. Conversely, bare soils and poor pastures were located on the eroded flats.

Morphometric Analysis for Soil Erosion Susceptibility Mapping Using Novel GIS-Based Ensemble Model

The morphometric characteristics of the Kalvārī basin were analyzed to prioritize sub-basins based on their susceptibility to erosion by water using a remote sensing-based data and a GIS. The morphometric parameters (MPs)—linear, relief, and shape—of the drainage network were calculated using data from the Advanced Land-observing Satellite (ALOS) phased-array L-type synthetic-aperture radar (PALSAR) digital elevation model (DEM) with a spatial resolution of 12.5 m. Interferometric synthetic aperture radar (InSAR) was used to generate the DEM. These parameters revealed the network’s texture, morpho-tectonics, geometry, and relief characteristics. A complex proportional assessment of alternatives (COPRAS)-analytical hierarchy process (AHP) novel-ensemble multiple-criteria decision-making (MCDM) model was used to rank sub-basins and to identify the major MPs that significantly influence erosion landforms of the Kalvārī drainage basin. The results show that in evolutionary terms this is a youthful landscape. Rejuvenation has influenced the erosional development of the basin, but lithology and relief, structure, and tectonics have determined the drainage patterns of the catchment. Results of the AHP model indicate that slope and drainage density influence erosion in the study area. The COPRAS-AHP ensemble model results reveal that sub-basin 1 is the most susceptible to soil erosion (SE) and that sub-basin 5 is least susceptible. The ensemble model was compared to the two individual models using the Spearman correlation coefficient test (SCCT) and the Kendall Tau correlation coefficient test (KTCCT). To evaluate the prediction accuracy of the ensemble model, its results were compared to results generated by the modified Pacific Southwest Inter-Agency Committee (MPSIAC) model in each sub-basin. Based on SCCT and KTCCT, the ensemble model was better at ranking sub-basins than the MPSIAC model, which indicated that sub-basins 1 and 4, with mean sediment yields of 943.7 and 456.3 m 3 km − 2 year − 1 , respectively, have the highest and lowest SE susceptibility in the study area. The sensitivity analysis revealed that the most sensitive parameters of the MPSIAC model are slope (R2 = 0.96), followed by runoff (R2 = 0.95). The MPSIAC shows that the ensemble model has a high prediction accuracy. The method tested here has been shown to be an effective tool to improve sustainable soil management.

Erodibility and sedimentation potential of marly formations at the watershed scale

Grupi and Kashkan marl formations comprise a considerable part of Zagros region. These formations have a considerable erodibility and sedimentation potential because of their special geological and mineralogical characteristics. The objective of this study was to compare the erosion and sediment yield of Kashkan and Grupi formations in Merk watershed located in southeast Kermanshah, using the Modified Pacific Southwest Inter-Agency Committee model. This model is suitable for estimating erosion and sediment intensity within each geomorphologic unit comprising nine effective environmental factors as geological, pedological, climate, runoff, topography, land cover, land use, surface, and river erosion factors. The results indicated that Kashkan formation comprises siltstone, sandstone, shale, and conglomerate, and Grupi formation contains shale, clay, and limestone with a high erodibility potential. Field measurements and soil samples analyzed for effective factors releaved that sediment yield for Merek watershed was 18080.6 m3/ha/y. Furthermore, field measurement and soil samples analyzed for effective factors releaved that sediment yields for Kashkan and Gurpi were 7243.3 and 10837.5 m3/ha/y, respectively. The reasons for erosion intensity and sedimentation in the two mentioned formations are slopes, vegetation and land use in addition to the type of rocks in Kashkan and Gurpi formations which are predominantly marl and shale.

Application of sediment rating curves to evaluate efficiency of EPM and MPSIAC using RS and GIS

Erosion potential method (EPM) and Modified Pacific Southwest Interagency Committee (MPSIAC) are two empirical models for estimating soil erosion and sediment delivery. These models use a relatively simple formulation, but they are still applied in various areas with different environmental conditions. However, evaluation of their efficiency is challenging. Accordingly, the main purpose of this study is investigating the performance of EPM and MPSIAC in estimating soil erosion and sediment yield using sediment rating curve (SRC) methods. Talar watershed in Iran was selected as the study area and suspended sediment load (SSL) of two Shirgah–Talar and Valikbon stations were used to assess the output of the models. Remote sensing and geographic information system were utilized in implementing the models. The estimated sediment yield values by the models were evaluated using the results of least square error regression and quantile regression (QR) SRC methods. Then, sediment yield values were obtained from 20-year discharge data (1992–2011). Despite the high uncertainty of QR results, the annual sediment delivery values of the models were achieved in an acceptable range. The most likely (with a probability of 0.5) average annual SSL values were between 713 × 103 and 840 × 103 ton for Shirgah–Talar station. Those values for Valikbon station were between 3142 × 101 and 3702 × 101. Moreover, the estimated average sediment yield in Shirgah–Talar station using MPSIAC and EPM were 591392 and 514054 ton/year, respectively. Those values for Valikbon station were 51881 and 27449 ton/year. Then, the results proved the better performance of MPSIAC in estimating SSL in the study area compared with EPM.

