Soil Conservation Service Model Research Articles

Towards evaluating the conditional probability of waterborne microbial risks associated with critical rainfall events following land application of animal waste — A focus on Irish pastures

ABSTRACT Modelling surface runoff and infiltration in an agricultural watershed is essential for understanding the nutrient cycle and water quality management. This research evaluates the critical rainfall events causing maximum surface runoff and infiltration. Empirical models such as Soil Conservation Service (SCS) curve number and Explicit Green-Ampt (EGA) were analysed for different soil hydraulic conditions and storm events with specific return periods. The present study forecasted the maximum daily rainfall and intensity as 113.6 mm and 19.9 cm h–1, respectively, considering a 100-year return period storm. The deterministic part of the model calculates the daily maximum surface runoff as 5.51 cm (from the SCS model). The EGA model revealed that the rainfall intensity of 0.143, 0.163, 0.175, 0.179, 0.181, 0.182, and 0.182 cm h−1 (duration of 24 h) was found critical for 1, 2, 5, 10, 25, 50, 100 year return period of the storm, respectively in different soil texture classes (sand, loamy sand, sandy loam, loam, silt loam, sandy clay loam, clay loam, silty clay soils). Exceptions imply for three occasions where the intensity of 0.407 cm h−1 and duration of 18 h produced maximum infiltration for silty clay loam, and intensity of 0.352 and 0.354 cm h−1 with 9 h rainfall (each) produced maximum infiltration for clay. The probabilistic model revealed that a daily storm event probability of 2.74 × 10–5 is associated with a simulated mean runoff depth of 0.69 cm and infiltration of 20.7 cm. Critical rainfall probabilities calculated in this study can be multiplied with the overall microbial/pollutant human health risk assessment framework to calculate conditional probability and better estimate microbial risk through the drinking water pathway. This study is very relevant for the wet climatic condition of Ireland, where most land use is pastures.

Evaluating future flood risk mitigation capacities in major cities across China

Rapid urbanization and climate change have significantly altered urban hydrological processes. Previous research has highlighted their adverse effects on escalating risk of urban flood. Nevertheless, few assessments have quantified how future urban flood risk mitigation capacities evolve under various urban expansion and climate change scenarios. This study simulates urban expansion of major cities across China using future urban-regional environment simulation model at 30-m resolution under shared socioeconomic pathways scenarios (SSP). Concurrently, future precipitation intensity changes are assessed based on climate projection data. Finally, the urban flood risk mitigation capacity impacted by urban expansion and climate change is evaluated using the soil conservation service model. The results reveal: (1) The sizes of major cities are projected to expand 30% by 2050, and the north and east China are primary urban growth poles. (2) Major cities' precipitation intensity increase 0.4% in SSP126, but decline 5.4% and 2.3% in SSP245 and SSP585. (3) The flood risk mitigation capacities of major cities decrease 2.7% in SSP126 and 2.1% in SSP585, but increase 0.2% in SSP245. Most cities experiencing capacity decrease are located in the north and east China. These results provide valuable insights for the formulation of future urban flood adaptation and mitigation strategies.

Assessing the performance of techniques for disaggregating daily rainfall in South Africa

Design flood estimation (DFE) methods are used to limit the risk of failure and ensure the safe design of hydrological and related infrastructure, and to inform water resources management. In order to improve DFE methods which are based on event or continuous simulation rainfall–runoff models, it is generally necessary to use sub-daily rainfall data. However, sub-daily rainfall gauges are relatively sparse and have shorter record lengths than daily rainfall gauges in South Africa. Rainfall temporal disaggregation (RTD) techniques can be used to produce finer resolution data from coarser resolution daily rainfall data. Several RTD approaches have been developed and are used in South Africa. However, there is a need to review and assess the performance of the available RTD methods. This paper contains an overview of selected RTD approaches and the performance of the methods at selected sites in South Africa, for disaggregating daily rainfall into 15-min intervals. Temporal distributions of rainfall were represented by dimensionless Huff curves, which served as the basis for comparison of observed and disaggregated rainfall. In a pilot study it was found that the SCS-SA (Soil Conservation Service model South Africa) distributions and the Knoesen model approaches performed considerably better than the other approaches. The RTD approaches were further assessed using data from 14 additional rainfall stations. For the additional stations, the Knoesen model and SCS-SA disaggregated rainfall generally provided the most realistic temporal distributions.

