A physically based method for prediction of runoff frequencies

A method is described for predicting changes in flood frequencies resulting from various causes affecting runoff in a watershed. The method utilizes the curve number and the traingular unit hydrograph procedures of the United States Department of Agriculture's Soil Conservation Service to transform rainfall frequencies into frequencies of peak discharge. The theory underlying the method is discussed. Application is illustrated by an example.     

Nonpoint Source Pollution Assessment of Wujiang RiverWatershed in Guizhou Province,SW China

The amount of pollution from nonpoint sources flowing in the streams of the Wujiang River watershed in Guizhou Province, SW China, is estimated by a geographic information system (GIS)-based method using rainfall, surface runoff and land use data. A grid of cells of 100 m in size is laid over the landscape. For each cell, mean annual surface runoff is estimated from rainfall and percent land use, and expected pollutant concentration is estimated from land use. The product of surface runoff and concentration gives expected pollutant loading from that cell. These loadings are accumulated going downstream to give the expected annual pollutant loadings in streams and rivers. By dividing these accumulated loadings by the similarly accumulated mean annual surface runoff, the expected pollutant concentration from nonpoint sources is determined for each location in a stream or river. Observed pollutant concentrations in the watershed are averaged at each sample point and compared to the expected concentrations at the same locations determined from the grid cell model. In general, annual nonpoint source nutrient loadings in the Wujiang River watershed are seen to be predominantly from the agricultural and meadow areas. The total annual loadings through the outlet of the watershed are 40,309 and 2,607 tons for total nitrogen (TN) and total phosphorus (TP), respectively.     

Modeling Runoff Response to Land Cover and Rainfall Spatial Variability in Semi-Arid Watersheds

Hydrologic response is an integrated indicator of watershed condition, and significant changes in land cover may affect the overall health and function of a watershed. This paper describes a procedure for evaluating the effects of land cover change and rainfall spatial variability on watershed response. Two hydrologic models were applied on a small semi-arid watershed; one model is event-based with a one-minute time step (KINEROS), and the second is a continuous model with a daily time step (SWAT). The inputs to the models were derived from Geographic Information System (GIS) theme layers of USGS digital elevation models, the State Soil Geographic Database (STATSGO) and the Landsat-based North American Landscape Characterization classification (NALC) in conjunction with available literature and look up tables. Rainfall data from a network of 10 raingauges and historical stream flow data were used to calibrate runoff depth using the continuous hydrologic model from 1966 to 1974. No calibration was carried out for the event-based model, in which six storms from the same period were used in the calculation of runoff depth and peak runoff. The assumption on which much of this study is based is that land cover change and rainfall spatial variability affect the rainfall-runoff relationships on the watershed. To validate this assumption, simulations were carried out wherein the entire watershed was transformed from the 1972 NALC land cover, which consisted of a mixture of desertscrub and grassland, to a single uniform land cover type such as riparian, forest, oak woodland, mesquite woodland, desertscrub, grassland, urban, agriculture, and barren. This study demonstrates the feasibility of using widely available data sets for parameterizing hydrologic simulation models. The simulation results show that both models were able to characterize the runoff response of the watershed due to changes of land cover.     

Estimation of Land Use Specific Runoff and Pollutant Concentration for Tapi River Basin in India

Non-point source (NPS) pollution is the result of various land use practices such as agriculture, sites of construction and waste disposal, urban development and so on. The control of NPS pollution is possible by regular monitoring and assessment on watershed basis to educate people for implementing well-known structural and non-structural measures. Recent trend is to use GIS based modelling tool for assessment of rainfall-runoff and non-point loading. The approach requires generation and analysis of basin wide data on various features of land and estimates of Event Mean Concentrations (EMCs) of pollutants in the runoff. In the present paper, basin wide data in different districts of Tapi basin has been analysed for land use distribution; fertilizer application; low, medium and high-density habitation; and annual rainfall. Coefficients of runoff have been estimated considering pervious and impervious area for different land use types, and compared with the reported values for Indian conditions. The estimated mean annual runoff flow indicated that two districts Jalgaon and Dhule contribute maximum runoff to the Tapi River. Estimates of EMCs for BOD and nutrients (N and P) in the runoff from various districts are useful in GIS-based modelling study for NPS pollution assessment.     