An improved RUSLE/SDR model for the evaluation of soil erosion

The accurate assessment of soil erosion is key to assess environmental parameters, such as the reduction in soil fertility, the increase in flood risk, the loss of nutrients, and degradation of water quality. In this study, we developed a methodology using the Revised Universal Soil Loss Equation (RUSLE) with the sediment delivery ratio (SDR) to estimate the annual amount of soil erosion and sediment yield in the Nozhian watershed (western Iran). The weighted total least-squares (WTLS) algorithm was applied to generate the rainfall–runoff erosivity surface using rainfall data and a digital elevation model (DEM) instead of traditional interpolation methods. The results demonstrated that the obtained sediment yield by the RUSLE/SDR model was approximately 802,000 tons per year. More than half of the watershed (61.6%) belonged to the high and severe erosion classes (20–100 t/ha year), and the mean soil erosion rate in the study area was 89.32 t/ha year. Several landslides extracted using a Google Earth map by expert interpretation were exactly consistent with areas that had high erosion rates based on the RUSLE results. This compatibility implies the compatibility between the results and reality. According to the statistical analysis, topographic features, especially slope steepness, had the greatest effect on the rate of soil erosion in the region. The results of our RUSLE/SDR analysis were also compared with the reported results from the Modify Pacific Southwest Interagency Committee (MPSIAC), Erosion Potential method (EPM), and Hydrophysical model. In situ data from the measured annual sediment yield during a 40-year interval from a hydrometric station were used for the accuracy analysis. The comparison indicated improvement in the accuracy of our approach by up to 65% in comparison to other reported results. These results can surely aid in the implementation of soil management and conservation practices to reduce soil erosion in the Nozhian watershed.

Spatial prediction of soil erosion susceptibility: an evaluation of the maximum entropy model

Soil erosion is considered as the most widespread form of soil degradation which causes serious environmental problems. This study investigates the performance of the maximum entropy (ME) in mapping rill erosion susceptibility in the Golgol watershed, Ilam province, Iran. To this end, ten rill erosion conditioning factors were selected to be employed in the modelling process based on an investigation of the literature. These layers are: elevation, slope percent, aspect, stream power index, topographic wetness index, distance from streams, plan curvature, lithology, land use, and soil. Then, a training dataset of rill erosion locations was used for modelling this phenomenon. The area under receiver operating characteristics curve was used for evaluating the performance of the ME model. In addition, Modified Pacific South-West Inter Agency Committee (MPSIAC) framework was applied and sediment yield was determined for different hydrological units in the study area. At last, Jackknife test was implemented to show the contribution of the factors in the modelling process. The results depicted that area under ROC curve for training and validation datasets were 0.867, and 0.794, respectively. Therefore, this conclusion can be achieved that ME worked well and could be a good tool for generating rill erosion susceptibility maps and its output could be employed for soil conservation in similar areas.

Investigation of RS and GIS techniques on MPSIAC model to estimate soil erosion

Soil erosion due to surface water is a standout among the serious threat land degradation problem and an hazard environmental destruction. The first stage for every kind of soil conservation planning is recognition of soil erosion status. In this research, the usability of two new techniques remote sensing and geographical information system was assessed to estimate the average annual specific sediments production and the intensity erosion map at two sub-basins of DEZ watershed, southwest of Lorestan Province, Iran, namely Absorkh and Keshvar sub-basins with 19,920 ha, using Modified Pacific Southwest Inter-Agency Committee (MPSIAC) soil erosion model. At the stage of imagery data processing of IRS-P6 satellite, the result showed that an overall accuracy and kappa coefficient were 90.3% and 0.901, respectively, which were considered acceptable or good for imagery data. According to our investigation, the study area can be categorized into three level of severity of erosion: moderate, high, and very high erosion zones. The amount of specific sediments and soil erosion predicted by MPSIAC model was 1374.656 and 2396.574 m3 km−2 year−1, respectively. The areas situated at the center and south parts of the watershed were subjected to significant erosion because of the geology formation and ground cover, while the area at the north parts was relatively less eroded due to intensive land cover. Based on effective of nine factors, the driving factors from high to low impact included: Topography > Land use > Upland erosion > Channel erosion > Climate > Ground cover > Soil > Runoff > Surface geology. The measured sediment yield of the watershed in the hydrometric station (Keshvar station) was approximately 2223.178 m3 km−2 year−1 and comparison of the amount of total sediment yield predicted by model with the measured sediment yield indicated that the MPSIAC model 38% underestimated the observed value of the watershed.