High-resolution mapping of the rainfall runoff pollution: case study of Shiwuli River watershed, China.

Rainfall runoff is the key factor of water quality deterioration in highly urbanized area, which is characterized by intensive human activities and frequent extreme weather events. Urban landscape system is composed of highly diverse and heterogeneous land patches, which makes the effective management of urban runoff pollution difficult. Therefore, high-resolution land-use data is imperative for the identification and analysis of spatial-temporal characteristics of urban runoff pollution. In this study, Shiwuli River watershed, a rapidly urbanizing area in China, is selected as the study area. We first interpret nine kinds of land-use types with a high-resolution remote sensing data of 2m [Formula: see text] 2m. Then, a localized Soil Conservation Service model based on field observation and rainfall experiments is applied to map the spatial-temporal pattern of runoff pollution. The results indicate that the COD, NH3-N, TP, and TN load generated by the runoff in the watershed accounted for 23.4%, 3.7%, 8.2%, and 9.0% of the total pollution load in 2016, respectively. Furthermore, the spatial-temporal pattern of the assessed runoff pollution was mainly subject to the distribution of rainfall and land-use patterns. We suggest that the sponge city construction combined with surface pollution control is an effective way to reduce the runoff pollution. This study highlights the necessity to identify spatial-temporal hotspots in developing precise pollution control measures, which provides valuable information for pollution control policy-making in Shiwuli River watershed and could serve as a reference for other river watersheds undergoing rapid urbanization.

Optimum parametrization of the soil conservation service (SCS) method for simulating the hydrological response in arid basins

The use of the soil conservation service (SCS) curve number (CN) model for estimation of the rainfall excess and the SCS-unit hydrograph (UH) model are common tools for flood studies in arid regions. In this research, we are investigating the capability of these models to simulate flood events in the arid region under the common parametrization provided by the SCS model (SCS-CN, the initial abstraction ratio, λ, and UH theory) and the optimum parameterization for best simulating the hydrologic response. A case study is performed in Al-Lith basin in the west of Saudi Arabia (SA). The study simulates measured rainfall-runoff events in the area using seven scenarios (various SCS-CN estimation methods: least-squares method (CNLSM), asymptotic fitting method (CN∞), SCS-CN tables (CNdesign), and antecedent moisture content CN (CNI, CNII, and CNIII), λ = 0.2 and 0.01, and SCS-UH and UH derived from streamflow data) and a comparison is made between the observations and model results under the common parameterization of the SCS model and parameterization estimated from the Saudi arid environment. The comparison between simulated and observed peak flow and runoff volume of the studied events shows high scatter which is a common feature in arid regions due to the inherent uncertainties in the hydrological processes which are not yet resolved due to the lack of detailed measurements of the rainfall-runoff processes. Statistical analysis showed that λ = 0.01 provides a minimum root mean square error (RMSE) in the peak flow (24.8 m3/s) and the runoff volume (0.31 million m3) with CNLSM obtained by LSM. CN∞ is bad to simulate the hydrologic response. The SCS-CN Tables cannot be used for hydrological simulation. They can rather be used for the design purposes of mitigation structures.

