Estimating potential direct runoff for ungauged urban watersheds based on RST and GIS

Estimating the potential direct runoff for urban watersheds is essential for flood risk mitigation and rainwater harvesting. Thus, this study aims to estimate the potential runoff depth based on the natural resources conservation service (NRCS) method and delineation of the watersheds in Riyadh, Saudi Arabia. To accomplish this objective, the geographic information systems (GIS) and remote sensing technique (RST) data were integrated to save time and improve analysis accuracy. The employed data include the digital elevation model (DEM), soil map, geology map, satellite images, and daily precipitation records. Accordingly, the hydrologic soil groups (HSG), the land use/land cover (LULC), and curve number (CN) were determined for each watershed in the study area. The results of this analysis show that the study area can be delineated into 40 watersheds with a total area of 8500 km². Furthermore, the dominant HSG is group D, which represents about 71% of the total area. The LULC maps indicate four major land types in the entire study area: urban, barren land, agricultural land, and roads. The CN of the study area ranges from 64 to 98, while the weighted CN is 92 for the city. The rainfall-runoff analysis shows that the area has a high and very high daily runoff (35–50 and >?50 mm, respectively). Therefore, in this case, the runoff leads to flooding, especially in the urban area and agricultural lands.     

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 (R ²?=?0.92–0.94), while geology, climate (rainfall), soil, and upland erosion factors were found to have moderate effect to the model output (R ²?=?0.74–0.59).     

Soil erosion assessment and its verification using the Universal Soil Loss Equation and Geographic Information System: a case study at Boun,Korea

This study is aimed at the evaluation of the hazard of soil erosion and its verification at Boun, Korea, using a Geographic Information System (GIS) and remote sensing. Precipitation, topographic, soil, and land use data were collected, processed, and constructed into a spatial database using GIS and remote sensing data. Areas that had suffered soil erosion were analysed and mapped using the Universal Soil Loss Equation (USLE). The factors that influence soil erosion are rainfall erosivitiy (R) from the precipitation database, soil erodibility (K) from the soil database, slope length and steepness (LS) from the topographic database, and crop and management (C) and conservation supporting practices (P) from the land use database. Land use was classified from Landsat Thematic Mapper satellite images. The soil erosion map verified use of the landslide location data. Landslide locations were identified in the Boun area from interpretation of aerial photographs and field surveys.     

Modeling runoff and soil erosion in a catchment area, using the GIS, in the Himalayan region, India

Remote sensing data and GIS techniques have been used to compute runoff and soil erosion in the catchment area along the NH-1A between Udhampur and Kud covering an area of approximately 181 km². Different thematic layers, for example lithology, a landuse and landcover map, geomorphology, a slope map, and a soil-texture map, were generated from these input data. By use of the US Soil Conservation Service curve number method, estimated runoff potential was classified into five levels—very low, low, moderate, high, and very high. Data integration was performed by use of the weighting rating technique, a conventional qualitative method, to give a runoff potential index value. The runoff potential index values were used to delineate the runoff potential zones, namely low, moderate, high, and very high. Annual spatial soil loss estimation was computed using the Morgan–Morgan–Finney mathematical model in conjunction with remote sensing data and GIS techniques. Greater soil erosion was found to occur in the northwestern part of the catchment area. When average soil loss from the catchment area was calculated it was found that a maximum average soil loss of more than 20 t ha⁻¹ occurred in 31 km² of the catchment area.     

