[Abstract]Water quality in Australia’s northern grains farming areas often exceeds water quality trigger values for suspended sediments, nutrients and some herbicides (CBWC, 1999). While there are many land uses in these areas that contribute to the resultant water quality, of particular concern for the grains farming industry is the widespread detection in rivers of chemicals used by their industry, namely atrazine and metolachlor. A comparison of Hodgson Creek catchment (South East Queensland, Australia) herbicide data with national water quality guidelines shows that trigger values are frequently exceeded. That water quality trigger values are exceeded is expected for a highly modified catchment such as Hodgson Creek, and the Australian New Zealand Environment and Conservation Council (ANZECC) (2000) guidelines make provision that in such catchments, locally derived targets should be set. Natural resource managers therefore require skills in linking planned management with their ability to set or meet targets. The opportunity suggested itself for using catchment modelling to set realistic targets for water quality based on the adoption of best management farming practices. This study investigated the suitability of the Soil and Water Assessment Tool (SWAT) to fulfil this modelling role in an Australian context of land use management. To test the suitability of SWAT to fulfil this role, the study aimed to determine the feasibility of using the model to explicitly depict farm management practices at a paddock scale to estimate resultant catchment water quality outcomes. SWAT operates as two distinct sub-models. A hydrologic response unit (HRU) (the paddock scale model) generates runoff and constituents, and the output of many HRU are summed and routed through a stream network. The method for calibration of SWAT proposed in the user manual (Neitsch et al., 2001) is to calibrate against streamflow before calibrating sediment and then herbicides. The logic of testing in a process dependent order is sensible, however the method proposed by Neitsch et al. (2001) assumes that the HRU processes are reliable and calibration only need consider catchment scale processes. A review of the literature suggested that there had been limited testing of HRU process in studies where SWAT had been applied. Data available for model testing came from both paddock and catchment studies. The effects of cultivation management practices on runoff and erosion have been well characterised for the study area by Freebairn and Wockner (1996). Atrazine dissipation in soil and loss in runoff was available from a study of a commercial farm in the Hodgson Creek catchment (Rattray et al, 2007). An ambient and event based water quality monitoring for suspended sediments and herbicides provided data for the Hodgson Creek catchment for the period 1999 to 2004 (Rattray, unpublished data). The model required minimal calibration to achieve good predictions of crop yields and surface cover for winter crops. However, testing of summer cropping component revealed structural problems in SWAT associated with the end of a calendar year. Testing also revealed that perennial pastures and trees are modelled with unrealistic fluctuations in biomass and leaf area index. The model was able to represent hydrology well across a range of scales (1-50,000 ha). Catchment scale runoff data was well matched for a range of tillage treatments. The model was found to be able to attain a good prediction of monthly runoff at the catchment scale. This is consistent with the finding of most other SWAT studies. The model was able to represent average annual erosion reasonably well using the Universal Soil Loss Equation (USLE) when tested at the HRU scale (1 ha) against a range of tillage management data. When tested at the catchment scale the model was found to be able to match average annual sediment loads for the catchment however annual variability in sediment loads was poorly matched. Testing of the herbicide model for SWAT found that model compared poorly with paddock scale trial data. The reason for poor model performance can be attributed to an inadequate representation of processes and model output was unrealistic compared to our understanding of herbicide transport processes. When the model was tested at a catchment scale it was found to compare very poorly with catchment scale observations. This can be explained in part by the deficiencies of the HRU herbicide model, but is also due in part to difficulties in parameterisation of spatial and temporal inputs at the catchment scale. While SWAT provides a model with detailed physical processes, the capacity to apply the model is let down by an ability to practically determine the spatial and temporal extent of the farming practices (i.e. where and when are tillage and herbicides applied in the catchment). The challenge to applying SWAT is that farming practices in Australia vary markedly from year to year. SWAT requires the user to input crop practices in as a fixed rotation while Australia’s highly variable climate with unreliable seasonal weather patterns results in opportunistic farming practices. Hence this is a major limitation in the models ability to predict catchment outcomes, particularly for herbicides where off site losses are highly dependant on application timing. In attempting to validate herbicide losses at the whole of catchment scale it became apparent that uncertainty in the temporal variation of farm operations within the catchment poses a major limitation to accurately reproducing observations at the catchment outlet. It is concluded that that there is limited usefulness of SWAT for investigating the impacts of land management on catchment scale herbicide transport for Australian conditions.

