Spatial variation and interaction of runoff generation and erosion within a semi-arid, complex terrain catchment: a hierarchical approach

2013 ◽  
Vol 13 (10) ◽  
pp. 1770-1783 ◽  
Author(s):  
Tongxin Zhu
Keyword(s):  
Spatial Variation ◽  
Complex Terrain ◽  
Hierarchical Approach ◽  
Runoff Generation ◽  
Semi Arid

Runoff generation from successive simulated rainfalls on a rocky, semi-arid, Mediterranean hillslope

2003 ◽  
Vol 17 (2) ◽  
pp. 279-296 ◽  
Author(s):  
J. Lange ◽  
N. Greenbaum ◽  
S. Husary ◽  
M. Ghanem ◽  
C. Leibundgut ◽  
...  
Keyword(s):  
Runoff Generation ◽  
Semi Arid

scholarly journals Evaluation of coupled ANN-GA model to prioritize flood source areas in ungauged watersheds

2020 ◽  
Vol 51 (3) ◽  
pp. 423-442
Author(s):  
Naser Dehghanian ◽  
S. Saeid Mousavi Nadoushani ◽  
Bahram Saghafian ◽  
Morteza Rayati Damavandi
Keyword(s):  
Flood Control ◽  
Mean Squared Error ◽  
Absolute Error ◽  
Ann Model ◽  
Runoff Generation ◽  
Source Areas ◽  
Walnut Gulch ◽  
Artificial Neural Network Ann ◽  
Semi Arid ◽  
Flood Source

Abstract An important step in flood control planning is identification of flood source areas (FSAs). This study presents a methodology for identifying FSAs. Unit flood response (UFR) approach has been proposed to quantify FSAs at subwatershed and/or cell scale. In this study, a distributed ModClark model linked with Muskingum flow routing was used for hydrological simulations. Furthermore, a fuzzy hybrid clustering method was adopted to identify hydrological homogenous regions (HHRs) resulting in clusters involving the most effective variables in runoff generation as selected through factor analysis (FA). The selected variables along with 50-year rainfall were entered into an artificial neural network (ANN) model optimized via genetic algorithm (GA) to predict flood index (FI) at cell scale. The case studies were two semi-arid watersheds, Tangrah in northeastern Iran and Walnut Gulch Experimental Watershed in Arizona. The results revealed that the predicted values of FI via ANN-GA were slightly different from those derived via UFR in terms of mean squared error (MSE), mean absolute error (MAE), and relative error (RE). Also, the prioritized FSAs via ANN-GA were almost similar to those of UFR. The proposed methodology may be applicable in prioritization of HHRs with respect to flood generation in ungauged semi-arid watersheds.

Processes of runoff generation operating during the spring and autumn seasons in a permafrost catchment on semi-arid plateaus

2017 ◽  
Vol 550 ◽  
pp. 307-317 ◽  
Author(s):  
Wang Genxu ◽  
Mao Tianxu ◽  
Chang Juan ◽  
Song Chunlin ◽  
Huang Kewei
Keyword(s):  
Runoff Generation ◽  
Semi Arid

scholarly journals A simplified approach for estimating soil carbon and nitrogen stocks in semi-arid complex terrain

Geoderma ◽  
2011 ◽  
Vol 165 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Melvin L. Kunkel ◽  
Alejandro N. Flores ◽  
Toni J. Smith ◽  
James P. McNamara ◽  
Shawn G. Benner
Keyword(s):  
Soil Carbon ◽  
Complex Terrain ◽  
Simplified Approach ◽  
Carbon And Nitrogen ◽  
Soil Carbon And Nitrogen ◽  
Semi Arid ◽  
Carbon And Nitrogen Stocks

scholarly journals Saturation sampling for spatial variation in multiple air pollutants across an inversion-prone metropolitan area of complex terrain

2014 ◽  
Vol 13 (1) ◽  
Author(s):  
Jessie LC Shmool ◽  
Drew R Michanowicz ◽  
Leah Cambal ◽  
Brett Tunno ◽  
Jeffery Howell ◽  
...  
Keyword(s):  
Spatial Variation ◽  
Metropolitan Area ◽  
Complex Terrain ◽  
Air Pollutants

Spatial Dynamics of Soil Moisture in a Complex Terrain in the Semi-Arid Loess Plateau Region, China1

2008 ◽  
Vol 44 (5) ◽  
pp. 1121-1131 ◽  
Author(s):  
Huaxing Bi ◽  
Jianjun Zhang ◽  
Jinzhao Zhu ◽  
Liangliang Lin ◽  
Chaoying Guo ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Loess Plateau ◽  
Complex Terrain ◽  
Spatial Dynamics ◽  
Plateau Region ◽  
Semi Arid

scholarly journals Controls on the temporal and spatial variability of soil moisture in a mountainous landscape: the signatures of snow and complex terrain

2008 ◽  
Vol 5 (4) ◽  
pp. 1927-1966 ◽  
Author(s):  
C. J. Williams ◽  
J. P. McNamara ◽  
D. G. Chandler
Keyword(s):  
Spatial Distribution ◽  
Soil Moisture ◽  
Spatial Variability ◽  
Complex Terrain ◽  
Soil Depth ◽  
Snow Accumulation ◽  
Slope Aspect ◽  
Spatial Correlations ◽  
Static Properties ◽  
Semi Arid

Abstract. The controls on the spatial distribution of soil moisture include static and dynamic variables. The superposition of static and dynamic controls can lead to different soil moisture patterns for a given catchment during wetting, draining, and drying periods. These relationships can be further complicated in snow-dominated mountain regions where soil water input by precipitation is largely dictated by the spatial variability of snow accumulation and melt. In this study, we assess controls on spatial and temporal soil moisture variability in a small (0.02 km2), snow-dominated, semi-arid catchment by evaluating spatial correlations between soil moisture and site characteristics through different hydrologic seasons. We assess the relative importance of snow with respect to other catchment properties on the spatial variability of soil moisture and track the temporal persistence of those controls. Spatial distribution of snow, distance from divide, soil texture, and soil depth exerted significant control on the spatial variability of moisture content throughout most of the hydrologic year. These relationships were strongest during the wettest period and degraded during the dry period. As the catchment cycled through wet and dry periods, the relative spatial variability of soil moisture tended to remain unchanged. We suggest that the static properties in complex terrain (slope, aspect, soils) impose first order controls on the spatial variability of snow and consequent soil moisture, and that the interaction of dynamic (timing of water input) and static properties propagate that relative constant spatial variability through the hydrologic year. The results demonstrate snow exerts significant influence on how water is retained within mid-elevation semi-arid catchments throughout the year and infer that reductions in annual snowpacks associated with changing climate regimes may strongly influence spatial and temporal soil moisture patterns and catchment physical and biological processes.

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