An artificial neural network model for flood simulation using GIS: Johor River Basin, Malaysia

Flooding is one of the most destructive natural hazards that cause damage to both life and property every year, and therefore the development of flood model to determine inundation area in watersheds is important for decision makers. In recent years, data mining approaches such as artificial neural network (ANN) techniques are being increasingly used for flood modeling. Previously, this ANN method was frequently used for hydrological and flood modeling by taking rainfall as input and runoff data as output, usually without taking into consideration of other flood causative factors. The specific objective of this study is to develop a flood model using various flood causative factors using ANN techniques and geographic information system (GIS) to modeling and simulate flood-prone areas in the southern part of Peninsular Malaysia. The ANN model for this study was developed in MATLAB using seven flood causative factors. Relevant thematic layers (including rainfall, slope, elevation, flow accumulation, soil, land use, and geology) are generated using GIS, remote sensing data, and field surveys. In the context of objective weight assignments, the ANN is used to directly produce water levels and then the flood map is constructed in GIS. To measure the performance of the model, four criteria performances, including a coefficient of determination (R ²), the sum squared error, the mean square error, and the root mean square error are used. The verification results showed satisfactory agreement between the predicted and the real hydrological records. The results of this study could be used to help local and national government plan for the future and develop appropriate (to the local environmental conditions) new infrastructure to protect the lives and property of the people of Johor.     

Estimation of soil erosion using RUSLE in Caijiamiao watershed,China

Soil erosion is a serious environmental and production problem in China. In particular, natural conditions and human impact have made the Chinese Loess Plateau particularly prone to intense soil erosion area. To decrease the risk on environmental impacts, there is an increasing demand for sound, and readily applicable techniques for soil conservation planning in this area. This work aims at the assessment of soil erosion and its spatial distribution in hilly Loess Plateau watershed (northwestern China) with a surface area of approximately 416.31 km². This study was conducted at the Caijiamiao watershed to determine the erosion hazard in the area and target locations for appropriate initiation of conservation measures using the revised universal soil loss equation (RUSLE). The erosion factors of RUSLE were collected and processed through a geographic information system (GIS)-based approach. The soil erosion parameters were evaluated in different ways: The R-factor map was developed from the rainfall data, the K-factor map was obtained from the soil map, the C-factor map was generated based on Landsat-5 Thematic Mapper image and spectral mixture analysis, and a digital elevation model with a spatial resolution of 25 m was derived from topographic map at the scale of 1:50,000 to develop the LS-factor map. Support practice P factor was from terraces that exist on slopes where crops are grown. By integrating the six-factor maps in GIS through pixel-based computing, the spatial distribution of soil loss in the study area was obtained by the RUSLE model. The results showed that spatial average soil erosion at the watershed was 78.78 ton ha^?1 year^?1 in 2002 and 70.58 ton ha^?1 year^?1 in 2010, while the estimated sediment yield was found to be 327.96 × 10⁴ and 293.85 × 10⁴ ton, respectively. Soil erosion is serious, respectively, from 15 to 35 of slope degree, elevation area from 1,126 to 1,395 m, in the particular area of soil and water loss prevention. As far as land use is concerned, soil losses are highest in barren land and those in waste grassland areas are second. The results of the study provide useful information for decision maker and planners to take appropriate land management measures in the area. It thus indicates the RUSLE–GIS model is a useful tool for evaluating and mapping soil erosion quantitatively and spatially at a river watershed scale on a cell basis in Chinese Loess Plateau and for planning of conservation practices.     

Remote sensing- and GIS-based runoff modeling with the effect of land-use changes (a case study of Cochin corporation)

