1. Кnun=(Lmax-Lmin)/Lmed (1)
Risk Assessment Of Non-Uniformity In Irrigation And Fertilization Under Furrow Irrigation
Zornitsa Popova
N.Poushkarov Institute of Soil Science 7,Shosse Bankya Str. Sofia 1080 Bulgaria Tel: Fax: ,
This paper evaluates the influence of nonuniformity of irrigation water/nitrogen fertiliser distribution on yield, water and nitrogen losses in a maize furrow set in the presence of year-to-year change of irrigation depth.
MATERIALS AND METHODS
Six maize vegetation seasons with contrastive probability of exceedence of irrigation depth PI are considered. Application depths are distributed over a furrow plot according to six scenarios of irrigation uniformity corresponding to Christiansen coefficient (Cu, %) range 53<Cu<90%. Spatial mathematical description of intake depth along the non-homogeneous furrows is made by FURMOD model. Stream advance L, when arranged in descending order, is approximated by a straight line (fig.1) with a coefficient of non-uniformity Knun :
Кnun=(Lmax-Lmin)/Lmed (1)
where Lmax, Lmin и Lmed are the wetted lengths of the least (No5), most (No1) and median (No3) permeable furrow from stream advance approximated line (fig.1).
Fig 2. Inter-row distribution of N-rate.
Fig 1. Relative distance of advance and intake depth in high , median and low intake furrows .
The duration of irrigation is defined as the relative extension of application time I, which represents the additional irrigation time tad after the irrigation stream has reached the furrow tail in the “median” furrow tl:
I= tad / tl (2)
Nitrogen fertilisation rate (200 kg N/ha) is applied over the furrow plot according to two scenarios: one of ideal N-split and distribution uniformity (coefficient of N variation Cv=0 %) and another practically oriented one with certain (Cv=30 %) inter-row nonuniformity of distribution as illustrated in fig.2.

2. RESULTS AND DISCUSSIONS
Distribution of relative intake depth mi over the furrow set depends only upon the parameters of longitudinal (I, eq.2) and lateral (Knun, eq.1) nonuniformity. Spatial representation of mi distribution for some nonuniformity scenarios is given in fig.3.
Figure 3. Intake depth in relative terms mi along median (No3), high intake (No1), low intake (No5) furrow for different scenarios of nonuniformity of irrigation water distribution: a) I=0 (eq.2), Кnun=0,5 (eq.1), Cu=69% ; b) I=0, Кnun=1, Cu=53% ; c) I=0.8, Кnun=0,5, Cu=83% ; d) I=0.8, Кnun=1, Cu=67%.
Description of intake depth along the non-homogeneous furrows is made by FURMOD model which calculates in relative terms water distribution for a wide range of conditions in irrigation practice, as application time and depth, soil infiltration parameters, water deficit in the root zone, “downfield” and “inter-row” non-uniformity of water distribution.

3. Yield losses due to nonuniformity and climate variation Chromic Luvisol, Sofia region
Yield losses in % of the yield, which should have been harvested with uniform irrigation/fertilisation, depend significantly on distribution nonuniformity and wetness of the irrigation season (PI). In case of nonuniform irrigation and split uniform N fertilisation, they are negligible after moderately wet irrigation periods (PI>60 %) and augment up to 14.2 % in dry seasons (PI=3%‑11 %) (fig.4 and fig.5-a).
Figure 4. Yield distribution along median (No3), high intake (No1), low intake (No5) furrow under “low uniformity” furrow irrigation scenario (I=0, Knun=1,Cu=53%) and split uniform fertilisation (Cv=0) in case of: a) moderate irrigation season and b) dry irrigation season.
Combination of disuniform fertilisation (Cv=30 %) and irrigation (Cu=53 %) with dry irrigation season leads to maximum losses (Fig.5-b) due to the reduction of productivity in the lower part of furrows (Fig.6-a).
Figure.6. Consequences of non-uniform irrigation (I=0, Kнер=1,Cu=53%) and fertilisation (Cv=30%) scenarios for maize plot in dry irrigation season (РI=3-11%) for : a) Yield distribution

4. Yield losses do not depend practically upon the variability of the climate when applying 50% more irrigation water (I=0.8) with a sufficient stream advance uniformity (Knun<0.5). Such irrigation treatment is economically feasible if the price of the water is relatively low and/or runoff is reused.
Figure 5. Yield losses due to irrigation water nonuniformity dependent on probability of the irrigation depth PI, Chromic Luvisol, Sofia region under: a) split uniform (Cv=0 %) fertiliser application b) single spring nonuniform (Cv=30 %) fertiliser broadcasting.