Comparing the Soil Conservation Service model with new machine learning algorithms for predicting cumulative infiltration in semi-arid regions

Water infiltration into soil is an important process in hydrologic cycle; however, its measurement is difficult, time-consuming and costly. Empirical and physical models have been developed to predict cumulative infiltration (CI), but are often inaccurate. In this study, several novel standalone machine learning algorithms (M5Prime (M5P), decision stump (DS), and sequential minimal optimization (SMO)) and hybrid algorithms based on additive regression (AR) ( i.e ., AR-M5P, AR-DS, and AR-SMO) and weighted instance handler wrapper (WIHW) ( i.e ., WIHW-M5P, WIHW-DS, and WIHW-SMO) were developed for CI prediction. The Soil Conservation Service (SCS) model developed by the United States Department of Agriculture (USDA), one of the most popular empirical models to predict CI, was considered as a benchmark. Overall, 154 measurements of CI (explanatory/input variables) were taken from 16 sites in a semi-arid region of Iran (Illam and Lorestan provinces). Six input variable combinations were considered based on Pearson correlations between candidate model inputs (time of measuring and soil bulk density, moisture content, and sand, clay, and silt percentages) and CI. The dataset was divided into two subgroups at random: 70% of the data were used for model building (training dataset) and the remaining 30% were used for model validation (testing dataset). The various models were evaluated using different graphical approaches (bar charts, scatter plots, violin plots, and Taylor diagrams) and quantitative measures (root mean square error (RMSE), mean absolute error (MAE), Nash-Sutcliffe efficiency (NSE), and percent bias (PBIAS)). Time of measuring had the highest correlation with CI in the study area. The best input combinations were different for different algorithms. The results showed that all hybrid algorithms enhanced the CI prediction accuracy compared to the standalone models. The AR-M5P model provided the most accurate CI predictions (RMSE = 0.75 cm, MAE = 0.59 cm, NSE = 0.98), while the SCS model had the lowest performance (RMSE = 4.77 cm, MAE = 2.64 cm, NSE = 0.23). The differences in RMSE between the best model (AR-M5P) and the second-best (WIHW-M5P) and worst (SCS) were 40% and 84%, respectively.

Runoff Curve Number (CN model) Evaluation Under Tropical Conditions

In tropical countries the Curve Number method (CN) of the Soil Conservation Service (SCS) is widely used in civil engineering (to calculate drainage infrastructure) as well as in agricultural and environmental studies. However, little is known about the accuracy of CN method in tropical watersheds. To reveal the CN method accuracy, this study compares the CN method results with field data measured in an Andean micro watershed. For this, CN values for the tropical micro watershed "La Vega" were identified using the tables proposed by the SCS and its respective moisture and slope corrections (CNAMC2S); subsequently CN values were derived from 55 events (CNQ) in which runoff and rainfall were measured. It was observed a different of 27% between CNQ and CNAMC2S (CNQ = 80, CNAMC2S 58.1). According to that, the data shows that in the tropical micro watershed evaluated in this study, the SCS method overestimated runoff. The CN model of the SCS is strongly influenced by the antecedent humidity and its impact becomes stronger after high rainfalls records; however, the antecedent humidity influence was not observed in measured runoff data. Despite the CN – SCS model did not present a relationship between CN and precipitation, this relationship was observed in measure data. This study shows that CN method has some inaccuracies and it requires further studies to know its applicability in tropical conditions.

Runoff assessment by Storm water management model (SWMM)- A new approach

The present study investigated the storm wise runoff collected in farm pond with the runoff estimated by Storm Water Management Model (SWMM) and Soil Conservation Service (SCS-CN) models. The SWMM and SCS-CN models estimated runoff depth storm wise. The runoff depths correspond to the catchment area given the runoff volume from the catchment. The runoff depth estimated from the Storm Water Management Model and Soil Conservation Service model was compared against the depth of runoff estimated from the Water balance model. For small rainfall depths, the runoff estimated from the Storm Water Management Model was at par with the actual runoff volume stored at the pond. It is necessary to know the watershed runoff contribution to the river or streams due to rainfall in order to determine environmental risk or flood potential. In larger rainfall depth, the runoff volume estimated from the SWMM model was less than the stored runoff volume at Farm Pond. The Soil Conservation Service Model gave better results for larger rainfall depth compared to Storm Water Management Model. SWMM was able to simulate runoff depth for small rainfall depths of 2mm. The peak runoff depths were produced by rainfall depths of 35.5mm. Initial abstractions of the study area for antecedent moisture content i.e. AMC I, AMCII and AMCIII are 53.2, 23.91 and 10.43mm, respectively. The comparison showed that both SWMM and SCS-CN models gave better runoff quantification results.