A study was conducted to estimate the runoff in urbanized zone using Soil Conservation Services Curve Number (SCS-CN) method through remote sensing and GIS techniques. In this study, the region was identified as Cochin Corporation (Kerala State, India) with an aerial extent of 96.44 km². The spatial and non-spatial data were collected from different sources, and the thematic layers of soil hydrologic group and land-use maps were prepared and overlaid with one other. The overlaid output results were assigned by curve numbers with respect to soil and land-use categories, and the CN map was prepared with the help of Visual Basic (VB) language in ArcGIS platform. Through supervised classifications, 13 different land-use classes were identified from Quickbird data for the year of 2005 and 2010. The most prominent land-use classes were water bodies, residential, mixed crops, commercial and industrial, and 3 types of soil hydrologic groups were identified namely A, B, and C categories. The B group is most prominent occupying 60 km² of the study area. The CN map shows the ranges that 92–100 is the major CN area with high runoff potential zone of the study region. At the final stage, the runoff was estimated by the maximum successive rainfall received in this study area in two different years—2005 and 2010 along with their land-use pattern. The runoff model is applied for temporal variation in land-use change, and impact of runoff was studied. The study area showed significant changes in land-use pattern between 2005 and 2010 particularly in the land-use change from agricultural into industrial, commercial, and residential (high density). The area covered by the highest runoff depth with the range of 92–100 CN values increased from 43.87 to 45.32 km² from 2005 to 2010. The volume of runoff was increased from 135.56 to 141.49 Mm³ from 2005 to 2010 due to the land-use change pattern.     

Evaluating the impacts of watershed management on runoff storage and peak flow in Gav-Darreh watershed,Kurdistan, Iran

Recently, water and soil resource competition and environmental degradation due to inadequate management practices have been increased and pose difficult problems for resource managers. Numerous watershed practices currently being implemented for runoff storage and flood control purposes have improved hydrologic conditions in watersheds and enhanced the establishment of riparian vegetation. The assessment of proposed management options increases management efficiency. The purpose of this study is to assess the impact of watershed managements on runoff storage and peak flow, and determine the land use and cover dynamics that it has induced in Gav-Darreh watershed, Kurdistan, Iran. The watershed area is 6.27 km² which has been subjected to non-structural and structural measures. The implemented management practices and its impact on land use and cover were assessed by integrating field observation and geographic information systems (GIS). The data were used to derive the volume of retained water and determine reduction in peak flow. The hydrology of the watershed was modeled using the Hydrologic Engineering Center–Hydrologic Modeling System (HEC–HMS) model, and watershed changes were quantified through field work. Actual storms were used to calibrate and validate HEC–HMS rainfall–runoff model. The calibrated HEC–HMS model was used to simulate pre- and post-management conditions in the watershed. The results derived from field observation and HEC–HMS model showed that the practices had significant impacts on the runoff storage and peak flow reduction.     

RS & GIS-based landslide susceptibility mapping of the Balason River basin,Darjeeling Himalaya,using logistic regression (LR) model

The present study deals with the preparation of a landslide susceptibility map of the Balason River basin, Darjeeling Himalaya, using a logistic regression model based on Geographic Information System and Remote Sensing. The landslide inventory map was prepared with a total of 295 landslide locations extracted from various satellite images and intensive field survey. Topographical maps, satellite images, geological, geomorphological, soil, rainfall and seismic data were collected, processed and constructed into a spatial database in a GIS environment. The chosen landslide-conditioning factors were altitude, slope aspect, slope angle, slope curvature, geology, geomorphology, soil, land use/land cover, normalised differential vegetation index, drainage density, lineament number density, distance from lineament, distance to drainage, stream power index, topographic wetted index, rainfall and peak ground acceleration. The produced landslide susceptibility map satisfied the decision rules and ?2 Log likelihood, Cox &; Snell R-Square and Nagelkerke R-Square values proved that all the independent variables were statistically significant. The receiver operating characteristic curve showed that the prediction accuracy of the landslide probability map was 96.10%. The proposed LR method can be used in other hazard/disaster studies and decision-making.     

