Impact Of Land Management Practices Research Articles

Soil erosion management using The Soil and Water Assessment Tool (SWAT) model in Semantok Watershed

The land use characteristics in the Semantok watershed have a significant impact on the reservoir's usable age. According to the land use patterns, including teak woods, rice fields, moorlands, dry fields, and residential areas, the Semantok watershed has the capacity to carry sediment when it rains. One of the models to analyze surface runoff and sediment is the Soil and Water Assessment Tool (SWAT). SWAT was developed to predict the impact of land management practices on water, sediment and agricultural chemical yields in large complex watersheds with varying soils, land use and management conditions over long periods of time. The purpose of this research is to quantify the amount of erosion and sedimentation that results from land use changes in the Semantok watershed in 2015 and 2021 and to determine management scenarios that can reduce the value of erosion and sedimentation that can implemented upstream of the Semantok dam using SWAT. The data used for the research are climatology data, DEM map, landuse map, and river data. The amount of erosion at the Semantok watershed outlet increased from 7.00 mm/year in 2015 to 14.18 mm/year in 2021. Based on Forestry Ministerial Regulation No. P.61/Menhut-II/2014, the Semantok watershed's carrying capacity is 3.95 falling into the pretty bad category (3.5 < DDD < 4.3). Three scenarios were compared in order to carry out control efforts: revegetation, check dams, and combining revegetation and check dams. The most efficient way to reduce erosion by up to 30.51% is to combine revegetation and check dam.

Dynamic Modelling of Water and Wind Erosion in Australia over the Past Two Decades

Soil erosion caused by water and wind is a complicated natural process that has been accelerated by human activity. It results in increasing areas of land degradation, which further threaten the productive potential of landscapes. Consistent and continuous erosion monitoring will help identify the location, magnitude, and trends of soil erosion. This information can then be used to evaluate the impact of land management practices and inform programs that aim to improve soil conditions. In this study, we applied the Revised Universal Soil Loss Equation (RUSLE) and the Revised Wind Erosion Equation (RWEQ) to simulate water and wind erosion dynamics. With the emerging earth observation big data, we estimated the monthly and annual water erosion (with a resolution of 90 m) and wind erosion (at 1 km) from 2001 to 2020. We evaluated the performance of three gridded precipitation products (SILO, GPM, and TRMM) for monthly rainfall erosivity estimation using ground-based rainfall. For model validation, water erosion products were compared with existing products and wind erosion results were verified with observations. The datasets we developed are particularly useful for identifying finer-scale erosion dynamics, where more sustainable land management practices should be encouraged.

Analyzing Factors Affecting the Sustainability of Land Management Practices in Mecha Woreda, Northwestern Ethiopia

In Ethiopia, the practice of land management started three decades ago in order to address the problem of land degradation and to further boost agricultural production. However, the impact of land management practices in curbing land degradation problems and improving the productivity of the agricultural sector is insignificant. Various empirical works have previously identified the determinants of the adoption rate of land management practices. However, the sustainability of land management practices after adoption, and the various factors that control the sustainability of implemented land management practices, are not well addressed. This study analyzed the factors affecting the sustainability of land management practices after implementation in Mecha Woreda, northwestern Ethiopia. The study used 378 sample respondents, selected by a systematic random sampling technique. Binary logistic regression was used to analyze the quantitative data, while the qualitative data were qualitatively and concurrently analyzed with the quantitative data. The sustained supply of fodder from the implemented land management practices, as well as improved cattle breed, increases the sustainability of the implemented land management practices. While lack of agreement in the community, lack of enforcing community bylaws, open cattle grazing, lack of benefits of implemented land management practices, acting as barrier for farming practices, poor participation of household heads during planning and decision-making processes, as well as the lack of short-term benefits, reduce the sustainability of the implemented land management practices. Thus, it is better to allow for the full participation of household heads in planning and decision-making processes to bring practical and visible results in land management practices. In addition, recognizing short-term benefits to compensate the land lost in constructing land management structures must be the strategy in land management practices. Finally, reducing the number of cattle and practicing stall feeding is helpful both for the sustainability of land management practices and the productivity of cattle. In line with this, fast-growing fodder grass species have to be introduced for household heads to grow on land management structures and communal grazing fields for stall feeding.