Morphological-hydrological relationships and the geomorphological instantaneous unit hydrograph of Makkah Al-Mukarramah watersheds

The present study focused on developing the predominant relationships between morphological and morphological-hydrological parameters of watersheds in the Makkah Al-Mukarramah region, Kingdom of Saudi Arabia (KSA). These relationships are essential for flood mitigation studies in the region. The relationships developed in this study are averaged over 43 watersheds (varying in size from 42.2 to 6081.4 km2) to provide a theoretical basis for regional morphological and hydrological analyses. In addition, the similarity of the hydrologic response of these watersheds is studied via the theory of geomorphological instantaneous unit hydrograph (GIUH). The results show that there is a relatively high similarity among the 43 basins (the average similarity parameter is 0.61, and the values vary from 0.57 to 0.68 at 95% confidence). Comparisons of the peaking factor between the Soil Conservation Service (SCS) and the Arid-Zone, Ari-Zo, (Albishi et al., Arabian Journal of Geosciences 10:1–13, 2017) models show that the common SCS model underestimates the peak discharge. The time of concentration is overpredicted by the Kirpich (Civil Engineering 10:362, 1940) equation (up to 17 times) compared to the Ari-Zo model. The GIUH and SCS models overestimate the time to peak when compared with the Ari-Zo model. These results are crucial for flood estimation and mitigation in the region.

Application of the soil conservation service model in small and medium basins of the mountainous region of Heilongjiang, China

Rainfall and run-off prediction capabilities for flash flood need improvement in the high porn regions of mountain hazard, those caused massive distraction. At some point, these events result in a massive loss of life and property. This research demonstrates the application of soil conservation service (SCS), a hydrological model used to simulate the relationship between rainfall and run-off. The data cover a 62-year observation period of torrential rains and debris flows, which number up to thirty flow events, all occurring in the mountainous regions close to the Tieli watershed area. Rainfall hydrographs were generated for each of the said torrential rain cases and can be used as markers for flood warnings for critical rainfalls lasting from 1 to 24 h. The results show that the SCS model can successfully define the rainfall-run-off-water level relationship of small-medium-size catchments wherein the calculated run-off values show good agreement with measured discharges. Moreover, from the relationship of the water level and SCS calculated run-off is similar to the relationship obtained using measured run-offs. From this relationship, critical water levels that would correspond to the occurrence of a possibly devastating flood can be determined to provide for an early warning measure for the nearby regions.

A Simple GIS-Based Model for Urban Rainstorm Inundation Simulation

With rapid urbanization, floods that occur are more frequently associated with non-riverine, urban flooding. Reliable and efficient simulation of rainstorm inundation in an urban environment is profound for risk analysis and sustainable development. Although sophisticated hydrodynamic models are now available to simulate the urban flooding processes with a high accuracy, the complexity and heavy computation requirement render these models difficult to apply. Moreover, a large number of input data describing the complex urban underlying surfaces is required to setup the models, which are typically unavailable in reality. In this paper, a simple and efficient urban rainstorm inundation simulation method, named URIS, was developed based on a geographic information system (GIS) with limited input data. The URIS method is a simplified distributed hydrological model, integrating three components of the soil conservation service (SCS) module, surface flow module, and drainage flow module. Cumulative rainfall-runoff, output from the SCS model, feeds the surface flow model, while the drainage flow module is an important waterlogging mitigation measure. The central urban area of Shanghai in China was selected as a study case to calibrate and verify the method. It was demonstrated that the URIS is capable of characterizing the spatiotemporal dynamic processes of urban inundation and drainage under a range of scenarios, such as different rainstorm patterns with varying return periods and different alterations of drainage diameters. URIS is therefore characterized with high efficiency, reasonable data input, and low hardware requirements and should be an alternative to hydrodynamic models. It is useful for urgent urban flood inundation estimation and is applicable for other cities in supporting emergency rescue and sustainable urban planning.