In 2005 an assessment of existing Total Maximum Daily Load studies by the U.S. Environmental Protection Agency showed sediment as the fourth leading cause of water quality impairment. A source assessment is important in developing a successful TMDL. Past research efforts have focused on controlling erosion sources in agricultural and urban land areas. New research suggests major contributions to overall sediment loads may be due to stream channel degradation. Monitoring and modeling techniques to assess the contribution of channel sediment to overall sediment load are needed to determine the reductions necessary to meet water quality standards. This research focused on testing the ability of watershed and reach-scale models to predict stream channel degradation. Model predictions were compared to estimates developed from a system of erosion pins and scour chains. A 500-m experimental reach in Blacksburg, VA, USA, was selected as the focus of channel degradation monitoring and modeling efforts. A series of over 250 erosion pins and seven scour chains were installed systematically throughout the experimental reach. A monthly monitoring program measured channel degradation for the period from July 2005 - June 2006. Point data were interpolated across individual bank segments to produce an estimate of soil erosion volume. Measured soil bulk densities were then used to calculate the estimated mass loading to Stroubles Creek from channel degradation. Two watershed models and one reach-scale model were developed to predict sediment loading to the stream channel from channel degradation. The Generalized Watershed Loading Function (GWLF) was selected to represent watershed models with limited channel degradation process detail; the Soil and Water Assessment Tool (SWAT) represented the level of channel degradation detail seen in the majority of watershed models; and the CONservation Channel Evolution and Pollutant Transport System (CONCEPTS) reach-scale model was used to evaluate the effectiveness of a detailed process model. Monthly model predictions were compared to retreat rates measured using the erosion pin network. Sediment loading to the stream from bank retreat was estimated as 41 tonnes/yr, based on erosion pin measurements. GWLF, SWAT, and CONCEPTS predicted stream channel sediment contributions of 8 tonnes/yr, 1500 tonnes/yr and 4 tonnes/yr, respectively. Theil-Sen non-parametric simple linear regression was used to test agreement between monthly model predictions and erosion pin estimates. No significant agreement was found between any model predictions and measured retreat, using a conservative a-value of 0.2. GWLF model predictions underpredicted measured channel degradation, but most closely approximated observed data. This result is likely due to similarities in climate and watershed characteristics for the Stroubles Creek watershed and the Pennsylvania watershed used in the empirical model development. SWAT predicted retreat rates exceeded measured values by two orders of magnitude. This result is explained by the inability of SWAT to predict daily flow and sediment discharge. Highly sensitive channel degradation parameters and the lack of calibration data also contributed to SWAT simulation error. CONCEPTS simulation predicted monthly retreat rates slightly less than GWLF. The lack of agreement between CONCEPTS simulation and observed data was mainly the result of limited input data availability. SWAT daily discharge predictions were used as CONCEPTS input data and likely contributed to poor model agreement. Poor estimation of sensitive sediment input parameters may have also contributed to underpredictions by CONCEPTS. Results showed the potential of screening-level watershed models in channel degradation prediction and the importance of flow and sediment time series discharge data in detailed process-based simulation. The limited flexibility of the GWLF channel degradation algorithm makes it unsuitable for evaluating the effects of stream restoration. SWAT and CONCEPTS should only be used for evaluation if appropriate input data are available. Future research will focus on the development of a long-term flow and sediment monitoring data set. Few long-term data sets of this nature exist, making channel degradation modeling difficult. Development of long-term data will allow more accurate modeling and better assessment of channel restoration impacts on channel degradation. Further modeling with GWLF in geographic regions outside the Eastern United States is also needed to determine the scope of applicability of the GWLF channel degradation empirical relationship. Additional research should also focus on the significance of subaerial processes for watersheds of various sizes and on the development of algorithms to simulate these processes. / Master of Science

Published Article / This paper presents the set-up and the performance of the SWAT model in the Modder River Basin. Two techniques widely used, namely quantitative statistics and graphical techniques, in evaluating hydrological models were used to evaluate the performance of SWAT model. Three quantitative statistics used were, Nash-Sutcliffe efficiency (NSE), present bias (PBIAS), and ratio of the mean square error to the standard deviation of measured data (RSR). The performance of the model was compared with the recommended statistical performance ratings for monthly time step data. The model performed well when compared against monthly model performance ratings during calibration and validation stage.