Modelling the Impact of Tillage on Water Quality for Sustainable Agricultural Development in a Savanna Ecological Zone, Kwara State, Nigeria

Abstract The aim of the study was to examine the effects of tillage methods on surface runoff and model the pattern and processes of surface water pollution associated with tillage methods using Soil Water Assessment Tool (SWAT). This model was designed to predict the impact of land management practices on water, sediment, and varying tillage types in watersheds over two planting seasons. Traditional heap (T), Plough/Harrow (PH), Plough/Harrow/Ridge (PHR) and No-tillage (NT) methods commonly used in the study area were applied to experimental plots at Unilorin Teaching and Research Farm and National Center for Agricultural Mechanization, Idofian (Nigeria). Using Randomized Complete Block Design (RCBD), each treatment had three replicates making 12 experimental plots at each location for the 2015 and 2016 planting season. Nine biophysical parameters were purposively selected, examined and modelled. The study revealed that four of nine biophysical factors (sediment yield: 10.54 t/ha; groundwater discharge: 174.45 mm; organic nitrogen: 62.62 kg/ha, and nitrogen in surface runoff: 5.15 kg/ha) were higher for traditional heaps, while three parameters (surface runoff: 374.42 mm; evapotranspiration: 752.78 mm, and soil loss: 1.05 kg/ha) were higher under plough/harrow and plough/harrow/ridge cultivation practices. The study concluded that tillage methods have impact on water quality. However, plough/harrow has comparatively more favorable effect on the contribution to surface runoff. It is therefore recommended that this type of tillage should be adopted to reduce water pollution and for sustainable environment.

Impact of land management practices on water use strategy for a dryland tree plantation and subsequent responses to drought

AbstractExtreme droughts, of increased frequency due to climate change, are threatening the sustainability of dryland plantations worldwide by exacerbating water scarcity. Here we aim to disentangle the impacts of combinations of terracing and mulching on water use strategy and their response to extreme droughts in a rainfed jujube (Ziziphus jujuba Mill.) plantation on the semiarid Loess Plateau of China, using 3‐year in situ field observations. Pruned jujube branches and maize straw were mulched on half‐moon terraces to form two combined treatments, referred to as JBT and MST, respectively. The efficacy of these two combinations on the water use strategy of jujube trees was compared with terracing alone (SHT) and control (no terrace). We found that under extreme drought there was clearly reduced soil water storage (SWS) for different treatments. However, the combined treatments showed significantly (p < .05) higher SWS than the SHT and control. Furthermore, the combined treatments enhanced soil water use in deep layers during both normal and drought years, thus helping jujube trees to resist droughts. Moreover, under extreme drought there was greatly reduced transpiration whereas for moderate drought increased transpiration at both seasonal and annual scales. Nonetheless, the combined treatments were associated with enhanced transpiration compared to the SHT and control during drought periods. Finally, jujube trees exhibited isohydric behavior which also helped them to cope with prolonged droughts. Overall, the findings here may provide insights into land management of dryland plantations worldwide under climate change.

Evaluating potential impacts of land management practices on soil erosion in the Gilgel Abay watershed, upper Blue Nile basin

Assessing the potential impacts of different land management practices helps to identify and implement sustainable watershed management measures. This study aims to assess a change in soil erosion rate under different land management practices in the Gilgel Abay watershed of the upper Blue Nile basin, Ethiopia. The Revised Universal Soil Loss Equation (RUSLE) model that was adapted to the Ethiopian highlands context was employed to estimate the rate of soil erosion. The impact of land management practices on soil erosion was estimated for three scenarios, which were baseline, intensive cultivation, and extensive cultivation scenarios. At the baseline scenario, the mean annual soil erosion was estimated at ~32.8 t ha−1yr−1, which is equivalent to a loss of ~13.66 Mt yr−1 from the entire watershed. While the rate of soil erosion reduced to ~11.3 t ha−1yr−1 during the implementation of intensive cultivation management practice, which reduced the total soil loss in the watershed by 65%. On the other hand, under the extensive cultivation scenario, the mean annual soil erosion rate increased to ~34.4 t ha−1yr−1. The findings suggest that implementing agricultural intensification management practices can significantly reduce soil erosion in the watershed.