Runoff Estimation by Using the (SCS-CN) Method with GIS and RS for Wadi Shuieb Watershed

The goal of this study is to estimate surface runoff using (SCS-CN) and Geographic Information System and remote sensing (GIS &RS) in Wadi Shuieb Basin which is located within the dry region in central Jordan. The maps of the hydrological soils and land use / land cover were used within the GIS environment toolbox to produce table and map of the curve number (CN). The model of the curve number was then used to estimate the runoff which corresponds to the rain storms within the watershed. Due to the inconsistence records of runoff within the study area, the SCS-CN model was found to be an effective method for estimating the runoff generation. The results show that the SCS-CN method provides high-precision results in estimating surface runoff which particularly based on rain storms. The corresponding values were (57.7), (76.5) and (88.4) under dry, normal and wet conditions respectively. This in turns influences the surface storage (S) and the initial loss (Ia). The results furthermore, illustrate that the highest rate of surface runoff (64940 m3) was in Salt meteorological station, whereas (Ira) meteorological station has the lowest rate of surface runoff (14580 m3). Key Words: Surface Runoff, Curve Number, Wadi Shuieb, Hydrologic, Soil Conservation Service Model.

GIS-based approach for identification of potential rainwater harvesting sites in Arsi Zone, Central Ethiopia

Water plays a crucial role in fulfilling basic human needs, for socio-economic developments and for ecosystem services. Ethiopia is experiencing pressure on water shortage for agricultural and domestic uses. Arsi Zone frequently faces drought and crop failure due to lack of water sources. Eleven physical characteristics of the study area layers were adopted integrating multi criteria decision analysis, which uses analytical hierarchy processes with a fuzzy logic approach and geographical information system. Soil conservation service model was used to estimate the runoff depth layer of the study area. Weighting was made based on environmental, socio-economical and hydro-geological characteristics of the study area, and available literature. Results show that potential suitability class was not suitable with constraints 5769.8 km2 (27.88%), less suitable 3104.34 km2 (15%), suitable 5695.42 km2 (27.52%), very suitable 4097 km2 (19.8%) and extremely suitable 2027.38 km2 (9.8%). The area coverage of constraints were 4540.37 km2 (21.94%) of the study area. Outcome of this study emphasized the importance of geospatial modeling in assessing rainwater harvesting potential sites, proposed to assist in planning water facility and to address water scarcity problem in the study area. The model developed in this research can be used in other areas to determine the potential of rainwater harvesting and integrate rainwater as an alternative water source to ensure availability for domestic, agricultural and industrial uses. It is recommended that detailed ground validation and socio-economic factors should be analyzed to increase its effectiveness before implementation.

Investigation of application of storm runoff harvesting system using geographic information systems (GIS): a case study of the Arak watershed, Markazi (Iran)

Integrated management of urban watersheds and effective productivity of its resources, especially water resources, requires knowledge of its hydrology. In this regard, flood events and urban runoff produced at the time of floods from the point of harvesting and consumption of critical are very important. In this study in order to evaluate the possibility of using the most appropriate rainwater harvesting systems in Arak watershed, by collecting basic information from the watershed overlooking the city, surrounding watersheds were grouped by using the cluster analysis in homogeneous areas. In each region using the soil conservation service model, the rate of base time and return periods was calculated. Also, using an analytic hierarchy process and quantitative and qualitative criteria, different systems of urban water harvesting were determined for each homogeneous region of Arak watershed.