The use of spatial empirical models to estimate soil erosion in arid ecosystems.

The central objective of this project was to utilize geographical information systems and remote sensing to compare soil erosion models, including Modified Pacific South-west Inter Agency Committee (MPSIAC), Erosion Potential Method (EPM), and Revised Universal Soil Loss Equation (RUSLE), and to determine their applicability for arid regions such as Kuwait. The northern portion of Umm Nigga, containing both coastal and desert ecosystems, falls within the boundaries of the de-militarized zone (DMZ) adjacent to Iraq and has been fenced off to restrict public access since 1994. Results showed that the MPSIAC and EPM models were similar in spatial distribution of erosion, though the MPSIAC had a more realistic spatial distribution of erosion and presented finer level details. The RUSLE presented unrealistic results. We then predicted the amount of soil loss between coastal and desert areas and fenced and unfenced sites for each model. In the MPSIAC and EPM models, soil loss was different between fenced and unfenced sites at the desert areas, which was higher at the unfenced due to the low vegetation cover. The overall results implied that vegetation cover played an important role in reducing soil erosion and that fencing is much more important in the desert ecosystems to protect against human activities such as overgrazing. We conclude that the MPSIAC model is best for predicting soil erosion for arid regions such as Kuwait. We also recommend the integration of field-based experiments with lab-based spatial analysis and modeling in future research.

Study of Erosion and Sediment in the Zarak Catchment Area at Yazd Province, Iran, Using Modified P.S.I.A.C, E.P.M and B.L.M Methods and Comparison of them

Yazd province is one of the arid provinces of Iran and such regions are expected to experience wind erosion. Unlike expectation, in the Zarak catchment area that is located at Yazd province, because of fixation of the soil surface, water erosion is more than wind erosion. On the other hand, due to daily temperature changes, geological formations split and then due to heavy showers, such split blocks provide ideal conditions for surface erosion. Of course, on slopes, rill erosion can be seen. Also in the waterways, when flow discharge increase, due to concentration of the kinetic energy of water in the bends of waterway, bank erosion is found. Given the importance of soil protection programs and determining the methods of management of erosion and sediment as well as the reduction of calculation and the detailed design of the dam size at the storage dams, it is necessary to estimate total size of annual erosion and sediment in a catchment area. The Zarak catchment area is no exception. On the other hand with respect to the existence of multiple methods to do this, using a method with more reasonable data and saving cost and time, in addition providing acceptable and realistic answer is needed. Of course many parameters are involved. According to these matters, in this study, to study erosion and sediment, quantitative methods of modified Pacific Southwest Inter-Agency Committee (P.S.I.A.C) and Erosion Potential Method (E.P.M), also qualitative Bureau of Land Management (B.L.M) method were used and in the end, the results were compared. With using topographic maps and aerial photos, the initial map of each type of erosion was prepared and then by combining them with data and maps of rocks sensitivity, erosion, geology, geomorphology, slopes, vegetation types and land capabilities, etc. a base map was prepared. After that, by conducting field inspection, base map’s information was controlled and status of various erosions, slope, vegetation, condition of the bed and banks of the waterways, width and depth and materials of the bed and waterways were determined. Also erosion forms classes and their ranges were identified and the most important factors involved in the intensification of erosion were identified with using modified P.S.I.A.C, E.P.M and B.L.M methods.In the end ,the results of the three methods were compared.