Spatial based compromise programming for multiple criteria decision making in land use planning

Today, competing land use is continuing to occur in many developed regions. In the Agricultural Development Zone of Western Sydney Region, which is characterised by complex landscape patterns, land use competition is widespread. From a land use planning perspective, identification of suitable locations for a given type of land use is necessary for decision makers to formulate land use alternatives in different locations, based on existing land potential and constraints. For such a region, use of a simple method that implements a categorical system and considers only inherent land characteristics in the analysis is often inadequate to arrive at an optimal spatial decision. The primary aim of this paper is to develop spatial modelling procedures for agricultural land suitability analysis using compromise programming (CoPr) and fuzzy set approach within a geographical information systems (GIS) environment. Five main sets of spatial data for use as decision criteria were developed by using fuzzy set methodology: a land suitability index (LSI) for maximising the land productivity objective; an erosion tolerance index (ETI) for minimising the erosion risk objective; a runoff curve number (CN) for maximising the water discharge regulation objective; an accessibility (RP) measure for maximising the land accessibility objective; and the proximity to water body (WP) for minimising the water pollution objective. An L _p -metric was used in the analysis utilising different strategies with representative indices ranging from a situation where full tradeoff among criteria occurs to a noncompensatory condition. Different weighting combinations were also applied, and decision analysis was carried out by using values ranging from 0 to 1.0, where 1.0 is considered as an ideal point. The CoPr model demonstrated in this paper yielded a promising result, as several different techniques of sensitivity analysis show reasonably good results. Likewise, an overlay of that result with the present land use/land cover indicates a good corresponding spatial matching between existing land use (orchard and cultivated land), and the cells (land parcels) classified as the best in CoPr. The results are amenable to various map display techniques, either using continuous values or by defining different cut off points in the data space within a raster GIS environment.     

WEPP and ANN models for simulating soil loss and runoff in a semi-arid Mediterranean region

This paper presents the use of both the Water Erosion Prediction Project (WEPP) and the artificial neural network (ANN) for the prediction of runoff and soil loss in the central highland mountainous of the Palestinian territories. Analyses show that the soil erosion is highly dependent on both the rainfall depth and the rainfall event duration rather than on the rainfall intensity as mostly mentioned in the literature. The results obtained from the WEPP model for the soil loss and runoff disagree with the field data. The WEPP underestimates both the runoff and soil loss. Analyses conducted with the ANN agree well with the observation. In addition, the global network models developed using the data of all the land use type show a relatively unbiased estimation for both runoff and soil loss. The study showed that the ANN model could be used as a management tool for predicting runoff and soil loss.     

Appraisal of the groundwater balance components from multi-remote sensing datasets in a semi-arid region

Semi-arid regions across the globe are fronting water crises, signaling a challenge to ensure future water security. Given the high inter-seasonal rainfall variability and unrestrained groundwater extraction, the precise quantification of groundwater flow components in an aquifer system is a priority. To address this challenge, we used high-resolution remote sensing (RS) data (Landsat and IRS) and GIS modeling (SEBAL, ArcCN) to spatially quantify major groundwater balance (GWB) components, viz., evapotranspiration (ET), rainfall recharge (R), surface runoff (Q), groundwater extraction (PG), irrigation return flow (IRF), and ultimately changes in groundwater storage (ΔS) in a small semi-arid crystalline representative watershed. Results show that a total of ~?230 mm of groundwater is extracted during 2008–2009, creating a negative impact on the groundwater resource, which is further enhanced by limited recharge and high ET. A decrease of approximately 65 mm in groundwater storage is observed in a single hydrological year, and given a very low specific yield, this decrease will introduce large water level decline. The study establishes that declining groundwater level in the watershed is a direct result of over-extraction, and owing to this scenario, efficient irrigation and land use policies are suggested as potential approaches to minimize extraction specifically in the dry season. Our methodology provides a systematic assessment of vital GWB components at a high spatial resolution and an insight on various sustainable mitigation methods. This methodology is useful in the planning and management of groundwater resources, particularly in water-stressed areas.     

