UNIVERSITY OF MILAN. ValorE* Experience in building and apply an expert system for agricultural nitrogen management at regional level

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1 UNIVERSITY OF MILAN DEPARTMENT OF AGRICULTURAL AND ENVIRONMENTAL SCIENCES PRODUCTION, LANDSCAPE, AGROENERGY ValorE* Experience in building and apply an expert system for agricultural nitrogen management at regional level Marco Acutis Department of Agricultural and Environmental Sciences - Production, Landscape, Agroenergy Via Celoria, Milano, Italy *Expert systems for the enhancement of livestock manure, Lombardia environment and land protection

2 Introduction The Po valley is one of the most important aquifer systems in Europe. More than two-thirds of nitrogen reaching groundwater and surface water are due to agriculture (ABaPo, 2001). The 27% of the national bovine livestock and the 45% of swine raised in Italy are concentrated in Lombardy (ISTAT, 2011). The Nitrate Vulnerable Zones (NVZs) occupy the 62% of the Utilised Agricultural Area (UAA). 1/24

3 The nitrate pollution problem in Lombardy (1 ML of Cows + 5 ml of pigs; 10 ML inhabitants) The areas with elevated nitrate rate in groundwater match with those designed as NVZs, where also the organic nitrogen loading is highest. (50 mg/l drinking water limit) NO 3 N concentrations (mg L 1 ) in soil water solution extracted by ceramic cups through soil profile. Arrows indicates Nitrate rate the time in groundwater points when in fertilization Northern Italy was ( ) applied. The small one stands for low amount fertilization of 11 Livestock-derived nitrogen loading in Lombardy 100 kg N ha 1 ; the medium size one indicates N input of kg N ha Livestock-derived 1 ; the large one shows N supply of nitrogen loading in NVZs kg N ha 1. Markers (+) indicate the time of measurement. (From Perego et al, 2012) 2/24

4 Aim of the Research (endowment: 1.5 ML ) Main Objective Development of Expert Systems able to serve as a well founded basis for decision making about livestock manure management Farm Scale USERS: farmers, agronomists and technicians of professional organizations. APPLICATION: analysis of the actual farm situation and a priori assessment of management decisions impact. RESULTS: expressed by a wide set of indicators. Regional Scale USERS: public officials, policy makers and technicians. APPLICATION: analysis of the actual situation in a given territory and assessment of potential intervention impacts. RESULTS: expressed by a wide set of indicators and maps. 3/24

5 Expert System ValorE: structure Alternatives Definition and Scenarios Building Information Data Bank Reference Tables Simulation and Analysis Engine Farm Scale Regional Scale Motore di Impacts and analisi e Effects simulazione Analysis Indicators Scenarios Comparison Multicriteria* * Under development 4/24

6 Expert System ValorE: features Use of regional DB: farm, soil, meteo. Availability of simulation models for all production chain steps. Use of reference tables and default data from experiments or published sources. Remote data acquisition, stand-alone simulations, local storage option. Many farms simulation option (shared management of livestock manure). Possibilty of calculating compliance with normative limit values (91/676/EEC). 5/24

7 Expert System - Data adequacy assessment Baseline Information: management data: farms structure, land using of each cadastral unit, livestock distribution according to age, livestock housing, manure and slurry storage and treatment, (from SIARL - Agricultural Information System of Lombardy Region); meteorological data : 20-years time series of daily meteorological data measured at 14 sites; soil data: physical and chemical properties of soil (from a digital soil map at a scale of 1:50000). Additional Information (from existing literature and farmers interviews): technical and functional parameters of different housing systems and treatment and storage facilities; ration protein content; agricultural practices, sowing and harvest dates of the most common cropping systems; current NVZ rules on manure timing, application techniques and storage. 6/24

8 Expert System ValorE: data flow 7/24

9 simulated Armosa modelling analysis NO3-N leaching [kg N ha -1 ] 400 The issue of livestock manure management was first faced using Armosa, a simulation model whose main features can be summarized as follows. 300 It is a dynamic model able to simulate soil water and soil N balance, crop growth, N leaching and N volatilization losses. It can simulate the wide range of soil and climate conditions existing in 200 Lombardy. y = 1,1352x - 14,258 It was calibrated and validated on 7 datasets and R² collected = 0,9493 from farms 100 located in 6 representative sites in Lombardy from 2 to six years. (continuous water content and potential, NO 3 every days) Good 0 performance in model comparison exercises It is a 0well-founded decision 100 support tool 200for the evaluation 300 of agricultural 400 observed practices. 8/24

10 Armosa modelling analysis: input and output data meteorological data soil database crop database N fertilizer database ARMOSA biophysical based model soil water content drainage water soil NO 3 -N soil NH 4 -N N mineralization N uptake N leaching N denitrification N volatilization N, C humus above ground biomass yield LAI Harvest Index ET water stress index N stress index 9/24

11 Agronomic meta-model Armosa ValorE It is able to run simulations under different pedoclimatic and cropping scenarios one at a time Each run lasts 2 minutes Need for short-time execution on millions of cadastral units AGRONOMIC META-MODEL 10/24

12 Agronomic meta model: development The meta model was created starting from the outputs of ARMOSA simulations under different cropping system scenarios in Lombardy. Input Output Armosa Output cropping systems organic and mineral N fertilisation (kg N) denitrification crop yield (t ha -1 ) Sensitivity analysis annual rainfall and irrigation (mm) annual ETO (mm) sand (%) Agronomic meta-model soil N fixation (kg N ha -1 year -1 ) N leaching (kg N ha -1 year -1 ) crop N uptake (kg N ha -1 year -1 ) clay (%) drainage (mm year -1 ) stone (%) N mineralization (kg N ha -1 year -1 ) organic carbon (%) NH 3 volatilization (kg N ha -1 year -1 ) 11/24