Development of a risk-based multi-criteria approach for watershed prioritization with consideration of soil erosion alleviation (case study of Iran)

The classification of erosion-prone areas is a pre-requisite for providing an efficient watershed management as well as soil conservation. Thus, a practical decision support tool is required to assign priority weights to different related criteria. In this article, 13 effective soil erosion criteria have been used to prioritize different sub-watersheds in Arangeh watershed, Iran. The criteria have been classified in four groups of soil, geomorphology, topography and climate categories. The ranking outcomes of sub-watersheds via Modified Pacific Southwest Inter-Agency Committee method were compared with induced ordered weighted averaging (IOWA) model which considered hierarchy-based attitude and risk-based attitude (RBA) criteria. Copeland aggregation method was also applied as a benchmark for the comparison. Kendall’s Tau, a nonparametric stochastic test, investigated that RBA-based IOWA with fairly optimistic coefficient (α = 0.5) is the most conclusive ranking model because of its highest correlation coefficient which was about 0.9. Finally, the hierarchical clustering method classified sub-catchments. According to the results, four priority groups were identified based on vulnerability of sub-watersheds to soil erosion.

Assessment of sediment yield using RS and GIS at two sub-basins of Dez Watershed, Iran

Soil erosion is a serious threat to soil and water resources in semi-arid regions. Modified Pacific South-west Inter Agency Committee (MPSIAC) and Erosion Potential Method (EPM), as two well-known models, have shown their performance in many case studies. The goal of present study is to assess the efficiency of these methods for estimating the sediments yield and erosion intensity within short-term and long-term timeframes over two sub-basins of Dez watershed, west of Iran. The results showed that the study area can be categorized into slight, moderate, high and very high erosion zones. Almost half of the study area is highly susceptible to erosion due to the geological formations and land cover. Moreover, the long-term (i.e. 30 years) sediment yield of 387 and 615 (kton)y−1 estimated by MPSIAC and EPM models demonstrated the superiority of EPM. Compared to the measured value of 612 (kton)y−1, the performance of EPM was astonishing. By splitting the dataset into six periods of five years, the sediment yield was predicted in short-term periods by both aforementioned methods. Such segmentation provides the opportunity to evaluate the impact of extreme flooding events on the models performances. The results showed that both models failed in estimation of sediment load during flood conditions. Nevertheless, the correlation coefficients for estimating the sediment yield were found to be R=0.93 and R=0.85 for EPM and MPSIAC models respectively, for short-term simulations.

Quantifying modern erosion rates and river-sediment contamination in the Bolivian Andes

We use petrographic, mineralogical and geochemical data on modern river sediments of the Tupiza basin in the Bolivian Andes to investigate the relationships among human activity, heavy-metal contamination of sediments and modern erosion rates in mountain fluvial systems. Forward mixing model was used to quantify the relative contributions from each main tributary to total sediment load of the Tupiza River. The absolute sediment load was estimated by using the Pacific Southwest Inter Agency Committee model (PSIAC, 1968) after two years of geological field surveys (2009; 2010), together with data obtained from the Instituto Nacional del Agua public authority (INA, 2007), and suspended-load data from Aalto et al. (2006).Our results indicate that the sediment yield in the drainage basin is 910 ± 752 ton/km2year and the mean erosion rate is 0.40 ± 0.33 mm/year. These values compare well with erosion rates measured by Insel et al. (2010) using 10Be cosmogenic radionuclide concentrations in Bolivian river sediments. More than 40% of the Tupiza river load is produced in the upper part of the catchment, where highly tectonized and weathered rocks are exposed and coupled with sporadic land cover and intense human activity (mines). In the Rio Chilco basin strong erosion of upland valleys produce an increase of erosion (∼10 mm/year) and the influx of large amounts of sediment by mass wasting processes. The main floodplain of the Tupiza catchment represents a significant storage site for the heavy metals (∼657 ton/year). Fluvial sediments contain zinc, lead, vanadium, chromium, arsenic and nickel. Since the residence time of these contaminants in the alluvial plain may be more than 100 years, they may represent a potential source of pollution for human health.

Validation of PSIAC Model for Sediment Yields Estimation in Ungauged Catchments of Tanzania

The main objective of this paper is to report on preliminary validation results of the newly applied sediment yields estimation model in Tanzania, the Pacific Southwest Inter-Agency Committee (PSIAC). This is a follow-up research on the call to customize simple and/or multi-processes sediment yields estimation models such as PSIAC in the region. The PSIAC approach is based on a sediment yield classification scheme employing individual drainage basin characteristics: surface geology, soils, climate, runoff, topography, ground cover, land use, upland erosion, channel erosion, and sediment transport. In this study, PSIAC model is built from readily available environmental variables sourced from Government ministries/agencies and public domain global spatial data. The sediment classification exercise was verified with field observations. The set up model was then validated by 31 small dams’ siltation surveys and previous sedimentation study findings. PSIAC model performance for major part of central Tanzania was good during calibration (BIAS = 7.88%) and validation (BIAS = 18.12%). Another observation was that uncalibrated model performs fairly well, though performance improves with calibration. The extension of the uncalibrated PSIAC model to 3 selected large basins of Tanzania, with drainage areas size up to 223,000 km2, registered a satisfactory performance in one of them with fair performance in the rest. For large basins, the performance seems to correlate with general ground slope. The higher the slope, the better the performance. It is, however, not apparent from this study on the threshold drainage area and slope requirements for better performance of the model. Notwithstanding, the PSIAC model has improved previous sediment yields estimates based on simple regressive models. Finally, the paper proposes two main further research works: use of high resolution geospatial data and additional validation dams siltation data even beyond the central part of Tanzania, and carries out rigorous study on spatial scale model application limitations.