Comparison of SCS and Green-Ampt Distributed Models for Flood Modelling in a Small Cultivated Catchment in Senegal

The vulnerability to floods in Africa has increased over the last decades, together with a modification of land cover as urbanized areas are increasing, agricultural practices are changing, and deforestation is increasing. Rainfall-runoff models that properly represent land use change and hydrologic response should be useful for the development of water management and mitigation plans. Although some studies have applied rainfall-runoff models in West Africa for flood modelling, there is still a need to develop such models, while many data are available and have not still been used for modelling improvement. The Ndiba catchment (16.2 km2), which is located in an agricultural area in south Senegal, is such catchment, where a lot of hydro-climatic data has been collected between 1983 and 1992. Twenty-eight flood events have been extracted and modelled by two event-based rainfall-runoff models that are based on the Soil Conservation Service (SCS) or the Green-Ampt (GA) models for runoff, both coupled with the distributed Lag and Route (LR) for routing. Both models were able to reproduce the flood events after calibration, but they had to account for that the infiltration processes are highly dependent on the tillage of the soils and the growing of the crops during the rainy season, which made the initialization of the event-based models difficult. The most influent parameters for both models (the maximal water storage capacity for SCS, the hydraulic conductivity at saturation for Green-Ampt) were mostly related to the development stage of the vegetation, described by a Normalized Difference Vegetation Index (NDVI) anomaly. The SCS model performed finally better than the Green-Ampt model, because Green-Ampt was very sensitive to the variability of the hydraulic conductivity at saturation. The variability of the parameters of the models highlights the complexity of this kind of cultivated catchment, with highly non stationary conditions. The models could be improved by a better knowledge of the tillage practices, and a better integration of these practices in the parameters predictors.

APPLICATION OF GIS AND MCE TECHNIQUES FOR OPTIMUM SITE SELECTION FOR WATER HARVESTING STRUCTURES

Water is a primary necessity for the sustainable survival of all forms of life and enormously scarce in arid parts of the world including India. The basic unit of water resources assessment and planning is a watershed. Water resources management at a watershed scale requires both water supply and demand management which includes water conservation through rainwater harvesting, groundwater recharge, and recycling. The present study is aimed to assess the potential of water harvesting and to identify suitable sites for water harvesting structures in Kolayat watershed of Bikaner district in Rajasthan by using Geographic Information System (GIS) and Multi-Criteria Evaluation (MCE). Proposed methodology of water harvesting site selection has compared with traditional methods of site selection. In traditional practices, the location of the structure is selected by visiting the geographical areas and looking at the various drainage patterns, soil erosion, land use land cover, water storage areas, availability of insects/ animals, native population feedback and past experiences. These practices are entirely dependent on instincts and results of the selected zones are uncertain. However, geospatial analysis techniques like RS, GIS, and MCE are the innovative tools which can be used to determine suitable sites for rainwater harvesting structures based on the watershed characteristics. The soil conservation service model (NRCS curve number) has been used to estimate the runoff. Further, spatial analysis in GIS has been carried out considering MCE along with the Analytical Hierarchy Processes (AHP) to assess the water harvesting potential and to identify the optimum locations of rainwater harvesting structures.

Impact of landuse/land cover change on run-off in the catchment of a hydro power project

The landuse/land cover change and rainfall have a significant influence on the hydrological response of the river basins. The run-off characteristics are changing naturally due to reduction of initial abstraction that increases the run-off volume. Therefore, it is necessary to quantify the changes in the run-off characteristics of a catchment under the influence of changed landuse/land cover. Soil conservation service model has been used in the present study to analyse the impact of various landuse/land cover (past, present and future time period) change in the run-off characteristics of a part of Narmada basin at the gauge discharge site of Mandaleswar in Madhya Pradesh, India. Calculated run-off has been compared with the observed run-off data for the study. The landuse/land cover maps of 1990, 2000 and 2009 have been prepared by digital classification method with proper accuracy using satellite imageries. The impact of the run-off change on hydro power potential has been assessed in the study along with the estimation of the future changes in hydro power potential. Five types of conditions (+10, +5 %, average, −5, −10 % of average rainfall) have been applied with 90 and 75 % dependability status. The generated energy will be less in 90 % dependable flow in respect to the 75 % dependable flow. This work will be helpful for future planning related to establishment of hydropower setup.

