IMPLICATIONS OF SHALLOW GROUNDWATER DYNAMICS ONWATER AND SALINITY MANAGEMENT AT KASINTHULASUGARCANE IRRIGATION SCHEME, MALAWIbyTRENCIO ENOCK HANWELL KANDINGAMini dissertation submitted in partial fulfilment of the requirement for thedegree MSc Water Resource Managementin theDepartment of Plant and Soil SciencesFaculty of Natural and Agricultural SciencesUniversity of PretoriaSupervisor: Prof J.G. AnnandaleCo-supervisors: Dr E.W. Christen: Prof R.J. Stirzaker: Dr A.J. SaneweFebruary 2019

DeclarationI hereby certify that this research dissertation is my own work, except where duly acknowledged.I also certify that no plagiarism was committed in writing this report.Signed:Date: 6th February 2019Trencio Enock Hanwell Kandingaii

DedicationTo my departed parents. May your precious souls rest in eternal peace.iii

AcknowledgementsThis material is based upon work supported by the United States Agency for InternationalDevelopment, as part of the Feed the Future Initiative, under the CGIAR Fund, award numberBFS-G-11-00002, and the predecessor fund, the food security and crisis Mitigation II grant, awardnumber EEM-G-00-04-00013.My sincere gratitude to the following people and organizations for their contribution to thesuccessful completion of the study:Virtual Irrigation Academy (VIA) Project under the Commonwealth Scientific and IndustrialResearch Organisation (CSIRO Agriculture and Food) through the Australian Centre forInternational Agricultural Research (ACIAR) of the Department of Foreign Affairs and Trade inAustralia for equipment and connecting me with wonderful people who helped shape everything.The Department of Irrigation Services of the Ministry of Agriculture and Water Development,Malawi, for granting me study leave to undertake my studies.My Supervisors: Prof John G Annandale, Dr Evan W Christen, Prof Richard J Stirzaker, DrAndrew J Sanewe for encouragement and expert guidance throughout the course of study. I can’tthank you all enough.Dr Isaac Fandika and staff of Kasinthula Research Station for hosting me and assisting with allnecessary logistics during data collection.Mr Sam Banda and staff of Kasinthula Cane Growers Limited for everything during and after datacollection.Dr Kenneth A Wiyo of LUANAR for mentorship and guidance throughout my academic lifeJames G Mwepa for his tireless efforts; Rex Mbiza, Akoma Phiri, Hastings Chikondano, YohaneSolomon, Laston Mawaya and all those that were involved in data collection.My wife Salome and daughter Lizzie for enduring during the tough time and providing moralsupport. I love you.Praise be to God Almighty for seeing me through in good health. I will forever be grateful.iv

Table of ContentsDECLARATION. IIDEDICATION. IIIACKNOWLEDGEMENTS . IVLIST OF FIGURES . VIIILIST OF TABLES . XABSTRACT . XIINTRODUCTION. 1BACKGROUND . 1OBJECTIVES . 3HYPOTHESES . 41.0LITERATURE REVIEW . 51.1 GROUNDWATER . 51.1.1 Definition of groundwater and aquifer properties . 51.1.2 Importance of groundwater . 71.1.3 Groundwater movement, monitoring and measurements . 71.1.4 Irrigation effects on groundwater. 81.1.5 Monitoring groundwater solutes . 91.2 SALINITY PROBLEMS IN IRRIGATION SCHEMES . 91.2.1 Classification and causes of salinity . 91.2.2 Effects of salinity in irrigation schemes . 101.2.3 Salinity measurement and monitoring . 111.3 IRRIGATION WATER MANAGEMENT . 111.3.1 Definition of irrigation water management . 111.3.2 Importance of irrigation water management. 121.3.3 Irrigation measurement and when to irrigate . 121.3.4 Factors to consider with irrigation water management . 141.3.5 Crop factors and crop characteristics . 16v



