Stochastic modeling of Rainfall Disaggregation using ANNShashank Singh
Rainfall Disaggregation modeling using stochastic model, Valencia-Schaake, Lane alongwith application of Artificial Neural Network to Disaggregate higher order scale time series to lower time scale series.
~Shashank Singh~
This document summarizes Stephen Quandzie's MSc thesis on the potential to increase agricultural water productivity in Ghana's Black Volta Basin. The research questions whether agricultural water productivity can be increased, if increased dry season agriculture would help reduce poverty, and which agricultural water management intervention has the potential to improve livelihoods sustainably. The methodology involves using the CROPWAT and CLIMWAT models to analyze crop water consumption factors and physical, economic, and livestock water productivity. The results found that small reservoirs, shallow wells, and water pumps with reservoirs over-irrigated crops. Water pumps with reservoirs or river access were identified as having the best potential to enhance agricultural water management and promote off-farm skills development.
Simulating the sensitivity of maize crop propagation to seasonal weather chan...CTA
This study used the CROPWAT model to simulate the effects of temperature changes on maize crop yields in Ibadan, Nigeria. The results showed that rising temperatures had a negative effect on maize yields, though the reduction trends were not definite due to variability in temperatures. Yield reductions were low under definite interval irrigation and high without irrigation. Definite interval irrigation was determined to be the most effective strategy to minimize yield losses from temperature increases and weather variability.
Flood Prediction Model using Artificial Neural NetworkEditor IJCATR
This paper presents a Flood Prediction Model (FPM) to predict flood in rivers using Artificial Neural Network (ANN)
approach. This model predicts river water level from rainfall and present river water level data. Though numbers of factors are
responsible for changes in water level, only two of them are considered. Flood prediction problem is a non-linear problem and to solve
this nonlinear problem, ANN approach is used. Multi Linear Perceptron (MLP) based ANN’s Feed Forward (FF) and Back
Propagation (BP) algorithm is used to predict flood. Statistical analysis shows that data fit well in the model. We present our
simulation results for the predicted water level compared to the actual water level. Results show that our model successfully predicts
the flood water level 24 hours ahead of time.
This document discusses using the CROPWAT and CLIMWAT models to evaluate and plan irrigation for cotton and rice crops in India. It summarizes that India currently produces lower rice yields than countries like China and Brazil from the same amount of land. Increasing yields through improved irrigation practices could increase production and reduce land usage. The document then outlines using the CROPWAT model to analyze reference evapotranspiration, crop water requirements, irrigation requirements, and develop irrigation schedules for cotton and rice in the Kurnool region of India based on climatic and soil data. It concludes that significantly increasing crop yields through using CROPWAT could boost the economy by improving farmer livelihoods and freeing up land.
There are 4 parks near the author's house that use different irrigation systems. DDA Park in Sector 11 uses sprinkler irrigation, which sprays water into the air to water the entire soil surface. DDA Park in Sector 6 uses drip irrigation, which applies water slowly at the base of plants. Rotary irrigation is used in DDA Park in Sector 10 and involves mechanically driven sprinklers that reach distances of up to 100 feet. The center-pivot system used in one park conserves water by using less than surface irrigation and reducing labor costs. Overextraction of groundwater has caused levels to drop by over 5 feet per year in some places.
Stochastic modeling of Rainfall Disaggregation using ANNShashank Singh
Rainfall Disaggregation modeling using stochastic model, Valencia-Schaake, Lane alongwith application of Artificial Neural Network to Disaggregate higher order scale time series to lower time scale series.
~Shashank Singh~
This document summarizes Stephen Quandzie's MSc thesis on the potential to increase agricultural water productivity in Ghana's Black Volta Basin. The research questions whether agricultural water productivity can be increased, if increased dry season agriculture would help reduce poverty, and which agricultural water management intervention has the potential to improve livelihoods sustainably. The methodology involves using the CROPWAT and CLIMWAT models to analyze crop water consumption factors and physical, economic, and livestock water productivity. The results found that small reservoirs, shallow wells, and water pumps with reservoirs over-irrigated crops. Water pumps with reservoirs or river access were identified as having the best potential to enhance agricultural water management and promote off-farm skills development.