Site Suitability Analysis of Water Harvesting Structures Using Remote Sensing and GIS – A Case Study of Pisangan Watershed, Ajmer District, Rajasthan

Abstract. Rajasthan is a region with very limited water resources. Water is the most crucial for maintaining an environment and ecosystem conducive to sustaining all forms of life. The principle of watershed management is the proper management of all the precipitation by the way of collection, storage and efficient utilization of runoff water and to recharge the ground water. The present study aim's to identify suitable zones for water harvesting structures in Pisangan watershed of Ajmer district, Rajasthan by using Geographic Information System (GIS) and Multi Criteria Evaluation (MSE). Multi criteria evaluation is carried out in Geographic Information system to help the decision makers in determining suitable zones for water harvesting structures based on the physical characteristics of the watershed. Different layers which were taken into account for multi criteria evaluation are; Soil texture, slope, rainfall data (2000–2012), land use/cover, geomorphology, lithology, lineaments, drainage network. The soil conservation service model was used to estimate the runoff depth of the study area Analytical Hierarchy Processes (AHP) is used to find suitable water harvesting structures on the basis of rainfall. Produced suitability map will help in the selection of harvesting structures such as percolation tanks, storage tank, check dams and stop dams.

Water-related ecosystem services provided by urban green space: A case study in Yixing City (China)

With the development of urbanization, green space in urban areas has received widespread attention and become an important symbol of urban ecosystem health. Urban green space plays a positive role in water regulation and purification, but this function is often ignored by municipal authorities. Based on remote-sensing image interpretation and practical investigations in Yixing (China), this study evaluated the water regulation and purification functions performed by urban green space, using the modified Soil Conservation Service model, in conjunction with relevant experimental data. The results show that during the period 2007 to 2009, the average volume of rainfall stored by the urban green space in Yixing was 5.3×107m3yr−1, which represented more than 88% of the rainfall received. The average figures for chemical oxygen demand (CODCr), total nitrogen (TN), ammoniacal nitrogen (NH4–N), and total phosphorus (TP) in rainfall that were removed by green space during 2007 to 2009 were 233.6×103kgyr−1, 70.9×103kgyr−1, 12.6×103kgyr−1, and 1.7×103kgyr−1, respectively. Differences were found between the water regulation and purification performed by urban green space inside built-up areas and those performed outside built-up areas, which relate to the importance attached to green space in the two types of area. This research will contribute to an understanding of the role that green space plays in water regulation and purification, and in the scientific management of urban green space.

PERENCAAAN PENGGUNAAN LAHAN DAN PENGARUHNYA TERHADAP SUMBERDAYA AIR DI DAS WAY BESAI - LAMPUNG

The problems on water resource are the decreasing of water supply due to the impact of land use changes. The population growth and the rising economy activity lead to the increasing of water demands. Way Besai area of 44,720 hectares has an important role in the provision of water resources. The aims of this research are: to assess the water supply and demand, to assess the water balance and, to formulate the best recommendation of land management planning. This research was conducted in 2011. The SCS (Soil Conservation Service) model was applied to determine land use planning scenarios and run-off prediction. The result shows that the water demand in Way Besai Watershed is 441,450,909m3/year, while water supply is 460,452,600 m3/year. Application of community forestry by applying agroforestry system, implementation of forest rehabilitation on area outside HKm permit, and conducting the change for coffee monoculture to mixed coffee crop in the area outside the forest is considered the best scenario of land management for Way Besai watershed. This scenario could produce 1,055.79 mm/years run-off, coefficient total runoff is 38.52%, water supply is 472,147,141 m3/years, storage is 7,911,616 m3/years and, can meet the of water demand in the dry months at 58.48%.