Changes in land use and management by farm type and the impact on soil cover in Canada, 1991–2011

Abstract A suite of indicators have been developed in Canada to assess and report on the status and trends of agri-environmental performance as impacted by agricultural production activities. The indicators include models that focus on the impact of land management practices on soil erosion, water contamination, greenhouse gas emissions, soil organic carbon and wildlife habitat. Soil Cover is one of these indicators and relates to soil protection afforded by crop canopy, crop residue and snow. It is quantified by the equivalent number of days in a year in which the soil is not exposed, and is a function of the type of crop, biomass yield, tillage, residue management practices, and weather (snow) conditions. Higher soil cover indicates a lower risk of soil erosion, better maintenance of soil organic carbon, improved wildlife habitat and lower greenhouse gas emissions. The Soil Cover Indicator has been calculated and reported on a spatial basis over the entire country every five years since 1981. Currently, the agri-environmental indicators program is being re-oriented toward assessing the environmental sustainability of different production sectors (beef, hogs, dairy, grains, oilseeds, etc.) and commodities (milk, eggs, beef, pork, etc.) rather than geographic/areal units such as soil polygons or watersheds. As an initial effort in this direction, we have developed a ‘farm types’ database on an ecostratification spatial framework, and have applied the Soil Cover Indicator to each farm type in order to assess its levels and changes pertaining to different farm types over the period from 1991 to 2011. The database identified land use compositions and their spatio-temporal variability typical of different types of farms. Initial outputs indicate that Beef, Other Livestock and Other Crop farm types provide the highest soil cover, Dairy and Poultry/Egg farms provide moderate levels, and Field Crop, Hog and Fruit/Vegetable farms have the lowest levels. Temporal analysis indicates a general improvement in soil cover across most farm types from 1991 to 2011.

Climate smart agriculture opportunities for mitigating soil greenhouse gas emissions across the U.S. Corn-Belt

Widespread adoption of climate smart agriculture (CSA) has the potential to greatly mitigate agricultural greenhouse gas (GHG) emissions by increasing soil organic carbon (SOC) stocks and decreasing nitrous oxide (N2O) emissions. However, quantifying the impact of land management practices on soil GHG fluxes including CO2 and N2O is difficult due temporal and spatial variability of localized weather conditions and subfield soil properties. A process-based biogeochemistry modeling framework coupled with public soils, weather, and yield data layers was used to estimate regionally specific soil GHG reductions associated with the adoption of one or more CSA practices in maize (Zea mays L.) and soybean (Glycine max (L.) Merr.) crop production fields. Site-specific, multi-year DeNintrification-DeComposition model simulations were performed on agricultural fields within 11 U.S. Corn-Belt states that were identified to be in maize or soybean production from 2013 to 2016. Differences between modeled changes in SOC stocks to a depth of 50 cm, N2O emissions, and CH4 fluxes corresponding with alternative land management scenarios simulated across field sites were converted to a CO2 equivalent basis and spatially weighted to a county-scale to highlight regional variability. County-scale GHG reductions corresponding with a conversion from conventional tillage to no-tillage practices are estimated to be have a mean reduction potential of 1477 kg CO2e ha−1 yr−1 (SOC, N2O, and CH4 flux reductions of 945, 549, −17 kg CO2e ha−1yr−1, respectively, where a negative reduction indicates an increase in emissions.) with a standard deviation of 605 kg CO2e ha−1 yr−1. Additionally, the adoption of cover crops is predicted to provide a mean reduction of 678 kg CO2e ha−1 yr−1 (SOC, N2O, and CH4 flux reductions of 824, -173, 26.7 kg CO2e ha−1yr−1, respectively), and improved N-fertilizer timing is estimated to mitigate 413 kg CO2e ha−1 yr−1 (SOC, N2O, and CH4 flux reductions of 75, 337, 1 kg CO2e ha−1yr−1, respectively). The adoption of multiple CSA practices is estimated to have the greatest mean reduction potential of 2861 kg CO2e ha−1 yr−1 (SOC, N2O, and CH4 flux reductions of 2210, 611, 39 kg CO2e ha−1yr−1, respectively). Use of the spatially explicit subfield modeling approach based on public data provides a relatively low-cost approach for strategically targeting CSA practices to agricultural regions where adoption is most impactful.