Spatial and temporal estimation of soil loss for the sustainable management of a wet semi-arid watershed cluster

The ungauged wet semi-arid watershed cluster, Seethagondi, lies in the Adilabad district of Telangana in India and is prone to severe erosion and water scarcity. The runoff and soil loss data at watershed, catchment, and field level are necessary for planning soil and water conservation interventions. In this study, an attempt was made to develop a spatial soil loss estimation model for Seethagondi cluster using RUSLE coupled with ARCGIS and was used to estimate the soil loss spatially and temporally. The daily rainfall data of Aphrodite for the period from 1951 to 2007 was used, and the annual rainfall varied from 508 to 1351 mm with a mean annual rainfall of 950 mm and a mean erosivity of 6789 MJ mm ha^?1 h^?1 year^?1. Considerable variation in land use land cover especially in crop land and fallow land was observed during normal and drought years, and corresponding variation in the erosivity, C factor, and soil loss was also noted. The mean value of C factor derived from NDVI for crop land was 0.42 and 0.22 in normal year and drought years, respectively. The topography is undulating and major portion of the cluster has slope less than 10°, and 85.3 % of the cluster has soil loss below 20 t ha^?1 year^?1. The soil loss from crop land varied from 2.9 to 3.6 t ha^?1 year^?1 in low rainfall years to 31.8 to 34.7 t ha^?1 year^?1 in high rainfall years with a mean annual soil loss of 12.2 t ha^?1 year^?1. The soil loss from crop land was higher in the month of August with an annual soil loss of 13.1 and 2.9 t ha^?1 year^?1 in normal and drought year, respectively. Based on the soil loss in a normal year, the interventions recommended for 85.3 % of area of the watershed includes agronomic measures such as contour cultivation, graded bunds, strip cropping, mixed cropping, crop rotations, mulching, summer plowing, vegetative bunds, agri-horticultural system, and management practices such as broad bed furrow, raised sunken beds, and harvesting available water using farm ponds and percolation tanks. This methodology can be adopted for estimating the soil loss from similar ungauged watersheds with deficient data and for planning suitable soil and water conservation interventions for the sustainable management of the watersheds.     

An experimental method to verify soil conservation by check dams on the Loess Plateau, China

A successful experiment with a physical model requires necessary conditions of similarity. This study presents an experimental method with a semi-scale physical model. The model is used to monitor and verify soil conservation by check dams in a small watershed on the Loess Plateau of China. During experiments, the model–prototype ratio of geomorphic variables was kept constant under each rainfall event. Consequently, experimental data are available for verification of soil erosion processes in the field and for predicting soil loss in a model watershed with check dams. Thus, it can predict the amount of soil loss in a catchment. This study also mentions four criteria: similarities of watershed geometry, grain size and bare land, Froude number (Fr) for rainfall event, and soil erosion in downscaled models. The efficacy of the proposed method was confirmed using these criteria in two different downscaled model experiments. The B-Model, a large scale model, simulates watershed prototype. The two small scale models, D_a and D_b, have different erosion rates, but are the same size. These two models simulate hydraulic processes in the B-Model. Experiment results show that while soil loss in the small scale models was converted by multiplying the soil loss scale number, it was very close to that of the B-Model. Obviously, with a semi-scale physical model, experiments are available to verify and predict soil loss in a small watershed area with check dam system on the Loess Plateau, China.     