Simulating the sensitivity of maize crop propagation to seasonal weather chan...CTA
This study used the CROPWAT model to simulate the effects of temperature changes on maize crop yields in Ibadan, Nigeria. The results showed that rising temperatures had a negative effect on maize yields, though the reduction trends were not definite due to variability in temperatures. Yield reductions were low under definite interval irrigation and high without irrigation. Definite interval irrigation was determined to be the most effective strategy to minimize yield losses from temperature increases and weather variability.
Flood Prediction Model using Artificial Neural NetworkEditor IJCATR
This paper presents a Flood Prediction Model (FPM) to predict flood in rivers using Artificial Neural Network (ANN)
approach. This model predicts river water level from rainfall and present river water level data. Though numbers of factors are
responsible for changes in water level, only two of them are considered. Flood prediction problem is a non-linear problem and to solve
this nonlinear problem, ANN approach is used. Multi Linear Perceptron (MLP) based ANN’s Feed Forward (FF) and Back
Propagation (BP) algorithm is used to predict flood. Statistical analysis shows that data fit well in the model. We present our
simulation results for the predicted water level compared to the actual water level. Results show that our model successfully predicts
the flood water level 24 hours ahead of time.
This document discusses using the CROPWAT and CLIMWAT models to evaluate and plan irrigation for cotton and rice crops in India. It summarizes that India currently produces lower rice yields than countries like China and Brazil from the same amount of land. Increasing yields through improved irrigation practices could increase production and reduce land usage. The document then outlines using the CROPWAT model to analyze reference evapotranspiration, crop water requirements, irrigation requirements, and develop irrigation schedules for cotton and rice in the Kurnool region of India based on climatic and soil data. It concludes that significantly increasing crop yields through using CROPWAT could boost the economy by improving farmer livelihoods and freeing up land.
There are 4 parks near the author's house that use different irrigation systems. DDA Park in Sector 11 uses sprinkler irrigation, which sprays water into the air to water the entire soil surface. DDA Park in Sector 6 uses drip irrigation, which applies water slowly at the base of plants. Rotary irrigation is used in DDA Park in Sector 10 and involves mechanically driven sprinklers that reach distances of up to 100 feet. The center-pivot system used in one park conserves water by using less than surface irrigation and reducing labor costs. Overextraction of groundwater has caused levels to drop by over 5 feet per year in some places.
Applications of Artificial Neural Networks in Civil EngineeringPramey Zode
An artificial brain-like network based on certain mathematical algorithms developed using a numerical computing environment is called as an ‘Artificial Neural Network (ANN)’. Many civil engineering problems which need understanding of physical processes are found to be time consuming and inaccurate to evaluate using conventional approaches. In this regard, many ANNs have been seen as a reliable and practical alternative to solve such problems. Literature review reveals that ANNs have already being used in solving numerous civil engineering problems. This study explains some cases where ANNs have been used and its future scope is also discussed.
This document summarizes four main irrigation methods: surface irrigation (flooding), sprinkler irrigation (applying water under pressure), drip or trickle irrigation (applying water slowly to the soil), and sub-surface irrigation (flooding water underground). Surface irrigation is the most widely used method, covering 90% of irrigated land. Sprinkler irrigation is ideal for scarce water areas. Drip irrigation conserves water, controls weeds, and applies water at a slow rate matching crop needs. Sub-surface irrigation is used where soil and topography allow watering underground.
This document provides an overview of irrigation engineering. It discusses the necessity of irrigation due to factors like insufficient rainfall and uneven distribution. It describes different types of irrigation systems including flow irrigation, lift irrigation, and storage irrigation. It also defines important terms used in irrigation like duty, delta, command area. The document outlines the benefits of irrigation such as increased crop yields and prosperity of farmers. It also notes some ill effects like raising water tables and creating breeding grounds for mosquitoes. Overall, the document provides a broad introduction to key concepts in irrigation engineering.
- The document introduces artificial neural networks, which aim to mimic the structure and functions of the human brain.
- It describes the basic components of artificial neurons and how they are modeled after biological neurons. It also explains different types of neural network architectures.
- The document discusses supervised and unsupervised learning in neural networks. It provides details on the backpropagation algorithm, a commonly used method for training multilayer feedforward neural networks using gradient descent.
Irrigation is the process of transporting water from areas with abundant supply like rivers or reservoirs to drier areas for agricultural and domestic purposes. Ancient Mesopotamians and Egyptians developed early irrigation systems using dams, reservoirs, and canals to supply water to lands away from water sources. Irrigation was invented to allow people living farther from water access to drink, grow crops, and meet other needs, and made obtaining water more reliable and regular. Today, irrigation continues to enable farming in more places and help ensure a secure food supply for more people.