Rainfall-runoff modeling of ungauged Wadis in arid environments (case study Wadi Rabigh—Saudi Arabia)

Flash flood forecasting of catchment systems is one of the challenges especially in the arid ungauged basins. This study is attempted to estimate the relationship between rainfall and runoff and also to provide flash flood hazard warnings for ungauged basins based on the hydrological characteristics using geographic information system (GIS). Morphometric characteristics of drainage basins provide a means for describing the hydrological behavior of a basin. The study examined the morphometric parameters of Wadi Rabigh with emphasis on its implication for hydrologic processes through the integration analysis between morphometric parameters and GIS techniques. Data for this study were obtained from ASTER data for digital elevation model (DEM) with 30-m resolution, topographic map (1:50,000), and geological maps (1,250,000) which were subject to field confirmation. About 36 morphometric parameters were measured and calculated, and interlinked to produce nine effective parameters for the evaluation of the flash flood hazard degree of the study area. Based on nine effective morphometric parameters that directly influence on the hydrologic behavior of the Wadi through time of concentration, the flash flood hazard of the Rabigh basin and its subbasins was identified and classified into three groups (High, medium, and low hazard degree). The present work proved that the physiographic features of drainage basin contribute to the possibility of a flash flood hazard evaluation for any particular drainage area. The study provides details on the flash flood prone subbasins and the mitigation measures. This study also helps to plan rainwater harvesting and watershed management in the flash flood alert zones. Based on two historical data events of rainfall and the corresponding maximum flow rate, morphometric parameters and Stormwater Management and Design Aid software (SMADA 6), it could be to generate the hydrograph of Wadi Rabigh basin. As a result of the model applied to Wadi Rabigh basin, a rainfall event of a total of 22 mm with a duration of 5 h at the station nearby the study area, which has an exceedance probability of 50 % and return period around 2 years, produces a discharge volume of 15.2?×?10⁶ m³ at the delta, outlet of the basin, as 12.5 mm of the rainfall infiltrates (recharge).     

Identification of hotspots for potential pyrethroid runoff: a GIS modeling study in San Joaquin River Watershed of California, USA

This paper attempts to identify the high-risk areas for potential runoff of pyrethroid pesticides in the San Joaquin River Watershed. Pyrethroid pesticides have been detected in water and fluvial sediments in this watershed, creating concerns about potential negative impacts on water quality. However, little documentation exists regarding the distributions or the extent of the adverse effects caused by the use of pyrethroids. This study developed a geographic information systems (GIS) model to identify areas with high potential for pyrethroid runoff during the rainy season. The model was then validated using field-monitoring data. Nine factors were identified for the runoff risk assessment: amount of active ingredient used, soil erodibility factor, hydrologic group, surface layer depth, seasonal rainfall, seasonal number of rainy days, seasonal number of storm events, stream density, and land cover. The results indicated that high pyrethroid runoff risks were associated with basins such as the Stanislaus River Sub-basin, Newman Gustine Sub-basin and South Merced Sub-basin. This study demonstrated that the GIS model is capable of predicting high-risk areas of pyrethroid runoff at sub-basin scale. The model can be used to prioritize sites for water quality monitoring and guide implementations of best management practices. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Utilization of remote sensing data and GIS tools for and use sustainability analysis: case study in El-Hammam area, Egypt

The North-Western Coast of Egypt (NWCE) represents one of the high priority regions for future development in the country. El-Hammam area is located in the NWCE with an area of 94752 acres and is one of the main challenging regions for sustaianble development. In this study, we have used remote sensing and soil data in combination with GIS tools, for land use sustainable analysis (SLU) in El-Hammam area. The SLU was established based on various factors such as: land capability and suitability, water resources availability, economic return from water and financial return from land and water. A physiographic soil map for the study area was prepared using remote sensing and GIS. Multiple field surveys were carried out for collecting information on various soil map units (SMUs) and their profiles. Laboratory analysis for the collected samples was performed, and then the soil properties were stored as attributes in a geographical soil database linked with the SMUs. Furthermore, land capability assessment was done to define the suitable areas for agricultural production using a capability model built in ALES software. Results indicate that the area currently lacks high capability and moderate capability classes. By improving the soil properties, the soil can attain potential capability; and 55630 acres will become marginally capable. The assessment of soil physical suitability for different land use types (LUTs) were analysed in ALES software, in order to generate the most suitable areas. The results from the land suitability analysis indicated that, 17114 acres are moderately suitable for wheat and sorghum; whereas 15823 acres are moderately suitable for barley and 12752 acres are moderately suitable for maize, olive and figs. Finally, the SLU was investigated based on two scenarios; (1) the most SLU under the conditions of shortage of irrigation water: clover, barley and sorghum against figs, as the irrigation requirements for barley and sorghum are low; (2) the most sustainable land use in the conditions of irrigation availability will be wheat and maize against figs and guava. From the results it is quite evident that GIS combined with modeling approaches are powerful tools for decision making in the study area.     