Artificial neural network analysis for reliability prediction of regional runoff utilization

Many factors in the reliability analysis of planning the regional rainwater utilization tank capacity need to be considered. Based on the historical daily rainfall data, the following four analyzing procedures will be conducted: the regional daily rainfall frequency, the amount of runoff, the water continuity, and the reliability. Thereafter, the suggested designed storage capacity can be obtained according to the conditions with the demand and supply reliability. By using the output data, two different types of artificial neural network models are used to build up small area rainfall–runoff supply systems for the simulation of reliability and the prediction model. They are also used for the testing of stability and learning speed assessment. Based on the result of this research, the radial basis function neural network (RBFNN) model, using the Gaussian function that has a similar trend as the nature as basic function, has better stability than using the back-propagation neural network (BPNN) model. Despite the fact that RBFNN was more reliable than BPNN, it still made a conservative estimate for the actual monitoring data. The error rate of RBFNN was still higher than the correction of BPNN 4-3-1-1. This should have significant benefit in the future application of the instantaneous prediction or the development of related intelligent instantaneous control equipment.     

Linking on-farm dairy management practices to storm-flow fecal coliform loading for California coastal watersheds

How and where to improve water quality within an agricultural watershed requires data at a spatial scale that corresponds with individual management decision units on an agricultural operation. This is particularly true in the context of water quality regulations, such as Total Maximum Daily Loads (TMDLs), that identify agriculture as one source of non-point source pollution through larger tributary watershed scale and above and below water quality investigations. We have conducted a systems approach study of 10 coastal dairies and ranches to document fecal coliform concentration and loading to surface waters at the management decision unit scale. Water quality samples were collected on a storm event basis from loading units that included: manure management systems; gutters; storm drains; pastures; and corrals and lots. In addition, in-stream samples were collected above and below the dairy facilities and from a control watershed, managed for light grazing and without a dairy facility or human residence and corresponding septic system. Samples were analyzed for fecal coliform concentration by membrane filtration. Instantaneous discharge was measured for each collected sample. Storm runoff was also calculated using the curve number method (SCS, 1985). Results for a representative dairy as well as the entire 10 dairy data set are presented. Fecal coliform concentrations demonstrate high variability both within and between loading units. Fecal coliform concentrations for pastures range from 206 to 2,288,888 cfu/100 ml and for lots from 1,933 to 166,105,000 cfu/100 ml. Mean concentrations for pastures and lots are 121,298 (SE=62,222) and 3,155,584 (SE=1,902,713) cfu/100 ml, respectively. Fecal coliform load from units of concentrated animals and manure are significantly more than units such as pastures while storm flow amounts were significantly less. Compared with results from earlier tributary scale studies in the watershed, this systems approach has generatedwater quality data that is beneficial for management decisions because of its scale and representation of current management activities. These results are facilitating on-farm changes through the cooperative efforts of dairy managers, regulatory agency staff, and sources of technical and financial assistance.     

Linking phosphorus export and hydrologic modeling: a case study in Central Italy

Soil erosion is an open topic, not only because soil fertility is lost, but also because nutrients are spilled into water bodies, thereby causing pollution. Research carried out in this field has amply described this process, but the interaction between these factors is complex and experimental research is needed to understand the production of loads of nutrients for different land uses. This paper describes a long-term monitoring case study using high-resolution rainfall data and runoff samples, carried out in the Lake Vico basin (Central Italy) to determine the phosphorus (P) export during erosive rainfall events. State of the art GIS-based basin characterization and advanced rainfall-runoff models are employed in order to describe the relationship between nutrient export and rainfall or runoff time distribution. Results show that the phosphorus export is strongly related to such time distributions, and less to the cumulative amount of rainfall or runoff.     