1. Irrigation is the artificial supply of water to crops through methods like surface, sprinkler, and drip irrigation. Surface irrigation involves distributing water over the soil surface by gravity in techniques like basin, border, and furrow irrigation.
2. Sprinkler irrigation applies water similar to rainfall through pipes and sprinklers. Drip irrigation drips water slowly from pipes and emitters directly to plant roots.
3. The suitable irrigation method depends on factors like soil type, crop type, technology, costs and previous experience. Surface irrigation is common on loamy and clay soils while sprinkler and drip are more suitable for sandy soils with low water storage.
By Asad Sarwar Qureshi, Samina Yasmin, Nikar C. Holader, Timothy J. Krupnik
Revitalizing the Ganges Coastal Zone Conference
21-23 October 2014, Dhaka, Bangladesh
http://waterandfood.org/ganges-conference/
By J. Bhattacharya, M.K. Mondal, E. Humphreys, M.H. Rashid, P.L.C. Paul, S.P. Ritu
Revitalizing the Ganges Coastal Zone Conference
21-23 October 2014, Dhaka, Bangladesh
http://waterandfood.org/ganges-conference/
By M. Maniruzzaman, J.C. Bisawas, M.A.I. Khan, G.W. Sarker, S.S. Haque, J.K. Biswas, M.H. Sarker, M.A. Rashid, N.U. Sekhar, A. Nemes, S. Xenarios, J. Deelstra
Revitalizing the Ganges Coastal Zone Conference
21-23 October 2014, Dhaka, Bangladesh
http://waterandfood.org/ganges-conference/
1) The study evaluated the feasibility of growing three rice crops per year in the coastal zones of Bangladesh where fresh water is available year-round.
2) The study tested different establishment dates for aus and aman rice varieties as well as sowing dates for boro rice. It found that growing three rice crops per year is possible and can yield 13.4 to 17.2 tons per hectare per year.
3) The study recommends further evaluating the system over a range of weather conditions and developing ecologically friendly management practices to address potential increases in pests and diseases from triple rice cropping.
By M. Harunur Rashid, Faruk Hossain, Deb Kumar Nath, Parimal Chandra Sarker, AKM Ferdous, Timothy Russel
Revitalizing the Ganges Coastal Zone Conference
21-23 October 2014, Dhaka, Bangladesh
http://waterandfood.org/ganges-conference/
By Camelia Dewan, Marie-Charlotte Buisson and Aditi Mukherji
Revitalizing the Ganges Coastal Zone Conference
21-23 October 2014, Dhaka, Bangladesh
http://waterandfood.org/ganges-conference/
The document discusses using innovation platforms to improve goat markets and farming systems in Zimbabwe. Key points:
- Innovation platforms bring together farmers, traders, processors, researchers and others to identify challenges and opportunities to improve goat production and marketing.
- Objectives are to improve market efficiency, reduce transaction costs, promote productivity-increasing technologies, and build local innovation capacity.
- Results included dramatically reduced goat mortality rates (from 25% to under 10%), higher prices for farmers, and investments in improved feeding and health practices.
- Other actors like NGOs and the government also increased support like building sale pens and improving veterinary services. The approach transformed the system from crop-focused to more livestock-focused and
By Urs Schulthess, Timothy J. Krupnik, Zia Uddin Ahmed, Andy J. McDonald
Revitalizing the Ganges Coastal Zone Conference
21-23 October 2014, Dhaka, Bangladesh
http://waterandfood.org/ganges-conference/
By Parvesh Kr Chandna, Andy Nelson, Zahirul Khan, Moqbul Hossain, Sohel Rana, Fazlur Rashid, M. Mondal, T.P. Tuong
Revitalizing the Ganges Coastal Zone Conference
21-23 October 2014, Dhaka, Bangladesh
http://waterandfood.org/ganges-conference/
By Parvesh Kumar Chandna, Andy Nelson, Sohel Rana, Marie-Charlotte Buisson, Sam Mohanty, Nazneed Sultana, Deepak Sethi, T.P. Tuong
Revitalizing the Ganges Coastal Zone Conference
21-23 October 2014, Dhaka, Bangladesh
http://waterandfood.org/ganges-conference/
By Asad Sarwar Qureshi, Samina Yasmin, Nikar C. Howlader, Timothy J. Krupnik
Revitalizing the Ganges Coastal Zone Conference
21-23 October 2014, Dhaka, Bangladesh
http://waterandfood.org/ganges-conference/
By Dr. Md. Ataur Rahman (Wheat Research Centre, BARI)
Revitalizing the Ganges Coastal Zone Conference
21-23 October 2014, Dhaka, Bangladesh
http://waterandfood.org/ganges-conference/
Applications of Artificial Neural Networks in Civil EngineeringPramey Zode
An artificial brain-like network based on certain mathematical algorithms developed using a numerical computing environment is called as an ‘Artificial Neural Network (ANN)’. Many civil engineering problems which need understanding of physical processes are found to be time consuming and inaccurate to evaluate using conventional approaches. In this regard, many ANNs have been seen as a reliable and practical alternative to solve such problems. Literature review reveals that ANNs have already being used in solving numerous civil engineering problems. This study explains some cases where ANNs have been used and its future scope is also discussed.