Assessment of surface runoff depth changes in Sǎrǎţel River basin,Romania using GIS techniques

Sǎrǎ?el River basin, which is located in Curvature Subcarpahian area, has been facing an obvious increase in frequency of hydrological risk phenomena, associated with torrential events, during the last years. This trend is highly related to the increase in frequency of the extreme climatic phenomena and to the land use changes. The present study is aimed to highlight the spatial and quantitative changes occurred in surface runoff depth in Sǎrǎ?el catchment, between 1990–2006. This purpose was reached by estimating the surface runoff depth assignable to the average annual rainfall, by means of SCS-CN method, which was integrated into the GIS environment through the ArcCN-Runoff extension, for ArcGIS 10.1. In order to compute the surface runoff depth, by CN method, the land cover and the hydrological soil classes were introduced as vector (polygon data), while the curve number and the average annual rainfall were introduced as tables. After spatially modeling the surface runoff depth for the two years, the 1990 raster dataset was subtracted from the 2006 raster dataset, in order to highlight the changes in surface runoff depth.     

Regional soil erosion risk mapping using RUSLE,GIS, and remote sensing: a case study in Miyun Watershed,North China

This paper applied the Revised Universal Soil Loss Equation (RUSLE), remote-sensing technique, and geographic information system (GIS) to map the soil erosion risk in Miyun Watershed, North China. The soil erosion parameters were evaluated in different ways: the R factor map was developed from the rainfall data, the K factor map was obtained from the soil map, the C factor map was generated based on a back propagation (BP) neural network method of Landsat ETM+ data with a correlation coefficient (r) of 0.929 to the field collected data, and a digital elevation model (DEM) with a spatial resolution of 30 m was derived from topographical map at the scale of 1:50,000 to develop the LS factor map. P factor map was assumed as 1 for the watershed because only a very small area has conservation practices. By integrating the six factor maps in GIS through pixel-based computing, the spatial distribution of soil loss in the upper watershed of Miyun reservoir was obtained by the RUSLE model. The results showed that the annual average soil loss for the upper watershed of Miyun reservoir was 9.86 t ha⁻¹ ya⁻¹ in 2005, and the area of 47.5 km² (0.3%) experiences extremely severe erosion risk, which needs suitable conservation measures to be adopted on a priority basis. The spatial distribution of erosion risk classes was 66.88% very low, 21.90% low, 6.19% moderate, 2.90% severe, and 1.84% very severe. Among all counties and cities in the study area, Huairou County is in the extremely severe level of soil erosion risk, about 39.6% of land suffer from soil erosion, while Guyuan County in the very low level of soil erosion risk suffered from 17.79% of soil erosion in 2005. Therefore, the areas which are in the extremely severe level of soil erosion risk need immediate attention from soil conservation point of view.     