Made available in DSpace on 2018-08-01T23:57:59Z (GMT). No. of bitstreams: 1 tese_10941_Dissertação - Luana - Final versão final eletronica.pdf: 3676894 bytes, checksum: 1e394ab09ed35e7ff57b847a108f68d1 (MD5) Previous issue date: 2017-04-19 / A modelagem de vazões médias vem acompanhada de incertezas relacionadas aos dados de entrada climatológicos e às características fisiográficas da bacia hidrográfica. A obtenção de vazões representativas da área de estudo requer o ajuste destas com os dados observados. Uma calibração satisfatória depende de uma série de fatores que interferem neste processo. Dessa forma, avaliou-se a eficácia da calibração das vazões estimadas pelo modelo Soil and Water Assessment Tool (SWAT) em uma bacia hidrográfica rural localizada no sul do estado do Espírito Santo, variando os parâmetros de calibração, diferentes estações de monitoramento de vazões, tamanho da série histórica e o número de sub-bacias envolvidas no processo, além de verificar o processo de análise de sensibilidade dos parâmetros de calibração e a influência dos mesmos e dos dados de entrada na estimativa das vazões. Os resultados da análise de sensibilidade identificaram que a maioria dos parâmetros mais sensíveis da área de estudo são iguais aos encontrados nos trabalhos realizados no Brasil e na região sudeste do país. Além disso, houveram diferenças nos parâmetros encontrados para cada tipo de análise realizada. As vazões médias obtidas pelo SWAT foram superestimadas quando comparadas com os dados observados, por isso foi necessário a calibração e análise da influência dos dados de entrada nesses resultados. Os testes de calibração foram realizados pelo programa SWAT-CUP e a eficácia de cada teste foi avaliada estatisticamente pelo Coeficiente de Eficiência de Nash-Sutcliffe (COE), Tendência Percentual (PBIAS) e Erro Quadrado Médio (EQM). Os testes de calibração com série longa de dados observados (29 anos) de duas estações fluviométricas não geraram resultados satisfatórios, o melhor resultado consistiu em variar todos os parâmetros de calibração em todas as sub-bacias da área de estudo. Utilizou esse teste com uma série histórica de 3 anos, e então foi possível obter uma calibração satisfatória com valores de COE iguais a 0,53 e 0,50, PBIAS iguais a 6,60 e 20,70 e EQM iguais a 0,72 e 0,69 para cada estação fluviométrica. Verifica-se que o processo de calibração é um ajuste fino, por isso requer que os dados simulados não apresentem resultados muito discrepantes com relação aos observados.

This study was conducted on two Mississippi watersheds. The SWAT model was applied to the Upper Pearl River Watershed (UPRW) to evaluate flow, sediment, nutrients, and fecal coliform bacteria (FCB) transport. The model was further applied to evaluate crop and sediment yields from three tillage systems (Conventional, Reduce 1, and Reduce 2) of the Big Sunflower River Watershed (BSRW). In the UPRW, flow and sediment simulations showed good to very good model performances (for flow R2 up to 0.76 and NSE up to 0.75; and for sediment R2 up to 0.72 and NSE up to 0.54). Both total nitrogen (TN) and total phosphorous (TP) simulations showed fair to good model performances (R2 up to 0.71 and NSE up to 0.63 for TN; R2 up to 0.70 and NSE up to 0.59 for TP). The FCB simulation showed good model performance (R2 up to 0.59 and NSE up to 0.58). In the BSRW, crop simulations showed good to very good model performances (for corn yield R2 up to 0.5 and NSE up to 0.9; and for soybean yield R2 and NSE up to 0.6). Furthermore, modeling outputs of the BSRW explained 64% of the water table fluctuations in the Mississippi alluvial aquifer. The future climates of the UPRW and the BSRW were evaluated for three emission scenarios (A1B, A2, and B1) from the Intergovernmental Panel on Climate Change (IPCC) with the help of the general circulation model, CCSM3. Simulations predict future sediment yields will increase as much as 25% in the UPRW. Both TN and TP yields will also be elevated as much as 7.3% and 14.3% respectively in future climates of the UPRW. Four best management practices (BMPs) were applied to the current and future climates in the UPRW and results showed that BMPs were able to reduce 51% of flow, 55% of sediment, 44% of TN, and 88% of TP in the baseline climate. Moreover, the effectiveness of TN removal will increase in future climates, while the effectiveness of TP removal will remain unchanged. The effects of climate variability on corn and soybean yield were insignificant in the BSRW.