This document summarizes four main irrigation methods: surface irrigation (flooding), sprinkler irrigation (applying water under pressure), drip or trickle irrigation (applying water slowly to the soil), and sub-surface irrigation (flooding water underground). Surface irrigation is the most widely used method, covering 90% of irrigated land. Sprinkler irrigation is ideal for scarce water areas. Drip irrigation conserves water, controls weeds, and applies water at a slow rate matching crop needs. Sub-surface irrigation is used where soil and topography allow watering underground.
This document provides an overview of irrigation engineering. It discusses the necessity of irrigation due to factors like insufficient rainfall and uneven distribution. It describes different types of irrigation systems including flow irrigation, lift irrigation, and storage irrigation. It also defines important terms used in irrigation like duty, delta, command area. The document outlines the benefits of irrigation such as increased crop yields and prosperity of farmers. It also notes some ill effects like raising water tables and creating breeding grounds for mosquitoes. Overall, the document provides a broad introduction to key concepts in irrigation engineering.
- The document introduces artificial neural networks, which aim to mimic the structure and functions of the human brain.
- It describes the basic components of artificial neurons and how they are modeled after biological neurons. It also explains different types of neural network architectures.
- The document discusses supervised and unsupervised learning in neural networks. It provides details on the backpropagation algorithm, a commonly used method for training multilayer feedforward neural networks using gradient descent.
Irrigation is the process of transporting water from areas with abundant supply like rivers or reservoirs to drier areas for agricultural and domestic purposes. Ancient Mesopotamians and Egyptians developed early irrigation systems using dams, reservoirs, and canals to supply water to lands away from water sources. Irrigation was invented to allow people living farther from water access to drink, grow crops, and meet other needs, and made obtaining water more reliable and regular. Today, irrigation continues to enable farming in more places and help ensure a secure food supply for more people.
1. Irrigation is the artificial supply of water to crops through methods like surface, sprinkler, and drip irrigation. Surface irrigation involves distributing water over the soil surface by gravity in techniques like basin, border, and furrow irrigation.
2. Sprinkler irrigation applies water similar to rainfall through pipes and sprinklers. Drip irrigation drips water slowly from pipes and emitters directly to plant roots.
3. The suitable irrigation method depends on factors like soil type, crop type, technology, costs and previous experience. Surface irrigation is common on loamy and clay soils while sprinkler and drip are more suitable for sandy soils with low water storage.
By Asad Sarwar Qureshi, Samina Yasmin, Nikar C. Holader, Timothy J. Krupnik
Revitalizing the Ganges Coastal Zone Conference
21-23 October 2014, Dhaka, Bangladesh
http://waterandfood.org/ganges-conference/
By J. Bhattacharya, M.K. Mondal, E. Humphreys, M.H. Rashid, P.L.C. Paul, S.P. Ritu
Revitalizing the Ganges Coastal Zone Conference
21-23 October 2014, Dhaka, Bangladesh
http://waterandfood.org/ganges-conference/
By M. Maniruzzaman, J.C. Bisawas, M.A.I. Khan, G.W. Sarker, S.S. Haque, J.K. Biswas, M.H. Sarker, M.A. Rashid, N.U. Sekhar, A. Nemes, S. Xenarios, J. Deelstra
Revitalizing the Ganges Coastal Zone Conference
21-23 October 2014, Dhaka, Bangladesh
http://waterandfood.org/ganges-conference/
1) The study evaluated the feasibility of growing three rice crops per year in the coastal zones of Bangladesh where fresh water is available year-round.