List of FiguresFigure 1.1 Cross section of a Cutthroat Flume and an image of a fabricated one . 14Figure 2.1 Map of Malawi showing Chikwawa District and Kasinthula Irrigation Scheme . 19Figure 2.2 Kasinthula Digital Elevation Map (DEM) showing monitoring points . 22Figure 3.1 Longitudinal cross section of Kasinthula Scheme. 33Figure 3.2 The Vector Map for the area showing water flow paths . 34Figure 3.3 Kasinthula crop water requirement (CWR), irrigation (I) and rainfall (R) . 34Figure 3.4 Average transect water table fluctuations over time at Kasinthula . 35Figure 3.5 Water table graph for Piezometer LP1 showing days of irrigation (I) and rainfall (R),ground level (GL) . 36Figure 3.6 Water table graph for Piezometer MLP3 showing days of irrigation (I), rainfall (R) andground level (GL) . 37Figure 3.7 Water table graph for Piezometer MUP4 showing days of irrigation (I), rainfall (R) andground level (GL) . 38Figure 3.8 Water table graph for Piezometer UP2 showing days of irrigation (I), rainfall (R) andground level (GL) . 39Figure 3.9 Scatter plot of LP1 showing water table rise or fall with amount of water receivedthrough irrigation or rainfall . 40Figure 3.10 Water table map for 12th August 2017 showing depth of water table surface from thesoil surface and positions of transects . 41Figure 3.11 Water table map for 16th December 2017 showing depth of water table and positionsof transects . 41Figure 3.12 Water table change map for 16th December 2017 from 10th August 2017 showingchange in depth of water table and positions of transects . 42Figure 3.13 Average groundwater salinities for each transect showing error bars . 44Figure 3.14 Average groundwater salinities for LP transect . 45Figure 3.15 Irrigation water salinities measured at Kasinthula . 46Figure 3.16 Saturated paste soil salinities calculated from measured 1:4 EC values obtained atKasinthula . 46Figure 3.17 Scatter plot of average soil salinities against water table depths. 50Figure 3.18 Cross section of MLP showing crests for feeder canals and troughs for drains .53viii

Figure 3.19 Average groundwater salinity variations across different piezometers in MLP .55Figure 3.20 A field showing signs of temporary waterlogging at Kasinthula, and a piezometer witha white cap .56Figure 4.1 Average annual scheme yield for Kasinthula . 59Figure 4.2 2001 Yield (ton/ha) map for Kasinthula Scheme . 60Figure 4.3 2017 Yield (ton/ha) map for Kasinthula Scheme . 60Figure 4.4 2001 and 2017 Subtracted yield map for Kasinthula Scheme . 61Figure 4.5 Yields of fields in LP from 2001 to 2017 . 62Figure 4.6 Yields of fields in MLP from 2001 to 2017 where MLP1 falls directly under MLP2while MLP3 and MLP4 fall under MLP5 . 62Figure 4.7 Yields of fields in MUP from 2001 to 2017 where MUP1 falls directly under MUP2while MUP3 and MUP4 fall under MUP5 . 63Figure 4.8 Yields of fields in UP from 2001 to 2017 where UP1 falls directly under UP2 whileUP4 falls under UP5 . 63Figure 4.9 Yearly average yields for individual transects at Kasinthula from 2001 to 2017 . 64Figure 4.10 Scatter graph of average scheme sugarcane yield losses in relation to field elevationabove sea level over the 17 years . 66Figure 4.11 Scatter plot for 2017 yields and water table depths . 67Figure 4.12 Scatter plot for 2017 yields and soil salinity (ECe) . 68Figure 4.13 Scatter plot for yield changes over time and water table depths . 68Figure 4.14 Scatter plot for yield changes over time and groundwater salinity . 69Figure 4.15 Expected sugarcane yield loss at different salinity levels above salinity threshold forKasinthula . 70Figure 4.16 Expected sugarcane yields at different salinity levels above salinity threshold forKasinthula . 70Figure 4.17 The visualisations from the Chameleon Sensor readings for LP5 showing nitratereadings ( . 71Figure 4.18 The visualisations from the Chameleon Sensor readings for LP3 showing nitratereadings ( . 72Figure 5.1 Schematic representation of a floating flag installed in the ground . 79ix

List of TablesTable 2.1 Characteristics of transects and piezometers . 20Table 2.2 Similarities in fields selected for monitoring points . 21Table 2.3 Chameleon sensor colours, matrix potential ranges and interpretations (Steyn 2016) . 28Table 3.1 Soil and aquifer characteristics of Kasinthula Irrigation Scheme . 32Table 3.2 Measured irrigation (I) and rainfall (R) event amounts for LP1 for the dates monitored. 36Table 3.3 Measured irrigation (I) and rainfall (R) event amounts for MLP3 for the dates monitored. 37Table 3.4 Measured irrigation (I) and Rainfall (R) event amounts for MUP4 for the dates monitored. 38Table 3.5 Measured irrigation (I) and Rainfall (R) event amounts for UP2 for the dates monitored. 39Table 3.6 Observed water table differences from subtracted maps, volume changes of water andnet recharge rates with rainfall and irrigation data and estimated drainable porosity . 43Table 3.7 Descriptive statistics of soil characteristics in the top 1 m and aquifer characteristics ofKasinthula Irrigation Scheme up to the 5 m depth . 48Table 3.8 Aquifer characteristics of the Kasinthula Scheme for top 5 metre soil depth . 51Table 4.1 Descriptive statistics for yields in 2001 and 2017 . 65Table 5.1 Colour delineation depths for action (Sources: Escolar et al. 1971; Hunsigi andSrivastava 1977; Gupta and Yadav 1993; Hurst et al. 2004) . 77Table 5.2 Water table depths and revised irrigation frequencies when the floating flags will be used. 80x