Technical Note: A Device to Directly Measure Transpiration from Vegetation Grown in Containers

Information about evaporation and transpiration fluxes is vital for water budgets, modeling of water flows and climate, as well as for assessing the hydrological impact of land management practices. Under natural conditions, these fluxes are difficult to measure accurately, which results in large measurement inaccuracies. These inaccuracies can be reduced in controlled experiments. We present a device that is especially useful for transpiration studies conducted in large and/or heavy containers where weighing becomes too cumbersome or expensive. With our device we set a water table and control soil moisture of potted small trees by periodically replenishing soil water consumed by the tree, thereby measuring the inflow volume, which represent whole-tree transpiration. The device is made of inexpensive, easily available and durable materials and can be used for in- and outdoor experiments. Data acquisition is fast and easy. The mean measurement error of the device is 4.5% (±3.2% SD) for refill (i.e., transpiration) volumes of 1.5 L or larger. For a transpiring surface of 3 m², this amount is equal to an accuracy of 0.02 mm. Validation on field data showed that transpiration measured by the device is comparable to transpiration measured by gravimetric changes.

Effect of tillage and maize-cowpea intercrop on fractal features of particle and aggregate size distribution on a tropical sandy loam soil in southwest Nigeria

The effects of tillage and cropping pattern on soil aggregation, fractal dimensions and distribution of organic carbon fractions were studied. Treatments were notillage (NT), conventional tillage (CT), and four cropping patterns viz: sole maize, sole cowpea, maize-cowpea intercrops and control (no crop). Soil samples were analysed for particle size distribution (PSD); aggregation ratio (AR), meanweight diameter (MWD) and aggregated silt+clay (ASC). Mass fractal dimension (Dm) was obtained from PSD; while fragmentation fractal dimension (Df) was obtained from aggregate sizes. Total organic carbon (TOC), free and occluded particulate organic carbon (fPOC and oPOC), were measured. Results showed that structural stability at micro-aggregate scale measured by aggregated silt + clay (ASC) was significantly (p < 0.05) highest for NT (4.07) than CT (1.58). The CT significantly (P ≤ 0.05) reduced the larger aggregate fraction (5.66-2.00 mm). The difference in fractal dimensions was significantly higher with NT than control with CT. Lower difference between Dm and Df with CT represents higher degree of fragmentation of aggregates. Correlation showed significant positive linear relationships between Dm and sand (p < 0.05, r = 0.627) and negative relationship with silt and clay (r = -0.675). Therefore, fractal dimensions derived from aggregates sizes rather than particle size distribution reflected the impact of land management practices on fragmentation of aggregates of most tropical soils.

Effect of tillage and maize-cowpea intercrop on fractal features of particle and aggregate size distribution on a tropical sandy loam soil in southwest Nigeria

The effects of tillage and cropping pattern on soil aggregation, fractal dimensions and distribution of organic carbon fractions were studied. Treatments were no- tillage (NT), conventional tillage (CT), and four cropping patterns viz: sole maize, sole cowpea, maize-cowpea intercrops and control (no crop). Soil samples were analysed for particle size distribution (PSD); aggregation ratio (AR), mean- weight diameter (MWD) and aggregated silt+clay (ASC). Mass fractal dimension (Dm) was obtained from PSD; while fragmentation fractal dimension (Df) was obtained from aggregate sizes. Total organic carbon (TOC), free and occluded particulate organic carbon (fPOC and oPOC), were measured. Results showed that structural stability at micro-aggregate scale measured by aggregated silt + clay (ASC) was significantly (p < 0.05) highest for NT (4.07) than CT (1.58). The CT significantly (P ≤ 0.05) reduced the larger aggregate fraction (5.66-2.00 mm). The difference in fractal dimensions was significantly higher with NT than control with CT. Lower difference between Dm and Df with CT represents high- er degree of fragmentation of aggregates. Correlation showed significant positive linear relationships between Dm and sand (p < 0.05, r = 0.627) and negative rela- tionship with silt and clay (r = -0.675). Therefore, fractal dimensions derived from aggregates sizes rather than particle size distribution reflected the impact of land management practices on fragmentation of aggregates of most tropical soils.