2) The study tested different establishment dates for aus and aman rice varieties as well as sowing dates for boro rice. It found that growing three rice crops per year is possible and can yield 13.4 to 17.2 tons per hectare per year.
3) The study recommends further evaluating the system over a range of weather conditions and developing ecologically friendly management practices to address potential increases in pests and diseases from triple rice cropping.
By M. Harunur Rashid, Faruk Hossain, Deb Kumar Nath, Parimal Chandra Sarker, AKM Ferdous, Timothy Russel
Revitalizing the Ganges Coastal Zone Conference
21-23 October 2014, Dhaka, Bangladesh
http://waterandfood.org/ganges-conference/
By Camelia Dewan, Marie-Charlotte Buisson and Aditi Mukherji
Revitalizing the Ganges Coastal Zone Conference
21-23 October 2014, Dhaka, Bangladesh
http://waterandfood.org/ganges-conference/
The document discusses using innovation platforms to improve goat markets and farming systems in Zimbabwe. Key points:
- Innovation platforms bring together farmers, traders, processors, researchers and others to identify challenges and opportunities to improve goat production and marketing.
- Objectives are to improve market efficiency, reduce transaction costs, promote productivity-increasing technologies, and build local innovation capacity.
- Results included dramatically reduced goat mortality rates (from 25% to under 10%), higher prices for farmers, and investments in improved feeding and health practices.
- Other actors like NGOs and the government also increased support like building sale pens and improving veterinary services. The approach transformed the system from crop-focused to more livestock-focused and
By Urs Schulthess, Timothy J. Krupnik, Zia Uddin Ahmed, Andy J. McDonald
Revitalizing the Ganges Coastal Zone Conference
21-23 October 2014, Dhaka, Bangladesh
http://waterandfood.org/ganges-conference/
By Parvesh Kr Chandna, Andy Nelson, Zahirul Khan, Moqbul Hossain, Sohel Rana, Fazlur Rashid, M. Mondal, T.P. Tuong
Revitalizing the Ganges Coastal Zone Conference
21-23 October 2014, Dhaka, Bangladesh
http://waterandfood.org/ganges-conference/
By Parvesh Kumar Chandna, Andy Nelson, Sohel Rana, Marie-Charlotte Buisson, Sam Mohanty, Nazneed Sultana, Deepak Sethi, T.P. Tuong
Revitalizing the Ganges Coastal Zone Conference
21-23 October 2014, Dhaka, Bangladesh
http://waterandfood.org/ganges-conference/
By Asad Sarwar Qureshi, Samina Yasmin, Nikar C. Howlader, Timothy J. Krupnik
Revitalizing the Ganges Coastal Zone Conference
21-23 October 2014, Dhaka, Bangladesh
http://waterandfood.org/ganges-conference/
By Dr. Md. Ataur Rahman (Wheat Research Centre, BARI)
Revitalizing the Ganges Coastal Zone Conference
21-23 October 2014, Dhaka, Bangladesh
http://waterandfood.org/ganges-conference/
By Sanjida P. Ritu, M.K. Mondal, T.P. Tuong, S.U. Talukdar, E. Humphreys
Revitalizing the Ganges Coastal Zone Conference
21-23 October 2014, Dhaka, Bangladesh
http://waterandfood.org/ganges-conference/
By Kazi Ahmed Kabir, S.B. Saha, Manjurul Karim, Craig A. Meisner, Michael J. Phillips
Revitalizing the Ganges Coastal Zone Conference
21-23 October 2014, Dhaka, Bangladesh
http://waterandfood.org/ganges-conference/
By S.B. Saha, K.A. Kabir, M.K. Mondal, M. Karim, P.L.C. Paul, M. Phillips, E. Humphreys, T.P. Tuong
Revitalizing the Ganges Coastal Zone Conference
21-23 October 2014, Dhaka, Bangladesh
http://waterandfood.org/ganges-conference/
BRAC aims to increase agricultural and aquacultural productivity in coastal Bangladesh through several strategies. These include converting single cropping areas to double or triple cropping, introducing short-duration rice varieties, stress-tolerant crops and fish varieties, and integrating fish/prawn-rice-vegetable systems in ghers. Technologies are disseminated to over 55,000 farmers across 59 upazilas. Hybrid rice varieties yield up to 9.5 tons/hectare. Integrated ghers provide net profits from 172,558-416,975 taka/hectare. Aquaculture in floodplains involves 257 farmers utilizing 73 acres in 2013, yielding an average 795 kg/hect
By Subhra Bikash Bhattacharyya, Tapas Kumar Ghoshal, Jitendra Kumar Sundaray (Central Institute of Brackishwater Aquaculture, India)
Revitalizing the Ganges Coastal Zone Conference
21-23 October 2014, Dhaka, Bangladesh
http://waterandfood.org/ganges-conference/
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Feeling lost in the digital marketing whirlwind of 2024? Technology is changing, consumer habits are evolving, and staying ahead of the curve feels like a never-ending pursuit. This e-book is your compass. Dive into actionable insights to handle the complexities of modern marketing. From hyper-personalization to the power of user-generated content, learn how to build long-term relationships with your audience and unlock the secrets to success in the ever-shifting digital landscape.