The San Joaquin Valley is regarded as one of the most productive agricultural regions in the world. This extensive agriculture has, however, caused extensive pollution of both ground water and surface water. This thesis develops a hydrologic model of the surface and ground waters of the San Joaquin Valley. Such modeling is useful in the development and implementation of water quality regulations such as Total Maximum Daily Loads (TMDLs). A properly validated watershed simulation model can supplement data collection and can account for watershed characteristics including topography, soils, climate, land cover, anthropogenic activities, as well as simulate watershed responses including streamflow and contaminant concentration at detailed spatial and temporal scales. Models can be used as a decision support tool to manage complex agricultural watersheds such as the San Joaquin Valley. Once developed, such watershed simulation models can be used to identify contaminant source areas, locate hot-spot areas that have high pollution risk, identify optimal monitoring sites, and determine best management practices to cost-effectively reduce pollution. As a step towards developing a model as a decision making tool, the objective of this study is to appraise effectiveness of a widely used watershed simulation model known as Soil and Water Assessment Tool (SWAT) to simulate hydrology of the San Joaquin Valley watershed. For this thesis SWAT was successfully calibrated for streamflow at several locations in the watershed, thus demonstrating the capability of the model to represent the complex, snow-driven hydrology of the San Joaquin Valley watershed including dams and reservoirs located in the mountains, and agricultural activities and flow diversion systems in the valleys. Calibration of sediment and nitrate loadings in the surface waters were also attempted; the results were, however, less than convincing compared to stream flow calibration. Future studies are recommended to improve accuracy of the water quality predictions and to evaluate long-term effectiveness of various watershed management policies in improving surface water and groundwater quality in the San Joaquin Valley. The hydrology model developed in this study can be used as a foundation for future studies that focus on water quality.

No description available.

La Región Pampeana es la región más importante del territorio argentino por sus características del clima y el suelo que la transforman en una zona agrícola y ganadera por excelencia. Debido a su gran extensión presenta importantes variaciones espaciales y temporales en los regímenes de temperatura y precipitación. La condición de llanura predomina en esta región resultando un escenario de particular fragilidad ante eventos hidrológicos extremos, tanto de déficit como de exceso hídrico. En este último caso, la incapacidad del relieve de evacuar volúmenes importantes de agua, junto a otros factores, conduce a la ocurrencia de vastos y persistentes anegamientos. El clima y la hidrología son los factores físicos que condicionan las actividades sociales y económicas de la región. Influyen directamente en la disponibilidad de agua y determinan la variabilidad del recurso. El estudio y análisis de estos factores y la relación entre los mismos, colabora directamente en la comprensión del comportamiento de un sistema como es una cuenca hidrográfica. La herramienta más utilizada para simular el sistema climático de la tierra son los modelos de circulación general de la atmósfera, mientras que los modelos hidrológicos son herramientas ideales para el análisis y la evaluación del comportamiento de una cuenca hídrica. La interacción entre estas herramientas es de gran interés, dada la necesidad de contar con pronósticos en diferentes escalas para la correcta administración de los recursos y la prevención de eventos extremos. En este trabajo de Tesis se ha evaluado la capacidad de modelos estadísticos de regionalización del clima (downscaling) basados en regresión lineal múltiple, para cuantificar las anomalías de precipitación mensual en la Región Pampeana Argentina, incluyendo la región fitogeográfica El Espinal y el Sudoeste Bonaerense. Luego, se aplicaron estos modelos para estimar las anomalías trimestrales de la lluvia en los sitios mencionados, combinando un ensamble de simulaciones con el modelo de circulación general de la atmósfera MCGA CSIRO-9, forzadas con la temperatura de la superficie del mar observada (TSM) y la aplicación de los modelos estadísticos de downscaling para la regionalización de la lluvia. Los resultados obtenidos indican que el procedimiento de downscaling puede mejorar la confiabilidad en el signo de las anomalías de lluvia estimadas localmente, respecto de los resultados del modelo global, pero no mejora substancialmente la estimación de su magnitud. Como aplicación hidrológica, se calibró y validó el modelo hidrológico SWAT en dos cuencas de especial interés ubicadas en la Región Pampeana: La cuenca del río Salado, por su condición de llanura y gran extensión areal; y la cuenca