State and trends of hillslope erosion across New South Wales, Australia

Hillslope erosion is a widespread natural hazard which often causes land and water quality degradation. Consistent and continuous erosion monitoring will help identify the impact of land management practices and improve soil condition. This paper presents an improved modeling approach for monitoring and predicting hillslope erosion on monthly basis over New South Wales (NSW), Australia by using the most recent time-series fractional vegetation cover data, regional climate projections and the Revised Universal Soil Loss Equation. The time-series estimation was used to analyze the state and trends of hillslope erosion, identifying the places and times of greatest erosion hazard. The average hillslope erosion rate for the current period (2000–2017) was estimated at 0.85 Mg ha−1 yr−1 over NSW. The areas with high erosion risk was the North Coast, Hunter and Greater Sydney regions with erosion rates of 4.04, 3.74 and 3.06 Mg ha−1 yr−1 respectively. The Western region had the lowest hillslope erosion risk (0.11 Mg ha−1 yr−1) due to its flat terrain. Hillslope erosion in NSW was generally decreasing over the past 18 years, with a reduction of 16% in the recent three years (2015–2017) compared to the previous 15-year (2000–14). However, the future hillslope erosion is predicted to increase about 7–21% in the next 60 years due to the likely increase in extreme rainfall events and decrease in groundcover. The methodology and datasets used in this study are general, thus they have the potential to be applied elsewhere.

Impact of Land Management Practices on Runoff, Soil Loss and Infiltration Under Simulated Rainfall

A laboratory study was conducted to quantify the effects of various land management practices on runoff, soil loss and infiltration under simulated rainfall conditions. A prototype rainfall simulator was designed and tested in the laboratory to simulate rainfall at 100 mm.h-1 intensity over different land management practices. The effect of five land management practices on runoff, infiltration and soil loss were evaluated for a set of rainfall intensity (100 mm.h-1), rainfall duration (15 min) and raindrop size/ pore size of the nozzle (3.5 mm). The considered management practices were intense tillage land cover, zero or no-tillage land cover, minimum tillage land cover, perennial grass system and urban environment. Perennial grasses were found to be the best management practices to minimize the surface runoff and soil loss with increase in infiltration rate. Experimental results showed that perennial vegetation produced minimum runoff (0.2 l), very small soil loss (4.99 kg.ha-1) and maximum infiltration rate (117.67 mm.h-1), whereas urban environment (concrete surface) produced maximum runoff (3.7 l), minimum infiltration rate (0.1 mm.h-1) and minimum sediment loss (0.08 kg.ha-1).

Modelling the Impacts of Land Use Change on Stream Flow in the Kimwarer Catchment Using SWAT

The Kimwarer River basin covers 138.2 km2. It has experienced ecosystem degradation due to extensive farming that has impacted on water yield. This study was undertaken to assess the impacts of land use changes on river flow using SWAT, a mathematical model that has the potential to predict the impact of land management practices on water at catchment scale. Current and historic flow data were collected for model calibration and validation. The model was then used to simulate stream flow for different land use and land cover scenarios by varying the extend of forest cover and agriculture. The model was successfully calibrated and validated for stream flow, and proved capable of predicting flow with R2 and NSE values of 0.79 and 0.31 respectively. During validation, the model predicted flows with R2 and NSE values of 0.70 and 0.50 respectively. For scenario analysis to determine the effect of land use change on stream flow, it was observed that runoff decreased with increase in forest cover, while base-flow increased. Introduction of terraces as a management operation on agricultural land reduced runoff by 46%. It is evident from the study that the current trend of land use change affects stream flow.