基于SWAT模型的湘江永州流域非点源氮磷污染特征分析

为精准治理流域非点源氮磷污染,基于SWAT模型,运用本地区第二次全国污染源普查数据和2000—2019年流域水文、水质数据,开展湘江永州流域非点源氮磷污染模拟。结果表明：湘江永州流域建立的SWAT模型具有较好的模拟效果,流域2005—2019年的总氮月均污染负荷为383.40～17 998.70 t/m;总磷月均污染负荷为64.62～567.86 t/m,总氮和总磷各月污染负荷均与各月降雨量呈显著相关关系;农田和林地是本流域总氮、总磷污染负荷总量最大的2种用地类型,但两者之间单位面积输出的污染负荷强度却相反,林地对流域水污染防控具有正面效应,农田种植面源污染是非点源氮磷污染治理的重点。     

A field study of the influence of land management and soil properties on runoff and soil loss in central Spain

Since the 1950s afforestation of degraded land has been the principal means of combatting erosion in a seasonally arid area of central Spain. In the 1970s tree planting of steep hillsides and gully sides was preceded by bench terracing. Experimental sites have been established to monitor runoff and soil losses under mature Pinus forest, 12-year-old Pinus forest, and Cistus matorral. The experiment is being conducted at three scales: large gully or small watershed (c. 3.5 ha), runoff erosion plot (10–21.5 m²), and rainfall simulation plot (1 m²). Monitoring began in October 1992. Discharge was recorded continuously, while sediment loss and soil moisture content were measured on a storm basis. The paper presents summary data on runoff and soil erosion for the three scales and comments on relationships between land management, site characteristics, and these losses. We stress the crucial role of vegetation and its interrelationship with soil properties such as structure and aggregate stability. Matorral was effective in combatting water and soil loss, but we question the practice of afforesting seasonally arid, steeply sided areas that have highly erodible soils.     

A water quality monitoring network design methodology for the selection of critical sampling points: Part II

In order to resolve the spatial component of the design of a water quality monitoring network, a methodology has been developed to identify the critical sampling locations within a watershed. This methodology, called Critical Sampling Points (CSP), focuses on the contaminant total phosphorus (TP), and is applicable to small, predominantly agricultural-forested watersheds. The CSP methodology was translated into a model, called Water Quality Monitoring Station Analysis (WQMSA). It incorporates a geographic information system (GIS) for spatial analysis and data manipulation purposes, a hydrologic/water quality simulation model for estimating TP loads, and an artificial intelligence technology for improved input data representation. The model input data include a number of hydrologic, topographic, soils, vegetative, and land use factors. The model also includes an economic and logistics component. The validity of the CSP methodology was tested on a small experimental Pennsylvanian watershed, for which TP data from a number of single storm events were available for various sampling points within the watershed. A comparison of the ratios of observed to predicted TP loads between sampling points revealed that the model's results were promising.     

Investigation of urban water quality using simulated rainfall in a medium size city of China

Road-deposited sediment (RDS) is an important environmental medium for impacting the characteristics of pollutants in stormwater runoff; it is of critical importance to investigate the water quality of urban environments. The paper develops a rainfall simulator as an important research tool to ensure homogeneity and reduce the large number of variables that are usually inherent to urban water quality research. The rainfall simulator was used to experiment runoff samples from typical residential and traffic areas in the Zhenjiang. The data show that land use is one of the major factors contributing to the difference in the pollutants concentration in the RDS. The maximum mean EMC for TN, TDN, TP, and TDP at residential area was 5.52, 3.07, 1.65, and 0.36 mg/L, respectively. The intense traffic area displayed the highest metal concentrations. Concentrations of runoff pollutants varied greatly with land use and storm characteristics. The correlation of pollutant concentrations with runoff times was another predominant phenomenon. Peaks in pollutants concentration occurred at 1 and 10 min during the whole storm event. A concentration peak that correlates with a peak in runoff flowrate correlates with rainfall intensity. The pollutant loadings (kilograms per hectare) in the Zhenjiang were 11.39 and 55.28 for COD, 8.42 and 57.48 for SS, 0.11 and 0.88 for TN, 0.02 and 0.14 for TP, 0.02 and 0.09 for Zn, and 0.01 and 0.04 for Pb. The higher rainfall contribute to the higher pollutant loading at the residential and intense traffic areas, as a result of the pollutant loadings direct dependence on rainfall intensity. The results confirmed that the rainfall simulator is a reliable tool for urban water quality research and can be used to simulate pollutant wash-off. These findings provide invaluable information for the development of appropriate management strategies to decrease nonpoint source contamination loading to the water environment in urban areas.     

