Estimation of surface runoff and water-covered area during filling of surface microrelief depressions

Abstract

During the _lling of surface microrelief depressions the precipitation excess "precipitation minus in_ltration and interception# is divided between surface storage and runo}\ i[e[ runo} starts before the surface depressions are _lled[ Information on the division of precipitation excess is needed for modelling surface runo} during the _lling of surface depressions[ Furthermore\ information on the surface of the area covered with water is needed for calculating in_ltration of water stored in soil surface depressions[ Thirty!two soil surface microreliefs were determined in Danish erosion study plots[ The slope was c[ 09) for all plots[ Data were treated initially by removing the slope\ after which 19 {arti_cial| slopes "0Ð19)# were introduced producing 539 new data sets[ Runo} during _lling of the microrelief storage was calculated for each of the 539 data sets using a model developed for calculating surface storage and runo} from grid elevation measurements[ Runo} started immedi! ately after the _rst addition of water for all data sets[ On a _eld scale\ however\ runo} has to travel some distance as overland~ow and storage in smaller and larger depressions below the runo} initiation point must be taken into consideration[ The runo} increases by intermittent steps[ Whenever a depression starts to over~ow to the border of the plot\ the runo} jumps accordingly[ In spite of the jumps\ the distribution between surface storage and runo} was closely related to the quotient between precipitation excess and depression storage capacity[ Surface area covered with water was exponentially related to the amount of water stored in surface depressions[ Models for calculating surface storage and runo} from grid elevation measurements are cumbersome and require time!consuming measurements of the soil surface microrelief[ Therefore\ estimation from roughness indices requiring fewer measurements is desirable[ New improved equations for such estimations are suggested[

Potential of low cost close‐range photogrammetry system in soil microtopography quantification

“…The depressions area percentage (DA%) increased with increasing surface roughness. This is in agreement with other studies (Onsted et al, 1984;Hansen, 2000). It is worth mentioning here that Jester and Klik (2005) reported decreasing depression numbers under high roughness conditions, which can be attributed mainly to experimental plot preparation and cannot be generalized to natural conditions.…”

Dynamic puddle delineation and modeling of puddle-to-puddle filling-spilling-merging-splitting overland flow processes

“…Increasing soil roughness tends to decrease surface runoff [ Kamphorst et al ., ], and the resulting slower overland flow velocity in turn reduces soil erosion and sediment transport [ Cogo et al ., ]. Due to the control of microtopography, surface runoff may exhibit a stepwise, intermittent increasing pattern with respect to time [ Hansen , ; Chu , ], which can be attributed to the dynamic puddle‐to‐puddle (P2P) filling, spilling, and merging processes and the related discontinuous, threshold‐driven overland flow [ Chu , ].…”

On depressional storages: The effect of DEM spatial resolution

“…However, since obtaining such data is time-consuming and cost intensive, they introduced a few site-specific surrogate variables such as Random Roughness (RR), Slope steepness and/or Mean Upslope Depression (MUD) to capture and/or predict variability of surface depressional storages (Onstad, 1984;Zobeck and Onstad, 1987;Mwendera and Feyen, 1992;Hansen et al, 1999;Hansen, 2000;Kamphorst and Duval, 2001;Planchon and Darboux, 2001). Firstly, it should be acknowledged that quantification of these substitute variables such as RR and MUD 'a priori' demands digital elevation data.…”