“Determination of spatially-distributed irrigation water requirements at scheme level using soil-water balance model and GIS” Term Project – CEE 6440 – GIS in Water Resources Tuesday, November 30th 2004 Prepared by Daniel Zaccaria Graduate student Department of Irrigation Engineering Utah State University

OBJECTIVES General Develop and test a tentative methodology for mapping I.W.R for large-scale agricultural areas, under different climatic scenarios Evaluate spatial variability and time-distribution of I.W.R. along irrigation season Specific Getting a better knowledge of main factors related to irrigated agricultural systems Identifying major sources of errors and uncertainties in large-scale estimations of irrigation requirements

Long-term purposes OVERALL Carrying out preliminary studies in order to come up with a better irrigation water management plan for the study area Carry out a performance analysis of distribution networks and eventually identify re-engineering options for low-performing systems or sub-systems OVERALL Show usefulness of coupling GIS environment and models capabilities to provide irrigation managers with operational tools to support decision-making processes

Background on the study area The study area is part of a large-scale irrigated area located in Southern Italy and managed by a local Water Users’ Association. The whole WUA scheme covers an area of 142,905 Ha

The study area is served by three large-scale irrigation schemes whose physical features and operational rules are different

Cropping pattern

Resulting consequence ENVIRONMENTAL AND ECONOMIC HAZARDS Why this study area? Several problems High number of small land-holdings (average farm size 1.5 -2.5 ha) Market-oriented horticulture, which is strongly depending on irrigation Irrigation networks are operated with rotation delivery schedule Water distribution to farms is too restrictive and is not timely matching crop water requirements Resulting consequence As a result of all the above factors, during the last 10 years a large number of farmers started developing their “private water sources” and refused to take water from large-scale irrigation networks. This led to a very large number of unlicensed irrigation wells, to over-pumping from groundwater, to sea-water intrusion and salt accumulation in the soil ENVIRONMENTAL AND ECONOMIC HAZARDS

………. AND MOREOVER There is a serious water deficit in the area An alarming message is being continuously spread out: There is a serious water deficit in the area But before spreading such a message we have to be able to come up with reliable numbers from application of sound methodologies

Therefore: A good estimate of actual water demand is strongly needed at whole scheme level in order to identify: Existence and potential magnitude of water deficit Total volume of water seasonally withdrawn from groundwater Existence and magnitude of environmental hazards Re-engineering options (modernization and/or rehabilitation of irrigation systems) aiming at improving irrigation systems’ performances and efficiency of water use

Applied methodology 1st step) Identification of 3 climatic scenarios (Average, Demanding, Very-high demanding) 7 Climatic stations, monthly values for 35 years of observation (1959-1994) Areal Clim. Deficit = SUM [(ETo – Reff) x Station Weight] ETo computed on a montly basis by Hargreaves- Samani method ETo = 0.0023 Ra (Tmax – Tmin)0.5 (Ta + 17.8) Tmax and Tmin in hot-dry situation are quite different 35 annual values of Areal Climatic Deficit Probability of non-exceedance 50 %, 75 % and 90 Probabilities

Sort years and values for (Eto-P) Region (Eto-P) Sort years and values for (Eto-P)   Frequency (%) 7098.82 1978 513.90 2.78 7053.39 1993 523.74 5.56 7094.20 1983 550.35 8.33 6853.05 1987 559.81 50.00 7261.66 1975 569.66 13.89 7092.38 1968 570.84 16.67 7178.08 1991 615.23 19.45 7068.11 1988 628.83 22.22 7319.20 1971 632.61 25.00 7279.63 1994 640.35 27.78 7249.34 1986 640.45 30.56 6920.60 1962 644.01 33.34 7395.44 1985 650.04 75.01 7298.62 1977 668.03 38.89 7207.09 1967 674.10 41.67 7357.64 1990 676.95 44.45 7290.98 1981 683.77 47.23 7472.63 1961 695.21 7337.10 1992 696.93 52.78 7272.84 1965 714.25 94.45 7434.61 1970 727.47 58.34 7393.89 1989 744.94 61.12 Probability Analysis

Methodology Climatic parameters => Evapotranspiration (ETo) Crop Irrigation Requirements and their time-distribution depend on: Crop characteristics => Crop coefficient (Kc) Soil characteristics => WHC o AW (FC – PWP) Soil-Water Balance => accounting for all water inflows and outflows Di = D(i-1) + ETc – (P – SRO) – Iinf + DP - GW

+ + + Intersect utility in ArcGIS MeteoStations polygons Soils polygons (13 different soil types) + + Crops polygons (8 different crops) MeteoStations polygons + Intersect utility in ArcGIS

Identification of Simulation Units Simulation units are polygons having the same crop-soil-climatic area combinations 153 unique soil-crop-clim.area combinations = 153 ID.Codes (153 x 3 climatic scenarios) = 459 Runnings of the Soil-Water Balance model

Soil-Water Balance algorithm in terms of depletion Di = Di-1 + ETc - (P - SRO) - Irr + DP - GW Assumptions: irrigation aiming at maximum yield; 2) No groundwater contribution; 3) No restriction imposed 4) Soils at F.C. at irrig. season starting Time to irrigate when: Di > MAD Wa Rz How much to irrigate? The amount necessary to replenish the root-zone to the F.C.

Results: Map of Net Irrigation requirements

Superimposing layer of irrigation districts’ boundaries Aggregation of IWR at district level for different time-scales

Sources of errors and uncertainties in up-scaling IWR Spatial variability of soils Spatial variability of crops => different crop’s age and cultivars Spatial variability of climatic conditions (Thiessen method enables rough estimation) Spatial variability of land elevation (not taken into account) Spatial variability of conveyance, distribution and application efficiencies Bottom line: I.W.R. are very close to what farmers give to crops in the area Further check the time-distribution of seasonal IWR values

QUESTIONS, COMMENTS OR SUGGESTIONS ?? Aknowledgements: G. H. HARGREAVES Stornara & Tara Water Users Association Technical University of Lisbon (PT) – Instituto Superior de Agricultura QUESTIONS, COMMENTS OR SUGGESTIONS ??

Evaluating NIR and their spatial and time distribution Basic information for : Water allocation plan Water distribution plan (time of deliveries) Indirect quantification of withdrawals from groundwater Investigation on available water supply and time distribution Comparing water supply with water demand enables identification of deficit periods and areas Performance analysis of irrigation networks based on : Water demand flow hydrographs Physical capability of the network Identify critical areas Simulate re-engineering option and evaluating their effectiveness