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Effect assessment of land cover pattern on soil and water loss on red soil plots |
TANG Chongjun1, LIU Yu2,3, XU Aizhen1, GUO Liping1,4 |
1. Jiangxi Provincial Institute of Soil and Water Conservation, Key Laboratory of Soil Erosion and Prevention, 330029, Nanchang, China; 2. Key Laboratory of Ecosystem Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 100101, Beijing, China; 3. University of Chinese Academy of Sciences, 100049, Beijing, China; 4. Research Center of Water Resources and Ecological Environment of Poyang Lake, the Ministry of Water Resources of the People's Republic of China, 330029, Nanchang, China |
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Abstract [Background] Evaluating the potential of spatial pattern of land cover on preventing soil and water loss by field monitoring is time-consuming and financially expensive. Pattern indices designed with concern of soil erosion, sediment flow and hydrological processes provide time-saving and low-cost solution. However, most of these indices are developed, tested and applied in arid and semiarid environment. Their suitability in areas covered by red soil and with greater precipitation is untested.[Methods] In this paper, the Directional Leakiness Index (DLI) and Flow-length-weighted Directional Leakiness Index (FDLI) were applied to assess the soil and water retention capacity of land cover patterns at plot scale in humid climate and with red soil. Runoff generation and sediment yield of ten 20m-by-5m plots (coded as PG1-PG10) with different land cover patterns were compared and used to test suitability of these two indices.[Results] The plots with grass bands paralleling to elevation contours have low DLI and FDLI compared with those without grass strips. The plots can be ranked differently according to runoff depth and sediment yield. According to runoff depth, the ten plots are ranked as PG4 > PG10 > PG9 > PG8 > PG1 > PG3 > PG6 > PG7 > PG2 > PG5. When ranked based on sediment yield, these plots are ranked as PG9 > PG10 > PG8 > PG4 > 2 > PG3 > PG1 > PG6 > PG7 > PG5. It is showed that DLI is logarithmically related with sediment production and runoff depth. Significant logarithmic regressions also are derived between FDLI and sediment yield, and between FDLI and runoff depth. The goodness of regression equations between land cover pattern indices and sediment yields (R2=0.771 6 for DLI, R2=0.890 7 for FDLI) is better than that of regression equations between land cover pattern indices and runoff depths (R2=0.598 7 for DLI, R2=0.684 7 for FDLI). For plots with a strong soil and water retention capacity, and accordingly lower DLI and FDLI, the responses of sediment yield and runoff generation to rainfall depth can be described by linear or exponential equations. However, for plots that have low capacity to retain soil and water, i.e., with great DLI and FDLI, the goodness of both linear and exponential regression equations between runoff depth and rainfall depths and between sediment yield and rainfall depth are close to zero, which argues that both linear equation and exponential equation are unsuitable for describing the response of runoff generation and sediment yield to rainfall depth.[Conculsions] These results confirmed the suitability of DLI and FDLI for ranking a set of land cover patterns according to capacity in soil and water loss prevention, and the importance of vegetation cover pattern for soil and water conservation in this humid and red soil covered region. It is also emphasized that reclassifying land cover into sources and sinks according to their actual effect on sediment yield and runoff generation is necessary, which can evidently promoted the effectiveness of the indices used to coupling the land cover pattern with soil loss and runoff generation.
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Received: 02 February 2019
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