The effects of land use change and precipitation change on direct runoff in Wei River watershed, China

2014 ◽  
Vol 71 (2) ◽  
pp. 289-295 ◽  
Author(s):  
Leihua Dong ◽  
Lihua Xiong ◽  
Upmanu Lall ◽  
Jiwu Wang
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Use Change ◽  
Agricultural Land ◽  
Curve Number ◽  
Runoff Generation ◽  
Direct Runoff ◽  
Land Use Types ◽  
Service Curve ◽  
Effects Of Land Use

The principles and degrees to which land use change and climate change affect direct runoff generation are distinctive. In this paper, based on the MODIS data of land use in 1992 and 2003, the impacts of land use and climate change are explored using the Soil Conservation Service Curve Number (SCS-CN) method under two defined scenarios. In the first scenario, the precipitation is assumed to be constant, and thus the consequence of land use change could be evaluated. In the second scenario, the condition of land use is assumed to be constant, so the influence only induced by climate change could be assessed. Combining the conclusions of two scenarios, the effects of land use and climate change on direct runoff volume can be separated. At last, it is concluded: for the study basin, the land use types which have the greatest effect on direct runoff generation are agricultural land and water body. For the big sub basins, the effect of land use change is generally larger than that of climate change; for middle and small sub basins, most of them suffer more from land use change than from climate change.

scholarly journals Variability of the Initial Abstraction Ratio in an Urban and an Agroforested Catchment

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 415 ◽  
Author(s):  
Adam Krajewski ◽  
Anna E. Sikorska-Senoner ◽  
Agnieszka Hejduk ◽  
Leszek Hejduk
Keyword(s):  
Land Use ◽  
Curve Number ◽  
Threshold Value ◽  
Storm Events ◽  
Direct Runoff ◽  
Initial Abstraction ◽  
Land Use Types ◽  
Rainfall Depth ◽  
Storm Rainfall ◽  
Service Curve

The Curve Number method is one of the most commonly applied methods to describe the relationship between the direct runoff and storm rainfall depth. Due to its popularity and simplicity, it has been studied extensively. Less attention has been given to the dimensionless initial abstraction ratio, which is crucial for an accurate direct runoff estimation with the Curve Number. This ratio is most often assumed to be equal to 0.20, which was originally proposed by the method’s developers. In this work, storm events recorded in the years 2009–2017 in two small Polish catchments of different land use types (urban and agroforested) were analyzed for variability in the initial abstraction ratio across events, seasons, and land use type. Our results showed that: (i) estimated initial abstraction ratios varied between storm events and seasons, and were most often lower than the original value of 0.20; (ii) for large events, the initial abstraction ratio in the catchment approaches a constant value after the rainfall depth exceeds a certain threshold value. Thus, when using the Soil Conservation Service-Curve Number (SCS-CN) method, the initial abstraction ratio should be locally verified, and the conditions for the application of the suggested value of 0.20 should be established.

Agriculture in the Boreal Forest: Understanding the Impact of Land Use Change on Soil Carbon for Developing Sustainable Community Food Systems 

2021 ◽  
Author(s):  
David Bysouth ◽  
Merritt Turetsky ◽  
Andrew Spring
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Use Change ◽  
Boreal Forest ◽  
Soil Carbon ◽  
Food Systems ◽  
Agricultural Land ◽  
Carbon Stocks ◽  
Soil Carbon Stocks ◽  
Carbon Losses