13 ValorE: indices and indicators 12/24

14 ValorE: Alternative Scenarios Building ValorE provides users with the possibility of running simulations under alternative scenarios for each step of the manure production chain. Users' options: Scenarios aimed to accomplish a predetermined goal, such as nitrogen emission reduction (provided by the system) Scenarios aimed to assess the effect of a single practice or treatment 13/24

15 ValorE: Alternative Scenarios (1) Sludge: Option 6 Aim: manure management improvement (decrease of storage volumes, reduction of time and costs for transportation to the fields), thermal energy production and/or electricity generation, high nitrogen removal. THERMAL ENERGY PRODUCTION AND/OR ELECTRICITY GENERATION SLUDGE FOR AGRICULTURAL USE ROUGH SEPARATION WITH SCREW OR SIEVE SEPARATOR ANAEROBIC DIGESTION FINE SOLIDS SEPARATION WITH CENTRIFUGE STOCK TANK LEGEND: manure IN Unstabilized semi-solids Stabilized semi-solids (compost) manure OUT Final product Water Atmospheric emissions Slurry NITRO DENITRO SBR OR CONTINUOUS- FLOW OXYGEN OR AIR SEDIMENTATION BELT PRESS AGRICULTURAL USE STORAGE IN COVERED FACILITY 14/24

16 Farm Scale Authenticated access Farm selection Data Loading from remote database Current situation analysis Identification of critical pathways along the management chain Alternative scenario setting Output assessment 15/24

17 Farm Scale: Alternative Scenarios example Protein Total N N volatilised N volatilised Total N N distributed content excreted from stable from storage volatilisation on field Farm type Scenario % kg N kg N kg N kg N kg N Actual ,784 14,747 11,805 26,552 63,232 Alternative ,542 13,704 9,481 23,185 60,357 Swine farm Difference -7% -7% -20% -13% -5% Incr.(+)/ Decr.(-) Actual ,829 5,390 6,532 11,922 44,907 Alternative ,992 4,657 4,594 9,251 39,741 Dairy farm Difference -14% -14% -30% -22% -12% Incr.(+)/ Decr.(-) Beef Cattle farm Dairy and swine farm Reduction in ration protein content Actual ,220 12,944 10,429 23,373 59,847 Alternative ,875 11,801 7,809 19,610 56,265 Difference Incr.(+)/ Decr.(-) -9% -9% -25% -16% -6% Actual ,361 5,254 5,241 10,495 31,866 Alternative ,277 4,818 4,010 8,828 29,449 Difference Incr.(+)/ Decr.(-) -10% -8% -23% -16% -8% 16/24

18 Regional Scale Authenticated access Default or Free query selection Scenario setting Output Indicators Output Maps 18/24

19 Regional Scale: database queries The database interrogation is based on a web-gis interface The procedure involves, first, the selection of the aggregation level (i.e. farm, municipality and provinces) and, second, the selection of the geographic area of interest (e.g. one or more municipality, provinces, agrarian regions). Default queries They provide the user with a set of queries previously defined by specialists and stakeholders. Free queries They can be written using a query generator developed ad hoc to make easier the database access. 19/24

20 Regional-based Expert System: Scenario Example Scenario s goal Reduction of organic N loading Area selection 9 neighbouring municipalities in Bergamo province Sample selection Livestock farms not compliant with nitrates directive Supposed scenario Introduction of nitro-denitro systems with strong nitrogen removal Results Map visualization and spreadsheet comparison 20/24

21 Regional-based Expert System: Scenarios Building 21/24

22 Regional-based Expert System: map visualization 0 Results 0 Actual situation (obtained using the query system 22/24

23 Expert System user friendly feautures In order to get a better usability of the software, different aspects were carefully strengthened: the farm simulator can be installed and run on any computer (Window compatible) no matter if internet connection is available; the graphic user interface retraces in succession the different stages of production and distribution of wastewater; all the default parameters can be modified by the user to make the simulation results more closely to their own reality; the input data from databases are loaded in a short time (few second for each farm); the results of simulations are immediately available (few second for each farm). 23/24

24 Miscellaneous The relationship between the leaching below the root zone and NO 3 in groundwater is not (still) developed; Farmers and agronomist are interested mainly (or only) to check the law compliance. (with ValorE it is really easy to evaluate alternatives, more than using the institutional software for nitrate directive compliance declaration) ; Low level of collaboration from professional organization: they was in charge to test the software, but the test was performed on few farms, the better ones. The software gives some possibility to control on farm activity: e.g., we have found farms with cows of 300 kg weight. But is better to risk a penalty (that probably will arrive never) that to change something even if there is the possibility to more income. Low interest in derogation from 170 kg/ha to 250 of organic N (ValorE can do easily this simulation) Low collaboration from Academics: no scientific interest in the transformation scientific knowledge in software ready to use. Even if there are possibility of validation of the knowledge. 23/24

25 Conclusions ValorE is a reliable expert system for the nitrate issue in Lombardia plain. It is a user friendly software used by 200 user for 4000 farms. It allows for analysis at different scales Try to use all information available from regional database and scientific knowledge to help the farmers and the decision makers to improve their global results. Professional organization are worried by the possibility to better monitoring of farms and their activity (risk of penalty for the farmers). 24/24

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