del río Sauce Grande, por sus características geomorfológicas y gran importancia regional para el abastecimiento de agua potable a un importante sector del sudoeste bonaerense. Se llevaron a cabo análisis de sensibilidad a las variables utilizadas en la calibración de cada cuenca. Finalmente, se integró un sistema de pronóstico del clima (CFSv2) con el modelo hidrológico aplicado en la cuenca del río Salado para analizar si es posible generar un pronóstico dinámico de caudales en escala estacional. / The Argentinean Pampas is one of the most important agricultural and livestock regions of the country because of their climate and soil characteristics. Due to its large dimension, this region has significant spatial and temporal variations in temperature and precipitation regimes. The region is in fact a floodplain, characterized by its great vulnerability to extreme hydrological events, either deficit or excess of water. In the latter case, the incapacity of the topography to evacuate these water excesses, together with other factors, lead to the occurrence of large and persistent flooding. The climate and the hydrology modulated the availability of water and determined the variability of this resource, consequently both are the physical factors that influence the social and economic activities of the region. The study of these factors and the interactions between them allow understand the behavior of the system such as a watershed. The most used tool for simulating the Climate System of the Earth are the Atmospheric General Circulation Models (AGCM) whereas hydrological models are the best tools for analyzing the behavior of a watershed. The interaction between both tools is of the great interest due to the need of forecasts at different scales for proper resource management and the prevention of extreme events. In this thesis the ability of downscaling statistical models based on multiple linear regression was evaluated with the aim of quantified monthly precipitation anomalies in the Pampas region, including the phyto-geographical region El Espinal and the southwest of Buenos Aires. Additionally, these models were applied to estimate seasonal rainfall anomalies over the mentioned sites, combining an ensemble of simulations with the AGCM MCGA CSIRO-9, forced with the observed sea surface temperature (SST) and the application of statistical downscaling models of regionalization of the rain. The results showed that the downscaling proceeding may improve the reliability in the estimation of the local sign of the seasonal precipitation anomalies in comparison with the results from the global model. However, the downscaling did not significantly improve the estimation of the magnitude of these anomalies. As an hydrological application, the SWAT hydrological model was calibrated and validated in two interested basins located in the Pampas regions: The Salado River Basin, for being a plain with large areal extent, and the Sauce Grande River Basin, for its geomorphology and regional importance due to the supply of drinking water to a large area over the southwest of Buenos Aires. In this context, sensitivity analyses for the variables used in the calibration of each basin were conducted. Finally, a climate forecast system (CFSv2) with the hydrological model applied in the Salado River basin was integrated with the aim of analyze the possibility to generate a dynamic flow forecast at the seasonal scale.

The detrimental influence of humans on the environment is of increasing concern. Humans, their livestock, and their pets have caused fecal contamination of waterways throughout the United States. Understanding the sources of fecal indicator bacteria (FIB) and the environmental processes that affect them can be crucial to reducing the number of impaired streams and limiting the negative impacts on the environment. Antibiotic resistance is an emerging issue facing human health in the United States and across the world. Antibiotic resistant bacteria (ARB) have antibiotic resistance genes (ARGs) that prevent antibiotics from killing them. Limited research has been done on the role of the environment in the propagation of antibiotic resistance. As the use of antibiotics increases, it is critical to examine how this impacts human health through the environment. Models of watersheds in Patillas, Puerto Rico and Christiansburg, Virginia were created using the Soil and Water Assessment Tool (SWAT) to compare how the differences in spatial and temporal sampling of FIB, climate, and population affect FIB movement. The performances of the calibrated bacteria models were comparable to other published studies. A primary challenge faced in this study was the use of grab samples taken months apart as monthly averages of FIB. The high precipitation and constant warm climate made the model for Patillas more difficult to fit because of the high variability in the observed data. While the Patillas watershed had a lower population of people and livestock, the Christiansburg watershed had more available data on wildlife. The lack of spatial