<p>Climate change is causing rapid warming at northern high latitudes and disproportionately affecting ecosystem services that northern communities rely upon. In Canada’s Northwest Territories (NWT), climate change is impacting the access and availability of traditional foods that are critical for community health and well-being. With climate change potentially expanding the envelope of suitable agricultural land northward, many communities in the NWT are evaluating including agriculture in their food systems. However, the conversion of boreal forest to agriculture may degrade the carbon rich soils that characterize the region, resulting in large carbon losses to the atmosphere and the depletion of existing ecosystem services associated with the accumulation of soil organic matter. Here, we first summarize the results of 35 publications that address land use change from boreal forest to agriculture, with the goal of understanding the magnitude and drivers of carbon stock changes with time-since-land use change. Results from the literature synthesis show that conversion of boreal forest to agriculture can result in up to ~57% of existing soil carbon stocks being lost 30 years after land use change occurs. In addition, a three-way interaction with soil carbon, pH and time-since-land use change is observed where soils become more basic with increasing time-since-land use change, coinciding with declines in soil carbon stocks. This relationship is important when looking at the types of crops communities are interested in growing and the type of agriculture associated with cultivating these crops. Partnered communities have identified crops such as berry bushes, root vegetables, potatoes and corn as crops they are interested in growing. As berry bushes grow in acidic conditions and the other mentioned crops grow in more neutral conditions, site selection and management practices associated with growing these crops in appropriate pH environments will be important for managing soil carbon in new agricultural systems in the NWT. Secondly, we also present community scale soil data assessing variation in soil carbon stocks in relation to potential soil fertility metrics targeted to community identified crops of interest for two communities in the NWT.  We collected 192 soil cores from two communities to determine carbon stocks along gradients of potential agriculture suitability. Our field soil carbon measurements in collaboration with the partnered NWT communities show that land use conversions associated with agricultural development could translate to carbon losses ranging from 2.7-11.4 kg C/m<sup>2</sup> depending on the type of soil, agricultural suitability class, and type of land use change associated with cultivation. These results highlight the importance of managing soil carbon in northern agricultural systems and can be used to emphasize the need for new community scale data relating to agricultural land use change in boreal soils. Through the collection of this data, we hope to provide northern communities with a more robust, community scale product that will allow them to make informed land use decisions relating to the cultivation of crops and the minimization of soil carbon losses while maintaining the culturally important traditional food system.</p>

scholarly journals Assessment of impacts of agricultural and climate change scenarios on watershed water quantity and quality, and crop production

2016 ◽  
Author(s):  
Awoke D. Teshager ◽  
Philip W. Gassman ◽  
Justin T. Schoof ◽  
Silvia Secchi
Keyword(s):  
Climate Change ◽  
Water Quality ◽  
Land Use ◽  
Land Use Change ◽  
21St Century ◽  
Agricultural Land ◽  
Agricultural Landscapes ◽  
Water Quantity ◽  
Agricultural Land Use ◽  
Water Quantity And Quality

Abstract. Modeling impacts of agricultural scenarios and climate change on surface water quantity and quality provides useful information for planning effective water, environmental, and land use policies. Despite the significant impacts of agriculture on water quantity and quality, limited literature exists that describes the combined impacts of agricultural land use change and climate change on future bioenergy crop yields and watershed hydrology. In this study, the Soil and Water Assessment Tool (SWAT) eco-hydrological model was used to model the combined impacts of five agricultural land use change scenarios and three downscaled climate pathways (representative concentration pathways, RCPs) that were created from an ensemble of eight atmosphere-ocean general circulation models (AOGCMs). These scenarios were implemented in a well calibrated SWAT model for the Raccoon River watershed (RRW) located in western Iowa. The scenarios were executed for the historical baseline, early-century, mid-century, and late-century periods. The results indicate that historical and more corn intensive agricultural scenarios with higher CO2 emissions consistently result in more water in the streams and greater water quality problems, especially late in the 21st century. Planting more switchgrass, on the other hand, results in less water in the streams and water quality improvements relative to the baseline. For all given agricultural landscapes simulated, all flow, sediment and nutrient outputs increase from early-to-late century periods for the RCP4.5 and RCP8.5 climate scenarios. We also find that corn and switchgrass yields are negatively impacted under RCP4.5 and RCP8.5 scenarios in the mid and late 21st century.