AbstractA study to understand the implications of shallow groundwater dynamics was carried out atKasinthula Irrigation Scheme in Chikwawa District, Malawi. Water table fluctuations,groundwater salinities and soil solute levels were monitored every week from August to December2017. Soils in the area are clay to clay loam and there is a uniform aquifer with a low hydraulicconductivity of 0.06 m/day and very high soil salinity reaching up to 8.5 dS/m. Effect of watertable fluctuations on historical sugarcane yields were assessed and was observed to have very littleeffect on yields, however, a comparison of actual yields against expected yields from the MaasHoffmann salinity function revealed low correlation since some areas with highest soil salinity hadhigher yields as compared to the areas with low soil salinity that were expected to produce higheryields. The area with highest soil salinity happened to have average water table closer to 1 m whichis known to help supplement irrigation water requirements. However, sugarcane yields were notedto be declining over time as some fields registered as low as 26 ton/ha from their previous highestyields of 120 ton/ha. These low yields can be attributed to poor water management and agronomicpractices carried out at the scheme that lead to waterlogging and nutrient leaching. It is from thisbackground that a shallow groundwater monitoring tool known as a floating flag is proposed sothat farmers can easily observe water table fluctuations in their fields which can help them bettermanage water application through adjusted irrigation schedules through observing colour changesin the floating flags. This will help reduce waterlogging and salinization problems because thegroundwater will be utilised to supplement irrigation and thus reduce operational costs to thefarmers.xi

IntroductionBackgroundIrrigation has made food production fairly stable, but agricultural water resources have beenoverused and misused, resulting in large-scale waterlogging and salinity in many irrigationschemes (Northey et al. 2006). Irrigation productivity is now at risk because of poor solutemanagement which has caused losses of productive lands the world over (Dandekar and Chougule2010; Stirzaker 2011). Over application of water tends to raise water tables on farms and insurrounding fields, resulting in waterlogging (Northey et al. 2006). This results in salts rising tothe surface and tends to cause salinity problems which affect soil physical and chemical properties,as well as crop yields (Malota and Senzanje 2016).This is very common in irrigation farms in Malawi and in Chikwawa District in particular. Malawi,just like many sub Saharan countries, is a semi-arid tropical country with long dry periods andshort rainy seasons. The dry periods necessitate use of irrigation for production, especially forperennial crops. This heavy reliance on irrigation has resulted in saline soils that have preventedmany schemes from meeting their potential (Umali 1993). Chikwawa is a district that has highpotential for irrigation development due to availability of many perennial rivers and good soilswith gentle slopes. However, it is also one of the districts with high salinity due to its geologicalhistory (Sehatzadeh 2011). The country depends on sugar as one of its largest export earners(Ministry of Agriculture (MoA) 2010), but of late, sugarcane (Saccharum officinarum) yieldshave decreased at an alarming rate. This necessitated this study, to ascertain possible causes ofwaterlogging and salinity and whether this is the cause of the low yields, and if so, torecommend possible management solutions.Waterlogged soils are those soils that are saturated with water for large parts of the year.Waterlogged soils tend to have slow organic matter oxidation from NH4 to NO2 (Tusneem andPatrick Jr 1971) and transformation of NO2 to NO3 is inhibited due to lack of oxygen in the soil.In submerged soils, all pore spaces are filled with water, thereby reducing aeration of the rootzonewhich reduces root respiration and leads to crop senescence, which subsequently affects yields.