Evaluation of sediment yield and soil loss by the MPSIAC model using GIS at Golestan watershed, northeast of Iran

Watershed degradation due to soil erosion and sedimentation is considered to be one of the major environmental problems in Iran. In order to address the critical conditions of watershed degradation in arid and semiarid regions, a study based on the Modified Pacific Southwest Inter-Agency Committee (MPSIAC) model was carried out at Golestan watershed, northeast of Iran. The model information layers comprising nine effective factors in erosion and sedimentation at the watershed site were obtained by digitalization and spatial interpolation of the basic information data in a GIS program. These factors are geology, soil, climate, runoff, topography, land cover, land use, channel, and upland erosion. The source data for the model were obtained from available records on rainfall and river discharge and sediment, topography, land use, geology, and soil maps as well as field surveys and laboratory analysis. The results of the MPSIAC model indicated that 60.75 % (194.4 km2) and 54.97 % (175.9 km2) of the total watershed area were classified in the heavy sedimentation and erosion classes, and the total basin sediment yield and erosion were calculated as 4,171.1 and 17,813.4 m3 km−2 year−1, respectively. In the sensitivity analysis, it was found that the most sensitive parameters of the model in order of importance were topography (slope), land cover and use, runoff, and channel erosion (R2 = 0.92–0.94), while geology, climate (rainfall), soil, and upland erosion factors were found to have moderate effect to the model output (R2 = 0.74–0.59).

Evaluation of sediment yield in PSIAC and MPSIAC models by using GIS at Toroq Watershed, Northeast of Iran

Regarding the importance of watersheds in arid and semi-arid regions, it is necessary to better protect water supplies such as dam reservoirs. The most efficient way of conserving water sources is to apply proper management to decrease erosion and sedimentation. The first step of this process is to be aware of sediment yield (Qs)/production and identify erosive zones in upper reach of reservoirs. The present study aims to evaluate Qs and production in Pacific Southwest Inter-Agency Committee (PSIAC) and modified PSIAC (MPSIAC) models by using satellite data, GIS analysis, and field observations. According to the results, the study area can be categorized into five erosive classes: very high, high, moderate, low and negligible. The east part of the watershed is slightly eroded due to its hard surface geology and relatively flat topography characteristics, while the northern and southern parts of the basin are highly eroded because of the high erodibility potential of soil and intensive cultivation of the area. A comparison of the output maps from PSIAC and MPSIAC models showed that the calculated Qs in most parts correspond well in both models and with field observations. The results of regression between main determining factors (surface geology, soil, topography and land cover) and Qs derived from each model indicated moderate to strong correlation coefficient (R2 = 0.436−0.996 to 0.893–0.998) after PSIAC and MPSIAC models, respectively.

Sediment Yield Assessment of a Large Basin using PSIAC Approach in GIS Environment

Reservoirs are the key infrastructure for the socio-economic development of a country. The reservoirs are proven to be a remedial solution of highly erratic spatial and temporal availability of water. The growth in population and consequent developmental activities within a catchment area has shown to aggravate the problem of sedimentation which comprised of erosion, sediment transport and its deposition in these reservoirs. Among all above mentioned, reservoir sediment deposition is most important as it reduces its useful life and impairs the purposes of these vast water resource. The sediment yield has been considered as comprehensive index for assessing sustainability of such resources. The present study investigates the suitability of Pacific Southwest Inter-Agency Committee (PSIAC) model in determining the sediment yield rate for a drainage basin considering nine basin factors in geographical information system (GIS) environment. For the analysis, a large river basin at the foothill of Himalayas in India has been considered as case study. It was realized that the GIS approach made large basin characteristic sampling very easy and efficient for this hilly basin. A regression equation between specific sediment yield and effective model factors was established based on geomorphic features for this basin. It was observed that most of the basin area is falling under moderate to high sediment yielding potential zone, leading to high sediment yield.