Application of integrated GIS and multimedia modeling on NPS pollution evaluation

In Taiwan, nonpoint source (NPS) pollution is one of the major causes of the impairment of surface waters. I-Liao Creek, located in southern Taiwan, flows approximately 90 km and drains toward the Kaoping River. Field investigation results indicate that NPS pollution from agricultural activities is one of the main water pollution sources in the I-Liao Creek Basin. Assessing the potential of NPS pollution to assist in the planning of best management practice (BMP) is significant for improving pollution prevention and control in the I-Liao Creek Basin. In this study, land use identification in the I-Liao Creek Basin was performed by properly integrating the skills of geographic information system (GIS) and global positioning system (GPS). In this analysis, 35 types of land use patterns in the watershed area of the basin are classified with the aid of Erdas Imagine process system and ArcView GIS system. Results indicate that betel palm farms, orchard farms, and tea gardens dominate the farmland areas in the basin, and are scattered around on both sides of the river corridor. An integrated watershed management model (IWMM) was applied for simulating the water quality and evaluating NPS pollutant loads to the I-Liao Creek. The model was calibrated and verified with collected water quality and soil data, and was used to investigate potential NPS pollution management plans. Simulated results indicate that NPS pollution has significant contributions to the nutrient loads to the I-Liao Creek during the wet season. Results also reveal that NPS pollution plays an important role in the deterioration of downstream water quality and caused significant increase in nutrient loads into the basin's water bodies. Simulated results show that source control, land use management, and grassy buffer strip are applicable and feasible BMPs for NPS nutrient loads reduction. GIS system is an important method for land use identification and waste load estimation in the basin. Linking the information of land utilization with the NPS pollution simulation model may further provide essential information of potential NPS pollution for all subregions in the river basin. Results and experience obtained from this study will be helpful in designing the watershed management and NPS pollution control strategies for other similar river basins.     

平原感潮河网地区不同土地利用下营养盐迁移特征

分别在南通平原河网地区选择典型非圩区开展野外原位试验,用野外观测和室内分析相结合的方法,研究平原非圩区典型试验小区不同土地利用下营养盐在自然降雨—径流驱动下迁移的时空分布特征.结果表明,导致营养盐迁移时空分布存在显著差异的主要原因为不同的土地利用类型、施肥条件及植被覆盖度等,不同土地利用下的径流量差异是导致营养盐迁移通...     

Role of Geographic Information System (GIS) in Watershed Simulation By Winvast Model

The uncertainty of modeling input will increase the simulation error, and this situation always happens in a model without user-friendly interface. WinVAST model, developed by the University of Virginia in 2003, treats an entire multi-catchment by a tree-view structure. Its extra computer programs can connect geographic information system (GIS). Model users can prepare all the necessary information in ArcGIS. Extracting information from GIS interface can not only decrease the inconvenience of data input, but also lower the uncertainty due to data preparation. The Daiyuku Creek and Qupoliao Creek in the Fei-tsui reservoir watershed in Northern Taiwan provided the setting for the case study reported herein. The required information, including slope, stream length, subbasin area, soil type and land-use condition, for WinVAST model should be prepared in a Microsoft Access database, which is the project file of WinVAST with extension mdb. In ArcGIS interface, when the soil layer, land-use layer, and Digital Elevation Model (DEM) map are prepared, all the watershed information can be created as well. This study compared the simulation results from automatically generated input and manual input. The results show that the relative simulation error resulting from the rough process of data input can be around 30% in runoff simulation, and even reach 70% in non-point source pollution (NPSP) simulation. It could conclude that GIS technology is significant for predicting watershed responses by WinVAST model, because it can efficiently reduce the uncertainty induced by input errors.