variance of data and the use of data from 1993-2018, hindered the ability for the model for Patillas to model FIB. Additionally, the model's performance was limited due to the strong hurricanes that affect land use, soils, and populations of humans and animals in the watershed. Using open-source data needs to be explored further as a faster and more cost-effective way of developing SWAT FIB models. The feasibility to use data collected in the Christiansburg and Patillas watershed to calibrate a SWAT-ARB model was determined based on available ARG data. The results indicate that the bacteria models need to be improved before an effective SWAT-ARB model can be calibrated. One limitation in the available ARG data for the two watersheds was that they were only sampled once. Out of the ARGs sampled, sul1 was the best modeled in both watersheds because it has the highest normalized values and correlated with the amount of developed land. / Master of Science / Humans negatively impact the environment. Humans and animals contribute to the bacteria contamination of waterways. Investigation into where the contamination sources are and environmental processes that contribute can help researchers limit the impact on the environment. Bacteria can build resistance to antibiotics, which can be especially dangerous to humans and livestock when exposed. Little research has been done on how the environment has contributed to the spread of antibiotic resistance in bacteria. The Soil and Water Assessment Tool (SWAT) was used to investigate bacteria in the Patillas, Puerto Rico and Christiansburg, Virginia watershed. These models used data published by the United States Geological Survey (USGS) and Environmental Protection Agency (EPA) to improve performance. When comparing simulated data to observed data, the performances of the models were comparable to other published studies. The Patillas watershed was particularly difficult to model because of the warm climate and high precipitation that caused high variability in bacteria concentrations. Strong weather events including hurricanes and a lack of available data on wildlife were other hinderances to the Patillas model. In comparison, more published data on wildlife was available in the Christiansburg watershed and it had a more temperate climate. The SWAT-ARB model was reviewed and recommendations were made to improve the model. Using the previously collected antibiotic resistance bacteria data in the Christiansburg and Patillas watersheds, it would be impossible to create accurate models. More antibiotic resistance data needs to be taken across as a greater time period before the performance of the models can be assessed.

Nowadays, one of the urgent issues in the management of river basin resources as land degradation, especially soil erosion risk occurs due to complex factors of climate, cultivation practices of human and impacting of the operation of socio-economic development taking place in the basin. Soil erosion has been considered as the primary cause of soil degradation since soil erosion leads to the loss of topsoil and soil organic matters, which are essential for the growing of plants. Ta Trach river watershed, is a mountainous basin lying to the West - South of Thua Thien Hue province, having complex terrain. The result of this study showed that the amount of sediment yield accounts for high percentage. The average annual sedimentation is 41.60 tones per hectometer in the period of 2005 to 2010, soil erosion were classified by 5 levels. In which, the less deleterious erosion level still occupies high percentage with more than 55 % of watershed area. The main area of less deleterious soil erosion was located at high topography and high slope. The area of deleterious soil erosion occupies percentage lower than 22.63% of the entire basin, but it is also a warning sign to the extent of land degradation taking place in the basin if the erosion rate increases in the future. / Ngày nay, một trong những vấn đề cấp bách trong quản lý tài nguyên lưu vực sông là sự thoái hóa đất và đặc biệt là nguy cơ xói mòn đất xảy ra do yếu tố khí hậu phức tạp, phương thức canh tác của con người và tác động của những hoạt động phát triển kinh tế - xã hội đang diễn ra ở lưu vực. Lưu vực sông Tả Trạch là một lưu vực miền núi nằm về phía Tây - Nam của tỉnh Thừa Thiên Huế, có địa hình khá phức tạp. Mục tiêu của nghiên cứu này là ứng dụng công cụ SWAT để mô phỏng xói mòn đất ở lưu vực sông Tả Trạch thuộc tỉnh Thừa Thiên Huế từ năm 2005 đến năm 2010. Kết quả của nghiên cứu cho thấy lượng đất bồi lắng ở lưu vực chiếm tỷ lệ cao, trung bình mỗi năm bồi lắng 41.60 tấn/ha trong giai đoạn 2005 đến 2010, mức độ xói mòn được phân cấp thành 5 cấp xói mòn. Trong đó, mức độ xói mòn ít nguy hại chiếm ở tỷ lệ cao hơn 55 % diện tích lưu vực, chủ yếu phân bố ở những khu vực có địa hình cao, độ dốc lớn. Diện tích xói mòn nguy hại chiếm tỷ lệ thấp hơn 22,63% diện tích toàn lưu vực nhưng đây cũng là một dấu hiệu báo động cho mức độ thoái hóa đất diễn ra ở lưu vực trong tương lai nếu mức xói mòn này tăng lên.