In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
This presentation delves into the development of a system designed to mimic Galileo's Open Service signal using software-defined radio (SDR) technology. We'll begin with a foundational overview of both Global Navigation Satellite Systems (GNSS) and the intricacies of digital signal processing.
The presentation culminates in a live demonstration. We'll showcase the manipulation of Galileo's Open Service pilot signal, simulating an attack on various software and hardware systems. This practical demonstration serves to highlight the potential consequences of unaddressed vulnerabilities, emphasizing the importance of offensive security practices in safeguarding critical infrastructure.
Crop water productivity modeling: Demand and impact at a field level
1.
2. Activities Model Used
• Estimate WR and consumption of crops • CROPWAT (vr. 8)
grown under different soils Climates: • AquaCrop (Vr. 4)
• Current Vs alternative AWM scenarios
3.
4.
5. Example 1: WR, Consumption and WP of wheat grown on
BBF and Flat seedbeds
Location and Growing season Actual ETc Grain WP with respect to WP with respect to
year actual ETc (kg m-3)
eff. rainfall (m3 (m3 ha-1) eff. rainfall (kg m-3)
ha-1) BBF Flat BBF Flat % increase BBF Flat
due to BBF
Enewari 1986 4770 3005 1086 0.23 0.22 5 0.37 0.99
Dogollo 1986 5740 3161 2582 0.32 0.22 45 0.58 0.49
Dejen 1987 5640 3000 1200 0.22 0.16 38 0.42 0.77
Bahir Dar 2007 7570 2804 2429 0.34 0.26 31 0.93 0.82
Merawi 2007 5720 3135 1206 0.30 0.10 200 0.54 0.50
Bichena 1997 4770 3005 1086 0.34
BBF and Flat beds planted on June 10 and August 15, respectively
0.19 79 0.53 0.83
Average 5876 3040 1669 0.33 0.24 57 0.66 0.89
6. Example 2: WR, Consumption and WP of rice, grass-pea and
extensively grazed grass grown on flat areas
Crop type: Rice
Location Yield (kg ha-1) Average eff. rain Actual ETc (m3 Grain WP (kg m-3) with respect Biomass WP with
(m3 ha-1) ha-1) to respect to eff. rain
Grain Straw Eff. rain Actual ETc
Fogera 2007 3510 4467 6330 5259 0.55 0.67 1.3
Fogera 2011 3744 4765 6330 4233 0.59 0.88 1.3
3627 4616 6330 4746 0.57 0.78 1.3
Pawe 2007 3644 4638 7900 4953 0.46 0.74 1.0
Pawe 2008 3547 4514 7900 5857 0.45 0.61 1.0
Average 3596 4576 7900 5405 0.46 0.68 1.0
Crop type: Grass -pea
Fogera 2007 6330 3130
Fogera 2011 6330 3130
Average 6330 3130
Pawe 2007 7900 4930
Pawe 2008 7900 4860
Average 4662 9558 7900 4895 0.59 0.95 1.8
Crop type: Pasture (extensive grazing)
Fogera 2011* Biomass (kg ha-1) Eff. rain (m3 ha-1) CWR (m3 ha-1) Biomass WP (kg m-3) with
respect to Actual ETc
2793 6330 1940 1.44 0.44
7. • Use of BBF increased water demand, but reduced
evaporation loss
• BBF increased WP with respect to effective rainfall
• Growing rice instead of grass-pea or grazing increased
water demand, but reduced evaporation
• Use of BBF on drainable and rice on flat land increased
Economic Water Productivity