Impact of Land Management Practices on Runoff, Soil Loss and Infiltration Under Simulated Rainfall

A laboratory study was conducted to quantify the effects of various land management practices on runoff, soil loss and infiltration under simulated rainfall conditions. A prototype rainfall simulator was designed and tested in the laboratory to simulate rainfall at 100 mm.h-1 intensity over different land management practices. The effect of five land management practices on runoff, infiltration and soil loss were evaluated for a set of rainfall intensity (100 mm.h-1), rainfall duration (15 min) and raindrop size/ pore size of the nozzle (3.5 mm). The considered management practices were intense tillage land cover, zero or no-tillage land cover, minimum tillage land cover, perennial grass system and urban environment. Perennial grasses were found to be the best management practices to minimize the surface runoff and soil loss with increase in infiltration rate. Experimental results showed that perennial vegetation produced minimum runoff (0.2 l), very small soil loss (4.99 kg.ha-1) and maximum infiltration rate (117.67 mm.h-1), whereas urban environment (concrete surface) produced maximum runoff (3.7 l), minimum infiltration rate (0.1 mm.h-1) and minimum sediment loss (0.08 kg.ha-1).

Modelling Transport of Nitrogen Compounds in Geita Wetland along Mtakuja River

The impacts of excessive nitrogen loading to streams in a watershed occur in the receiving waters such as rivers at the outlet of the watershed. To quantify the impacts of land use and management practices on the nitrogen loading at the watershed outlet, simulation models are needed that can both predict the nitrogen loading at the edge of individual fields and predict the fate of nitrogen as it moves through the river network to the watershed outlet. This paper presents the results of a model analysis for describing the processes governing transformations and transport of nitrogen compounds (NO3-N and NH4-N) through Mtakuja River in the Geita wetland. The model was made in Soil and Water Assessment Tool (SWAT), a watershed model developed to assess the impact of land management practices on water, sediment and agricultural chemical yields with varying soils, land use and management conditions. Two monitoring stations namely MTSP1 and MTSP2 were established along Mtakuja River. A set of SWAT model inputs representative of the water conditions was collected from the established monitoring stations. The model was calibrated and validated for the prediction of flow and nitrogen compounds (NO3-N and NH4-N) transport, against a set of measured mean monthly monitoring data. Sensitive model parameters were adjusted within their feasible ranges during calibration to minimize model prediction errors. At the gauging station MTSP2, the calibration results showed that the model predicted mean monthly flow within 18% of the measured mean monthly flow with the r2 coefficient and Nash-Sutcliffe (NSE) were 0.84 and 0.82, respectively. At the water quality monitoring station MTSP2, the calibration results showed the model predicted nitrogen compounds (NO3-N and NH4-N) loadings within 21% and 23% of their respective measured mean monthly loadings. The mean monthly comparisons of r 2 values for nitrogen compounds ranged from 0.77 to 0.81 while the Nash-Sutcliffe Efficiency (NSE) values were between 0.72 and 0.73. The model results and field measurements demonstrated that about 70% of the annual nitrogen compounds loadings which would otherwise reach Lake Victoria are retained in the wetland. The Mtakuja river model can therefore be used for prediction of nitrogen compounds (NO3-N and NH4-N) transformation processes in the Geita wetland.

Parameter estimation of SWAT and quantification of consequent confidence bands of model simulations

Soil and Water Assessment Tool (SWAT) is a river basin scale model widely used to study the impact of land management practices in large, complex watersheds. Even though model output uncertainties are generally recognized to affect watershed management decisions, those uncertainties are largely ignored in model applications. The uncertainties of SWAT simulations are quantified using various methods, but simultaneous attempt to calibrate a model so as to reduce the uncertainty are seldom done. This study aims to use an uncertainty reduction procedure that helps calibrate the SWAT model. The shuffled complex evolutionary metropolis algorithm for uncertainty analysis is employed for this purpose, and is demonstrated using the data from the St. Joseph River basin, USA. The values of the performance indices, the r2 and the Nash–Sutcliffe efficiency (NSE) for the simulations during calibration period was found to be 0.81 (same for r2 and NSE) and 0.79 for validation period indicating a good simulation by the model. The results also indicate that the algorithm helps reduce the uncertainty (percentage of coverage = 62% and average width = 19.2 m3/s), and also identifies the plausible range of parameters that simulate the processes with less uncertainty. The confidence bands of simulations are obtained that can be employed in making uncertainty-based decisions on watershed management practices.