Land suitability assessment for sugarcane cultivation in Bijnor district,India using geographic information system and fuzzy analytical hierarchy process

Land suitability evaluation is prerequisite for assessing the limitations for sustainable land use planning. We used ten site specific criteria (rainfall, texture, drainage, soil depth, slope, distance to major road, distance to nearest sugar mill, erosion hazard, risk of flooding and pH) and applied weighted multi-criteria evaluation (MCE) technique in a geographic information system (GIS) environment to evaluate land suitability for sugarcane cultivation in Bijnor district, India. The weightage of all the parameters was calculated through fuzzy analytical hierarchy process. Sugarcane suitability map was prepared integrating various parameters through weighted overlay analysis. The map was categorized as highly suitable (S1), moderately suitable (S2), marginally suitable (S3) and unsuitable (N). The analysis revealed that of the total cultivable land of the district, largest area (61%) was highly suitable followed by moderately suitable (24%), marginally suitable (7%) and unsuitable (8%) for sugarcane cultivation. Nagina, Najibabad and Bijnor sub-districts need attention of land managers and policy makers to remove the limitations and increase the suitability of sugarcane in such areas. Only 7% area was unsuitable for sugarcane cultivation. Slope, soil depth and erosion hazard were the major limiting factors making the land unsuitable for sugarcane cultivation. Therefore, these areas should be given priority for land and soil restoration efforts. The study showed effectiveness of integrated GIS and MCE approach for land suitability analysis of sugarcane.     

Quantitatively analyze the impact of land use/land cover change on annual runoff decrease

Annual runoff in Luanhe river basin was detected a downward trend and caused water crisis in Tianjin, China. To quantify the decreased runoff volume, Mann–Kendall test and Pettitt test were employed to check whether there existed significant trend and change points for annual rainfall and runoff time series in Panjiakou reservoir basin and 8 sub-watersheds. It was found that the annual runoff time series had a significant downward trend at 5 % confidence level, and the change point was at 1979 in Panjiakou reservoir watershed. Then double mass curve of annual rainfall and annual runoff was plotted, and two lines were fitted before and after 1979, respectively. Based on this method, the comprehensive effects of land use/land cover change on annual runoff were estimated. To further quantify the contributions of each main factor to annual runoff decrease, water stored in check dams and social water use in different periods were surveyed first. And then multi-linear regression was used to develop the relations between annual runoff and the driven factors. Water area decrease was identified to be the main factor contributing to annual runoff reduction. The results in this study can provide valuable information for water resources planners and policy makers.     

Assessing the impacts of land use changes on watershed hydrology using MIKE SHE

A fully distributed, physically-based hydrologic modeling system, MIKE SHE, was used in this study to investigate whole-watershed hydrologic response to land use changes within the Gyeongancheon watershed in Korea. A grid of 200 × 200 m was established to represent spatial variations in geology, soil, and land use. Initial model performance was evaluated by comparing observed and simulated streamflow from 1988 to 1991. Results indicated that the calibrated MIKE SHE model was able to predict streamflow well during the calibration and validation periods. Proportional changes in five classes of land use within the watershed were derived from multi-temporal Landsat TM imageries taken in 1980, 1990 and 2000. These imageries revealed that the watershed experienced conversion of approximately 10% non-urban area to urban area between 1980 and 2000. The calibrated MIKE SHE model was then programmed to repeatedly analyze an artificial dataset under the various land use proportions identified in the Landsat TM imageries. The analysis was made to quantitatively assess the impact of land use changes (predominantly urbanization) on watershed hydrology. There were increases in total runoff (5.5%) and overland flow (24.8%) as a response to the land use change.     

Regional modelling of rainfall-induced runoff using hydrological model by incorporating plant cover effects: case study in Kelantan,Malaysia