When the soil is waterlogged, soil temperature is lowered because wet soils have greater specificheat than drier soils. In addition, the longer the soil is under water, the greater the likelihood thatsoil structure is destroyed, resulting in compacted soils. This results in soil organic matter beingleached, leaving the inorganic components without binding factors (van der Zee et al. 2010). Thereare more nitrogen deficiency problems in waterlogged soils and there are reports of soil pH reversalin such soils (van der Zee et al. 2010). This is where pH increases in acidic soils and decreases inalkaline soils. All these factors tend to impact heavily on field crops, except rice, as there is lowaeration and unavailability of nutrients.Salinized soils, on the other hand, refer to those soils that have salt build-up that is toxic ordetrimental for plant growth. Soil salinity decreases osmotic potential of the soil so that water isless available for crop uptake. Irrigating with poor quality water (high salt load) can lead to salinityproblems. Soil salinity is a major concern in poorly drained soils especially when groundwater iswithin 3 m of the surface, depending on the soil type (Malota and Senzanje 2016). In such cases,water rises to the surface by capillary action and crop water uptake through transpiration, ratherthan percolating down through the entire soil profile, and then evaporates from the soil surface.This is more pronounced in semi-arid areas where there is insufficient water to leach out salts andespecially in lower lying areas of irrigation schemes.In studies conducted in sugarcane fields in Pakistan, it was found that highest crop yields wereobtained when water tables were deeper than 2 m (Kahlown et al. 1998; Kahlown et al. 2005).Therefore, there is a need to develop water management strategies that will ensure improveddrainage in areas with water tables close to the surface. One way is the reduction of irrigation waterthat does not affect crop yields or increase salinity (Kahlown et al. 2005). Ideally, shallowgroundwater can be effectively utilised as a water resource (Hurst et al. 2004) if it is of good qualityand within the rootzone (Northey et al. 2006).Malawi has a high population per unit area and is frequently hit by droughts, but mostly relies onsubsistence farming practices. There is very little commercial farming due to high illiteracy levelsamong farmers and fragmentation of the landscape into small parcels of land. However, farmersare encouraged to form irrigation groups where they farm together as smallholders. Unfortunately,most irrigation schemes like Kasinthula Scheme, face salinity challenges, and as much as 69 000ha are reportedly affected by salinity (Mashali 1999). Therefore, this research will not only help2

farmers at Kasinthula, but the whole country, to achieve Malawi’s Growth and DevelopmentStrategy (MGDS) III. The MGDS recognises that meaningful agricultural productivity can onlybe improved if there is good water management, prevention of land degradation and pollution ofthe environment and natural resources (Malawi Government 2017). In Malawi, sugarcane is grownalong the western shores of Lake Malawi and the Shire Valley, using furrow and pressurisedirrigation systems. The sugar is exported to most European countries and helps the country sourceforex revenue (Ministry of Agriculture 2010).ObjectivesThis research was conducted to address the following concerns related to salinity and shallowwater table fluctuations related mainly to water management in the scheme.1. To investigate the effect of amount of applied irrigation water on water table fluctuationin order to develop irrigation water management guidelines for Kasinthula Scheme.2. To estimate the effect of soil salinity on sugarcane yield at Kasinthula Scheme so as toestimate potential yield improvement with better water management.3. To estimate the effect of amount of applied irrigation water on the yield produced atKasinthula Scheme.4. To estimate the effect of amount of applied water on soil salinity levels at KasinthulaScheme.5. To estimate the soil salinity threshold for action or water table level at which growersneed to actively reduce applied water.3

HypothesesThe hypotheses to be tested by this research (Ho null hypothesis, and Ha the alternative hypothesis)were that:I. Ho: The groundwater table will rise to within 2 m of the soil surface in the lowelevation land due to irrigation activities as compared to the high elevation landwithin the irrigation schemeHa: Irrigation water application will not influence groundwater table fluctuationwithin the scheme based on elevationII. Ho: Sugarcane yields will be depressed in areas with higher soil salinity in therootzone (whose saturated paste extract EC is above the sugarcane threshold of 1.7dSm-1), while higher yields are expected in areas of low salinityHa: Soil salinity levels in the scheme have no effect on sugarcane yieldsIII. Ho: Sugarcane yields in the scheme will be depressed when water table rises above2 m from the surfaceHa: Ground water table depths will not affect yield of sugarcane in the schemeIV. Ho: Groundwater and soil salinities will increase from higher lying areas to lowerareas in the scheme due to salt transport by irrigation waterHa: Irrigation water application will not influence differential distribution of soiland groundwater salinities within the scheme based on elevation4

1.0 Literature review1.1 Groundwater1.1.1 Definition of groundwater and aquifer propertiesGroundwater is defined in many ways, one of which is the “cohesive subsurface water that movesas a result of gravity” while another is “any water that has not yet exchanged with surface water”while the other definition is that “water that is retained and flows through aquifers undersaturation” (Holmes 2000). Groundwater discharges its water into streams (Schmidt and Hahn2012). Classifications of groundwater are made according to location and interaction as:(1) Shallow aquifer, where groundwater is determined by precipitation and soil recharge;(2) Shallow aquifer, where groundwater is determined through the interaction of surface waterbodies such as rivers and lakes, and(3) Deep aquifer, where groundwater rarely interacts with surface water.The ability of an aquifer to store and to all

Figure 4.2 2001 Yield (ton/ha) map for Kasinthula Scheme Figure 4.3 2017 Yield (ton/ha) map for Kasinthula Scheme A closer look at yield map for 2001 shows that most fields had yields ranging from 80-100 ton/ha, except in a small area that has very high