Exploring the Impact of Overgrazing on Soil Erosion and Land Degradation in a Dry Mediterranean Agro-Forest Landscape (Crete, Greece)

The impact of land management practices on soil erosion and land degradation was assessed during three consecutive years (December 2008–November 2011) in a rural area sensitive to desertification (Crete, Greece). The area is characterized by soils formed on flysch parent material, dry sub-humid climate with water deficit concentrated in summer, and frequent drought episodes. Precipitation, water runoff, sediment loss, soil moisture, air and soil temperature, and plant cover were recorded at two sites experiencing overgrazing and sustainable grazing. Sustainable grazing was associated with lower water runoff, reduced sediment loss and lower soil temperature than overgrazing. Plant cover protected soils from water erosion more effectively in the “sustainable grazing” plot than in the “overgrazing” plot. The study identifies overgrazing as a driver of land degradation in southern Europe and points out the contribution of sustainable management of pastoral landscapes in the mitigation of desertification risk.

Impact of land management practices on crop production and household income of farmers in Oyo State, Nigeria

Impact of land management practices on crop production and household income of farmers in Oyo State, Nigeria

Assessment of climate and land use change impacts with SWAT

The Soil and Water Assessment Tool (SWAT) is a deterministic continuous-time semi-distributed hydrological model for application at the river basin scale. The model was developed by the USDA Agricultural Research Service in the early 1990s based on Simulator for Water Resources in Rural Basins (SWRRB) and including routing procedures from Routing Outputs To Outlet (ROTO) tool (Arnold et al. 1995, 1998). SWAT is initialized by spatially distributed data on topography, land use/land cover, soils, land management and climate. The spatial disaggregation scheme includes subbasins delineated based on topography, which are further subdivided into nonspatial hydrological response units using the principle of similarity. Several versions of GIS interface were developed for SWAT enabling the model parametrization and initialization from maps and related data, starting from a GRASS GIS version (Srinivasan and Arnold 1994) to the current ArcGIS 10.1/10.2.2 interface version. From the early 1990s, the SWAT model has undergone continuous testing, review, modifications and enhancement of many modules (Arnold et al. 1998; Neitsch et al. 2004, 2005; Gassman et al. 2007). The model is process-based and simulates water flows in soil and groundwater, crop/vegetation growth, nutrient cycling, erosion, pesticides, bacteria, lateral flows of water, sediments and nutrients, as well as environmental impact of land management practices on the main model outputs. A number of agricultural practices can be simulated, such as fertilizer and manure application, tillage, irrigation, subsurface drainage, buffer strips, as well as wetlands and ponds. The river routing component in SWAT routes the simulated water flows, sediments, nutrients, pesticides and bacteria along the river network in a basin. The reservoir module accounts for transformation of water fluxes, nutrients and sediments when passing the reservoir. The main model outputs include water, sediments, nutrients, pesticides and bacteria yields that can be provided for every subbasin outlet at a daily time step. The SWAT tool belongs to a family of models, with several versions that are currently being distributed (see more information in Douglas-Mankin et al. 2010 and on the SWAT website: http://swat.tamu.edu/). Besides, several currently applied models were developed based on SWAT and still have many similar or identical components. The main reasons for this development were to adapt the model to other data formats outside USA, to modify/enhance some specific components, and to add new components. Among them are the following: the SWIM model (Soil and Water Integrated Model) (Krysanova et al. 1998, 2000), aiming mainly at climate and land use change impact assessment at a large regional scale; the ESWAT model (van Griensven and Bauwens 2005) with an adjustment for the hourly time step; the ALMANAC model (Kiniry et al. 2008) focused on simulation of crops, perennial grasses and forest ecosystems including successional changes; the coupled surface and groundwater model SWAT–MODFLOW (Kim et al. 2008); and the APEX model (Gassman et al. 2010) developed for assessment of various agricultural management strategies and accounting for economical costs. V. Krysanova (&) Potsdam Institute for Climate Impact Research (PIK), PO Box 601203, Telegrafenberg, 14412 Potsdam, Germany e-mail: krysanova@pik-potsdam.de