The objective of this paper is to develop a spatial temporal runoff modelling of local rainfall patterns effect on the plant cover hilly lands in Kelantan River Basin. Rainfall interception loss based on leaf area index, loss/infiltration on the ground surface, and runoff calculation were considered as the main plant cover effects on the runoff volume. In this regard, a hydrological and geotechnical grid-based regional model (integrated model) was performed using Microsoft Excel^® and GIS framework system for deterministic modelling of rainfall-induced runoff by incorporating plant cover effects. The infiltration process of the current model was integrated with the precipitation distribution method and rainfall interception approach while the runoff analysis of integrated model was employed based on loss/infiltration water on the ground surface with consideration of water interception loss by canopy and the remaining surface water. In the following, the spatial temporal analysis of rainfall-induced runoff was performed using 10 days of hourly rainfall events at the end of December 2014 in Kelantan River Basin. The corresponding changes in pressure head and consequent rate of infiltration were calculated during rainfall events. Subsequently, flood volume is computed using local rainfall patterns, along with water interception loss and the remaining surface water in the study area. The results showed the land cover changes caused significant differences in hydrological response to surface water. The increase in runoff volume of the Kelantan River Basin is as a function of deforestation and urbanization, especially converting the forest area to agricultural land (i.e. rubber and mixed agriculture).     

甘肃迭部扎尕那地区山地土壤过程的垂直分带性研究

为了研究迭部扎尕那地区山地土壤过程的垂直分带性, 对不同海拔分布的土壤类型进行垂直分带取样, 并针对不同植被类型和特殊地理因素进行横向取样, 分析土壤的化学成分及其结构. 应用GIS软件数字化研究区地形图, 提取海拔、 坡度、 坡向等地形因子, 结合土地利用资料得到土地利用类型图. 通过采样点数据与数字化地形因子图与土地利用类型图的叠加, 结合属性数据的统计分析, 讨论影响土壤过程垂直分带性各要素的垂直性规律和分布. 结果表明: 有机碳含量和全氮含量呈极好的线性正相关, 并随海拔的升高而增加. 此外, 在同一海拔范围内, 土壤有机碳含量随着土地利用类型和坡向的变化呈规律性变化. 其中, 不同土地利用类型下的土壤有机碳含量依次为有林地>高寒草甸>高覆盖度草地>农村居民点>平原耕地>山地耕地; 不同坡向上, 土壤有机碳含量依次为阴坡>半阴坡>半阳坡>阳坡.     

Impact of the new common agricultural policy of the EU on the runoff production and soil moisture content in a Mediterranean agricultural system

Soil moisture variability and the depth of water stored in the arable layer of the soil are important topics in agricultural research and rangeland management. In this study, we use the distributed rainfall-runoff (DR2) model to perform a detailed mapping of topsoil moisture status (SMS) in a mountain Mediterranean catchment. This model, previously tested in the same study area against the Palmer Z-index, is run at monthly scale for the current scenario of land uses and under three scenarios that combine the land abandonment and the application of the new common agricultural policy (CAP) of the European Union. Under the current conditions, runoff yield is scarce and presents a high spatial variability when monthly rainfall intensity and depth are low, and infiltration processes mainly lead to water storage in the soil. When rainfall intensity is high, runoff accumulation along the hillslopes controls the depth of available water in the soil, and SMS is more homogeneous. On average, scrublands and pasture have the wettest values, crops of winter cereal and abandoned fields have intermediate conditions, and areas of bare soil and forest have the driest conditions all the year around. The abandonment and no revegetation of the low productive fields located in steep areas and the collapse of their landscape linear elements (LLEs) produce not only an increase of 2.3 % of the overall SMS in the catchment in comparison with the current scenario but also an increment of the effective runoff that cross the cultivated areas of the lowlands and the runoff depth that reach the wetlands, increasing the soil erosion risk and compromising the conservation of the lakes. When the new green areas of the CAP are installed in the upper part of the fields of the lowlands and around the lakes, the runoff depth and thus siltation risk clearly decreases but also SMS decreases 1.7 and 1.1 % considering the current land uses and adding revegetation practices in the abandoned fields, respectively. Hence, a management scenario where: (1) abandoned fields are covered with a dense cover of shrubs, (2) the LLEs are preserved, (3) the green areas of the PAC are created, and (4) runoff harvesting practices are applied to partially compensate the water deficit, will help to preserve the humidity of the soil and will be of interest to keep the agricultural land use around the protected lakes of the study area.