5. Pollution of groundwater due to nonuniformity and climate variation Chromic Luvisol, Sofia region
Figure.6. b) N-leach totals for “Oct-Apr” period due to nonuniform furrow irrigation and fertilisation in dry maize irrigation season (РI=3-11%) .
Mean N-leach is harmless (between 1.3 and 3.9 kg N/ha) in medium and dry irrigation seasons under “low uniform” irrigation (I=0; Knun=1; Cu=53 %) (fig.7-a). The drier is the irrigation season the higher is risk to environment due to nonuniformity in irrigation water distribution and N-broadcast.
Figure 7. Impact of nonuniform irrigation (I=0 Knun=1 Cu=53%), fertilisation and probability of irrigation depth (PI) upon mean and STDEV of: (a) drainage and N-leaching totals for May-September period; (b) residual N-NO3 in the soil.

6. Mitigation of Adverse impact of furrow irrigation on ecology
Adverse impact of furrow irrigation on productivity and environment is mitigated by improving “inter-row” nonuniformity of both stream advance (to Knun<0.5) and N-broadcast. That reduces 2-3 folds STDEV bars of drainage, N-leaching and residual N-NO3 in the soil when I=0 (fig.8).
Figure 8. Impact of irrigation treatment (I=0 Knun=0 Cu=76 %) , fertilisation uniformity and probability of irrigation depth (PI) upon mean and STDEV of: (a) drainage&N-leaching for May-September period; (b) residual soil N-NO3
Application of 50 % more irrigation water (I=0.8) is not sustainable for environment (fig.9). Mean drainage/N-losses for “May-Sept” period rise two folds i.e. about 37‑45 % of applied irrigation water and up to 10-12% of the nitrogen fertiliser is lost by deep percolation.
Figure 9. Impact of irrigation treatment ( I=0.8 Knun=0.5 Cu=83 %) , fertilisation uniformity and probability of irrigation depth (PI) upon mean and STDEV of: (a) drainage and N-leaching totals for May-September period; (b) residual soil N-NO3 .

7. CONCLUSIONS
Water distribution is quite non-uniform along the furrow length under surface irrigation. This “down field” disuniformity is usually combined with “inter-row” non-uniformity of irrigation water and nitrogen fertilizer distribution. Special variation of application depth and nitrogen (N) fertilization rate in the furrow set provokes yield, drainage and nitrogen losses. In addition to that, due to year-to-year variability of climate, regional irrigation depths range significantly (from 0 to 360 mm/season). The impact of uniformity of irrigation/fertilization under surface irrigation and climate variability on ground water pollution and yield is studied in six maize vegetation seasons with contrastive probability of exceedence of irrigation depth. Irrigation water is distributed according to six scenarios for “downfield” and “inter-row” non-uniformity. Nitrogen fertilization broadcast corresponds to two scenarios of lateral non-uniformity. CERES-maize model is applied with the different “climate-irrigation nonuniformity-fertilization nonuniformity” situations to simulate water/nitrogen cycle and crop growth on a daily basis in 30 representative points along “median”, “high intake” and ”low intake” furrows. It is established that yield/water/nitrogen losses vary over uniformity scenarios and years. Combination of non-uniform irrigation/fertilization and dry/moderate irrigation season causes losses of yield by 2‑14.5 %, irrigation water (40-45% of applied depth) and nitrogen (up to 10-12% of N-rate). Poor distribution of irrigation water and fertilizers could be managed by improving inter-row uniformity of stream advance and fertilizer broadcast.