Spatiotemporal patterns of global land use change: Understanding processes and drivers

2021 ◽  
Author(s):  
Karina Winkler ◽  
Richard Fuchs ◽  
Mark Rounsevell ◽  
Martin Herold
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Use Change ◽  
Land Surface ◽  
Agricultural Land ◽  
Spatiotemporal Patterns ◽  
Sustainable Land Use ◽  
Environmental Drivers ◽  
Climate Mitigation ◽  
Global Land

<p>Land use change is a major contributor to greenhouse gas emissions and biodiversity loss and, hence, a key topic for current sustainability debates and climate change mitigation. To understand its impacts, accurate data of global land use change and an assessment of its extent, dynamics, causes and interrelations are crucial. However, although numerous observational data is publicly available (e.g. from remote sensing), the processes and drivers of land use change are not yet fully understood. In particular, current global-scale land change assessments still lack either temporal consistency, spatial explicitness or thematic detail. <br>Here, we analyse the patterns of global land use change and its underlying drivers based on our novel high-resolution (~1x1 km) dataset of global land use/cover (LULC) change from 1960-2019, HILDA+ (Historic Land Dynamics Assessment+). The data harmonises multiple Earth Observation products and FAO land use statistics. It covers all transitions between six major LULC categories (urban areas, cropland, pasture/rangeland, forest, unmanaged grass-/shrubland and no/sparse vegetation).<br>On this basis, we show (1) a classification of global LULC transitions into major processes of land use change, (2) a quantification of their spatiotemporal patterns and (3) an identification of their major socioeconomic and environmental drivers across the globe. By using temporal cross-correlation, we study the influence of selected drivers on processes such as agricultural land abandonment, deforestation, forest degradation or urbanisation.<br>With this, we are able to map the patterns and drivers of global land use change at unprecedented resolution and compare them for different world regions. Giving new data-driven and quantitative insights into a largely untouched field, we identify tele-coupled globalisation patterns and climate change as important influencing factors for land use dynamics. Learning from the recent past, understanding how socio-economic and environmental factors affect the way humans use the land surface is essential for estimating future impacts of land use change and implementing measures of climate mitigation and sustainable land use policies.</p>

scholarly journals Surface Runoff Responses to Suburban Growth: An Integration of Remote Sensing, GIS, and Curve Number

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 452
Author(s):  
Khurshid Jahan ◽  
Soni M. Pradhanang ◽  
Md Abul Ehsan Bhuiyan
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Use Change ◽  
Surface Runoff ◽  
Agricultural Land ◽  
Curve Number ◽  
Integrated Approach ◽  
Substantial Impact ◽  
Sensing Applications ◽  
Scs Cn

Suburban growth and its impacts on surface runoff were investigated using the soil conservation service curve number (SCS-CN) model, compared with the integrated advanced remote sensing and geographic information system (GIS)-based integrated approach, over South Kingston, Rhode Island, USA. This study analyzed and employed the supervised classification method on four Landsat images from 1994, 2004, 2014, and 2020 to detect land-use pattern changes through remote sensing applications. Results showed that 68.6% urban land expansion was reported from 1994 to 2020 in this suburban area. After land-use change detection, a GIS-based SCS-CN model was developed to examine suburban growth and surface runoff estimation. The developed model demonstrated the spatial distribution of runoff for each of the studied years. The results showed an increasing spatial pattern of 2% to 10% of runoff from 1994 to 2020. The correlation between runoff co-efficient and rainfall indicated the significant impact of suburban growth in surface runoff over the last 36 years in South Kingstown, RI, USA, showing a slight change of forest (8.2% area of the total area) and agricultural land (4.8% area of the total area). Suburban growth began after 2000, and within 16 years this land-use change started to show its substantial impact on surface runoff. We concluded that the proposed integrated approach could classify land-use and land cover information to understand suburban growth and its potential impact on the area.

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